2019 Kenya Population and Housing Census DDI_KEN_2019_PHC_v01_M_v7.6_A_IPUMS IPUMS

Integrated Public Use Microdata Series (IPUMS) International

IPUMS April 2, 2025 IPUMS, 50 Willey Hall, 225 - 19th Avenue South, Minneapolis, MN 55455 Organization for Economic Co-operation and Development, Development Co-operation Directorate JADE#:60525;MEHLB(2010)12 IPUMS Version 7.6 October 2025 : NEW FEATURES. --NO "new features" listed in Revision History NEW SAMPLES. --Six new census samples for Honduras (2013), Kenya (2019), Malawi (2018), Mongolia (2010, 2020), and Mozambique (2017) were added to the data series. All census samples extend pre-existing series for those countries. --91 quarterly labor force surveys from the Philippines (1997 - 2019) were added to IPUMS. SUPPLEMENTAL DATA. --No "supplemental data" listed in revision history NEW VARIABLES. --New spatially harmonized birthplace and previous-residence variables are available for samples in this data release. More information is available here (https://international.ipums.org/international/geo_mig.shtml). --Users should note that many older migration and birthplace variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. For birthplace variables refer to this table (https://international.ipums.org/international/resources/misc_docs/migCrosswalk_names.pdf). EDITED SAMPLES. --For the Zambia 2000 sample, an error in the household breaks was corrected, resulting in the creation of 1,988 new households (1% increase) that were previously combined with other households. The person records included in the sample did not change. Due to an inconsistency in the original file, no household-level information other than geographic location is available for these newly identified households, necessitating the addition of "unknown" values for this sample to the following variables: BEDROOMS, ELECTRIC, FLOOR, FUELCOOK, FUELHEAT, OWNERSHIP, PHONE, RADIO, REFRIG, ROOMS, SEWAGE, TRASH, WATSRC, TV, TOILET, GQ, ROOF, WATSUP, BIKE, MOTORCYCLE, KITCHEN, GQTYPE, AUTOS, and WALL. EDITED VARIABLES. --For the 1998 and 2008 Malawi samples, the family interrelationship pointer variables MOMLOC and POPLOC were modified to allow a "Spouse/partner" of the household head to be linked as a parent to an "Other relative", because the enumeration instructions specify that adopted and stepchildren were categorized as "Other relative". These samples are now consistent with the links made in the newly released 2018 Malawi sample, which had the same enumeration instructions for adopted and stepchildren. --In the samples for Côte d'Ivoire 1988 and 1998, Rwanda 1991 and 2002, Togo 1960 and 2010, and South Africa 2001, for the harmonized variable POLYGAM, persons in consensual unions were previously coded as "No, in monogamous union". Because there was no response option in these samples for polygamous consensual unions, it is more appropriate to treat these cases as not-in-universe, so they have been recoded to "NIU (not in universe)". --MARST has been edited for Honduras 1974 to reclassify the source variable responses "married, wife lives separately" and "consensual union, companion lives separately" as separations. The documentation suggests that "separately" actually indicates a relationship separation and not an absent spouse or companion. Other minor edits were implemented for MARST for Mozambique 1997 and 2007. --In the Mozambique 1997 sample, an error was corrected that recoded persons with a relationship of "Unknown" in the source data to "Other relative or non-relative" (6000) in the harmonized variable RELATE. These persons are now coded as "Not Stated/Unknown" (9999). --In the Malawi 1987, 1998, and 2008 samples, for variable WATSUP, a programming error was corrected such that any households who reported having piped water in either the wet or the dry season are classified as having access to piped water. This programming was also applied to the newly released 2018 sample. --The NATIVITY variable has been edited in the Chile 2017 sample to correct a programming error that mistakenly classified as foreign-born about 20 thousand person records that were actually native-born. --The MIGRATE5 variable has been edited in the Chile 2017 sample, given a programming error that classified most migrants as having changed their major geographic unit. The MIGRATE5 variable for the Chile 1982 and 1992 samples has been edited to use spatially harmonized geographic units to calculate migration status. --In the 1989, 1999, and 2009 Kenya samples, households who indicated that their lighting type or fuel was "Solar" were recoded from "No" to "Yes" in ELECTRIC, based on secondary sources documenting the spread of home solar energy systems in Kenya beginning in the mid-1980s. In the 1989 and 1999 Kenya samples, programming was removed that previously recoded households that reported using electricity as their main cooking fuel to "Yes" in the access to electricity variable ELECTRIC, making it more consistent across samples. Other minor edits were implemented for ELECTRIC in Botswana 2011, Ethiopia 1984 and 1994, Mongolia 1989, Mozambique 2007. --Some samples in DISCARE classified responses indicating "some" difficulty into "yes". These cases were revised to consistently include in "yes" only responses indicating "a lot of difficulty" or "cannot do at all". --Some codes were improperly labeled for municipalities in Honduras 1961 and 1974, which affect variables on place of residence, birthplace, and previous residence. 2019 Kenya Population and Housing Census - IPUMS Subset PHC ke2019a (IPUMS Harmonized Subset) KEN_2019_PHC_v01_M_v7.6_A_IPUMS Kenya National Bureau of Statistics IPUMS (c) Copyright 2019, Kenya National Bureau of Statistics and Minnesota Population Center Kenya National Bureau of Statistics Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.6 Version 7.6. The datasets contain selected variables from the original microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Fertility and Mortality Variables -- PERSON Nativity and Birthplace Variables -- PERSON Utilities Variables -- HOUSEHOLD Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Geography: F-N Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Migration: F-N Variables -- PERSON Technical Person Variables -- PERSON Technical Household Variables -- HOUSEHOLD Technical Person Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Demographic Variables -- PERSON Geography: Global Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Other Person Variables -- PERSON Ethnicity and Language Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Education Variables -- PERSON Utilities Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Disability Variables -- PERSON Nativity and Birthplace Variables -- PERSON Geography: F-N Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Dwelling Characteristics Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Demographic Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Technical Person Variables -- PERSON Ethnicity and Language Variables -- PERSON Nativity and Birthplace Variables -- PERSON Migration: Global Variables -- PERSON Fertility and Mortality Variables -- PERSON Disability Variables -- PERSON Disability Variables -- PERSON Education Variables -- PERSON Work Variables -- PERSON Work: Industry Variables -- PERSON Other Person Variables -- PERSON Work: Occupation Variables -- PERSON August 24-25, 2019 7 days after census day, to August 31 Kenya Division Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes UNIT DESCRIPTIONS: - Dwellings: A homestead is an isolated compound with one or more structures, and may be inhabited by one or more households. In most cases, fences, hedges, walls, etc. surround homesteads. A homestead may contain, for example, a hut or a group of huts. A manyatta, thus is considered as a homestead. However, a wall/fence or hedge need not necessarily surround a homestead. For instance, boys' quarters, garage, kitchen, etc. may be part of a homestead whether or not they are surrounded by a fence/wall, etc. A structure is a freestanding building used for the purposes of residential, business or any other activity. For census purposes, a structure constitutes a building used for dwelling purposes. In rural areas, most of the structures will be found within a homestead. A structure can contain one or more dwelling units. In urban areas, a structure may contain several dwelling units. For example, storeyed buildings, or any other building containing more than one dwelling unit. A dwelling unit is a place of abode or residence with a private entrance. There can be many dwelling units within a structure. A dwelling unit may have one or more habitable rooms. - Households: A person or group of persons who reside in the same homestead/compound but not necessarily in the same dwelling unit, have same cooking arrangements, and are answerable to the same household head. - Group quarters: Group quarters refer to persons enumerated in collective living quarters such as army barracks and hostels in learning institutions. All persons who spent the Census Night in Kenya. Persons who sleep outdoors and travelers in hotels, lodges, and boarding houses Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Kenya 2019 MICRODATA SOURCE: Kenya National Bureau of Statistics SAMPLE SIZE (person records): 4721394. SAMPLE DESIGN: Systematic sample of every tenth household. Persons who sleep outdoors and travelers in hotels, lodges, and boarding houses Face-to-face [f2f] A long form was used to enumerate individuals in private households, including those within institutions such as schools, colleges, barracks, refugee camps, or convents/monasteries. The long form includes both individual and housing characteristics. Short forms were used for persons in transit, persons who slept outdoors, or persons in hotels or boarding houses. An emigrant questionnaire was used to obtain information on emigrants in enumerated households. de facto, CENSUS DAY: August 24-25, 2019 Self-weighting. Expansion factor = 10. IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS International are designed to extend this record. Kenya National Bureau of Statistics Steven Ruggles, Lara Cleveland, Rodrigo Lovaton, Sula Sarkar, Matthew Sobek, Derek Burk, Dan Ehrlich, Quinn Heimann, Jane Lee, and Nate Merrill. Integrated Public Use Microdata Series, International: Version 7.6 [dataset]. Minneapolis, MN: IPUMS, 2025. https://doi.org/10.18128/D020.V7.6 Researchers should also acknowledge the statistical agency that originally produced the data: Kenya, Kenya National Bureau of Statistics. 2019 Kenya Population and Housing Census The licensing agreement for use of IPUMS International data requires that users supply IPUMS International with the title and full citation for any publications, research reports, or educational materials making use of the data or documentation. Copies of such materials are also gratefully received at ipums@umn.edu. Printed matter should be sent to: IPUMS International Minnesota Population Center University of Minnesota 50 Willey Hall 225 19th Avenue South Minneapolis, MN 55455 An adapted version of the dataset, harmonized for international comparability, is available from IPUMS International (https://international.ipums.org/international/) under the following conditions: IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. User-provided description: DOI:10.18128/D020.V7.6 Extract for ke2019a, 2025 KEN2019_PHC-H-H.dat Household records 1,214,156 ascii Minnesota Population Center Version 7.5, IPUMS sample KEN2019_PHC-P-H.dat Person records 4721394 ascii Minnesota Population Center Version 7.5, IPUMS sample Record type RECTYPE identifies the type of record for the case: household or person. NOTE: RECTYPE is an alphabetic (character string) variable with a value of 'H' for household records and 'P' for person records. RECTYPE will not appear as a variable in the default rectangular extracts produced by the data extract system. It is only available in hierarchical extracts, to distinguish between the two record types. H Household P Person Technical Household Variables -- HOUSEHOLD Country COUNTRY gives the country from which the sample was drawn. The codes assigned to each country are those used by the UN Statistics Division and the ISO (International Organization for Standardization). 032 Argentina 051 Armenia 040 Austria 050 Bangladesh 112 Belarus 204 Benin 068 Bolivia 072 Botswana 076 Brazil 854 Burkina Faso 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 208 Denmark 214 Dominican Republic 218 Ecuador 818 Egypt 222 El Salvador 231 Ethiopia 242 Fiji 246 Finland 250 France 276 Germany 288 Ghana 300 Greece 320 Guatemala 324 Guinea 332 Haiti 340 Honduras 348 Hungary 352 Iceland 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 384 Côte d'Ivoire 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 418 Laos 426 Lesotho 430 Liberia 454 Malawi 458 Malaysia 466 Mali 480 Mauritius 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 104 Myanmar 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 578 Norway 586 Pakistan 275 Palestine 591 Panama 598 Papua New Guinea 600 Paraguay 604 Peru 608 Philippines 616 Poland 620 Portugal 630 Puerto Rico 642 Romania 643 Russia 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 703 Slovak Republic 705 Slovenia 710 South Africa 728 South Sudan 724 Spain 729 Sudan 740 Suriname 752 Sweden 756 Switzerland 834 Tanzania 764 Thailand 768 Togo 780 Trinidad and Tobago 792 Turkey 800 Uganda 804 Ukraine 826 United Kingdom 840 United States 858 Uruguay 862 Venezuela 704 Vietnam 894 Zambia 716 Zimbabwe Technical Household Variables -- HOUSEHOLD Year YEAR gives the year in which the census or survey was taken. For samples that span years, the midpoint or first year of the interval is reported. 1703 1703 1729 1729 1787 1787 1801 1801 1819 1819 1845 1845 1848 1848 1850 1850 1851 1851 1852 1852 1860 1860 1861 1861 1865 1865 1868 1868 1870 1870 1871 1871 1875 1875 1880 1880 1881 1881 1885 1885 1890 1890 1891 1891 1900 1900 1901 1901 1910 1910 1911 1911 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1966 1966 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 Technical Household Variables -- HOUSEHOLD IPUMS sample identifier SAMPLE identifies the IPUMS sample from which the case is drawn. Each sample receives a unique 9-digit code. The code is structured as follows: The first 3 digits are the ISO/UN codes used in COUNTRY The next 4 digits are the year of the census/survey The final 2 digits identify the sample within the year. For the last two digits, censuses or large census-like surveys have a value "0" (e.g, 01) in the second-to-last digit, household surveys have a value of "2" (e.g., 21), and employment surveys have a value of "4" (e.g., 41). 032197001 Argentina 1970 032198001 Argentina 1980 032199101 Argentina 1991 032200101 Argentina 2001 032201001 Argentina 2010 051200101 Armenia 2001 051201101 Armenia 2011 040197101 Austria 1971 040198101 Austria 1981 040199101 Austria 1991 040200101 Austria 2001 040201101 Austria 2011 050199101 Bangladesh 1991 050200101 Bangladesh 2001 050201101 Bangladesh 2011 112199901 Belarus 1999 112200901 Belarus 2009 204197901 Benin 1979 204199201 Benin 1992 204200201 Benin 2002 204201301 Benin 2013 068197601 Bolivia 1976 068199201 Bolivia 1992 068200101 Bolivia 2001 068201201 Bolivia 2012 072198101 Botswana 1981 072199101 Botswana 1991 072200101 Botswana 2001 072201101 Botswana 2011 076196001 Brazil 1960 076197001 Brazil 1970 076198001 Brazil 1980 076199101 Brazil 1991 076200001 Brazil 2000 076201001 Brazil 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 116199801 Cambodia 1998 116200401 Cambodia 2004 116200801 Cambodia 2008 116201301 Cambodia 2013 116201901 Cambodia 2019 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124185201 Canada 1852 124187101 Canada 1871 124188101 Canada 1881 124189101 Canada 1891 124190101 Canada 1901 124191101 Canada 1911 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 124201101 Canada 2011 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 152201701 Chile 2017 156198201 China 1982 156199001 China 1990 156200001 China 2000 170196401 Colombia 1964 170197301 Colombia 1973 170198501 Colombia 1985 170199301 Colombia 1993 170200501 Colombia 2005 188196301 Costa Rica 1963 188197301 Costa Rica 1973 188198401 Costa Rica 1984 188200001 Costa Rica 2000 188201101 Costa Rica 2011 192200201 Cuba 2002 192201201 Cuba 2012 208178701 Denmark 1787 208180101 Denmark 1801 208184501 Denmark 1845 208188001 Denmark 1880 208188501 Denmark 1885 214196001 Dominican Republic 1960 214197001 Dominican Republic 1970 214198101 Dominican Republic 1981 214200201 Dominican Republic 2002 214201001 Dominican Republic 2010 218196201 Ecuador 1962 218197401 Ecuador 1974 218198201 Ecuador 1982 218199001 Ecuador 1990 218200101 Ecuador 2001 218201001 Ecuador 2010 818184801 Egypt 1848 818186801 Egypt 1868 818198601 Egypt 1986 818199601 Egypt 1996 818200601 Egypt 2006 222199201 El Salvador 1992 222200701 El Salvador 2007 231198401 Ethiopia 1984 231199401 Ethiopia 1994 231200701 Ethiopia 2007 242196601 Fiji 1966 242197601 Fiji 1976 242198601 Fiji 1986 242199601 Fiji 1996 242200701 Fiji 2007 242201401 Fiji 2014 246201001 Finland 2010 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 276181901 Germany 1819 (Mecklenburg) 276197001 Germany 1970 (West) 276197101 Germany 1971 (East) 276198101 Germany 1981 (East) 276198701 Germany 1987 (West) 288198401 Ghana 1984 288200001 Ghana 2000 288201001 Ghana 2010 300197101 Greece 1971 300198101 Greece 1981 300199101 Greece 1991 300200101 Greece 2001 300201101 Greece 2011 320196401 Guatemala 1964 320197301 Guatemala 1973 320198101 Guatemala 1981 320199401 Guatemala 1994 320200201 Guatemala 2002 324198301 Guinea 1983 324199601 Guinea 1996 324201401 Guinea 2014 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 340196101 Honduras 1961 340197401 Honduras 1974 340198801 Honduras 1988 340200101 Honduras 2001 340201301 Honduras 2013 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 348201101 Hungary 2011 352170301 Iceland 1703 352172901 Iceland 1729 352180101 Iceland 1801 352190101 Iceland 1901 352191001 Iceland 1910 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 356200941 India 2009 360197101 Indonesia 1971 360197601 Indonesia 1976 360198001 Indonesia 1980 360198501 Indonesia 1985 360199001 Indonesia 1990 360199501 Indonesia 1995 360200001 Indonesia 2000 360200501 Indonesia 2005 360201001 Indonesia 2010 364200601 Iran 2006 364201101 Iran 2011 368199701 Iraq 1997 372190101 Ireland 1901 372191101 Ireland 1911 372197101 Ireland 1971 372197901 Ireland 1979 372198101 Ireland 1981 372198601 Ireland 1986 372199101 Ireland 1991 372199601 Ireland 1996 372200201 Ireland 2002 372200601 Ireland 2006 372201101 Ireland 2011 372201601 Ireland 2016 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 376200801 Israel 2008 380200101 Italy 2001 380201101 Italy 2011 380201121 Italy 2011 Q1 LFS 380201221 Italy 2012 Q1 LFS 380201321 Italy 2013 Q1 LFS 380201421 Italy 2014 Q1 LFS 380201521 Italy 2015 Q1 LFS 380201621 Italy 2016 Q1 LFS 380201721 Italy 2017 Q1 LFS 380201821 Italy 2018 Q1 LFS 380201921 Italy 2019 Q1 LFS 380202021 Italy 2020 Q1 LFS 384198801 Côte d'Ivoire 1988 384199801 Côte d'Ivoire 1998 388198201 Jamaica 1982 388199101 Jamaica 1991 388200101 Jamaica 2001 400200401 Jordan 2004 404196901 Kenya 1969 404197901 Kenya 1979 404198901 Kenya 1989 404199901 Kenya 1999 404200901 Kenya 2009 404201901 Kenya 2019 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 418199501 Laos 1995 418200501 Laos 2005 418201501 Laos 2015 426199601 Lesotho 1996 426200601 Lesotho 2006 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 454201801 Malawi 2018 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 480199001 Mauritius 1990 480200001 Mauritius 2000 480201101 Mauritius 2011 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 484201501 Mexico 2015 484202001 Mexico 2020 484200521 Mexico 2005 Q1 LFS 484200522 Mexico 2005 Q2 LFS 484200523 Mexico 2005 Q3 LFS 484200524 Mexico 2005 Q4 LFS 484200621 Mexico 2006 Q1 LFS 484200622 Mexico 2006 Q2 LFS 484200623 Mexico 2006 Q3 LFS 484200624 Mexico 2006 Q4 LFS 484200721 Mexico 2007 Q1 LFS 484200722 Mexico 2007 Q2 LFS 484200723 Mexico 2007 Q3 LFS 484200724 Mexico 2007 Q4 LFS 484200821 Mexico 2008 Q1 LFS 484200822 Mexico 2008 Q2 LFS 484200823 Mexico 2008 Q3 LFS 484200824 Mexico 2008 Q4 LFS 484200921 Mexico 2009 Q1 LFS 484200922 Mexico 2009 Q2 LFS 484200923 Mexico 2009 Q3 LFS 484200924 Mexico 2009 Q4 LFS 484201021 Mexico 2010 Q1 LFS 484201022 Mexico 2010 Q2 LFS 484201023 Mexico 2010 Q3 LFS 484201024 Mexico 2010 Q4 LFS 484201121 Mexico 2011 Q1 LFS 484201122 Mexico 2011 Q2 LFS 484201123 Mexico 2011 Q3 LFS 484201124 Mexico 2011 Q4 LFS 484201221 Mexico 2012 Q1 LFS 484201222 Mexico 2012 Q2 LFS 484201223 Mexico 2012 Q3 LFS 484201224 Mexico 2012 Q4 LFS 484201321 Mexico 2013 Q1 LFS 484201322 Mexico 2013 Q2 LFS 484201323 Mexico 2013 Q3 LFS 484201324 Mexico 2013 Q4 LFS 484201421 Mexico 2014 Q1 LFS 484201422 Mexico 2014 Q2 LFS 484201423 Mexico 2014 Q3 LFS 484201424 Mexico 2014 Q4 LFS 484201521 Mexico 2015 Q1 LFS 484201522 Mexico 2015 Q2 LFS 484201523 Mexico 2015 Q3 LFS 484201524 Mexico 2015 Q4 LFS 484201621 Mexico 2016 Q1 LFS 484201622 Mexico 2016 Q2 LFS 484201623 Mexico 2016 Q3 LFS 484201624 Mexico 2016 Q4 LFS 484201721 Mexico 2017 Q1 LFS 484201722 Mexico 2017 Q2 LFS 484201723 Mexico 2017 Q3 LFS 484201724 Mexico 2017 Q4 LFS 484201821 Mexico 2018 Q1 LFS 484201822 Mexico 2018 Q2 LFS 484201823 Mexico 2018 Q3 LFS 484201824 Mexico 2018 Q4 LFS 484201921 Mexico 2019 Q1 LFS 484201922 Mexico 2019 Q2 LFS 484201923 Mexico 2019 Q3 LFS 484201924 Mexico 2019 Q4 LFS 484202021 Mexico 2020 Q1 LFS 484202023 Mexico 2020 Q3 LFS 496198901 Mongolia 1989 496200001 Mongolia 2000 496201001 Mongolia 2010 496202001 Mongolia 2020 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 508201701 Mozambique 2017 104201401 Myanmar 2014 524200101 Nepal 2001 524201101 Nepal 2011 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 528201101 Netherlands 2011 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 578180101 Norway 1801 578186501 Norway 1865 578187501 Norway 1875 578190001 Norway 1900 578191001 Norway 1910 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 275199701 Palestine 1997 275200701 Palestine 2007 275201701 Palestine 2017 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 598198001 Papua New Guinea 1980 598199001 Papua New Guinea 1990 598200001 Papua New Guinea 2000 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 604201701 Peru 2017 608199721 Philippines 1997 Q1 LFS 608199722 Philippines 1997 Q2 LFS 608199723 Philippines 1997 Q3 LFS 608199724 Philippines 1997 Q4 LFS 608199821 Philippines 1998 Q1 LFS 608199822 Philippines 1998 Q2 LFS 608199823 Philippines 1998 Q3 LFS 608199824 Philippines 1998 Q4 LFS 608199921 Philippines 1999 Q1 LFS 608199922 Philippines 1999 Q2 LFS 608199923 Philippines 1999 Q3 LFS 608199924 Philippines 1999 Q4 LFS 608200021 Philippines 2000 Q1 LFS 608200022 Philippines 2000 Q2 LFS 608200023 Philippines 2000 Q3 LFS 608200024 Philippines 2000 Q4 LFS 608200121 Philippines 2001 Q1 LFS 608200122 Philippines 2001 Q2 LFS 608200123 Philippines 2001 Q3 LFS 608200124 Philippines 2001 Q4 LFS 608200221 Philippines 2002 Q1 LFS 608200222 Philippines 2002 Q2 LFS 608200223 Philippines 2002 Q3 LFS 608200224 Philippines 2002 Q4 LFS 608200321 Philippines 2003 Q1 LFS 608200322 Philippines 2003 Q2 LFS 608200323 Philippines 2003 Q3 LFS 608200324 Philippines 2003 Q4 LFS 608200421 Philippines 2004 Q1 LFS 608200422 Philippines 2004 Q2 LFS 608200423 Philippines 2004 Q3 LFS 608200424 Philippines 2004 Q4 LFS 608200521 Philippines 2005 Q1 LFS 608200522 Philippines 2005 Q2 LFS 608200523 Philippines 2005 Q3 LFS 608200524 Philippines 2005 Q4 LFS 608200621 Philippines 2006 Q1 LFS 608200622 Philippines 2006 Q2 LFS 608200623 Philippines 2006 Q3 LFS 608200624 Philippines 2006 Q4 LFS 608200721 Philippines 2007 Q1 LFS 608200722 Philippines 2007 Q2 LFS 608200723 Philippines 2007 Q3 LFS 608200724 Philippines 2007 Q4 LFS 608200821 Philippines 2008 Q1 LFS 608200822 Philippines 2008 Q2 LFS 608200823 Philippines 2008 Q3 LFS 608200824 Philippines 2008 Q4 LFS 608200921 Philippines 2009 Q1 LFS 608200922 Philippines 2009 Q2 LFS 608200923 Philippines 2009 Q3 LFS 608200924 Philippines 2009 Q4 LFS 608201021 Philippines 2010 Q1 LFS 608201022 Philippines 2010 Q2 LFS 608201023 Philippines 2010 Q3 LFS 608201024 Philippines 2010 Q4 LFS 608201121 Philippines 2011 Q1 LFS 608201122 Philippines 2011 Q2 LFS 608201123 Philippines 2011 Q3 LFS 608201124 Philippines 2011 Q4 LFS 608201221 Philippines 2012 Q1 LFS 608201222 Philippines 2012 Q2 LFS 608201223 Philippines 2012 Q3 LFS 608201224 Philippines 2012 Q4 LFS 608201321 Philippines 2013 Q1 LFS 608201322 Philippines 2013 Q2 LFS 608201323 Philippines 2013 Q3 LFS 608201324 Philippines 2013 Q4 LFS 608201421 Philippines 2014 Q1 LFS 608201422 Philippines 2014 Q2 LFS 608201423 Philippines 2014 Q3 LFS 608201424 Philippines 2014 Q4 LFS 608201521 Philippines 2015 Q1 LFS 608201522 Philippines 2015 Q2 LFS 608201523 Philippines 2015 Q3 LFS 608201524 Philippines 2015 Q4 LFS 608201621 Philippines 2016 Q1 LFS 608201622 Philippines 2016 Q2 LFS 608201623 Philippines 2016 Q3 LFS 608201624 Philippines 2016 Q4 LFS 608201721 Philippines 2017 Q1 LFS 608201722 Philippines 2017 Q2 LFS 608201723 Philippines 2017 Q3 LFS 608201724 Philippines 2017 Q4 LFS 608201821 Philippines 2018 Q1 LFS 608201822 Philippines 2018 Q2 LFS 608201823 Philippines 2018 Q3 LFS 608201824 Philippines 2018 Q4 LFS 608201921 Philippines 2019 Q1 LFS 608201922 Philippines 2019 Q2 LFS 608201923 Philippines 2019 Q3 LFS 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 608201001 Philippines 2010 616197801 Poland 1978 616198801 Poland 1988 616200201 Poland 2002 616201101 Poland 2011 620198101 Portugal 1981 620199101 Portugal 1991 620200101 Portugal 2001 620201101 Portugal 2011 630197001 Puerto Rico 1970 630198001 Puerto Rico 1980 630199001 Puerto Rico 1990 630200001 Puerto Rico 2000 630200501 Puerto Rico 2005 630201001 Puerto Rico 2010 630201501 Puerto Rico 2015 630202001 Puerto Rico 2020 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 642201101 Romania 2011 643200201 Russia 2002 643201001 Russia 2010 646199101 Rwanda 1991 646200201 Rwanda 2002 646201201 Rwanda 2012 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 686201301 Senegal 2013 694200401 Sierra Leone 2004 694201501 Sierra Leone 2015 703199101 Slovak Republic 1991 703200101 Slovak Republic 2001 703201101 Slovak Republic 2011 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 710201601 South Africa 2016 728200801 South Sudan 2008 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 724200521 Spain 2005 Q1 LFS 724200522 Spain 2005 Q2 LFS 724200523 Spain 2005 Q3 LFS 724200524 Spain 2005 Q4 LFS 724200621 Spain 2006 Q1 LFS 724200622 Spain 2006 Q2 LFS 724200623 Spain 2006 Q3 LFS 724200624 Spain 2006 Q4 LFS 724200721 Spain 2007 Q1 LFS 724200722 Spain 2007 Q2 LFS 724200723 Spain 2007 Q3 LFS 724200724 Spain 2007 Q4 LFS 724200821 Spain 2008 Q1 LFS 724200822 Spain 2008 Q2 LFS 724200823 Spain 2008 Q3 LFS 724200824 Spain 2008 Q4 LFS 724200921 Spain 2009 Q1 LFS 724200922 Spain 2009 Q2 LFS 724200923 Spain 2009 Q3 LFS 724200924 Spain 2009 Q4 LFS 724201021 Spain 2010 Q1 LFS 724201022 Spain 2010 Q2 LFS 724201023 Spain 2010 Q3 LFS 724201024 Spain 2010 Q4 LFS 724201121 Spain 2011 Q1 LFS 724201122 Spain 2011 Q2 LFS 724201123 Spain 2011 Q3 LFS 724201124 Spain 2011 Q4 LFS 724201221 Spain 2012 Q1 LFS 724201222 Spain 2012 Q2 LFS 724201223 Spain 2012 Q3 LFS 724201224 Spain 2012 Q4 LFS 724201321 Spain 2013 Q1 LFS 724201322 Spain 2013 Q2 LFS 724201323 Spain 2013 Q3 LFS 724201324 Spain 2013 Q4 LFS 724201421 Spain 2014 Q1 LFS 724201422 Spain 2014 Q2 LFS 724201423 Spain 2014 Q3 LFS 724201424 Spain 2014 Q4 LFS 724201521 Spain 2015 Q1 LFS 724201522 Spain 2015 Q2 LFS 724201523 Spain 2015 Q3 LFS 724201524 Spain 2015 Q4 LFS 724201621 Spain 2016 Q1 LFS 724201622 Spain 2016 Q2 LFS 724201623 Spain 2016 Q3 LFS 724201624 Spain 2016 Q4 LFS 724201721 Spain 2017 Q1 LFS 724201722 Spain 2017 Q2 LFS 724201723 Spain 2017 Q3 LFS 724201724 Spain 2017 Q4 LFS 724201821 Spain 2018 Q1 LFS 724201822 Spain 2018 Q2 LFS 724201823 Spain 2018 Q3 LFS 724201824 Spain 2018 Q4 LFS 724201921 Spain 2019 Q1 LFS 724201922 Spain 2019 Q2 LFS 724201923 Spain 2019 Q3 LFS 724201924 Spain 2019 Q4 LFS 724202021 Spain 2020 Q1 LFS 724202022 Spain 2020 Q2 LFS 724202023 Spain 2020 Q3 LFS 724202024 Spain 2020 Q4 LFS 729200801 Sudan 2008 740200401 Suriname 2004 740201201 Suriname 2012 752188001 Sweden 1880 752189001 Sweden 1890 752190001 Sweden 1900 752191001 Sweden 1910 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 756201101 Switzerland 2011 834198801 Tanzania 1988 834200201 Tanzania 2002 834201201 Tanzania 2012 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 768196001 Togo 1960 768197001 Togo 1970 768201001 Togo 2010 780197001 Trinidad and Tobago 1970 780198001 Trinidad and Tobago 1980 780199001 Trinidad and Tobago 1990 780200001 Trinidad and Tobago 2000 780201101 Trinidad and Tobago 2011 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 800201401 Uganda 2014 804200101 Ukraine 2001 826185101 United Kingdom 1851 (England and Wales) 826185102 United Kingdom 1851 (Scotland) 826185103 United Kingdom 1851 (2% sample) 826186101 United Kingdom 1861 (England and Wales) 826186102 United Kingdom 1861 (Scotland) 826187101 United Kingdom 1871 (Scotland) 826188101 United Kingdom 1881 (England and Wales) 826188102 United Kingdom 1881 (Scotland) 826189101 United Kingdom 1891 (England and Wales) 826189102 United Kingdom 1891 (Scotland) 826190101 United Kingdom 1901 (England and Wales) 826190102 United Kingdom 1901 (Scotland) 826191101 United Kingdom 1911 (England and Wales) 826196101 United Kingdom 1961 826197101 United Kingdom 1971 826199101 United Kingdom 1991 826200101 United Kingdom 2001 840185001 United States 1850 (100%) 840185002 United States 1850 (1%) 840186001 United States 1860 (1%) 840187001 United States 1870 (1%) 840188001 United States 1880 (100%) 840188002 United States 1880 (10%) 840190001 United States 1900 (5%) 840191001 United States 1910 (1%) 840196001 United States 1960 840197001 United States 1970 840198001 United States 1980 840199001 United States 1990 840200001 United States 2000 840200501 United States 2005 840201001 United States 2010 840201501 United States 2015 840202001 United States 2020 858196301 Uruguay 1963 858196302 Uruguay 1963 (full count) 858197501 Uruguay 1975 858197502 Uruguay 1975 (full count) 858198501 Uruguay 1985 858198502 Uruguay 1985 (full count) 858199601 Uruguay 1996 858199602 Uruguay 1996 (full count) 858200621 Uruguay 2006 858201101 Uruguay 2011 858201102 Uruguay 2011 (full count) 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 704201901 Vietnam 2019 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 716201201 Zimbabwe 2012 Technical Household Variables -- HOUSEHOLD Household serial number SERIAL is an identifying number unique to each household in a given sample. All person records are assigned the same serial number as the household record that they follow. (Person records also have their own unique identifiers -- see PERNUM.) The combination of SAMPLE and SERIAL provides a unique identifier for every household in the IPUMS-International database; SAMPLE, SERIAL and PERNUM uniquely identify every person in the database. SERIAL can be used to identify dwellings in some samples. In these samples, the first 7 digits of SERIAL provide the dwelling number common to all households that were sampled from the same structure. The last three digits give the sequence of the household within the dwelling. The following is a list of samples in which dwellings can be inferred: Chile 1970, 1992, 2002Colombia 1993, 2005Costa Rica 1984, 2000Cuba 2002Dominican Republic 1981, 2002, 2010Ecuador 1990, 2001Germany 1971Hungary 1980, 1990, 2001Jamaica 1982, 1991, 2001Malaysia 1970, 1991, 2000Mexico 1995, 1990, 2000, 2005Nigeria 2006Panama 2000Peru 1993, 2007Portugal 1981, 1991, 2001Spain 1991Uruguay 2011Venezuela 1990, 2001Vietnam 1989In all other samples, the last 3 digits are always zeroes. SERIAL was constructed for IPUMS-International, and has no relation to the serial number in the original datasets. The U.S. 1900 sample and 1880 10% sample have multi-household dwellings that can be identified using the last 3 digits of SERIAL. SERIAL is a 10-digit numeric variable. The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes. Technical Household Variables -- HOUSEHOLD Number of person records in the household PERSONS indicates how many person records are included in the household (i.e., the number of person records associated with the household record in the sample). These person records will all have the same serial number (SERIAL) as the household record. The information contained in the household record will normally apply to all of these persons. PERSONS is a 4-digit numeric variable. Technical Household Variables -- HOUSEHOLD Household weight HHWT indicates the number of households in the population represented by the household in the sample. For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics. NOTE: HHWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Household Variables -- HOUSEHOLD Subsample number SUBSAMP allocates each case to one of 100 subsample replicates, randomly numbered from 0 to 99. Each subsample is nationally representative and preserves any stratification of the sample from which it is drawn. Users who need a representative subset of a sample can use SUBSAMP to select their cases. For example, to randomly extract 10% of the cases from a sample, select any 10 of the 100 subsamples. 00 1st 1% subsample 01 2nd 1% subsample 02 3rd 1% subsample 03 4th 1% subsample 04 5th 1% subsample 05 6th 1% subsample 06 7th 1% subsample 07 8th 1% subsample 08 9th 1% subsample 09 10th 1% subsample 10 11th 1% subsample 11 12th 1% subsample 12 13th 1% subsample 13 14th 1% subsample 14 15th 1% subsample 15 16th 1% subsample 16 17th 1% subsample 17 18th 1% subsample 18 19th 1% subsample 19 20th 1% subsample 20 21st 1% subsample 21 22nd 1% subsample 22 23rd 1% subsample 23 24th 1% subsample 24 25th 1% subsample 25 26th 1% subsample 26 27th 1% subsample 27 28th 1% subsample 28 29th 1% subsample 29 30th 1% subsample 30 31st 1% subsample 31 32nd 1% subsample 32 33rd 1% subsample 33 34th 1% subsample 34 35th 1% subsample 35 36th 1% subsample 36 37th 1% subsample 37 38th 1% subsample 38 39th 1% subsample 39 40th 1% subsample 40 41st 1% subsample 41 42nd 1% subsample 42 43rd 1% subsample 43 44th 1% subsample 44 45th 1% subsample 45 46th 1% subsample 46 47th 1% subsample 47 48th 1% subsample 48 49th 1% subsample 49 50th 1% subsample 50 51st 1% subsample 51 52nd 1% subsample 52 53rd 1% subsample 53 54th 1% subsample 54 55th 1% subsample 55 56th 1% subsample 56 57th 1% subsample 57 58th 1% subsample 58 59th 1% subsample 59 60th 1% subsample 60 61st 1% subsample 61 62nd 1% subsample 62 63rd 1% subsample 63 64th 1% subsample 64 65th 1% subsample 65 66th 1% subsample 66 67th 1% subsample 67 68th 1% subsample 68 69th 1% subsample 69 70th 1% subsample 70 71st 1% subsample 71 72nd 1% subsample 72 73rd 1% subsample 73 74th 1% subsample 74 75th 1% subsample 75 76th 1% subsample 76 77th 1% subsample 77 78th 1% subsample 78 79th 1% subsample 79 80th 1% subsample 80 81st 1% subsample 81 82nd 1% subsample 82 83rd 1% subsample 83 84th 1% subsample 84 85th 1% subsample 85 86th 1% subsample 86 87th 1% subsample 87 88th 1% subsample 88 89th 1% subsample 89 90th 1% subsample 90 91st 1% subsample 91 92nd 1% subsample 92 93rd 1% subsample 93 94th 1% subsample 94 95th 1% subsample 95 96th 1% subsample 96 97th 1% subsample 97 98th 1% subsample 98 99th 1% subsample 99 100th 1% subsample Technical Household Variables -- HOUSEHOLD Strata identifier This variable is the strata identifier for the sample. The STRATA variable provides information about the sample design that can be used to improve estimation. STRATA is a 12-digit numeric variable. Technical Household Variables -- HOUSEHOLD Group quarters (collective dwelling) status GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools. Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification. Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions. 00 Vacant 10 Households 20 Group quarters (collective), n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified Group Quarters Variables -- HOUSEHOLD Number of unrelated persons UNREL indicates the number of persons in the household who are unrelated to the head as defined in the variable RELATE. 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ Group Quarters Variables -- HOUSEHOLD Urban-rural status URBAN indicates whether the household was located in a place designated as urban or as rural. 1 Rural 2 Urban 9 Unknown Geography: Global Variables -- HOUSEHOLD Continent and region of country REGIONW identifies the continent and region of each country. 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia Geography: Global Variables -- HOUSEHOLD 1st subnational geographic level, world [consistent boundaries over time] GEOLEV1 indicates the major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. First administrative units in GEOLEV1 have been spatiotemporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV1 is a 6-digit numeric variable. GEOLEV1 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO1_BR. Geography: Global Variables -- HOUSEHOLD 2nd subnational geographic level, world [consistent boundaries over time] GEOLEV2 indicates the second major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. Second administrative units in GEOLEV2 have been spatio-temporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV2 is a 9-digit numeric variable. GEOLEV2 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO2_BR. Geography: Global Variables -- HOUSEHOLD Population density of GEOLEV1 unit, in persons per square kilometer POPDENSGEO1 indicates the population density in persons per square kilometer of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO1 is an 8-digit numeric variable listing the population density in persons per square kilometer. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Population density of GEOLEV2 unit, in persons per square kilometer POPDENSGEO2 indicates the population density in persons per square kilometer of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO2 is a 12-digit numeric variable listing the population density in persons per square kilometer. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Area of GEOLEV1 unit in square kilometers AREAMOLLWGEO1 indicates the area in square kilometers of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO1 is a 10-digit numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Area of GEOLEV2 unit in square kilometers AREAMOLLWGEO2 indicates the area in square kilometers of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO2 is a 10-digit numeric variable listing the area in square kilometers. Codes0 = Unknown. Geography: Global Variables -- HOUSEHOLD Kenya, Province 1969 - 2019 [Level 1; consistent boundaries, GIS] GEO1_KE identifies the household's province or national capital within Kenya in all sample years. Provinces or national capital are the first level administrative units of the country. GEO1_KE is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_KE can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Kenya can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 404001 Nairobi 404002 Central 404003 Coast 404004 Eastern 404005 Northeastern 404006 Nyanza 404007 Rift Valley 404008 Western Geography: F-N Variables -- HOUSEHOLD Kenya, Province 2019 [Level 1, GIS] GEO1_KE2019 identifies the household's province or national capital within Kenya in 2019. Provinces or national capital are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_KE2019 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Kenya can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 001 Nairobi 002 Central 003 Coast 004 Eastern 005 Northeastern 006 Nyanza 007 Rift Valley 008 Western Geography: F-N Variables -- HOUSEHOLD Kenya, District 1969 - 2019 [Level 2; consistent boundaries, GIS] GEO2_KE identifies the household's county within Kenya in all sample years. Counties are the second level administrative units of the country. GEO2_KE is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_KE can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Kenya can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 404001047 Nairobi City 404002018 Nyandarua 404002019 Nyeri 404002020 Kirinyaga 404002022 Kiambu, Murang'a 404003001 Mombasa 404003002 Kwale 404003003 Kilifi 404003004 Tana River 404003005 Lamu 404003006 Taita-Taveta 404004010 Marsabit 404004011 Isiolo 404004012 Meru, Tharaka-Nithi 404004015 Kitui 404004016 Machakos, Makueni, Embu 404005007 Garissa 404005008 Wajir 404005009 Mandera 404006041 Siaya 404006042 Kisumu 404006043 Homa Bay, Migori 404006045 Kisii, Nyamira 404007023 Turkana 404007024 West Pokot 404007025 Samburu 404007026 Trans Nzoia 404007027 Uasin Gishu 404007028 Elgeyo-Marakwet 404007029 Nandi 404007030 Baringo, Laikipia 404007032 Nakuru 404007033 Narok 404007034 Kajiado 404007035 Kericho, Bomet 404008037 Kakamega, Vihiga 404008039 Bungoma 404008040 Busia Geography: F-N Variables -- HOUSEHOLD Kenya, District 2019 [Level 2, GIS] GEO2_KE2019 identifies the household's county within Kenya in 2019. Counties are the second level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO2_KE2019 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Kenya can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 001047 Nairobi City 002018 Nyandarua 002019 Nyeri 002020 Kirinyaga 002021 Murang'a 002022 Kiambu 003001 Mombasa 003002 Kwale 003003 Kilifi 003004 Tana River 003005 Lamu 003006 Taita/Taveta 004010 Marsabit 004011 Isiolo 004012 Meru 004013 Tharaka-Nithi 004014 Embu 004015 Kitui 004016 Machakos 004017 Makueni 005007 Garissa 005008 Wajir 005009 Mandera 006041 Siaya 006042 Kisumu 006043 Homa Bay 006044 Migori 006045 Kisii 006046 Nyamira 007023 Turkana 007024 West Pokot 007025 Samburu 007026 Trans Nzoia 007027 Uasin Gishu 007028 Elgeyo/Marakwet 007029 Nandi 007030 Baringo 007031 Laikipia 007032 Nakuru 007033 Narok 007034 Kajiado 007035 Kericho 007036 Bomet 008037 Kakamega 008038 Vihiga 008039 Bungoma 008040 Busia Geography: F-N Variables -- HOUSEHOLD Kenya, Subcounty 2019 [Level 3, GIS] GEO3_KE2019 identifies the household's sub-county within Kenya in 2019. Sub-counties are the third level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO3_KE2019 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Kenya can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. 001047001 Dagoretti 001047002 Embakasi 001047003 Kamukunji 001047004 Kasarani 001047005 Kibra 001047006 Lang'Ata 001047007 Makadara 001047008 Mathare 001047009 Njiru 001047010 Starehe 001047011 Westlands 002018001 Kinangop 002018002 Nyandarua South 002018003 Mirangine 002018004 Kipipiri 002018005 Nyandarua Central 002018006 Nyandarua West 002018007 Nyandarua North 002018098 Nyandarua county, unknown subcounty 002019001 Tetu 002019002 Kieni East 002019003 Kieni West 002019004 Mathira East 002019005 Mathira West 002019006 Nyeri South 002019007 Mukurwe-Ini 002019008 Nyeri Central 002019098 Nyeri county, unknown subcounty 002020001 Kirinyaga Central 002020002 Kirinyaga East 002020003 Kirinyaga West 002020004 Mwea East 002020005 Mwea West 002020098 Kirinyaga county, unknown subcounty 002021001 Murang'a East 002021002 Kangema 002021003 Mathioya 002021004 Kahuro 002021005 Murang'A South 002021006 Gatanga 002021007 Kigumo 002021008 Kandara 002021098 Murang'a county, unknown subcounty 002022001 Gatundu North 002022002 Gatundu South 002022003 Githunguri 002022004 Juja 002022005 Kabete 002022006 Kiambaa 002022007 Kiambu 002022008 Kikuyu 002022009 Lari 002022010 Limuru 002022011 Ruiru 002022012 Thika East 002022013 Thika West 003001001 Changamwe 003001002 Jomvu 003001003 Kisauni 003001004 Likoni 003001005 Mvita 003001006 Nyali 003002001 Kinango 003002002 Lunga Lunga 003002003 Matuga 003002004 Msambweni 003002005 Samburu 003003001 Chonyi 003003002 Ganze 003003003 Kaloleni 003003004 Kauma 003003005 Kilifi North 003003006 Kilifi South 003003007 Magarini 003003008 Malindi 003003009 Rabai 003004001 Tana Delta 003004002 Tana North 003004003 Tana River 003005001 Lamu East 003005002 Lamu West 003006001 Mwatate 003006002 Taita 003006003 Taveta 003006004 Voi 004010001 Loiyangalani 004010002 Marsabit Central 004010003 Marsabit North 004010004 Marsabit South 004010005 Moyale 004010006 North Horr 004010007 Sololo 004011001 Garbatulla 004011002 Isiolo 004011003 Merti 004012001 Buuri East 004012002 Buuri West 004012003 Igembe Central 004012004 Igembe North 004012005 Igembe South 004012006 Imenti North 004012007 Imenti South 004012008 Meru Central 004012009 Tigania West 004012010 Tigania East 004012011 Tigania West 004012098 Meru county, unknown subcounty 004013001 Igambang'Ombe 004013002 Maara 004013003 Meru South 004013004 Tharaka North 004013005 Tharaka South 004013098 Tharaka-Nithi county, unknown subcounty 004014001 Embu East 004014002 Embu North 004014003 Embu West 004014004 Mbeere South 004014005 Mbeere North 004014098 Embu county, unknown subcounty 004015001 Ikutha 004015002 Katulani 004015003 Kisasi 004015004 Kitui Central 004015005 Kitui West 004015006 Kyuso 004015007 Lower Yatta 004015008 Matinyani 004015009 Migwani 004015010 Mumoni, Thagicu 004015011 Mutitu 004015012 Mutitu North 004015013 Mutomo 004015014 Mwingi Central 004015015 Mwingi East 004015016 Nzambani 004015018 Tseikuru 004016001 Athi River 004016002 Kalama 004016003 Kangundo 004016004 Kathiani 004016005 Machakos 004016006 Masinga 004016007 Matungulu 004016008 Mwala 004016009 Yatta 004017001 Kathonzweni 004017002 Kibwezi 004017003 Kilungu 004017004 Makindu 004017005 Makueni 004017006 Mbooni East 004017007 Mbooni West 004017008 Mukaa 004017009 Nzaui 005007001 Balambala 005007002 Dadaab 005007003 Fafi 005007004 Garissa 005007005 Hulugho 005007006 Ijara 005007007 Lagdera 005008001 Buna 005008002 Eldas 005008003 Habaswein 005008004 Tarbaj 005008005 Wajir East 005008006 Wajir North 005008007 Wajir South 005008008 Wajir West 005009001 Mandera West 005009002 Banisa 005009003 Kotulo 005009004 Lafey 005009005 Mandera Central 005009006 Mandera East 005009007 Mandera North 006041001 Siaya 006041002 Gem 006041003 Ugenya 006041004 Ugunja 006041005 Bondo 006041006 Rarieda 006042001 Kisumu East 006042002 Kisumu Central 006042003 Kisumu West 006042004 Seme 006042005 Muhoroni 006042006 Nyando 006042007 Nyakach 006043001 Homa Bay 006043002 Ndhiwa 006043003 Rachuonyo North 006043004 Rachuonyo East 006043005 Rachuonyo South 006043006 Rangwe 006043007 Suba North 006043008 Suba South 006044001 Awendo 006044002 Kuria East 006044003 Kuria West 006044004 Nyatike 006044005 Rongo 006044006 Suna East 006044007 Suna West 006044008 Uriri 006045001 Etago 006045002 Gucha 006045003 Gucha South 006045004 Kenyenya 006045005 Kisii Central 006045006 Kisii South 006045007 Kitutu Central 006045008 Marani 006045009 Masaba South 006045010 Nyamache 006045011 Sameta 006046001 Borabu 006046002 Manga 006046003 Masaba North 006046004 Nyamira North 006046005 Nyamira South 007023001 Kibish 007023002 Loima 007023003 Turkana Central 007023004 Turkana East 007023005 Turkana North 007023006 Turkana South 007023007 Turkana West 007024001 Kipkomo 007024002 Pokot Central 007024003 Pokot North 007024004 Pokot South 007024005 West Pokot 007025001 Samburu Central 007025002 Samburu East 007025003 Samburu North 007026001 Trans Nzoia West 007026002 Trans Nzoia East 007026003 Kwanza 007026004 Endebess 007026005 Kiminini 007027001 Ainabkoi 007027002 Kapseret 007027003 Kesses 007027004 Moiben 007027005 Soy 007027006 Turbo 007028001 Keiyo North 007028002 Keiyo South 007028003 Marakwet East 007028004 Marakwet West 007029001 Chesumei 007029002 Nandi Central 007029003 Nandi East 007029004 Nandi North 007029005 Nandi South 007029006 Tinderet 007030001 Baringo Central 007030002 Baringo North 007030003 East Pokot 007030004 Koibatek 007030005 Marigat 007030006 Mogotio 007030007 Tiaty East 007030098 Baringo county, unknown subcounty 007031001 Laikipia Central 007031002 Laikipia East 007031003 Laikipia North 007031004 Laikipia West 007031005 Nyahururu 007032001 Gilgil 007032002 Kuresoi North 007032003 Kuresoi South 007032004 Molo 007032005 Naivasha 007032006 Nakuru East 007032007 Nakuru North 007032008 Nakuru West 007032009 Njoro 007032010 Rongai 007032011 Subukia 007033001 Narok East 007033002 Narok North 007033003 Narok South 007033004 Narok West 007033005 Trans Mara East 007033006 Trans Mara West 007033098 Narok county, unknown subcounty 007034001 Isinya 007034002 Kajiado Central 007034003 Kajiado North 007034004 Kajiado West 007034005 Loitokitok 007034006 Mashuuru 007035001 Belgut 007035002 Bureti 007035003 Kericho East 007035004 Kipkelion 007035005 Londiani 007035006 Soin Sigowet 007035098 Kericho county, unknown subcounty 007036001 Bomet East 007036002 Chepalungu 007036003 Konoin 007036004 Sotik 007036005 Bomet Central 007036098 Bomet county, unknown subcounty 008037001 Butere 008037002 Kakamega Central 008037003 Kakamega East 008037004 Kakamega North 008037005 Kakamega South 008037006 Khwisero 008037007 Likuyani 008037008 Lugari 008037009 Matete 008037010 Matungu 008037011 Mumias East 008037012 Mumias West 008037013 Navakholo 008038001 Emuhaya 008038002 Vihiga 008038003 Sabatia 008038004 Luanda 008038005 Hamisi 008038098 Vihiga county, unknown subcounty 008039001 Bumula 008039002 Bungoma Central 008039003 Bungoma East 008039004 Bungoma North 008039005 Bungoma South 008039006 Cheptais 008039007 Kimilili 008039008 Mt Elgon 008039009 Bungoma West 008039010 Tongaren 008039011 Webuye West 008039098 Bungoma county, unknown subcounty 008040001 Bunyala 008040002 Busia 008040003 Butula 008040004 Nambale 008040005 Samia 008040006 Teso North 008040007 Teso South Geography: F-N Variables -- HOUSEHOLD DHS-IPUMS-I Kenya regions, 1969-2019 [consistent boundaries, GIS] DHS_IPUMSI_KE provides geographic codes for Kenya that match those in the DHS and IPUMS-International databases. This variable can be used to link contextual area data from IPUMS-DHS to IPUMS-International or vice versa. The codes in DHS_IPUMSI_KE indicate the major administrative unit in which the household was enumerated or surveyed. GIS shapefiles for Kenya can be downloaded here. 1 Nairobi 2 Central 3 Coast 4 Eastern 5 Nyanza 6 Rift Valley 7 Western 8 Northeastern Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Ownership of dwelling [general version] OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. 0 NIU (not in universe) 1 Owned 2 Not owned 9 Unknown Household Economic Variables -- HOUSEHOLD Ownership of dwelling [detailed version] OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. 000 NIU (not in universe) 100 Owned 110 Owned, already paid 120 Owned, still paying 130 Owned, constructed 140 Owned, inherited 190 Owned, other 191 Owned, house 192 Owned, condominium 193 Apartment proprietor 194 Shared ownership 200 Not owned 210 Renting, not specified 211 Renting, government 212 Renting, local authority 213 Renting, parastatal 214 Renting, private 215 Renting, private company 216 Renting, individual 217 Renting, collective 218 Renting, joint state and individual 219 Renting, public subsidized 220 Renting, private subsidized 221 Renting, co-tenant 222 Renting, relative of tenant 223 Renting, cooperative 224 Renting, with a job or business 225 Renting, loan-backed habitation 226 Renting, mixed contract 227 Furnished dwelling 228 Sharecropping 230 Subletting 231 Rent to own 239 Renting, other 240 Occupied de facto/squatting 250 Free/usufruct (no cash rent) 251 Free, provided by employer 252 Free, without work or services 253 Free, provided by family or friend 254 Free, private 255 Free, public 256 Free, condemned 257 Free, other 260 Endowment, Waqf (Egypt historical) 290 Not owned, other 999 Unknown Household Economic Variables -- HOUSEHOLD Number of international migrants INTMIG1 indicates the number of people from the household who traveled to another country to live and have not permanently returned. 00 No migrants 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 or more 98 Unknown 99 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Electricity ELECTRIC indicates whether the household had access to electricity. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Utilities Variables -- HOUSEHOLD Water supply WATSUP describes the physical means by which the housing unit receives its water. The primary distinction is whether or not the household had piped (running) water. 00 NIU (not in universe) 10 Yes, piped water 11 Piped inside dwelling 12 Piped, exclusively to this household 13 Piped, shared with other households 14 Piped outside the dwelling 15 Piped outside dwelling, in building 16 Piped within the building or plot of land 17 Piped outside the building or lot 18 Have access to public piped water 20 No piped water 99 Unknown Utilities Variables -- HOUSEHOLD Sewage SEWAGE indicates whether the household has access to a sewage system or septic tank. 00 NIU (not in universe) 10 Connected to sewage system or septic tank 11 Sewage system (public sewage disposal) 12 Septic tank (private sewage disposal) 20 Not connected to sewage disposal system 99 Unknown Utilities Variables -- HOUSEHOLD Cooking fuel FUELCOOK indicates the predominant type of fuel or energy used for cooking. 00 NIU (not in universe) 10 None 20 Electricity 30 Petroleum gas, unspecified 31 Gas -- piped/utility 32 Gas -- tanked or bottled 33 Propane 34 Liquefied petroleum gas 35 Gas -- piped and bottled 40 Petroleum liquid 41 Oil, kerosene, and other liquid fuels 42 Kerosene/paraffin 43 Kerosene or oil 44 Kerosene or gasoline 45 Gasoline 46 Cocinol 47 Diesel 50 Wood, coal, and other solid fuels 51 Wood and other plant fuels 52 Non-wood plant materials 53 Coal or charcoal 54 Charcoal 55 Coal 56 Wood or charcoal 60 Multiple fuels 61 Bottled gas and wood 62 Propane and electricity 63 Propane, kerosene, and electricity 64 Propane and kerosene 65 Kerosene and electrictiy 66 Other combinations 70 Other 71 Alcohol 72 Biogas 73 Discarded or waste material 74 Dung/manure 75 Other combined organic waste materials 76 Solar energy 77 Candle 99 Unknown/missing Utilities Variables -- HOUSEHOLD Cellular phone availability CELL indicates the availability of a cellular phone in the household. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Utilities Variables -- HOUSEHOLD Internet access INTERNET indicates whether or not the household had an internet connection. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown Utilities Variables -- HOUSEHOLD Trash disposal This variable indicates whether the household's waste or garbage is collected by a sanitation service or disposed of in some other manner. 00 NIU (not in universe) 10 Collected by a sanitation service 11 Collected directly from the household or dwelling 12 Collected indirectly from a garbage container or deposit 13 Collected by a sanitation service only 14 Collected by a sanitation service and disposed of in some other manner 20 Disposed of in some other manner 21 Burned or buried 22 Burned 23 Buried 24 Thrown into street, vacant land, or common area 25 Thrown into river, lake, ocean, lagoon, etc. 26 Thrown into canyon or gulley 27 Dumped in pit 28 Communal refuse dump 29 Own refuse dump 30 Authorized refuse dump 31 Illegal refuse dump 32 Other dumping 33 Outside 34 In the fields 35 Fed to animals 36 Composted 37 Heap 38 Garden 39 Other, none 99 Unknown/missing Utilities Variables -- HOUSEHOLD Automobiles available AUTOS records whether a member of the household owned or had use of a vehicle and, in many samples, the number of such vehicles. 0 No autos 1 1 auto 2 2 autos 3 3 autos 4 4 autos 5 5 autos 6 6+ autos 7 Have auto, number unspecified 8 Unknown 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Computer COMPUTER indicates whether the household had a personal computer. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Refrigerator REFRIG indicates whether the household had a refrigerator. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Television set TV indicates whether the household had a television. 00 NIU (not in universe) 10 No 20 Yes, color or black-and-white not specified 21 1 television 22 2 televisions 23 3 televisions 24 4 televisions 25 5 televisions 26 6 televisions 27 7 televisions 28 8 televisions 29 9+ televisions 30 Yes, at least one color tv 31 1 color tv 32 2 color tvs 33 3+ televisions 40 Yes, black-and-white only 41 1 black-white tv 42 2 black-white tvs 43 3+ black-white tvs 99 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Radio in household RADIO indicates whether the household had a radio. 0 NIU (not in universe) 1 No 2 Yes 9 Unknown/missing Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Number of rooms ROOMS indicates the number of rooms occupied by the housing unit. 00 Part of a room; no rooms 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Toilet TOILET indicates whether the household had access to a toilet and, in most cases, whether it was a flush toilet or other type of installation. 00 NIU (not in universe) 10 No toilet 11 No flush toilet 20 Have toilet, type not specified 21 Flush toilet 22 Non-flush, latrine 23 Non-flush, other and unspecified 99 Unknown Dwelling Characteristics Variables -- HOUSEHOLD Floor material FLOOR indicates the dwelling's predominant flooring material. 000 NIU (not in universe) 100 None/unfinished (earth) 110 Sand 120 Dung 200 Finished 201 Cement, tile, or brick 202 Cement 203 Concrete 204 Cement screed 205 Ceramic tile 206 Paving stone, cement tile 207 Stone 208 Brick 209 Brick or stone 210 Brick or cement 211 Block 212 Terrazzo 213 Wood 214 Palm, bamboo 215 Parquet 216 Parquet, tile, vinyl 217 Parquet, tile, marble 218 Ceramic, marble, granite 219 Ceramic, marble, tile, or vinyl 220 Marble 221 Mosaic 222 Tile 223 Tile, linoleum, ceramic, etc 224 Tile, cement 225 Tile, stone 226 Tile, stone, brick 227 Tile, stone, vinyl, brick 228 Tile, vinyl, brick 229 Tile, vinyl 230 Vinyl, linoleum, etc 231 Asphalt sheet, vinyl, etc 232 Synthetic, plastic 233 Cane 234 Carpet, rug 235 Scrap material 236 Other finished, n.e.c. 999 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Wall or building material This variable indicates the primary material used in the construction of the dwelling, particularly the dwelling's exterior walls. 000 NIU (not in universe) 100 No walls 200 Cardboard, scrap, and miscellaneous materials 201 Waste, scrap, or discarded material 202 Fabric or discarded material 203 Zinc, fabric, cardboard, tins, and waste material 204 Cardboard sheet 205 Plastic sheeting, cardboard 206 Makeshift, salvaged, or improvised materials 207 Reused materials 300 Wood 310 Rough wood 320 Wood, fibercement or plywood 330 Wood, formica, and other 340 Wood or bamboo 350 Wood or straw 400 Other plant-based materials 401 Plantain leaves and similar material 402 Bamboo or cane 403 Bamboo, sawali, cogon, nipa 404 Straw or bamboo 405 Grass, straw or reed 406 Reed, bamboo, or palm 407 Cane, palm leaves, logs 408 Palm leaves or palm planks 409 Bark, sticks, or cane 500 Masonry, stone, cement, adobe, metal, glass, and other fabricated materials (sometimes mixed with wood) 501 Brick, block, stone, or cement 502 Brick, stone, concrete 503 Brick, stone, or substitutes (dividing panels made of reinforced concrete) 504 Brick, stone, or substitutes (dividing panels made of wood) 505 Brick or tile 506 Brick or stone 507 Brick or cement block 508 Brick with plaster exterior 509 Brick without plaster exterior 510 Burnt or stabilized brick 511 Covered brick 512 Brick 513 Unburnt brick 514 Unburnt brick with cement 515 Unburnt brick with mud 516 Concrete 517 Landcrete, sandcrete 518 Cement blocks 519 Cement blocks or brick 520 Cement blocks or brick, unfinished 521 Cement and adobe bricks 522 Cement and stone block 523 Cement and tiles 524 Reinforced concrete, pre-cast concrete panels, or steel skeleton framed concrete 525 Concrete, reinforced concrete, blocks, panels 526 Fibercement 527 Adobe 528 Adobe walls with plaster exterior 529 Adobe walls without plaster exterior 530 Adobe with cement exterior 531 Wood and earth adobe 532 Wood and cement adobe 533 Mud or adobe 534 Pressed dirt 535 Clay 536 Coated clay/mud with sticks/cane 537 Clay or clay-covered sticks 538 Netted bamboo or cane with mud 539 Bundle of mud, straw, other materials 540 Mud with wood/wattle 541 Pole and mud 542 Mud with cement 543 Unfinished lathe and plaster, stucco, etc. 544 Stone 545 Hand-laid stone 546 Quarried stone 547 Cut stone and concrete 548 Cemented stone 549 Stone with clay 550 Blocks of light material 551 Prefabricated material 552 Asbestos 553 Metal or asbestos sheet 554 Metal or iron sheet 555 Metal or fibercement sheeting 556 Galvanized iron or aluminum 557 Tin 558 Glass 559 Cloth 560 Covintec panels 561 Mixed material 562 Mixed material: part wood; part concrete, brick, or stone 563 Wood plastered with clay, adobe, other materials; wood pressed panels; rolled mud bricks; etc. 564 Mixed material: wood or galvanized metal 570 Mainly permanent materials 600 Other material 601 Partition wall, lined with wood or steel 602 Partition wall, unlined 999 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Roof material This variable indicates the dwelling's predominant roofing material. 00 NIU (not in universe) 10 Masonry, concrete, clay tile, or tiles of unspecified type 11 Concrete or cement 12 Reinforced concrete (slab) 13 Cement or sheet metal 14 Tile, unspecified material 15 Clay tile 16 Tile or cement 17 Modern tiles, industrial 18 Traditional tiles, locally made 19 Tile or flat stone 20 Tile, unspecified or mixed materials 21 Fibercement or plastic 22 Fibercement or metal sheets 23 Asphalt or laminate cover 24 Tile, cement, asphalt 25 Asphalt tile 26 Slate or tile 27 Slate or asbestos 28 Asbestos 29 Adobe 30 Tiles or wood planks 31 Roofing shingles 32 Tar paper 33 Metal 34 Sheet metal 35 Zinc or tin 36 Tin 37 Sheet metal or other sheet material 38 Sheet metal, tile, slate 40 Wood and other plant materials 41 Wood 42 Wood, including bamboo 43 Bamboo 44 Cogon, nipa, anahaw 45 Thatch (straw, grass, leaves, palm, etc.) 46 Cane, wood, straw 47 Grass or straw 48 Papyrus 49 Banana leaves or fiber 50 Palm or makuti 51 Straw, bamboo, polythene 52 Wood with clay 53 Grass and mud 54 Rustic mat 60 Mud or earth 61 Clay 70 Cardboard, scrap, and miscellaneous materials 71 Discarded or scrap material 72 Cardboard 73 Plastic, tarpaulin 80 Other, unspecified 90 No roof 99 Unknown/missing Dwelling Characteristics Variables -- HOUSEHOLD Household classification HHTYPE is a constructed variable that describes the composition of households. HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ. 00 Vacant household 01 One-person household 02 Married/cohab couple, no children 03 Married/cohab couple with children 04 Single-parent family 05 Polygamous family 06 Extended family, relatives only 07 Composite household, family and non-relatives 08 Non-family household 09 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable Constructed Household Variables -- HOUSEHOLD Number of families in household NFAMS is a constructed variable that indicates the number of families within each household. Family membership is defined by FAMUNIT. A "family" is any group of persons related by blood, adoption, or marriage. An unrelated individual within the household is considered a separate family. Thus, a household consisting of a widow and a domestic employee contains two families; a household consisting of a large, multi-generation extended family with no persons unrelated to the head counts as a single family. NFAMS is constructed from information in RELATE (relationship to head) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). See those variable descriptions for more detail. 0 Vacant household 1 1 family 2 2 families 3 3 families 4 4 families 5 5 families 6 6 families 7 7 families 8 8 families 9 9 or more families Constructed Household Variables -- HOUSEHOLD Number of married couples in household NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household. NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household). 0 No married couples in household 1 1 couple 2 2 couples 3 3 couples 4 4 couples 5 5 couples 6 6 couples 7 7 couples 8 8 couples 9 9 or more couples Constructed Household Variables -- HOUSEHOLD Number of mothers in household NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household. NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household). 0 No mothers in household 1 1 mother 2 2 mothers 3 3 mothers 4 4 mothers 5 5 mothers 6 6 mothers 7 7 mothers 8 8 mothers 9 9 or more mothers in household Constructed Household Variables -- HOUSEHOLD Number of fathers in household NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household. NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household). 0 No fathers in household 1 1 father 2 2 fathers 3 3 fathers 4 4 fathers 5 5 fathers 6 6 fathers 7 7 fathers 8 8 fathers 9 9 or more fathers in household Constructed Household Variables -- HOUSEHOLD Head's location in household HEADLOC gives the person number (PERNUM) of the head of household in samples in which persons are organized into households. HEADLOC is a 3-digit numeric variable. Constructed Household Variables -- HOUSEHOLD Dwelling number Kenya 2019: All records This variable indicates the dwelling number. This is a 7-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Number of persons in household Kenya 2019: All records This variable indicates the number of persons in household. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 35 35 40 40 50 50 Technical Household Variables -- HOUSEHOLD Dwelling created by splitting apart a large dwelling or household Kenya 2019: All records This variable indicates whether a dwelling was created by splitting apart a large dwelling or household. 0 No problem 1 Yes: households within a large dwelling were split apart into separate dwellings 2 Yes: persons within a large household were split apart into separate dwellings Technical Household Variables -- HOUSEHOLD Urban or rural enumeration area 10.2. Different categories of EAs</p> <p>There are four distinct categories of EAs:</p> <div class="i1">i. EAs in settled agricultural areas;<br />ii. EAs in urban/peri urban areas;<br />iii. EAs in arid and semi-arid areas; and<br />iv. EAs in forests / national parks or game reserves.</div><p>EAs in settled agricultural areas are based on villages e.g. an EA is formed by part of a village (as is the case of Ochi village which has been split to form two EAs: 004 and 005), a whole village (as is the case of Kipgeigei village EA 006) or by combining two or more villages (as is the case of EA 002 which is made up of two villages i.e. Chepsetyon and Chelogon (See Appendix 5 Map 1). In the peri urban areas, the EAs are based on villages and hence are mapped as EAs in settled agricultural areas. In case of difficulty or doubt about the EA boundary, please contact your supervisor, the Assistant Chief or Village Elder.</p> <p>In urban areas, the EAs are based on estate boundaries/blocks (flats). All the structures in this category have been numbered and are clearly shown on the maps. For example, the 9th structure on the ground is numbered as KNBS/KPHC/2019/009 while on the map is numbered as 009. (See Appendix 5 Map 2).</p> <p>In arid and semi-arid areas, the EAs have been delineated on the basis of settlement points. The boundaries have been fixed arbitrarily. The settlement areas can easily be identified through the location of homesteads which have been plotted on the map. You must contact your supervisor, the Assistant Chief or Village Elder to assist you to locate the settlement points (See Appendix 5 Map 3).</p> <p>Large forests, national parks and reserves have been treated as special EAs on their own. You must, with the assistance of the forest officials or game wardens, identify where people live in such EAs (See Appendix 5 Map 4). Kenya 2019: All households This variable indicates whether the household is located in an urban or rural enumeration area. 1 Rural 2 Urban Geography: F-N Variables -- HOUSEHOLD Formal or informal enumeration area Kenya 2019: All households This variable indicates whether the household is located in a formal or informal enumeration area. 1 Informal 2 Formal Geography: F-N Variables -- HOUSEHOLD Type of questionnaire <span class="em">18. Layout of the main census questionnaire</span></p> <p>18.1. Identification panel <br />The top of the questionnaire is reserved for information identifying the household and summaries for each household. It provides the geo information for each area, which is necessary for identifying the geographic positioning of households within the Country during analysis. Computer Assisted Personal Interviewing (CAPI) will have this area pre-filled and your role will be to select your assigned area and populate only the household numbers. In addition, you will be required to ask the respondent the Total Number of persons by sex who spent the Census Night in each household and fill it before proceeding to list/roster them.</p> <p>18.2. Main census questionnaire sections</p> <div class="i1">i. Section A: Information regarding all persons. This information is contained in columns P-00 to P-25. Questions in this section will apply to all persons. The respondent will be the head of Household or any responsible adult in absence of HH head or one delegated so by the head of the Household.<br /><br />Note: Questions prefixed with "P" are person level (Individual) questions and "H" are household level questions.<br /><br />ii. Section B: Information regarding females aged 12 years and above. This section covers columns P-26 to P-41. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. As much as possible, obtain the information directly from the female concerned and ensure privacy. Information should only be obtained from someone else if the respondent cannot be reached.<br /><br />iii. Section C: Information regarding persons with difficulties in performing activities of daily life. It covers columns P42 to P44 and asks questions relating to persons with difficulties in performing activities of daily life. You are required to ask these questions to all persons unless where stated otherwise.<br /><br />iv. Section D: Information regarding education. This section covers columns P45 to P48. Columns P45 to P47 shall be asked to all persons aged 3 years and above while P48 shall be asked to persons aged 15 years and above.<br /><br />v. Section E: Labour force particulars. This section covers columns P49 to P54 and should be asked of all persons aged 5 years and above.<br /><br />vi. Section F: Information regarding ICT (information, communication and technology). It covers columns P55 to P59. Columns P55 to P58 apply to all persons aged 3 years and above while column P59 applies to persons aged 15 years and above.<br /><br />vii. Section G: Annual live births and deaths: (Note that this section is the start of the Household Level Questions). The section covers column H10 to H18 and seeks information on all live births and deaths that occurred in the household between 24/8/2018 and 24/8/2019 (last 12 months). The questions should be posed to the head of the household or any other responsible member of the household.<br /><br />viii. Section H: Information regarding crop farming, livestock, fishing and aquaculture: The section covers columns H19 to H26 and captures data on crops, livestock and fishing activities within the county. The questions should be posed to the head of the household or any other responsible member of the household.<br /><br />ix. Section I: Housing conditions and amenities. This section covers columns H27 to H38. These questions are to be posed to the Head of the Household or any other responsible person.<br /><br />x. Section J: Ownership of household assets: This section covers column H39 and seeks information on the ownership of common household assets by any household member. Examples of assets include radio, television, mobile phone etc. The question is posed to the Household head or any other responsible member of the household.<br /><br />xi. Section K: Emigrants. This section covers column H40 and seeks information on any member of the household who may have migrated to another country since 2004 (last 15 years). Details about persons who have migrated will be captured using a short Emigrants questionnaire. (CAPI will prompt you to call this questionnaire for the households where applicable).</div> Kenya 2019: All households This variable indicates the type of questionnaire. 1 Main form 9 Unknown Other Household Variables -- HOUSEHOLD Live births last 12 months <span class="h2">G: Information about annual live births and deaths in the household</span></p> <p>H-10. How many live births occurred in this household between 24/08/2018 and 24/08/2019 last 12 months?</p> <div class="i1">_ _ Boys<br />_ _ Girls</div> <span class="em">26. Section G: Information on annual live births and deaths in the household</span> <br />This section is about all live births and deaths that occurred in the household in the last 12 months (between 24th August, 2018 and 24th August, 2019).</p> <p>26.1. Column H10: Births in the household <br />Ask: How many live births have occurred in this household between 24/8/2018 and 24/8/2019. Record the responses in column H10. Births will be captured in the households where they occurred, i.e. if a woman gave birth to a child while still staying with her parents but has since moved from the household, the birth should be captured in the parent's household where it occurred. Women who gave birth while visiting, the births should be recorded with the household they were visiting. Those who gave birth within a health facility, the birth will be captured in the household where she was staying. Kenya 2019: Private households [discrepancies: none] This variable indicates whether there were live births in the household in the last 12 months. 0 No births last 12 months 1 1 birth 2 2 3 3 9 NIU (not in universe) Other Household Variables -- HOUSEHOLD Deaths last 12 months <span class="h2">G: Information about annual live births and deaths in the household</span></p> <p>H-11. How many deaths occurred in this household between 24/08/2018 and 24/08/2019 last 12 months?</p> <div class="i1">Number of deaths _____<br /><br />If "00" skip to H-19.</div> 26.2. Columns H11- H18: Recent deaths in the household</p> <div class="i1">i. Purpose of the section<br />This section seeks to capture information on recent deaths in the household. The duration being considered is the period between August, 2018 and August, 2019.<br /><br />ii. Respondent<br />The household head or any other responsible household member should answer the questions in this section (H11--H18). Deaths will only be captured in the households where they occurred i.e. if a death occurred to somebody visiting a different household that death should be captured in the household that was being visited. If death occurred to somebody who was transfered directly from one county to a health facility in another county, that death should be captured in the household in the county of residence.<br /><br />Note: Some respondents may avoid mentioning children who died at very young ages or during birth. Cases of still births should not be captured. In this case, a child who shows any of the following signs, soon after birth, is considered a "live" birth: cries, moves spontaneously or shows any sign of life. However, a birth that shows none of the above signs is called a 'still birth' and should be excluded in this section. A live birth that dies soon after birth or within 12 months prior to the census interview should be included.</div><p>26.3. Column H11: Deaths in the household <br />Ask, "How many deaths occurred in this household between August, 2018 and August, 2019?" If there were deaths, record the number; if none, record "0" and skip to Section H. All deaths should be captured, whether at infancy or very old ages. Please note the following scenarios;</p> <div class="i1">- If a death occurred in another household and the body was brought into the current household just for burial, that death should not be captured in this household but in the household where it occured.<br />- If a death occurred in hospital or on the way to hospital or as a result of an accident, that death will be captured in the household where the person was living before death.</div> Kenya 2019: Private households [discrepancies: type I none; type II trace] This variable indicates whether there were deaths in the household in the last 12 months. 0 No deaths last 12 months 1 1 death 2 2 3 3 4 4+ 8 Unknown 9 NIU (not in universe) Other Household Variables -- HOUSEHOLD Household member farmed crops in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-19. During the last 12 months, did any member of this household engage in the following within this county?</p> <div class="i1">If "2" or "9", skip to H-25.</div><div class="i1">Crop farming</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">27. Section H: Information regarding crop, livestock, fishing and aquaculture</span> <br />This section will be administered at the household level while seeking information on crops, livestock, fishing and fish-farming (aquaculture). In particular, the section collects information on crop farming, the numbers by type of livestock being reared or managed by the household, fishing activities by members of the household and fish farming or aquaculture through use of fish ponds/cages.</p> <p>27.1. Key agricultural concepts - agricultural holding: <br />This is a unit where agricultural activities are practiced under the management of a member of the household. These include:</p> <div class="i1">i. Growing of crops<br />ii. Keeping of livestock<br />iii. Fish farming<br />iv. Tree farming (agro-forestry)</div><p>Annual/temporary crop: a plant that completes its life cycle, from germination to the production of seeds, within a few months up to one year, and then dies. Many do not have woody stems.</p> <p>Perennial/permanent crop: Long-living crops that grow for more than one year; many have woody stems.</p> <p>Tillers: A tiller is a stem produced by a plant (mainly grass family) and refers to all shoots that grow after the initial parent shoot grows from a seed. Tillers grow separately from the main shoot and may mature to form own flowers and seeds.</p> <p>Compact plantation: plants, trees and shrubs planted in the holding in a regular and systematic spacing pattern; usually, area of compact plantation is easy to measure.</p> <p>Scattered plantation: trees, fruits, etc. planted in the holding with no clear spacing pattern, along fences, etc. usually area not easy to measure.</p> <p>27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25). Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member farmed crops in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member reared livestock in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-19. During the last 12 months, did any member of this household engage in the following within this county?</p> <div class="i1">If "2" or "9", skip to H-25.</div><div class="i1">Livestock rearing</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">27. Section H: Information regarding crop, livestock, fishing and aquaculture</span> <br />This section will be administered at the household level while seeking information on crops, livestock, fishing and fish-farming (aquaculture). In particular, the section collects information on crop farming, the numbers by type of livestock being reared or managed by the household, fishing activities by members of the household and fish farming or aquaculture through use of fish ponds/cages.</p> <p>27.1. Key agricultural concepts - agricultural holding: <br />This is a unit where agricultural activities are practiced under the management of a member of the household. These include:</p> <div class="i1">i. Growing of crops<br />ii. Keeping of livestock<br />iii. Fish farming<br />iv. Tree farming (agro-forestry)</div><p>Annual/temporary crop: a plant that completes its life cycle, from germination to the production of seeds, within a few months up to one year, and then dies. Many do not have woody stems.</p> <p>Perennial/permanent crop: Long-living crops that grow for more than one year; many have woody stems.</p> <p>Tillers: A tiller is a stem produced by a plant (mainly grass family) and refers to all shoots that grow after the initial parent shoot grows from a seed. Tillers grow separately from the main shoot and may mature to form own flowers and seeds.</p> <p>Compact plantation: plants, trees and shrubs planted in the holding in a regular and systematic spacing pattern; usually, area of compact plantation is easy to measure.</p> <p>Scattered plantation: trees, fruits, etc. planted in the holding with no clear spacing pattern, along fences, etc. usually area not easy to measure.</p> <p>27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25). Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member reared livestock in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member engaged in aquaculture in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-19. During the last 12 months, did any member of this household engage in the following within this county?</p> <div class="i1">If "2" or "9", skip to H-25.</div><div class="i1">Aquaculture</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">27. Section H: Information regarding crop, livestock, fishing and aquaculture</span> <br />This section will be administered at the household level while seeking information on crops, livestock, fishing and fish-farming (aquaculture). In particular, the section collects information on crop farming, the numbers by type of livestock being reared or managed by the household, fishing activities by members of the household and fish farming or aquaculture through use of fish ponds/cages.</p> <p>27.1. Key agricultural concepts - agricultural holding: <br />This is a unit where agricultural activities are practiced under the management of a member of the household. These include:</p> <div class="i1">i. Growing of crops<br />ii. Keeping of livestock<br />iii. Fish farming<br />iv. Tree farming (agro-forestry)</div><p>Annual/temporary crop: a plant that completes its life cycle, from germination to the production of seeds, within a few months up to one year, and then dies. Many do not have woody stems.</p> <p>Perennial/permanent crop: Long-living crops that grow for more than one year; many have woody stems.</p> <p>Tillers: A tiller is a stem produced by a plant (mainly grass family) and refers to all shoots that grow after the initial parent shoot grows from a seed. Tillers grow separately from the main shoot and may mature to form own flowers and seeds.</p> <p>Compact plantation: plants, trees and shrubs planted in the holding in a regular and systematic spacing pattern; usually, area of compact plantation is easy to measure.</p> <p>Scattered plantation: trees, fruits, etc. planted in the holding with no clear spacing pattern, along fences, etc. usually area not easy to measure.</p> <p>27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25). Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member engaged in aquaculture in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Main purpose of agricultural production <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-20. What was the main purpose of the main agricultural production?</p> <div class="i1">[] 1. Producing mainly for own consumption subsistence<br />[] 2. Producing mainly for sale commercial<br />[] 3. Not applicable<br />[] 9. DK</div> <span class="em">27. Section H: Information regarding crop, livestock, fishing and aquaculture</span> <br />This section will be administered at the household level while seeking information on crops, livestock, fishing and fish-farming (aquaculture). In particular, the section collects information on crop farming, the numbers by type of livestock being reared or managed by the household, fishing activities by members of the household and fish farming or aquaculture through use of fish ponds/cages.</p> <p>27.1. Key agricultural concepts - agricultural holding: <br />This is a unit where agricultural activities are practiced under the management of a member of the household. These include:</p> <div class="i1">i. Growing of crops<br />ii. Keeping of livestock<br />iii. Fish farming<br />iv. Tree farming (agro-forestry)</div><p>Annual/temporary crop: a plant that completes its life cycle, from germination to the production of seeds, within a few months up to one year, and then dies. Many do not have woody stems.</p> <p>Perennial/permanent crop: Long-living crops that grow for more than one year; many have woody stems.</p> <p>Tillers: A tiller is a stem produced by a plant (mainly grass family) and refers to all shoots that grow after the initial parent shoot grows from a seed. Tillers grow separately from the main shoot and may mature to form own flowers and seeds.</p> <p>Compact plantation: plants, trees and shrubs planted in the holding in a regular and systematic spacing pattern; usually, area of compact plantation is easy to measure.</p> <p>Scattered plantation: trees, fruits, etc. planted in the holding with no clear spacing pattern, along fences, etc. usually area not easy to measure.</p> <p>27.3. Column H20: Main purpose of agricultural production <br />For those who respond yes in Column H19,</p> <p>Ask, "what was the main purpose of agricultural production?" <br />The aim of this question is to establish how agricultural households participate in the market economy. These are:</p> <div class="i1">i. Producing mainly for own consumption (subsistence)<br />ii. Producing mainly for sale (commercial)</div><p>If the production is used mainly for fodder, establish whether the fodder is for own use (subsistence) or for sale (commercial).</p> <p>In cases where a household sells some produce and uses the rest for own consumption, "main purpose" should be which of the two represents the larger value of the production. Sale refers to exchange of produce for cash or for other goods or services (barter). <br />Disposal of agricultural produce in other ways such as giving gifts, paying dowry, etc., should not be considered while assessing the main purpose of production. Kenya 2019: Households with agricultural activities in current county last year [discrepancies: type I trace; type II none] This variable indicates the household's main purpose of agricultural production. 1 Producing mainly for own consumption (subsistence) 2 Producing mainly for sale (commercial) 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Area of agricultural holding in this county (in acres) <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-21. What is the area of agriculture holding operated by this household in acres in this county? <span class="ital">1 Ha = 2.47 acres</span>:</p> <div class="i1">_____ acres</div> <span class="em">27. Section H: Information regarding crop, livestock, fishing and aquaculture</span> <br />This section will be administered at the household level while seeking information on crops, livestock, fishing and fish-farming (aquaculture). In particular, the section collects information on crop farming, the numbers by type of livestock being reared or managed by the household, fishing activities by members of the household and fish farming or aquaculture through use of fish ponds/cages.</p> <p>27.1. Key agricultural concepts - agricultural holding: <br />This is a unit where agricultural activities are practiced under the management of a member of the household. These include:</p> <div class="i1">i. Growing of crops<br />ii. Keeping of livestock<br />iii. Fish farming<br />iv. Tree farming (agro-forestry)</div><p>Annual/temporary crop: a plant that completes its life cycle, from germination to the production of seeds, within a few months up to one year, and then dies. Many do not have woody stems.</p> <p>Perennial/permanent crop: Long-living crops that grow for more than one year; many have woody stems.</p> <p>Tillers: A tiller is a stem produced by a plant (mainly grass family) and refers to all shoots that grow after the initial parent shoot grows from a seed. Tillers grow separately from the main shoot and may mature to form own flowers and seeds.</p> <p>Compact plantation: plants, trees and shrubs planted in the holding in a regular and systematic spacing pattern; usually, area of compact plantation is easy to measure.</p> <p>Scattered plantation: trees, fruits, etc. planted in the holding with no clear spacing pattern, along fences, etc. usually area not easy to measure.</p> <p>27.4. Column H21: Area of agricultural holding</p> <p>Ask, "What is the area of agricultural holding (in acres) operated by this household in this county?" If the area is given in hectares, convert to acres using the conversion; <br />1 ha = 2.47 acres</p> <p>An agricultural holding is all land used wholly or partly for agricultural production purposes, without regard to title, legal form, or size. That is, land area where crops are grown (even on road side), livestock are kept, and or fish are reared. <br />It refers to an economic unit of agricultural production under single management. Single management may be exercised by:</p> <div class="i1">i. an individual member of household, or household (through head of household); or jointly by two or more individuals or households; or<br />ii. Juridical person/ legal entity created by law, acting like a person, but is not a natural person, such as a corporation, company, college, cooperative or government agency. Usually, the legal entity has a distinct identity and legal rights and obligations under the law.</div><p>An agricultural holding may be made up of parcels; whereby a parcel is a smaller piece of land within holding with clear separating boundary, such as road, foot path, etc. The parcel may be surrounded by other land belonging to different owner(s), or other natural features. A parcel may also be divided into plots, which are smaller units, or fields dedicated to specific activities or enterprises.</p> <p>A holding may consist of one or more parcels, located in one or more separate areas or in one or more territorial or administrative divisions, provided the parcels share the same production means, such as labour, farm buildings, machinery or draught animals. Operationally, the focus of this question will be to aggregate the area of all parcels operated by the household within the county during the reference period. The same principle should be applied for non-household establishments, that is, those agricultural establishments managed by corporations, cooperatives or government agencies, etc.</p> <p>The following additional points relate to the identification of an agricultural holding:</p> <div class="i1">i. Agricultural holdings may be operated by persons who do not have any legal rights to use the land (e.g. farmers using road reserves).<br />ii. If a non-household entity such as a company, school or cooperative, etc. allocates a member a part of the institution's holding for agricultural production, that is, the allocated portion is operated under the member's management, and over which the member has general, technical and economic responsibility. Then in such a case, the allocated unit represents a separate holding belonging to the member.<br />iii. Open rangeland, such as open land for communal grazing, should not be considered part of the holding belonging to a particular household or member of household. For households having access to communal grazing land, their share of such land should not be included in the area of their holding unless the holding has been specifically assigned a certain area delineated by fencing or other form of boundary demarcation.<br />iv. The area of the holding is the area of all the land making up the agricultural holding. It includes all land operated by members of a household. Land rented to others by the household should not be included in the area of the holding. Conversely, land not owned by members of a household but rented from others for agricultural production purposes should be included in the area of the holding.<br />v. Sometimes, the area of the holding could be insignificant or even zero, but nevertheless, the holding could have an agricultural activity. For example, some holdings without any significant area such as a building unit may be used for raising poultry, or keeping other livestock (such as houses in urban areas). In this case, the agricultural holding could be considered as landless.</div><p>The enumerator is supposed to get the area in acres of the holding estimated up to three (3) decimal points. For respondents with difficulties estimating their sizes of holding, the enumerators should assist them bearing in mind that one football pitch is about 2 acres while most plots in urban centres are either eighth or quarter an acre. For example, an eighth (1/8) of an acre is 0.125 acres. Kenya 2019: Households with agricultural activities in current county last year [discrepancies: type I 0.2%; type II none] This variable indicates the household's area of agricultural holding in this county (in acres). This is a 8-digit numeric variable with 3 implied decimal places Household Economic Variables -- HOUSEHOLD Household member practiced irrigation on agricultural holding in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-22. During the last 12 months, did any member of this household practice irrigation on the agriculture holding?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.5. Column H22: Irrigation on agricultural holding <br />Ask, "during the last 12 months, did any member of the household practice irrigation on the agriculture holding in this county?"</p> <p>Irrigation is the practice of conveying water from a source through an established hydraulic system to crops for agricultural production. Sources of water include rivers, lakes, reservoirs, boreholes, and wells. The hydraulic system includes canals and/or pipe network and application is through either basin, furrow, sprinkler, and drips systems. Overhead systems such as center pivots, rainguns, etc. all fall under sprinklers.</p> <p>Note that the human practice of drawing water from water source using watering cans or buckets and pouring the water on crops without any developed infrastructure for channeling the water should not be considered as irrigation.</p> <p>Indicate a "yes" if any member of the household practices irrigation using the above methods and "no" if none. Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member practiced irrigation on agricultural holding in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Agricultural holding includes tea as a permanent crop <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-23. Does the holding have any of the following permanent crops within this county?</p> <div class="i1">Tea</div><div class="i2">[] 1. Yes, compact plantation<br />[] 2. Yes, scattered plants<br />[] 3. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.6. Column H23: Permanent crops on the holding <br />Ask, "does the holding have any of the following permanent crops in this county?"</p> <p>The question is whether permanent crops are present on the holding during the reference period. Permanent crops include those crops produced from plants that stay in the holding for several years once planted, rather than being planted every season, or replanted after each harvest. For such crops, the trees or bushes take a number of years before the first harvest. Examples of such crops are tea, coffee, avocado, citrus, mango, coconut, macadamia, cashew nut and khat (miraa).</p> <p>Permanent crops can be grown either in compact plantations, or in form of scattered trees depending on the interest. A compact plantation includes plants, trees and shrubs planted in a regular and systematic manner. However, scattered plants are those planted in such a manner that they are scattered within or around the holding.</p> <p>For purposes of this census, plantations of trees such as bamboo, eucalyptus, or any other cultivated non-food tree crops will not be considered as permanent crops.</p> <div class="i1">Tea (Majani Chai)<br />An evergreen shrub or small tree, usually grown in compact plantation, whose leaves and leaf buds (last 3 young leaves) are plucked and processed in factories in order to produce tea. In Kenya, tea is grown in cool, wet places. In recent times, some farmers have started planting of purple tea (with purple leaves).<br />Farmer with less than 50 productive bushes, whether compact or scattered, should not be considered as tea farmer.</div><div class="i1">Coffee (Kahawa)<br />Is a small perennial tree or shrub with woody stem that has several branches. Mature crop produces seeds, called coffee beans, which are greenish when immature but turn into reddish cherry as they ripen. The cherry are harvested and processed to make various coffee beverages.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as coffee farmer.</div><div class="i1">Coconut (Nazi)<br />Is a large palm tree, with large umbrella-like leaves, usually grown as scattered trees. For mature crops, the old leaves break away, leaving smooth strong stem or trunk. A mature tree produces a fruit with a hard outer cover and whitish flesh that can be eaten raw or dried into powder. Immature, greenish fruit has liquid that can be used as human drink. In Kenya, coconut is mainly grown in warm, low altitude, coastal regions.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as coconut farmer.</div><div class="i1">Cashew Nut (Korosho)<br />The cashew tree is large and evergreen, with a short stem, often with several branches when mature. A mature tree produces several flowers forming into an oval or pear-shaped yellowish fruit. When dry, the fruit turns into a hard shell with single kidney shaped nut. The nut is extracted carefully either through roasting or shelling.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as cashew nut farmer.</div><div class="i1">Macadamia<br />Macadamia is an evergreen tree, with large, dark-green leaves. A mature tree forms a greenish fruit that contains a hard, brownish shell. When the shell is cracked, a dark brown spherical shaped nut is found.<br /><br />Farmer with less than 3 productive trees, whether compact or scattered, should not be considered as macadamia farmer.</div><div class="i1">Citrus<br />These are large shrubs or small to moderate-sized trees, with evergreen, shiny leaves that are often very strongly scented. The term citrus refers to a group of crops including oranges, lemons, tangerines and limes. A mature tree produces green to orange colored fruits with juice that usually contains a high quantity of citric acid giving them their characteristic sharp flavour.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as citrus farmer.</div><div class="i1">Avocado (Parachichi)<br />The avocado is a dense, evergreen tree, shedding many leaves during dry periods. The leaves are dark green and dropped leaves are slow to decompose and may collect in mounds beneath trees. Mature tree produce green-skinned, fleshy fruit that may be pear-shaped, egg-shaped, or spherical. Mostly, the fruits ripen after harvesting.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as avocado farmer.</div><div class="i1">Mango (Maembe)<br />Mango is a deep rooted, tropical tree with several branches. Young leaves are pinkish, turning to dark green as they mature. A mature tree produces fruits that may be round, oval, or kidney-shaped. Ripe fruits have a distinctive sweet smell and have a single, large seed protected by a tough casing.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as mango farmer.</div><div class="i1">Khat (Miraa)<br />Khat is a slow-growing evergreen shrub, which is cultivated as a bush or small tree. The leaves are dark pink, and usually plucked for chewing. The plant is seedless and hardy, growing mainly in warm climatic conditions. The leaves of khat are chewed by the people for its stimulant action. In Kenya, miraa is mainly grown in Meru, Embu and parts of Tharaka Nithi Counties.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as Khat/miraa farmer.</div><p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether the household's agricultural holding includes tea as a permanent crop. 1 Yes 3 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Agricultural holding includes coffee as a permanent crop <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-23. Does the holding have any of the following permanent crops within this county?</p> <div class="i1">Coffee</div><div class="i2">[] 1. Yes, compact plantation<br />[] 2. Yes, scattered plants<br />[] 3. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.6. Column H23: Permanent crops on the holding <br />Ask, "does the holding have any of the following permanent crops in this county?"</p> <p>The question is whether permanent crops are present on the holding during the reference period. Permanent crops include those crops produced from plants that stay in the holding for several years once planted, rather than being planted every season, or replanted after each harvest. For such crops, the trees or bushes take a number of years before the first harvest. Examples of such crops are tea, coffee, avocado, citrus, mango, coconut, macadamia, cashew nut and khat (miraa).</p> <p>Permanent crops can be grown either in compact plantations, or in form of scattered trees depending on the interest. A compact plantation includes plants, trees and shrubs planted in a regular and systematic manner. However, scattered plants are those planted in such a manner that they are scattered within or around the holding.</p> <p>For purposes of this census, plantations of trees such as bamboo, eucalyptus, or any other cultivated non-food tree crops will not be considered as permanent crops.</p> <div class="i1">Tea (Majani Chai)<br />An evergreen shrub or small tree, usually grown in compact plantation, whose leaves and leaf buds (last 3 young leaves) are plucked and processed in factories in order to produce tea. In Kenya, tea is grown in cool, wet places. In recent times, some farmers have started planting of purple tea (with purple leaves).<br />Farmer with less than 50 productive bushes, whether compact or scattered, should not be considered as tea farmer.</div><div class="i1">Coffee (Kahawa)<br />Is a small perennial tree or shrub with woody stem that has several branches. Mature crop produces seeds, called coffee beans, which are greenish when immature but turn into reddish cherry as they ripen. The cherry are harvested and processed to make various coffee beverages.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as coffee farmer.</div><div class="i1">Coconut (Nazi)<br />Is a large palm tree, with large umbrella-like leaves, usually grown as scattered trees. For mature crops, the old leaves break away, leaving smooth strong stem or trunk. A mature tree produces a fruit with a hard outer cover and whitish flesh that can be eaten raw or dried into powder. Immature, greenish fruit has liquid that can be used as human drink. In Kenya, coconut is mainly grown in warm, low altitude, coastal regions.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as coconut farmer.</div><div class="i1">Cashew Nut (Korosho)<br />The cashew tree is large and evergreen, with a short stem, often with several branches when mature. A mature tree produces several flowers forming into an oval or pear-shaped yellowish fruit. When dry, the fruit turns into a hard shell with single kidney shaped nut. The nut is extracted carefully either through roasting or shelling.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as cashew nut farmer.</div><div class="i1">Macadamia<br />Macadamia is an evergreen tree, with large, dark-green leaves. A mature tree forms a greenish fruit that contains a hard, brownish shell. When the shell is cracked, a dark brown spherical shaped nut is found.<br /><br />Farmer with less than 3 productive trees, whether compact or scattered, should not be considered as macadamia farmer.</div><div class="i1">Citrus<br />These are large shrubs or small to moderate-sized trees, with evergreen, shiny leaves that are often very strongly scented. The term citrus refers to a group of crops including oranges, lemons, tangerines and limes. A mature tree produces green to orange colored fruits with juice that usually contains a high quantity of citric acid giving them their characteristic sharp flavour.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as citrus farmer.</div><div class="i1">Avocado (Parachichi)<br />The avocado is a dense, evergreen tree, shedding many leaves during dry periods. The leaves are dark green and dropped leaves are slow to decompose and may collect in mounds beneath trees. Mature tree produce green-skinned, fleshy fruit that may be pear-shaped, egg-shaped, or spherical. Mostly, the fruits ripen after harvesting.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as avocado farmer.</div><div class="i1">Mango (Maembe)<br />Mango is a deep rooted, tropical tree with several branches. Young leaves are pinkish, turning to dark green as they mature. A mature tree produces fruits that may be round, oval, or kidney-shaped. Ripe fruits have a distinctive sweet smell and have a single, large seed protected by a tough casing.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as mango farmer.</div><div class="i1">Khat (Miraa)<br />Khat is a slow-growing evergreen shrub, which is cultivated as a bush or small tree. The leaves are dark pink, and usually plucked for chewing. The plant is seedless and hardy, growing mainly in warm climatic conditions. The leaves of khat are chewed by the people for its stimulant action. In Kenya, miraa is mainly grown in Meru, Embu and parts of Tharaka Nithi Counties.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as Khat/miraa farmer.</div><p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether the household's agricultural holding includes coffee as a permanent crop. 1 Yes, compact plantation 2 Yes, scattered crops 3 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Agricultural holding includes avocado as a permanent crop <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-23. Does the holding have any of the following permanent crops within this county?</p> <div class="i1">Avocado</div><div class="i2">[] 1. Yes, compact plantation<br />[] 2. Yes, scattered plants<br />[] 3. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.6. Column H23: Permanent crops on the holding <br />Ask, "does the holding have any of the following permanent crops in this county?"</p> <p>The question is whether permanent crops are present on the holding during the reference period. Permanent crops include those crops produced from plants that stay in the holding for several years once planted, rather than being planted every season, or replanted after each harvest. For such crops, the trees or bushes take a number of years before the first harvest. Examples of such crops are tea, coffee, avocado, citrus, mango, coconut, macadamia, cashew nut and khat (miraa).</p> <p>Permanent crops can be grown either in compact plantations, or in form of scattered trees depending on the interest. A compact plantation includes plants, trees and shrubs planted in a regular and systematic manner. However, scattered plants are those planted in such a manner that they are scattered within or around the holding.</p> <p>For purposes of this census, plantations of trees such as bamboo, eucalyptus, or any other cultivated non-food tree crops will not be considered as permanent crops.</p> <div class="i1">Tea (Majani Chai)<br />An evergreen shrub or small tree, usually grown in compact plantation, whose leaves and leaf buds (last 3 young leaves) are plucked and processed in factories in order to produce tea. In Kenya, tea is grown in cool, wet places. In recent times, some farmers have started planting of purple tea (with purple leaves).<br />Farmer with less than 50 productive bushes, whether compact or scattered, should not be considered as tea farmer.</div><div class="i1">Coffee (Kahawa)<br />Is a small perennial tree or shrub with woody stem that has several branches. Mature crop produces seeds, called coffee beans, which are greenish when immature but turn into reddish cherry as they ripen. The cherry are harvested and processed to make various coffee beverages.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as coffee farmer.</div><div class="i1">Coconut (Nazi)<br />Is a large palm tree, with large umbrella-like leaves, usually grown as scattered trees. For mature crops, the old leaves break away, leaving smooth strong stem or trunk. A mature tree produces a fruit with a hard outer cover and whitish flesh that can be eaten raw or dried into powder. Immature, greenish fruit has liquid that can be used as human drink. In Kenya, coconut is mainly grown in warm, low altitude, coastal regions.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as coconut farmer.</div><div class="i1">Cashew Nut (Korosho)<br />The cashew tree is large and evergreen, with a short stem, often with several branches when mature. A mature tree produces several flowers forming into an oval or pear-shaped yellowish fruit. When dry, the fruit turns into a hard shell with single kidney shaped nut. The nut is extracted carefully either through roasting or shelling.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as cashew nut farmer.</div><div class="i1">Macadamia<br />Macadamia is an evergreen tree, with large, dark-green leaves. A mature tree forms a greenish fruit that contains a hard, brownish shell. When the shell is cracked, a dark brown spherical shaped nut is found.<br /><br />Farmer with less than 3 productive trees, whether compact or scattered, should not be considered as macadamia farmer.</div><div class="i1">Citrus<br />These are large shrubs or small to moderate-sized trees, with evergreen, shiny leaves that are often very strongly scented. The term citrus refers to a group of crops including oranges, lemons, tangerines and limes. A mature tree produces green to orange colored fruits with juice that usually contains a high quantity of citric acid giving them their characteristic sharp flavour.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as citrus farmer.</div><div class="i1">Avocado (Parachichi)<br />The avocado is a dense, evergreen tree, shedding many leaves during dry periods. The leaves are dark green and dropped leaves are slow to decompose and may collect in mounds beneath trees. Mature tree produce green-skinned, fleshy fruit that may be pear-shaped, egg-shaped, or spherical. Mostly, the fruits ripen after harvesting.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as avocado farmer.</div><div class="i1">Mango (Maembe)<br />Mango is a deep rooted, tropical tree with several branches. Young leaves are pinkish, turning to dark green as they mature. A mature tree produces fruits that may be round, oval, or kidney-shaped. Ripe fruits have a distinctive sweet smell and have a single, large seed protected by a tough casing.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as mango farmer.</div><div class="i1">Khat (Miraa)<br />Khat is a slow-growing evergreen shrub, which is cultivated as a bush or small tree. The leaves are dark pink, and usually plucked for chewing. The plant is seedless and hardy, growing mainly in warm climatic conditions. The leaves of khat are chewed by the people for its stimulant action. In Kenya, miraa is mainly grown in Meru, Embu and parts of Tharaka Nithi Counties.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as Khat/miraa farmer.</div><p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether the household's agricultural holding includes avocado as a permanent crop. 1 Yes, compact plantation 2 Yes, scattered crops 3 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Agricultural holding includes citrus as a permanent crop <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-23. Does the holding have any of the following permanent crops within this county?</p> <div class="i1">Citrus</div><div class="i2">[] 1. Yes, compact plantation<br />[] 2. Yes, scattered plants<br />[] 3. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.6. Column H23: Permanent crops on the holding <br />Ask, "does the holding have any of the following permanent crops in this county?"</p> <p>The question is whether permanent crops are present on the holding during the reference period. Permanent crops include those crops produced from plants that stay in the holding for several years once planted, rather than being planted every season, or replanted after each harvest. For such crops, the trees or bushes take a number of years before the first harvest. Examples of such crops are tea, coffee, avocado, citrus, mango, coconut, macadamia, cashew nut and khat (miraa).</p> <p>Permanent crops can be grown either in compact plantations, or in form of scattered trees depending on the interest. A compact plantation includes plants, trees and shrubs planted in a regular and systematic manner. However, scattered plants are those planted in such a manner that they are scattered within or around the holding.</p> <p>For purposes of this census, plantations of trees such as bamboo, eucalyptus, or any other cultivated non-food tree crops will not be considered as permanent crops.</p> <div class="i1">Tea (Majani Chai)<br />An evergreen shrub or small tree, usually grown in compact plantation, whose leaves and leaf buds (last 3 young leaves) are plucked and processed in factories in order to produce tea. In Kenya, tea is grown in cool, wet places. In recent times, some farmers have started planting of purple tea (with purple leaves).<br />Farmer with less than 50 productive bushes, whether compact or scattered, should not be considered as tea farmer.</div><div class="i1">Coffee (Kahawa)<br />Is a small perennial tree or shrub with woody stem that has several branches. Mature crop produces seeds, called coffee beans, which are greenish when immature but turn into reddish cherry as they ripen. The cherry are harvested and processed to make various coffee beverages.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as coffee farmer.</div><div class="i1">Coconut (Nazi)<br />Is a large palm tree, with large umbrella-like leaves, usually grown as scattered trees. For mature crops, the old leaves break away, leaving smooth strong stem or trunk. A mature tree produces a fruit with a hard outer cover and whitish flesh that can be eaten raw or dried into powder. Immature, greenish fruit has liquid that can be used as human drink. In Kenya, coconut is mainly grown in warm, low altitude, coastal regions.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as coconut farmer.</div><div class="i1">Cashew Nut (Korosho)<br />The cashew tree is large and evergreen, with a short stem, often with several branches when mature. A mature tree produces several flowers forming into an oval or pear-shaped yellowish fruit. When dry, the fruit turns into a hard shell with single kidney shaped nut. The nut is extracted carefully either through roasting or shelling.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as cashew nut farmer.</div><div class="i1">Macadamia<br />Macadamia is an evergreen tree, with large, dark-green leaves. A mature tree forms a greenish fruit that contains a hard, brownish shell. When the shell is cracked, a dark brown spherical shaped nut is found.<br /><br />Farmer with less than 3 productive trees, whether compact or scattered, should not be considered as macadamia farmer.</div><div class="i1">Citrus<br />These are large shrubs or small to moderate-sized trees, with evergreen, shiny leaves that are often very strongly scented. The term citrus refers to a group of crops including oranges, lemons, tangerines and limes. A mature tree produces green to orange colored fruits with juice that usually contains a high quantity of citric acid giving them their characteristic sharp flavour.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as citrus farmer.</div><div class="i1">Avocado (Parachichi)<br />The avocado is a dense, evergreen tree, shedding many leaves during dry periods. The leaves are dark green and dropped leaves are slow to decompose and may collect in mounds beneath trees. Mature tree produce green-skinned, fleshy fruit that may be pear-shaped, egg-shaped, or spherical. Mostly, the fruits ripen after harvesting.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as avocado farmer.</div><div class="i1">Mango (Maembe)<br />Mango is a deep rooted, tropical tree with several branches. Young leaves are pinkish, turning to dark green as they mature. A mature tree produces fruits that may be round, oval, or kidney-shaped. Ripe fruits have a distinctive sweet smell and have a single, large seed protected by a tough casing.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as mango farmer.</div><div class="i1">Khat (Miraa)<br />Khat is a slow-growing evergreen shrub, which is cultivated as a bush or small tree. The leaves are dark pink, and usually plucked for chewing. The plant is seedless and hardy, growing mainly in warm climatic conditions. The leaves of khat are chewed by the people for its stimulant action. In Kenya, miraa is mainly grown in Meru, Embu and parts of Tharaka Nithi Counties.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as Khat/miraa farmer.</div><p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether the household's agricultural holding includes citrus as a permanent crop. 1 Yes, compact plantation 2 Yes, scattered crops 3 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Agricultural holding includes mango as a permanent crop <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-23. Does the holding have any of the following permanent crops within this county?</p> <div class="i1">Mango</div><div class="i2">[] 1. Yes, compact plantation<br />[] 2. Yes, scattered plants<br />[] 3. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.6. Column H23: Permanent crops on the holding <br />Ask, "does the holding have any of the following permanent crops in this county?"</p> <p>The question is whether permanent crops are present on the holding during the reference period. Permanent crops include those crops produced from plants that stay in the holding for several years once planted, rather than being planted every season, or replanted after each harvest. For such crops, the trees or bushes take a number of years before the first harvest. Examples of such crops are tea, coffee, avocado, citrus, mango, coconut, macadamia, cashew nut and khat (miraa).</p> <p>Permanent crops can be grown either in compact plantations, or in form of scattered trees depending on the interest. A compact plantation includes plants, trees and shrubs planted in a regular and systematic manner. However, scattered plants are those planted in such a manner that they are scattered within or around the holding.</p> <p>For purposes of this census, plantations of trees such as bamboo, eucalyptus, or any other cultivated non-food tree crops will not be considered as permanent crops.</p> <div class="i1">Tea (Majani Chai)<br />An evergreen shrub or small tree, usually grown in compact plantation, whose leaves and leaf buds (last 3 young leaves) are plucked and processed in factories in order to produce tea. In Kenya, tea is grown in cool, wet places. In recent times, some farmers have started planting of purple tea (with purple leaves).<br />Farmer with less than 50 productive bushes, whether compact or scattered, should not be considered as tea farmer.</div><div class="i1">Coffee (Kahawa)<br />Is a small perennial tree or shrub with woody stem that has several branches. Mature crop produces seeds, called coffee beans, which are greenish when immature but turn into reddish cherry as they ripen. The cherry are harvested and processed to make various coffee beverages.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as coffee farmer.</div><div class="i1">Coconut (Nazi)<br />Is a large palm tree, with large umbrella-like leaves, usually grown as scattered trees. For mature crops, the old leaves break away, leaving smooth strong stem or trunk. A mature tree produces a fruit with a hard outer cover and whitish flesh that can be eaten raw or dried into powder. Immature, greenish fruit has liquid that can be used as human drink. In Kenya, coconut is mainly grown in warm, low altitude, coastal regions.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as coconut farmer.</div><div class="i1">Cashew Nut (Korosho)<br />The cashew tree is large and evergreen, with a short stem, often with several branches when mature. A mature tree produces several flowers forming into an oval or pear-shaped yellowish fruit. When dry, the fruit turns into a hard shell with single kidney shaped nut. The nut is extracted carefully either through roasting or shelling.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as cashew nut farmer.</div><div class="i1">Macadamia<br />Macadamia is an evergreen tree, with large, dark-green leaves. A mature tree forms a greenish fruit that contains a hard, brownish shell. When the shell is cracked, a dark brown spherical shaped nut is found.<br /><br />Farmer with less than 3 productive trees, whether compact or scattered, should not be considered as macadamia farmer.</div><div class="i1">Citrus<br />These are large shrubs or small to moderate-sized trees, with evergreen, shiny leaves that are often very strongly scented. The term citrus refers to a group of crops including oranges, lemons, tangerines and limes. A mature tree produces green to orange colored fruits with juice that usually contains a high quantity of citric acid giving them their characteristic sharp flavour.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as citrus farmer.</div><div class="i1">Avocado (Parachichi)<br />The avocado is a dense, evergreen tree, shedding many leaves during dry periods. The leaves are dark green and dropped leaves are slow to decompose and may collect in mounds beneath trees. Mature tree produce green-skinned, fleshy fruit that may be pear-shaped, egg-shaped, or spherical. Mostly, the fruits ripen after harvesting.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as avocado farmer.</div><div class="i1">Mango (Maembe)<br />Mango is a deep rooted, tropical tree with several branches. Young leaves are pinkish, turning to dark green as they mature. A mature tree produces fruits that may be round, oval, or kidney-shaped. Ripe fruits have a distinctive sweet smell and have a single, large seed protected by a tough casing.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as mango farmer.</div><div class="i1">Khat (Miraa)<br />Khat is a slow-growing evergreen shrub, which is cultivated as a bush or small tree. The leaves are dark pink, and usually plucked for chewing. The plant is seedless and hardy, growing mainly in warm climatic conditions. The leaves of khat are chewed by the people for its stimulant action. In Kenya, miraa is mainly grown in Meru, Embu and parts of Tharaka Nithi Counties.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as Khat/miraa farmer.</div><p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether the household's agricultural holding includes mango as a permanent crop. 1 Yes, compact plantation 2 Yes, scattered crops 3 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Agricultural holding includes coconut as a permanent crop <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-23. Does the holding have any of the following permanent crops within this county?</p> <div class="i1">Coconut</div><div class="i2">[] 1. Yes, compact plantation<br />[] 2. Yes, scattered plants<br />[] 3. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.6. Column H23: Permanent crops on the holding <br />Ask, "does the holding have any of the following permanent crops in this county?"</p> <p>The question is whether permanent crops are present on the holding during the reference period. Permanent crops include those crops produced from plants that stay in the holding for several years once planted, rather than being planted every season, or replanted after each harvest. For such crops, the trees or bushes take a number of years before the first harvest. Examples of such crops are tea, coffee, avocado, citrus, mango, coconut, macadamia, cashew nut and khat (miraa).</p> <p>Permanent crops can be grown either in compact plantations, or in form of scattered trees depending on the interest. A compact plantation includes plants, trees and shrubs planted in a regular and systematic manner. However, scattered plants are those planted in such a manner that they are scattered within or around the holding.</p> <p>For purposes of this census, plantations of trees such as bamboo, eucalyptus, or any other cultivated non-food tree crops will not be considered as permanent crops.</p> <div class="i1">Tea (Majani Chai)<br />An evergreen shrub or small tree, usually grown in compact plantation, whose leaves and leaf buds (last 3 young leaves) are plucked and processed in factories in order to produce tea. In Kenya, tea is grown in cool, wet places. In recent times, some farmers have started planting of purple tea (with purple leaves).<br />Farmer with less than 50 productive bushes, whether compact or scattered, should not be considered as tea farmer.</div><div class="i1">Coffee (Kahawa)<br />Is a small perennial tree or shrub with woody stem that has several branches. Mature crop produces seeds, called coffee beans, which are greenish when immature but turn into reddish cherry as they ripen. The cherry are harvested and processed to make various coffee beverages.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as coffee farmer.</div><div class="i1">Coconut (Nazi)<br />Is a large palm tree, with large umbrella-like leaves, usually grown as scattered trees. For mature crops, the old leaves break away, leaving smooth strong stem or trunk. A mature tree produces a fruit with a hard outer cover and whitish flesh that can be eaten raw or dried into powder. Immature, greenish fruit has liquid that can be used as human drink. In Kenya, coconut is mainly grown in warm, low altitude, coastal regions.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as coconut farmer.</div><div class="i1">Cashew Nut (Korosho)<br />The cashew tree is large and evergreen, with a short stem, often with several branches when mature. A mature tree produces several flowers forming into an oval or pear-shaped yellowish fruit. When dry, the fruit turns into a hard shell with single kidney shaped nut. The nut is extracted carefully either through roasting or shelling.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as cashew nut farmer.</div><div class="i1">Macadamia<br />Macadamia is an evergreen tree, with large, dark-green leaves. A mature tree forms a greenish fruit that contains a hard, brownish shell. When the shell is cracked, a dark brown spherical shaped nut is found.<br /><br />Farmer with less than 3 productive trees, whether compact or scattered, should not be considered as macadamia farmer.</div><div class="i1">Citrus<br />These are large shrubs or small to moderate-sized trees, with evergreen, shiny leaves that are often very strongly scented. The term citrus refers to a group of crops including oranges, lemons, tangerines and limes. A mature tree produces green to orange colored fruits with juice that usually contains a high quantity of citric acid giving them their characteristic sharp flavour.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as citrus farmer.</div><div class="i1">Avocado (Parachichi)<br />The avocado is a dense, evergreen tree, shedding many leaves during dry periods. The leaves are dark green and dropped leaves are slow to decompose and may collect in mounds beneath trees. Mature tree produce green-skinned, fleshy fruit that may be pear-shaped, egg-shaped, or spherical. Mostly, the fruits ripen after harvesting.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as avocado farmer.</div><div class="i1">Mango (Maembe)<br />Mango is a deep rooted, tropical tree with several branches. Young leaves are pinkish, turning to dark green as they mature. A mature tree produces fruits that may be round, oval, or kidney-shaped. Ripe fruits have a distinctive sweet smell and have a single, large seed protected by a tough casing.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as mango farmer.</div><div class="i1">Khat (Miraa)<br />Khat is a slow-growing evergreen shrub, which is cultivated as a bush or small tree. The leaves are dark pink, and usually plucked for chewing. The plant is seedless and hardy, growing mainly in warm climatic conditions. The leaves of khat are chewed by the people for its stimulant action. In Kenya, miraa is mainly grown in Meru, Embu and parts of Tharaka Nithi Counties.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as Khat/miraa farmer.</div><p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether the household's agricultural holding includes coconut as a permanent crop. 1 Yes, compact plantation 2 Yes, scattered crops 3 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Agricultural holding includes macadamia as a permanent crop <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-23. Does the holding have any of the following permanent crops within this county?</p> <div class="i1">Macadamia</div><div class="i2">[] 1. Yes, compact plantation<br />[] 2. Yes, scattered plants<br />[] 3. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.6. Column H23: Permanent crops on the holding <br />Ask, "does the holding have any of the following permanent crops in this county?"</p> <p>The question is whether permanent crops are present on the holding during the reference period. Permanent crops include those crops produced from plants that stay in the holding for several years once planted, rather than being planted every season, or replanted after each harvest. For such crops, the trees or bushes take a number of years before the first harvest. Examples of such crops are tea, coffee, avocado, citrus, mango, coconut, macadamia, cashew nut and khat (miraa).</p> <p>Permanent crops can be grown either in compact plantations, or in form of scattered trees depending on the interest. A compact plantation includes plants, trees and shrubs planted in a regular and systematic manner. However, scattered plants are those planted in such a manner that they are scattered within or around the holding.</p> <p>For purposes of this census, plantations of trees such as bamboo, eucalyptus, or any other cultivated non-food tree crops will not be considered as permanent crops.</p> <div class="i1">Tea (Majani Chai)<br />An evergreen shrub or small tree, usually grown in compact plantation, whose leaves and leaf buds (last 3 young leaves) are plucked and processed in factories in order to produce tea. In Kenya, tea is grown in cool, wet places. In recent times, some farmers have started planting of purple tea (with purple leaves).<br />Farmer with less than 50 productive bushes, whether compact or scattered, should not be considered as tea farmer.</div><div class="i1">Coffee (Kahawa)<br />Is a small perennial tree or shrub with woody stem that has several branches. Mature crop produces seeds, called coffee beans, which are greenish when immature but turn into reddish cherry as they ripen. The cherry are harvested and processed to make various coffee beverages.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as coffee farmer.</div><div class="i1">Coconut (Nazi)<br />Is a large palm tree, with large umbrella-like leaves, usually grown as scattered trees. For mature crops, the old leaves break away, leaving smooth strong stem or trunk. A mature tree produces a fruit with a hard outer cover and whitish flesh that can be eaten raw or dried into powder. Immature, greenish fruit has liquid that can be used as human drink. In Kenya, coconut is mainly grown in warm, low altitude, coastal regions.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as coconut farmer.</div><div class="i1">Cashew Nut (Korosho)<br />The cashew tree is large and evergreen, with a short stem, often with several branches when mature. A mature tree produces several flowers forming into an oval or pear-shaped yellowish fruit. When dry, the fruit turns into a hard shell with single kidney shaped nut. The nut is extracted carefully either through roasting or shelling.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as cashew nut farmer.</div><div class="i1">Macadamia<br />Macadamia is an evergreen tree, with large, dark-green leaves. A mature tree forms a greenish fruit that contains a hard, brownish shell. When the shell is cracked, a dark brown spherical shaped nut is found.<br /><br />Farmer with less than 3 productive trees, whether compact or scattered, should not be considered as macadamia farmer.</div><div class="i1">Citrus<br />These are large shrubs or small to moderate-sized trees, with evergreen, shiny leaves that are often very strongly scented. The term citrus refers to a group of crops including oranges, lemons, tangerines and limes. A mature tree produces green to orange colored fruits with juice that usually contains a high quantity of citric acid giving them their characteristic sharp flavour.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as citrus farmer.</div><div class="i1">Avocado (Parachichi)<br />The avocado is a dense, evergreen tree, shedding many leaves during dry periods. The leaves are dark green and dropped leaves are slow to decompose and may collect in mounds beneath trees. Mature tree produce green-skinned, fleshy fruit that may be pear-shaped, egg-shaped, or spherical. Mostly, the fruits ripen after harvesting.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as avocado farmer.</div><div class="i1">Mango (Maembe)<br />Mango is a deep rooted, tropical tree with several branches. Young leaves are pinkish, turning to dark green as they mature. A mature tree produces fruits that may be round, oval, or kidney-shaped. Ripe fruits have a distinctive sweet smell and have a single, large seed protected by a tough casing.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as mango farmer.</div><div class="i1">Khat (Miraa)<br />Khat is a slow-growing evergreen shrub, which is cultivated as a bush or small tree. The leaves are dark pink, and usually plucked for chewing. The plant is seedless and hardy, growing mainly in warm climatic conditions. The leaves of khat are chewed by the people for its stimulant action. In Kenya, miraa is mainly grown in Meru, Embu and parts of Tharaka Nithi Counties.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as Khat/miraa farmer.</div><p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether the household's agricultural holding includes macadamia as a permanent crop. 1 Yes, compact plantation 2 Yes, scattered crops 3 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Agricultural holding includes cashew nut as a permanent crop <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-23. Does the holding have any of the following permanent crops within this county?</p> <div class="i1">Cashew nut</div><div class="i2">[] 1. Yes, compact plantation<br />[] 2. Yes, scattered plants<br />[] 3. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.6. Column H23: Permanent crops on the holding <br />Ask, "does the holding have any of the following permanent crops in this county?"</p> <p>The question is whether permanent crops are present on the holding during the reference period. Permanent crops include those crops produced from plants that stay in the holding for several years once planted, rather than being planted every season, or replanted after each harvest. For such crops, the trees or bushes take a number of years before the first harvest. Examples of such crops are tea, coffee, avocado, citrus, mango, coconut, macadamia, cashew nut and khat (miraa).</p> <p>Permanent crops can be grown either in compact plantations, or in form of scattered trees depending on the interest. A compact plantation includes plants, trees and shrubs planted in a regular and systematic manner. However, scattered plants are those planted in such a manner that they are scattered within or around the holding.</p> <p>For purposes of this census, plantations of trees such as bamboo, eucalyptus, or any other cultivated non-food tree crops will not be considered as permanent crops.</p> <div class="i1">Tea (Majani Chai)<br />An evergreen shrub or small tree, usually grown in compact plantation, whose leaves and leaf buds (last 3 young leaves) are plucked and processed in factories in order to produce tea. In Kenya, tea is grown in cool, wet places. In recent times, some farmers have started planting of purple tea (with purple leaves).<br />Farmer with less than 50 productive bushes, whether compact or scattered, should not be considered as tea farmer.</div><div class="i1">Coffee (Kahawa)<br />Is a small perennial tree or shrub with woody stem that has several branches. Mature crop produces seeds, called coffee beans, which are greenish when immature but turn into reddish cherry as they ripen. The cherry are harvested and processed to make various coffee beverages.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as coffee farmer.</div><div class="i1">Coconut (Nazi)<br />Is a large palm tree, with large umbrella-like leaves, usually grown as scattered trees. For mature crops, the old leaves break away, leaving smooth strong stem or trunk. A mature tree produces a fruit with a hard outer cover and whitish flesh that can be eaten raw or dried into powder. Immature, greenish fruit has liquid that can be used as human drink. In Kenya, coconut is mainly grown in warm, low altitude, coastal regions.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as coconut farmer.</div><div class="i1">Cashew Nut (Korosho)<br />The cashew tree is large and evergreen, with a short stem, often with several branches when mature. A mature tree produces several flowers forming into an oval or pear-shaped yellowish fruit. When dry, the fruit turns into a hard shell with single kidney shaped nut. The nut is extracted carefully either through roasting or shelling.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as cashew nut farmer.</div><div class="i1">Macadamia<br />Macadamia is an evergreen tree, with large, dark-green leaves. A mature tree forms a greenish fruit that contains a hard, brownish shell. When the shell is cracked, a dark brown spherical shaped nut is found.<br /><br />Farmer with less than 3 productive trees, whether compact or scattered, should not be considered as macadamia farmer.</div><div class="i1">Citrus<br />These are large shrubs or small to moderate-sized trees, with evergreen, shiny leaves that are often very strongly scented. The term citrus refers to a group of crops including oranges, lemons, tangerines and limes. A mature tree produces green to orange colored fruits with juice that usually contains a high quantity of citric acid giving them their characteristic sharp flavour.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as citrus farmer.</div><div class="i1">Avocado (Parachichi)<br />The avocado is a dense, evergreen tree, shedding many leaves during dry periods. The leaves are dark green and dropped leaves are slow to decompose and may collect in mounds beneath trees. Mature tree produce green-skinned, fleshy fruit that may be pear-shaped, egg-shaped, or spherical. Mostly, the fruits ripen after harvesting.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as avocado farmer.</div><div class="i1">Mango (Maembe)<br />Mango is a deep rooted, tropical tree with several branches. Young leaves are pinkish, turning to dark green as they mature. A mature tree produces fruits that may be round, oval, or kidney-shaped. Ripe fruits have a distinctive sweet smell and have a single, large seed protected by a tough casing.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as mango farmer.</div><div class="i1">Khat (Miraa)<br />Khat is a slow-growing evergreen shrub, which is cultivated as a bush or small tree. The leaves are dark pink, and usually plucked for chewing. The plant is seedless and hardy, growing mainly in warm climatic conditions. The leaves of khat are chewed by the people for its stimulant action. In Kenya, miraa is mainly grown in Meru, Embu and parts of Tharaka Nithi Counties.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as Khat/miraa farmer.</div><p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether the household's agricultural holding includes cashew nut as a permanent crop. 1 Yes, compact plantation 2 Yes, scattered crops 3 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Agricultural holding includes khat (miraa) as a permanent crop <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-23. Does the holding have any of the following permanent crops within this county?</p> <div class="i1">Khat miraa</div><div class="i2">[] 1. Yes, compact plantation<br />[] 2. Yes, scattered plants<br />[] 3. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>27.6. Column H23: Permanent crops on the holding <br />Ask, "does the holding have any of the following permanent crops in this county?"</p> <p>The question is whether permanent crops are present on the holding during the reference period. Permanent crops include those crops produced from plants that stay in the holding for several years once planted, rather than being planted every season, or replanted after each harvest. For such crops, the trees or bushes take a number of years before the first harvest. Examples of such crops are tea, coffee, avocado, citrus, mango, coconut, macadamia, cashew nut and khat (miraa).</p> <p>Permanent crops can be grown either in compact plantations, or in form of scattered trees depending on the interest. A compact plantation includes plants, trees and shrubs planted in a regular and systematic manner. However, scattered plants are those planted in such a manner that they are scattered within or around the holding.</p> <p>For purposes of this census, plantations of trees such as bamboo, eucalyptus, or any other cultivated non-food tree crops will not be considered as permanent crops.</p> <div class="i1">Tea (Majani Chai)<br />An evergreen shrub or small tree, usually grown in compact plantation, whose leaves and leaf buds (last 3 young leaves) are plucked and processed in factories in order to produce tea. In Kenya, tea is grown in cool, wet places. In recent times, some farmers have started planting of purple tea (with purple leaves).<br />Farmer with less than 50 productive bushes, whether compact or scattered, should not be considered as tea farmer.</div><div class="i1">Coffee (Kahawa)<br />Is a small perennial tree or shrub with woody stem that has several branches. Mature crop produces seeds, called coffee beans, which are greenish when immature but turn into reddish cherry as they ripen. The cherry are harvested and processed to make various coffee beverages.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as coffee farmer.</div><div class="i1">Coconut (Nazi)<br />Is a large palm tree, with large umbrella-like leaves, usually grown as scattered trees. For mature crops, the old leaves break away, leaving smooth strong stem or trunk. A mature tree produces a fruit with a hard outer cover and whitish flesh that can be eaten raw or dried into powder. Immature, greenish fruit has liquid that can be used as human drink. In Kenya, coconut is mainly grown in warm, low altitude, coastal regions.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as coconut farmer.</div><div class="i1">Cashew Nut (Korosho)<br />The cashew tree is large and evergreen, with a short stem, often with several branches when mature. A mature tree produces several flowers forming into an oval or pear-shaped yellowish fruit. When dry, the fruit turns into a hard shell with single kidney shaped nut. The nut is extracted carefully either through roasting or shelling.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as cashew nut farmer.</div><div class="i1">Macadamia<br />Macadamia is an evergreen tree, with large, dark-green leaves. A mature tree forms a greenish fruit that contains a hard, brownish shell. When the shell is cracked, a dark brown spherical shaped nut is found.<br /><br />Farmer with less than 3 productive trees, whether compact or scattered, should not be considered as macadamia farmer.</div><div class="i1">Citrus<br />These are large shrubs or small to moderate-sized trees, with evergreen, shiny leaves that are often very strongly scented. The term citrus refers to a group of crops including oranges, lemons, tangerines and limes. A mature tree produces green to orange colored fruits with juice that usually contains a high quantity of citric acid giving them their characteristic sharp flavour.<br /><br />Farmer with less than 10 productive trees, whether compact or scattered, should not be considered as citrus farmer.</div><div class="i1">Avocado (Parachichi)<br />The avocado is a dense, evergreen tree, shedding many leaves during dry periods. The leaves are dark green and dropped leaves are slow to decompose and may collect in mounds beneath trees. Mature tree produce green-skinned, fleshy fruit that may be pear-shaped, egg-shaped, or spherical. Mostly, the fruits ripen after harvesting.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as avocado farmer.</div><div class="i1">Mango (Maembe)<br />Mango is a deep rooted, tropical tree with several branches. Young leaves are pinkish, turning to dark green as they mature. A mature tree produces fruits that may be round, oval, or kidney-shaped. Ripe fruits have a distinctive sweet smell and have a single, large seed protected by a tough casing.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as mango farmer.</div><div class="i1">Khat (Miraa)<br />Khat is a slow-growing evergreen shrub, which is cultivated as a bush or small tree. The leaves are dark pink, and usually plucked for chewing. The plant is seedless and hardy, growing mainly in warm climatic conditions. The leaves of khat are chewed by the people for its stimulant action. In Kenya, miraa is mainly grown in Meru, Embu and parts of Tharaka Nithi Counties.<br /><br />Farmer with less than 5 productive trees, whether compact or scattered, should not be considered as Khat/miraa farmer.</div><p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether the household's agricultural holding includes khat (miraa) as a permanent crop. 1 Yes, compact plantation 2 Yes, scattered crops 3 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated maize in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Maize</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Maize <br />Maize, or corn, is a tall, cereal crop grown mainly for the maize grains. In some cases, however, maize is grown for livestock feeding as well as snack (baby corn) in the horticulture industry. In Kenya, maize is the most widely grown staple food. Maize varieties differ widely, with traditional varieties having a wide range of grain colors while most hybrid varieties have white to light brown/yellowish color. Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated maize in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated sorghum in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Sorghum</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Sorghum <br />Sorghum is a short-period, tall cereal crop grown mainly for sorghum seed. The seeds can be red, brown, white or other colours. In Kenya, sorghum is a versatile crop that grows widely in the regions with low rainfall and other marginal zones.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated sorghum in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated rice in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Rice</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Rice <br />Rice is a grass-like, short-period cereal crop grown mainly for production of rice grains used for human consumption and other uses. In Kenya, most rice are grown as paddy fields in major irrigation schemes. In recent times, a few highland rice varieties that do not rely on irrigated fields have been introduced in some counties.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated rice in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated potatoes in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Potatoes</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Potatoes <br />Potato, also known as Irish Potatoes, is a short, leafy crop with starchy tubers used for human consumption. In Kenya, potato is mainly grown in the cool to cold, high altitude regions. Most common varieties have pink or white skinned tubers.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated potatoes in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated beans in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Beans</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Beans <br />Beans (Dry or field Beans) is a short-period, leafy shrub grown mainly for production of beans seeds, which are consumed as source of protein. In the field, most of the beans grow as short, leafy shrubs, though a few varieties are climbing beans. There are four broad categories of beans in Kenya, namely dry beans, french beans, soya beans and dolicos (lablab) or njahi beans. This question targets only dry beans shown in the photo below.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated beans in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated sugarcane in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Sugarcane</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Sugarcane (Miwa) <br />Sugarcane is a tropical, perennial plant of grass family with long sword-shaped leaves. Mature crops produce multiple stems, or cane stalks. The stalks are composed of many segments, and has sugary, sweet liquid that is usually processed to produce sugar. The green leaves may also be used as animal feeds. In Kenya, sugarcane is grown either for factory processing or for chewing. It is important to note that the interest here will be cane grown mainly for factory to produce sugar.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated sugarcane in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated cassava in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Cassava</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Cassava (Muhogo) <br />Cassava plant is a perennial woody shrub that grows to about 2-3 metres in height. The leaves are palmate (like open hand-shaped) and dark green in colour. A mature crop has long roots that grow into dark-brown, starchy tubers with rough skin. Cassava is generally considered as one of the most drought tolerant crop. The root has a brown fibrous skin and snowy white interior flesh. The leaves of some varieties are used as a vegetable. The crop is mainly grown in warm places in the Coast, Eastern, Western and Nyanza regions.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated cassava in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated sweet potatoes in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Sweet potatoes</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Sweet potatoes (Viazi tamu) <br />Sweet potato is a short, ground covering branching plant with trailing long stems which are usually referred to as vines. The leaves are evergreen, soft, smooth, and shiny. A mature crop has long roots that develop into long and tapered tubers, with a smooth skin and flesh whose colour ranges between cream, yellow, orange, red, brown and purple. The flesh has a starchy, sweet taste. In Kenya, the crop is grown in most parts of the country.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated sweet potatoes in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated wheat in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Wheat</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated wheat in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated green grams in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Green grams</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Green Grams (Ndengu) <br />Short, annual crop grown in warm places. A mature plant forms pencil sized pods with edible grains. Most grains are greenish in color but some varieties have brown/yellowish grains.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated green grams in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated bananas in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Bananas</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Banana (Ndizi) <br />A banana plant is a large tropical plant with large, wide, evergreen leaves. The original plant usually produces several tillers, unless pruned. The trunk or stem is soft and watery. A mature crop produces a large sized head with several green fruits that often turn yellowish as the fruit matures. The fruits which are called bananas can be eaten ripe as dessert or cooked depending on the variety.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated bananas in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated cabbages in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Cabbages</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Cabbages (Kabeji) <br />Cabbage is a short annual crop with thick leaves that may be pale green, whitish or pink in colour. The leaves tend to be thick. For mature crops, the leaves curl inwards to cover a round head that range from 0.5kg to 4 kilograms. Cabbage is prepared and consumed in many ways. The simplest ways include eating the vegetable raw or steaming or frying it. The vegetable is grown either under irrigation or in cool climates under rain-fed conditions.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated cabbages in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated tomatoes in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Tomatoes</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Tomato (Nyanya) <br />Short, annual/seasonal crop with several branches. A mature plant produces juicy fruits; immature fruits are greenish, while mature fruits turn cherry red.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated tomatoes in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated onions in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Onions</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Groundnuts (Njugu karanga) <br />The groundnut, also known as the peanut, is an annual crop grown mainly for its edible seeds. The seeds grow in the soil inside special pods. The pods are broken to give the edible seed. The crop is mainly grown in western Kenya, Nyanza, parts of Meru and Taita Taveta. The shelled nuts can either be deep brown or very light brown in colour. Major uses of groundnuts is roasted and eaten as a snack, ground into paste for stews or used for making of peanut butter and for oil extraction.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated onions in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated ground nuts in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Ground nuts</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Onions (Kitunguu) <br />The onion is most frequently a biennial plant, but is usually treated as an annual plant and harvested in its first growing season. The onion plant has hollow, bluish-green leaves that may grow up to one ruler length. For some varieties, the stem of a mature crop turns into a round-oval shaped bulb, usually found underground. Some varieties do not form round bulbs and are harvested as such. Both the leaves, stem and bulbs have strong, pungent smell that may irritate the eyes. In Kenya, four main varieties are grown, namely bulb onions, garlic, chives and leeks.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated ground nuts in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated millet in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Millet</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Millet (Mawele/Wimbi) <br />Millet is a short annual crop with several tillers (additional stems from the main stem) with small seeds. Millet belongs to the grass family and is mainly found in warm places. The seed is used as cereal or source of energy but also has other many nutrition values. Kenya grows two main types of millet, namely: (a) finger millet - short (about knee/waist height) grass like plant with several tillers and mature head appearing like open human fingers, grain is brownish, other varieties are black in colour; (b) pearl millet - slightly taller (human height) plant with larger stems and grows several tillers and greyish green in colour.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated millet in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated watermelons in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Watermelons</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated watermelons in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated kales in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Kales</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Cotton (Pamba) <br />Cotton plant is a short perennial shrub grown in warm regions. It is mainly grown for its fruits, known as "bolls". Once ripe, the bolls split to reveal whitish fibre known as cotton. The raw product is known as seed cotton, which is ginned to separate the fibre from the seeds. The fibre is spun to make yarn and woven to make fabric. The seeds provide oil and animal feed cakes.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated kales in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member cultivated cotton in this county in the last 12 months <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-24. During the last 12 months, did any member of this household cultivate any of the following crops in this county?</p> <div class="i1">Cotton</div><div class="i2">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.2. Column H19: Engaging in agricultural production</p> <p>Ask; "during the last 12 months, did any member of the household engage in crop farming, livestock rearing and/or aquaculture within this county?"</p> <div class="i1">1. Crop farming: yes/no<br />2. Livestock rearing: yes/no<br />3. Aquaculture: yes/no<br />9. DK:</div><p>The question seeks to establish if the household is a farming household that engaged in agricultural production in the last 12 months. Enter code appropriately depending on the response given. That is "yes", "no", or don't know". Agricultural production refers to a deliberate process of producing food, feed, fiber or other products that are ultimately consumed or sold as raw materials to make other secondary products. These activities include: planting and harvesting of crops; raising or rearing of livestock, as well as rearing of fish in ponds or cages. Note that growing of crops or rearing of livestock or fish for leisure, decoration or domestic pet should not be categorized as farming. Furthermore, caging and feeding of wild animals should not be categorized as farming. However, caging and feeding of fish, which are ultimately "harvested" and consumed or sold, should be treated as agriculture. For livestock, the farmer may be rearing any of the following: cattle, sheep, goats, pigs, horses, donkeys, camels, poultry, bees, silkworms, rabbits, other emerging livestock, etc. It is important to note that farming household is one engaged in agriculture on own account; that is, for direct self or household's gains. Hence, if head of household or any members of a household engaged in farming through employment by another household or establishment, that does not make the particular employed household to be a farming one!</p> <p>If the response is no to all (crop farming, livestock rearing and aquaculture) or "DK" skip to fishing (Column H25).</p> <p>Column H24: Cultivation of other crops <br />Ask, "during the last 12 months, did any member of this household cultivate the following crops in this county?"</p> <p>The question therefore seeks to establish the number of farming households in the country that grow the various crops and by location.</p> <p>Note that a farmer growing any of these crops under intensive cultivation (involving irrigation, greenhouse, hydroponics), or urban farming; where the value of what is produced contributes significantly to household food/nutrition or income, should be enumerated as farmer irrespective of farm size. However, for other normal farming, if the crop size is less than quarter of an acre, or the crop does not contribute significantly to household food or income, then the qualification of being a farmer does not apply for such crop.</p> <p>Cotton (Pamba) <br />Cotton plant is a short perennial shrub grown in warm regions. It is mainly grown for its fruits, known as "bolls". Once ripe, the bolls split to reveal whitish fibre known as cotton. The raw product is known as seed cotton, which is ginned to separate the fibre from the seeds. The fibre is spun to make yarn and woven to make fabric. The seeds provide oil and animal feed cakes.</p> <p>Enumerators are required to ask if the household or any member of the household is engaged in cultivation of any of the crops. Record appropriately as Yes, if cultivated, No, if not cultivated, or Don't Know if not aware. Note that it is highly discouraged to use the Don't Know option. Also note that the reference period is the last 12 months or crop/agriculture year.</p> <p>The enumerator is required to enquire and record appropriately, taking into account that the farmer (holder) knows what they grow in most cases since these are crops mainly grown for commercial purposes. Record "yes, in compact plantation", "yes, in scattered plants", "no", or "don't know". Kenya 2019: Households farming crops in current county last year [discrepancies: type I trace; type II none] This variable indicates whether a household member cultivated cotton in this county in the last 12 months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Household member is engaged in fishing activities in this county <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-25. Is there any member of this household who is engaged in fishing activities within this county?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> 27.8. Column H25: Fishing activities <br />Ask, "Is there any household member who is engaged in fishing activities in this county?" <br />Fishing comprises hunting, collecting and gathering activities directed at removing or collecting live wild aquatic organisms, (predominantly fish, molluscs and crustaceans). Mollusk are soft-bodied invertebrate such as starfish, or sometimes wholly or partly enclosed in a hard calcium carbonate shell, such snails, etc. Crustaceans are arthropods or insect-like water-living animals as crabs, lobsters, crayfish, shrimp, etc. usually with a hard skin of crust covering the body. In some cases, fishing may be extended to include collection of aquatic plants from the oceanic, coastal or inland waters. Fishing is usually carried out by various means such as use of fishing gear e.g. nets, lines, spearing or stationary traps. One or more members of a household may be involved in the fishing activity for livelihood and as a means of income, especially if they live near water bodies. <br />Note that:</p> <div class="i1">i. Engaging in fishing as pass-time activity is not to be considered as fishing activity for the household;<br />ii. Fishing from small streams for subsistence is not to be considered as fishing for the household though trout fishing activity supporting a household is to be considered as fishing; and<br />iii. If a member of the household is employed in an activity that deals with fish trading or processing, this does not qualify that household to be a fishing household.</div><p>Enumerator should indicate a "Yes" if any member of the household is involved in fishing, "No" if none is involved and DK if the respondent does not have the information. This may arise if the respondent is new in the household. Kenya 2019: Private households [discrepancies: type I none; type II trace] This variable indicates whether a household member is engaged in fishing activities in this county. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any exotic dairy cattle <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 4.0%; type II none] This variable indicates whether the household owns, rears, or manages any exotic dairy cattle. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of exotic dairy cattle owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing exotic dairy cattle in current county [discrepancies: type I none; type II trace] This variable indicates the household's number of exotic dairy cattle owned, reared, or managed. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 040 40 041 41 042 42 044 44 045 45 047 47 048 48 050 50+ 999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any exotic beef cattle <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 4.0%; type II none] This variable indicates whether the household owns, rears, or manages any exotic beef cattle. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of exotic beef cattle owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing beef cattle in current county [discrepancies: type I none; type II trace] This variable indicates the household's number of exotic beef cattle owned, reared, or managed. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 040 40 041 41 043 43 044 44 045 45 046 46 047 47 048 48 050 50+ 999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any indigenous cattle <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any indigenous cattle. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of indigenous cattle owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing indigenous cattle in current county [discrepancies: none] This variable indicates the household's number of indigenous cattle owned, reared, or managed. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 0100 100 0102 102 0103 103 0105 105 0106 106 0108 108 0109 109 0110 110 0111 111 0112 112 0113 113 0115 115 0116 116 0117 117 0120 120 0121 121 0122 122 0123 123 0124 124 0125 125 0126 126 0127 127 0128 128 0129 129 0130 130 0132 132 0133 133 0135 135 0136 136 0140 140 0142 142 0144 144 0145 145 0146 146 0147 147 0150 150 0152 152 0153 153 0154 154 0156 156 0158 158 0160 160 0162 162 0165 165 0170 170 0171 171 0172 172 0173 173 0175 175 0177 177 0178 178 0180 180 0182 182 0185 185 0188 188 0189 189 0193 193 0200 200 0201 201 0205 205 0207 207 0208 208 0210 210 0211 211 0214 214 0220 220 0222 222 0225 225 0230 230 0231 231 0232 232 0234 234 0235 235 0236 236 0240 240 0241 241 0243 243 0245 245 0250 250 0251 251 0253 253 0254 254 0255 255 0256 256 0258 258 0259 259 0260 260 0265 265 0267 267 0268 268 0272 272 0273 273 0280 280 0281 281 0284 284 0287 287 0288 288 0296 296 0300 300+ 9999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any sheep <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any sheep. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of sheep owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing sheep in current county [discrepancies: none] This variable indicates the household's number of sheep owned, reared, or managed. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 0100 100 0101 101 0102 102 0103 103 0104 104 0105 105 0107 107 0108 108 0109 109 0110 110 0112 112 0113 113 0114 114 0115 115 0116 116 0117 117 0118 118 0120 120 0121 121 0122 122 0123 123 0124 124 0125 125 0126 126 0127 127 0128 128 0129 129 0130 130 0131 131 0132 132 0133 133 0134 134 0135 135 0136 136 0137 137 0138 138 0140 140 0141 141 0142 142 0143 143 0144 144 0145 145 0146 146 0147 147 0148 148 0149 149 0150 150 0152 152 0153 153 0154 154 0155 155 0156 156 0157 157 0158 158 0159 159 0160 160 0162 162 0163 163 0164 164 0165 165 0167 167 0168 168 0169 169 0170 170 0172 172 0174 174 0175 175 0176 176 0177 177 0178 178 0180 180 0181 181 0183 183 0184 184 0185 185 0188 188 0190 190 0195 195 0197 197 0198 198 0200 200 0201 201 0202 202 0203 203 0204 204 0205 205 0206 206 0207 207 0208 208 0210 210 0211 211 0212 212 0213 213 0214 214 0215 215 0217 217 0218 218 0220 220 0221 221 0222 222 0223 223 0225 225 0230 230 0231 231 0233 233 0234 234 0235 235 0236 236 0238 238 0239 239 0240 240 0241 241 0243 243 0245 245 0250 250 0251 251 0252 252 0253 253 0254 254 0255 255 0256 256 0257 257 0258 258 0260 260 0267 267 0268 268 0269 269 0270 270 0271 271 0274 274 0279 279 0280 280 0281 281 0283 283 0285 285 0286 286 0288 288 0290 290 0293 293 0298 298 0300 300 0308 308 0310 310 0312 312 0315 315 0320 320 0321 321 0324 324 0325 325 0332 332 0340 340 0344 344 0350 350 0351 351 0352 352 0354 354 0362 362 0365 365 0369 369 0370 370 0380 380 0386 386 0387 387 0390 390 0400 400 0411 411 0412 412 0420 420 0423 423 0428 428 0430 430 0437 437 0444 444 0450 450 0452 452 0453 453 0458 458 0460 460 0465 465 0466 466 0470 470 0480 480 0487 487 0488 488 0500 500+ 9999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any goats <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any goats. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of goats owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing goats in current county [discrepancies: none] This variable indicates the household's number of goats owned, reared, or managed. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 0100 100 0101 101 0102 102 0103 103 0104 104 0105 105 0106 106 0107 107 0108 108 0109 109 0110 110 0111 111 0112 112 0113 113 0114 114 0115 115 0116 116 0117 117 0118 118 0119 119 0120 120 0121 121 0122 122 0123 123 0124 124 0125 125 0126 126 0127 127 0128 128 0129 129 0130 130 0131 131 0132 132 0133 133 0134 134 0135 135 0136 136 0137 137 0138 138 0140 140 0141 141 0142 142 0143 143 0144 144 0145 145 0146 146 0147 147 0148 148 0149 149 0150 150 0151 151 0152 152 0153 153 0154 154 0155 155 0156 156 0157 157 0158 158 0159 159 0160 160 0161 161 0162 162 0163 163 0164 164 0165 165 0166 166 0167 167 0168 168 0169 169 0170 170 0172 172 0173 173 0174 174 0175 175 0176 176 0177 177 0178 178 0179 179 0180 180 0181 181 0182 182 0183 183 0184 184 0185 185 0186 186 0187 187 0188 188 0189 189 0190 190 0191 191 0192 192 0194 194 0195 195 0196 196 0197 197 0198 198 0199 199 0200 200 0201 201 0202 202 0203 203 0204 204 0205 205 0206 206 0208 208 0210 210 0211 211 0212 212 0213 213 0214 214 0215 215 0216 216 0217 217 0218 218 0220 220 0222 222 0223 223 0225 225 0228 228 0230 230 0231 231 0232 232 0233 233 0234 234 0235 235 0236 236 0237 237 0238 238 0240 240 0241 241 0243 243 0245 245 0246 246 0247 247 0248 248 0249 249 0250 250 0251 251 0253 253 0254 254 0255 255 0256 256 0257 257 0258 258 0259 259 0260 260 0265 265 0268 268 0270 270 0271 271 0273 273 0275 275 0276 276 0277 277 0278 278 0279 279 0280 280 0283 283 0284 284 0285 285 0287 287 0288 288 0290 290 0291 291 0293 293 0295 295 0296 296 0298 298 0299 299 0300 300 0301 301 0302 302 0305 305 0308 308 0310 310 0311 311 0312 312 0313 313 0314 314 0315 315 0317 317 0320 320 0321 321 0323 323 0324 324 0325 325 0326 326 0328 328 0331 331 0333 333 0335 335 0341 341 0345 345 0347 347 0348 348 0350 350 0351 351 0352 352 0355 355 0357 357 0358 358 0359 359 0360 360 0361 361 0362 362 0364 364 0365 365 0366 366 0368 368 0369 369 0370 370 0380 380 0386 386 0387 387 0390 390 0391 391 0394 394 0399 399 0400 400 0405 405 0410 410 0412 412 0413 413 0414 414 0420 420 0421 421 0422 422 0423 423 0425 425 0427 427 0430 430 0432 432 0435 435 0448 448 0450 450 0452 452 0455 455 0456 456 0457 457 0458 458 0460 460 0467 467 0468 468 0470 470 0478 478 0480 480 0500 500+ 9998 Unknown 9999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any camels <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any camels. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of camels owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing camels in current county [discrepancies: type I none; type II trace] This variable indicates the household's number of camels owned, reared, or managed. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 0100 100 0101 101 0102 102 0103 103 0104 104 0105 105 0106 106 0108 108 0110 110 0111 111 0112 112 0113 113 0114 114 0115 115 0117 117 0120 120 0121 121 0122 122 0123 123 0124 124 0125 125 0126 126 0128 128 0129 129 0130 130 0132 132 0133 133 0135 135 0138 138 0140 140 0141 141 0142 142 0144 144 0145 145 0146 146 0147 147 0148 148 0149 149 0150 150 0151 151 0153 153 0154 154 0156 156 0157 157 0158 158 0159 159 0163 163 0164 164 0168 168 0169 169 0170 170 0173 173 0175 175 0180 180 0183 183 0185 185 0190 190 0192 192 0196 196 0198 198 0200 200 0201 201 0205 205 0206 206 0208 208 0210 210 0211 211 0213 213 0214 214 0218 218 0230 230 0231 231 0234 234 0235 235 0236 236 0240 240 0241 241 0243 243 0245 245 0247 247 0250 250+ 9999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any donkeys <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any donkeys. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of donkeys owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing donkeys in current county [discrepancies: none] This variable indicates the household's number of donkeys owned, reared, or managed. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25+ 999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any pigs <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any pigs. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of pigs owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing pigs in current county [discrepancies: type I none; type II trace] This variable indicates the household's number of pigs owned, reared, or managed. 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 049 49 050 50+ 999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any indigenous chickens <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any indigenous chickens. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of indigenous chicken owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing indigenous chicken in current county [discrepancies: bibe] This variable indicates the household's number of indigenous chicken owned, reared, or managed. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0080 80 0082 82 0083 83 0084 84 0085 85 0086 86 0088 88 0090 90 0091 91 0092 92 0095 95 0096 96 0097 97 0098 98 0099 99 0100 100 0101 101 0102 102 0103 103 0104 104 0105 105 0106 106 0107 107 0108 108 0109 109 0110 110 0113 113 0115 115 0117 117 0120 120 0122 122 0123 123 0124 124 0125 125 0127 127 0128 128 0130 130 0132 132 0133 133 0138 138 0140 140 0143 143 0144 144 0145 145 0146 146 0147 147 0150 150 0153 153 0154 154 0156 156 0160 160 0165 165 0167 167 0170 170 0172 172 0173 173 0174 174 0175 175 0176 176 0180 180 0195 195 0196 196 0198 198 0200 200 0210 210 0211 211 0220 220 0224 224 0229 229 0230 230 0236 236 0245 245 0248 248 0250 250 0253 253 0259 259 0280 280 0281 281 0290 290 0300 300 0320 320 0321 321 0350 350 0400 400+ 9998 Unknown 9999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any exotic egg-laying chickens <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any exotic egg-laying chickens. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of exotic egg-laying chickens owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing egg-laying chicken in current county [discrepancies: none] This variable indicates the household's number of exotic egg-laying chickens owned, reared, or managed. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0065 65 0066 66 0067 67 0068 68 0070 70 0071 71 0072 72 0074 74 0075 75 0076 76 0077 77 0079 79 0080 80 0082 82 0084 84 0085 85 0086 86 0087 87 0088 88 0090 90 0091 91 0092 92 0093 93 0095 95 0096 96 0097 97 0098 98 0100 100 0101 101 0102 102 0103 103 0104 104 0105 105 0107 107 0109 109 0110 110 0115 115 0120 120 0125 125 0128 128 0129 129 0130 130 0136 136 0140 140 0144 144 0145 145 0150 150 0156 156 0160 160 0167 167 0170 170 0180 180 0200 200 0210 210 0216 216 0220 220 0222 222 0230 230 0240 240 0245 245 0250 250 0260 260 0265 265 0270 270 0272 272 0279 279 0280 280 0283 283 0290 290 0300 300 0348 348 0350 350 0360 360 0370 370 0378 378 0380 380 0400 400 0420 420 0450 450 0475 475 0480 480 0483 483 0500 500 0550 550 0586 586 0600 600 0650 650 0660 660 0700 700 0750 750 0780 780 0800 800 0840 840 0850 850 0900 900 1000 1000+ 9999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any exotic broiler chickens <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any exotic broiler chickens. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of exotic broiler chickens owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing broiler chicken in current county [discrepancies: type I none; type II trace] This variable indicates the household's number of exotic broiler chickens owned, reared, or managed. 0000 0 0001 1 0002 2 0003 3 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0062 62 0066 66 0070 70 0072 72 0073 73 0075 75 0077 77 0078 78 0080 80 0085 85 0086 86 0088 88 0090 90 0098 98 0100 100 0105 105 0110 110 0116 116 0120 120 0123 123 0129 129 0130 130 0138 138 0140 140 0144 144 0150 150 0160 160 0170 170 0180 180 0195 195 0198 198 0200 200 0210 210 0220 220 0230 230 0240 240 0242 242 0248 248 0250 250 0270 270 0280 280 0290 290 0292 292 0298 298 0300 300 0350 350 0380 380 0400 400 0412 412 0450 450 0500 500+ 9999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any bees <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any bees. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of beehives owned or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing beehives in current county [discrepancies: none] This variable indicates the household's number of beehives owned or managed. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 065 65 066 66 068 68 070 70 071 71 072 72 074 74 078 78 080 80 081 81 082 82 083 83 084 84 086 86 090 90 092 92 093 93 095 95 097 97 100 100+ 999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own or manage any fish ponds <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households engaged in aquaculture in current county [discrepancies: type I trace; type II none] This variable indicates whether the household owns or manages any fish ponds. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of fish ponds owned or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing fish ponds in current county [discrepancies: none] This variable indicates the household's number of fish ponds owned or managed. 01 1 02 2 03 3 04 4 05 5+ 99 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own or manage any fish cages <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households engaged in aquaculture in current county [discrepancies: type I trace; type II none] This variable indicates whether the household owns or manages any fish cages. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of fish cages owned or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing fish ponds in current county [discrepancies: none] This variable indicates the household's number of fish cages owned or managed. 01 1 02 2 03 3+ 99 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Own, rear, or manage any rabbits <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing livestock in current county [discrepancies: type I 1.0%; type II none] This variable indicates whether the household owns, rears, or manages any rabbits. 1 Yes 2 No 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of rabbits owned, reared, or managed <span class="h2">H: Information regarding crop farming, livestock, fishing, and aquaculture</span></p> <p>H-26. How many of each of the following livestock are currently owned/reared/managed within this household in this county?</p> <div class="i1"><span class="ital">If None, code '00000'</span></div><div class="i1">_ _ _ _ _ 1. Exotic cattle - Dairy</div><div class="i1">_ _ _ _ _ 2. Exotic cattle - Beef</div><div class="i1">_ _ _ _ _ 3. Indigenous cattle</div><div class="i1">_ _ _ _ _ 4. Sheep</div><div class="i1">_ _ _ _ _ 5. Goats</div><div class="i1">_ _ _ _ _ 6. Camels</div><div class="i1">_ _ _ _ _ 7. Donkeys</div><div class="i1">_ _ _ _ _ 8. Pigs</div><div class="i1">_ _ _ _ _ 9. Indigenous chicken</div><div class="i1">_ _ _ _ _ 10. Exotic chicken - Layers</div><div class="i1">_ _ _ _ _ 11. Exotic chicken - Broilers</div><div class="i1">_ _ _ _ _ 12. Bees - Number of beehives</div><div class="i1">_ _ _ _ _ 13Fish - Fish ponds</div><div class="i1">_ _ _ _ _ 14. Fish - Fish cage</div><div class="i1">_ _ _ _ _ 15. Rabbits</div> 27.9. Column H26: Type and number of livestock <br />Ask, "how many of each of the following livestock are currently owned/rared/managed by this household in this county?"</p> <div class="i1">i. Livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes. These include cattle, camel, donkey, sheep, goat, camels, and pigs, rabbits as well as chicken and bees.<br />ii. For cattle, distinction should be made between exotic cattle-beef (exotic cattle kept mainly for meat) and exotic cattle-dairy (kept mainly for milk production). Under the exotic cattle dairy there also exists exotic cattle-dairy bulls (for breeding) and steers (castrated males) kept within dairy herd. The steers are mainly for sale but should not be confused with the beef breeds kept for meat. Therefore, they don't qualify as exotic cattle-beef. Indigenous cattle are the local zebu cattle kept for meat and some little milk. These are mainly reared in the arid and semi-arid areas with the pastoral communities keeping big numbers.<br />iii. Indigenous chicken are local chicken kept for meat and eggs. Chicken-layers are exotic chicken kept specifically for egg production on commercial basis; while chicken broilers are exotic chicken kept mainly for meat on commercial basis.<br />iv. The number of animals is the animal population on the holding at a specific point in time, usually the census reference day. The animal population kept by the household refers to the total number of animals in the holding on the census reference date, regardless of ownership.<br />v. The animals listed should be within the County. Some institutions such as schools, prisons, ranches, or private companies keep or rear livestock. For institutions, which own livestock and where the special population is absent during enumeration, the enumerator should complete such details when linked to a particular household inside the institution, otherwise should be left to be enumerated using a different approach.<br />vi. Note that some households/communities might be reluctant in providing the correct livestock numbers. Under such circumstances, the enumerators should try probing in order to get the correct livestock numbers. Use local language may assist in getting information on the numbers<br />vii. Presence of aquaculture refers to fish farming in the holding in association with agricultural production. Aquaculture comprises pond culture, cage culture, among others.<br />viii. Pond culture is the breeding or rearing of fish or other aquatic plants and animals in natural or artificial enclosures. Pond culture is usually carried out in stagnant waters with periodic water exchange or water flushing through inlets and outlets.<br />ix. Cage aquaculture involves the growing of fishes in existing water resources while being enclosed in a net cage, which allows free flow of water. It is an aquaculture production system made of a floating frame, net materials and mooring system (with rope, buoy, anchor, etc.) with a round or square shape floating net to hold and culture large number of fishes and can be installed in reservoir, river, lake or sea.</div><p>The enumerator will be required to enquire about the number of ponds and cages operated by the household as of the census reference day and record accordingly. Kenya 2019: Households rearing rabbits in current county [discrepancies: type I none; type II trace] This variable indicates the household's number of rabbits owned, reared, or managed. 000 0 001 1 002 2 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30+ 999 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Number of dwelling units occupied by household <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-27. Dwelling units: How many dwelling units does this household occupy? _ _ <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.1. Column H27: Dwelling units <br />- For purposes of this census, a dwelling unit is a place of abode or residence occupied by one or more households (used for sleeping, eating, entertaining guests, etc.) with a private entrance. There can be more than one dwelling unit within a structure (for instance in flats, Swahili structures). A dwelling unit may be a whole structure or part of a structure, especially in urban settings. <br />- There are situations, especially in rural areas, whereby the kitchen is a stand-alone structure. Such a kitchen must be counted as a dwelling unit in its own right. <br />- Record the number of dwelling units available to a household in column H27. Kenya 2019: Private households [discrepancies: none] This variable indicates the number of dwelling units occupied by the household. 01 1 dwelling unit 02 2 dwelling units 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15+ 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Number of habitable rooms, including all dwelling units <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-28. Habitable rooms: How many habitable rooms do these units contain? _ _ <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.2. Column H28: Habitable rooms <br />- As defined earlier, habitable rooms are rooms in the dwelling unit that are used mainly for living and exclude stores, granaries, offices, toilets and garages. <br />- A kitchen, under normal circumstances, should not be counted as a habitable room. However, if the household uses the kitchen for eating and/or sleeping purposes, or even for purposes of entertaining guests, then it should be counted as a habitable room. The same applies to a store and garage. <br />- Record the number of habitable rooms available in all the dwelling units that belong to a household in column H28. Kenya 2019: Private households [discrepancies: none] This variable indicates the dwelling's number of habitable rooms, including all dwelling units. 01 1 room 02 2 rooms 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Ownership status of main dwelling unit <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-29. Tenure status of main dwelling unit. Is the main dwelling unit owned or rented/provided?</p> <div class="i1">If owner occupied, state whether:</div><div class="i2">[] 1. Purchased<br />[] 2. Constructed<br />[] 3. Inherited</div><div class="i1">If rented/provided, state whether:</div><div class="i2">[] 4. National government<br />[] 5. County government<br />[] 6. Parastatal<br />[] 7. Private company<br />[] 8. Individual<br />[] 9. FBO/NGO/church/temple/mosque</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.3. Column H29: Tenure status of main dwelling unit <br />Column H29 seeks information on status of tenure, i.e. whether the dwelling unit is owner occupied or rented by the household or provided. <br />Ask the head of the household or any other responsible person whether the main residential/dwelling unit is owned or rented by him/her or any other member of the household. You are supposed to select the answers using the categories provided. The tenure status referred to in this section is about the occupancy status of the dwelling unit itself as opposed to ownership of the land on which it stands or security of tenure for that matter.</p> <p>Owner occupied: Under owner occupied, the options are:</p> <div class="i1">- Purchased: Means that a member of the household has bought the structure or is in the process of paying for the structure and household members are living in it.<br />- Constructed: Means that a member of the household has built the structure they are living in.<br />- Inherited: Means that a member of the household has received the building by right of succession or by a will. However, in this case, do not ask for proof. Accept what the respondent says.</div><p>Rented/provided/donated: Under rented/provided/donated are dwelling units either provided by an employer of a member of the household, rented by a member of the household or donated to a member of the household. This includes:</p> <div class="i1">i. National government: Covers all houses rented or provided by the National Government of Kenya<br />ii. County government: Covers all houses rented or provided by County Governments<br />iii. Parastatal owned entities: Covers organizations like Kenya Railways, Kenya Power and Lighting Co., Universities, etc.<br />iv. Private Company: Covers private firms and foreign governments<br />v. Individual: Covers private individuals only<br />vi. FBO: Faith based organisations, e.g. churches, mosques, temples, etc.</div><p>NB: If a household is housed by an institution, probe further on whether the institution is privately owned, managed by the county or national government, etc. and select code appropriately. Kenya 2019: Private households [discrepancies: none] This variable indicates the dwelling's ownership status of the main dwelling unit. 1 Owned 2 Rented or provided 9 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Detailed ownership status of main dwelling unit <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-29. Tenure status of main dwelling unit. Is the main dwelling unit owned or rented/provided?</p> <div class="i1">If owner occupied, state whether:</div><div class="i2">[] 1. Purchased<br />[] 2. Constructed<br />[] 3. Inherited</div><div class="i1">If rented/provided, state whether:</div><div class="i2">[] 4. National government<br />[] 5. County government<br />[] 6. Parastatal<br />[] 7. Private company<br />[] 8. Individual<br />[] 9. FBO/NGO/church/temple/mosque</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.3. Column H29: Tenure status of main dwelling unit <br />Column H29 seeks information on status of tenure, i.e. whether the dwelling unit is owner occupied or rented by the household or provided. <br />Ask the head of the household or any other responsible person whether the main residential/dwelling unit is owned or rented by him/her or any other member of the household. You are supposed to select the answers using the categories provided. The tenure status referred to in this section is about the occupancy status of the dwelling unit itself as opposed to ownership of the land on which it stands or security of tenure for that matter.</p> <p>Owner occupied: Under owner occupied, the options are:</p> <div class="i1">- Purchased: Means that a member of the household has bought the structure or is in the process of paying for the structure and household members are living in it.<br />- Constructed: Means that a member of the household has built the structure they are living in.<br />- Inherited: Means that a member of the household has received the building by right of succession or by a will. However, in this case, do not ask for proof. Accept what the respondent says.</div><p>Rented/provided/donated: Under rented/provided/donated are dwelling units either provided by an employer of a member of the household, rented by a member of the household or donated to a member of the household. This includes:</p> <div class="i1">i. National government: Covers all houses rented or provided by the National Government of Kenya<br />ii. County government: Covers all houses rented or provided by County Governments<br />iii. Parastatal owned entities: Covers organizations like Kenya Railways, Kenya Power and Lighting Co., Universities, etc.<br />iv. Private Company: Covers private firms and foreign governments<br />v. Individual: Covers private individuals only<br />vi. FBO: Faith based organisations, e.g. churches, mosques, temples, etc.</div><p>NB: If a household is housed by an institution, probe further on whether the institution is privately owned, managed by the county or national government, etc. and select code appropriately. Kenya 2019: Private households [discrepancies: none] This variable indicates the detailed ownership status of the main dwelling unit. 11 Owned, purchased 12 Owned, constructed 13 Owned, inherited 24 Rented from or provided by the national government 25 Rented from or provided by the county government 26 Rented from or provided by a parastatal organization 27 Rented from or provided by a private company 28 Rented from or provided by an individual 29 Rented from or provided by a faith-based or non-governmental organization, church, temple, or mosque 99 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Dominant roof material of main dwelling unit <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-30. Dominant construction material of the roof in the main dwelling unit</p> <div class="i1">[] 1. No roof<br />[] 2. Grass thatch/twigs<br />[] 3. Makuti thatch<br />[] 4. Dung/mud<br />[] 5. Iron sheets<br />[] 6. Tin cans<br />[] 7. Asbestos sheet<br />[] 8. Concrete/cement<br />[] 9. Tiles<br />[] 10. Canvas/tents<br />[] 11. Decra/versatile<br />[] 12. Nylon/cartons/cardboard<br />[] 13. Shingles</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.4. Column H30: Dominant construction material of roof for main dwelling unit <br />Enter the main construction materials used to build the roof, e.g. 1=No roof, 2=grass thatch/twigs, 3=makuti thatch, 4=dung/mud, 5=Iron sheets (include the ordinary corrugated iron sheets), 6=tin cans, 7=asbestos sheets, 8=concrete/cement, 9=tiles (include clay, wooden, fibre and cement tiles), 10=canvas/tent, 11=Decra/versatile (include premium roofing made of plain steel/stone coated steel/iron sheets with appearance of tiles), 12=nylon/cartons/cardboard, 13=Shingles. Pictorials of some of these roofing materials are as shown below. <br />Note: For persons living in apartments, take the roof immediately above each household. Kenya 2019: Private households [discrepancies: none] This variable indicates the dominant roof material of the main dwelling unit. 01 Grass thatch or twigs 02 Makuti thatch 03 Dung or mud 04 Iron sheets 05 Tin cans 06 Asbestos sheet 07 Concrete or cement 08 Tiles 09 Canvas or tents 10 Decra or versatile 11 Nylon, cartons, or cardboard 12 Shingles 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Dominant wall material of main dwelling unit <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-31. Dominant construction material of the wall in the main dwelling unit</p> <div class="i1">[] 1. No walls<br />[] 2. Cane/palm/trunks<br />[] 3. Grass/reeds<br />[] 4. Mud/cow dung<br />[] 5. Stone with mud<br />[] 6. Covered adobe<br />[] 7. Uncovered adobe<br />[] 8. Plywood/cardboard<br />[] 9. Off cuts/reused wood/wood planks<br />[] 10. Iron sheets<br />[] 11. Concrete/concrete blocks/precast wall<br />[] 12. Stone with lime/cement<br />[] 13. Bricks<br />[] 14. Canvas/tents<br />[] 15. Nylon/cartons<br />[] 16. Timber<br />[] 17. Prefabricated panels</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.5. Column H31: Dominant construction material of walls of main dwelling unit <br />Code in column H31, the dominant construction materials used to build the wall; 1=No walls, 2=Cane/palm/trunks, 3=Grass/reeds, 4=Mud/cow dung, 5=Stone with mud, 6=Covered adobe, 7=Uncovered adobe, 8=Plywood/Cardboard, 9=Wood Offcuts/Reused wood/ Planks, 10=Iron sheets, 11=Concrete/Concrete blocks/precast wall, 12=Stone with lime/cement, 13=Bricks (Kiln baked), 14=Canvas/Tent, 15=Nylon/cartons, 16=Timber, 17=Prefabricated pannels <br />Consider the main material that constitutes the structure. In cases where several materials are used, select the most dominant. <br />NB:</p> <div class="i1">- Adobe means (sun dried bricks)<br />- Precast wall, refers to wall produced by casting concrete in a reusable mold or "form" which is then cured in a controlled environment, transported to the construction site and lifted into place.<br />- Prefabricated panels, these are factory manufactured wall panels -- which are transported and assembled at the construction site, e.g. expanded polystyrene (EPS).</div> Kenya 2019: Private households [discrepancies: none] This variable indicates the dominant wall material of the main dwelling unit. 01 Cane, palm, or trunks 02 Grass or reeds 03 Mud or cow dung 04 Stone with mud 05 Covered adobe 06 Uncovered adobe 07 Plywood or cardboard 08 Off cuts, reused wood, or wood planks 09 Iron sheets 10 Concrete, concrete blocks, or precast wall 11 Stone with lime or cement 12 Bricks 13 Canvas or tents 14 Nylon or cartons 15 Timber 16 Prefabricated panels 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Dominant floor material of main dwelling unit <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-32. Dominant construction material of the floor in the main dwelling unit</p> <div class="i1">[] 1. Earth/sand<br />[] 2. Dung<br />[] 3. Wood planks/shingles/timber<br />[] 4. Palm/bamboo<br />[] 5. Parquet or polished wood<br />[] 6. Vinyl or asphalt strips<br />[] 7. Ceramic tiles<br />[] 8. Concrete/cement/terrazzo<br />[] 9. Wall to wall carpet</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.6. Columns H32: Dominant construction material of floor of main dwelling unit <br />Select code in column H32 the construction material used to build the floor <br />e.g. enter 1=Earth/sand, 2=Dung, 3=Wood planks/ shingles/timber, 4=Palm/ bamboo, 5=Parquet or polished wood, 6=Vinyl or asphalt strips, 7=Ceramic tiles, 8=Concrete/ Cement/Terrazo, 9=Wall to wall Carpet, refers to fitted carpet covering a floor entirely.96=Other Kenya 2019: Private households [discrepancies: none] This variable indicates the dominant floor material of the main dwelling unit. 01 Earth or sand 02 Dung 03 Wood planks, shingles, or timber 04 Palm or bamboo 05 Parquet or polished wood 06 Vinyl or asphalt strips 07 Ceramic tiles 08 Concrete, cement, or terrazo 09 Wall to wall carpet 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Main source of drinking water <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-33. Main source of drinking water</p> <div class="i1">[] 1. Pond/water pan<br />[] 2. Dam<br />[] 3. Lake<br />[] 4. Stream/river<br />[] 5. Protected spring<br />[] 6. Unprotected spring<br />[] 7. Protected well<br />[] 8. Unprotected well<br />[] 9. Borehole/tube well<br />[] 10. Piped into dwelling<br />[] 11. Piped to yard/plot<br />[] 12. Bottled water<br />[] 13. Rain/harvested water<br />[] 14. Water vendor<br />[] 15. Public tap/standpipe</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.7. Column H33: Main source of drinking water <br />In column H33: Ask, "what is the main source of drinking water for this household?" <br />You are required to select the main source of drinking water. This is the source from which, for most part of the year, the household draws its drinking water. For example, if during the wet season the household draws their drinking water from a tank but then the longer part of the year draws it from a river, then '4' stream/river is the main source of their drinking water. <br />The main sources of drinking water listed are:</p> <div class="i1">i. Pond/water pan: A small area of still water. Usually this water collects after rain or through an underground drainage.<br />ii. Dam: A reservoir formed by building a barrier across a river to hold water back and control its flow.<br />iii. Lake: It is a large natural water mass which collects its water through rain, rivers, etc. It is different from a dam in that it is not man-made.<br />iv. Stream/river: This is a naturally flowing source of water. Water from dry river beds falls in this category.<br />v. Protected spring: This is a spring protected from runoff, bird droppings, and animals by a "spring box" which is typically constructed of brick, masonry, or concrete and is built around the spring so that water flows directly out of the box into a pipe without being exposed to outside pollution.<br />vi. Unprotected spring: This is a spring that is subject to runoff and/or bird droppings or animals. Unprotected springs typically do not have a "spring box".<br />vii. Protected Well: This is a dug well that is (1) protected from runoff water through a well lining or casing that is raised above ground level and a platform that diverts spilled water away from the well; and (2) covered so that bird droppings and animals cannot fall into the well. Both conditions must be observed for a dug well to be considered as protected.<br />viii. Unprotected well: This is a dug well which is (1) unprotected from runoff water; (2) unprotected from bird droppings and animals; or (3) both.<br />ix. Borehole/tube well: A deep hole that has been bored or drilled with the purpose of reaching ground water supplies. In most cases, water is delivered from a tubewell or borehole through a pump which may be human, animal, wind, electric, diesel or solar-powered.<br />x. Piped to yard/plot: Means pipe connected to a tap outside the house in the yard or plot. Sometimes called a yard connection.<br />xi. Piped into dwelling: Means pipe connected with in-house plumbing to one or more taps, e.g. in the kitchen and bathroom. Sometimes called a house connection.<br />xii. Public tap or standpipe: Public water point from which community members may collect water. A standpipe may also be known as a public fountain or public tap. Public standpipes can have one or more taps and are typically made of brickwork, masonry or concrete.<br />xiii. Rain harvested water: Rain water that is collected or harvested from surfaces by roof or ground catchment and stored in a container, tank, Jabia or cistern.<br />xiv. Water vendor: Refers to water purchased by households from mobile sellers or distributors. Examples of ferrying include cart, motorcycle/Tuk Tuk, bicycle, individuals, truck, etc. The source of the water may be known by the households or not.<br />xv. Bottled water: This means drinking water (well water, distilled water, mineral water, or spring water) packaged in plastic bottles.</div><p>In cases where households draw drinking water from neighbours, school, church, etc probe on the source of the water. Kenya 2019: Private households [discrepancies: none] This variable indicates the household's main source of drinking water. 01 Pond 02 Dam 03 Lake 04 Stream or river 05 Protected spring 06 Unprotected spring 07 Protected well 08 Unprotected well 09 Borehole or tube well 10 Piped into dwelling 11 Piped to yard or plot 12 Bottled water 13 Rain or harvested water 14 Water vendor 15 Public tap or standpipe 99 NIU (not in universe) Utilities Variables -- HOUSEHOLD Main mode of human waste disposal <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-34. Main mode of human waste disposal</p> <div class="i1">[] 1. Main sewer<br />[] 2. Septic tank<br />[] 3. Cesspool<br />[] 4. VIP Pit latrine<br />[] 5. Pit latrine covered<br />[] 6. Pit latrine uncovered<br />[] 7. Bucket latrine<br />[] 8. Open<br />[] 9. Bio-septic tank/biodigester</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.8. Column H34: Main mode of human waste disposal <br />In column H34: Ask, "Where do members of this household dispose off human waste?" Select the answers according to the categories given, e.g. code "3" for cesspool, "4" for ventilated improved pit latrine (VIP), etc. <br />The categories of main type of sewage disposal are:</p> <div class="i1">i. Main sewer: Means the sewage liquid waste from the structure is drained by pipes into a main trunk sewer line. This type of sewage disposal is common in main urban centres like Nairobi, Mombasa, etc.<br />ii. Septic tank: This is a tank into which household(s) sewage is conveyed and remains there until it is emptied. Examples of septic tanks are found in urban areas, where the tank is often located within the compound where you find dwelling structures.<br />iii. Bucket latrine: This is a bucket placed in a residential area used to collect human excreta. It is emptied occasionally. This type of waste disposal is now rare but can still be found in some urban residential estates and in North-Eastern towns.<br />iv. Cess pool: This is a communal pool where liquid waste is drained into from dwelling units until it is emptied.<br />v. Ventilated Improved Pit (VIP) latrine: This is a latrine ventilated by a pipe extending above the latrine roof. The open end of the vent pipe is covered with gauze mesh or fly-proof netting and the inside of the superstructure is kept dark.<br />vi. Pit latrine covered: This is a pit latrine without ventilation pipe with covering (shelter).<br />vii. Pit Latrine uncovered: Means holes or dug pits with temporary coverings or without shelter.<br />viii. Bioseptic Tank/Biodigester: This is like septic tank but offers a compact sewage treatment system that safely processes and recycles human waste by use of bacteria and enzymes to clear odourless water.<br />ix. Open: Bush is an open field (a non-facility) where members dispose excreta. Flying toilet is where household members dispose human waste by throwing off the same using polythene papers. This is common in urban centers and especially in slums/informal settlements.</div><p>Where households share a toilet facility with neighbours or relatives, ask the type of the shared 'borrowed' facility. Kenya 2019: Private households [discrepancies: none] This variable indicates the household's main mode of human waste disposal. 01 Main sewer 02 Septic tank 03 Cess pool 04 Ventilated improved pit (VIP) latrine 05 Pit latrine, covered 06 Pit latrine, uncovered 07 Bucket latrine 08 Bush 09 Bio-septic tank or biodigester 99 NIU (not in universe) Utilities Variables -- HOUSEHOLD Facility for human waste disposal is shared with at least one other household <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-35. Sharing of human waste disposal facility. Is the facility shared with any other household?</p> <div class="i1">If the response in H-34 is code 4, 5, 6, or 7.<br /><br />[] 1. Yes<br />[] 2. No</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.9. Column H35: Sharing of human waste disposal facility <br />Ask, the households who have responded with code 4, 5, 6 or 7 in column H34, VIP pit latrine, Pit latrine covered and Pit latrine uncovered respectively, if the facility is shared with one or more other households and enter code appropriately. Kenya 2019: Private households [discrepancies: type I none; type II trace] This variable indicates whether the facility for human waste disposal is shared with at least one other household. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Main mode of solid waste disposal <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-36. Main mode of solid waste disposal</p> <div class="i1">[] 1. Collected by county government<br />[] 2. Collected by community association CBOs, youth groups, faith-based organizations<br />[] 3. Collected by private company<br />[] 4. Dumped in the compound<br />[] 5. Dumped in the street/vacant plot/drain/waterways<br />[] 6. Dumped in the latrine<br />[] 7. Burnt in open<br />[] 8. Buried<br />[] 9. Compost pit<br />[] 10. Burnt in a pit</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.10. Column H36: Main mode of solid waste disposal <br />In Column H36, Ask how the solid waste from the household is collected/disposed off. Indicate who collects the solid waste for the household, for example, it may be collected by the County Government, community association or private companies. For those whose waste is not collected, find out how they dispose it and enter appropriate code. 1=Collected by County Government; 2=Collected by Community Association (CBOs, Youth Groups, Faith Based Organizations); 3=Collected by private company; 4=Dumped in the compound; 5=Dumped in the street/vacant plot/drain/waterways, 6=Dumped in the Latrine, 7=Burnt in open, 8=Buried, 9=Compost pit, this is a pit is a hole dug on the ground where organic materials decompose to form humus (compost) that is used as fertilizer; 10=Burnt in a pit. Kenya 2019: Private households [discrepancies: none] This variable indicates the household's main mode of solid waste disposal. 01 Collected by county government 02 Collected by community association (community based organization, youth group, faith based organization) 03 Collected by private company 04 Dumped in the compound 05 Dumped in the street, a vacant plot, a drain, or waterways 06 Dumped in the latrine 07 Burnt in the open 08 Buried 09 Compost pit 10 Burnt in a pit 99 NIU (not in universe) Utilities Variables -- HOUSEHOLD Main type of cooking fuel <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-37. Main type of cooking fuel</p> <div class="i1">[] 1. Electricity<br />[] 2. Paraffin<br />[] 3. LPG gas<br />[] 4. Biogas<br />[] 5. Firewood and other raw wood products<br />[] 6. Charcoal<br />[] 7. Solar</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.11. Column H37: Main type of cooking fuel <br />Ask: "What is the main cooking fuel used in this household?" <br />In column H37, note that some households may use electricity, paraffin, gas and firewood, all at the same time. The answer required here is the fuel used most of the time. Firewood includes other raw wood products like sawdust, timber, offcuts, etc. Enter the appropriate answer in column H37. 1=Mains Electricity, 2=Paraffin, 3=LPG (gas), 4=Biogas, 5=Firewood and other raw wood products, 6=Charcoal/Charcoal briquettes, 7=Solar. Kenya 2019: Private households [discrepancies: none] This variable indicates the household's main type of cooking fuel. 1 Electricity 2 Paraffin 3 Liquefied petroleum gas (LPG) 4 Biogas 5 Firewood 6 Charcoal 7 Solar 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Main type of lighting <span class="h2">I: Housing conditions and amenities</span></p> <p>To be asked of the household head or any other responsible person.</p> <p>H-38. Main type of lighting</p> <div class="i1">[] 1. Mains electricity<br />[] 2. Paraffin pressure lamp<br />[] 3. Paraffin lantern<br />[] 4. Paraffin tin lamp<br />[] 5. Gas lamp<br />[] 6. Wood<br />[] 7. Solar<br />[] 8. Torch/spotlight - Solar charged<br />[] 9. Torch/spotlight - Dry cells<br />[] 10. Candle<br />[] 11. Battery car/charged<br />[] 12. Generator diesel/petrol<br />[] 13. Biogas</div> <span class="em">28. Section I: Housing conditions and amenities</span> <br />Columns H-27 to H-38 have questions pertaining to housing conditions and amenities and are to be asked of the head of the household or any other responsible person.</p> <p>28.12. Column H38: Main type of lighting <br />In column H38, select the answer according to the categories given. 1=Mains Electricity, Electricity here means the mains/national transmission grid. Other sources of electricity like generators and batteries (car or charged) should be coded accordingly, 2=Paraffin Pressure Lamp, 3=Paraffin Lantern, 4=Paraffin Tin lamp, Tin lamps include plastic or bottle lamps, which may be known by various local names like koroboi, tamambul, tadoba, nyangile, ekebeya, ngwatira, etc. 5=Gas Lamp, 6=Wood, 7=Solar, 8=Torch/Spotlight-Solar Charged, 9=Torch/Spot light-Dry cells, 10=Candle, 11=Battery(Car/Charged), 12=Generator (Diesel/Petrol), 13=Biogas. Kenya 2019: Private households [discrepancies: none] This variable indicates the household's main type of lighting. 01 Mains electricity 02 Paraffin pressure lamp 03 Paraffin lantern 04 Paraffin tin lamp 05 Gas lamp 06 Wood 07 Solar 08 Torch or spotlight, solar charged 09 Torch or spotlight, dry cells 10 Candle 11 Battery (car or charged) 12 Generator (diesel or petrol) 13 Biogas 99 NIU (not in universe) Utilities Variables -- HOUSEHOLD Household member owns a stand-alone radio <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Stand-alone radio</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">i. Stand-alone radio: A radio is a device capable of receiving broadcast radio signals, using common frequencies, such as FM or AM. This only includes a stand-alone radio device and excludes radios integrated in other devices such as a mobile phone, digital audio player (MP3), computer, car, TV, etc. A stand-alone radio is considered as one of the most common old ICT devices used to relay information to the public as it is widely accessible, relatively cheap and simple to use. As a communication device, organizations, government, businesses, family and friends use the radio to communicate important messages to various audiences. The intention of this question is to find out how many households own or have a stand-alone radio regardless of how they acquired it as long as it is considered as a household asset. The stand-alone radio should be working properly at the time of the census night.</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a stand-alone radio. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a TV with free to air set-top-box or a digital TV <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">TV with free to air set-top-box/digital tv</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">ii. Television: A television (TV) set is a device capable of receiving broadcast television signals, using means such as over the air, cable and satellite. The TV should be a stand-alone device and should be working at the time of the census night. It excludes TV functionality integrated with another device, such as a computer, mobile phone, car, alarm clock, etc. The intention of this question is to establish the number of households with at least one of the TV connections below by type. Since the digital migration, many households were left in the dark and most had to acquire either a free to air (FTA) set top box, digital TV, smart TV/internet protocol TV (IPTV) or a pay TV decoder. The responses for this are:</div><div class="i2">a. TV with free to air set top box/ Built in digital TV -- A set-top box is a hardware device that allows a digital signal to be received, decoded and displayed on a television to enable the channels to be displayed on your analogue TV set. The digital TV is the transmission of television signals using digital rather than conventional analogue methods. This is where an individual owns a TV which is digital or owns a TV together with a set top box. This option, therefore, will include households with TV and free to air set top box or built in digital TV.<br />b. TV with pay TV decoder -- Pay TV decoder is more or less of a set top box as explained above. However, for pay TV, in most cases, it offers a number of channels that one has to pay a monthly fee to be able to view the programmes. This includes decoders such as DSTV, Star times, Zuku, Go-TV etc. regardless of the subscription amount. The pay TV decoder should have been subscribed at least once in the last 3 months.<br />c. Internet protocol TV (IPTV): This is a type of TV that receives the multimedia services over an IP based network managed to support the required level of high quality. The IPTV normally has got an in-built internet connection. Basically, IPTV is the most expensive and may range from 200,000 Ksh to more than a million. Be careful not to include those digital TVs that access internet through HDMI cables or through set top boxes that have internet interface (e.g. android boxes, Safaricom big box, etc.) in this option.<br />d. Analogue TV with no connection -- These are households who have a TV but after the digital migration they have never acquired any of the connections to enable them view the digital programmes. Hence, the TV is not connected to either a set top box or a decoder. The intention of this question is to know the number of households that have a TV but not able to view the channels due to various reasons. Note that households that have no TV at all, should be excluded here.</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a TV with free to air set-top-box or a digital TV. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a TV with pay TV decoder <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">TV with pay tv decoder</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">ii. Television: A television (TV) set is a device capable of receiving broadcast television signals, using means such as over the air, cable and satellite. The TV should be a stand-alone device and should be working at the time of the census night. It excludes TV functionality integrated with another device, such as a computer, mobile phone, car, alarm clock, etc. The intention of this question is to establish the number of households with at least one of the TV connections below by type. Since the digital migration, many households were left in the dark and most had to acquire either a free to air (FTA) set top box, digital TV, smart TV/internet protocol TV (IPTV) or a pay TV decoder. The responses for this are:</div><div class="i2">a. TV with free to air set top box/ Built in digital TV -- A set-top box is a hardware device that allows a digital signal to be received, decoded and displayed on a television to enable the channels to be displayed on your analogue TV set. The digital TV is the transmission of television signals using digital rather than conventional analogue methods. This is where an individual owns a TV which is digital or owns a TV together with a set top box. This option, therefore, will include households with TV and free to air set top box or built in digital TV.<br />b. TV with pay TV decoder -- Pay TV decoder is more or less of a set top box as explained above. However, for pay TV, in most cases, it offers a number of channels that one has to pay a monthly fee to be able to view the programmes. This includes decoders such as DSTV, Star times, Zuku, Go-TV etc. regardless of the subscription amount. The pay TV decoder should have been subscribed at least once in the last 3 months.<br />c. Internet protocol TV (IPTV): This is a type of TV that receives the multimedia services over an IP based network managed to support the required level of high quality. The IPTV normally has got an in-built internet connection. Basically, IPTV is the most expensive and may range from 200,000 Ksh to more than a million. Be careful not to include those digital TVs that access internet through HDMI cables or through set top boxes that have internet interface (e.g. android boxes, Safaricom big box, etc.) in this option.<br />d. Analogue TV with no connection -- These are households who have a TV but after the digital migration they have never acquired any of the connections to enable them view the digital programmes. Hence, the TV is not connected to either a set top box or a decoder. The intention of this question is to know the number of households that have a TV but not able to view the channels due to various reasons. Note that households that have no TV at all, should be excluded here.</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a TV with pay TV decoder. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns an internet protocol TV <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Internet protocol IP tv</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">ii. Television: A television (TV) set is a device capable of receiving broadcast television signals, using means such as over the air, cable and satellite. The TV should be a stand-alone device and should be working at the time of the census night. It excludes TV functionality integrated with another device, such as a computer, mobile phone, car, alarm clock, etc. The intention of this question is to establish the number of households with at least one of the TV connections below by type. Since the digital migration, many households were left in the dark and most had to acquire either a free to air (FTA) set top box, digital TV, smart TV/internet protocol TV (IPTV) or a pay TV decoder. The responses for this are:</div><div class="i2">a. TV with free to air set top box/ Built in digital TV -- A set-top box is a hardware device that allows a digital signal to be received, decoded and displayed on a television to enable the channels to be displayed on your analogue TV set. The digital TV is the transmission of television signals using digital rather than conventional analogue methods. This is where an individual owns a TV which is digital or owns a TV together with a set top box. This option, therefore, will include households with TV and free to air set top box or built in digital TV.<br />b. TV with pay TV decoder -- Pay TV decoder is more or less of a set top box as explained above. However, for pay TV, in most cases, it offers a number of channels that one has to pay a monthly fee to be able to view the programmes. This includes decoders such as DSTV, Star times, Zuku, Go-TV etc. regardless of the subscription amount. The pay TV decoder should have been subscribed at least once in the last 3 months.<br />c. Internet protocol TV (IPTV): This is a type of TV that receives the multimedia services over an IP based network managed to support the required level of high quality. The IPTV normally has got an in-built internet connection. Basically, IPTV is the most expensive and may range from 200,000 Ksh to more than a million. Be careful not to include those digital TVs that access internet through HDMI cables or through set top boxes that have internet interface (e.g. android boxes, Safaricom big box, etc.) in this option.<br />d. Analogue TV with no connection -- These are households who have a TV but after the digital migration they have never acquired any of the connections to enable them view the digital programmes. Hence, the TV is not connected to either a set top box or a decoder. The intention of this question is to know the number of households that have a TV but not able to view the channels due to various reasons. Note that households that have no TV at all, should be excluded here.</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns an internet protocol TV. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns an analog TV that cannot receive a digital signal <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Analog tv with no connection/signal</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">ii. Television: A television (TV) set is a device capable of receiving broadcast television signals, using means such as over the air, cable and satellite. The TV should be a stand-alone device and should be working at the time of the census night. It excludes TV functionality integrated with another device, such as a computer, mobile phone, car, alarm clock, etc. The intention of this question is to establish the number of households with at least one of the TV connections below by type. Since the digital migration, many households were left in the dark and most had to acquire either a free to air (FTA) set top box, digital TV, smart TV/internet protocol TV (IPTV) or a pay TV decoder. The responses for this are:</div><div class="i2">a. TV with free to air set top box/ Built in digital TV -- A set-top box is a hardware device that allows a digital signal to be received, decoded and displayed on a television to enable the channels to be displayed on your analogue TV set. The digital TV is the transmission of television signals using digital rather than conventional analogue methods. This is where an individual owns a TV which is digital or owns a TV together with a set top box. This option, therefore, will include households with TV and free to air set top box or built in digital TV.<br />b. TV with pay TV decoder -- Pay TV decoder is more or less of a set top box as explained above. However, for pay TV, in most cases, it offers a number of channels that one has to pay a monthly fee to be able to view the programmes. This includes decoders such as DSTV, Star times, Zuku, Go-TV etc. regardless of the subscription amount. The pay TV decoder should have been subscribed at least once in the last 3 months.<br />c. Internet protocol TV (IPTV): This is a type of TV that receives the multimedia services over an IP based network managed to support the required level of high quality. The IPTV normally has got an in-built internet connection. Basically, IPTV is the most expensive and may range from 200,000 Ksh to more than a million. Be careful not to include those digital TVs that access internet through HDMI cables or through set top boxes that have internet interface (e.g. android boxes, Safaricom big box, etc.) in this option.<br />d. Analogue TV with no connection -- These are households who have a TV but after the digital migration they have never acquired any of the connections to enable them view the digital programmes. Hence, the TV is not connected to either a set top box or a decoder. The intention of this question is to know the number of households that have a TV but not able to view the channels due to various reasons. Note that households that have no TV at all, should be excluded here.</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns an analog TV that cannot receive a digital signal. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a mobile phone or portable modem with internet access <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Internet through mobile phone/modem</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">iii. Internet through mobile phone/modem -- Refers to internet through a portable modem, mobile phone, USB wireless modem, tablet, etc. WIFI access available inside a home through a mobile connection, modem or any other device that has to use SIM card should be included as mobile broadband. The mobile phone or the modem usually has a SIM card that is registered with mobile networks operators including Airtel, Telkom, Safaricom, Finserve (Equitel), Faiba, etc.</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a mobile phone or portable modem with internet access. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member has a fixed internet connection in the home <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Fixed internet at home e.g., fiber, satellite dish, Lan, wi-fi</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">iv. Fixed internet at home e.g. fiber to the home/building, satellite dish, local area network (LAN), wifi -- This is where an individual has a fixed connection in the house including fibre to the home (FttH), cable modem, Integrated Services Digital Network (ISDN), Digital Subscriber Line (DSL), WIMAX, fixed CDMA and also satellite which passes through the radio waves and Very Small Aperture Terminal (VSAT) dish antenna with a transceiver normally located at the subscriber's premises etc. This is commonly available especially to those homesteads connected to fibre technology or have subscribed to services offered by companies such as ZUKU, Access Kenya, Safaricom, Faiba, etc</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member has a fixed internet connection in the home. 1 Yes 2 No 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Household member owns a desktop computer, laptop, or tablet <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Desktop computer/laptop/tablet</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a desktop computer, laptop, or tablet. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a bicycle <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Bicycle</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a bicycle. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a motorcycle <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Motorcycle</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a motorcycle. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a car <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Car</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a car. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a truck, lorry, bus, or three wheeler truck <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Truck/lorry/bus/three wheeler truck</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a truck, lorry, bus, or three wheeler truck. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a refrigerator <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Refrigerator</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a refrigerator. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a motorboat <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Motor boat</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a motorboat. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns an animal drawn cart <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Animal drawn cart</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns an animal drawn cart. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a canoe <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Canoes</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a canoe. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a tuk-tuk <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Tuk tuk</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a tuk-tuk. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns a tractor <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Tractor</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns a tractor. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Household member owns an ox plow <span class="h2">J: Ownership of household assets</span></p> <p>H-39. Does any member of this household own any of the following items?</p> <div class="i1">Ox-plough</div><div class="i2">[] 1. Yes<br />[] 2. No</div> <span class="em">29. Section J: Household assets</span></p> <p>29.1. Column H39: Ownership of household assets <br />The assets should at least be working at the time of census night (census night to be used as reference).</p> <p>Establish if any member of the household owns any of the following items and select the appropriate code. ICT household assets include: radio, TV with free to air set top box/digital TV, TV with pay TV decoder, internet protocol TV (IPTV), analogue TV with no connection/signal, internet through mobile phone/modem, fixed internet at home (e.g fiber to the home/building, satellite dish, local area network (LAN), wifi) and computer/laptop/tablet.</p> <div class="i1">v. Desktop computer/ laptop/ tablet: The intention of this question is to know the number of households who own these devices since individuals at home can improve their ICT skills and use the internet in particular advanced applications and services, which are more difficult to use on a smartphone. Computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer commonly referred to as "PC", workstations, server.</div><div class="i2">Other household assets include:<br />- Bicycle<br />- Motor cycle<br />- Car<br />- Truck/lorry/ bus/three wheeler truck<br />- Refrigerator<br />- Motor boat<br />- Animal drawn cart<br />- Canoes<br />- Tuk tuk<br />- Tractor<br />- Oxplough</div> Kenya 2019: Private households [discrepancies: none] This variable indicates whether a household member owns an ox plow. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Number of household members who migrated to another country for at least six months since 2004 <span class="h2">K: Emigrants</span></p> <p><span class="ital">Emigrants in the last 15 years since 2005.</span></p> <p>H-40. How many members of this household have migrated to another country since 2004 for at least 6 months?</p> <div class="i1">If none write "00" and end the interview.<br /><br />Number of emigrants _____</div> <span class="em">30. Section K: Emigrants</span> <br />Column H40 seeks information on any member of the household who may have migrated to another country since 2004. If there is any member of the household who travelled out of the country or crossed Kenyan borders, detailed information will be captured using the short emigrant questionnaire, even if the emigrant has since returned to Kenya.</p> <p>30.1. Short questionnaire on emigrants <br />This questionnaire collects information on any member of the household who may have migrated to another country since 2004. An emigrant is a person who has changed his/her country of residence to another country (country of destination/host country) for a period of at least six months, so that the country of destination effectively becomes his/her new country of usual residence.</p> <p>For instance, an emigrant is that person who has since migrated from Kenya and lives in another foreign country, either permanently or temporarily for whatever reason. A case can happen that an emigrant is found within the Kenyan borders on the census night (24th/25th August). He/she may either be visiting or may have come back to stay. Such a person will still be considered as an emigrant. Thus, as a special case, do enlist both cases in both the main census questionnaire and the emigrant short questionnaire. Other than these special cases, all other Kenyan emigrants must only be enlisted in the emigrant short questionnaire.</p> <p>30.2. Column E-01(a): Line number of respondent <br />Enter the line number of the person providing information about the emigrant in Column E-01(a). The line number will be retrieved from the household questionnaire. Enter "0" if the respondent did not spend the census night in this household and hence, not on the roster. Kenya 2019: Private households [discrepancies: type I none; type II trace] This variable indicates the number of household members who migrated to another country for at least six months since 2004. 0 0 1 1 2 2 3 3 4 4 5 5+ 9 NIU (not in universe) Other Household Variables -- HOUSEHOLD Household type _ _County <br />_ _Sub-County <br />_ _Division <br />_ _Location <br />_ _Sub-Location</p> <p>E. A. number _ _ <br />E. A. type _ <br />E. A. status _</p> <p>Household No. _ _ <br />Household type _ <br />Structure No. _ _ <br />Constituency _ _ <br />Ward _ _</p> <p>_ _ _ Males <br />_ _ _ Females <br />_ _ _ Others <br />_ _ _ Total household population Kenya 2019: All households This variable indicates the household type. 1 Conventional (private) 2 Group quarters Group Quarters Variables -- HOUSEHOLD Strata Kenya 2019: All households This variable indicates the strata. This is a 6-digit numeric variable with 0 implied decimal places Geography: Global Variables -- HOUSEHOLD Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. Technical Person Variables -- PERSON Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. Technical Person Variables -- PERSON Mother's location in household MOMLOC is a constructed variable that indicates whether or not the person's mother lived in the same household and, if so, gives the person number of the mother (see PERNUM). MOMLOC makes it easy for researchers to link the characteristics of children and their (probable) mothers. The method by which probable child-mother links are identified is described in PARRULE. The general design of MOMLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of MOMLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: MOMLOC identifies social relationships (such as stepmother and adopted mother) as well as biological relationships. The variable STEPMOM is designed to identify some of these social relationships. To restrict MOMLOC to biological mothers, such as for own children fertility estimation, MOMLOC should be reset to zero when STEPMOM is greater than zero. MOMLOC is a 3-digit numeric variable. Codes0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother Constructed Family Interrelationship Variables -- PERSON Father's location in household POPLOC is a constructed variable that indicates whether or not the person's father lived in the same household and, if so, gives the person number of the father (see PERNUM). POPLOC makes it easy for researchers to link the characteristics of children and their (probable) fathers. The method by which probable child-father links are identified is described in PARRULE. The general design of POPLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of POPLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: POPLOC identifies social relationships (such as stepfather and adopted father) as well as biological relationships. The variable STEPPOP is designed to identify some of these social relationships. To restrict POPLOC to biological mothers, such as for own children fertility estimation, POPLOC should be reset to zero when STEPPOP is greater than zero. POPLOC is a 3-digit numeric variable. Codes0 = No father of this person present in the household. 1 or higher = The person number of this person's father Constructed Family Interrelationship Variables -- PERSON Spouse's location in household SPLOC is a constructed variable that indicates whether or not the person's spouse lived in the same household and, if so, gives the person number (PERNUM) of the spouse. SPLOC makes it easy for researchers to link the characteristics of (probable) spouses. The method by which probable spouse-spouse links are identified is described in SPRULE. The general design of SPLOC and other constructed variables is modeled on the methods developed for IPUMS-USA "Family Interrelationships", but the details vary significantly. For more details on the construction of SPLOC, see the Comparability section of SPRULE and this paper on IPUMSI family linking methodology. SPLOC is a 3-digit numeric variable. Codes0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse Constructed Family Interrelationship Variables -- PERSON Rule for linking parent PARRULE describes the criteria by which the IPUMS International variables MOMLOC and POPLOC linked the person to a probable mother and/or father. IPUMS International establishes child-parent links according to five basic rules, and PARRULE gives the number of the rule that applied to the link in question. A link to any parent automatically generates a second link to that parent's spouse or partner, so only one rule is needed to describe both MOMLOC and POPLOC. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. 00 No parent of person in household 11 Link to head or spouse, unambiguous 12 Link to head or spouse, ambiguous 21 Child-Grandchild, within empirical child cap 22 Child-Grandchild, within constructed child cap 23 Child-Grandchild, exceeds child cap 31 Specified Other Relatives, within empirical child cap 32 Specified Other Relatives, within constructed child cap 33 Specified Other Relatives, exceeds child cap 41 Other Relatives, within empirical child cap 42 Other Relatives, within constructed child cap 51 Non-Relatives, within empirical child cap 52 Non-Relatives, within constructed child cap Constructed Family Interrelationship Variables -- PERSON Rule for linking spouse SPRULE explains the criteria by which the IPUMS-International variable SPLOC linked the person to his/her probable spouse. IPUMS International establishes spouse-spouse links according to five basic rules, and SPRULE gives the number of the rule that applied to the link in question. A sixth rule identifies sample-specific linking procedures only imposed in selected instances. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. 00 No spouse present 01 Rule 1: strong relationship pairing, couple adjacent 02 Rule 2: strong relationship pairing, couple not adjacent 03 Rule 3: weak relationship pairing, couple adjacent 04 Rule 4: weak relationship pairing, couple not adjacent 05 Rule 5: weak consensual union pairings 06 Rule 6: sample-specific rules (usually child-to-child) Constructed Family Interrelationship Variables -- PERSON Probable stepmother STEPMOM indicates whether a person's mother, as identified by MOMLOC, was most probably not the person's biological mother. Non-zero values of STEPMOM explain why it is probable that the person's mother was a step- or adopted mother. A value of 0 indicates no likely stepmother because (1) the mother identified in MOMLOC was probably the biological mother or (2) there is no mother of this person present in the household. The codes for STEPMOM are as follows: 0 = Biological mother or no mother of this person present in household. 1 = Mother has no children born or surviving. 2 = Child reports mother is deceased. 3 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner, stepchild/child-in-law). 4 = Mother reports no children in the home. 5 = Age difference between mother and child was less than 12 or greater than 54 years. 6 = Child exceeds known fertility of mother. In cases where more than one criterion for a likely stepmother is met, STEPMOM will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. In cases where a mother is linked to more children than she reports in CHBORN or CHSURV, the determination of which children to flag as probable stepchildren is based first on the strength of the child-mother pairing (see PARRULE), and then on the order of children in the household roster. Since most links to a given mother will be made at the same strength level, order will often be the decisive factor in flagging probable stepmother relationships. Users should note that there are many stepmothers and adopted mothers in the population that cannot be identified with information available in the censuses. Therefore, STEPMOM will always under-represent their actual number in the population. 0 Biological mother or no mother present 1 Mother has no children born or surviving 2 Child reports mother is deceased 3 Explicitly identified step relationship 4 Mother reports no children in the home 5 Age difference implausible 6 Child exceeds known fertility of mother Constructed Family Interrelationship Variables -- PERSON Probable stepfather STEPPOP indicates whether a person's father, as identified by POPLOC, was most probably not the person's biological father. Non-zero values of STEPPOP explain why it is probable that the person's father was a step- or adopted father. A value of 0 indicates no likely stepfather because (1) the father identified in POPLOC was probably the biological father or (2) there is no father of this person present in the household. The codes for STEPPOP are as follows: 0 = Biological father or no father of this person present in household. 1 = Child reports father is deceased. 2 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner; stepchild/child-in-law). 3 = Age difference between father and child was less than 12 or greater than 54 years. In cases where more than one criterion for a likely stepfather is met, STEPPOP will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepfathers and adopted fathers in the population that cannot be identified with information available in the censuses. Therefore, STEPPOP will always under-represent their actual number in the population. 0 Biological father or no father present 1 Child reports father is deceased 2 Explicitly identified step relationship 3 Age difference implausible 4 Spouse of mother 5 Identified as adopted 6 Surname difference -- male child or never-married female Constructed Family Interrelationship Variables -- PERSON Man with more than one wife linked POLYMAL indicates if a man had more than one wife linked to him in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The point of POLYMAL is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. 0 No more than one wife linked via SPLOC 1 More than one wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON Woman is second or higher order wife POLY2ND indicates if a woman was the second or higher order wife linked to a husband in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The variable does not suggest the actual marital order of wives, only their relative positions in the person order of the household as it was enumerated. The point of POLY2ND is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. 0 Person is not the 2nd or higher order wife linked via SPLOC 1 Person is the 2nd or higher order wife linked via SPLOC Constructed Family Interrelationship Variables -- PERSON Family unit membership FAMUNIT is a constructed variable indicating to which family within the household a person belongs. All persons related to the household head receive a 1 (see RELATE). Each secondary family or secondary individual receives a higher code. For purposes of FAMUNIT, secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). FAMUNIT is a 4-digit numeric variable. CodesIf there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on. Constructed Family Interrelationship Variables -- PERSON Number of own family members in household FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them. FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membership). The primary family is defined as all persons related to the head in the RELATE variable. Secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). 0001 1 family member present 0002 2 family members present 0003 3 family members present 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 or more persons Constructed Family Interrelationship Variables -- PERSON Number of own children in household NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children in household Constructed Family Interrelationship Variables -- PERSON Number of own children under age 5 in household NCHLT5 provides a count of the person's own children under age five living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more own children under age 5 in household 98 One or more children have unknown age Constructed Family Interrelationship Variables -- PERSON Age of eldest own child in household ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. ELDCH is top-coded at age 50 or older. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Age of youngest own child in household YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. YNGCH is top-coded at age 50 or older. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household Constructed Family Interrelationship Variables -- PERSON Relationship to household head [general version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown Demographic Variables -- PERSON Relationship to household head [detailed version] RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling's sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder, or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown Demographic Variables -- PERSON Age AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. 000 Less than 1 year 001 1 year 002 2 years 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100+ 999 Not reported/missing Demographic Variables -- PERSON Age, grouped into intervals AGE2 gives computed years of age grouped into intervals. 01 0 to 4 02 5 to 9 03 10 to 14 04 15 to 19 05 0 to 5 06 6 to 10 07 10 to 15 08 11 to 14 09 15 to 17 10 16 to 19 11 18 to 24 12 20 to 24 13 25 to 29 14 30 to 34 15 35 to 39 16 40 to 44 17 45 to 49 18 50 to 54 19 55 to 59 20 60 to 64 21 65 to 69 22 70 to 74 23 75 to 79 24 80 to 84 25 85+ 98 Unknown Demographic Variables -- PERSON Sex SEX reports the sex (gender) of the respondent. 1 Male 2 Female 9 Unknown Demographic Variables -- PERSON Marital status [general version] MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. 0 NIU (not in universe) 1 Single/never married 2 Married/in union 3 Separated/divorced/spouse absent 4 Widowed 9 Unknown/missing Demographic Variables -- PERSON Marital status [detailed version] MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. 000 NIU (not in universe) 100 Single/never married 110 Engaged 111 Never married and never cohabited 200 Married or consensual union 210 Married, formally 211 Married, civil 212 Married, religious 213 Married, civil and religious 214 Married, civil or religious 215 Married, traditional/customary 216 Married, monogamous 217 Married, polygamous 219 Married, spouse absent (historical samples) 220 Consensual union 300 Separated/divorced/spouse absent 310 Separated or divorced 320 Separated or annulled 330 Separated 331 Separated legally 332 Separated de facto 333 Separated from marriage 334 Separated from consensual union 335 Separated from consensual union or marriage 340 Annulled 350 Divorced 400 Widowed 410 Widowed or divorced 411 Widowed from consensual union or marriage 412 Widowed from marriage 413 Widowed from consensual union 420 Widowed, divorced, or separated 999 Unknown/missing Demographic Variables -- PERSON Polygamous union POLYGAM indicates whether the respondent was in a polygamous union and, in some samples, the number of wives or the rank order of the wife. 00 NIU (not in universe) 01 No, in monogamous union 02 Yes, in polygamous union 03 Man in polygamous union 04 Polygamous man, 2 wives 05 Polygamous man, 3 or more wives 06 Woman in polygamous union 07 Polygamous marriage, 2 wives 08 Polygamous marriage, 3 or more wives 09 First wife 10 Second wife 11 Third or higher order wife 99 Unknown/missing Demographic Variables -- PERSON Year of birth BIRTHYR gives the person's year of birth. 0000 NIU (not in universe) 1628 1628 1629 1629 1630 1630 1631 1631 1634 1634 1635 1635 1636 1636 1637 1637 1638 1638 1639 1639 1640 1640 1641 1641 1642 1642 1643 1643 1644 1644 1645 1645 1646 1646 1647 1647 1648 1648 1649 1649 1650 1650 1651 1651 1652 1652 1653 1653 1654 1654 1655 1655 1656 1656 1657 1657 1658 1658 1659 1659 1660 1660 1661 1661 1662 1662 1663 1663 1664 1664 1665 1665 1666 1666 1667 1667 1668 1668 1669 1669 1670 1670 1671 1671 1672 1672 1673 1673 1674 1674 1675 1675 1676 1676 1677 1677 1678 1678 1679 1679 1680 1680 1681 1681 1682 1682 1683 1683 1684 1684 1685 1685 1686 1686 1687 1687 1688 1688 1689 1689 1690 1690 1691 1691 1692 1692 1693 1693 1694 1694 1695 1695 1696 1696 1697 1697 1698 1698 1699 1699 1700 1700 1701 1701 1702 1702 1703 1703 1704 1704 1705 1705 1706 1706 1707 1707 1708 1708 1709 1709 1710 1710 1711 1711 1712 1712 1713 1713 1714 1714 1715 1715 1716 1716 1717 1717 1718 1718 1719 1719 1720 1720 1721 1721 1722 1722 1723 1723 1724 1724 1725 1725 1726 1726 1727 1727 1728 1728 1729 1729 1730 1730 1731 1731 1732 1732 1733 1733 1734 1734 1735 1735 1736 1736 1737 1737 1738 1738 1739 1739 1740 1740 1741 1741 1742 1742 1743 1743 1744 1744 1745 1745 1746 1746 1747 1747 1748 1748 1749 1749 1750 1750 1751 1751 1752 1752 1753 1753 1754 1754 1755 1755 1756 1756 1757 1757 1758 1758 1759 1759 1760 1760 1761 1761 1762 1762 1763 1763 1764 1764 1765 1765 1766 1766 1767 1767 1768 1768 1769 1769 1770 1770 1771 1771 1772 1772 1773 1773 1774 1774 1775 1775 1776 1776 1777 1777 1778 1778 1779 1779 1780 1780 1781 1781 1782 1782 1783 1783 1784 1784 1785 1785 1786 1786 1787 1787 1788 1788 1789 1789 1790 1790 1791 1791 1792 1792 1793 1793 1794 1794 1795 1795 1796 1796 1797 1797 1798 1798 1799 1799 1800 1800 1801 1801 1802 1802 1803 1803 1804 1804 1805 1805 1806 1806 1807 1807 1808 1808 1809 1809 1810 1810 1811 1811 1812 1812 1813 1813 1814 1814 1815 1815 1816 1816 1817 1817 1818 1818 1819 1819 1820 1820 1821 1821 1822 1822 1823 1823 1824 1824 1825 1825 1826 1826 1827 1827 1828 1828 1829 1829 1830 1830 1831 1831 1832 1832 1833 1833 1834 1834 1835 1835 1836 1836 1837 1837 1838 1838 1839 1839 1840 1840 1841 1841 1842 1842 1843 1843 1844 1844 1845 1845 1846 1846 1847 1847 1848 1848 1849 1849 1850 1850 1851 1851 1852 1852 1853 1853 1854 1854 1855 1855 1856 1856 1857 1857 1858 1858 1859 1859 1860 1860 1861 1861 1862 1862 1863 1863 1864 1864 1865 1865 1866 1866 1867 1867 1868 1868 1869 1869 1870 1870 1871 1871 1872 1872 1873 1873 1874 1874 1875 1875 1876 1876 1877 1877 1878 1878 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9999 Unknown Demographic Variables -- PERSON Month of birth BIRTHMO indicates the person's month of birth. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON Children ever born CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children surviving CHSURV reports the number of children born to a woman who were still living at the time of the census. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female children ever born CHBORNF indicates the number of female children ever born to a woman. Only live births are counted. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male children ever born CHBORNM indicates the number of male children ever born to a woman. Only live births are counted. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female children surviving CHSURVF indicates the number of female children ever born to a woman still living at the time of the census. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male children surviving CHSURVM indicates the number of male children ever born to a woman still living at the time of the census. 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Month of last birth LASTBMO indicates the month of birth of the last child born by the respondent. The data refer to live births. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Year of last birth LASTBYR indicates the year of birth of the last child born by the respondent. The data refer to live births. 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 Unknown 9999 NIU (not in universe) Fertility and Mortality Variables -- PERSON Sex of last birth LASTBSEX indicates the sex of a woman's most recent birth. 0 NIU (not in universe) 1 Male 2 Female 3 Both sexes (multiple births) 9 Unknown Fertility and Mortality Variables -- PERSON Number of children dead CHDEAD reports how many of the children ever born to a woman were no longer living at the time of the census. Women were to consider all live births by all fathers; they were to exclude still births. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown/missing 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of female children dead CHDEADFEM indicates the number of female children ever born to a woman who are no longer living. Stillbirths are not counted. It is possible to calculate total child deaths for samples that have both the "Female children ever born" and "Female children surviving" variables. That is not done in CHDEADFEM, which includes only the samples that directly reported the information in the appropriate form. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of male children dead CHDEADMALE indicates the number of male children ever born to a woman who are no longer living. Stillbirths are not counted. It is possible to calculate total child deaths for samples that have both the "Male children ever born" and "Male children surviving" variables. That is not done in CHDEADMALE, which includes only the samples that directly reported the information in the appropriate form. 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Mortality status of last birth LASTBMORT indicates the mortality status of the last child born to a woman. There is no constraint on how long ago the child may have been born. Only live births are considered. 0 NIU (not in universe) 1 Alive 2 Dead 9 Unknown Fertility and Mortality Variables -- PERSON Year of death of the last child born CHDEADYR indicates whether the woman's last child had died and, if so, the year of the death. Respondents were to exclude still births from consideration. Also see CHDEADMO. 0000 Last child not dead 1915 1915 1930 1930 1931 1931 1932 1932 1933 1933 1935 1935 1936 1936 1937 1937 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 9998 Unknown/missing 9999 NIU (not in universe) Fertility and Mortality Variables -- PERSON Month of death of the last child born CHDEADMO indicates whether the woman's last child had died and, if so, the month of the death. Respondents were to exclude still births from consideration. Also see CHDEADYR. 00 Last child not dead 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown/missing 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Mortality status of mother MORTMOT indicates whether the person's biological mother was still living at the time of the census. 1 Alive 2 Dead 7 Does not know 8 Missing 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Mortality status of father MORTFAT indicates whether the person's biological father was still living. 1 Alive 2 Dead 7 Does not know 8 Missing 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own children in household HOMECHILD indicates the number of surviving biological children living in the household with their mother (the respondent) at the time of the census. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own female children in household HOMEFEM indicates the number of female children born living in the household with their mother (the respondent). 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 17 17 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own male children in household HOMEMALE indicates the number of male children born living in the household with their mother (the respondent). 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own children living elsewhere AWAYCHILD indicates the number of surviving biological children not living in the household with their mother (the respondent) at the time of the census. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own female children living elsewhere AWAYFEM indicates the number of surviving biological female children not living in the household with their mother (the respondent). 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of own male children living elsewhere AWAYMALE indicates the number of surviving biological male children not living in the household with their mother (the respondent). 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Nativity status NATIVITY indicates whether the person was native-born or foreign-born. 0 NIU (not in universe) 1 Native-born 2 Foreign-born 9 Unknown/missing Nativity and Birthplace Variables -- PERSON Country of birth BPLCOUNTRY indicates the person's country of birth. 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11005 British Indian Ocean Territory 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11051 Ethiopia (including Eritrea) 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, other or n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15021 Upper Volta 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15081 Guinea-Bissau and Cape Verde 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15180 Canary Islands 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21200 St. Croix 21210 St. John 21220 St. Lucia 21230 St Thomas 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21991 Caribbean commonwealth, n.s. 21999 Caribbean, other or n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, other or n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, other or n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32042 India/Pakistan/Bangladesh/Sri Lanka 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32101 Pakistan/Bangladesh 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32999 South-Central Asia, other or n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33999 South-Eastern Asia, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34071 Israel/Palestine 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34111 West Bank 34112 Gaza Strip 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41991 Albania, Bulgaria, Czech, Hungary, Romania, Yugoslavia 41992 Central-Eastern Europe 41999 Eastern Europe, other or n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43121 Spain/Portugal 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43991 Gibraltar/Malta 43992 Portugal/Greece 43993 Italy, Holy See, San Marino 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44021 Belgium/Luxemburg 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44042 West Germany 44043 Germany/Austria 44044 Mecklenburg-Schwerin 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44991 Belgium, Denmark, Luxembourg, Netherlands 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (original 15) 49994 Other European Union (not original 15) 49999 Europe, other or n.s. 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53060 Federated States of Micronesia 53999 Micronesia, other or n.s. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 80000 AT SEA 90000 Other countries n.s. 99999 Unknown Nativity and Birthplace Variables -- PERSON Citizenship CITIZEN indicates the person's citizenship status within the country in which they were enumerated. 1 Citizen, not specified 2 Citizen by birth 3 Naturalized citizen 4 Not a citizen 5 Without citizenship, stateless 8 Unknown 9 NIU (not in universe) Nativity and Birthplace Variables -- PERSON Country of citizenship NATION indicates the person's country of citizenship. 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, other or n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt/United Arab Rep. 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21220 St. Lucia 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21999 Caribbean, other or n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, other or n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24021 Canada, First Nations 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, other or n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32990 Burma, India, Pakistan, Ceylon 32999 South-Central Asia, other or n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33991 Laos and Cambodia 33992 Malaysia and Singapore 33999 South-Eastern Asia, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41992 Central-Eastern Europe 41999 Eastern Europe, other or n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42121 Britain 42122 Scotland 42123 Wales 42990 Nordic countries 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44011 Austro-Hungarian 44020 Belgium 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44041 East Germany 44042 West Germany 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (Original 15) 49994 Other European Union 49999 Europe, other or n.s. 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53999 Micronesia, other or n.s. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 90000 Other countries n.s. 99998 No citizenship/nationality 99999 Unknown Nativity and Birthplace Variables -- PERSON Year of immigration YRIMM indicates the calendar year that a foreign-born person came to live in the country in which they were enumerated. 0000 NIU (not in universe) 1790 1790 1800 1800 1801 1801 1802 1802 1803 1803 1804 1804 1805 1805 1806 1806 1807 1807 1808 1808 1809 1809 1810 1810 1811 1811 1812 1812 1813 1813 1814 1814 1815 1815 1816 1816 1817 1817 1818 1818 1819 1819 1820 1820 1821 1821 1822 1822 1823 1823 1824 1824 1825 1825 1826 1826 1827 1827 1828 1828 1829 1829 1830 1830 1831 1831 1832 1832 1833 1833 1834 1834 1835 1835 1836 1836 1837 1837 1838 1838 1839 1839 1840 1840 1841 1841 1842 1842 1843 1843 1844 1844 1845 1845 1846 1846 1847 1847 1848 1848 1849 1849 1850 1850 1851 1851 1852 1852 1853 1853 1854 1854 1855 1855 1856 1856 1857 1857 1858 1858 1859 1859 1860 1860 1861 1861 1862 1862 1863 1863 1864 1864 1865 1865 1866 1866 1867 1867 1868 1868 1869 1869 1870 1870 1871 1871 1872 1872 1873 1873 1874 1874 1875 1875 1876 1876 1877 1877 1878 1878 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 9998 In transit 9999 Unknown Nativity and Birthplace Variables -- PERSON Province of birth, Kenya; [Level1: consistent boundaries, GIS] BPL1_KE indicates the person's province of birth within Kenya. Birthplace province codes from BPL1_KE are compatible with codes from GEO1_KE. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. 404001 Nairobi 404002 Central 404003 Coast 404004 Eastern 404005 Northeastern 404006 Nyanza 404007 Rift Valley 404008 Western 404097 Abroad 404098 Unknown 404099 NIU (not in universe) Nativity and Birthplace Variables -- PERSON District of birth, Kenya; [Level 2; consistent boundaries, GIS] BPL2_KE indicates the person's district of birth within Kenya. Birthplace district codes from BPL2_KE are compatible with codes from GEO2_KE. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. 404001047 Nairobi City 404002018 Nyandarua 404002019 Nyeri 404002020 Kirinyaga 404002022 Kiambu, Murang'a 404002099 Central Province, unknown district 404003001 Mombasa 404003002 Kwale 404003003 Kilifi 404003004 Tana River 404003005 Lamu 404003006 Taita-Taveta 404003099 Coast Province, unknown district 404004010 Marsabit 404004011 Isiolo 404004012 Meru, Tharaka-Nithi 404004015 Kitui 404004016 Machakos, Makueni, Embu 404004099 Eastern Province, unknown district 404005007 Garissa 404005008 Wajir 404005009 Mandera 404005099 Northeastern Province, unknown district 404006041 Siaya 404006042 Kisumu 404006043 Homa Bay, Migori 404006045 Kisii, Nyamira 404006099 Nyanza Province, unknown district 404007023 Turkana 404007024 West Pokot 404007025 Samburu 404007026 Trans Nzoia 404007027 Uasin Gishu 404007028 Elgeyo-Marakwet 404007029 Nandi 404007030 Baringo, Laikipia 404007032 Nakuru 404007033 Narok 404007034 Kajiado 404007035 Kericho, Bomet 404007099 Rift Valley Province, unknown district 404008037 Kakamega, Vihiga 404008039 Bungoma 404008040 Busia 404008099 Western Province, unknown district 404097097 Abroad 404098098 Unknown 404099099 NIU (not in universe) Nativity and Birthplace Variables -- PERSON Religion [general version] RELIGION indicates the person's religion, including "none." 0 NIU (not in universe) 1 No religion 2 Buddhist 3 Hindu 4 Jewish 5 Muslim 6 Christian 7 Other 9 Unknown Ethnicity and Language Variables -- PERSON Religion [detailed version] RELIGION indicates the person's religion, including "none." 0000 NIU (not in universe) 1000 No religion 1001 Atheist 1002 Agnostic 1003 Without religion 2000 Buddhist 3000 Hindu 4000 Jewish 5000 Muslim 5005 Ahmadis 5006 Sunni 6000 Christian 6001 Catholic (Roman or unspecified) 6002 Orthodox 6003 Protestant 6004 Evangelical protestant 6005 Pentecostal 6006 Adventist / Seventh-day adventist 6007 Anglican 6008 Assembly of God 6009 Baptist 6010 Church of the Nazarene 6011 Congregational 6012 Dutch Reformed 6013 Episcopalian 6014 Jehovah's Witnesses 6015 Latter Day Saints (Mormon) 6016 Lutheran 6017 Mennonite 6018 Methodist 6019 New Apostolic 6020 Presbyterian 6021 Zion Christian 6022 Moravian 6090 Other Christian, historical 6100 Other Christian, Armenia 6101 Armenia apostolic 6102 Nestorian 6103 Molokai 6104 Other Christian, Austria 6105 Old Catholic 6106 Protestant, Augsburg confession 6107 Protestant, Westminster confession 6108 Protestant, Helvetic confession 6109 Greek Oriental 6110 Armenian Apostolic 6111 Other Protestant 6112 Christian Community for renewal 6113 Christian Community, not specified 6114 Other Christian, Benin 6115 Other Christian 6116 Celestial 6117 Other Christian, Brazil 6118 Christian Congregation of Brazil 6119 Brazilian Catholic Apostolic 6120 Brazil for Christ 6121 Foursquare Gospel 6122 Universal of the Kingdom of God 6123 House of the Blessing 6124 House of Prayer 6125 God is Love 6126 Maranata 6127 Other Christian, Brazil 1991 6128 Undetermined Protestant 6129 Other traditional Protestant 6130 Neo-Christian 6131 Other Neo-Christian 6132 Undetermined Christian 6133 Other Christian, Brazil 2000 6134 Other Catholic 6135 Renewed Evangelical Protestant without institutional ties 6136 Pentecostal Evangelical without institutional ties 6137 New Life Evangelical Protestant Pentecostal 6138 Evangelical Protestant Biblical Revival Pentecostal 6139 Chain Of Prayer Pentecostal 6140 Undetermined Evangelical Protestant 6141 Religion Of God 6142 Christian without institutional ties 6143 Other Christian, Brazil 2010 6144 Salvation Army 6145 Other Christian, Canada 6146 Other Catholic 6147 United Church 6148 Protestant, not specified 6149 Other Protestant 6150 Other Christian, Cameroon 6151 Other Christian, Fiji 6152 Christian undefined 6153 Church of England 6154 Gospel Hall and Brethern 6155 Christian Mission Fellowship (CMF) or Every Home 6156 Salvation Army 6157 All Nations Christian Fellowship 6158 Apostles Gospel Outreach Fellowship 6159 Christian Outreach Centre 6160 Other Christian 6161 Other Christian, Germany 6162 Oriental Christian 6163 Other Christian, Ghana 6164 Other Christian, Iran 6165 Assyrian or Chaldean 6166 Armenian 6167 Other Christians 6168 Other Christian, Indonesia 6169 Other Christian 6170 Protestant/Other Christian 6171 Other Christian, Ireland 6172 Church of Ireland 6173 Church of Scotland 6174 Independent 6175 Unitarian 6176 Salvation Army 6177 Free Church 6178 Brethren 6179 Christian Brethren 6180 Plymouth Brethren 6181 Quaker 6182 Other Christians 6183 Other Christian, Ivory Coast 6184 Other Christian, Jamaica 6185 Brethren 6186 Church of God 6187 Church of God of Prophecy 6188 Other Church of God 6189 United Church 6190 Salvation Army 6191 New Testament 6192 Disciples of Christ 6193 Other Christian, Mauritius 6194 Christian Tamil 6195 Salvation and Healing Mission 6196 Voice of Deliverance 6197 Other Christian 6198 Other Christian, Mexico 6199 Anabaptist 6200 Calvinist 6201 Cuaquera 6202 Disciples of Christ 6203 Christian Friendship Church 6204 Prayer House Church 6205 Faith Center 6206 Agape Force Church 6207 Alpha and Omega Church 6208 Living Water Church 6209 Apostolic Church 6210 Church of God 6211 Church of God of Prophecy 6212 Complete Gospel Church 6213 Evangelical Siblings Church 6214 Upper Room Church 6215 Pentecostal Indigenous Church 6216 Angular Stone Voice Church 6217 Pentecostal Missionary 6218 Christian 6219 Christian Societies 6220 Evangelical 6221 Evangelical Societies 6222 New Testament Evangelical 6223 Pentecostal 6224 Pentecostal Societies 6225 Independent Pentecostal 6226 Evangelical Christian Societies 6227 Pentecostal Christian Societies 6228 Evangelical Pentecostal Societies 6229 Evangelical Pentecostal Christian Societies 6230 Soldiers of Christ's Cross Church 6231 Tabernacle 6232 Traditionalists 6233 Other Evangelical Pentecostal Societies 6234 Pentecostal not clearly specified 6235 Living God, Light of the World 6236 Christian and Missionary Alliance 6237 Non-Pentecostal Apostolic 6238 Evangelical Associations 6239 Biblical 6240 Confraternities 6241 Christ Church 6242 Peace Grace and Misericordia Church 6243 Open Bible Church 6244 Holiness Church 6245 Evangelical Salem Church 6246 Beautiful Woman Dressed in the Sun 6247 Messianic Church 6248 Evangelical Ministers 6249 Evangelical Missionaries 6250 Evangelical Movements 6251 New Jerusalem 6252 World Vision Church 6253 Evangelical not clearly specified 6254 Biblical - non-evangelicals 6255 Other Christians not clearly specified 6256 Assumptionist 6257 Carmelite 6258 Claretian 6259 Conception Franciscan 6260 Maronite Diocese of Mexico 6261 Dominican 6262 Servants of Mary Immaculate 6263 Franciscan 6264 Guadalupan 6265 Daughters of the Immaculate Conception 6266 Jesuit 6267 Legionaries of Christ 6268 Divine Word Missionary 6269 Pauline 6270 Sacred Heart 6271 Saint Joseph of Tarbes 6272 Servant of the Lord and the Virgin 6273 Servant of Jesus 6274 Greek Catholic Church 6275 Reformed Roman Catholic Church 6276 Mexican National Catholic Church 6277 Tridentine Latin Rite Catholic Church 6278 Priestly Society Trento 6279 Mexican Catholic Union of Trento 6280 Anabaptist / Memnonite 6281 Anglican / Episcopal 6282 House of Prayer 6283 Center of Faith, Hope and Love of the Missionary Revival Crusade 6284 Center of Faith, Hope and Love Agape Force 6285 Salvation Army 6286 Independent Pentecostal Fellowship 6287 Upper Chamber Church 6288 Faith Apostolic Church of Jesus Christ 6289 Spiritual Christian Church 6290 Pentecostal Evangelical Christian Church 6291 Interdenominational Christian Church 6292 Church of God Full Gospel in Mexico 6293 Church of Jesus Christ on the Rock 6294 Christ Evangelical Pentecostal Church Rock of my Salvation 6295 Mexican Church of Christ's Gospel Pentecost 6296 United Pentecostal Church of Mexico 6297 Universal Church of the Kingdom of God 6298 Only Christ Savior Christian Church 6299 Independent Evangelical Pentecostal Movement 6300 Prince of Peace 6301 National Union of Evangelical Christian Churches (UNICE) 6302 Union of Independent Evangelical Churches 6303 Other associations Pentecostal 6304 Church of the Living God, Pillar and Support of Truth, the Light of the World 6305 Bible Church 6306 Interdenominational Christian Church in Mexico 6307 Church of Christ 6308 Honey Church of Christ 6309 Independent Evangelical Church in Mexico 6310 Renewed Church of Jesus Christ and the Apostles of Divine Love 6311 Other Christian and Evangelical associations without Pentecostal support 6312 Faith Christian Church 6313 Traditional Apostolic Catholic Holy Church Mexico-USA 6314 Mexican Apostolic Catholic Church 6315 Elias 6316 Spiritualistic 6317 Spiritualist 6318 Marian Trinitarian Spirituality 6319 Spirituality of the Third Age 6320 Christian Spiritual 6321 Judiciary Society Reign of Leonardo Alcalá Leos 6322 Spirituality for the Divine Master and the purity of Mary 6323 Light and Hope 6324 Holy Spirit, Purity, Love and Light 6325 Christian Science 6326 Neo-Israelite Jewish Syncretic Movements 6327 Other Christian, Netherlands 6328 Reformed Churches in The Netherlands 6329 Other Reformed 6330 Other Christian, Papua New Guinea 6331 Asian Pacific Christian Mission 6332 Asutalian Church 6333 Bamu River Mission 6334 Christian Brethren Church of PNG 6335 Christian Mission of Many Lands 6336 Christian Revival Crusade 6337 Christain Union Mission 6338 Church of Christ of PNG 6339 Faith mission 6340 Four Square Gospel Mission 6341 Kwato Church 6342 Life Center 6343 Lighthouse church 6344 New Guinea Gospel Mission 6345 New Life Mission 6346 New tribes Mission 6347 Paliau Christian Native Church 6348 Rhema Fellowship 6349 Salvation Army 6350 Sovereign Grace 6351 United Church 6352 Wewak Fellowship 6353 Western Highland 6354 Independent 6355 Plymouth Brethern 6356 Tiliba Mission 6357 Tokarara Christian Fellowship 6358 Village Mission 6359 Other Christian 6360 Other Christian, Paraguay 6361 Christian Community 6362 Free Brothers 6363 Church of God 6364 Church of God of Prophecy 6365 New testament 6366 God is love 6367 Universal Church of the Kingdom of God 6368 People of God 6369 Family worship center 6370 Pseudo-Christian groups 6371 Other Christian, Philippines 6372 Aglipay 6373 Bible Christian Committees 6374 Born-again Christian 6375 Bread of Life Ministries 6376 Cathedral of Praise, Incorporated 6377 Charismatic Full Gospel Ministries 6378 Christ the Living Stone Fellowship 6379 Christian and Missionary Alliance 6380 Christians Missions 6381 Christian Reformed Church in the Philippines, Incorporated 6382 Church of Christ 6383 Crusaders of the Divine Church of Christ, Incorporated 6384 Evangelical Christian Outreach Foundation 6385 Evangelical Free Church 6386 Filipino Assemblies of the First Born Inc. 6387 Foursquare Gospel 6388 Free Believers in Christ Fellowship 6389 Free Mission in the Philippines Inc. 6390 God World Mission 6391 Good News Christian Churches 6392 IEMELIF Reform Movement 6393 Iglesia Evangelista Methodista en Las 6394 Iglesia Evangelica Unida de Cristo 6395 Iglesia ni Cristo 6396 Iglesia sa Dios Espiritu Santo, Incorporated 6397 Jesus Christ Saves Global Outreach 6398 Jesus is Alive Community, Incorporated 6399 Jesus is Lord Church 6400 Jesus Reigns Ministries 6401 Love of Christ International Ministries 6402 Other Evangelical 6403 Other Evangelical Church 6404 Other Protestants 6405 Philippine Ecumenical Christian Church 6406 Philippine Evangelical Mission 6407 Philippine Grace Gospel Fellowship 6408 Philippines Benevolent Missionaries 6409 Philippines General Council of the Assemblies of God 6410 Potter's House Christian Center 6411 Salvation Army Philippines 6412 Take the Nation for Jesus Global Ministries (Corpus Christi) 6413 UNIDA Evangelical Church 6414 Union Espiritista Cristiana de Filipinas, Incorporated 6415 United Church of Christ in the Philippines 6416 United Evangelical Church of the Philippines (Chinese) 6417 Victory Chapel Christian Fellowship 6418 Wesleyan Church 6419 World Missionary Evangelism 6420 Worldwide Church of God 6421 Zion Christian Community Church 6422 Other Christian, Portugal 6423 Other Christian, Romania 6424 Greek Catholic 6425 Reformed Church 6426 Evangelic of Augustan Confession 6427 Evangelic Synodo-Presbyterian 6428 Christian of Old Rite 6429 Christian by Gospel 6430 Evangelic 6431 Other Christian, Rwanda 2002 6432 Other Christian, Sierra Leone 6433 Other Christian, Slovak Republic 6434 Old Catholic 6435 Greek Catholic 6436 Christian Reformed 6437 Other Christian, South Africa 6438 Reformed 6439 International Fellowship of Christian Churches 6440 Apostolic Faith Mission of SA 6441 Other Apostolic Churches 6442 Pinkster Protestant Church 6443 Afrikaanse Protestant Church 6444 Full Gospel Church of God in Southern Africa 6445 Pentecostal Churches 6446 Salvation Army 6447 Bandla Lama Nazaretha 6448 African Methodist Episcopal Church 6449 St John's Apostolic Church 6450 International Pentecost Church 6451 Ethiopian type churches 6452 Ethnic churches 6453 Other African Independent Churches 6454 Other Christian Churches 6455 Other Catholic Churches 6456 Other Pentecostal Churches 6457 Other Orthodox Churches 6458 Other African Apostolic churches 6459 Other Assemblies 6460 Christian Scientist 6461 Christian Centres 6462 Other Evangelical Churches 6463 Other Charismatic Churches 6464 Just a Christian or non-denominational 6465 Other 6466 Other Christian, Suriname 6467 Other Christian 6468 Other Christian, Saint Lucia 6469 Church of God 6470 Other Christian, Senegal 6471 Other Christian 6472 Other Christian, Switzerland 6473 Other protestant churches and communities 6474 Christ-Catholic church 6475 Other Christian communities 6476 Other Christian, Trinidad and Tobago 6477 Church of God 6478 African Methodist Espiscopalians 6479 Brethren, Christian or Plymouth 6480 Church of Christ 6481 Gospel Hall or Gospel Missionary 6482 Nazarenes 6483 Pilgrim Holiness 6484 Ethiopian Orthodox 6485 Open Bible Church 6486 Assemblies of Yahweh 6487 Evangelical Church of West Indies 6488 Christadelphian 6489 Full Gospel Fellowship 6490 Dutch Reform 6491 Christian Brotherhood Assembly 6492 Other Christian, Uganda 6493 Other Christian 6494 Salvation Army 6495 Other Christian non-Catholic, Uruguay 6496 Other Christian non-Catholic, Guatemala 6497 Other Christian, Togo 7000 Other 7001 Bahai 7002 Sikh 7003 Rastafarian 7100 Other, Armenia 7101 Pagan 7102 Shar-fadinian 7103 Other, Austria 7104 Unification Church, Austria 7105 Other, Benin 7106 Traditional 7107 Vodoun 7108 Other, Botswana 7109 Badimo 7110 Other, Brazil 7111 Spiritist 7112 Kardecist Spiritist 7113 Afro Spiritist 7114 Mediumistic Spiritist 7115 Umbandist Mediumistic 7116 Candomblecist Mediumistic 7117 Other Afro-Brazilian 7118 Oriental, Brazil 7119 New Oriental 7120 Oriental Seicho No-le 7121 Other Oriental, Brazil 7122 Esoteric, Brazil 7123 Indigenous, Brazil 7124 Other minority groups, Brazil 7125 Other, Burkina Faso 7126 Animist 7127 Other, Cameroon 7128 Animist 7129 Other, Canada 7130 Eastern religions, Canada 7131 Other, Chile 7132 Theosophism 7133 Shintoism 7134 Other, Ethiopia 7135 Traditional 7136 Other, Ethiopia 7137 Other, Fiji 7138 Confucian 7139 Kabir Panthi 7140 Satya Sai Baba 7141 Bahai 7142 Other non-Christian, Fiji 7143 Other, Germany 7144 Other, Germany 7145 Other, Ghana 7146 Traditional, Ghana 7147 Other, Guinea 7148 Animist 7149 Other, Guinea 7150 Other, Haiti 7151 Voodoo 7152 Other, India 7153 Jainism 7154 Zoroastrianism 7155 Other, India 7156 Other, Indonesia 7157 Confucianism 7158 Other, Indonesia 7159 Other, Iran 7160 Zoroastrian 7161 Other, Iran 7162 Other, Ivory Coast 7163 Animist 7164 Harrist 7165 Other, Jamaica 7166 Muslim/Hindu 7167 Other, Israel 7168 Druse 7169 Other, Israel 7170 Other, Laos 7171 Animist 7172 Other, Liberia 7173 Traditional 7174 Other, Malaysia 7175 Confucianism/Taoism 7176 Tribal/Folk religion, Malaysia 7177 Other, Mali 7178 Animist 7179 Other, Mexico 7180 Brahmanism 7181 Hare Krishna 7182 Shintoism 7183 Taoism 7184 Mexican Movements 7185 Ananda Marga 7186 Church of Scientology 7187 Masons 7188 Raelian Movement 7189 New Age Movement 7190 Neoisraelites 7191 Occultists 7192 Palmar of Troya 7193 Rose Cross 7194 Theosophism 7195 Spiritualist Special Keys 7196 Onkaranada Center 7197 Confucianism 7198 Shia 7199 Universal Great Brotherhood 7200 Esoteric Science 7201 Gnosticism 7202 Metaphysics 7203 Wicca 7204 Shamanism 7205 The Custom 7206 Mexicayotl 7207 Restorative Confederate Movement of Anahuac Culture 7208 African Origin 7209 Indigenous Religions 7210 Growing in Grace 7211 Eckankar 7212 Transcendental Meditation 7213 Mission Branch 7214 Children of God 7215 Sri Sathya Sai Baba 7216 Other religions from Asia 7217 Ethnic roots 7218 Afro roots 7219 Popular cults 7220 Other new religious movements 7221 Other, Nepal 7222 Kirat 7223 Jain 7224 Garaute 7225 Tap jura 7226 Bon 7227 Prakriti 7228 Other, Nigeria 7229 Traditional 7230 Other, Pakistan 7231 Ahmadi 7232 Parsi 7233 Scheduled caste 7234 Other, Paraguay 7235 Philosophical revelations 7236 Indigenous religion 7237 Reyukai 7238 Other, Paraguay 7239 Other, Philippines 7240 Door of Faith 7241 Faith Tabernacle Church (Living Rock Ministries) 7242 Iglesia Filipina Independiente 7243 International One Way Outreach 7244 Miracle Life Fellowship International 7245 Miracle Revival Church of the Philippines 7246 Philippine Good News Ministries 7247 Philippine Missionary fellowship 7248 Things to Come 7249 Way of Salvation 7250 Word of the World 7251 Word International Ministries 7252 Tribal Religions, Philippines 7253 Other, Romania 7254 Unitarian 7255 Armenian 7256 Mosaic 7257 Other, Romania 7258 Other, Rwanda 7259 Traditional religion, Rwanda 7260 Other, Rwanda 7261 Other, Sierra Leone 7262 Traditional religion, Sierra Leone 7263 Other, South Africa 7264 African traditional belief 7265 Taoist 7266 Confucian 7267 New Age 7268 Winti 7269 Javanism 7270 Other non-Christian, S. Africa 7271 Other, Suriname 7272 Javanism 7273 Traditional 7274 Winti 7275 Other, Thailand 7276 Confucian 7277 Other, Trinidad and Tobago 7278 Pocamania or Shango 7279 Orisha 7280 Other, Uganda 7281 Traditional religion 7282 Mammon 7283 Other non-Christian, Uganda 7284 Other, United Kindom 7285 Other, Uruguay 7286 Umbanda/other Afro-American 7287 Other, Uruguay 7288 Other, Vietnam 7289 Cao Dai 7290 Cham Brahmin 7296 Other, Togo 7297 Animist 7900 Other, not elsewhere classified 9999 Unknown Ethnicity and Language Variables -- PERSON School attendance SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census. 0 NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing Education Variables -- PERSON Educational attainment, international recode [general version] EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. 0 NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown Education Variables -- PERSON Educational attainment, international recode [detailed version] EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. 000 NIU (not in universe) 100 Less than primary completed (n.s.) 110 No schooling 120 Some primary completed 130 Primary (4 yrs) completed 211 Primary (5 yrs) completed 212 Primary (6 yrs) completed 221 Lower secondary general completed 222 Lower secondary technical completed 311 Secondary, general track completed 312 Some college completed 320 Secondary or post-secondary technical completed 321 Secondary, technical track completed 322 Post-secondary technical education 400 University completed 999 Unknown/missing Education Variables -- PERSON Years of schooling YRSCHOOL indicates the highest grade/level of schooling the person had completed, in years. Only formal schooling is counted. YRSCHOOL accounts for the number of years of study, regardless of the track or kind of study. Information on degree and/or technical track is available in EDATTAIN. Years of schooling for Israel, categorized into intervals, are given in YRSCHOOL2. Users should pay close attention to the top-codes in each sample, as discussed in the comparability section. 00 None or pre-school 01 1 year 02 2 years 03 3 years 04 4 years 05 5 years 06 6 years 07 7 years 08 8 years 09 9 years 10 10 years 11 11 years 12 12 years 13 13 years 14 14 years 15 15 years 16 16 years 17 17 years 18 18 years or more 90 Not specified 91 Some primary 92 Some technical after primary 93 Some secondary 94 Some tertiary 95 Adult literacy 96 Special education 98 Unknown/missing 99 NIU (not in universe) Education Variables -- PERSON Educational attainment, Kenya EDUCKE indicates the person's educational attainment in Kenya in terms of the level of schooling completed. 00 None 01 Pre-primary 02 Standard 1, incomplete 03 Standard 1 04 Standard 2 05 Standard 3 06 Standard 4 07 Standard 5 08 Standard 6 09 Standard 7 10 Standard 8 11 Form 1 12 Form 2 13 Form 3 14 Form 4 15 Form 5 16 Form 6 21 Basic literacy 22 Adult basic education 23 Adult secondary education 30 Youth polytechnic 40 University, completion unspecified 41 University, incomplete 42 University, complete 43 College (training schools) 44 University, undergraduate 45 University, Masters or PhD 50 Madrassa 98 Unknown 99 NIU (not in universe) Education Variables -- PERSON Activity status (employment status) [general version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 0 NIU (not in universe) 1 Employed 2 Unemployed 3 Inactive 9 Unknown/missing Work Variables -- PERSON Activity status (employment status) [detailed version] EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". 000 NIU (not in universe) 100 Employed, not specified 110 At work 111 At work, and 'student' 112 At work, and 'housework' 113 At work, and 'seeking work' 114 At work, and 'retired' 115 At work, and 'no work' 116 At work, and other situation 117 At work, family holding, not specified 118 At work, family holding, not agricultural 119 At work, family holding, agricultural 120 Have job, not at work in reference period 130 Armed forces 131 Armed forces, at work 132 Armed forces, not at work in reference period 133 Military trainee 140 Marginally employed 200 Unemployed, not specified 201 Unemployed 6 or more months 202 Worked fewer than 6 months, permanent job 203 Worked fewer than 6 months, temporary job 210 Unemployed, experienced worker 220 Unemployed, new worker 230 No work available 240 Inactive unemployed 300 Inactive (not in labor force) 301 Unavailable jobseekers 302 Available potential jobseekers 310 Housework 320 Health reasons, unable to work, or disabled 321 Permanent disability 322 Temporary illness 323 Disabled or imprisoned 330 In school 340 Retirees and living on rent 341 Living on rents 342 Living on rents or pension 343 Retirees/pensioners 344 Retired 345 Pensioner 346 Non-retirement pension 347 Disability pension 348 Retired without benefits 350 Elderly 351 Elderly or disabled 360 Institutionalized 361 Prisoner 370 Intermittent worker 371 Not working, seasonal worker 372 Not working, occasional worker 380 Other income recipient 390 Inactive, other reasons 391 Too young to work 392 Dependent 999 Unknown/missing Work Variables -- PERSON Labor force participation LABFORCE is a dichotomous variable identifying whether a person participated in the labor force. Labor force participation generally means working or seeking work within a specified reference period. For most samples LABFORCE is a recode of EMPSTAT (employment status). A consistent lower age universe of 15 or older has been applied to increase comparability across samples. Full detail is retained in EMPSTAT, which should be used for any study of child labor. 1 No, not in the labor force 2 Yes, in the labor force 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Occupation, ISCO general OCCISCO records the person's primary occupation, coded according to the major categories in the International Standard Classification of Occupations (ISCO) scheme for 1988. For someone with more than one job, the primary occupation is typically the one in which the person had spent the most time or earned the most money. 01 Legislators, senior officials and managers 02 Professionals 03 Technicians and associate professionals 04 Clerks 05 Service workers and shop and market sales 06 Skilled agricultural and fishery workers 07 Crafts and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 10 Armed forces 11 Other occupations, unspecified or n.e.c. 97 Response suppressed 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Occupation, unrecoded OCC records the person's primary occupation, classified according to the system used by the respective national census office at the time. For someone with more than one job, the primary occupation is usually the one in which the person spent the most time or earned the most money, although this may not have been explicit in the instructions for a specific census. To ensure confidentiality, very small occupations are recoded to a residual category indicating the persons had an occupation, but the job title is not identified. The number of cases recoded should be too small to affect analyses. OCC is a 4-digit numeric variable. Some samples use fewer than 4 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_OCC3 - Occupation [3 digit] Argentina 1980 - see Variable: AR1980A_OCC - Occupation Argentina 1991 - see Variable: AR1991A_OCC - Occupation Argentina 2001 - see Variable: AR2001A_OCC4 - Occupation (4-digits) Armenia 2011 - see Variable: AM2011A_OCC - Occupation Austria 1971 - see Variable: AT1971A_OCCSM - Occupation of supporter: sub-major groups Austria 1981 - see Variable: AT1981A_OCCSM - Occupation of supporter: sub-major groups Austria 1991 - see Variable: AT1991A_OCCSM - Occupation of supporter: sub-major groups Austria 2001 - see Variable: AT2001A_OCCSM - Occupation of supporter: sub-major groups Belarus 1999 - see Variable: BY1999A_OCC2 - Occupation, 2 digits Belarus 2009 - see Variable: BY2009A_OCC - Occupation Benin 1979 - see Variable: BJ1979A_OCC - Occupation (2-digits) Benin 1992 - see Variable: BJ1992A_OCC3 - Occupation (3-digits) Benin 2002 - see Variable: BJ2002A_OCC - Occupation (3-digits) Benin 2013 - see Variable: BJ2013A_OCC - Occupation (3-digit) Bolivia 1976 - see Variable: BO1976A_OCC2 - Occupation, 2 digits Bolivia 1992 - see Variable: BO1992A_OCC - Occupation Bolivia 2001 - see Variable: BO2001A_OCC - Occupation, 3 digits Bolivia 2012 - see Variable: BO2012A_OCC2 - Occupation (3 digit) Botswana 1981 - see Variable: BW1981A_OCC - Occupation Botswana 1991 - see Variable: BW1991A_OCC - Occupation (last 30 days) Botswana 2001 - see Variable: BW2001A_OCC - Occupation in the past 7 days, 3 digit Botswana 2011 - see Variable: BW2011A_OCC - Occupation, 3-digits Brazil 1960 - see Variable: BR1960A_USUALOCC - Usual occupation Brazil 1970 - see Variable: BR1970A_MAINOCC - Principal occupation Brazil 1980 - see Variable: BR1980A_OCC - Occupation Brazil 1991 - see Variable: BR1991A_OCC - Occupation Brazil 2000 - see Variable: BR2000A_OCC - Occupation, 4 digits Brazil 2010 - see Variable: BR2010A_OCC - Occupation held from July 25 to July 31, 2010 Burkina Faso 1985 - see Variable: BF1985A_OCC - Principal occupation Burkina Faso 1996 - see Variable: BF1996A_OCC - Principal occupation Cambodia 1998 - see Variable: KH1998A_OCC - Occupation Cambodia 2004 - see Variable: KH2004A_OCC3 - Occupation (3-digits) Cambodia 2008 - see Variable: KH2008A_OCC - Occupation Cambodia 2013 - see Variable: KH2013A_OCC - Occupation (3-digits) Cambodia 2019 - see Variable: KH2019A_OCC1 - Occupation, 1-digit Cameroon 1976 - see Variable: CM1976A_OCC2 - Occupation (2 digits) Cameroon 2005 - see Variable: CM2005A_OCC - Occupation Canada 1971 - see Variable: CA1971A_OCC - Occupation Canada 1981 - see Variable: CA1981A_OCC - Occupation (1981 classification basis) Canada 1991 - see Variable: CA1991A_OCC80 - Occupation (1980 classification basis) Canada 2001 - see Variable: CA2001A_NOCS01P - Occupation (2001 national occupational classification for statistics) Canada 2011 - see Variable: CA2011A_OCC - Occupation Chile 1960 - see Variable: CL1960A_OCC - Occupation Chile 1970 - see Variable: CL1970A_OCC3 - Occupation (3-digit) Chile 1982 - see Variable: CL1982A_OCC3 - Occupation (3-digit) Chile 1992 - see Variable: CL1992A_OCC3 - Occupation (3-digit) Chile 2002 - see Variable: CL2002A_OCC - Occupation China 1982 - see Variable: CN1982A_OCC - Occupation China 1990 - see Variable: CN1990A_OCC - Occupation China 2000 - see Variable: CN2000A_OCC - Occupation (2-digit) Colombia 1964 - see Variable: CO1964A_OCC2 - Occupation (COTA, 4 digits) Colombia 1973 - see Variable: CO1973A_OCC - Occupation last week Costa Rica 1973 - see Variable: CR1973A_OCC3 - Occupation, 3 digits Costa Rica 1984 - see Variable: CR1984A_OCC - Occupation, 3 digits Costa Rica 2000 - see Variable: CR2000A_OCC3 - Occupation, 3 digits Costa Rica 2011 - see Variable: CR2011A_OCC - Occupation, 2-digit Cuba 2002 - see Variable: CU2002A_OCC - Occupation Cuba 2012 - see Variable: CU2012A_OCC3 - Main occupation (3-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_OCC2 - Current occupation (2-digit) Dominican Republic 1960 - see Variable: DO1960A_OCC - Occupation Dominican Republic 1970 - see Variable: DO1970A_OCC1 - Current occupation, 3 digits Dominican Republic 1981 - see Variable: DO1981A_OCC - Occupation Dominican Republic 2002 - see Variable: DO2002A_OCC - Occupation Dominican Republic 2010 - see Variable: DO2010A_OCC - Occupation Ecuador 1962 - see Variable: EC1962A_OCC - Occupation Ecuador 1974 - see Variable: EC1974A_OCC3 - Occupation, three digits Ecuador 1982 - see Variable: EC1982A_OCC3 - Occupation, 3 digits Ecuador 1990 - see Variable: EC1990A_OCC3 - Occupation, 3 digits Ecuador 2001 - see Variable: EC2001A_OCC - Occupation, 3 digits Ecuador 2010 - see Variable: EC2010A_OCC3 - Occupation (3 digits, ISCO 08) Egypt 1986 - see Variable: EG1986A_OCC3 - Occupation (3-digit) Egypt 2006 - see Variable: EG2006A_OCC - Primary occupation, 3-digit El Salvador 1992 - see Variable: SV1992A_OCC - Occupation (3-digit) El Salvador 2007 - see Variable: SV2007A_OCC3DIG - Occupation (3-digit) Ethiopia 1984 - see Variable: ET1984A_OCC2 - Occupation (2-digit) Ethiopia 1994 - see Variable: ET1994A_OCC - Occupation Fiji 1976 - see Variable: FJ1976A_OCC - Occupation Fiji 1986 - see Variable: FJ1986A_OCC - Occupation Fiji 1996 - see Variable: FJ1996A_OCC3 - Occupation (3 digits) Fiji 2007 - see Variable: FJ2007A_OCC3 - Occupation, 3 digits Fiji 2014 - see Variable: FJ2014A_OCC3 - Occupation (3 digits) Finland 2010 - see Variable: FI2010A_OCC - Occupation France 1962 - see Variable: FR1962A_SOCCUP - SAPHIR occupation France 1968 - see Variable: FR1968A_SOCC - SAPHIR occupation France 1975 - see Variable: FR1975A_SOCC - SAPHIR occupation France 1982 - see Variable: FR1982A_SOCC - SAPHIR occupation France 1990 - see Variable: FR1990A_SOCC - Saphir occupation France 1999 - see Variable: FR1999A_OCC - Occupation, ISCO France 2006 - see Variable: FR2006A_PROF486 - Detailed profession (4-digit) France 2011 - see Variable: FR2011A_PROF - Profession, 486 categories Germany 1970 - see Variable: DE1970A_OCC - Occupation Germany 1981 - see Variable: DE1981A_OCC - Occupation Germany 1987 - see Variable: DE1987A_OCC - Occupation Ghana 1984 - see Variable: GH1984A_OCC2 - Occupation, 2 digits Ghana 2000 - see Variable: GH2000A_OCC - Occupation Ghana 2010 - see Variable: GH2010A_OCC - Occupation (major groups) Greece 1971 - see Variable: GR1971A_OCC - Occupation Greece 1981 - see Variable: GR1981A_OCC - Occupation Greece 1991 - see Variable: GR1991A_OCC - Occupation Greece 2001 - see Variable: GR2001A_OCC - Occupation Greece 2011 - see Variable: GR2011A_OCC - Occupation Guatemala 1964 - see Variable: GT1964A_OCC3 - Occupation (3-digits) Guatemala 1973 - see Variable: GT1973A_OCC3 - Principal occupation (3-digits) Guatemala 1981 - see Variable: GT1981A_OCC3 - Principal occupation (3-digits) Guatemala 1994 - see Variable: GT1994A_OCC - Principal occupation (1-digit) Guatemala 2002 - see Variable: GT2002A_OCC3 - Principal occupation (3-digits) Guinea 1983 - see Variable: GN1983A_OCC2 - Occupation, 2 digits Guinea 1996 - see Variable: GN1996A_OCC - Occupation Guinea 2014 - see Variable: GN2014A_OCC - Occupation (3-digit) Haiti 1982 - see Variable: HT1982A_OCC - Main occupation or profession Haiti 2003 - see Variable: HT2003A_OCC2 - Occupation, 3 digits Honduras 1961 - see Variable: HN1961A_OCC - Occupation (2-digits) Honduras 1974 - see Variable: HN1974A_OCC2 - Occupation (3-digits) Honduras 1988 - see Variable: HN1988A_OCC4 - Occupation (4-digits) Honduras 2001 - see Variable: HN2001A_OCC - Occupation (4-digit) Honduras 2013 - see Variable: HN2013A_OCC3 - Occupation (3-digit) Hungary 1970 - see Variable: HU1970A_OCC - Occupation Hungary 1980 - see Variable: HU1980A_OCC - Occupation, scope of activity Hungary 1990 - see Variable: HU1990A_OCC - Occupation Hungary 2001 - see Variable: HU2001A_OCC - Occupation Hungary 2011 - see Variable: HU2011A_OCC - Occupation Indonesia 1971 - see Variable: ID1971A_OCC - Occupation Indonesia 1976 - see Variable: ID1976A_OCC - Primary occupation during past week Indonesia 1980 - see Variable: ID1980A_OCC - Primary occupation during the previous week (3 digit version) Indonesia 1985 - see Variable: ID1985A_OCC - Primary occupation Indonesia 1990 - see Variable: ID1990A_OCC - Main occupation last week Indonesia 1995 - see Variable: ID1995A_OCC - Occupation Indonesia 2005 - see Variable: ID2005A_OCC - Occupation Iran 2006 - see Variable: IR2006A_OCC4 - Occupation Iran 2011 - see Variable: IR2011A_OCC - Occupation (3-digit) Iraq 1997 - see Variable: IQ1997A_OCC - Occupation Ireland 1971 - see Variable: IE1971A_OCC - Occupation Ireland 1981 - see Variable: IE1981A_OCC - Occupation Ireland 1986 - see Variable: IE1986A_OCC - Occupation group Ireland 1991 - see Variable: IE1991A_OCC - Occupation group Ireland 1996 - see Variable: IE1996A_OCC - Occupation Ireland 2002 - see Variable: IE2002A_OCC - Occupation Ireland 2006 - see Variable: IE2006A_OCC - Occupation group Ireland 2011 - see Variable: IE2011A_OCC - Occupation (shuffled) Ireland 2016 - see Variable: IE2016A_OCC - Occupation (groups) Israel 1972 - see Variable: IL1972A_OCC - Occupation Israel 1983 - see Variable: IL1983A_OCC - Occupation Israel 1995 - see Variable: IL1995A_OCC - Occupation Israel 2008 - see Variable: IL2008A_OCC - Occupation Italy 2001 - see Variable: IT2001A_OCC - Occupation Italy 2011 - see Variable: IT2011A_WKTYPE - Type of work Jamaica 1982 - see Variable: JM1982A_OCC - Occupation during past week / in last job Jamaica 1991 - see Variable: JM1991A_OCC - Occupation during past week/in last job Jamaica 2001 - see Variable: JM2001A_OCC3 - Occupation 3-digit Jordan 2004 - see Variable: JO2004A_OCC3 - Major current occupation (3-digit) Kenya 1989 - see Variable: KE1989A_OCC4 - Occupation, 4 digits Kenya 2019 - see Variable: KE2019A_OCC3 - Occupation (3-digit) Kyrgyzstan 1999 - see Variable: KG1999A_OCC - Main activity Laos 1995 - see Variable: LA1995A_OCC1 - Main occupation in the last 12 months (1-digit) Lesotho 1996 - see Variable: LS1996A_OCC - Occupation (2-digits) Lesotho 2006 - see Variable: LS2006A_OCC - Occupation (2-digits) Liberia 1974 - see Variable: LR1974A_OCC2 - Occupation (2-digit) Liberia 2008 - see Variable: LR2008A_OCC - Occupation Malawi 1987 - see Variable: MW1987A_OCC2 - Occupation, 2 digit Malawi 1998 - see Variable: MW1998A_OCC2 - Occupation, 2-digit Malawi 2008 - see Variable: MW2008A_OCC2 - Occupation (2 digits) Malawi 2018 - see Variable: MW2018A_OCC1 - Main occupation (1-digit) Malaysia 1970 - see Variable: MY1970A_OCC - Occupation last week Malaysia 1980 - see Variable: MY1980A_OCC3 - Principal occupation last week (3 digits) Malaysia 1991 - see Variable: MY1991A_OCC3 - Principal occupation (3 digits) Malaysia 2000 - see Variable: MY2000A_OCC3 - Occupation -- 3 digits Mali 1987 - see Variable: ML1987A_OCC - Occupation last month Mali 1998 - see Variable: ML1998A_OCC - Main occupation Mali 2009 - see Variable: ML2009A_OCC - Principal occupation Mauritius 1990 - see Variable: MU1990A_OCC3 - Occupation (3-digit) Mauritius 2000 - see Variable: MU2000A_OCC4 - Occupation (4 digit) Mauritius 2011 - see Variable: MU2011A_OCC4 - Occupation (4-digit) Mexico 1960 - see Variable: MX1960A_OCC2 - Principal occupation, 2 digits Mexico 1970 - see Variable: MX1970A_OCC3 - Occupation 3 digit Mexico 1990 - see Variable: MX1990A_OCC - Occupation, 4 digits Mexico 1995 - see Variable: MX1995A_OCC - Occupation Mexico 2000 - see Variable: MX2000A_OCC4 - Occupation, 4 digits Mexico 2010 - see Variable: MX2010A_OCC - Occupation or trade Mexico 2015 - see Variable: MX2015A_OCC - Occupation Mexico 2020 - see Variable: MX2020A_OCC3 - Occupation (3-digits) Mongolia 2000 - see Variable: MN2000A_OCC - Occupation Mongolia 2010 - see Variable: MN2010A_OCC3 - Occupation 3 digits (ISCO-2008) Mongolia 2020 - see Variable: MN2020A_OCC3 - Occupation (3-digit) Morocco 1982 - see Variable: MA1982A_OCC3 - Occupation (3-digit) Morocco 1994 - see Variable: MA1994A_OCC3 - Occupation, 3-digit Morocco 2004 - see Variable: MA2004A_OCC3 - Occupation (3-digit) Morocco 2014 - see Variable: MA2014A_OCC2 - Occupation (2-digit) Mozambique 1997 - see Variable: MZ1997A_OCC2 - Occupation 3-digit Mozambique 2007 - see Variable: MZ2007A_OCC - Occupation Mozambique 2017 - see Variable: MZ2017A_OCC3 - Main occupation (3-digits ISCO 2008) Myanmar 2014 - see Variable: MM2014A_OCC - Occupation Nepal 2001 - see Variable: NP2001A_OCC - Usual occupation Nepal 2011 - see Variable: NP2011A_OCC1 - Occupation (1-digit) Netherlands 1960 - see Variable: NL1960A_OCC - Occupation Netherlands 1971 - see Variable: NL1971A_OCC - Occupation Netherlands 2001 - see Variable: NL2001A_OCC - Occupation Netherlands 2011 - see Variable: NL2011A_OCC - Occupation (1-digit) Nicaragua 1971 - see Variable: NI1971A_OCC - Occupation Nicaragua 1995 - see Variable: NI1995A_OCC - Occupation (ISCO 88, 3 digits) Nicaragua 2005 - see Variable: NI2005A_OCC3 - Occupation (ISCO 88, 3 digits) Pakistan 1973 - see Variable: PK1973A_OCC3 - Occupation Palestine 1997 - see Variable: PS1997A_OCC - Main occupation Palestine 2007 - see Variable: PS2007A_OCC - Main occupation Palestine 2017 - see Variable: PS2017A_OCC - Occupation Panama 1960 - see Variable: PA1960A_OCC4 - Occupation (4-digit) Panama 1970 - see Variable: PA1970A_OCC2 - Occupation, 2-digit Panama 1980 - see Variable: PA1980A_OCC2 - Occupation (3-digit) Panama 1990 - see Variable: PA1990A_OCC - Occupation Panama 2000 - see Variable: PA2000A_OCC - Occupation Panama 2010 - see Variable: PA2010A_OCC - Occupation, 3 digits Papua New Guinea 1980 - see Variable: PG1980A_OCC - Occupation, 3 digits Papua New Guinea 1990 - see Variable: PG1990A_OCC - Occupation Papua New Guinea 2000 - see Variable: PG2000A_OCC - Occupation (4-digit) Paraguay 1962 - see Variable: PY1962A_OCC1 - Occupation (1-digit) Paraguay 1972 - see Variable: PY1972A_OCC3 - Occupation (3 digits) Paraguay 1982 - see Variable: PY1982A_OCC3 - Occupation, 3-digits Paraguay 1992 - see Variable: PY1992A_OCC2 - Main occupation, 3 digits Paraguay 2002 - see Variable: PY2002A_OCC - Occupation (4 digits) Peru 1993 - see Variable: PE1993A_OCC - Occupation (3 digits) Peru 2007 - see Variable: PE2007A_OCC - Main occupation last week (3 digits) Peru 2017 - see Variable: PE2017A_OCC1 - Occupation (1-digit, in primary job last week) Philippines 1990 - see Variable: PH1990A_OCC - Occupation Philippines 2000 - see Variable: PH2000A_OCC - Occupation Philippines 2010 - see Variable: PH2010A_OCC3 - Usual occupation (3-digit) Poland 1978 - see Variable: PL1978A_OCC - Occupation Poland 1988 - see Variable: PL1988A_OCC - Main occupation Poland 2002 - see Variable: PL2002A_OCC - Occupation Portugal 1981 - see Variable: PT1981A_OCC - Main occupation Portugal 1991 - see Variable: PT1991A_OCC - Main occupation Portugal 2001 - see Variable: PT2001A_OCC - Main occupation Portugal 2011 - see Variable: PT2011A_OCC - Main occupation Puerto Rico 1970 - see Variable: PR1970A_OCC - Occupation Puerto Rico 1980 - see Variable: PR1980A_OCC - Occupation Puerto Rico 1990 - see Variable: PR1990A_OCC - Occupation Puerto Rico 2000 - see Variable: PR2000A_OCC - Occupation Puerto Rico 2005 - see Variable: PR2005A_OCC - Occupation Puerto Rico 2010 - see Variable: PR2010A_OCC - Occupation Puerto Rico 2015 - see Variable: PR2015A_OCC - Occupation last week Puerto Rico 2020 - see Variable: PR2020A_OCC2010 - Occupation last week, 2010 basis Romania 1992 - see Variable: RO1992A_OCC - Occupation Romania 2002 - see Variable: RO2002A_OCC4 - Occupation, 4 digits Romania 2011 - see Variable: RO2011A_OCC - Occupation (unrecoded) Rwanda 2002 - see Variable: RW2002A_OCC - Occupation Rwanda 2012 - see Variable: RW2012A_OCC2 - Occupation (3-digit) Saint Lucia 1991 - see Variable: LC1991A_OCC - Occupation Senegal 1988 - see Variable: SN1988A_OCC - Occupation Senegal 2002 - see Variable: SN2002A_OCC3 - Occupation, 3 digits Senegal 2013 - see Variable: SN2013A_OCC3 - Profession or occupation (3-digit) Sierra Leone 2004 - see Variable: SL2004A_OCC - Occupation Sierra Leone 2015 - see Variable: SL2015A_OCC - Main occupation in the past 12 months Slovakia 1991 - see Variable: SK1991A_OCC - Occupation (2-digit) Slovakia 2001 - see Variable: SK2001A_OCC2 - Occupation (2-digit) Slovakia 2011 - see Variable: SK2011A_OCC2 - Occupation (2-digit) Slovenia 2002 - see Variable: SI2002A_OCC - Occupation South Africa 1996 - see Variable: ZA1996A_OCC3 - Occupation, 3 digits South Africa 2001 - see Variable: ZA2001A_OCC - Occupation, 3 digit South Africa 2007 - see Variable: ZA2007A_OCC3 - Occupation, 3 digits South Sudan 2008 - see Variable: SS2008A_OCC - Occupation Spain 1981 - see Variable: ES1981A_OCC - Occupation Spain 1991 - see Variable: ES1991A_OCC - Occupation Spain 2001 - see Variable: ES2001A_OCC - Occupation Spain 2011 - see Variable: ES2011A_OCC - Occupation, 2-digits Sudan 2008 - see Variable: SD2008A_OCC - Occupation Suriname 2004 - see Variable: SR2004A_OCC - Occupation Suriname 2012 - see Variable: SR2012A_OCC - Occupation (groups) Switzerland 1970 - see Variable: CH1970A_ISCO - Present occupation (ISCO) Switzerland 1980 - see Variable: CH1980A_ISCO - Present occupation (ISCO-COM) Switzerland 1990 - see Variable: CH1990A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2000 - see Variable: CH2000A_ISCO4 - Present occupation (ISCO-COM) Switzerland 2011 - see Variable: CH2011A_OCC - Current occupation (1-digit, ISCO-08) Tanzania 1988 - see Variable: TZ1988A_OCC - Occupation Tanzania 2002 - see Variable: TZ2002A_OCC - Occupation last week Tanzania 2012 - see Variable: TZ2012A_OCC - Occupation Thailand 1970 - see Variable: TH1970A_OCC - Principal occupation last year Thailand 1980 - see Variable: TH1980A_OCC - Occupation last year Thailand 1990 - see Variable: TH1990A_OCC3 - Occupation last year Thailand 2000 - see Variable: TH2000A_OCC3 - Occupation last year, 3 digits Togo 1960 - see Variable: TG1960A_OCC - Occupation (3-digits) Togo 1970 - see Variable: TG1970A_OCC3 - Occupation (3-digits) Togo 2010 - see Variable: TG2010A_OCC2 - Occupation (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_OCC - Main occupation (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_OCC - Main occupation during previous week (three digits) Trinidad and Tobago 2000 - see Variable: TT2000A_OCC - Main occupation (3 digits) Turkey 1985 - see Variable: TR1985A_OCC2 - Occupation (2-digit) Turkey 1990 - see Variable: TR1990A_OCC2 - Current occupation (2 digits) Turkey 2000 - see Variable: TR2000A_OCC2 - Current occupation, 2 digit Uganda 1991 - see Variable: UG1991A_OCC - Occupation, 3 digits Uganda 2002 - see Variable: UG2002A_OCC - Occupation, 3 digits Uganda 2014 - see Variable: UG2014A_OCC - Occupation (2-digits) United Kingdom 1961 - see Variable: UK1961A_OCC - Occupation United Kingdom 1971 - see Variable: UK1971A_OCC - Occupation United Kingdom 1991 - see Variable: UK1991A_OCC - Occupational classification United Kingdom 2001 - see Variable: UK2001A_OCC3 - Standard occupational classification 2000-minor United States 1960 - see Variable: US1960A_OCC - Occupation United States 1970 - see Variable: US1970A_OCC - Occupation United States 1980 - see Variable: US1980A_OCC - Occupation United States 1990 - see Variable: US1990A_OCC - Occupation United States 2000 - see Variable: US2000A_OCC - Occupation United States 2005 - see Variable: US2005A_OCC2000M - Occupation, 2000 basis, modal category assignment United States 2010 - see Variable: US2010A_OCC - Occupation United States 2015 - see Variable: US2015A_OCC - Occupation last week United States 2020 - see Variable: US2020A_OCC - Occupation last week Uruguay 1963 - see Variable: UY1963A_OCC2 - Primary occupation [2-digit] Uruguay 1975 - see Variable: UY1975A_OCC - Occupation (COTA, 3 digits) Uruguay 1985 - see Variable: UY1985A_OCC - Occupation during the past week Uruguay 1996 - see Variable: UY1996A_OCC - Occupation (ISCO 88, 3 digits) Uruguay 2006 - see Variable: UY2006A_OCC3 - Occupation (ISCO-88, 3 digits) Venezuela 1981 - see Variable: VE1981A_OCC3 - Occupation, 3 digits Venezuela 1990 - see Variable: VE1990A_OCC - Occupation, 3 digits Venezuela 2001 - see Variable: VE2001A_OCC - Occupation Vietnam 1989 - see Variable: VN1989A_OCC2 - Occupation, 2 digits Vietnam 1999 - see Variable: VN1999A_OCC3 - Occupation, 3 digit Vietnam 2009 - see Variable: VN2009A_OCC - Occupation Vietnam 2019 - see Variable: VN2019A_OCC1 - Occupation, 1 digit Zambia 1990 - see Variable: ZM1990A_OCC - Occupation Zambia 2000 - see Variable: ZM2000A_OCC - Main occupation last 12 months, 3 digits Zambia 2010 - see Variable: ZM2010A_OCC2 - Main occupation last 12 months, 3 digits Zimbabwe 2012 - see Variable: ZW2012A_OCC - Occupation (3-digits) Work Variables -- PERSON Industry, general recode INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown Work Variables -- PERSON Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. Argentina 1970 - see Variable: AR1970A_IND4 - Industry [4 digit] Argentina 1980 - see Variable: AR1980A_IND - Industry Argentina 1991 - see Variable: AR1991A_IND - Industry Argentina 2001 - see Variable: AR2001A_IND - Industry Armenia 2001 - see Variable: AM2001A_IND - Principal activity at place of work Armenia 2011 - see Variable: AM2011A_IND - Industry Austria 1971 - see Variable: AT1971A_INDBR - Economic activity of supporter: branch Austria 1981 - see Variable: AT1981A_INDBR - Economic activity of supporter: branch Austria 1991 - see Variable: AT1991A_INDBR - Economic activity of supporter: branch Austria 2001 - see Variable: AT2001A_INDBR - Economic activity of supporter: branch Austria 2011 - see Variable: AT2011A_IND - Industry Bangladesh 1991 - see Variable: BD1991A_IND - Industry Bangladesh 2001 - see Variable: BD2001A_IND - Main work field Bangladesh 2011 - see Variable: BD2011A_IND - Industry Belarus 2009 - see Variable: BY2009A_ECONACT - Industry Benin 1979 - see Variable: BJ1979A_IND - Industry (1-digit) Benin 1992 - see Variable: BJ1992A_IND3 - Industry (2-digits) Benin 2002 - see Variable: BJ2002A_IND2 - Industry (2-digits) Benin 2013 - see Variable: BJ2013A_IND3 - Industry (3-digit) Bolivia 1976 - see Variable: BO1976A_IND - Industry Bolivia 1992 - see Variable: BO1992A_IND3 - Activity, 3 digits Bolivia 2001 - see Variable: BO2001A_IND3 - Industry, 3 digits Bolivia 2012 - see Variable: BO2012A_IND2 - Industry (2 digit) Botswana 1981 - see Variable: BW1981A_IND - Industry Botswana 1991 - see Variable: BW1991A_IND - Industry Botswana 2001 - see Variable: BW2001A_IND - Industry Botswana 2011 - see Variable: BW2011A_IND - Industry, 3-digits Brazil 1960 - see Variable: BR1960A_INDUSTRY - Industry Brazil 1970 - see Variable: BR1970A_INDUSTRY - Industry Brazil 1980 - see Variable: BR1980A_INDUSTRY - Industry Brazil 1991 - see Variable: BR1991A_IND - Industry Brazil 2000 - see Variable: BR2000A_IND - Industry, 5 digits Brazil 2010 - see Variable: BR2010A_IND - Industry of work from July 25 to July 31, 2010 Burkina Faso 1996 - see Variable: BF1996A_IND - Branch of activity Cambodia 1998 - see Variable: KH1998A_IND - Industry Cambodia 2004 - see Variable: KH2004A_IND3 - Industry (3-digits) Cambodia 2008 - see Variable: KH2008A_IND - Industry Cambodia 2013 - see Variable: KH2013A_IND - Industry (3-digits) Cambodia 2019 - see Variable: KH2019A_IND3 - Industy (ISIC rev 4, 3-digit) Cameroon 2005 - see Variable: CM2005A_IND - Industry Canada 1971 - see Variable: CA1971A_IND - Industry Canada 1981 - see Variable: CA1981A_IND - Industry (1981 standard industrial classification) Canada 1991 - see Variable: CA1991A_IND80 - Industry (1980 standard industrial classification) Canada 2001 - see Variable: CA2001A_IND80P - Industry (1980 Standard Industrial Classification) Canada 2011 - see Variable: CA2011A_IND - Industry Chile 1960 - see Variable: CL1960A_IND - Industry Chile 1970 - see Variable: CL1970A_IND4 - Industry (4-digit) Chile 1982 - see Variable: CL1982A_IND4 - Industry (4-digit) Chile 1992 - see Variable: CL1992A_IND - Industry Chile 2002 - see Variable: CL2002A_IND - Industry Chile 2017 - see Variable: CL2017A_IND - Industry (1-digit) China 1982 - see Variable: CN1982A_INDUSTRY - Industry China 1990 - see Variable: CN1990A_IND - Industry China 2000 - see Variable: CN2000A_IND - Industry (2-digit) Colombia 1964 - see Variable: CO1964A_IND4 - Industry, 4 digits Colombia 1973 - see Variable: CO1973A_IND - Industry Colombia 1993 - see Variable: CO1993A_IND - Industry Colombia 2005 - see Variable: CO2005A_IND - Industry (2-digit) Costa Rica 1963 - see Variable: CR1963A_IND3 - Industry, 3 digits Costa Rica 1973 - see Variable: CR1973A_IND4 - Industry, 4 digits Costa Rica 1984 - see Variable: CR1984A_IND4 - Industry, 4 digits Costa Rica 2000 - see Variable: CR2000A_IND3 - Industry, 3 digits Costa Rica 2011 - see Variable: CR2011A_IND - Industry 2-digit Cuba 2002 - see Variable: CU2002A_IND - Industry Cuba 2012 - see Variable: CU2012A_IND - Industry Côte d'Ivoire 1988 - see Variable: CI1988A_IND - Industry (1-digit) Côte d'Ivoire 1998 - see Variable: CI1998A_IND2 - Industry sector (detailed) Dominican Republic 1960 - see Variable: DO1960A_IND - Industry Dominican Republic 1970 - see Variable: DO1970A_IND1 - Industry, 3 digits Dominican Republic 1981 - see Variable: DO1981A_IND - Industry (3-digit) Dominican Republic 2002 - see Variable: DO2002A_IND - Industry Dominican Republic 2010 - see Variable: DO2010A_IND - Main activity of business Ecuador 1962 - see Variable: EC1962A_IND3 - Industry, 3 digits Ecuador 1982 - see Variable: EC1982A_IND3 - Industry Ecuador 1990 - see Variable: EC1990A_IND3 - Industry, 3 digits Ecuador 2001 - see Variable: EC2001A_IND - Industry, 3 digits Ecuador 2010 - see Variable: EC2010A_IND3 - Industry (3 digits, ISIC rev 4) Egypt 1986 - see Variable: EG1986A_IND3 - Industry (3-digit) Egypt 1996 - see Variable: EG1996A_IND3 - Industry (ISIC) Egypt 2006 - see Variable: EG2006A_IND - Industry, 3-digit El Salvador 1992 - see Variable: SV1992A_IND - Industry (3-digit) El Salvador 2007 - see Variable: SV2007A_IND3DIG - Industry (3-digit) Ethiopia 1984 - see Variable: ET1984A_IND2 - Industry Ethiopia 1994 - see Variable: ET1994A_IND - Industry Fiji 1966 - see Variable: FJ1966A_IND - Industry Fiji 1976 - see Variable: FJ1976A_IND - Industry Fiji 1986 - see Variable: FJ1986A_IND - Industry 3 digits Fiji 1996 - see Variable: FJ1996A_IND2DIG - Industry (2 digits) Fiji 2007 - see Variable: FJ2007A_IND2 - Industry, 2 digits Fiji 2014 - see Variable: FJ2014A_IND - Industry Finland 2010 - see Variable: FI2010A_IND - Industry France 1962 - see Variable: FR1962A_IND - Industry France 1968 - see Variable: FR1968A_IND41 - Industry, 41 categories France 1975 - see Variable: FR1975A_INDUN - Industry, UNO France 1982 - see Variable: FR1982A_INDUN - Industry, United Nations nomenclature France 1990 - see Variable: FR1990A_IND15 - Industry, 15 categories France 1999 - see Variable: FR1999A_INDCITI - Industry, ISIC France 2006 - see Variable: FR2006A_IND700N - Economic activity in 700 categories (2003 classification) numeric recode France 2011 - see Variable: FR2011A_IND - Industry, 732 categories Germany 1970 - see Variable: DE1970A_IND - Industry Germany 1971 - see Variable: DE1971A_IND - Industry Germany 1981 - see Variable: DE1981A_IND - Industry Germany 1987 - see Variable: DE1987A_IND - Industry Ghana 2000 - see Variable: GH2000A_IND - Industry Ghana 2010 - see Variable: GH2010A_IND - Industry (major groups) Greece 1971 - see Variable: GR1971A_IND - Industry Greece 1981 - see Variable: GR1981A_IND - Industry Greece 1991 - see Variable: GR1991A_IND - Industry Greece 2001 - see Variable: GR2001A_IND - Industry Greece 2011 - see Variable: GR2011A_IND - Industry Guatemala 1964 - see Variable: GT1964A_IND3 - Field of economic activity (3-digits) Guatemala 1973 - see Variable: GT1973A_IND3 - Industry (3-digits) Guatemala 1981 - see Variable: GT1981A_IND3 - Industry (3-digits) Guatemala 1994 - see Variable: GT1994A_IND2 - Field of economic activity (2-digits) Guatemala 2002 - see Variable: GT2002A_IND1 - Field of economic activity (1-digit) Guinea 1983 - see Variable: GN1983A_IND2 - Branch of economic activity, 2 digits Guinea 2014 - see Variable: GN2014A_IND - Industry (3-digit) Haiti 1982 - see Variable: HT1982A_IND - Branch of work Haiti 2003 - see Variable: HT2003A_IND2 - Industry, 3 digits Honduras 1961 - see Variable: HN1961A_IND - Industry (2-digits) Honduras 1974 - see Variable: HN1974A_IND - Industry (3-digits) Honduras 2001 - see Variable: HN2001A_IND - Industry (4-digit) Honduras 2013 - see Variable: HN2013A_IND3 - Economic activity (3-digit) Hungary 2001 - see Variable: HU2001A_IND - Industry, branch of economy Hungary 2011 - see Variable: HU2011A_IND - Industry Indonesia 1971 - see Variable: ID1971A_IND - Industry Indonesia 1976 - see Variable: ID1976A_IND - Industry Indonesia 1980 - see Variable: ID1980A_IND - Industry Indonesia 1985 - see Variable: ID1985A_IND - Industry of primary occupation Indonesia 1990 - see Variable: ID1990A_IND - Industry of main occupation last week Indonesia 1995 - see Variable: ID1995A_IND - Industry Indonesia 2000 - see Variable: ID2000A_IND - Industry of primary occupation Indonesia 2005 - see Variable: ID2005A_IND - Industry Indonesia 2010 - see Variable: ID2010A_IND - Industry Iran 2006 - see Variable: IR2006A_IND4 - Industry Iran 2011 - see Variable: IR2011A_IND - Industry (3-digit) Iraq 1997 - see Variable: IQ1997A_IND - Industry Ireland 1971 - see Variable: IE1971A_IND - Industry Ireland 1981 - see Variable: IE1981A_IND - Industry class Ireland 1986 - see Variable: IE1986A_IND - Industry class Ireland 1991 - see Variable: IE1991A_IND - Industry class Ireland 1996 - see Variable: IE1996A_IND - Industry class Ireland 2002 - see Variable: IE2002A_IND - Industry class Ireland 2006 - see Variable: IE2006A_IND - Industry class Ireland 2011 - see Variable: IE2011A_IND - Industry Ireland 2016 - see Variable: IE2016A_IND - Industry Israel 1972 - see Variable: IL1972A_IND - Industry Israel 1983 - see Variable: IL1983A_IND - Industry Israel 1995 - see Variable: IL1995A_IND - Industry Israel 2008 - see Variable: IL2008A_IND - Branch of economy Italy 2001 - see Variable: IT2001A_IND - Industry Italy 2011 - see Variable: IT2011A_IND - Sector of economic activity Jamaica 1982 - see Variable: JM1982A_IND - Industry or type of business during past week / in last job Jamaica 1991 - see Variable: JM1991A_IND3 - Industry during past week or in last job, 3 digits Jamaica 2001 - see Variable: JM2001A_IND3 - Industry 3-digit Jordan 2004 - see Variable: JO2004A_IND - Major current economic activity of the establishment Kenya 2019 - see Variable: KE2019A_IND1 - Industry, ISIC section Kyrgyzstan 1999 - see Variable: KG1999A_IND - Activity type of an enterprise you are working in Kyrgyzstan 2009 - see Variable: KG2009A_IND - Type of industry, enterprise or organization Laos 1995 - see Variable: LA1995A_IND2 - Main industry in the last 12 months (2-digit) Laos 2005 - see Variable: LA2005A_IND3 - Industry (ISIC 3-digit) Laos 2015 - see Variable: LA2015A_IND2 - Industry (2-digit ISIC Rev. 4) Lesotho 2006 - see Variable: LS2006A_IND - Industry (2-digits) Liberia 1974 - see Variable: LR1974A_IND - Industry (3-digit) Liberia 2008 - see Variable: LR2008A_IND - Industry Malawi 1987 - see Variable: MW1987A_IND2 - Industry, 2 digit Malawi 1998 - see Variable: MW1998A_IND4 - Industry, 4-digit Malawi 2008 - see Variable: MW2008A_IND2 - Main industry Malawi 2018 - see Variable: MW2018A_IND3 - Main industry (ISIC 2008 3-digit) Malaysia 1970 - see Variable: MY1970A_IND3 - Industry last week Malaysia 1980 - see Variable: MY1980A_IND3 - Industry last week (3 digits) Malaysia 1991 - see Variable: MY1991A_IND3 - Main industry (3 digits) Malaysia 2000 - see Variable: MY2000A_IND3 - Main industry - 3 digits Mali 1987 - see Variable: ML1987A_IND - Principal branch of employment last month Mali 1998 - see Variable: ML1998A_IND - Branch of economic activity Mali 2009 - see Variable: ML2009A_IND - Industry Mauritius 1990 - see Variable: MU1990A_IND - Industry (1-digit) Mauritius 2000 - see Variable: MU2000A_IND1 - Industry (1 digit) Mauritius 2011 - see Variable: MU2011A_IND2 - Industry (2-digit) Mexico 1960 - see Variable: MX1960A_IND - Industry Mexico 1970 - see Variable: MX1970A_IND - Industry Mexico 1990 - see Variable: MX1990A_IND5 - Industry, 5 digits Mexico 1995 - see Variable: MX1995A_IND - Industry Mexico 2000 - see Variable: MX2000A_IND3 - Industry, 3 digits Mexico 2010 - see Variable: MX2010A_IND - Industry Mexico 2015 - see Variable: MX2015A_IND - Industry Mexico 2020 - see Variable: MX2020A_IND - Industry (4-digits) Mongolia 2000 - see Variable: MN2000A_IND - Industry Mongolia 2010 - see Variable: MN2010A_IND2 - Industry, division (ISIC Revision 4) Mongolia 2020 - see Variable: MN2020A_IND3 - Main industry (3-digit) Morocco 1982 - see Variable: MA1982A_IND3 - Industry (3-digit) Morocco 1994 - see Variable: MA1994A_IND2 - Industry (2 digits) Morocco 2004 - see Variable: MA2004A_IND2 - Sector of economic activity (2-digit) Morocco 2014 - see Variable: MA2014A_IND2 - Industry (2-digit) Mozambique 1997 - see Variable: MZ1997A_IND1 - Industry Mozambique 2007 - see Variable: MZ2007A_IND - Industry Mozambique 2017 - see Variable: MZ2017A_IND2 - Main economic activity (2-digits CAE Rev.2) Myanmar 2014 - see Variable: MM2014A_IND - Industry Nepal 2001 - see Variable: NP2001A_IND - Usual industry Nepal 2011 - see Variable: NP2011A_IND - Industry (2-digit) Netherlands 1960 - see Variable: NL1960A_IND - Industry Netherlands 1971 - see Variable: NL1971A_IND - Industry Netherlands 2001 - see Variable: NL2001A_IND - Industry Netherlands 2011 - see Variable: NL2011A_IND - Industry (1-digit) Nicaragua 1971 - see Variable: NI1971A_IND3 - Industry (ISIC2), 3 digits Nicaragua 1995 - see Variable: NI1995A_IND - Industry (ISIC 3.1, 3 digits) Nicaragua 2005 - see Variable: NI2005A_IND3 - Industry (ISIC 3.1, 3 digits)) Pakistan 1973 - see Variable: PK1973A_IND2 - Industry, 2 digit Palestine 1997 - see Variable: PS1997A_IND - Industry Palestine 2007 - see Variable: PS2007A_IND - Industry Palestine 2017 - see Variable: PS2017A_IND - Industry Panama 1960 - see Variable: PA1960A_IND3 - Industry (3 digit) Panama 1970 - see Variable: PA1970A_IND3 - Industry [3 digit] Panama 1980 - see Variable: PA1980A_IND - Industry, 3-digit Panama 1990 - see Variable: PA1990A_IND3 - Industry - 3 Digits Panama 2000 - see Variable: PA2000A_IND - Economic activity, 3 digits Panama 2010 - see Variable: PA2010A_IND - Economic activity, 4 digits Papua New Guinea 1980 - see Variable: PG1980A_IND - Industry, 3 digits Papua New Guinea 2000 - see Variable: PG2000A_IND3 - Industry (3-digit) Paraguay 1962 - see Variable: PY1962A_IND3 - Industry (3 digits) Paraguay 1972 - see Variable: PY1972A_IND3 - Industry (3 digits) Paraguay 1982 - see Variable: PY1982A_IND3 - Industry, 3-digits Paraguay 1992 - see Variable: PY1992A_IND3 - Industry, 3 digits Paraguay 2002 - see Variable: PY2002A_IND - Industry (4 digits) Peru 1993 - see Variable: PE1993A_IND - Economic activity (4 digits) Peru 2007 - see Variable: PE2007A_IND - Economic activity (4-digits) Peru 2017 - see Variable: PE2017A_IND4 - Economic activity (4-digits, in primary job last week) Philippines 1990 - see Variable: PH1990A_IND - Industry Philippines 1995 - see Variable: PH1995A_IND - Industry Philippines 2000 - see Variable: PH2000A_IND - Industry Philippines 2010 - see Variable: PH2010A_IND3 - Kind of business or industry (3-digit) Poland 1978 - see Variable: PL1978A_IND - Industry (of person providing support) Poland 2002 - see Variable: PL2002A_IND - Industry (main employer) Portugal 1981 - see Variable: PT1981A_IND - Industry Portugal 1991 - see Variable: PT1991A_IND - Industry Portugal 2001 - see Variable: PT2001A_IND - Industry Portugal 2011 - see Variable: PT2011A_IND - Industry Puerto Rico 1970 - see Variable: PR1970A_IND1990 - Industry, 1990 basis Puerto Rico 1980 - see Variable: PR1980A_IND1990 - Industry, 1990 basis Puerto Rico 1990 - see Variable: PR1990A_IND - Industry Puerto Rico 2000 - see Variable: PR2000A_IND1990 - Industry, 1990 basis Puerto Rico 2005 - see Variable: PR2005A_IND1990 - Industry, 1990 basis Puerto Rico 2010 - see Variable: PR2010A_IND - Industry Puerto Rico 2015 - see Variable: PR2015A_IND - Industry Puerto Rico 2020 - see Variable: PR2020A_IND - Industry Romania 1977 - see Variable: RO1977A_IND - Industry of supporter Romania 1977 - see Variable: RO1977A_WKACT - Activity category Romania 1992 - see Variable: RO1992A_IND - Industry Romania 2002 - see Variable: RO2002A_IND - Industry Romania 2011 - see Variable: RO2011A_INDGEN - Industry (general categories) Rwanda 2002 - see Variable: RW2002A_IND - Industry Rwanda 2012 - see Variable: RW2012A_IND2 - Industry (3-digit) Saint Lucia 1991 - see Variable: LC1991A_IND3 - Industry, 2 digit Senegal 1988 - see Variable: SN1988A_IND - Industry Senegal 2013 - see Variable: SN2013A_IND3 - Industry (3-digit) Sierra Leone 2004 - see Variable: SL2004A_IND - Industry Slovenia 2002 - see Variable: SI2002A_IND - Industry South Africa 1996 - see Variable: ZA1996A_IND2 - Industry, 2 digits South Africa 2001 - see Variable: ZA2001A_IND3 - Industry, 3 digit South Africa 2007 - see Variable: ZA2007A_IND3 - Industry, 3 digit South Sudan 2008 - see Variable: SS2008A_IND - Industry Spain 1981 - see Variable: ES1981A_IND - Industry Spain 1991 - see Variable: ES1991A_IND - Activity of the establishment Spain 2001 - see Variable: ES2001A_IND - Industry Spain 2011 - see Variable: ES2011A_IND - Industry, 2-digits Sudan 2008 - see Variable: SD2008A_IND - Industry Suriname 2004 - see Variable: SR2004A_IND - Industry Suriname 2012 - see Variable: SR2012A_IND - Industry (groups) Switzerland 1970 - see Variable: CH1970A_IND - Branch of economic activity (industry) Switzerland 1980 - see Variable: CH1980A_IND - Branch of economic activity (industry) Switzerland 1990 - see Variable: CH1990A_IND - Branch of economic activity (industry) Switzerland 2000 - see Variable: CH2000A_IND - Branch of economic activity (industry) Switzerland 2011 - see Variable: CH2011A_IND2 - Industry of local unit, workplace (NOGA 2-digit) Tanzania 2002 - see Variable: TZ2002A_IND - Industry last week Tanzania 2012 - see Variable: TZ2012A_IND - Industry Thailand 1970 - see Variable: TH1970A_IND - Principal industry last year Thailand 1980 - see Variable: TH1980A_IND - Principal industry last year Thailand 1990 - see Variable: TH1990A_IND3 - Principal industry last year, 3 digits Thailand 2000 - see Variable: TH2000A_IND3 - Industry last year, 3 digits Togo 1970 - see Variable: TG1970A_IND - Industry (1-digit) Togo 2010 - see Variable: TG2010A_IND3 - Industry (3-digits) Trinidad and Tobago 1980 - see Variable: TT1980A_IND - Industry (2-digit) Trinidad and Tobago 1990 - see Variable: TT1990A_IND - Industry Trinidad and Tobago 2000 - see Variable: TT2000A_IND - Industry (2 digits) Turkey 1985 - see Variable: TR1985A_INDALT - Industry (2-digit) Turkey 1990 - see Variable: TR1990A_IND2 - Industry (2 digits) Turkey 2000 - see Variable: TR2000A_IND2 - Industry, 2 digit Uganda 2002 - see Variable: UG2002A_IND - Industry United Kingdom 1961 - see Variable: UK1961A_IND - Industry United Kingdom 1971 - see Variable: UK1971A_IND - Industry United Kingdom 1991 - see Variable: UK1991A_IND - Industrial classification United Kingdom 2001 - see Variable: UK2001A_IND - Industry classification United States 1960 - see Variable: US1960A_IND - Industry United States 1970 - see Variable: US1970A_IND - Industry United States 1980 - see Variable: US1980A_IND - Industry United States 1990 - see Variable: US1990A_IND - Industry United States 2000 - see Variable: US2000A_IND - Industry United States 2005 - see Variable: US2005A_IND - Industry United States 2010 - see Variable: US2010A_IND - Industry United States 2015 - see Variable: US2015A_IND - Industry United States 2020 - see Variable: US2020A_IND - Industry Uruguay 1963 - see Variable: UY1963A_IND2 - Primary industry [2-digit] Uruguay 1985 - see Variable: UY1985A_IND - Industry during the past week Uruguay 1996 - see Variable: UY1996A_IND2 - Industry (ISIC 3, 2 digits) Uruguay 2006 - see Variable: UY2006A_IND3 - Industry (ISIC rev 3, 3 digits) Venezuela 1981 - see Variable: VE1981A_IND - Industry Venezuela 1990 - see Variable: VE1990A_IND - Industry Venezuela 2001 - see Variable: VE2001A_IND - Industry Vietnam 1989 - see Variable: VN1989A_IND2 - Industry, 2 digits Vietnam 1999 - see Variable: VN1999A_IND3 - Industry, 3 digit Vietnam 2009 - see Variable: VN2009A_IND - Industry Vietnam 2019 - see Variable: VN2019A_IND3 - Industry, 3 digit Zambia 1990 - see Variable: ZM1990A_IND - Industry Zambia 2000 - see Variable: ZM2000A_IND - Type of industry, 3 digits Zambia 2010 - see Variable: ZM2010A_IND2 - Industry, 3 digits Work Variables -- PERSON Status in employment (class of worker) [general version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 0 NIU (not in universe) 1 Self-employed 2 Wage/salary worker 3 Unpaid worker 4 Other 9 Unknown/missing Work Variables -- PERSON Status in employment (class of worker) [detailed version] CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. 000 NIU (not in universe) 100 Self-employed 101 Self-employed, unincorporated 102 Self-employed, incorporated 110 Employer 111 Sharecropper, employer 120 Working on own account 121 Own account, agriculture 122 Domestic worker, self-employed 123 Subsistence worker, own consumption 124 Own account, other 125 Own account, without temporary/unpaid help 126 Own account, with temporary/unpaid help 130 Member of cooperative 140 Sharecropper 141 Sharecropper, self-employed 142 Sharecropper, employee 150 Kibbutz member 199 Self-employed, not specified 200 Wage/salary worker 201 Management 202 Non-management 203 White collar (non-manual) 204 Blue collar (manual) 205 White or blue collar 206 Day laborer 207 Employee, with a permanent job 208 Employee, occasional, temporary, contract 209 Employee without legal contract 210 Wage/salary worker, private employer 211 Apprentice 212 Religious worker 213 Wage/salary worker, non-profit, NGO 214 White collar, private 215 Blue collar, private 216 Paid family worker 217 Cooperative employee 220 Wage/salary worker, government or public sector 221 Federal, government employee 222 State government employee 223 Local government employee 224 White collar, public 225 Blue collar, public 226 Public companies 227 Civil servants, local collectives 230 Domestic worker (work for private household) 240 Seasonal migrant 241 Seasonal migrant, no broker 242 Seasonal migrant, uses broker 250 Other wage and salary 251 Canal zone/commission employee 252 Government employment/training program 253 Mixed state/private enterprise/parastatal 254 Government public work program 255 State enterprise employee 256 Coordinated and continuous collaboration job 300 Unpaid worker 310 Unpaid family worker 320 Apprentice, unpaid or unspecified 330 Trainee 340 Apprentice or trainee 350 Works for others without wage 400 Other 999 Unknown/missing Work Variables -- PERSON Sector of employment EMPSECT indicates the economic sector in which the person was employed. Economic sector is defined in terms of ownership or control of the enterprise in which the person worked. 00 NIU (not in universe) 10 Public 20 Private 21 Private, not elsewhere classified 22 Individual/family enterprise, and self-employed 23 Foreign 30 Mixed: public-private or parastatal 40 Collective or cooperative 50 Foreign government or non-governmental organization 60 Other, unspecified 61 Canal zone 62 Faith-based organization 63 Informal sector 99 Unknown Work Variables -- PERSON Hours worked per week HRSWORK1 indicates the number of hours the respondent worked per week at all jobs. 000 0 hours 001 1 hour 002 2 hours 003 3 hours 004 4 hours 005 5 hours 006 6 hours 007 7 hours 008 8 hours 009 9 hours 010 10 hours 011 11 hours 012 12 hours 013 13 hours 014 14 hours 015 15 hours 016 16 hours 017 17 hours 018 18 hours 019 19 hours 020 20 hours 021 21 hours 022 22 hours 023 23 hours 024 24 hours 025 25 hours 026 26 hours 027 27 hours 028 28 hours 029 29 hours 030 30 hours 031 31 hours 032 32 hours 033 33 hours 034 34 hours 035 35 hours 036 36 hours 037 37 hours 038 38 hours 039 39 hours 040 40 hours 041 41 hours 042 42 hours 043 43 hours 044 44 hours 045 45 hours 046 46 hours 047 47 hours 048 48 hours 049 49 hours 050 50 hours 051 51 hours 052 52 hours 053 53 hours 054 54 hours 055 55 hours 056 56 hours 057 57 hours 058 58 hours 059 59 hours 060 60 hours 061 61 hours 062 62 hours 063 63 hours 064 64 hours 065 65 hours 066 66 hours 067 67 hours 068 68 hours 069 69 hours 070 70 hours 071 71 hours 072 72 hours 073 73 hours 074 74 hours 075 75 hours 076 76 hours 077 77 hours 078 78 hours 079 79 hours 080 80 hours 081 81 hours 082 82 hours 083 83 hours 084 84 hours 085 85 hours 086 86 hours 087 87 hours 088 88 hours 089 89 hours 090 90 hours 091 91 hours 092 92 hours 093 93 hours 094 94 hours 095 95 hours 096 96 hours 097 97 hours 098 98 hours 099 99 hours 100 100 hours 101 101 hours 102 102 hours 103 103 hours 104 104 hours 105 105 hours 106 106 hours 107 107 hours 108 108 hours 109 109 hours 110 110 hours 111 111 hours 112 112 hours 113 113 hours 114 114 hours 115 115 hours 116 116 hours 117 117 hours 118 118 hours 119 119 hours 120 120 hours 121 121 hours 122 122 hours 123 123 hours 124 124 hours 125 125 hours 126 126 hours 127 127 hours 128 128 hours 129 129 hours 130 130 hours 131 131 hours 132 132 hours 133 133 hours 134 134 hours 135 135 hours 136 136 hours 137 137 hours 138 138 hours 139 139 hours 140 140+ hours 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Hours worked per week, categorized HRSWORK2 indicates the number of hours the respondent worked per week at all jobs, categorized into intervals. 0 None 1 1 to 14 hours (except tt1980, tt1990 and tt2000) 2 15 to 29 hours (except de1970, ps2017, tt1980, tt1990, tt2000, and ve1971) 3 30 to 39 hours (except de1970, ps2017, tt1980, tt1990, tt2000, and ve1971) 4 40-48 hours (except il1972, tt1980, tt1990, and tt2000) 5 49 hours or more (except il1972 and tt2000) 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Actual hours worked per week HRSACTUAL1 indicates the actual number of hours the respondent worked per week at all jobs. 000 0 hours 001 1 hour 002 2 hours 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100 101 101 102 102 103 103 104 104 105 105 106 106 107 107 108 108 109 109 110 110 111 111 112 112 113 113 114 114 115 115 116 116 117 117 118 118 119 119 120 120 121 121 122 122 123 123 124 124 125 125 126 126 127 127 128 128 129 129 130 130 131 131 132 132 133 133 134 134 135 135 136 136 137 137 138 138 139 139 140 140+ hours 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Actual hours worked per week, categorized HRSACTUAL2 indicates the actual number of hours the respondent worked per week at all jobs, categorized into intervals. 0 None 1 1 to 14 hours (except tt1980, tt1990, and tt2000) 2 15 to 29 hours (except ps2017, tt1980, tt1990, tt2000, and ve1971) 3 30 to 39 hours (except ps2017, tt1980, tt1990, tt2000, and ve1971) 4 40 to 48 hours (except tt1980, tt1990, and tt2000) 5 49 hours or more (except tt2000) 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Migration status, 1 year MIGRATE1 indicates the person's place of residence 1 year ago. The first digit records movement across major administrative divisions and countries; the second digit reports movement across minor administrative divisions. 00 NIU (not in universe) 10 Same major administrative unit 11 Same major, same minor administrative unit 12 Same major, different minor administrative unit 20 Different major administrative unit 30 Abroad 99 Unknown/missing Migration: Global Variables -- PERSON Country of residence 1 year ago MIGCTRY1 indicates the country of residence 1 year ago for international migrants. Persons who did not live abroad 1 year prior are coded to the "non-migrant" category. 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, n.s. 13000 Northern Africa 13010 Algeria 13020 Egypt/United Arab Rep. 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15199 Western African, n.s. 19990 Africa, n.s. 19991 Central and South Africa 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21200 St. Croix 21210 St. Jon 21220 St. Lucia 21230 St. Thomas 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21999 Caribbean, n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23990 South America, n.s. 23991 Central and South America 24000 North America 24010 Bermuda 24020 Canada 24030 Greenland 24040 United States 24041 U.S. Outlying Areas and Territories 24999 North America, n.s. 29990 Americas, other and n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33199 Other South-Eastern Asia 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34990 Western Asia, n.s. 34991 Middle East, n.e.c. 39999 Asia, n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41030 Czech Republic 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41999 Eastern Europe, n.e.c. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42110 Sweden 42120 United Kingdom 42999 Northern Europe, n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43144 Kosovo 43999 Southern Europe, n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44030 France 44040 Germany 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44999 Western Europe, n.e.c. 49990 Europe, n.s. 49991 Central-Eastern Europe 49992 European Union 49993 European Union (original 15) 49994 Other European Union (not original 15) 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53999 Micronesia, n.e.c. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Samoa 54060 Tokelau 54070 Tonga 54080 Tuvalu 54090 Wallis and Futuna Isls. 59999 Oceania, n.s. 60000 Other 90000 Non-migrant (international) 99998 Response suppressed 99999 Unknown Migration: Global Variables -- PERSON 1st subnational geographic level of residence 1 years prior to survey, world [consistent boundaries over time] GEOMIG1_1 indicates the major administrative unit in which the person resided one year prior to the survey. Only intra-national migrations are recorded; however, the variable incorporates geographies for every country that lists place of residence one year ago, to enable comparative analysis of subnational migration. Foreign migrants are coded 097 or 997. Codes for GEOMIG1_1 match the geographic codes in GEOLEV1 (current place of residence). For similar information for different time intervals since migration, see variables GEOMIG1_P, GEOMIG1_5, and GEOMIG1_10. More on migration and geography can be found here. 040011 Burgenland [State: Austria] 040012 Niederösterreich [State: Austria] 040013 Wien [State: Austria] 040021 Kärnten [State: Austria] 040022 Steiermark [State: Austria] 040031 Oberösterreich [State: Austria] 040032 Salzburg [State: Austria] 040033 Tirol [State: Austria] 040034 Vorarlberg [State: Austria] 040097 Foreign country [State: Austria] 040099 NIU [State: Austria] 854001 Boucle du Mouhoun [Region: Burkina Faso] 854002 Cascades [Region: Burkina Faso] 854003 Centre [Region: Burkina Faso] 854004 Centre-Est [Region: Burkina Faso] 854005 Centre-Nord [Region: Burkina Faso] 854006 Centre-Ouest [Region: Burkina Faso] 854007 Centre-Sud [Region: Burkina Faso] 854008 Est [Region: Burkina Faso] 854009 Hauts-Bassins [Region: Burkina Faso] 854010 Nord [Region: Burkina Faso] 854011 Plateau Central [Region: Burkina Faso] 854012 Sahel [Region: Burkina Faso] 854013 Sud-Ouest [Region: Burkina Faso] 854997 Abroad [Region: Burkina Faso] 854998 Unknown [Region: Burkina Faso] 854999 NIU [Region: Burkina Faso] 072001 Gaborone [District: Botswana] 072002 Francistown [District: Botswana] 072003 Lobatse [District: Botswana] 072004 Selebi Phikwe [District: Botswana] 072007 Central Tutume, Sowa [District: Botswana] 072010 Ngwaketse, Ngwaketse West, Ngwaketse Southern, Southern, Jwaneng [District: Botswana] 072011 Borolong [District: Botswana] 072020 South East [District: Botswana] 072030 Kweneng, Kweneng South, Kweneng North [District: Botswana] 072040 Kgatleng [District: Botswana] 072050 Central Serowe/Palapye [District: Botswana] 072051 Central Mahalapye [District: Botswana] 072052 Central Bobonong [District: Botswana] 072053 Central Boteti, Orapa [District: Botswana] 072060 North East [District: Botswana] 072070 Ngamiland East [District: Botswana] 072071 Ngamiland West, Delta [District: Botswana] 072072 Chobe [District: Botswana] 072080 Ghanzi, Central Kgalagadi Game Reserve (CKGR) [District: Botswana] 072090 Tshabong (Kgalagadi South) [District: Botswana] 072091 Hukunsti (Kgalagadi North) [District: Botswana] 072092 Botswana, district unknown [District: Botswana] 072097 Abroad [District: Botswana] 072098 Unknown [District: Botswana] 072099 NIU (not in universe) [District: Botswana] 124010 Newfoundland and Labrador [Province: Canada] 124011 Prince Edward Island, Yukon Territory, Northwest Territories, Nunavut [Province: Canada] 124012 Nova Scotia [Province: Canada] 124013 New Brunswick [Province: Canada] 124024 Quebec [Province: Canada] 124035 Ontario [Province: Canada] 124046 Manitoba [Province: Canada] 124047 Saskatchewan [Province: Canada] 124048 Alberta [Province: Canada] 124059 British Columbia [Province: Canada] 124098 Unknown [Province: Canada] 124099 NIU (not in universe) [Province: Canada] 384001 Lagunes, Sud Comoé, Sud Bandama, Agneby [Region: Cote D'Ivoire] 384002 Haut Sassandra, Marahoué, Fromager [Region: Cote D'Ivoire] 384003 Savanes [Region: Cote D'Ivoire] 384004 Vallée du Bandam, Lacs, N'Zi Comoé [Region: Cote D'Ivoire] 384005 Moyen Comoé [Region: Cote D'Ivoire] 384006 Montagnes, Moyen Cavally [Region: Cote D'Ivoire] 384008 Zanzan [Region: Cote D'Ivoire] 384009 Bas Sassandra [Region: Cote D'Ivoire] 384010 Denguele, Worodougou, Bafing [Region: Cote D'Ivoire] 384097 Abroad [Region: Cote D'Ivoire] 384098 Unknown [Region: Cote D'Ivoire] 384099 NIU [Region: Cote D'Ivoire] 300001 Etolia and Akarnania [Department: Greece] 300003 Viotia [Department: Greece] 300004 Evia [Department: Greece] 300005 Evrytania [Department: Greece] 300006 Fthiotida [Department: Greece] 300007 Fokida [Department: Greece] 300011 Argolida [Department: Greece] 300012 Arkadia [Department: Greece] 300013 Achaia [Department: Greece] 300014 Ilia [Department: Greece] 300015 Korinthia [Department: Greece] 300016 Lakonia [Department: Greece] 300017 Messinia [Department: Greece] 300021 Zakynthos [Department: Greece] 300022 Kerkyra [Department: Greece] 300023 Kefallinia [Department: Greece] 300024 Lefkada [Department: Greece] 300031 Arta [Department: Greece] 300032 Thesprotia [Department: Greece] 300033 Ioannina [Department: Greece] 300034 Preveza [Department: Greece] 300041 Karditsa [Department: Greece] 300042 Larissa [Department: Greece] 300043 Magnissia [Department: Greece] 300044 Trikala [Department: Greece] 300051 Grevena [Department: Greece] 300052 Drama [Department: Greece] 300053 Imathia [Department: Greece] 300054 Thessaloniki [Department: Greece] 300055 Kavala [Department: Greece] 300056 Kastoria [Department: Greece] 300057 Kilkis [Department: Greece] 300058 Kozani [Department: Greece] 300059 Pella [Department: Greece] 300061 Pieria [Department: Greece] 300062 Serres [Department: Greece] 300063 Florina [Department: Greece] 300064 Chalkidiki and Agion Oros [Department: Greece] 300071 Evros [Department: Greece] 300072 Xanthi [Department: Greece] 300073 Rodopi [Department: Greece] 300081 Dodekanissos [Department: Greece] 300082 Kyklades [Department: Greece] 300083 Lesvos [Department: Greece] 300084 Samos [Department: Greece] 300085 Chios [Department: Greece] 300091 Iraklio [Department: Greece] 300092 Lassithi [Department: Greece] 300093 Rethymno [Department: Greece] 300094 Chania [Department: Greece] 300101 Prefecture of Athens [Department: Greece] 300102 Prefecture of East Attiki [Department: Greece] 300103 Prefecture of West Attiki [Department: Greece] 300104 Prefecture of Pireas [Department: Greece] 300996 Foreign country [Department: Greece] 300997 Response suppressed [Department: Greece] 300998 Unknown [Department: Greece] 300999 NIU (not in universe) [Department: Greece] 372001 Dublin [Region: Ireland] 372002 Midlands [Region: Ireland] 372003 Mid-East, Border [Region: Ireland] 372004 Mid-West, South-East [Region: Ireland] 372006 West [Region: Ireland] 372008 South West [Region: Ireland] 372096 Ireland, region not specified [Region: Ireland] 372097 Abroad [Region: Ireland] 372098 Unknown [Region: Ireland] 372099 NIU (not in universe) [Region: Ireland] 380001 Piemonte, Valle d'Aosta [Region: Italy] 380003 Lombardia [Region: Italy] 380004 Trentino Alto Adige [Region: Italy] 380005 Veneto [Region: Italy] 380006 Friuli Venezia Giulia [Region: Italy] 380007 Liguria [Region: Italy] 380008 Emilia Romagna, Marche [Region: Italy] 380009 Toscana [Region: Italy] 380010 Umbria [Region: Italy] 380012 Lazio [Region: Italy] 380013 Abruzzo [Region: Italy] 380014 Molise [Region: Italy] 380015 Campania [Region: Italy] 380016 Puglia [Region: Italy] 380017 Basilicata [Region: Italy] 380018 Calabria [Region: Italy] 380019 Sicilia [Region: Italy] 380020 Sardegna [Region: Italy] 380097 Foregin Country [Region: Italy] 380099 NIU [Region: Italy] 404001 Nairobi [Province: Kenya] 404002 Central [Province: Kenya] 404003 Coast [Province: Kenya] 404004 Eastern [Province: Kenya] 404005 Northeastern [Province: Kenya] 404006 Nyanza [Province: Kenya] 404007 Rift Valley [Province: Kenya] 404008 Western [Province: Kenya] 404097 Abroad [Province: Kenya] 404098 Unknown [Province: Kenya] 404099 NIU (not in universe) [Province: Kenya] 454101 Chitipa [District: Malawi] 454102 Karonga [District: Malawi] 454103 Nkhata Bay, Likoma [District: Malawi] 454104 Rumphi [District: Malawi] 454105 Mzimba, Mzuzu City [District: Malawi] 454201 Kasungu [District: Malawi] 454202 Nkhotakota [District: Malawi] 454203 Ntchisi [District: Malawi] 454204 Dowa [District: Malawi] 454205 Salima [District: Malawi] 454206 Lilongwe, Lilongwe City [District: Malawi] 454207 Mchinji [District: Malawi] 454208 Dedza [District: Malawi] 454209 Ntcheu [District: Malawi] 454301 Mangochi [District: Malawi] 454302 Machinga [District: Malawi] 454303 Zomba, Zomba City [District: Malawi] 454304 Chiradzulu [District: Malawi] 454305 Blantyre, Blantyre City [District: Malawi] 454306 Mwanza, Neno [District: Malawi] 454307 Thyolo [District: Malawi] 454308 Mulanje [District: Malawi] 454309 Phalombe [District: Malawi] 454310 Chikwawa [District: Malawi] 454311 Nsanje [District: Malawi] 454312 Balaka [District: Malawi] 454997 Abroad [District: Malawi] 454998 Unknown [District: Malawi] 454999 NIU (not in universe) [District: Malawi] 508001 Niassa [Province: Mozambique] 508002 Cabo Delgado [Province: Mozambique] 508003 Nampula [Province: Mozambique] 508004 Zambézia [Province: Mozambique] 508005 Tete [Province: Mozambique] 508006 Manica [Province: Mozambique] 508007 Sofala [Province: Mozambique] 508008 Inhambane [Province: Mozambique] 508009 Gaza [Province: Mozambique] 508010 Maputo [Province: Mozambique] 508011 Cidade de Maputo [Province: Mozambique] 508097 Foreign Country [Province: Mozambique] 508098 Unknown [Province: Mozambique] 508099 NIU (not in universe) [Province: Mozambique] 598001 Western [Province: Papua New Guinea] 598002 Gulf [Province: Papua New Guinea] 598003 Central [Province: Papua New Guinea] 598004 National Capital District [Province: Papua New Guinea] 598005 Milne Bay [Province: Papua New Guinea] 598006 Northern [Province: Papua New Guinea] 598007 Southern Highlands, Hela [Province: Papua New Guinea] 598008 Enga [Province: Papua New Guinea] 598009 Western Highlands, Jiwaka [Province: Papua New Guinea] 598010 Chimbu [Province: Papua New Guinea] 598011 Eastern Highlands [Province: Papua New Guinea] 598012 Morobe [Province: Papua New Guinea] 598013 Madang [Province: Papua New Guinea] 598014 East Sepik [Province: Papua New Guinea] 598015 West Sepik [Province: Papua New Guinea] 598016 Manus [Province: Papua New Guinea] 598017 New Ireland [Province: Papua New Guinea] 598018 East New Britain [Province: Papua New Guinea] 598019 West New Britain [Province: Papua New Guinea] 598020 Autonomous Region of Bougainville [Province: Papua New Guinea] 598097 Foreign country [Province: Papua New Guinea] 598098 Unknown [Province: Papua New Guinea] 598099 NIU (not in universe) [Province: Papua New Guinea] 616002 Dolnośląskie [Vovoidship (Province): Poland] 616004 Kujawsko pomorskie [Vovoidship (Province): Poland] 616006 Lubelskie [Vovoidship (Province): Poland] 616008 Lubuskie [Vovoidship (Province): Poland] 616010 Łódzkie [Vovoidship (Province): Poland] 616012 Małopolskie [Vovoidship (Province): Poland] 616014 Mazowieckie [Vovoidship (Province): Poland] 616016 Opolskie [Vovoidship (Province): Poland] 616018 Podkarpackie [Vovoidship (Province): Poland] 616020 Podlaskie [Vovoidship (Province): Poland] 616022 Pomorskie [Vovoidship (Province): Poland] 616024 Śląskie [Vovoidship (Province): Poland] 616026 Świętokrzyskie [Vovoidship (Province): Poland] 616028 Warmińsko mazurskie [Vovoidship (Province): Poland] 616030 Wielkopolskie [Vovoidship (Province): Poland] 616032 Zachodniopomorskie [Vovoidship (Province): Poland] 616098 Unknown [Vovoidship (Province): Poland] 616099 NIU (not in universe) [Vovoidship (Province): Poland] 620111 Minho-Lima [Subregion: Portugal] 620112 Cávado [Subregion: Portugal] 620113 Ave [Subregion: Portugal] 620114 Grande Porto [Subregion: Portugal] 620115 Tâmega [Subregion: Portugal] 620116 Entre Douro e Vouga [Subregion: Portugal] 620117 Douro [Subregion: Portugal] 620118 Alto Trás-os-Montes [Subregion: Portugal] 620150 Algarve [Subregion: Portugal] 620161 Baixo Vouga [Subregion: Portugal] 620162 Baixo Mondego [Subregion: Portugal] 620163 Pinhal Litoral [Subregion: Portugal] 620165 Dão-Lafões [Subregion: Portugal] 620166 Oeste [Subregion: Portugal] 620167 Médio Tejo [Subregion: Portugal] 620169 Other Center [Subregion: Portugal] 620171 Grande Lisboa [Subregion: Portugal] 620172 Península de Setúbal [Subregion: Portugal] 620185 Lezíria do Tejo [Subregion: Portugal] 620189 Other Alentejo [Subregion: Portugal] 620200 Região Autónoma dos Açores [Subregion: Portugal] 620300 Região Autónoma da Madeira [Subregion: Portugal] 620998 Foreign country [Subregion: Portugal] 620999 NIU (not in universe) [Subregion: Portugal] 643001 Altai Krai [Region: Russia] 643003 Krasnodar Krai [Region: Russia] 643004 Krasnoyarsk Krai [Region: Russia] 643005 Primorsky Krai [Region: Russia] 643007 Stavropol Krai [Region: Russia] 643008 Khabarovsk Krai [Region: Russia] 643010 Amur Oblast [Region: Russia] 643011 Arkhangelsk Oblast [Region: Russia] 643012 Astrakhan Oblast [Region: Russia] 643013 Nenets Autonomous District 643014 Belgorod Oblast [Region: Russia] 643015 Bryansk Oblast [Region: Russia] 643017 Vladimir Oblast [Region: Russia] 643018 Volgograd Oblast [Region: Russia] 643019 Vologda Oblast [Region: Russia] 643020 Voronezh Oblast [Region: Russia] 643022 Nizhny Novgorod Oblast [Region: Russia] 643024 Ivanovo Oblast [Region: Russia] 643025 Irkutsk Oblast [Region: Russia] 643026 Republic of Ingushetia [Region: Russia] 643027 Kaliningrad Oblast [Region: Russia] 643028 Tver Oblast [Region: Russia] 643029 Kaluga Oblast [Region: Russia] 643030 Kamchatka Krai [Region: Russia] 643032 Kemerovo Oblast [Region: Russia] 643033 Kirov Oblast [Region: Russia] 643034 Kostroma Oblast [Region: Russia] 643036 Samara Oblast [Region: Russia] 643037 Kurgan Oblast [Region: Russia] 643038 Kursk Oblast [Region: Russia] 643040 City of Federal Importance St. Petersburg [Region: Russia] 643041 Leningrad Oblast [Region: Russia] 643042 Lipetsk Oblast [Region: Russia] 643044 Magadan Oblast [Region: Russia] 643045 City of Federal Importance Moscow [Region: Russia] 643046 Moscow Oblast [Region: Russia] 643047 Murmansk Oblast [Region: Russia] 643049 Novgorod Oblast [Region: Russia] 643050 Novosibirsk Oblast [Region: Russia] 643052 Omsk Oblast [Region: Russia] 643053 Orenburg Oblast [Region: Russia] 643054 Oryol Oblast [Region: Russia] 643056 Penza Oblast [Region: Russia] 643057 Perm Krai [Region: Russia] 643058 Pskov Oblast [Region: Russia] 643060 Rostov Oblast [Region: Russia] 643061 Ryazan Oblast [Region: Russia] 643063 Saratov Oblast [Region: Russia] 643064 Sakhalin Oblast [Region: Russia] 643065 Sverdlovsk Oblast [Region: Russia] 643066 Smolensk Oblast [Region: Russia] 643068 Tambov Oblast [Region: Russia] 643069 Tomsk Oblast [Region: Russia] 643070 Tula Oblast [Region: Russia] 643071 Tyumen Oblast [Region: Russia] 643072 Khanty-Mansi Autonomous District - Yugra [Region: Russia] 643073 Ulyanovsk Oblast [Region: Russia] 643074 Yamalo-Nenets Autonomous District [Region: Russia] 643075 Chelyabinsk Oblast [Region: Russia] 643076 Zabaykalsky Krai, Aginsky Buryat District [Region: Russia] 643077 Chukotka Autonomous Region [Region: Russia] 643078 Yaroslavskaya Oblast [Region: Russia] 643079 Republic of Adygea [Region: Russia] 643080 Republic of Bashkortostan [Region: Russia] 643081 Republic of Buryatia [Region: Russia] 643082 Republic of Dagestan [Region: Russia] 643083 Kabardino-Balkaria Republic [Region: Russia] 643084 Altai Republic [Region: Russia] 643085 Republic of Kalmykia [Region: Russia] 643086 Republic of Karelia [Region: Russia] 643087 Komi Republic [Region: Russia] 643088 Mari El Republic [Region: Russia] 643089 Republic of Mordovia [Region: Russia] 643090 Republic of North Ossetia-Alania [Region: Russia] 643091 Karachay-Cherkess Republic [Region: Russia] 643092 Republic of Tatarstan [Region: Russia] 643093 Tyva Republic [Region: Russia] 643094 Udmurtia Republic [Region: Russia] 643095 Republic of Khakassia [Region: Russia] 643096 Chechen Republic [Region: Russia] 643097 Chuvash Republic [Region: Russia] 643098 Republic of Sakha (Yakutia) [Region: Russia] 643099 Jewish Autonomous Region [Region: Russia] 643997 Foreign Country [Region: Russia] 643998 Unknown [Region: Russia] 643999 NIU [Region: Russia] 686001 Dakar [Region: Senegal] 686002 Ziguinchor [Region: Senegal] 686003 Diourbel [Region: Senegal] 686004 Saint Louis, Louga, Matam [Region: Senegal] 686005 Tambacounda, Kedougou [Region: Senegal] 686006 Kaolack, Fatick, Kaffrine [Region: Senegal] 686007 Thiès [Region: Senegal] 686010 Kolda, Sedhiou [Region: Senegal] 686097 Abroad [Region: Senegal] 686099 NIU (not in universe) [Region: Senegal] 724011 Galicia [Communities & autonomous city: Spain] 724012 Principado de Asturias [Communities & autonomous city: Spain] 724013 Cantabria [Communities & autonomous city: Spain] 724021 País Vasco [Communities & autonomous city: Spain] 724022 Comunidad Foral de Navarra [Communities & autonomous city: Spain] 724023 La Rioja [Communities & autonomous city: Spain] 724024 Aragón [Communities & autonomous city: Spain] 724030 Comunidad de Madrid [Communities & autonomous city: Spain] 724041 Castilla y León [Communities & autonomous city: Spain] 724042 Castilla-La Mancha [Communities & autonomous city: Spain] 724043 Extremadura [Communities & autonomous city: Spain] 724051 Cataluña [Communities & autonomous city: Spain] 724052 Comunidad Valenciana [Communities & autonomous city: Spain] 724053 Islas Baleares [Communities & autonomous city: Spain] 724061 Andalucía [Communities & autonomous city: Spain] 724062 Región de Murcia [Communities & autonomous city: Spain] 724063 Ciudad Autónoma de Ceuta [Communities & autonomous city: Spain] 724064 Ciudad Autónoma de Melilla [Communities & autonomous city: Spain] 724070 Canarias [Communities & autonomous city: Spain] 724097 Foreign country [Communities & autonomous city: Spain] 724999 NIU (not in universe) [Communities & autonomous city: Spain] 728011 Northern [State:South Sudan] 728012 Nahr El Nil [State:South Sudan] 728021 Red Sea [State:South Sudan] 728022 Kassala [State:South Sudan] 728023 Al Gedarif [State:South Sudan] 728031 Khartoum [State:South Sudan] 728041 Al Gezira [State:South Sudan] 728042 White Nile [State:South Sudan] 728043 Sinnar [State:South Sudan] 728044 Blue Nile [State:South Sudan] 728051 North Kordofan [State:South Sudan] 728052 South Kordofan [State:South Sudan] 728061 North Darfur [State:South Sudan] 728062 West Darfur [State:South Sudan] 728063 South Darfur [State:South Sudan] 728071 Upper Nile [State: South Sudan] 728072 Jonglei [State: South Sudan] 728073 Unity [State: South Sudan] 728081 Warrap [State: South Sudan] 728082 Northern Bahr El Ghazal [State: South Sudan] 728083 Western Bahr El Ghazal [State: South Sudan] 728084 Lakes [State: South Sudan] 728091 Western Equatoria [State: South Sudan] 728092 Central Equatoria [State: South Sudan] 728093 Eastern Equatoria [State: South Sudan] 728098 Abroad [State: South Sudan] 728099 NIU (Not in universe) [State: South Sudan] 729011 Northern [State: Sudan] 729012 Nahr El Nil [State: Sudan] 729021 Red Sea [State: Sudan] 729022 Kassala [State: Sudan] 729023 Al Gedarif [State: Sudan] 729031 Khartoum [State: Sudan] 729041 Al Gezira [State: Sudan] 729042 White Nile [State: Sudan] 729043 Sinnar [State: Sudan] 729044 Blue Nile [State: Sudan] 729051 North Kordofan [State: Sudan] 729052 South Kordofan [State: Sudan] 729061 North Darfur [State: Sudan] 729062 West Darfur [State: Sudan] 729063 South Darfur [State: Sudan] 729071 Upper Nile [State: Sudan] 729072 Jonglei [State: Sudan] 729073 Unity [State: Sudan] 729081 Warrap [State: Sudan] 729082 Northern Bahr El Ghazal [State: Sudan] 729083 Western Bahr El Ghazal [State: Sudan] 729084 Lakes [State: Sudan] 729091 Western Equatoria [State: Sudan] 729092 Central Equatoria [State: Sudan] 729093 Eastern Equatoria [State: Sudan] 729098 Abroad [State: Sudan] 780010 Port of Spain [Region: Trinidad and Tobago] 780020 San Fernando [Region: Trinidad and Tobago] 780080 Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] 780094 St. Paul, St. Mary, St. David, St. George, St. Patrick, St. Andrew, St. John, Tobago [Region: Trinidad and Tobago] 780098 Unknown [Region: Trinidad and Tobago] 780099 NIU (not in universe) [Region: Trinidad and Tobago] 826101 North East [Region: United Kingdom] 826102 North West [Region: United Kingdom] 826103 Yorkshire and the Humber [Region: United Kingdom] 826104 East Midlands [Region: United Kingdom] 826105 West Midlands [Region: United Kingdom] 826106 East of England [Region: United Kingdom] 826107 South East [Region: United Kingdom] 826108 South West [Region: United Kingdom] 826110 Outer London, Inner London [Region: United Kingdom] 826111 Scotland [Region: United Kingdom] 826112 Wales [Region: United Kingdom] 826113 Northern Ireland [Region: United Kingdom] 826197 Other country [Region: United Kingdom] 826198 Unknown [Region: United Kingdom] 826199 NIU (not in universe) [Region: United Kingdom] 834001 Dodoma [Region: Tanzania] 834002 Arusha, Manyara [Region: Tanzania] 834003 Kilimanjaro [Region: Tanzania] 834004 Tanga [Region: Tanzania] 834005 Morogoro [Region: Tanzania] 834006 Pwani [Region: Tanzania] 834007 Dar es Salaam [Region: Tanzania] 834008 Lindi [Region: Tanzania] 834009 Mtwara [Region: Tanzania] 834010 Ruvuma [Region: Tanzania] 834011 Iringa, Njombe [Region: Tanzania] 834012 Mbeya [Region: Tanzania] 834013 Singida [Region: Tanzania] 834014 Tabora [Region: Tanzania] 834015 Katavi, Rukwa [Region: Tanzania] 834016 Kigoma [Region: Tanzania] 834019 Geita, Kagera, Mwanza, Shinyanga, Simiyu [Region: Tanzania] 834020 Mara [Region: Tanzania] 834051 Zanzibar North [Region: Tanzania] 834052 Zanzibar South [Region: Tanzania] 834053 Zanzibar Town/West [Region: Tanzania] 834054 Pemba North [Region: Tanzania] 834055 Pemba South [Region: Tanzania] 834097 Abroad [Region: Tanzania] 834098 Unknown [Region: Tanzania] 834099 NIU (not in universe) [Region: Tanzania] 840001 Alabama [State: United States] 840002 Alaska [State: United States] 840004 Arizona [State: United States] 840005 Arkansas [State: United States] 840006 California [State: United States] 840008 Colorado [State: United States] 840009 Connecticut [State: United States] 840010 Delaware [State: United States] 840011 District of Columbia [State: United States] 840012 Florida [State: United States] 840013 Georgia [State: United States] 840015 Hawaii [State: United States] 840016 Idaho [State: United States] 840017 Illinois [State: United States] 840018 Indiana [State: United States] 840019 Iowa [State: United States] 840020 Kansas [State: United States] 840021 Kentucky [State: United States] 840022 Louisiana [State: United States] 840023 Maine [State: United States] 840024 Maryland [State: United States] 840025 Massachusetts [State: United States] 840026 Michigan [State: United States] 840027 Minnesota [State: United States] 840028 Mississippi [State: United States] 840029 Missouri [State: United States] 840030 Montana [State: United States] 840031 Nebraska [State: United States] 840032 Nevada [State: United States] 840033 New Hampshire [State: United States] 840034 New Jersey [State: United States] 840035 New Mexico [State: United States] 840036 New York [State: United States] 840037 North Carolina [State: United States] 840038 North Dakota [State: United States] 840039 Ohio [State: United States] 840040 Oklahoma [State: United States] 840041 Oregon [State: United States] 840042 Pennsylvania [State: United States] 840044 Rhode Island [State: United States] 840045 South Carolina [State: United States] 840046 South Dakota [State: United States] 840047 Tennessee [State: United States] 840048 Texas [State: United States] 840049 Utah [State: United States] 840050 Vermont [State: United States] 840051 Virginia [State: United States] 840053 Washington [State: United States] 840054 West Virginia [State: United States] 840055 Wisconsin [State: United States] 840056 Wyoming [State: United States] 840097 Abroad [State: United States] 840999 NIU (not in universe) [State: United States] 894001 Central [Province: Zambia] 894002 Copperbelt [Province: Zambia] 894003 Eastern, Muchinga, Northern [Province: Zambia] 894004 Luapula [Province: Zambia] 894005 Lusaka [Province: Zambia] 894008 North Western [Province: Zambia] 894009 Southern [Province: Zambia] 894010 Western [Province: Zambia] 894097 Foreign country [Province: Zambia] 894098 Unknown [Province: Zambia] 894099 NIU (not in universe) [Province: Zambia] Migration: Global Variables -- PERSON Years residing in current locality MIGYRS1 indicates how many years the person has resided in their current locality of residence. 00 Less than 1 year 01 1 year (or 1 year or less) 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95+ years 96 Less than 5 years 97 More than 5 years 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Reason for migration MIGCAUSE indicates the reason why the person moved from their previous place of residence. 00 NIU (not in universe) 10 Work 11 Seeking work 12 Job relocation 13 Job assignment 14 Opportunity 15 Proximity to work 16 Job loss 19 Other work 20 Family move 21 Follow household head 22 Follow spouse 23 Follow relative 24 Marriage of a family member 25 Divorce or separation of a family member 26 Healthcare or age of a family member 27 Death or birth of a family member 29 Other family 30 Education 31 Studies 32 End of education 33 Proximity to education 34 Other education 40 Marriage, divorce, widowhood 41 Marriage or union 42 Divorce or widowhood 50 Insecurity, disaster, or violence 51 War, conflict 52 Violence or insecurity 53 Domestic violence 54 Social or political problems, including security 55 Natural disaster 56 Refugee, reason not specified 57 Asylum seeker, reason not specified 59 Other insecurity, disaster, or violence 60 Personal 61 Age related reasons 62 Quality of life 63 Become independent 69 Other personal 70 Other reason 71 Health 72 Repatriation 73 Retirement 74 House or flat acquisition 75 Housing problems 76 Visiting 77 Ordination 78 Military or institutional housing 79 Other reason, not elsewhere classified 99 Unknown Migration: Global Variables -- PERSON Province of residence 1 year ago, Kenya; consistent boundaries, GIS MIG1_1_KE indicates the person's province of residence within Kenya 1 year ago. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. 404001 Nairobi 404002 Central 404003 Coast 404004 Eastern 404005 Northeastern 404006 Nyanza 404007 Rift Valley 404008 Western 404097 Abroad 404098 Unknown 404099 NIU (not in universe) Migration: F-N Variables -- PERSON District of residence 1 year ago, Kenya; consistent boundaries, GIS MIG2_1_KE indicates the person's district of residence in Kenya 1 year ago. Migration district codes from MIG2_1_KE are compatible with codes from GEO2_KE. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. 404001047 Nairobi City 404002018 Nyandarua 404002019 Nyeri 404002020 Kirinyaga 404002022 Kiambu, Murang'a 404002099 Central Province, unknown district 404003001 Mombasa 404003002 Kwale 404003003 Kilifi 404003004 Tana River 404003005 Lamu 404003006 Taita-Taveta 404003099 Coast Province, unknown district 404004010 Marsabit 404004011 Isiolo 404004012 Meru, Tharaka-Nithi 404004015 Kitui 404004016 Machakos, Makueni, Embu 404004099 Eastern Province, unknown district 404005007 Garissa 404005008 Wajir 404005009 Mandera 404005099 Northeastern Province, unknown district 404006041 Siaya 404006042 Kisumu 404006043 Homa Bay, Migori 404006045 Kisii, Nyamira 404006099 Nyanza Province, unknown district 404007023 Turkana 404007024 West Pokot 404007025 Samburu 404007026 Trans Nzoia 404007027 Uasin Gishu 404007028 Elgeyo-Marakwet 404007029 Nandi 404007030 Baringo, Laikipia 404007032 Nakuru 404007033 Narok 404007034 Kajiado 404007035 Kericho, Bomet 404007099 Rift Valley Province, unknown district 404008037 Kakamega, Vihiga 404008039 Bungoma 404008040 Busia 404008099 Western Province, unknown district 404097097 Abroad 404098098 Unknown 404099099 NIU (not in universe) Migration: F-N Variables -- PERSON Disability status DISABLED indicates whether the person reported a disability of any kind. 0 NIU (not in universe) 1 Yes, disabled 2 No, not disabled 9 Unknown Disability Variables -- PERSON Employment disability DISEMP indicates if the respondent was economically inactive because of disabilities or, in some instances, other health-related reasons. 1 Disabled 2 Not disabled 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Blind or vision-impaired DISBLND indicates whether the person was blind or had limited vision. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Deaf or hearing-impaired DISDEAF indicates whether the person was deaf or had limited hearing. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Mute or speech impaired DISMUTE indicates if the person could not speak or had a significant speech impediment. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Disability limiting ability to walk DISMOBIL indicates whether the person has difficulty walking or climbing stairs. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Mental disability DISMNTL indicates whether the person suffered a mental disability in the form of diminished capacity. 0 NIU (not in universe) 1 Yes 2 No 9 Unknown Disability Variables -- PERSON Personal care limitation DISCARE indicates whether the respondent had any permanent condition that made it difficult for him/her to take care of their personal needs. 0 NIU (not in universe) 1 Yes, personal care limitation 2 No personal care limitation 9 Unknown Disability Variables -- PERSON Work disability DISWORK indicates whether the respondent had any lasting physical or mental health condition, that either limited the amount or type of work they could do or prevented them from working altogether. This did not include temporary health conditions. 0 NIU (not in universe) 1 No disability that affects work 2 Disability causes difficulty or limits work 3 Disability prevents work 4 Unknown Disability Variables -- PERSON Difficulty with self-care (Washington group) WGCARE indicates the person's level of difficulty in caring for herself or himself, related to activities such as dressing or bathing. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Difficulty remembering or concentrating (Washington group) WGCOGN indicates the person's level of difficulty in remembering or concentrating. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Difficulty communicating (Washington group) WGCOMM indicates the person's level of difficulty in communicating, related to being understood or understanding, even in a usual language. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Difficulty hearing (Washington group) WGHEAR indicates the person's level of difficulty in hearing, even if using a hearing aid. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Difficulty walking or climbing stairs (Washington group) WGMOBIL indicates the person's level of difficulty in walking or climbing stairs. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Difficulty seeing (Washington group) WGVISION indicates the person's level of difficulty in seeing, even while wearing glasses. 1 No difficulty 2 Some difficulty 3 A lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Refugee status REFUGEE indicates whether a person is a refugee or not. 0 NIU (not in universe) 1 Refugee 2 Registered refugee 3 Non-registered refugee 4 Non-refugee 9 Unknown/missing Other Person Variables -- PERSON Person number (within household) Kenya 2019: All records This variable indicates the person number (within household). 00 Household record 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 Technical Person Variables -- PERSON Relationship to household head <span class="h2">A: Information regarding all persons</span></p> <p>P-10. Relationship: What is [the respondent]'s relationship to the head of this household?</p> <div class="i1">[] 1. Head<br />[] 2. Spouse<br />[] 3. Son/daughter<br />[] 4. Grandchild<br />[] 5. Brother/sister<br />[] 6. Father/mother<br />[] 7. Nephew/niece<br />[] 8. In-law<br />[] 9. Grandparent<br />[] 10. Other relative<br />[] 11. Non-relative<br />[] 99. DK</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.3. Columns P10 and P11: Relationship and sex</p> <div class="i1">i. After you have written all the names in column P00, enter relationship in column P10 and sex in column P11. For example: for Head, select "1" in P10 and insert the appropriate code in P11 as far as sex is concerned. Then code the relationship of each person to the head of household, for example "2" for spouse (refers to the partner or wife or husband depending on who the household head is), "3" for son/daughter, "4" for grandchild, "5" for brother/sister, "6" for father/mother, "7" for nephew/niece, "8" for in-law (father/mother in-law, brother/sister in-law), "9" for grandparent, "10" for other relative not elsewhere classified, "11" for non-relative such as visitors, friends, etc., and "99" for those who say "don't know" for relationship.<br /><br />ii. There are several persons who may not be related by blood or marriage but constitute a household, mostly in urban areas. Without telling them, select one of them as 'head' (enter "1 ") and the rest as 'non-relative' (enter "11").<br /><br />iii. There are certain communities where women are culturally allowed to "marry" other women. For purposes of the census, marriage should involve only partners of the opposite sex. Whenever you encounter such cases where one woman (supposedly the head of the household) claims that another woman is her "spouse", select "10" (other-relative) rather than "2" (spouse) in P10.<br /><br />iv. Make sure you understand the relationship well before you make any entry. In other words, relationship of each person is linked to the household head (person No. 1 on the list). For instance, the head's relationship to himself/herself is code "1" (head). Ensure that the entry is strictly and legibly written within the boxes provided.<br />Check that the sex is compatible with relationship; do not assign "male" to persons shown as wives or daughters nor "female" for persons shown as sons or husbands. Take particular care to record the sex of very young children correctly. Often, you will not know whether a baby carried on its mother's back is a boy or a girl. In such cases, you must ask - do not guess.<br /><br />For Male, select 1; for Female, select 2. For other sex characteristics, select 3; "other". An example of other sex characteristics is an intersex. Intersex refers to a person who is born with ambiguous sex organs, which makes it difficult to determine whether the person is male or female.<br /><br />Note: Select the answer as provided by the respondent and not as per your judgement.<br />You should ensure that sex is recorded for everybody.</div> Kenya 2019: All persons This variable indicates the person's relationship to household head. 01 Head 02 Spouse 03 Son or daughter 04 Grandchild 05 Brother or sister 06 Father or mother 07 Nephew or niece 08 In-law 09 Other relative 10 Non-relative 11 Group quarters 98 Unknown Demographic Variables -- PERSON Sex <span class="h2">A: Information regarding all persons</span></p> <p>P-11. Sex: What is [the respondent]'s sex?</p> <div class="i1">[] 1. Male<br />[] 2. Female<br />[] 3. Other</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.3. Columns P10 and P11: Relationship and sex</p> <div class="i1">i. After you have written all the names in column P00, enter relationship in column P10 and sex in column P11. For example: for Head, select "1" in P10 and insert the appropriate code in P11 as far as sex is concerned. Then code the relationship of each person to the head of household, for example "2" for spouse (refers to the partner or wife or husband depending on who the household head is), "3" for son/daughter, "4" for grandchild, "5" for brother/sister, "6" for father/mother, "7" for nephew/niece, "8" for in-law (father/mother in-law, brother/sister in-law), "9" for grandparent, "10" for other relative not elsewhere classified, "11" for non-relative such as visitors, friends, etc., and "99" for those who say "don't know" for relationship.<br /><br />ii. There are several persons who may not be related by blood or marriage but constitute a household, mostly in urban areas. Without telling them, select one of them as 'head' (enter "1 ") and the rest as 'non-relative' (enter "11").<br /><br />iii. There are certain communities where women are culturally allowed to "marry" other women. For purposes of the census, marriage should involve only partners of the opposite sex. Whenever you encounter such cases where one woman (supposedly the head of the household) claims that another woman is her "spouse", select "10" (other-relative) rather than "2" (spouse) in P10.<br /><br />iv. Make sure you understand the relationship well before you make any entry. In other words, relationship of each person is linked to the household head (person No. 1 on the list). For instance, the head's relationship to himself/herself is code "1" (head). Ensure that the entry is strictly and legibly written within the boxes provided.<br />Check that the sex is compatible with relationship; do not assign "male" to persons shown as wives or daughters nor "female" for persons shown as sons or husbands. Take particular care to record the sex of very young children correctly. Often, you will not know whether a baby carried on its mother's back is a boy or a girl. In such cases, you must ask - do not guess.<br /><br />For Male, select 1; for Female, select 2. For other sex characteristics, select 3; "other". An example of other sex characteristics is an intersex. Intersex refers to a person who is born with ambiguous sex organs, which makes it difficult to determine whether the person is male or female.<br /><br />Note: Select the answer as provided by the respondent and not as per your judgement.<br />You should ensure that sex is recorded for everybody.</div> Kenya 2019: All persons This variable indicates the person's sex. 1 Male 2 Female 3 Intersex Demographic Variables -- PERSON Age <span class="h2">A: Information regarding all persons</span></p> <p>P-12. Age: How old is [the respondent]?</p> <div class="i1">Record age in completed years. If under 1 year, record "00".<br /><br />Age _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.4. Column P12: Age <br />Age is one of the most important pieces of information to be sought in a census. You must try as much as possible to record the correct age of the respondent. Under no circumstances should this column be left blank. You must probe to make sure that you get even a rough estimate.</p> <p>How old is [the respondent]?</p> <div class="i1">i. Always start by asking the person's age and follow up with the question on the date of birth as a consistency check on the former. Enter the person's age in completed years - that is, the person's age at his or her last birthday. For babies under one year of age, enter "0", etc.<br /><br />ii. The two questions, P-12 and P-13, should be asked separately and reconciliation made if both don't yield the same answer. Do not calculate year of birth in P-13 based on answer given in P-12.<br /><br />iii. Be careful not to round up ages to the next birthday. For example, a child who is aged four years and eleven months should, be entered as "4" and not "5".<br /><br />iv. Many people do not know their ages. If a person's age is not known, you must make the best estimate possible.<br /><br />v. There are various ways in which you can estimate a person's age. Sometimes, people have documents, such as baptismal certificates, which show the year of birth, in which case it is easy to calculate age. Most people have identity cards showing when they were born. These ID cards may be grossly inaccurate for some of the older people. Avoid using the IDs as the sole means to estimate such a person's age. However, for persons below 50 years of age the ID cards may generally give a more accurate representation of age.<br /><br />vi. Generally, it is not so easy to estimate age for members of the household if all of them are ignorant of their ages. Concentrate first on establishing the age(s) of one or two persons in the household. One reliable age may help in working out the ages of others if it is known whether they are older or younger and by how many years.<br /><br />vii. It is sometimes possible to estimate a person's age by relating his or her birth to some notable historical event. With these instructions, is a historical calendar of events (see appendix 1) which lists the dates of events in the history of each county. If the person can remember how old he/she was at the time of the event, you can work out the person's age.</div><p>How to use the historical calendar of events to estimate the respondent's age:</p> <div class="i1">i. Ask for any historical event (national or local) which occurred around the time of the birth/childhood of the respondent.<br /><br />ii. Ask how old the respondent was when that event occurred or how many years elapsed before his/her birth.<br /><br />Then use this information to work out his/her age. For example, if a respondent was about 15 years when Kenya attained her Independence, this person should be 15 + 55 (i.e. 12th Dec. 1963 to 24th August 2019) = 70 years.</div><p>If this method fails, you should try the following approach.</p> <div class="i1">i. Simply estimate how old he/she may be.<br /><br />ii. Then select from your list of local, or county historical events, some events which occurred about the time when according to your estimate, he/she must have been born.<br /><br />iii. Ask whether he/she has heard about any of those events.<br /><br />iv. If he/she has, ask him/her to give you an indication of how old he/she was when this event occurred or how many years elapsed before he/she was born.<br /><br />v. Then, from this information, work out his/her age.<br /><br />vi. Some ethnic groups have systems of 'age grades' or 'age sets' from which a person's age can be worked out. A person's age grade may only give a rough idea of his or her age since the same grade may have in it people of widely different ages, but it is better than nothing. Some ethnicities have grades for men but not for women, but you can often obtain an idea of a woman's age by asking which age grade of men she associated with, or which set her brothers belonged to and whether they are older or younger. Some age grades are listed in the Calendar of Events.<br /><br />vii. If all else fails, then base your estimate on biological relationships. For instance, a woman who does not know her age but who has two or three children of her own is unlikely to be less than 15 years old however small she may look. You may then try to work out her age by the following methods:<br /><br />viii. Determine the age of her oldest child.<br /><br />ix. Ask her to give an estimate of her age at the birth of this child. However, without further probing, you should not base your assumption on the oldest child who is presently living. There is the likelihood that in certain cases, the first child died or that the woman had miscarriages or stillbirths. Therefore, if the woman tells you that she had one miscarriage or stillbirth before the oldest living child was born, you should make your estimation from the year of the first miscarriage/still-birth or live birth.<br /><br />x. Only as a last resort should you estimate a person's age from his physical features. If you are obtaining information about an absent person from a third party, then rely on the information given to you to estimate the absent person's age.<br /><br />xi. When you have arrived at the best estimate you can make of a person's age, check that it is compatible with his or her relationship to others in the household. Obviously, children cannot be older than their parents.<br /><br />xii. Any estimate of age, however rough, is better than leaving the column blank. Do the best you can to report ages accurately.</div><p>Note: Questions P10-P12 on relationship, sex and age are extremely important and must be responded to for all persons enumerated in the household. Kenya 2019: All persons This variable indicates the person's age. 000 Less than 1 year 001 1 year 002 2 years 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100 101 101 102 102 103 103 104 104 105 105 106 106 107 107 108 108+ Demographic Variables -- PERSON Birth year <span class="h2">A: Information regarding all persons</span></p> <p>P-13. Date of Birth: What is [the respondent]'s date of birth?</p> <div class="i1"><span class="ital">mmyyyy</span><br /><br />Month _ _<br />Year _ _ _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.5. Column P13: Date of birth</p> <div class="i1">i. Even if the age of the respondent has been provided (in P12), you must ask for his/her date of birth. Do not assume. After getting the response for P13, compare with that of P12. If the responses differ, probe to establish whether it's P12 or P13 that is incorrect and adjust accordingly.<br /><br />ii. If the respondent knows his/her date of birth, enter it in the appropriate boxes for month and year. You will need to convert the month into numbers. For this, January is '01', February is '02', March is '03', and so on. If the respondent does not know his/her month of birth, select "DK" and ask his/her for the year of her birth. If he/she knows the year, enter it in the boxes for year. Try under all circumstances to obtain at least the year of birth.</div> Kenya 2019: All persons This variable indicates the person's birth year. 1911 1911 or before 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 Demographic Variables -- PERSON Birth month <span class="h2">A: Information regarding all persons</span></p> <p>P-13. Date of Birth: What is [the respondent]'s date of birth?</p> <div class="i1"><span class="ital">mmyyyy</span><br /><br />Month _ _<br />Year _ _ _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.5. Column P13: Date of birth</p> <div class="i1">i. Even if the age of the respondent has been provided (in P12), you must ask for his/her date of birth. Do not assume. After getting the response for P13, compare with that of P12. If the responses differ, probe to establish whether it's P12 or P13 that is incorrect and adjust accordingly.<br /><br />ii. If the respondent knows his/her date of birth, enter it in the appropriate boxes for month and year. You will need to convert the month into numbers. For this, January is '01', February is '02', March is '03', and so on. If the respondent does not know his/her month of birth, select "DK" and ask his/her for the year of her birth. If he/she knows the year, enter it in the boxes for year. Try under all circumstances to obtain at least the year of birth.</div> Kenya 2019: All persons This variable indicates the person's birth month. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December Demographic Variables -- PERSON Mother person number <span class="h2">A: Information regarding all persons</span></p> <p>P-14. Line number of mother</p> <div class="i1">Please insert line number of [the respondent]'s biological mother. Enter "00" if biological mother is not in the household.<br /><br />Line number _____</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.6. Column P14: Line number of mother</p> <p>If name's biological mother is alive and is listed in the household schedule - column p00, record "line number" of the mother. If she is not listed in the household, record "0". Kenya 2019: All persons This variable indicates the mother person number. 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 87 Mother not in household 88 Age difference is less than 12 98 Unknown Constructed Family Interrelationship Variables -- PERSON Usual household member <span class="h2">A: Information regarding all persons</span></p> <p>P-15. Usual member: Is [the respondent] a usual member of this household?</p> <div class="i1">[] 1. Yes<br />[] 2. No</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.7. Column P15: Usual member of household</p> <p>For purposes of the 2019 census, a person is considered to be a usual member of a household if he/she has been living in that household most of the time, (at least 6 months in the last 12 months); or intends to stay there for some time. Most of the people to be enumerated during the census have not moved for some time and thus categorising them as "usual residents" should be clear.</p> <p>Ask: "Is [the respondent] a usual member of this household?" <br />A usual member of a household is one who spends most of his/her time in the household. However, that person must be answerable to the household head, shares cooking arrangements with the rest and lives in the same house or compound or dwelling unit. If the answer is yes, select "1", if the listed person is not a "usual" member, then select "2" for No in the appropriate box. Usual residents may be citizens or not and may include refugees. Foreigners who have been in the country for a period of at least 6 months should be considered usual residents. Persons who have been absent from the household for most of the last 12 months should be excluded. A threshold of 6 months will be applied. If a person has lived continuously for most of the last 12 months, i.e. at least 6 months, not including temporary absences, or intends to live for at least six months at the place of enumeration, then this is a usual member of the household. This also applies to newborns or those who have come to stay indefinitely. Exceptions include children who are in schools and live in the households. Kenya 2019: Persons in private households [discrepancies: type I trace; type II none] This variable indicates whether the person is an usual household member. 1 Yes 2 No 8 Unknown Technical Person Variables -- PERSON Nationality <span class="h2">A: Information regarding all persons</span></p> <p>P-16. Ethnicity/nationality: What is [the respondent]'s ethnicity or nationality?</p> <div class="i1">For Kenyans, write ethnicity code. For non-Kenyans, write code for nationality. The code list is provided.<br /><br />Ethnicity/nationality _____ _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.8. Column P16: Ethnicity/nationality</p> <p>Ask: What is [the respondent]'s ethnicity or nationality?</p> <div class="i1">i. Care should be taken when asking this question as some respondents might be uneasy responding to it. First, establish the nationality of the person, then for Kenyans select the ethnicity from the code list provided. For non-Kenyans, select the nationality based on the code list provided for the country of origin.<br /><br />ii. For Kenyans, select ethnicity from the code list provided; for example: 'Kikuyu, 013'; 'Nandi, 411', etc. If code for ethnicity is not among those provided, select "Other Kenyan, select 543". If the respondent refuses to state his/her ethnicity, select "Refusal/Kenyan, 544".<br /><br />iii. For Kenyans of other origins, select the country code as provided. For example, persons originating from Asia should be coded "519", whereas persons originating from European countries should be coded "520", etc. For foreigners, select code using country of origin. For example, persons originating from United Arab Emirates should be coded "711". If the country of origin is not among those provided or is unknown, select "Other Nationality, 811". Those who indicate they are stateless, select "812". CAPI will provide a drop down list.<br /><br />iv. Accept the answer as given to you without question. Do not get involved in any argument on this issue. The census is not concerned with the legal position. Accept what the person tells you and record the ethnicity or nationality to which the person considers he/she belongs.</div><p>Note: Codes with "other" should be used as last option. Kenya 2019: All persons This variable indicates the person's nationality. 100 Kenya 605 Burundi 606 Cameroon 610 Comoros 611 Congo, Republic of the 613 Democratic Republic of the Congo 615 Egypt 617 Eritrea 618 Ethiopia 621 Ghana 628 Malawi 636 Nigeria 637 Rwanda 642 Somalia 643 South Africa 645 South Sudan 644 Sudan 649 Uganda 650 United Republic of Tanzania 651 Zambia 652 Zimbabwe 676 China 680 India 685 Japan 699 Pakistan 700 Philippines 702 Republic of Korea 704 Saudi Arabia 706 Sri Lanka 711 United Arab Emirates 713 Yemen 720 Belgium 726 Denmark 728 Finland 729 France 731 Germany 736 Italy 747 Netherlands 748 Norway 761 Sweden 765 Turkey 768 United Kingdom of Great Britain and Northern Ireland 774 Canada 790 United States of America 802 Australia 991 Africa, country unknown 992 Asia, country unknown 993 Europe, country unknown 994 Americas, country unknown 995 Oceania and Pacific, country unknown 996 Other nationality 997 Stateless (Galjeel, Shona, Wapemba, Pare, etc.) 998 Refugee or asylum seeker 999 Unknown Ethnicity and Language Variables -- PERSON Religion <span class="h2">A: Information regarding all persons</span></p> <p>P-17. Religion: What is [the respondent]'s religion?</p> <div class="i1">[] 1. Catholic<br />[] 2. Protestant<br />[] 3. Evangelical churches<br />[] 4. African instituted churches<br />[] 5. Orthodox<br />[] 6. Other Christian<br />[] 7. Islam<br />[] 8. Hindu<br />[] 9. Traditionists<br />[] 10. Other religion<br />[] 11. No religion/Atheists<br />[] 99. DK</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.9. Column P17: Religion</p> <p>Ask: What is [the respondent]'s religion?</p> <p>This question is seeking information on religious affiliation and not the name of the church one attends. For instance, I could be attending AIC, my religion in this case will be "protestant, select code 2", etc. The possible codes for column P17 are as follows;</p> <div class="i1">i. Catholics, select code "1": Those who believe in Catholic faith and recognize the Pope as the head of the Church<br />ii. Protestants, select code "2": Group of churches, which broke away from the Catholic Church, e.g. Anglican Church of Kenya (ACK), Presbyterian Church of East Africa (PCEA), African Inland Church (AIC), Lutheran, Quakers (Friends), Methodists, Seventh Day Adventists (SDA), Salvation Army, Baptists, etc.<br />iii. Evangelical Churches, select code "3": These are evangelical churches, e.g., CITAM, Redeemed, Full Gospel, Pentecostal, Deliverance, PAG, Kenya Assemblies, Winners, Apostolic church, Jehovah Witnesses, etc.<br />iv. African Instituted Churches, select code "4": This category caters for Christians who are not covered under select "1", "2", and "3" above, e.g., Legio Maria, Israel, Church of Christ, Roho, African Independent churches, etc.<br />v. Orthodox, select "5": Orthodox is the name of the branch of Judaism that strictly follows traditional beliefs and customs, derived from orthodox in the earlier meaning of "strictly observant". It is distinguished by its doctrinal differences from the other divisions of the Christian Church.<br />vi. Other Christian, select "6": Are individuals who confess Christian faith but are not affiliated to any of the above faiths, e.g., people who don't go to any church yet they consider themselves Christians.<br />vii. Islam, select "7": Those who profess the Islamic faith and recognize Muhammad as the prophet of God.<br />viii. Hindus/Sikh, select "8": These are religions that originated from South East Asian countries e.g., India, Pakistan, Bangladesh, Sri Lanka.<br />ix. Traditionalists, select "9": Those who believe in divine powers, e.g., Dini ya Msambwa, Tent of the Living God, etc.<br />x. Other Religion, select "10": These are people with religious affiliations other than those mentioned above- e.g., Buddhists, Bahais, Confucius etc.<br />xi. No religion/Atheists/Pagan, select "11": These are people who do not believe in the existence of supernatural powers. They do not follow any particular religion.<br />xii. DK, select "99".</div><p>Note: Please read and internalize these codes as provided. Take keen interest in the ones likely to be found in your county/region/or EA to avoid misclassification. Codes with "Other" should be used as a last option. Kenya 2019: All persons This variable indicates the person's religion. 01 Catholic 02 Protestant 03 Evangelical churches 04 African instituted churches 05 Orthodox 06 Other Christian 07 Islam 08 Hindu 09 Traditional 10 Other religion 11 No religion or atheist 98 Unknown Ethnicity and Language Variables -- PERSON Marital status <span class="h2">A: Information regarding all persons</span></p> <p>P-18. Marital status: What is [the respondent]'s marital status?</p> <div class="i1">Applicable to age 12 and above.<br /><br />[] 1. Never married<br />[] 2. Married monogamous<br />[] 3. Married polygamous<br />[] 4. Widowed<br />[] 5. Divorced<br />[] 6. Separated<br />[] 9. DK</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.10. Column P18: Marital status <br />The question on marital status is to be asked of persons aged 12 years and above. Marriage should only involve partners of the opposite sex.</p> <p>Ask if this person monogamously or polygamously married, widowed, divorced or separated, or never married. Record whatever the respondent mentions irrespective of the legal status.</p> <div class="i1">i. Persons who have never been married including young children should be coded "1" (never married).<br />ii. People who regard themselves as husband and wife should be coded "2" or "3" regardless of whether or not they have been through any civil, religious or customary ceremonies. The census is not trying to find out who is legally married and who is not. Accept the answer as it is given to you.<br />iii. If a person is widowed at the time of the Census, he/she should be coded as "4", i.e., widowed. If a person has been widowed but has since remarried, he/she should be coded as married ("2" or "3" as the case may be).<br />iv. If people think of themselves as divorced or separated, select code as such. It does not matter whether they have been to court or gone through other formalities. Accept the answer as it is given to you.<br />v. Accept what people say about their marital status. Do not embarrass yourself or the respondent by inquiring into the nature of marriage or divorce.</div> Kenya 2019: Persons age 12+ [discrepancies: type I trace; type II trace] This variable indicates the person's marital status. 01 Never married 02 Married, monogamous 03 Married, polygamous 04 Widowed 05 Divorced 06 Separated 98 Unknown 99 NIU (not in universe) Demographic Variables -- PERSON County of birth <span class="h2">A: Information regarding all persons</span></p> <p>P-19. Birth place: Where was [the respondent] born?</p> <div class="i1">Write county code, if in Kenya, or country code, if outside Kenya. The code list provided.<br /><br />Birth place _____ _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.11. Column P19: Country/county of birth</p> <p>Ask: Where was [the respondent] born?</p> <p>Birth place is the place of residence of mother at the time of the respondent's birth. This question is meant to establish persons who are not enumerated in their places of birth and hence have migrated. Sometimes, expectant mothers move from rural areas to urban areas for purposes of delivery since maternity services are better at the latter. This kind of movement is short lived and must not be confused with a migratory one. For example, if a woman who usually resides in Kiambu County moves to Nairobi to deliver her child, it will be assumed that the woman went to Nairobi purposely for maternity services. Thus, the County of birth of the child will be recorded as Kiambu County.</p> <div class="i1">i. For persons born in Kenya, select the county code if you are using hard copy questionnaire, else click on the dropdown menu and pick the appropriate county code using the list provided. For example, a person born in Kiambu, select "22", and for a person born in Tharaka Nithi, select "13".<br />ii. Relate the person's birthplace to the present county's frontiers/boundaries as far as possible. The codes must, however, be based on the code list provided.<br />iii. For persons born outside Kenya, select the country code if you are using the hard copy questionnaire. Otherwise, click on the dropdown menu and pick the appropriate country code. For example, a person born in Tanzania will be coded "849", Uganda "848", Somalia "842" etc.<br />iv. Select "998" if County/Country of birth is not known and "999" for not stated.</div> Kenya 2019: All persons This variable indicates the person's county of birth. 01 Mombasa 02 Kwale 03 Kilifi 04 Tana River 05 Lamu 06 Taita-Taveta 07 Garissa 08 Wajir 09 Mandera 10 Marsabit 11 Isiolo 12 Meru 13 Tharaka-Nithi 14 Embu 15 Kitui 16 Machakos 17 Makueni 18 Nyandarua 19 Nyeri 20 Kirinyaga 21 Murang'a 22 Kiambu 23 Turkana 24 West Pokot 25 Samburu 26 Trans Nzoia 27 Uasin Gishu 28 Elgeyo-Marakwet 29 Nandi 30 Baringo 31 Laikipia 32 Nakuru 33 Narok 34 Kajiado 35 Kericho 36 Bomet 37 Kakamega 38 Vihiga 39 Bungoma 40 Busia 41 Siaya 42 Kisumu 43 Homa Bay 44 Migori 45 Kisii 46 Nyamira 47 Nairobi City 97 Abroad 98 Unknown Nativity and Birthplace Variables -- PERSON Country of birth <span class="h2">A: Information regarding all persons</span></p> <p>P-19. Birth place: Where was [the respondent] born?</p> <div class="i1">Write county code, if in Kenya, or country code, if outside Kenya. The code list provided.<br /><br />Birth place _____ _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.11. Column P19: Country/county of birth</p> <p>Ask: Where was [the respondent] born?</p> <p>Birth place is the place of residence of mother at the time of the respondent's birth. This question is meant to establish persons who are not enumerated in their places of birth and hence have migrated. Sometimes, expectant mothers move from rural areas to urban areas for purposes of delivery since maternity services are better at the latter. This kind of movement is short lived and must not be confused with a migratory one. For example, if a woman who usually resides in Kiambu County moves to Nairobi to deliver her child, it will be assumed that the woman went to Nairobi purposely for maternity services. Thus, the County of birth of the child will be recorded as Kiambu County.</p> <div class="i1">i. For persons born in Kenya, select the county code if you are using hard copy questionnaire, else click on the dropdown menu and pick the appropriate county code using the list provided. For example, a person born in Kiambu, select "22", and for a person born in Tharaka Nithi, select "13".<br />ii. Relate the person's birthplace to the present county's frontiers/boundaries as far as possible. The codes must, however, be based on the code list provided.<br />iii. For persons born outside Kenya, select the country code if you are using the hard copy questionnaire. Otherwise, click on the dropdown menu and pick the appropriate country code. For example, a person born in Tanzania will be coded "849", Uganda "848", Somalia "842" etc.<br />iv. Select "998" if County/Country of birth is not known and "999" for not stated.</div> Kenya 2019: All persons This variable indicates the person's country of birth. 100 Kenya 600 Algeria 601 Angola 603 Botswana 605 Burundi 606 Cameroon 611 Congo, Republic of the 613 Democratic Republic of the Congo 615 Egypt 617 Eritrea 618 Ethiopia 621 Ghana 628 Malawi 636 Nigeria 637 Rwanda 642 Somalia 643 South Africa 644 Sudan 645 South Sudan 649 Uganda 650 Tanzania 651 Zambia 652 Zimbabwe 672 Bangladesh 676 China 680 India 685 Japan 699 Pakistan 700 Philippines 702 Republic of Korea 704 Saudi Arabia 706 Sri Lanka 711 United Arab Emirates 713 Yemen 720 Belgium 726 Denmark 728 Finland 729 France 731 Germany 736 Italy 747 Netherlands 748 Norway 761 Sweden 762 Switzerland 765 Turkey 768 United Kingdom 774 Canada 790 United States of America 802 Australia 991 Africa, country unknown 992 Asia, country unknown 993 Europe, country unknown 994 Americas, country unknown 995 Oceania and Pacific, country unknown 996 Other nationality 998 Refugee or asylum seeker 999 Unknown Nativity and Birthplace Variables -- PERSON County of residence one year ago (August 2018) <span class="h2">A: Information regarding all persons</span></p> <p>P-20. Previous residence: Where was [the respondent] living in August 2018?</p> <div class="i1">Write county code, if in Kenya, or country code, if outside Kenya. If aged under 1 year, write "000". The code list provided.<br /><br />Previous residence _____ _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.12. Column P20: Previous residence</p> <p>Ask: Where was [the respondent] living in August 2018?</p> <div class="i1">i. If the person is aged below one year, enter "000" in this column.<br />ii. For persons who were living in Kenya in August 2018, indicate the county code in column P20 (county codes are the same as for P19). For example, for persons whose previous residence was Mombasa county enter "001".<br />iii. A person who may have been absent from home temporarily for some reason such as visiting relatives or in hospital, or who may have been overseas on a visit of less than six months, should be shown where they normally lived in August, 2018.<br />iv. It is necessary to make a separate enquiry for each member of the household because a man, for instance, does not always take his wife and children along when he goes away to work. He may only have some of his family with him leaving the others behind.<br />v. If the person was living in another country in August 2018, use the code pertaining to the specific country.<br />vi. Enter "888" if county/country of previous residence is not known and "999" for not stated.</div> Kenya 2019: Persons age 1+ [discrepancies: type I none; type II trace] This variable indicates the person's county of residence one year ago (August 2018). 01 Mombasa 02 Kwale 03 Kilifi 04 Tana River 05 Lamu 06 Taita-Taveta 07 Garissa 08 Wajir 09 Mandera 10 Marsabit 11 Isiolo 12 Meru 13 Tharaka-Nithi 14 Embu 15 Kitui 16 Machakos 17 Makueni 18 Nyandarua 19 Nyeri 20 Kirinyaga 21 Murang'a 22 Kiambu 23 Turkana 24 West Pokot 25 Samburu 26 Trans Nzoia 27 Uasin Gishu 28 Elgeyo-Marakwet 29 Nandi 30 Baringo 31 Laikipia 32 Nakuru 33 Narok 34 Kajiado 35 Kericho 36 Bomet 37 Kakamega 38 Vihiga 39 Bungoma 40 Busia 41 Siaya 42 Kisumu 43 Homa Bay 44 Migori 45 Kisii 46 Nyamira 47 Nairobi City 97 Abroad 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Country of residence one year ago (August 2018) <span class="h2">A: Information regarding all persons</span></p> <p>P-20. Previous residence: Where was [the respondent] living in August 2018?</p> <div class="i1">Write county code, if in Kenya, or country code, if outside Kenya. If aged under 1 year, write "000". The code list provided.<br /><br />Previous residence _____ _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.12. Column P20: Previous residence</p> <p>Ask: Where was [the respondent] living in August 2018?</p> <div class="i1">i. If the person is aged below one year, enter "000" in this column.<br />ii. For persons who were living in Kenya in August 2018, indicate the county code in column P20 (county codes are the same as for P19). For example, for persons whose previous residence was Mombasa county enter "001".<br />iii. A person who may have been absent from home temporarily for some reason such as visiting relatives or in hospital, or who may have been overseas on a visit of less than six months, should be shown where they normally lived in August, 2018.<br />iv. It is necessary to make a separate enquiry for each member of the household because a man, for instance, does not always take his wife and children along when he goes away to work. He may only have some of his family with him leaving the others behind.<br />v. If the person was living in another country in August 2018, use the code pertaining to the specific country.<br />vi. Enter "888" if county/country of previous residence is not known and "999" for not stated.</div> Kenya 2019: Persons age 1+ [discrepancies: type I none; type II trace] This variable indicates the person's country of residence one year ago (August 2018). 100 Kenya 605 Burundi 611 Congo, Republic of the 613 Democratic Republic of the Congo 615 Egypt 617 Eritrea 618 Ethiopia 636 Nigeria 637 Rwanda 642 Somalia 643 South Africa 644 Sudan 645 South Sudan 649 Uganda 650 Tanzania 651 Zambia 671 Bahrain 676 China 680 India 699 Pakistan 701 Qatar 704 Saudi Arabia 711 United Arab Emirates 729 France 731 Germany 736 Italy 747 Netherlands 761 Sweden 768 United Kingdom of Great Britain and Northern Ireland 774 Canada 790 United States of America 802 Australia 991 Africa, country unspecified 992 Asia, country unknown 993 Europe, country unspecified 994 America, country unknown 995 Oceania and Pacific, country unspecified 998 Unknown 999 NIU (not in universe) Migration: Global Variables -- PERSON Month moved to this county <span class="h2">A: Information regarding all persons</span></p> <p>Duration of residence: When did [the respondent] move to the current county?</p> <div class="i1">For respondents enumerated in their county of birth, code month and year of birth. If date of movement is not known, write "99" for month and "9999" for year.<br /><br />P-21. Month _ _<br /><br />P-22. Year _ _ _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.13. Column P21-P22: Duration of residence</p> <p>Ask: When did [the respondent] move to the current county?</p> <div class="i1">i. Record the month in P21 (e.g. "05" for May) and year in P22 (e.g. 1997). Check to see that the person's age is consistent with duration of residence, i.e., the person's age must always be greater or equal to duration of residence.<br />ii. If the date one moved is not known or not stated, enter "99" for month in columns P21 and "9999" for year in column P22.</div> Kenya 2019: Persons age 1+ [discrepancies: none] This variable indicates the month the person moved to this county. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Year moved to this county <span class="h2">A: Information regarding all persons</span></p> <p>Duration of residence: When did [the respondent] move to the current county?</p> <div class="i1">For respondents enumerated in their county of birth, code month and year of birth. If date of movement is not known, write "99" for month and "9999" for year.<br /><br />P-21. Month _ _<br /><br />P-22. Year _ _ _ _</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.13. Column P21-P22: Duration of residence</p> <p>Ask: When did [the respondent] move to the current county?</p> <div class="i1">i. Record the month in P21 (e.g. "05" for May) and year in P22 (e.g. 1997). Check to see that the person's age is consistent with duration of residence, i.e., the person's age must always be greater or equal to duration of residence.<br />ii. If the date one moved is not known or not stated, enter "99" for month in columns P21 and "9999" for year in column P22.</div> Kenya 2019: Persons age 1+ [discrepancies: none] This variable indicates the year the person moved to this county. 1908 1908 or before 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 9998 Unknown 9999 NIU (not in universe) Migration: Global Variables -- PERSON Reason for migration <span class="h2">A: Information regarding all persons</span></p> <p>P-23. Reason for migration: Why did [the respondent] move to the current place of residence?</p> <div class="i1">[] 1. Work/employment<br />[] 2. Business<br />[] 3. Marriage<br />[] 4. Education<br />[] 5. Settlement<br />[] 6. Relocation due to development<br />[] 7. Conflict/disaster displacement<br />[] 8. Refugee<br />[] 9. Asylum seeker<br />[] 10. Family related movement<br />[] 11. Retirement<br />[] 12. Visiting<br />[] 99. DK</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.14. Column P23: Reason for moving to the current place of residence</p> <p>People move from one place of residence to another for various reasons, e.g., economic, social, political and environmental.</p> <p>Ask: Why did [the respondent] move to the current place of residence? <br />The choices provided are:</p> <div class="i1">1 = Work/employment,<br />2 = Business,<br />3 = Marriage,<br />4 = Education,<br />5 = Settlement,<br />6 = Relocation due to development (e.g., building of dam, road or change of land use etc.),<br />7 = Conflict/disaster displacement (e.g., floods),<br />8 = Refugee,<br />9 = Asylum seeker,<br />10 = Family related movement (e.g., husband/wife joining the spouse),<br />11 = Retirement,<br />12 = Visiting,<br />99 = DK.</div><p>Note: In cases where children moved with their parents/family for whatever reasons, enter code "10" as reason for movement to current location. Kenya 2019: Persons who ever migrated [discrepancies: not verifiable] This variable indicates the person's reason for migration. 01 Work or employment 02 Business 03 Marriage 04 Education 05 Settlement 06 Relocation due to development 07 Conflict or disaster displacement 08 Refugee 09 Asylum seeker 10 Family related movement 11 Retirement 12 Visiting 13 Other 98 Unknown 99 NIU (not in universe) Migration: Global Variables -- PERSON Biological father is alive <span class="h2">A: Information regarding all persons</span></p> <p>P-24. Orphanhood: Is [the respondent]'s biological father alive?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.15. Column P24-P25: Orphanhood <br />Ask: Is [the respondent]'s biological father/mother alive?</p> <div class="i1">i. Enter the appropriate codes in column P-24 and P-25 in respect of the survival status of the respondent's biological father and mother respectively. Note that at times some children are brought up or adopted at a very young age. Such foster parents should not be considered as the biological parents of the respondent.<br />ii. In some cases, a child's biological father/mother may not be married or living with the mother/father. In this case, the mother/father might report that she/he does not know whether the father/mother of her child is alive or dead. In this case, enter "9" for 'don't know'. You must always probe to ensure you obtain the most satisfactory answer.<br />iii. Each question should be asked independently as it appears in the questionnaire (or CAPI).</div> Kenya 2019: All persons This variable indicates whether the person's biological father is alive. 1 Yes 2 No 8 Unknown Fertility and Mortality Variables -- PERSON Biological mother is alive <span class="h2">A: Information regarding all persons</span></p> <p>P-25. Orphanhood: Is [the respondent]'s biological mother alive?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">20. Section A: Information regarding all persons</span></p> <p>20.15. Column P24-P25: Orphanhood <br />Ask: Is [the respondent]'s biological father/mother alive?</p> <div class="i1">i. Enter the appropriate codes in column P-24 and P-25 in respect of the survival status of the respondent's biological father and mother respectively. Note that at times some children are brought up or adopted at a very young age. Such foster parents should not be considered as the biological parents of the respondent.<br />ii. In some cases, a child's biological father/mother may not be married or living with the mother/father. In this case, the mother/father might report that she/he does not know whether the father/mother of her child is alive or dead. In this case, enter "9" for 'don't know'. You must always probe to ensure you obtain the most satisfactory answer.<br />iii. Each question should be asked independently as it appears in the questionnaire (or CAPI).</div> Kenya 2019: All persons This variable indicates whether the person's biological mother is alive. 1 Yes 2 No 8 Unknown Fertility and Mortality Variables -- PERSON Children ever born, male <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of all live births:</span></p> <p>P-26. How many boys have you ever borne alive? _ _ <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.1. Columns P26 to P33: Particulars of all live births</p> <div class="i1">i. Answers are required of all females aged 12 years and above in this category. It does not matter whether or not they are married, never married, divorced or separated; whether or not they are still attending school; or what their relationship to the head of the household is. These questions are on lifelong fertility experience of the female. You must ask the questions of all females aged twelve years and over. First thing to do is check in columns P11 and P12 and then identify all those to whom these questions should be posed.<br /><br />Make sure you make your entries in the correct line numbers for the eligible women. Where possible, obtain answers to these questions from the respective females and in private; if not then from the household head.<br />ii. For all males and for girls below twelve years of age, leave columns P26 to P41 blank. For childless women, enter "0" in the appropriate boxes. [remember that for a childless woman, you must enter "0" in the appropriate boxes. Do not leave the boxes blank for any woman 12 years and above even if childless].<br />iii. Some women do not like answering questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness and tact.</div><p>21.2. Columns P26-P27: Children born alive</p> <p>Ask: How many children have you ever borne alive?</p> <p>A child born alive is one who shows one or more of the following signs of life immediately after birth:</p> <div class="i1">i. Crying or similar sounds<br />ii. Movement of the limbs or any other parts of the body<br />iii. Any other tangible signs of life.</div><p>The census is concerned only with children born alive. Do not include stillbirths, that is, children who were born dead and, therefore, did not show any sign(s) of life as above at the time of birth. <br />If the woman has born any child alive, enter the number of boys in the boxes in P26 and the number of girls in P27. Kenya 2019: Females age 12+ [discrepancies: none] This variable indicates the person's children ever born, male. 00 None 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children ever born, female <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of all live births:</span></p> <p>P-27. How many girls have you ever borne alive? _ _ <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.1. Columns P26 to P33: Particulars of all live births</p> <div class="i1">i. Answers are required of all females aged 12 years and above in this category. It does not matter whether or not they are married, never married, divorced or separated; whether or not they are still attending school; or what their relationship to the head of the household is. These questions are on lifelong fertility experience of the female. You must ask the questions of all females aged twelve years and over. First thing to do is check in columns P11 and P12 and then identify all those to whom these questions should be posed.<br /><br />Make sure you make your entries in the correct line numbers for the eligible women. Where possible, obtain answers to these questions from the respective females and in private; if not then from the household head.<br />ii. For all males and for girls below twelve years of age, leave columns P26 to P41 blank. For childless women, enter "0" in the appropriate boxes. [remember that for a childless woman, you must enter "0" in the appropriate boxes. Do not leave the boxes blank for any woman 12 years and above even if childless].<br />iii. Some women do not like answering questions about their children. There are various reasons for this, but it is your duty to obtain the answers. It will require firmness, politeness and tact.</div><p>21.2. Columns P26-P27: Children born alive</p> <p>Ask: How many children have you ever borne alive?</p> <p>A child born alive is one who shows one or more of the following signs of life immediately after birth:</p> <div class="i1">i. Crying or similar sounds<br />ii. Movement of the limbs or any other parts of the body<br />iii. Any other tangible signs of life.</div><p>The census is concerned only with children born alive. Do not include stillbirths, that is, children who were born dead and, therefore, did not show any sign(s) of life as above at the time of birth. <br />If the woman has born any child alive, enter the number of boys in the boxes in P26 and the number of girls in P27. Kenya 2019: Females age 12+ [discrepancies: none] This variable indicates the person's children ever born, female. 00 None 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children living in the household, male <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of all live births:</span></p> <p>P-28. How many boys have you ever borne alive who usually live in this household? _ _ <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.3. Columns P28-P29: Children living in the household</p> <p>If the woman has born children alive, ask, "of the children you have born alive, how many usually live with you in this household?" Remember that for all childless women, you must enter "0" in the appropriate boxes.</p> <p>Enter the number of boys and girls who usually live in the household in columns P28 and P29 respectively. If none of the boys or girls the woman has borne alive are living in the household, write "00" in the appropriate boxes. Children borne to the woman who are in boarding schools should be included among the children who usually live in the household. In case of a visitor who spent the census night with her children in the household, these children should not be captured in P28 and P29 but in P30 and P31. Kenya 2019: Females age 12+ [discrepancies: none] This variable indicates the person's children living in the household, male. 00 None 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children living in the household, female <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of all live births:</span></p> <p>P-29. How many girls have you ever borne alive who usually live in this household? _ _ <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.3. Columns P28-P29: Children living in the household</p> <p>If the woman has born children alive, ask, "of the children you have born alive, how many usually live with you in this household?" Remember that for all childless women, you must enter "0" in the appropriate boxes.</p> <p>Enter the number of boys and girls who usually live in the household in columns P28 and P29 respectively. If none of the boys or girls the woman has borne alive are living in the household, write "00" in the appropriate boxes. Children borne to the woman who are in boarding schools should be included among the children who usually live in the household. In case of a visitor who spent the census night with her children in the household, these children should not be captured in P28 and P29 but in P30 and P31. Kenya 2019: Females age 12+ [discrepancies: none] This variable indicates the person's children living in the household, female. 00 None 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children living elsewhere, male <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of all live births:</span></p> <p>P-30. How many boys have you ever borne alive who usually live elsewhere? <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.4. Columns P30-P31: Children living elsewhere</p> <p>Next ask: "Of the children you have born alive, how many usually live elsewhere?" <br />Enter the number of boys who usually live elsewhere in column P30 and the number of girls in column P31. If none of the boys or girls she has borne alive live elsewhere, write, "00" in the appropriate boxes.</p> <p>Include in these columns (P30 and P31) all the children the woman has borne alive who usually live elsewhere. It may be that they have grown up and married, or have gone off to work, or are living with relatives, etc. Make sure that none of the children she has borne alive are missed out. You may ask further questions to probe -- for example, "are any of your children away?", "at work?", "with other relatives?" etc. Kenya 2019: Females age 12+ [discrepancies: none] This variable indicates the person's children living elsewhere, male. 00 None 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children living elsewhere, female <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of all live births:</span></p> <p>P-31. How many girls have you ever borne alive who usually live elsewhere? <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.4. Columns P30-P31: Children living elsewhere</p> <p>Next ask: "Of the children you have born alive, how many usually live elsewhere?" <br />Enter the number of boys who usually live elsewhere in column P30 and the number of girls in column P31. If none of the boys or girls she has borne alive live elsewhere, write, "00" in the appropriate boxes.</p> <p>Include in these columns (P30 and P31) all the children the woman has borne alive who usually live elsewhere. It may be that they have grown up and married, or have gone off to work, or are living with relatives, etc. Make sure that none of the children she has borne alive are missed out. You may ask further questions to probe -- for example, "are any of your children away?", "at work?", "with other relatives?" etc. Kenya 2019: Females age 12+ [discrepancies: none] This variable indicates the person's children living elsewhere, female. 00 None 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children who died, male <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of all live births:</span></p> <p>P-32. How many boys have you ever borne alive who have died? <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.5. Columns P32-P33: Children who have died</p> <p>Then ask, "of the children you have born alive, how many have died?"</p> <p>It is usually painful to talk about dead children. It is therefore best to ask this question in a matter of fact and without embarrassment. Please refer to Section B above for the definition of a live birth.</p> <p>Enter the number of boys and girls who have died in columns P32 and P33 respectively. If none of the boys and girls she has borne alive has died, enter "00" in the appropriate columns. If, in spite of your best efforts, you cannot obtain this information about the children who have died, leave columns P32 and P33 blank. However, this will not be encouraged.</p> <p>Before proceeding to columns P34-P41, probe to confirm whether the number of children given in columns P28-P33 is correct by comparing with the entries in columns P26 and P27. If these totals differ, probe further and adjust your entries accordingly. Kenya 2019: Females age 12+ [discrepancies: none] This variable indicates the person's children who died, male. 00 None 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Children who died, female <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of all live births:</span></p> <p>P-33. How many girls have you ever borne alive who have died? <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.5. Columns P32-P33: Children who have died</p> <p>Then ask, "of the children you have born alive, how many have died?"</p> <p>It is usually painful to talk about dead children. It is therefore best to ask this question in a matter of fact and without embarrassment. Please refer to Section B above for the definition of a live birth.</p> <p>Enter the number of boys and girls who have died in columns P32 and P33 respectively. If none of the boys and girls she has borne alive has died, enter "00" in the appropriate columns. If, in spite of your best efforts, you cannot obtain this information about the children who have died, leave columns P32 and P33 blank. However, this will not be encouraged.</p> <p>Before proceeding to columns P34-P41, probe to confirm whether the number of children given in columns P28-P33 is correct by comparing with the entries in columns P26 and P27. If these totals differ, probe further and adjust your entries accordingly. Kenya 2019: Females age 12+ [discrepancies: none] This variable indicates the person's children who died, female. 00 None 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Month of last birth <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of last live births:</span></p> <p>When was your last child born?</p> <div class="i1">If date of birth is not known code "99" for month and "9999" for year.<br /><br />P-34.Month _ _<br /><br />P-35.Year _ _ _ _</div> <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.6. Columns P34-P41: Particulars of last live births: These questions are to be asked of all females aged 12 years and above</p> <p>21.7. Columns P34-P35: Date when last child was born <br />Ask, "when was your last child born?"</p> <p>Record the month and year of birth in columns P34 and P35 respectively. Enter the month in column P34, i.e., "01" for January, "02" for February, "12" for December; and the year in column P35, i.e., "1980", "1989". This question should be asked regardless of the age of the last born child (he or she could be an adult by now).</p> <p>The subsequent questions (P36-P41 will apply to births since August 2014). You should probe for all children born since August, 2014 even if the exact date is not known. Kenya 2019: Females age 12+ who gave birth [discrepancies: none] This variable indicates the person's month of last birth. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Year of last birth <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of last live births:</span></p> <p>When was your last child born?</p> <div class="i1">If date of birth is not known code "99" for month and "9999" for year.<br /><br />P-34.Month _ _<br /><br />P-35.Year _ _ _ _</div> <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.6. Columns P34-P41: Particulars of last live births: These questions are to be asked of all females aged 12 years and above</p> <p>21.7. Columns P34-P35: Date when last child was born <br />Ask, "when was your last child born?"</p> <p>Record the month and year of birth in columns P34 and P35 respectively. Enter the month in column P34, i.e., "01" for January, "02" for February, "12" for December; and the year in column P35, i.e., "1980", "1989". This question should be asked regardless of the age of the last born child (he or she could be an adult by now).</p> <p>The subsequent questions (P36-P41 will apply to births since August 2014). You should probe for all children born since August, 2014 even if the exact date is not known. Kenya 2019: Females age 12+ who gave birth [discrepancies: none] This variable indicates the person's year of last birth. 1944 1944 or before 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 9998 Unknown 9999 NIU (not in universe) Fertility and Mortality Variables -- PERSON Type of facility where last birth took place <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of last live births:</span></p> <p>P-36. Where did this last birth occur?</p> <div class="i1">[] 1. In a health facility<br />[] 2. Non-health facility<br />[] 9. DK</div> <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.6. Columns P34-P41: Particulars of last live births: These questions are to be asked of all females aged 12 years and above</p> <p>21.8. Columns P36: Place where the birth of last child occurred</p> <p>Ask, "Where was this last child born?" <br />Births can occur either within a health facility or outside a health facility, e.g., at home, on the roadside, etc. enter code "1" for a birth that occurred in a health facility, "2" for a birth that occurred outside a health facility, (e.g., at home, in an ambulance/taxi/tuktuk/ on way to the facility, just outside hospital gate etc.) and "Enter 9" for don't know. <br />Note: Mobile clinics that are equipped with medical facilities will be treated as a facility. Kenya 2019: Females age 12+ who gave birth [discrepancies: none] This variable indicates the person's type of facility where last birth took place. 1 In a health facility 2 Non-health Facility 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Sex of last born child <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of last live births:</span></p> <p>P-37. What was the sex of this child/children?</p> <div class="i1">[] 1. Male<br />[] 2. Female<br />[] 3. Male twins<br />[] 4. Female twins<br />[] 5. Male-female twins<br />[] 9. DK</div> <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.6. Columns P34-P41: Particulars of last live births: These questions are to be asked of all females aged 12 years and above</p> <p>21.9. Column P37: Sex of the last born child/children</p> <p>Ask, 'What was the sex of this last born child/children?' <br />Enter the sex of the last born child in column P37. Enter "1" for male, "2" for female, "3" for male twins, "4" for female twins, "5" for twins with one of either sex (male and female twins), and "6" for other multiple births, and "9" for don't know. Kenya 2019: Females age 12+ who gave birth [discrepancies: type I one; type II 2.9%] This variable indicates the sex of last born child. 1 Male 2 Female 3 Male twins 4 Female twins 5 Male-female twins 6 Multiple births 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Last birth was registered <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of last live births:</span></p> <p>P-38. Was this last birth notified?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.6. Columns P34-P41: Particulars of last live births: These questions are to be asked of all females aged 12 years and above</p> <p>21.10. Column P38: Birth notification</p> <p>Ask, 'Was the birth of the last child notified?' <br />Enter the correct code in column P-38, i.e. "1" for yes, "2" for no and "9" for DK. Notification is the process whereby a parent or guardian or officer in charge of an institution (e.g., prison) where the birth has occurred reports to a government official responsible for registration of births within 6 months of occurrence. The government officials responsible for registration of births that occur at home are assistant chiefs and health personnel at immunization clinics while births that occur in health institutions are registered by personnel in those institutions. Kenya 2019: Females age 12+ who gave birth [discrepancies: type I one; type II 0.3%] This variable indicates whether the person's last birth was registered. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Last born child is alive <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of last live births:</span></p> <p>P-39. Is this last child/children still alive?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 3. Yes, one of the twins<br />[] 4. Yes, both twins<br />[] 5. Yes, one of the multiples<br />[] 6. Yes, two of the multiples<br />[] 7. Yes, all of the multiples<br />[] 9. DK</div> <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.6. Columns P34-P41: Particulars of last live births: These questions are to be asked of all females aged 12 years and above</p> <p>21.11. Columns P39-P41: Survival status of last born child</p> <p>Column P39, ask, "is the last child/ children still alive". Note that even though the question is about the last child, it refers to the last birth. A birth can either be single or twins/multiple. If it is a single birth and the child is still alive, Enter 1 for 'Yes" and if the child has since died, enter 2 for "no".</p> <p>For twin births, if one of the twins is alive enter 3 "yes, one of the twins", if both twins are alive enter 4 for "yes, both twins". If none of the twins is alive enter 2 for "no". For multiple births i.e. three children, if one of the multiples is alive then enter 5 for "yes, one of the multiples". If two of the three children are alive then enter 6 for "yes, two of the multiples"; if all the children are alive then enter 7 "yes, all of the multiples". If none of the multiples is alive enter 2 "no". If the respondent does not know if the child/children born are alive or not, Enter 9 "DK" Kenya 2019: Females age 12+ who gave birth within the last 5 years [discrepancies: type I trace; type II trace] This variable indicates whether the person's last born child is alive. 1 Yes 2 No 3 Yes, one of the twins 4 Yes, both twins 5 Yes, all of the multiples 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Month of death of last born child <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of last live births:</span></p> <p>If the last child is not alive, when did the child die?</p> <div class="i1">If date of death is not known code "99" for month and "9999" for year.<br /><br />P-40. Month _ _<br /><br />P-41. Year _ _ _ _</div> <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.6. Columns P34-P41: Particulars of last live births: These questions are to be asked of all females aged 12 years and above</p> <p>Column P40 - P41: If last birth was a single and the child has since died, record the date when the death occurred. Record the month and year in columns P40 and P41 respectively. If the birth was twin or multiple, record the date of the last death. Enter the month in column P40, i.e., "01" for January, "02" for February, "12" for December, and the year in column P41, i.e., "2014", "2016". If the date is not known, enter "99" for month and "9999" for year. Kenya 2019: Females age 12+ who gave within the last 5 years and whose last child born died [discrepancies: type I trace; type II trace] This variable indicates the month of death of the person's last born child. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Year of death of last born child <span class="h2">B: Information regarding females aged 12 years and above</span> <br />[Questions 26-41 were asked of females age 12 or more]</p> <p><span class="em">Particulars of last live births:</span></p> <p>If the last child is not alive, when did the child die?</p> <div class="i1">If date of death is not known code "99" for month and "9999" for year.<br /><br />P-40. Month _ _<br /><br />P-41. Year _ _ _ _</div> <span class="em">21. Section B: Information regarding females aged 12 years and above</span></p> <p>21.6. Columns P34-P41: Particulars of last live births: These questions are to be asked of all females aged 12 years and above</p> <p>Column P40 - P41: If last birth was a single and the child has since died, record the date when the death occurred. Record the month and year in columns P40 and P41 respectively. If the birth was twin or multiple, record the date of the last death. Enter the month in column P40, i.e., "01" for January, "02" for February, "12" for December, and the year in column P41, i.e., "2014", "2016". If the date is not known, enter "99" for month and "9999" for year. Kenya 2019: Females age 12+ who gave within the last 5 years and whose last child born died [discrepancies: type I trace; type II trace] This variable indicates the year of death of the person's last born child. 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 9998 Unknown 9999 NIU (not in universe) Fertility and Mortality Variables -- PERSON Has difficulty seeing, even if wearing glasses <span class="h2">C: Information regarding persons with difficulties doing activities of daily life</span></p> <p><span class="ital">To be asked of persons aged 5 years and above except P-43</span> <br />[Question 42 was asked of persons age 5 or more]</p> <p>P-42. Do you/does [the respondent] have difficulty ... (read out):</p> <div class="i1">Seeing, even if wearing glasses? Would you say ...</div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes - a lot of difficulty<br />[] 4. Cannot do at all<br />[] 9. DK</div> <span class="em">22. Section C: Information regarding persons with difficulties in performing activities of daily life</span></p> <p>Columns p42 to p44 contain questions pertaining to persons with difficulties in performing activities of daily life. These questions are to be asked of the head of the household or any other responsible person.</p> <p>22.1. Introduction <br />Questions regarding persons with difficulties in performing activities of daily life have to be asked very carefully and with caution due to the sensitivity and stigma associated with difficulties.</p> <p>22.2. Questions to be asked to respondents <br />During this census, the following questions will be asked;</p> <p>Questions P42 to P44 are to be asked of persons aged 5 years and above except P43.</p> <p>Questions P42</p> <div class="i1">i. Does [the respondent] have difficulty seeing, even if wearing glasses?<br />ii. Does [the respondent] have difficulty hearing, even if using a hearing aid?<br />iii. Does [the respondent] have difficulty walking or climbing steps?<br />iv. Does [the respondent] have difficulty remembering or concentrating?<br />v. Does [the respondent] have difficulty with self-care such as washing all over or dressing?<br />vi. Does [the respondent] have difficulty communicating, using his/her usual language, for example understanding or being understood?</div><p>Each of the above six questions has five possible response categories:</p> <div class="i1">1. No, no difficulty,<br />2. Yes, some difficulty,<br />3. Yes, a lot of difficulty, or<br />4. Cannot do it at all<br />5. Don't know</div><p>The enumerator should read questions in P42 together with the response options without pause except option 5 - Don't Know</p> <p>For example: "Does [the respondent] have difficulty walking or climbing stairs? Would you say: No, no difficulty; or yes, some difficulty; or yes, a lot of difficulty or cannot do it at all"</p> <p>22.3. Question by question specifications</p> <p>Question 1: Do you have difficulty seeing, even if wearing glasses? <br />The purpose of this question is to identify persons who have vision difficulties or problems seeing even when wearing glasses. "Seeing" refers to an individual using his/her eyes and visual capacity in order to perceive or observe what is happening around them. "Even when wearing glasses" refers to difficulty seeing with glasses if the respondent has, and uses, them - not how vision would be if glasses, or better glasses, were provided to one who needed them. <br />Included are problems: "seeing things close up or far away", and "seeing out of one eye or only seeing directly in front but not to the sides". Any problem with vision that the respondent considers a problem should be captured. Kenya 2019: Persons age 5+ [discrepancies: none] This variable indicates whether the person has difficulty seeing, even if wearing glasses. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Has difficulty hearing, even if using hearing aid <span class="h2">C: Information regarding persons with difficulties doing activities of daily life</span></p> <p><span class="ital">To be asked of persons aged 5 years and above except P-43</span> <br />[Question 42 was asked of persons age 5 or more]</p> <p>P-42. Do you/does [the respondent] have difficulty ... (read out):</p> <div class="i1">Hearing, even if using a hearing aid? Would you say ...</div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes - a lot of difficulty<br />[] 4. Cannot do at all<br />[] 9. DK</div> <span class="em">22. Section C: Information regarding persons with difficulties in performing activities of daily life</span></p> <p>Columns p42 to p44 contain questions pertaining to persons with difficulties in performing activities of daily life. These questions are to be asked of the head of the household or any other responsible person.</p> <p>22.1. Introduction <br />Questions regarding persons with difficulties in performing activities of daily life have to be asked very carefully and with caution due to the sensitivity and stigma associated with difficulties.</p> <p>22.2. Questions to be asked to respondents <br />During this census, the following questions will be asked;</p> <p>Questions P42 to P44 are to be asked of persons aged 5 years and above except P43.</p> <p>Questions P42</p> <div class="i1">i. Does [the respondent] have difficulty seeing, even if wearing glasses?<br />ii. Does [the respondent] have difficulty hearing, even if using a hearing aid?<br />iii. Does [the respondent] have difficulty walking or climbing steps?<br />iv. Does [the respondent] have difficulty remembering or concentrating?<br />v. Does [the respondent] have difficulty with self-care such as washing all over or dressing?<br />vi. Does [the respondent] have difficulty communicating, using his/her usual language, for example understanding or being understood?</div><p>Each of the above six questions has five possible response categories:</p> <div class="i1">1. No, no difficulty,<br />2. Yes, some difficulty,<br />3. Yes, a lot of difficulty, or<br />4. Cannot do it at all<br />5. Don't know</div><p>The enumerator should read questions in P42 together with the response options without pause except option 5 - Don't Know</p> <p>For example: "Does [the respondent] have difficulty walking or climbing stairs? Would you say: No, no difficulty; or yes, some difficulty; or yes, a lot of difficulty or cannot do it at all"</p> <p>Question 2: Do you have difficulty hearing, even if using a hearing aid? <br />The purpose of this question is to identify persons who have some hearing limitation or problems of any kind with their hearing even when using a hearing aid (if they wear a hearing aid). "Hearing" refers to an individual using their ears and auditory (or hearing) capacity in order to know what is being said to them or the sounds of activity, including danger that is happening around them. "Even if using a hearing aid" refers to difficulty hearing with a hearing aid if the respondent has, and uses, that device -- not how hearing would be if hearing aids, or better hearing aids, were provided to one who needed them. <br />Included are problems: "hearing in a noisy or a quiet environment", "distinguishing sounds from different sources", and "hearing in one ear or both ears". Any difficulty with hearing that is considered a problem should be captured. Kenya 2019: Persons age 5+ [discrepancies: none] This variable indicates whether the person has difficulty hearing, even if using hearing aid. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Has difficulty in walking or climbing steps <span class="h2">C: Information regarding persons with difficulties doing activities of daily life</span></p> <p><span class="ital">To be asked of persons aged 5 years and above except P-43</span> <br />[Question 42 was asked of persons age 5 or more]</p> <p>P-42. Do you/does [the respondent] have difficulty ... (read out):</p> <div class="i1">Walking or climbing steps? Would you say ...</div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes - a lot of difficulty<br />[] 4. Cannot do at all<br />[] 9. DK</div> <span class="em">22. Section C: Information regarding persons with difficulties in performing activities of daily life</span></p> <p>Columns p42 to p44 contain questions pertaining to persons with difficulties in performing activities of daily life. These questions are to be asked of the head of the household or any other responsible person.</p> <p>22.1. Introduction <br />Questions regarding persons with difficulties in performing activities of daily life have to be asked very carefully and with caution due to the sensitivity and stigma associated with difficulties.</p> <p>22.2. Questions to be asked to respondents <br />During this census, the following questions will be asked;</p> <p>Questions P42 to P44 are to be asked of persons aged 5 years and above except P43.</p> <p>Questions P42</p> <div class="i1">i. Does [the respondent] have difficulty seeing, even if wearing glasses?<br />ii. Does [the respondent] have difficulty hearing, even if using a hearing aid?<br />iii. Does [the respondent] have difficulty walking or climbing steps?<br />iv. Does [the respondent] have difficulty remembering or concentrating?<br />v. Does [the respondent] have difficulty with self-care such as washing all over or dressing?<br />vi. Does [the respondent] have difficulty communicating, using his/her usual language, for example understanding or being understood?</div><p>Each of the above six questions has five possible response categories:</p> <div class="i1">1. No, no difficulty,<br />2. Yes, some difficulty,<br />3. Yes, a lot of difficulty, or<br />4. Cannot do it at all<br />5. Don't know</div><p>The enumerator should read questions in P42 together with the response options without pause except option 5 - Don't Know</p> <p>For example: "Does [the respondent] have difficulty walking or climbing stairs? Would you say: No, no difficulty; or yes, some difficulty; or yes, a lot of difficulty or cannot do it at all"</p> <p>Question 3: Do you have difficulty walking or climbing stairs? <br />This question is intended to identify persons who have some limitation or problems of any kind getting around on foot. "Walking" refers to the use of lower limbs (legs) in such a way as to propel oneself over the ground to get from point A to point B. The capacity to walk should be without assistance of any device (wheelchair, crutches, walker etc.) or human. If such assistance is needed, the person has difficulty walking.</p> <p>Difficulties walking can include those resulting from impairments in balance, endurance, or other non-musculoskeletal systems, for example blind people having difficulty walking in an unfamiliar place or deaf people having difficulty climbing stairs when there is no lighting. Any difficulty with walking (whether it is on flat land or, up or down stairs) that is considered a problem should be captured.</p> <p>Included are problems: "walking short (about 100 yards/meters) or long distances (about 500 yards/meters)", "walking any distance without stopping to rest is included", and "walking up or down stairs". Kenya 2019: Persons age 5+ [discrepancies: none] This variable indicates whether the person has difficulty in walking or climbing steps. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Has difficulty remembering or concentrating <span class="h2">C: Information regarding persons with difficulties doing activities of daily life</span></p> <p><span class="ital">To be asked of persons aged 5 years and above except P-43</span> <br />[Question 42 was asked of persons age 5 or more]</p> <p>P-42. Do you/does [the respondent] have difficulty ... (read out):</p> <div class="i1">Remembering or concentrating? Would you say ...</div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes - a lot of difficulty<br />[] 4. Cannot do at all<br />[] 9. DK</div> <span class="em">22. Section C: Information regarding persons with difficulties in performing activities of daily life</span></p> <p>Columns p42 to p44 contain questions pertaining to persons with difficulties in performing activities of daily life. These questions are to be asked of the head of the household or any other responsible person.</p> <p>22.1. Introduction <br />Questions regarding persons with difficulties in performing activities of daily life have to be asked very carefully and with caution due to the sensitivity and stigma associated with difficulties.</p> <p>22.2. Questions to be asked to respondents <br />During this census, the following questions will be asked;</p> <p>Questions P42 to P44 are to be asked of persons aged 5 years and above except P43.</p> <p>Questions P42</p> <div class="i1">i. Does [the respondent] have difficulty seeing, even if wearing glasses?<br />ii. Does [the respondent] have difficulty hearing, even if using a hearing aid?<br />iii. Does [the respondent] have difficulty walking or climbing steps?<br />iv. Does [the respondent] have difficulty remembering or concentrating?<br />v. Does [the respondent] have difficulty with self-care such as washing all over or dressing?<br />vi. Does [the respondent] have difficulty communicating, using his/her usual language, for example understanding or being understood?</div><p>Each of the above six questions has five possible response categories:</p> <div class="i1">1. No, no difficulty,<br />2. Yes, some difficulty,<br />3. Yes, a lot of difficulty, or<br />4. Cannot do it at all<br />5. Don't know</div><p>The enumerator should read questions in P42 together with the response options without pause except option 5 - Don't Know</p> <p>For example: "Does [the respondent] have difficulty walking or climbing stairs? Would you say: No, no difficulty; or yes, some difficulty; or yes, a lot of difficulty or cannot do it at all"</p> <p>Question 4: Do you have difficulty remembering or concentrating? <br />The purpose of this question is to identify persons who have some problems with remembering or focusing attention that contribute to difficulty in doing their daily activities. "Remembering" refers to the use of memory to recall incidents or events. It means the individual can bring to mind or think again about something that has taken place in the past (either the recent past or further back)</p> <p>With younger people, remembering is often associated with storing facts learned in school and being able to retrieve them when needed. Remembering should not be equated with memorizing or with good or bad memories. Concentrating refers to the use of mental ability to accomplish some task such as reading, calculating numbers, learning something. It is associated with focusing on the task at hand in order to complete the task.</p> <p>Included are problems: "finding one's way around, being unable to concentrate on an activity, or forgetting one's whereabouts or the date", and "problems remembering what someone just said or becoming confused or frightened about most things". Any difficulty with remembering, concentrating or understanding what is going on around them that they or family members (if the family member is the respondent) consider a problem should be captured.</p> <p><span class="pg">[p.47]</span></p> <p>Exclusions: difficulties remembering or concentrating because of common everyday situations such as high workload or stress, or as a result of substance abuse are excluded. Kenya 2019: Persons age 5+ [discrepancies: none] This variable indicates whether the person has difficulty remembering or concentrating. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Has difficulty with self-care such as washing all over or dressing <span class="h2">C: Information regarding persons with difficulties doing activities of daily life</span></p> <p><span class="ital">To be asked of persons aged 5 years and above except P-43</span> <br />[Question 42 was asked of persons age 5 or more]</p> <p>P-42. Do you/does [the respondent] have difficulty ... (read out):</p> <div class="i1">With self-care such as washing all over or dressing? Would you say ...</div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes - a lot of difficulty<br />[] 4. Cannot do at all<br />[] 9. DK</div> <span class="em">22. Section C: Information regarding persons with difficulties in performing activities of daily life</span></p> <p>Columns p42 to p44 contain questions pertaining to persons with difficulties in performing activities of daily life. These questions are to be asked of the head of the household or any other responsible person.</p> <p>22.1. Introduction <br />Questions regarding persons with difficulties in performing activities of daily life have to be asked very carefully and with caution due to the sensitivity and stigma associated with difficulties.</p> <p>22.2. Questions to be asked to respondents <br />During this census, the following questions will be asked;</p> <p>Questions P42 to P44 are to be asked of persons aged 5 years and above except P43.</p> <p>Questions P42</p> <div class="i1">i. Does [the respondent] have difficulty seeing, even if wearing glasses?<br />ii. Does [the respondent] have difficulty hearing, even if using a hearing aid?<br />iii. Does [the respondent] have difficulty walking or climbing steps?<br />iv. Does [the respondent] have difficulty remembering or concentrating?<br />v. Does [the respondent] have difficulty with self-care such as washing all over or dressing?<br />vi. Does [the respondent] have difficulty communicating, using his/her usual language, for example understanding or being understood?</div><p>Each of the above six questions has five possible response categories:</p> <div class="i1">1. No, no difficulty,<br />2. Yes, some difficulty,<br />3. Yes, a lot of difficulty, or<br />4. Cannot do it at all<br />5. Don't know</div><p>The enumerator should read questions in P42 together with the response options without pause except option 5 - Don't Know</p> <p>For example: "Does [the respondent] have difficulty walking or climbing stairs? Would you say: No, no difficulty; or yes, some difficulty; or yes, a lot of difficulty or cannot do it at all"</p> <p>Question 5: Do you have difficulty with self-care, such as washing all over or dressing? <br />The purpose of this question is to identify persons who have some problems with taking care of themselves independently. "Washing all over" refers to the process of cleaning one's entire body (usually with soap and water) in the usual manner for the culture. The washing activity includes cleaning hair and feet, as well as gathering any necessary items for bathing such as soap or shampoo, a washcloth, or water. "Dressing" refers to all aspects of putting clothing or garments on the upper and lower body including the feet if culturally appropriate. Washing and dressing represents tasks that occur on a daily basis and are considered basic, universal activities. <br />Included are: the acts of gathering clothing from storage areas (i.e. closet, dressers), securing buttons, tying knots, zipping, etc. Kenya 2019: Persons age 5+ [discrepancies: none] This variable indicates whether the person has difficulty with self-care such as washing all over or dressing. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Has difficulty communicating using their usual language, including difficulty understanding or being understood <span class="h2">C: Information regarding persons with difficulties doing activities of daily life</span></p> <p><span class="ital">To be asked of persons aged 5 years and above except P-43</span> <br />[Question 42 was asked of persons age 5 or more]</p> <p>P-42. Do you/does [the respondent] have difficulty ... (read out):</p> <div class="i1">Communicating using his/her usual language, for example understanding or being understood? Would you say ...</div><div class="i2">[] 1. No - no difficulty<br />[] 2. Yes - some difficulty<br />[] 3. Yes - a lot of difficulty<br />[] 4. Cannot do at all<br />[] 9. DK</div> <span class="em">22. Section C: Information regarding persons with difficulties in performing activities of daily life</span></p> <p>Columns p42 to p44 contain questions pertaining to persons with difficulties in performing activities of daily life. These questions are to be asked of the head of the household or any other responsible person.</p> <p>22.1. Introduction <br />Questions regarding persons with difficulties in performing activities of daily life have to be asked very carefully and with caution due to the sensitivity and stigma associated with difficulties.</p> <p>22.2. Questions to be asked to respondents <br />During this census, the following questions will be asked;</p> <p>Questions P42 to P44 are to be asked of persons aged 5 years and above except P43.</p> <p>Questions P42</p> <div class="i1">i. Does [the respondent] have difficulty seeing, even if wearing glasses?<br />ii. Does [the respondent] have difficulty hearing, even if using a hearing aid?<br />iii. Does [the respondent] have difficulty walking or climbing steps?<br />iv. Does [the respondent] have difficulty remembering or concentrating?<br />v. Does [the respondent] have difficulty with self-care such as washing all over or dressing?<br />vi. Does [the respondent] have difficulty communicating, using his/her usual language, for example understanding or being understood?</div><p>Each of the above six questions has five possible response categories:</p> <div class="i1">1. No, no difficulty,<br />2. Yes, some difficulty,<br />3. Yes, a lot of difficulty, or<br />4. Cannot do it at all<br />5. Don't know</div><p>The enumerator should read questions in P42 together with the response options without pause except option 5 - Don't Know</p> <p>For example: "Does [the respondent] have difficulty walking or climbing stairs? Would you say: No, no difficulty; or yes, some difficulty; or yes, a lot of difficulty or cannot do it at all"</p> <p>Question 6: Using your usual language, do you have difficulty communicating, (for example understanding or being understood by others)?</p> <p>The purpose of this question is to identify persons who have some problems with talking, listening or understanding speech such that it contributes to difficulty in making themselves understood to others or understanding others. "Communicating" refers to a person exchanging information or ideas with other people through the use of usual language. Communication difficulties can originate in numerous places in the exchange process. It may involve mechanical problems such as hearing impairment or speech impairment, or it may be related to the ability of the mind to interpret the sounds that the auditory system is gathering and to recognize the words that are being used or an inability of the mind to compose a sentence or say a word even when the person knows the word and sentence.</p> <p>Included is: the use of the voice for the exchange or using signs (including sign language) or writing the information to be conveyed. Included also are problems making oneself understood, or problems understanding other people when they speak or try to communicate in other ways.</p> <p><span class="pg">[p.48]</span></p> <p>Exclusion: Difficulty understanding or being understood due to non-native or unfamiliar language is not included. Kenya 2019: Persons age 5+ [discrepancies: none] This variable indicates whether the person has difficulty communicating using their usual language, including difficulty understanding or being understood. 1 No, no difficulty 2 Yes, some difficulty 3 Yes, a lot of difficulty 4 Cannot do at all 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON Has albinism <span class="h2">C: Information regarding persons with difficulties doing activities of daily life</span></p> <p><span class="ital">To be asked of persons aged 5 years and above except P-43</span> <br />[Question 42 was asked of persons age 5 or more]</p> <p>P-43. Does [the respondent] have albinism?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">22. Section C: Information regarding persons with difficulties in performing activities of daily life</span></p> <p>Questions P43</p> <div class="i1">vii. Does [the respondent] have albinism?</div><p>Both questions P43 and P44 have three possible response categories:</p> <div class="i1">1. Yes<br />2. No<br />3. Don't know</div><p>Question 7: Does [the respondent] have albinism? <br />This question is to identify persons who have albinism. Albinism is a defect of melanin production that results in little or no colour (pigment) in the skin, hair and eyes. There are two (2) types of albinism</p> <div class="i1">i. Oculocutaneous albinism: an individual has white or pink hair, skin and iris colour as well as visual problems.<br />ii. Ocular albinism: The person's skin and eye colors are usually in the normal range. However, an eye exam will show there is no colouring in the back of the eye (retina).</div><p>Many forms of albinism may present with absence of colour in the hair, skin, or iris of the eye, being lighter than normal skin and hair, patchy and missing skin colour, crossed eyes, light sensitivity, rapid eye movements, vision problems, or functional blindness. Kenya 2019: All persons This variable indicates whether the person has albinism. 1 Yes 2 No 8 Unknown Disability Variables -- PERSON Has difficulty engaging in economic activity due to disability <span class="h2">C: Information regarding persons with difficulties doing activities of daily life</span></p> <p><span class="ital">Applicable to persons age 5 years and above.</span> <br />[Question 44 was asked of persons age 5 or more]</p> <p>If "no" in P-42 and P-43 skip to P-45</p> <p>P-44. Because of the difficulty, does [the respondent] have problems in engaging in any economic activity?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">22. Section C: Information regarding persons with difficulties in performing activities of daily life</span></p> <p>Question P44 is applicable for persons recording "some difficulty", "a lot of difficulty" or "cannot do at all", in P42 and "yes" in P43.</p> <p>Questions P44</p> <div class="i1">viii. Because of the difficulty, does [the respondent] have a problem in engaging in any economic activity?</div><p>Both questions P43 and P44 have three possible response categories:</p> <div class="i1">1. Yes<br />2. No<br />3. Don't know</div><p>Question 8: Because of the difficulty, does [the respondent] have a problem in engaging in any economic activity?</p> <p>This question seeks to establish if [the respondent]'s economic activities are affected by his/her difficulties in performing activities of daily life Kenya 2019: Persons age 5+ with a disability or albinism [discrepancies: type I none; type II trace] This variable indicates whether the person has difficulty engaging in economic activity due to disability. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON School attendance <span class="h2">D: Information regarding education attainment</span></p> <p><span class="ital">For persons aged 3 years and above.</span> <br />[Question 43-47 were asked of persons age 3 or more]</p> <p>P-45. What is the current school/learning institution attendance status of [the respondent]? <br /><span class="ital">If 4 or 9, skip to P-49</span><div class="i1">[] 1. At school/learning institution<br />[] 2. Left school/learning institution after completion<br />[] 3. Left school/learning institution before completion<br />[] 4. Never been to school/learning institution<br />[] 9. DK</div> <span class="em">23. Section D: Education status for persons aged 3 years and above</span></p> <p>23.1. Columns P45 - P48: Information regarding education and training</p> <p>Questions on Column P45 to P47 are applicable to persons age 3 years and above and refer to formal and non-formal education, while P48 applies to persons age 15 and above. Formal education covers pre-primary, primary, secondary, vocational training centres (formerly youth polytechnics), middle level colleges and university. Non-formal education (NFE) is any other form of education that does not follow standard approved curricula of the formal system but offers numeric and literacy skills through flexible learning, e.g. adult education, apprenticeship, madrassa/Duksi, etc.</p> <p>Definitions</p> <div class="i1">i. School/learning institution - This is a place or centre in which learning is offered to a particular group of persons at a given level of education (levels of education can be ECDE, primary, secondary, university, etc). This also includes centres where special needs education is provided. Note: for those in distance/open/remote/online, etc learning, are considered to be registered in a school/learning institution, and in which case, the same definition applies.<br /><br />ii. Early childhood development education (ECDE) - This is an education programme offered to provide holistic integrated services that create a strong foundation for a child's cognitive (talents), psycho-social, moral, spiritual, emotional and psychomotor (physical education-PE) needs. Note: Although the education section will target persons aged 3 years and above, the official target group for the ECDE programme is children under 6 years. In addition, some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. Under this system child aged 3-5 years attend nursery/pre-primary; Early Years Foundations Stage (EYFS).<br /><br />iii. Primary - This refers to the level of education immediately after ECDE and covers 8 years under the 8-4-4 system. Before the 8-4-4 system, there was the 7-4-2-3 structure in which the length of primary education was 7 years. In the proposed system (2-6-3-3), primary education will last 6 years after ECDE. While the 7-4-2-3 and 8-4-4 systems had end of cycle examinations - Certificate of Primary Education (CPE) and Kenya Certificate of Primary Education (KCPE) - the proposed system will not have a summative evaluation of learners. Note: Some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. There are 5 Key Stages under BIC. Primary education is under Key Stage 1 and 2 and it lasts for 6 years (lower primary 3 years and upper primary 3 years).<br /><br />iv. Secondary - This refers to the level of education immediately after primary and covers 4 years under the 8-4-4 system. Before the 8-4-4 system, the 7-4-2-3 offered secondary education lasting 6 years (4 years at Ordinary Level and 2 years at Advanced Level). Note: Some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. There are 5 Key Stages under BIC. Secondary education is under Key Stage 3 (Junior School) that lasts for 3 years, Key Stage 4 (Senior School) that lasts for 2 years and Key Stage 5 (Pre-University Studies) that also lasts for 2 years. At the end of year 11 (senior school) students sit for International General Certificate of Secondary Education (IGCSE) exams. At the end of year 12 (Secondary 12) students sit for Advanced Subsidiary (AS) exams while at the end of year 13 (Secondary 13) students sit for Advanced (A) level exams.<br /><br />v. Vocational skills -- these are practical or first-hand capabilities that help learners to have basic skills on how to carry out a given job/assignment effectively.<br /><br />vi. Vocational training centre (formerly youth polytechnic) - This is a training institution that offers vocational skills training to primary/secondary school leavers. The courses offered in vocational training centres last 1 to 2 years and may include artisan 1 and 2; craft 1 and 2, such as carpentry, masonry, electrical, hair dressing and tailoring, etc.<br /><br />vii. Middle level/technical training -- This is a post-secondary education programme that offers various courses at certificate, diploma and higher national diploma level. The programme caters for students who have completed secondary education. The institutions that offer these courses include primary teacher training colleges that offer primary teaching certificate and diploma; medical training colleges that offer certificate and diploma in nursing/clinical medicine etc.; agriculture training colleges; media colleges; ICT colleges; technical training institutes; national polytechnics, among others.<br /><br />viii. University- This is the last cycle of the formal education programme in the country providing various courses according to sector professional prescriptions. This level of education offers pre-university courses, undergraduate degree courses and post-graduate courses.<br /><br />ix. Non-formal education (NFE) - This is an education programme that offers flexible learning for adults and children of school going age who are not able to join the formal system of education. The objective of the programme is to help learners acquire basic and post-basic literacy including vocational skills identified to be relevant and adequate for their level. Note: Non-formal education is offered in centres/learning institutions invariably called non-formal schools (NFS), or informal schools/centres</div><p>Where basic education involves mainly teaching numeric and literacy skills. A learner is considered to have achieved basic level of education after sitting and passing recommended proficiency examination.</p> <p>Post literacy education teaches learners on subjects similar to those in formal primary schools. Like in basic literacy, a learner is considered to have achieved post-basic literacy education after sitting and passing recommended proficiency examination or the Kenya Certificate of Primary Education (KCPE).</p> <p>23.2. Column P45: School /learning institution attendance status</p> <p>Ask: What is the current school/learning institution attendance status of [the respondent]? <br />Record "1" for persons attending school/learning institution this year; "2" for persons who have left school/learning institution after completion; "3" for persons who have left school/learning institution before completion; "4" for persons who have never been to school/learning institution; and "9" for persons whose schooling status is not known. Leave the box blank if the respondent is below 3 years. Kenya 2019: Persons age 3+ [discrepancies: type I trace; type II none] This variable indicates the person's school attendance. 1 Currently at school or learning institution 2 Left school or learning institution after completion 3 Left school or learning institution before completion 4 Never went to school or learning institution 8 Unknown 9 NIU (not in universe) Education Variables -- PERSON Highest educational standard, form, or grade reached <span class="h2">D: Information regarding education attainment</span></p> <p><span class="ital">For persons aged 3 years and above.</span> <br />[Question 43-47 were asked of persons age 3 or more]</p> <p>P-46. What is the highest std/form/grade reached by [the respondent]?</p> <div class="i1">The code list provided. Write "97" if P-45 = 4 or 9.<br /><br />Highest std/form/grade reached _ _</div> <span class="em">23. Section D: Education status for persons aged 3 years and above</span></p> <p>23.1. Columns P45 - P48: Information regarding education and training</p> <p>Questions on Column P45 to P47 are applicable to persons age 3 years and above and refer to formal and non-formal education, while P48 applies to persons age 15 and above. Formal education covers pre-primary, primary, secondary, vocational training centres (formerly youth polytechnics), middle level colleges and university. Non-formal education (NFE) is any other form of education that does not follow standard approved curricula of the formal system but offers numeric and literacy skills through flexible learning, e.g. adult education, apprenticeship, madrassa/Duksi, etc.</p> <p>Definitions</p> <div class="i1">i. School/learning institution - This is a place or centre in which learning is offered to a particular group of persons at a given level of education (levels of education can be ECDE, primary, secondary, university, etc). This also includes centres where special needs education is provided. Note: for those in distance/open/remote/online, etc learning, are considered to be registered in a school/learning institution, and in which case, the same definition applies.<br /><br />ii. Early childhood development education (ECDE) - This is an education programme offered to provide holistic integrated services that create a strong foundation for a child's cognitive (talents), psycho-social, moral, spiritual, emotional and psychomotor (physical education-PE) needs. Note: Although the education section will target persons aged 3 years and above, the official target group for the ECDE programme is children under 6 years. In addition, some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. Under this system child aged 3-5 years attend nursery/pre-primary; Early Years Foundations Stage (EYFS).<br /><br />iii. Primary - This refers to the level of education immediately after ECDE and covers 8 years under the 8-4-4 system. Before the 8-4-4 system, there was the 7-4-2-3 structure in which the length of primary education was 7 years. In the proposed system (2-6-3-3), primary education will last 6 years after ECDE. While the 7-4-2-3 and 8-4-4 systems had end of cycle examinations - Certificate of Primary Education (CPE) and Kenya Certificate of Primary Education (KCPE) - the proposed system will not have a summative evaluation of learners. Note: Some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. There are 5 Key Stages under BIC. Primary education is under Key Stage 1 and 2 and it lasts for 6 years (lower primary 3 years and upper primary 3 years).<br /><br />iv. Secondary - This refers to the level of education immediately after primary and covers 4 years under the 8-4-4 system. Before the 8-4-4 system, the 7-4-2-3 offered secondary education lasting 6 years (4 years at Ordinary Level and 2 years at Advanced Level). Note: Some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. There are 5 Key Stages under BIC. Secondary education is under Key Stage 3 (Junior School) that lasts for 3 years, Key Stage 4 (Senior School) that lasts for 2 years and Key Stage 5 (Pre-University Studies) that also lasts for 2 years. At the end of year 11 (senior school) students sit for International General Certificate of Secondary Education (IGCSE) exams. At the end of year 12 (Secondary 12) students sit for Advanced Subsidiary (AS) exams while at the end of year 13 (Secondary 13) students sit for Advanced (A) level exams.<br /><br />v. Vocational skills -- these are practical or first-hand capabilities that help learners to have basic skills on how to carry out a given job/assignment effectively.<br /><br />vi. Vocational training centre (formerly youth polytechnic) - This is a training institution that offers vocational skills training to primary/secondary school leavers. The courses offered in vocational training centres last 1 to 2 years and may include artisan 1 and 2; craft 1 and 2, such as carpentry, masonry, electrical, hair dressing and tailoring, etc.<br /><br />vii. Middle level/technical training -- This is a post-secondary education programme that offers various courses at certificate, diploma and higher national diploma level. The programme caters for students who have completed secondary education. The institutions that offer these courses include primary teacher training colleges that offer primary teaching certificate and diploma; medical training colleges that offer certificate and diploma in nursing/clinical medicine etc.; agriculture training colleges; media colleges; ICT colleges; technical training institutes; national polytechnics, among others.<br /><br />viii. University- This is the last cycle of the formal education programme in the country providing various courses according to sector professional prescriptions. This level of education offers pre-university courses, undergraduate degree courses and post-graduate courses.<br /><br />ix. Non-formal education (NFE) - This is an education programme that offers flexible learning for adults and children of school going age who are not able to join the formal system of education. The objective of the programme is to help learners acquire basic and post-basic literacy including vocational skills identified to be relevant and adequate for their level. Note: Non-formal education is offered in centres/learning institutions invariably called non-formal schools (NFS), or informal schools/centres</div><p>Where basic education involves mainly teaching numeric and literacy skills. A learner is considered to have achieved basic level of education after sitting and passing recommended proficiency examination.</p> <p>Post literacy education teaches learners on subjects similar to those in formal primary schools. Like in basic literacy, a learner is considered to have achieved post-basic literacy education after sitting and passing recommended proficiency examination or the Kenya Certificate of Primary Education (KCPE).</p> <p>23.3. Column P46: Highest standard/form/grade reached</p> <p>Ask: What is the highest standard/form/grade of education reached by [the respondent]? <br />Enter in column P46 the highest level of formal education the person has reached from the provided code list: For example, if a person reached standard 4, he/she should be coded "4". If a person has reached/attending adult education basic literacy class, he/she should be coded "21". <br />However, if the person is enrolled/reached for KCPE examinations in an adult literacy centre then he/she should be coded "8".</p> <p>If a person is attending/attended, a course in a vocational training centre he/she should be coded "23".</p> <p>If a person is attending/attended a certificate course in a middle level college/technical training institute (post-secondary education), he/she should be coded "15".</p> <p>If a person is attending/attended a diploma course in a middle level college/technical Training Institute (post-secondary education), he/she should be coded "16". If P45= 4 or 9 then enter "97". Kenya 2019: Persons age 3+ who ever attended school [discrepancies: none] This variable indicates the person's highest educational standard, form, or grade reached. 010 Pre-primary 101 Standard or grade 1 102 Standard or grade 2 103 Standard or grade 3 104 Standard or grade 4 105 Standard or grade 5 106 Standard or grade 6 107 Standard or grade 7 108 Standard or grade 8 109 Form 1 or grade 9 110 Form 2 or grade 10 111 Form 3 or grade 11 112 Form 4 or grade 12 113 Form 5 114 Form 6 115 Certificate 116 Diploma 117 Under graduate (first degree) 118 Post graduate diploma 119 Masters 120 Ph.D., M.D., or doctorate 121 Adult basic education 122 Adult secondary education 123 Vocational training 124 Madrassa or Duksis 998 Unknown 999 NIU (not in universe) Education Variables -- PERSON Highest educational standard, form, or grade completed <span class="h2">D: Information regarding education attainment</span></p> <p><span class="ital">For persons aged 3 years and above.</span> <br />[Question 43-47 were asked of persons age 3 or more]</p> <p>P-47. What is the highest std/form/grade completed by [the respondent]?</p> <div class="i1">The code list provided. Write "97" if P-45 = 4 or 9.<br /><br />Highest std/form/grade completed _ _</div> <span class="em">23. Section D: Education status for persons aged 3 years and above</span></p> <p>23.1. Columns P45 - P48: Information regarding education and training</p> <p>Questions on Column P45 to P47 are applicable to persons age 3 years and above and refer to formal and non-formal education, while P48 applies to persons age 15 and above. Formal education covers pre-primary, primary, secondary, vocational training centres (formerly youth polytechnics), middle level colleges and university. Non-formal education (NFE) is any other form of education that does not follow standard approved curricula of the formal system but offers numeric and literacy skills through flexible learning, e.g. adult education, apprenticeship, madrassa/Duksi, etc.</p> <p>Definitions</p> <div class="i1">i. School/learning institution - This is a place or centre in which learning is offered to a particular group of persons at a given level of education (levels of education can be ECDE, primary, secondary, university, etc). This also includes centres where special needs education is provided. Note: for those in distance/open/remote/online, etc learning, are considered to be registered in a school/learning institution, and in which case, the same definition applies.<br /><br />ii. Early childhood development education (ECDE) - This is an education programme offered to provide holistic integrated services that create a strong foundation for a child's cognitive (talents), psycho-social, moral, spiritual, emotional and psychomotor (physical education-PE) needs. Note: Although the education section will target persons aged 3 years and above, the official target group for the ECDE programme is children under 6 years. In addition, some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. Under this system child aged 3-5 years attend nursery/pre-primary; Early Years Foundations Stage (EYFS).<br /><br />iii. Primary - This refers to the level of education immediately after ECDE and covers 8 years under the 8-4-4 system. Before the 8-4-4 system, there was the 7-4-2-3 structure in which the length of primary education was 7 years. In the proposed system (2-6-3-3), primary education will last 6 years after ECDE. While the 7-4-2-3 and 8-4-4 systems had end of cycle examinations - Certificate of Primary Education (CPE) and Kenya Certificate of Primary Education (KCPE) - the proposed system will not have a summative evaluation of learners. Note: Some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. There are 5 Key Stages under BIC. Primary education is under Key Stage 1 and 2 and it lasts for 6 years (lower primary 3 years and upper primary 3 years).<br /><br />iv. Secondary - This refers to the level of education immediately after primary and covers 4 years under the 8-4-4 system. Before the 8-4-4 system, the 7-4-2-3 offered secondary education lasting 6 years (4 years at Ordinary Level and 2 years at Advanced Level). Note: Some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. There are 5 Key Stages under BIC. Secondary education is under Key Stage 3 (Junior School) that lasts for 3 years, Key Stage 4 (Senior School) that lasts for 2 years and Key Stage 5 (Pre-University Studies) that also lasts for 2 years. At the end of year 11 (senior school) students sit for International General Certificate of Secondary Education (IGCSE) exams. At the end of year 12 (Secondary 12) students sit for Advanced Subsidiary (AS) exams while at the end of year 13 (Secondary 13) students sit for Advanced (A) level exams.<br /><br />v. Vocational skills -- these are practical or first-hand capabilities that help learners to have basic skills on how to carry out a given job/assignment effectively.<br /><br />vi. Vocational training centre (formerly youth polytechnic) - This is a training institution that offers vocational skills training to primary/secondary school leavers. The courses offered in vocational training centres last 1 to 2 years and may include artisan 1 and 2; craft 1 and 2, such as carpentry, masonry, electrical, hair dressing and tailoring, etc.<br /><br />vii. Middle level/technical training -- This is a post-secondary education programme that offers various courses at certificate, diploma and higher national diploma level. The programme caters for students who have completed secondary education. The institutions that offer these courses include primary teacher training colleges that offer primary teaching certificate and diploma; medical training colleges that offer certificate and diploma in nursing/clinical medicine etc.; agriculture training colleges; media colleges; ICT colleges; technical training institutes; national polytechnics, among others.<br /><br />viii. University- This is the last cycle of the formal education programme in the country providing various courses according to sector professional prescriptions. This level of education offers pre-university courses, undergraduate degree courses and post-graduate courses.<br /><br />ix. Non-formal education (NFE) - This is an education programme that offers flexible learning for adults and children of school going age who are not able to join the formal system of education. The objective of the programme is to help learners acquire basic and post-basic literacy including vocational skills identified to be relevant and adequate for their level. Note: Non-formal education is offered in centres/learning institutions invariably called non-formal schools (NFS), or informal schools/centres</div><p>Where basic education involves mainly teaching numeric and literacy skills. A learner is considered to have achieved basic level of education after sitting and passing recommended proficiency examination.</p> <p>Post literacy education teaches learners on subjects similar to those in formal primary schools. Like in basic literacy, a learner is considered to have achieved post-basic literacy education after sitting and passing recommended proficiency examination or the Kenya Certificate of Primary Education (KCPE).</p> <p>23.4. Column P47: Highest standard/form/grade of education completed <br />Objective: to determine the education attainment levels of the population in the country and their distribution. Explain none: those currently attending pre-primary and have not completed.</p> <p>Ask: What is the highest std/form/grade completed by [the respondent]?</p> <p>This question seeks to establish the highest class completed by the person whose details are being given. If the person was at school in standard 4 and left before completing, the highest standard he/she is considered to have completed is standard/grade 3 and so should be allocated code "3". Refer to the code list provided. If P45=4 use code "97" and if P45=9 use code "98".</p> <div class="i1">i. The simple rule here is that for all persons attending school this year, the highest level completed should be one standard/grade/form lower than the highest level reached. For persons not attending school during the year of census, the highest level completed may be the same as the highest level reached or one level below it, but should never be greater.<br />ii. For example: record the highest standard/grade/form the person has completed in the formal primary or secondary school system e.g. a person currently attending secondary form 1 will certainly have completed standard 8 and therefore should be given the code "8" for the highest standard/grade/form completed. Those who are in form 2 should be allocated code "9".<br />iii. If a person is attending the first year in the vocational training centre, the highest standard/grade/form completed for such a person is standard 8 and should be coded "8".<br />iv. If a person has attended university but never completed or is currently attending undergraduate studies, such a person will be taken to have completed secondary school, either form 4 or 6 whichever is applicable. If the person is in a master's programme, the highest completed level is the first degree of an undergraduate, enter code "17". If a person is in a doctoral programme, the highest completed level is a master's degree, and in that case, the person should be coded "19".</div> Kenya 2019: Persons age 3+ who ever attended school [discrepancies: none] This variable indicates the person's highest educational standard, form, or grade completed. 000 None 010 Pre-primary 101 Standard or grade 1 102 Standard or grade 2 103 Standard or grade 3 104 Standard or grade 4 105 Standard or grade 5 106 Standard or grade 6 107 Standard or grade 7 108 Standard or grade 8 109 Form 1 or grade 9 110 Form 2 or grade 10 111 Form 3 or grade 11 112 Form 4 or grade 12 113 Form 5 114 Form 6 115 Certificate 116 Diploma 117 Under graduate (first degree) 118 Post graduate diploma 119 Masters 120 Ph.D., M.D., or doctorate 121 Adult basic education 122 Adult secondary education 123 Vocational training 124 Madrassa or Duksis 998 Unknown 999 NIU (not in universe) Education Variables -- PERSON Main field of post-secondary training <span class="h2">D: Information regarding education attainment</span></p> <p><span class="ital">For persons aged 15 years and above.</span> <br />[Question 48 was asked of persons age 15 or more]</p> <p>P-48. What is the main training that [the respondent] has acquired and qualified for?</p> <div class="i1">Applies when P-45=1, 2, and 3. Code list provided.<br /><br />Main training _ _</div> <span class="em">23. Section D: Education status for persons aged 3 years and above</span></p> <p>23.1. Columns P45 - P48: Information regarding education and training</p> <p>Questions on Column P45 to P47 are applicable to persons age 3 years and above and refer to formal and non-formal education, while P48 applies to persons age 15 and above. Formal education covers pre-primary, primary, secondary, vocational training centres (formerly youth polytechnics), middle level colleges and university. Non-formal education (NFE) is any other form of education that does not follow standard approved curricula of the formal system but offers numeric and literacy skills through flexible learning, e.g. adult education, apprenticeship, madrassa/Duksi, etc.</p> <p>Definitions</p> <div class="i1">i. School/learning institution - This is a place or centre in which learning is offered to a particular group of persons at a given level of education (levels of education can be ECDE, primary, secondary, university, etc). This also includes centres where special needs education is provided. Note: for those in distance/open/remote/online, etc learning, are considered to be registered in a school/learning institution, and in which case, the same definition applies.<br /><br />ii. Early childhood development education (ECDE) - This is an education programme offered to provide holistic integrated services that create a strong foundation for a child's cognitive (talents), psycho-social, moral, spiritual, emotional and psychomotor (physical education-PE) needs. Note: Although the education section will target persons aged 3 years and above, the official target group for the ECDE programme is children under 6 years. In addition, some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. Under this system child aged 3-5 years attend nursery/pre-primary; Early Years Foundations Stage (EYFS).<br /><br />iii. Primary - This refers to the level of education immediately after ECDE and covers 8 years under the 8-4-4 system. Before the 8-4-4 system, there was the 7-4-2-3 structure in which the length of primary education was 7 years. In the proposed system (2-6-3-3), primary education will last 6 years after ECDE. While the 7-4-2-3 and 8-4-4 systems had end of cycle examinations - Certificate of Primary Education (CPE) and Kenya Certificate of Primary Education (KCPE) - the proposed system will not have a summative evaluation of learners. Note: Some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. There are 5 Key Stages under BIC. Primary education is under Key Stage 1 and 2 and it lasts for 6 years (lower primary 3 years and upper primary 3 years).<br /><br />iv. Secondary - This refers to the level of education immediately after primary and covers 4 years under the 8-4-4 system. Before the 8-4-4 system, the 7-4-2-3 offered secondary education lasting 6 years (4 years at Ordinary Level and 2 years at Advanced Level). Note: Some pupils undergo the British International Curriculum (BIC) system that runs in the country parallel to the existing system. There are 5 Key Stages under BIC. Secondary education is under Key Stage 3 (Junior School) that lasts for 3 years, Key Stage 4 (Senior School) that lasts for 2 years and Key Stage 5 (Pre-University Studies) that also lasts for 2 years. At the end of year 11 (senior school) students sit for International General Certificate of Secondary Education (IGCSE) exams. At the end of year 12 (Secondary 12) students sit for Advanced Subsidiary (AS) exams while at the end of year 13 (Secondary 13) students sit for Advanced (A) level exams.<br /><br />v. Vocational skills -- these are practical or first-hand capabilities that help learners to have basic skills on how to carry out a given job/assignment effectively.<br /><br />vi. Vocational training centre (formerly youth polytechnic) - This is a training institution that offers vocational skills training to primary/secondary school leavers. The courses offered in vocational training centres last 1 to 2 years and may include artisan 1 and 2; craft 1 and 2, such as carpentry, masonry, electrical, hair dressing and tailoring, etc.<br /><br />vii. Middle level/technical training -- This is a post-secondary education programme that offers various courses at certificate, diploma and higher national diploma level. The programme caters for students who have completed secondary education. The institutions that offer these courses include primary teacher training colleges that offer primary teaching certificate and diploma; medical training colleges that offer certificate and diploma in nursing/clinical medicine etc.; agriculture training colleges; media colleges; ICT colleges; technical training institutes; national polytechnics, among others.<br /><br />viii. University- This is the last cycle of the formal education programme in the country providing various courses according to sector professional prescriptions. This level of education offers pre-university courses, undergraduate degree courses and post-graduate courses.<br /><br />ix. Non-formal education (NFE) - This is an education programme that offers flexible learning for adults and children of school going age who are not able to join the formal system of education. The objective of the programme is to help learners acquire basic and post-basic literacy including vocational skills identified to be relevant and adequate for their level. Note: Non-formal education is offered in centres/learning institutions invariably called non-formal schools (NFS), or informal schools/centres</div><p>Where basic education involves mainly teaching numeric and literacy skills. A learner is considered to have achieved basic level of education after sitting and passing recommended proficiency examination.</p> <p>Post literacy education teaches learners on subjects similar to those in formal primary schools. Like in basic literacy, a learner is considered to have achieved post-basic literacy education after sitting and passing recommended proficiency examination or the Kenya Certificate of Primary Education (KCPE).</p> <p>23.5. Column P48: Professional training (to be asked to persons aged 15 years and above) <br />Ask: What is the main training that [the respondent] has acquired and qualified for?</p> <p>This question seeks to establish the main area of training for each member of the household who has completed any of the following three levels: post primary vocational training, post-secondary technical training and university.</p> <p>Note: In some cases, some members of a household may have trained in multiple courses to enhance their career growth. In such cases, the enumerator is expected to establish the main training of the household member and record this. For instance, a person who has been trained as architecture can pursue further training in business administration at the master level. The main area of training for such a person will be professions and applied sciences specialty in architecture. Likewise, a teacher who pursues further training in psychology or guidance and counseling will have their main area of training in professions and applied sciences specialty in education.</p> <p>The code list for the areas of training is presented in various domains. For instance, there is a humanities domain, which includes specialties like anthropology, history, language, and linguistics. If a person is trained in history, for example, the enumerator should select humanities and then enter "12". Similarly, in the domain of professions and applied sciences, the specialties include agriculture, animal health and veterinary sciences, health and human medicine (doctors), etc. In this case, a doctor will be clustered under professions and applied sciences and code "63" is applied.</p> <p>Code list for highest education level and grade reached and completed for question P-46 and P47 Kenya 2019: Persons age 15+ who ever attended school [discrepancies: none] This variable indicates the person's main field of post-secondary training. 011 Anthropology 012 History 013 Languages and linguistics 014 Philosophy 015 Religion 016 Arts, including literary, performance, and visual 021 Economics 022 Geography 023 Interdisciplinary studies (including cultural studies, gender studies, organizational studies - project management, planning, human resource management, development studies, demography, and urban planning) 024 Political science 025 Psychology 026 Sociology 031 Biology 032 Chemistry 033 Earth sciences (geology and meteorology) 034 Physics 035 Space sciences - astronomy 041 Computer science 042 Logic 043 Mathematics (pure and applied) 044 Statistics (including actuarial, biometry, biostatistics, social statistics, and financial statistics) 045 Systems sciences (including computing) 051 Agriculture (including horticulture, agribusiness, agricultural economics, and crop sciences) 080 Animal health and veterinary sciences 052 Architecture and design (including quantity surveying and structural engineering) 053 Business (including commerce, accounting, finance, marketing, administration, management, insurance, hotel management, and tourism) 054 Divinity and pastoral related (theological studies) 055 Education (including science, arts, special, management, and economics) 056 Engineering and technology (civil, electrical and electronics, mechanical, chemical, aeronautical, and biosystems) 057 Environmental studies, marine ecology, and forestry 058 Family and consumer sciences (including home economics, applied human nutrition, and dietetics) 059 Human physical performance and recreation (including sports science and sports economics) 060 Journalism, media studies and communication (including public relations, mass communication, and speech and rhetoric) 061 Law 062 Library, information science, and museum studies 063 Health and human medicine: Doctors 081 Health and human medicine: Dentists and pharmacists 064 Health and human medicine: Laboratory technologists, radiologists, anesthesists, and similar 065 Health and human medicine: Clinical officers, nurses, physiotherapists, and similar 066 Military sciences 067 Public administration - public policy 068 Social work 069 Transportation-logistics management 070 Vocational training (including plant, motor vehicle, plumbing, wiring, masonry, carpentry and joinery, refrigeration and air conditioning, hair dressing, tailoring, and commercial vehicle driving) 071 Aviation (including air craft maintenance, piloting, stewardship, and air traffic control) 097 Others 098 None 998 Unknown 999 NIU (not in universe) Education Variables -- PERSON Main activity during the last seven days <span class="h2">E: Labor force participation</span></p> <p><span class="ital">To be asked of all persons aged 5 years and above.</span> <br />[Questions 49-54 were asked of persons age 5 or more]</p> <p>P-49. Activity status. What was [the respondent] mainly doing during the last 7 days preceding the census night 24th/25th August, 2019?</p> <div class="i1">Code list provided.<br /><br />Activity status _ _</div> <span class="em">24. Section E: Labour force participation</span></p> <p>24.1. Introduction <br />A population census is one of the main sources of labour statistics, which are an important element in the measurement of economic growth and development in a country. Work is defined as "any activity performed by persons of any sex and age to produce goods or services. All work or productive activities are thus included, irrespective of their formal or informal character or the legality of the activity. Excluded are activities that do not involve producing goods or services (for example begging and stealing), self-care (for example, personal grooming and hygiene), and activities that cannot be performed by another person on one's own behalf (for example, sleeping, learning and activities for own recreation).</p> <p>Questions on economic characteristics refer to the last seven days preceding the census night and are asked of all persons aged 5 years and above.</p> <p>24.2. Labour force participation</p> <p>Questions on labour force participation refer to questions in columns P49 to P54.</p> <p>Column P49: Activity status <br />Ask: What was [the respondent] mainly doing during the last seven days preceding the census night (24th/25th August, 2019)?</p> <p>What the respondent was mainly doing will denote the economic activity that occupied most of the respondent's time during the 7 days preceding the census night. Persons who held a job but were temporarily absent from work during the 7 days preceding the census should be coded based on the status of engagement as detailed below. The responses in column P49 are as follows:</p> <div class="i1">i. Worked for pay<br />This comprises persons who, during the 7 days preceding the census night, worked most of the time for wages, salaries, commissions, tips, contracts and paid in kind (especially in the rural areas where people who have rendered services may be paid using food or clothing). Any member of the household working on the holding for pay will fall under code "01".</div><div class="i1">ii. Worked on own/family business<br />This category comprises self-employed persons who worked on own business or persons who worked on family business for family gain. It includes "jua-kali" artisans, mechanics, traders in farm produce, and family workers not on wage employment. All persons working on own or family businesses should fall under code "02".</div><div class="i1">iii. Worked on own/family agricultural holding<br />A holding in this case is a unit of land, farm or shamba which is owned or rented by the family and is used for purposes of cultivation or rearing livestock. The production may either mainly be intended for the market or for household consumption. All the members of the household who are working on the holding without pay/profit, and production is mainly meant for the market will be coded "03" (i.e. worked on own family/holding (market)). Any member of the household working on the holding for pay will fall under code "01" (i.e. worked for pay).</div><div class="i1">iv. Apprentice<br />An apprentice is a person whose training is done on the job for an agreed period. This helps the person to learn their trade, in exchange for their labour. The person may be unpaid or partially paid (usually in form of a stipend). Enter paid and unpaid apprentices as appropriate.</div><div class="i1">v. Intern and students on attachment<br />Intern: This refers to a student or trainee who works, sometimes without pay, at a trade or occupation in order to gain work experience. In most cases, an intern will have completed a certain level of education or training. In certain engagements, interns may be paid during their internship while in others, they are not paid for enter as appropriate i.e. paid interns or unpaid interns.<br /><br />Student on attachment is a person pursuing a certain course in a certain college but as part of his / her training spends time in a practicing institution learning as well as working.</div><div class="i1">vi. Volunteer work<br />Volunteers: Persons in volunteer work are defined as all those above a specified age who, during a short reference period, performed any unpaid, non-compulsory activity to produce goods or provide services for others.<br /><br />There are instances where individuals are engaged as 'volunteers' but in actual sense they are paid allowances which are equivalent to those being compensated for work done or services rendered. Such individuals should be coded as "08" i.e. "Volunteer - Paid".<br /><br />"Unpaid" is interpreted as the absence of remuneration in cash or in kind, for work done or hours worked; nevertheless, volunteer workers may receive some form of cash reimbursement for out-of-pocket expenses, a stipend to cover living expenses or in-kind compensation (such as meals, transportation, or symbolic gifts); such persons should be coded as "09". These people do not receive any compensation for services rendered other than reimbursement for out-of pocket expenses.</div><div class="i1">vii. Future starters<br />These are defined as persons "not in employment" and "currently available" but who did not "seek employment" because they had already made arrangements to start a job within a short subsequent period, set according to the general length of waiting time for starting a new job in the national context but generally not greater than three months. Code these as "10".</div><div class="i1">viii. Seeking work<br />The persons to be classified in any of the seeking work categories should be those who are not employed during the reference period. This category should, therefore, not include the under-employed (those who have paid work but wish to leave current employment for better opportunities). Further, a general declaration of being in search of work is not sufficient to code one in this category. The enumerator should probe to establish whether any action was taken and code appropriately as "11" or "12". Furthermore, the person should be available to take up a job even if they did not actively seek work in the reference period.</div><div class="i1">ix. No work available<br />This is a person who is neither working nor looking for work because he/she is discouraged but would usually take up a job when offered one.</div><div class="i1">x. Retired<br />This is a person who reports that, during the 7 days preceding the census night, he/she was not engaged in any economic activity because he/she had retired either due to age, sickness or voluntarily. If a person has retired and is doing some work/business, he/she should be coded appropriately, either as "01", "02", or "03". If one has retired and is seeking work he/she should be coded as "11" or "12" depending on the job search status.</div><div class="i1">xi. Too old to work<br />This category will be for persons who will give age (too old) as the reason for not being engaged in any economic activity. This should be distinguished from those who give retirement as a reason.</div><div class="i1">xii. Homemaker<br />This is a person of either sex involved in household chores in his/her own home, e.g. fetching water, cooking, babysitting, etc., who did not work for pay or profit nor sought work. This category should not include houseboys/girls who fall under category "01". If such a person worked on family holding, they should be coded as "02" or "03" and not as "16". Please probe.</div><div class="i1">xiii. Full-time student/attending an educational institution<br />This is a person who spent most of his/her time in a regular public or private educational institution (primary, secondary, college, university, etc.) for systematic instruction at any level of education and hence not available for work. If, for instance, a student was on holiday during the 7 days preceding the census night, and may have been engaged in gainful employment, he/she should be coded appropriately.</div><div class="i1">xiv. Incapacitated<br />This is a person who cannot work. Do not assume that all physically challenged persons cannot work. For example, a blind person who is in wage employment will fall under category "01" and not "18". Similarly, persons living with disabilities working on the family holding should fall under category "02" or "03". Please probe.</div> Kenya 2019: Persons age 5+ [discrepancies: none] This variable indicates the person's main activity during the last seven days. 01 Worked for pay 02 Worked on own or family's business 03 Worked on own or family's agricultural holding 04 Apprentice, paid 05 Apprentice, unpaid 06 Intern, paid 07 Intern, unpaid 08 Volunteer, paid 09 Volunteer, unpaid 10 Waiting for an arranged job to start 11 Seeking work, action taken 12 Seeking work, no action taken 13 No work available 14 Retired 15 Too old to work 16 Home maker 17 Full time student 18 Incapacitated 19 Too young to work 98 Unknown 99 NIU (not in universe) Work Variables -- PERSON Main employer (sector) <span class="h2">E: Labor force participation</span></p> <p><span class="ital">For those who worked or held a job (including those on leave/sick leave.)</span> <br />[Questions 50-54 were asked of persons age 5 or more who worked or held a job, including those on leave/sick leave]</p> <p>P-50. Who was [the respondent]'s main employer?</p> <div class="i1">The code list provided. Code "99" for not applicable.<br /><br />Main employer _ _</div> <span class="em">24. Section E: Labour force participation</span></p> <p>24.3. Column P50: Main employer <br />This question applies to those whose response to P49 was 1 to 9. Ask: Who was [the respondent]'s main employer?</p> <p>Establish [the respondent]'s main employer. Each person who is working or held a job in the reference period will be asked whom they work for.</p> <p>To clarify: <br />Broadly, employment sector refers to whether the employment is public (governmental) or private (non-governmental) or informal.</p> <div class="i1">i. National government<br />National government covers all institutions and establishments of the National government such as the ministries.</div><div class="i1">ii. State owned enterprises<br />State owned enterprises refer to parastatals, semi-autonomous government agencies and any other entity where the government has majority share/rights control, its statutory corporations (wholly owned corporations or parastatals). These exclude the Teachers Service Commission (TSC), which is categorized separately.</div><div class="i1">iii. Teachers service commission<br />Teachers Service Commission includes teachers employed under the TSC and the secretariat.</div><div class="i1">iv. Other constitutional commissions<br />Other constitutional commissions are those independent commissions that were created under the Constitution of Kenya, 2010, e.g. Kenya National Human Rights and Equality Commission, Public Service Commission, National Land Commission, Parliamentary Service Commission, Judicial Service Commission, Commission on Revenue Allocation, Independent Electoral and Boundaries Commission, Salaries and Remuneration Commission, etc.</div><div class="i1">v. County government employees<br />County Government employees include members of the County Executive Committees and all employees of the county governments.</div><div class="i1">vi. Private sector enterprise employees<br />Private sector enterprise employees include all persons employed by formal private sector enterprises excluding those that are self-employed and those categorized below.</div><div class="i1">vii. International non-governmental organizations (NGOs)<br />International Non-Governmental Organizations (NGOs) are NGOs that may be operating locally or have local chapters but whose ownership is not local, e.g. CARE International, Oxfam, Amnesty International, Action Aid etc.</div><div class="i1">viii. Extraterritorial organizations and bodies<br />These include international organizations such as the United Nations and its specialized agencies, regional bodies, etc., the International Monetary Fund, the World Bank, the World Customs Organization, the Organization for Economic Co-operation and Development, the Organization of Petroleum Exporting Countries, the European Communities, the European Free Trade Association, International Committee of the Red Cross (ICRC) and Red Crescent Societies, etc. It also includes diplomatic and consular missions.</div><div class="i1">ix. Local NGOs/community based organizations (CBOs)<br />Local NGOs/Community Based Organizations (CBOs) are locally managed/registered non-profit making bodies which mainly engage in charity work. These include: Green Belt Movement, Family Health Options Kenya, and Federation of Women Lawyers - Kenya Chapter (FIDA), etc.</div><div class="i1">x. A Faith?based organization (FBO)<br />It may include organizations such as schools, hospitals, etc. whose leaders are affiliated to religious organizations and groups founded by missionaries or religious leaders, so long as the founders are still active in the group.</div><div class="i1">xi. Self-employed formal<br />Covers individuals and or professionals who operate and work in their own enterprises/businesses. Examples of self-employed formal sector may include doctors, lawyers in private practice, etc. whose businesses are registered with the Registrar of Companies.</div><div class="i1">xii. Informal sector "Jua Kali" (employed)<br />Includes persons who are employed in private unincorporated enterprises that are unregistered or small in terms of the number of employed persons. Such enterprises are unincorporated if they are not constituted as separate legal entities independent of their owner(s) and do not maintain complete sets of accounts.</div><div class="i1">xiii. Self-employed (informal)<br />Includes persons who operate their own businesses that are not registered with the Registrar of Companies. For example, a person who buys and sells agricultural produce, e.g. milk, maize, cabbages, "sukuma wiki", etc. will be classified as self-employed informal if the business is not registered with the Registrar of Companies.</div><div class="i1">xiv. Small scale agriculture/ fisherman (employed)<br />Includes persons who are employed by other individuals and/or households in small scale agriculture/fishing/forestry/loggers etc.</div><div class="i1">xv. Self--small scale agriculture/ fishing<br />Includes persons whose main job is in their own or household owned small scale agricultural activities.</div><div class="i1">xvi. Pastoralist activities (employed)<br />Persons/individuals employed by other individuals and/or households in pastoralist activities.</div><div class="i1">xvii. Self-pastoralists activities<br />Covers individuals whose main work involves taking care of their own or household owned livestock.</div><div class="i1">xviii. Individual/private household<br />Includes persons/individuals employed by households, e.g. domestic workers, gardeners, etc.</div><p>All efforts should be made to place individuals in the above categories and enumerators should be able to correctly code.</p> <p>Selected examples</p> <div class="i1">i. A person employed by the Kenya National Bureau of Statistics (KNBS) as a cleaner will be classified as working in state owned enterprise;<br /><br />ii. If KNBS outsourced cleaning services from a private company, the cleaner will be classified as working in private owned enterprise;<br /><br />iii. A person who works as a cleaner in someone's home will be classified in Individual/Private household;<br /><br />iv. A person working in a Parish or Mosque should be coded as working for an FBO;<br /><br />v. A person who buys and sells agricultural produce, e.g. milk, maize cabbages, "sukuma wiki", etc. will be classified as self? employed informal if the business is not registered with the registrar of companies.</div> Kenya 2019: Persons age 5+ who worked or had a job [discrepancies: none] This variable indicates the person's main employer (sector). 01 National government 02 State owned enterprise or institution, or parastatals 03 Teachers service commission 04 Other constitutional commission 05 County government 06 Private sector enterprise 07 International organization, including non-governmental (NGO) 08 Extraterritorial organizations and bodies 09 Local non-governmental organization (NGO) or community based organization (CBO) 10 Faith based organization 11 Self-employed, formal 12 Employed in the informal sector, or Jua Kali 13 Self-employed, informal 14 Employed in small scale agriculture 15 Self-employed, small scale agriculture 16 Employed in pastoralist activities 17 Self-employed, pastoralist activities 18 Individual or private household 19 Schools board of management (BOM) 99 NIU (not in universe) Work Variables -- PERSON Status in the main job <span class="h2">E: Labor force participation</span></p> <p><span class="ital">For those who worked or held a job (including those on leave/sick leave.)</span> <br />[Questions 50-54 were asked of persons age 5 or more who worked or held a job, including those on leave/sick leave]</p> <p>P-51. What was [the respondent]'s status in the main job?</p> <div class="i1">The code list provided. Code "99" for not applicable.<br /><br />Status in main job _ _</div> <span class="em">24. Section E: Labour force participation</span></p> <p>24.4. Column P51: Status in employment <br />This question applies to those whose response to P49 was 1 to 9.</p> <p>Status in employment refers to the type of a contract of employment with other persons or organizations that the employed person has in his or her main job. The basic criteria used to define the group's classification are the type of economic risk, an element of which is the strength of the attachment between the person and the job, and the type of authority over establishments and other workers that the person has or will have in the job. Ensure that an employed person is classified by status in employment on the basis of the main job i.e. the same one used for classifying the person by "occupation", "industry" and "sector".</p> <div class="i1">i. Paid employee/worked for pay<br />These are individuals who earn for the services rendered either by cash or in kind. An employee is a person who works in a job where a contract of employment gives the incumbent a basic remuneration that is independent of the revenue of the unit for which he or she works (this unit can be a corporation, a non-profit institution, a government unit or a household).<br /><br />Employees are typically remunerated by wages and salaries, but may be paid by commission from sales, or through piece rates, bonuses or in-kind payment such as food, housing or training. Some or all of the tools, capital equipment, information systems and premises used by the incumbent may be owned by others, and the incumbent may work under the direct supervision of or according to strict guidelines set by the owner or persons in the owner's employment. These are further categorized as those engaged outside the household and within the household. Enter code "1" or "2" as may be appropriate.</div><div class="i1">ii. Working employer<br />An employer is a person who, working on his or her own account or with one or a few partners, holds a self-employment job and, in this capacity, has engaged on a continuous basis (including the reference period) one or more persons to work for him or her as employees. The incumbent makes the operational decisions affecting the enterprise, or delegates such decisions while retaining responsibility for the welfare of the enterprise. Some countries may wish to distinguish among employers according to the number of persons they employ.</div><div class="i1">iii. Own-account worker<br />An own-account worker is a person who, working on his or her own account or with one or a few partners, holds a self-employment job, and has not engaged any employees on a continuous basis. (Note, however, that during the reference period, an own-account worker may have engaged one or more employees on a short-term and non-continuous basis without being thereby classifiable as an employer). Persons engaged in agriculture (including livestock care), fishing, hunting and gathering, intended mainly for own consumption by their households, should also be included as having done some work / in employment on the sole basis of that activity and should, therefore, be considered as "own-account workers".</div><div class="i1">iv. Member of a producers' cooperative<br />A member of a producers' cooperative is a person who holds a self-employment job in an establishment organized as a cooperative, in which each member takes part on an equal footing with other members in determining the organization of production, sales or other work, investments and the distribution of proceeds among the members. Note that employees of producers' cooperatives are not to be classified as in this group but should be classified as "employees".</div><div class="i1">v. Contributing family worker<br />A contributing family worker (CFW) is a person who holds a self-employment job in a market-oriented establishment operated by a related person, who actually controls the enterprise as either employers or own-account workers in the enterprise and living in the same or in another household. A CFW is by definition unpaid and is neither an employer nor own-account worker, this is because the degree of his or her commitment to the operation of the establishment, in terms of working time or other factors to be determined by national circumstances, is not at a level comparable with that of the head of the establishment.</div><div class="i1">vi. Volunteer/ apprentice<br />As described above.</div> Kenya 2019: Persons age 5+ who worked or had a job [discrepancies: none] This variable indicates the person's status in the main job. 01 Paid employee outside household 02 Paid employee within household 03 Working employer 04 Own account worker 05 Members of producers' co-operatives 06 Contributing family worker 07 Paid apprentice or intern 08 Paid volunteer 09 Other 99 NIU (not in universe) Work Variables -- PERSON Hours worked in past seven days <span class="h2">E: Labor force participation</span></p> <p><span class="ital">For those who worked or held a job (including those on leave/sick leave.)</span> <br />[Questions 50-54 were asked of persons age 5 or more who worked or held a job, including those on leave/sick leave]</p> <p>P-52. How many hours did [the respondent] work in the last 7 days preceding the census night?</p> <div class="i1">Code "99" for not applicable.<br /><br />Hours worked _ _</div> <span class="em">24. Section E: Labour force participation</span></p> <p>24.5. Column P52: Working time <br />The concept of working time comprises the time associated with productive or work activities and the arrangement of this time during a specified reference period. Information on working time is necessary to prepare estimates of the volume of work or labour input for complete national production accounts. It is also essential to support the design, monitoring and evaluation of economic, social and labour market policies and programmes targeting labour market flexibility, work-life balance and conditions of work, including situations of underemployment due to insufficient working time (that is, time-related under-employment) and of excessive working time.</p> <p>The measurement of working time is generally restricted to reference of one day or one week. Working time is usually measured and expressed in terms of units of time. These units are the smallest units used for measurement purposes and cannot be divided (i.e. a person who worked during part (or most) of the time unit should be reported as having worked during that unit). The time unit chosen by convention is generally one hour. Hours of work are categorized for the census into (a) usual/normal hours of work and (b) actual hours worked. Normal/usual hours of work refers to hours of work fixed by or in pursuance of laws, regulation, collective agreement or arbitral wards.</p> <p>Ask how many hours [the respondent] actually worked seven days prior to the census night.</p> <p>This question seeks to establish the actual number of hours worked in the seven days preceding the census night. In this section, one may be required to make some arithmetic calculations. If the respondent cannot remember the number of hours over the past 7 days, ask for the number of hours in one day and ask how many days the task was done in the seven days. Then multiply the number of hours by the number of days to get the total number of hours for the last 7 days.</p> <p>Where a person did not actually work during the reference period, but held a job, ask for the usual hours of work and calculate.</p> <p>For example, <br />i. Civil servants normally work eight hours per day for five days translating to 40 hours per week. <br />ii. A factory worker who works overtime whether paid or not paid, for the extra time, the usual work hours will be less the extra time worked. Kenya 2019: Persons age 5+ who worked or had a job [discrepancies: none] This variable indicates the person's hours worked in past seven days. 001 1 hour 002 2 hours 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100 101 101 102 102 103 103 104 104 105 105 106 106 107 107 108 108 109 109 110 110 111 111 112 112 999 NIU (not in universe) Work Variables -- PERSON Industry, ISIC section <span class="h2">E: Labor force participation</span></p> <p><span class="ital">For those who worked or held a job (including those on leave/sick leave.)</span> <br />[Questions 50-54 were asked of persons age 5 or more who worked or held a job, including those on leave/sick leave]</p> <p>P-53. What kind of economic activity is [the respondent] engaged in?</p> <div class="i1">Main job. The code list provided. Code "99" for not applicable.<br /><br />Economic activity _ _</div> <span class="em">24. Section E: Labour force participation</span></p> <p>24.6. Column P53: Industry/economic activity <br />Ask [the respondent] the kind of economic activity associated with their main job. This question seeks to determine the economic activity of the establishment in which an employed person worked during the reference period or last worked if unemployed. This activity is defined in terms of the kinds of goods produced, or services offered by the economic unit or establishment in which the person works i.e. the kind of economic activity associated with their main job. The branch of economic activity of a person does not depend on one's occupation. Therefore, if a driver reports working in a factory producing suitcases and handbags, the activity would be considered as Manufacturing. It should also be pointed out that the terms "industry" and "economic activity" are interchangeably used to mean the same thing. The categories used are based on the International Standard of Industrial Classification (ISIC) Rev 4. These broadly cover the following categories referred to as sections:</p> <p>Section A - Agriculture, forestry and fishing <br />This section includes the exploitation of vegetable and animal natural resources, comprising the activities of growing of crops, raising and breeding of animals, harvesting of timber and other plants, animals or animal products from a farm or their natural habitats. Examples: Flower farms, dominion farms, irrigation schemes, livestock rearing including emerging livestock, Kenya Forests Services, Logging activities; Agricultural extension offices, Fishing activities</p> <p>Section B - Mining and quarrying <br />This section includes the extraction of minerals occurring naturally as solids (coal and ores), liquids (petroleum) or gases (natural gas). Mining activities include mining and quarrying of fossil fuels (coal, lignite, petroleum, gas); metal ores, various minerals and quarry products (sand, stone etc). Examples: Tullow oil; Magadi Soda; Companies mining gemstones, Gold.</p> <p>Section C - Manufacturing <br />This section includes the physical or chemical transformation of materials, substances, or components into new products. The materials, substances, or components transformed are raw materials that are products of agriculture, forestry, fishing, mining or quarrying as well as products of other manufacturing activities. Examples: KETEPA; United millers; Mumias sugar; Kisii bottlers; Rivatex; General Motors; Tailoring, welding; carpentry; bakeries; Tea/coffee factories; Bidco; Menengai oil; fish processing companies.</p> <p>Section D - Electricity, gas, steam and air conditioning supply <br />This section includes the activity of providing electric power through a permanent infrastructure (network) of lines and mains. Also included is the distribution of electricity in industrial parks or residential buildings. This section therefore includes the operation of electric and gas utilities, which generate, control and distribute electric power. Examples: KPLC; KENGEN; KETRACO; Independent Power Producers-AGGREKO; Mini hydro generation entities.</p> <p>Section E - Water supply; sewerage, waste management and remediation activities <br />This section includes activities related to the management (including collection, treatment and disposal) of various forms of waste, such as solid or non-solid industrial or household waste, as well as contaminated sites. Activities of water supply are also grouped in this section, since they are often carried out in connection with, or by units also engaged in, the treatment of sewage. Examples: Water and sewerage Companies (WASCOs)-Subsidiaries of county governments; Private companies engaged in solid waste management-Bins.</p> <p>Section F - Construction <br />This section includes general construction and specialized construction activities for buildings and civil engineering works. It includes new work, repair, additions and alterations, the erection of prefabricated buildings or structures on the site and construction of a temporary nature. Examples: Construction companies-China Wu Yi; Kirinyaga construction; entities doing electrical works; Plumbing activities.</p> <p>Section G - Wholesale and retail trade; repair of motor vehicles and motorcycles <br />This section includes wholesale and retail sale (i.e. sale without transformation) of any type of goods (merchandise) and the rendering of services incidental to the sale of these goods. Wholesaling and retailing are the final steps in the distribution of goods. Also included in this section are the repair of motor vehicles and motorcycles. Examples: Car Bazaars; Garages; Small retail shops; Supermarkets; hardware shops. Pharmaceutical shops/outlets, electronic shops; Beer depots; butcheries, stalls, dealing in second hand clothes.</p> <p>Section H - Transportation and storage <br />This section includes the provision of passenger or freight transport, whether scheduled or not, by rail, pipeline, road, water or air and associated activities such as terminal and parking facilities, cargo handling, storage etc. Included in this section is the renting of transport equipment with driver or operator. Also included are postal and courier activities. Example: Matatu transport; Bodaboda; Water Transport- ferries/ships; air transport-Kenya airways, Fly 540; Air Kenya; Kenya pipeline; Uber; taxify; Warehouses-Storage godowns; Postal and Courier services.</p> <p>Section I - Accommodation and food service activities <br />This section includes the provision of short-stay accommodation for visitors and other travellers and the provision of complete meals and drinks fit for immediate consumption. Examples: Hotels and restaurants; Lodgings; small restaurants offering meals and drinks, bars, night clubs</p> <p>Section J - Information and communication <br />This section includes the production and distribution of information and cultural products, the provision of the means to transmit or distribute these products, as well as data or communications, information technology activities and the processing of data and other information service activities. Examples: Telecommunication companies-Safaricom, Airtel, Telkom; Publishing Companies-Longhorn, Jomo Kenyatta Foundation; Radio and TV broadcasting-NTV, K24, Ramogi FM, Radio Maisha, other ICT related activities, Internet Service providers- Dimension data, Liquid Telecoms, Swift Global, Huawei Technologies</p> <p>Section K - Financial and insurance activities <br />This section includes financial service activities, including insurance, reinsurance and pension funding activities and activities to support financial services. Also included are activities of holding assets, such as activities of holding companies and the activities of trusts, funds and similar financial entities. Examples: Banks, insurance companies, insurance brokers, SACCOs, private pension funds, Trusts, Mobile money transfer activities- MPESA. Airtel Money, Telkom Cash</p> <p>Section L - Real estate activities <br />This section includes acting as lessors, agents and/or brokers in one or more of the following: selling or buying real estate, renting real estate, providing other real estate services such as appraising real estate or acting as real estate escrow agents. Also included is the building of structures, combined with maintaining ownership or leasing of such structures and real estate property managers. Examples: Property management-agents-Lloyd Masika, Knight Frank, Land buying Companies.</p> <p>Section M - Professional, scientific and technical activities <br />This section includes specialized professional, scientific and technical activities. These activities require a high degree of training and make specialized knowledge and skills available to users. Examples: Law firms, audit firms, architects, management consultants, advertising, veterinary doctors, accounting firms, engineering, research and experimental work-KARI, KEMRI-CDC;</p> <p>Section N - Administrative and support service activities <br />This section includes a variety of activities that support general business operations. These activities differ from those in section M, since their primary purpose is not the transfer of specialized knowledge. Examples: Private security firms- well Fargo, G4S, Lavington Security; car hire services, tour and travel operators, employment bureaus, general cleaning of buildings- Parapet etc, photocopying and type setting services; call centers- kencall; equipment hire without operator.</p> <p>Section O - Public administration and defence; compulsory social security <br />This section includes activities of a governmental nature, normally carried out by the public administration. This includes the enactment and judicial interpretation of laws and their pursuant regulation, as well as the administration of programmes based on them, legislative activities, taxation, national defence, public order and safety, immigration services, foreign affairs and the administration of government programmes. This section also includes compulsory social security activities. Examples: Ministries, County government, Constitutional offices except teachers, NHIF, NSSF, KDF, police, prisons.</p> <p>Section P - Education <br />It includes education by the different institutions in the regular school system at its different levels as well as adult education, literacy programmes etc. Also included are military schools and academies, prison schools etc. at their respective levels. The section includes public as well as private education. Examples: Teachers in primary and secondary schools, lecturers in universities, other workers such as bursars, watchmen, support staff in learning institutions; adult education, military schools; prison schools etc.</p> <p>Section Q - Human health and social work activities <br />Activities include a wide range of activities, starting from health care provided by trained medical professionals in hospitals and other facilities, over residential care activities that still involve a degree of health care activities to social work activities without any involvement of health care professionals. Examples: Hospitals and health centres; hospices, rehabilitation centres, Social work (most NGO's/ CBO's) etc</p> <p>Section R - Arts, entertainment and recreation <br />This section includes a wide range of activities to meet varied cultural, entertainment and recreational interests of the general public, including live performances, operation of museum sites, gambling, sports and recreation activities. Examples: National Museums of Kenya, Sportpesa, Betin, Gormahia(kogalo), wild waters, Lunar parks, Kenya wildlife Services, Conservancies.</p> <p>Section S - Other service activities <br />This section (as a residual category) includes the activities of membership organizations, the repair of computers and personal and household goods and a variety of personal service activities not covered elsewhere in the classification. Examples: COTU, KNUT, religious organisations such as churches, mosques, temples; etc Barbershops (Kinyozi), salons, repair shops except garages.</p> <p>Section T - Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use <br />This section allows the domestic personnel employed to state the activity of their employer in censuses or studies, even though the employer is an individual. It includes activities of households as employers of domestic personnel. Examples: maids, cooks, waiters, valets, butlers, laundresses, gardeners, gatekeepers, stable-lads, chauffeurs, caretakers, governesses, babysitters, tutors, secretaries etc.</p> <p>Section U - Activities of extraterritorial organizations and bodies <br />This class includes activities of diplomatic and consular missions when being determined by the country of their location rather than by the country they represent. Also included are activities of international organizations. Examples: the United Nations and the specialized agencies of the United Nations system, regional bodies etc., the International Monetary Fund, the World Bank, the World Customs Organization, the Organisation for Economic Co-operation and Development, Comesa, EGAD, EAC, African Union Commission(AUC), the European Communities, the European Free Trade Association etc.</p> <p>24.7. Column P53 (a): Occupation in main job <br />Ask: What specific work does [the respondent] usually do within the main job / business that he/she had during the 7 days preceding the census night? (Enter the job title and briefly describe the main tasks) <br />Occupation is a major component of national labour market information and the data is important for policy formulation and evaluation for, labour market programmes, educational planning and work-related migration.</p> <p>Occupation refers to the type of work done by the person employed irrespective of where (the industry), or under what status in employment, it is being done. It is a "set of jobs whose main tasks and duties are characterized by a high degree of similarity" and should not be confused with the Economic activity/Industry or Status in Employment as described above. <br />This question seeks to establish the occupations of persons who worked or held a job in the reference period (last 7 days). A person will be associated with an occupation through the main job currently held.</p> <p>Examples: <br />- Security guard at a supermarket/shop <br />- Security guard at an airport <br />- Primary school teacher or teacher of primary school children <br />- Secondary school teacher <br />- Cashier in a bank <br />- Labourer in a construction site ("Mtu wa mkono") <br />- Accountant at a hotel <br />- Bus driver who drives passengers to the aircraft at an airport <br />- Subsistence farmer <br />- Farm hand on a farm <br />- Househelp in a private home Kenya 2019: Persons age 5+ who worked or had a job [discrepancies: none] This variable indicates the person's industry, ISIC section. 01 Agriculture 02 Mining and quarrying 03 Manufacturing 04 Electricity, gas, steam and air conditioning supply 05 Water supply; sewerage, waste management and remediation activities 06 Construction 07 Wholesale and retail trade; repair of motor vehicles and motorcycles 08 Transportation and storage 09 Accommodation and food service activities 10 Information and communication 11 Financial and insurance activities 12 Real estate activities 13 Professional, scientific and technical activities 14 Administrative and support service activities 15 Public administration and defense; compulsory social security 16 Education 17 Human health and social work activities 18 Arts, entertainment and recreation 19 Other service activities 20 Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use 21 Activities of extraterritorial organizations and bodies 99 NIU (not in universe) Work: Industry Variables -- PERSON Currently working in field of training <span class="h2">E: Labor force participation</span></p> <p><span class="ital">For those who worked or held a job (including those on leave/sick leave.)</span> <br />[Questions 50-54 were asked of persons age 5 or more who worked or held a job, including those on leave/sick leave]</p> <p>P-54. Is [the respondent] currently working/employed in the field of training in P-48?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">24. Section E: Labour force participation</span></p> <p>24.8. Column P54: Current work/employment and field of training <br />Ask: Is [the respondent] currently working/employed in the field of training given in P_48? <br />This question seeks to establish whether the respondent is doing work or is engaged in an occupation related to the main training identified in P_48. The work referred to here is that which is measured from P_49 to P_53a. Response to this question should be "Yes" (Enter "1") for those working in a field related to their main training and "No" (Enter "2") for those in an occupation different from their main training. Where it is not known, Enter "3" for (Don't know). Kenya 2019: Persons age 15+ who worked or had a job [discrepancies: type I trace; type II trace] This variable indicates whether the person is currently working in field of training. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Work Variables -- PERSON Owned a mobile phone in the last three months <span class="h2">F: Information regarding ICT</span></p> <p><span class="ital">To be asked of persons aged 3 years and above.</span> <br />[Questions 55-58 were asked of persons age 3 or more]</p> <p>P-55. Has [the respondent] owned a mobile phone in the last 3 months?</p> <div class="i1">[] 1. Yes. Skip to P-57<br />[] 2. No<br />[] 9. DK</div> <span class="em">25. Section F: Particulars regarding information and communication technology (ict)</span></p> <p>25.1. Introduction <br />The following questions on Information and Communication Technology (ICT) are to be asked to all members of the household age 3 years and above who may have owned, or used the ICTs at any one point, in the last 3 months before the census night (i.e. 24th May to 24th August, 2019). Take note that some of the questions under this section are technical and hence enumerators are requested to understand and only adhere to the definitions given here to avoid confusion. Enumerators are advised to probe further to get correct responses during data collection. <br />Columns P55--P58 to be asked to persons age 3 years and above. At this age, some children are introduced to school learning activities through different programmes such as the early childhood development (ECD) programme. It is, therefore, expected that some children may be using or owning a mobile phone (refer to the definition of mobile ownership below), using internet and computer/laptop/tablet) either at school, home or elsewhere.</p> <p>Columns P59 to be asked to persons aged 15 years and above. The question seeks to capture the uptake of e-commerce (only online purchases considered).</p> <p>25.2. Column P55: Mobile phone ownership <br />Ask, has [the respondent] owned a mobile phone in the last 3 months? If the response is yes then go to P57.</p> <p>Definition of mobile phone ownership: An individual owns a mobile phone if he/she has a mobile phone with at least one active SIM card for personal use regardless of how it was acquired in the last 3 months (24th May to 24th August, 2019). The intention of this question is to measure the actual penetration rate of mobile phone ownership in the country. Individuals who may not have owned a phone at any time between 24th May to 24th August, 2019 (the 3 months period) are excluded.</p> <p>Persons considered to own a mobile phone include the following:</p> <div class="i1">i. Individuals with mobile phone regardless how it was acquired, e.g. as a gift<br />ii. Individuals with mobile phone supplied by employers but used for personal use (to make personal calls, access personal information on internet via the phone, send text messages, etc.)<br />iii. Individuals with a mobile phone for personal use but the SIM card is not registered under her/his name. This includes individuals below 18 years and adults who may not be having the identification card at the time of acquiring the phone for some reasons, and opted to use someone else's ID.<br />iv. Individuals who have mobile phones but don't purchase the airtime and may be given airtime as gifts, benefits or free.</div><p>Persons not considered to own a mobile phone include:</p> <div class="i1">i. Individuals with only active registered or unregistered SIM card and have no mobile phone but borrow mobile devices from other people.<br />ii. Individuals who have been given mobile phones by their employers but cannot make any personal calls with these devices<br />iii. Individuals who use their parents/spouses phones any time they want, but do not own them</div><p>To be able to get correct responses, the enumerator should probe further to ensure that the respondent meets the criteria for owning a phone. Kenya 2019: Persons age 3+ [discrepancies: type I none; type II trace] This variable indicates whether the person owned a mobile phone in the last three months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Used a mobile phone in the last three months <span class="h2">F: Information regarding ICT</span></p> <p><span class="ital">To be asked of persons aged 3 years and above.</span> <br />[Questions 55-58 were asked of persons age 3 or more]</p> <p>P-56. Has [the respondent] used a mobile phone in the last 3 months?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">25. Section F: Particulars regarding information and communication technology (ict)</span></p> <p>25.1. Introduction <br />The following questions on Information and Communication Technology (ICT) are to be asked to all members of the household age 3 years and above who may have owned, or used the ICTs at any one point, in the last 3 months before the census night (i.e. 24th May to 24th August, 2019). Take note that some of the questions under this section are technical and hence enumerators are requested to understand and only adhere to the definitions given here to avoid confusion. Enumerators are advised to probe further to get correct responses during data collection. <br />Columns P55--P58 to be asked to persons age 3 years and above. At this age, some children are introduced to school learning activities through different programmes such as the early childhood development (ECD) programme. It is, therefore, expected that some children may be using or owning a mobile phone (refer to the definition of mobile ownership below), using internet and computer/laptop/tablet) either at school, home or elsewhere.</p> <p>Columns P59 to be asked to persons aged 15 years and above. The question seeks to capture the uptake of e-commerce (only online purchases considered).</p> <p>25.3. Column P56: Mobile phone use <br />Skip P56 if the response in P55 is yes. Otherwise,</p> <p>Ask, has [the respondent] used a mobile phone in the last 3 months? Those to be included are:</p> <div class="i1">- individuals who borrow a phone from friends, neighbors, relatives, spouses, parents, guardians, colleagues etc. to either make a phone call, text, send or withdraw money or use internet through the phone or modem;<br />- individuals who own a registered or unregistered SIM card but borrow a handset so that they can use any phone related services.<br />- young children (3 years and above) who may access the parent's or guardian's phone.</div> Kenya 2019: Persons age 3+ who did not own a mobile phone [discrepancies: type I none; type II trace] This variable indicates whether the person used a mobile phone in the last three months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Used the internet from any location in the last three months <span class="h2">F: Information regarding ICT</span></p> <p><span class="ital">To be asked of persons aged 3 years and above.</span> <br />[Questions 55-58 were asked of persons age 3 or more]</p> <p>P-57. Has [the respondent] used the internet from any location in the last 3 months?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">25. Section F: Particulars regarding information and communication technology (ict)</span></p> <p>25.1. Introduction <br />The following questions on Information and Communication Technology (ICT) are to be asked to all members of the household age 3 years and above who may have owned, or used the ICTs at any one point, in the last 3 months before the census night (i.e. 24th May to 24th August, 2019). Take note that some of the questions under this section are technical and hence enumerators are requested to understand and only adhere to the definitions given here to avoid confusion. Enumerators are advised to probe further to get correct responses during data collection. <br />Columns P55--P58 to be asked to persons age 3 years and above. At this age, some children are introduced to school learning activities through different programmes such as the early childhood development (ECD) programme. It is, therefore, expected that some children may be using or owning a mobile phone (refer to the definition of mobile ownership below), using internet and computer/laptop/tablet) either at school, home or elsewhere.</p> <p>Columns P59 to be asked to persons aged 15 years and above. The question seeks to capture the uptake of e-commerce (only online purchases considered).</p> <p>25.4. Column P57: Use of internet</p> <p>Ask, has [the respondent] used the internet from any location in the last 3 months?</p> <p>The internet is a world-wide public computer network. It provides access to a number of communication services including the world-wide web (www) and carries email, news, entertainment and data files irrespective of the device used. The use of internet can be personal or official/work purposes at any place, e.g. their own internet enabled phones, cyber café, home, office, school, areas with hot spots like restaurants, street, or any other location. Activities carried via internet include the following but not limited to:</p> <div class="i1">? Sending office email through yahoo, gmail, hotmail, office emails, etc.<br />? Personal purposes such as chatting with friends through Whatsapp, Facebook, Instagram, telegram, etc.<br />? Shopping for personal items online through Olx, Jumia, Amazon, etc.<br />? Entertainment purposes such as playing games online, watching movies online through Youtube, Netflix, Viusasa or other streaming sites<br />? Learning/educational purposes such as doing a course online, researching, reading articles online, etc.<br />? Business purposes such as downloading movies to sell<br />? Importing or exporting goods and services online<br />? Using internet applications such as uber, taxify, little cab, booking.com, etc. to order services</div><p>In order for the respondents to understand this question, the enumerators can ask whether they use Facebook, Whatsapp, sending email, Google, and other common activities carried out via internet. Kenya 2019: Persons age 3+ [discrepancies: type I none; type II trace] This variable indicates whether the person used the internet from any location in the last three months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Used a computer, laptop, or tablet from any location in the last three months <span class="h2">F: Information regarding ICT</span></p> <p><span class="ital">To be asked of persons aged 3 years and above.</span> <br />[Questions 55-58 were asked of persons age 3 or more]</p> <p>P-58. Has [the respondent] used a computer/Laptop/Tablet from any location in the last 3 months?</p> <div class="i1">[] 1. Yes<br />[] 2. No<br />[] 9. DK</div> <span class="em">25. Section F: Particulars regarding information and communication technology (ict)</span></p> <p>25.1. Introduction <br />The following questions on Information and Communication Technology (ICT) are to be asked to all members of the household age 3 years and above who may have owned, or used the ICTs at any one point, in the last 3 months before the census night (i.e. 24th May to 24th August, 2019). Take note that some of the questions under this section are technical and hence enumerators are requested to understand and only adhere to the definitions given here to avoid confusion. Enumerators are advised to probe further to get correct responses during data collection. <br />Columns P55--P58 to be asked to persons age 3 years and above. At this age, some children are introduced to school learning activities through different programmes such as the early childhood development (ECD) programme. It is, therefore, expected that some children may be using or owning a mobile phone (refer to the definition of mobile ownership below), using internet and computer/laptop/tablet) either at school, home or elsewhere.</p> <p>Columns P59 to be asked to persons aged 15 years and above. The question seeks to capture the uptake of e-commerce (only online purchases considered).</p> <p>25.5. Column P58: Use of desktop computer/ laptop/ tablet <br />Ask, has [the respondent] used a computer/ laptop/ tablet from any location in the last 3 months? <br />Desktop computer: This refers to a programmable electronic device that can store, retrieve and process data, as well as share information in a highly structured manner. This includes a desktop personal computer (PC), workstations and server.</p> <p>Laptop: A laptop, often referred to as a notebook, is a small portable and foldable computer. The laptop usually has an in-built screen, keyboard and touch pad/mouse.</p> <p>Tablet: A tablet is a portable computer typically with a mobile operating system and in-built touch screen. In most cases, the smallest screen size of a tablet is 7 inches. An iPad can be categorized as a tablet but iPhone, smart phones, smart TV set, etc. are not included. Kenya 2019: Persons age 3+ [discrepancies: type I none; type II trace] This variable indicates whether the person used a computer, laptop, or tablet from any location in the last three months. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Bought or ordered goods or services online in the last three months <span class="h2">F: Information regarding ICT</span></p> <p><span class="ital">To be asked of persons aged 15 years and above.</span> <br />[Question 59 was asked of persons age 15 or more]</p> <p>P-59. Has [the respondent] bought or ordered goods or services online in the last 3 months?</p> <div class="i1">[] 1. Searched and bought online<br />[] 2. Searched and bought elsewhere<br />[] 3. Searched only<br />[] 4. Never<br />[] 9. DK</div> <span class="em">25. Section F: Particulars regarding information and communication technology (ict)</span></p> <p>25.1. Introduction <br />The following questions on Information and Communication Technology (ICT) are to be asked to all members of the household age 3 years and above who may have owned, or used the ICTs at any one point, in the last 3 months before the census night (i.e. 24th May to 24th August, 2019). Take note that some of the questions under this section are technical and hence enumerators are requested to understand and only adhere to the definitions given here to avoid confusion. Enumerators are advised to probe further to get correct responses during data collection. <br />Columns P55--P58 to be asked to persons age 3 years and above. At this age, some children are introduced to school learning activities through different programmes such as the early childhood development (ECD) programme. It is, therefore, expected that some children may be using or owning a mobile phone (refer to the definition of mobile ownership below), using internet and computer/laptop/tablet) either at school, home or elsewhere.</p> <p>Columns P59 to be asked to persons aged 15 years and above. The question seeks to capture the uptake of e-commerce (only online purchases considered).</p> <p>25.6. Column P59: Ordering or purchasing goods through Internet</p> <p>Ask, has [the respondent] bought or ordered goods or services online in the last 3 months?</p> <p>The intent of this question is to measure the use of internet in buying or placing an order. This is regardless of mode of delivery and/or payment of goods/ services. In other words, paying goods via mobile money such as Mpesa, Airtel money etc; paying via credit card, debit card, online banking etc. is not considered here neither is how goods are delivered.</p> <p>The question captures only those respondents who at least placed an order or bought online within the last 3 months. The options are as follows:</p> <p>Only one option/answer should be selected:</p> <div class="i1">i. Searched and bought online: These are individuals who used internet to search, order or buy goods or services online. It includes individuals who used services such as OLX, Jumia, Kilimall, Amazon, Facebook, Instagram, Uber, Taxify (Bolt), Little cab, Masoko, etc. to order or buy goods or services. Ordering services such as hotel, airline/bus/rail etc bookings where individuals book for services and pay. Individuals who also purchase movies, games online qualify to be here. Individuals who pay/subscribe for long-term online services such as using certain softwares, subscribing to Netflix and other online streaming channels, etc. also qualify. For respondents to fall under this option, they must have completed the orders successfully, and purchased or paid for them.<br />ii. Searched and bought elsewhere: This is where an individual searched for goods and services online but did not purchase or order the product or service through the internet. This happens mostly when the individual is looking for information on a product or service such as prices, specification of a product, location, etc.<br />iii. Searched only: These are individuals who searched for products or services but never ordered or purchased them. It also includes individuals who ordered for the goods or services and cancelled at some point.<br />iv. Never: This is where an individual did not use the internet at all to search, order or buy any goods or services in the last 3 months.</div><p>The enumerator should probe further to get the right response. In case the respondent may have experienced options (i), (ii) or (iii), then tick as follows:</p> <div class="i1">a. Where option (i), (ii) or (iii) may apply, pick option (i).<br />b. Where option (ii) or (iii) may apply, pick option (ii).</div> Kenya 2019: Persons age 15+ [discrepancies: type I trace; type II none] This variable indicates whether the person bought or ordered goods or services online in the last three months. 1 Searched and bought online 2 Searched and bought elsewhere 3 Searched only 4 Never 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Occupation (1-digit) <span class="h2">E: Labor force participation</span></p> <p><span class="ital">For those who worked or held a job (including those on leave/sick leave.)</span> <br />[Questions 50-54 were asked of persons age 5 or more who worked or held a job, including those on leave/sick leave]</p> <p>P-53a. What specific work does [the respondent] usually do in the main job / business that he/she had during the last 7 days?</p> <div class="i1">Specific work _____</div> 24.7. Column P53 (a): Occupation in main job <br />Ask: What specific work does [the respondent] usually do within the main job / business that he/she had during the 7 days preceding the census night? (Enter the job title and briefly describe the main tasks) <br />Occupation is a major component of national labour market information and the data is important for policy formulation and evaluation for, labour market programmes, educational planning and work-related migration.</p> <p>Occupation refers to the type of work done by the person employed irrespective of where (the industry), or under what status in employment, it is being done. It is a "set of jobs whose main tasks and duties are characterized by a high degree of similarity" and should not be confused with the Economic activity/Industry or Status in Employment as described above. <br />This question seeks to establish the occupations of persons who worked or held a job in the reference period (last 7 days). A person will be associated with an occupation through the main job currently held.</p> <p>Examples: <br />- Security guard at a supermarket/shop <br />- Security guard at an airport <br />- Primary school teacher or teacher of primary school children <br />- Secondary school teacher <br />- Cashier in a bank <br />- Labourer in a construction site ("Mtu wa mkono") <br />- Accountant at a hotel <br />- Bus driver who drives passengers to the aircraft at an airport <br />- Subsistence farmer <br />- Farm hand on a farm <br />- Househelp in a private home Kenya 2019: Persons age 5+ who worked or had a job [discrepancies: type I none; type II trace] This variable indicates the person's occupation (1-digit). 00 Armed forces 01 Legislators, administrators and managers 02 Professionals 03 Technicians and associate professionals 04 Secretarial, clerical services and related workers 05 Service workers, shop and market sales workers 06 Skilled farm fishery wildlife and related workers 07 Craft and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 98 Unknown 99 NIU (not in universe) Work: Occupation Variables -- PERSON Occupation (2-digit) <span class="h2">E: Labor force participation</span></p> <p><span class="ital">For those who worked or held a job (including those on leave/sick leave.)</span> <br />[Questions 50-54 were asked of persons age 5 or more who worked or held a job, including those on leave/sick leave]</p> <p>P-53a. What specific work does [the respondent] usually do in the main job / business that he/she had during the last 7 days?</p> <div class="i1">Specific work _____</div> 24.7. Column P53 (a): Occupation in main job <br />Ask: What specific work does [the respondent] usually do within the main job / business that he/she had during the 7 days preceding the census night? (Enter the job title and briefly describe the main tasks) <br />Occupation is a major component of national labour market information and the data is important for policy formulation and evaluation for, labour market programmes, educational planning and work-related migration.</p> <p>Occupation refers to the type of work done by the person employed irrespective of where (the industry), or under what status in employment, it is being done. It is a "set of jobs whose main tasks and duties are characterized by a high degree of similarity" and should not be confused with the Economic activity/Industry or Status in Employment as described above. <br />This question seeks to establish the occupations of persons who worked or held a job in the reference period (last 7 days). A person will be associated with an occupation through the main job currently held.</p> <p>Examples: <br />- Security guard at a supermarket/shop <br />- Security guard at an airport <br />- Primary school teacher or teacher of primary school children <br />- Secondary school teacher <br />- Cashier in a bank <br />- Labourer in a construction site ("Mtu wa mkono") <br />- Accountant at a hotel <br />- Bus driver who drives passengers to the aircraft at an airport <br />- Subsistence farmer <br />- Farm hand on a farm <br />- Househelp in a private home Kenya 2019: Persons age 5+ who worked or had a job [discrepancies: type I none; type II trace] This variable indicates the person's occupation (2-digit). 01 Armed forces 11 Legislators and constitutional officials 12 Administrators and senior officials of special interest organizations 13 Corporate managers 14 Non-departmental managers 15 Other administrators and managers 21 Physical science professionals 22 Mathematicians statisticians and computing professionals 23 Engineering science professionals 24 Health and life science professionals 25 Teaching professionals 26 Legal professionals 27 Social science and related professionals 28 Business professionals 29 Other professionals 31 Engineering technicians 32 Medical and health science associate professionals 33 Physical and life science technicians 34 Ship and aircraft controllers 35 Business and social services associate professionals 36 Administration and middle level personnel 37 Primary and pre-primary education and other teachers 39 Other business social services athletics sports and related workers 41 Secretaries and office clerks 42 Client oriented clerks 51 Models shop assistants and demonstrators 52 Personal and protective service workers 53 House stewards caterers waiters and related workers 54 Travel attendants and guides 61 Farm workers (except fish) 62 Fishery and related workers 63 Subsistence agricultural and fishery workers 64 Forestry and related workers 65 Hunting and wildlife workers 71 Extraction and building trades workers 72 Metal machinery and related trades workers 73 Precision and handicraft workers 74 Printing and related trades workers 75 Food processing and related trades 76 Woodworking trades workers 77 Textile garment and related trades 78 Upholsterers pelt leather and shoemaking trades workers 81 Drilling and mining plant and mineral products machine operators 82 Metal processing plant operators and metal working machine operators 83 Wood processing plant and wood rubber and plastic machine operators 84 Chemical processing plant and chemical products machine operators 85 Power production plant operators 86 Food and related products machine operators 87 Assemblers 88 Drivers and mobile machinery operators 89 Other plant and machine operators and assemblers 91 Sales and services elementary occupations 92 Agricultural fishery and related labour(er)s 93 Labour(er)s in mining construction manufacturing and transport 98 Unknown 99 NIU (not in universe) Work: Occupation Variables -- PERSON Occupation (3-digit) <span class="h2">E: Labor force participation</span></p> <p><span class="ital">For those who worked or held a job (including those on leave/sick leave.)</span> <br />[Questions 50-54 were asked of persons age 5 or more who worked or held a job, including those on leave/sick leave]</p> <p>P-53a. What specific work does [the respondent] usually do in the main job / business that he/she had during the last 7 days?</p> <div class="i1">Specific work _____</div> 24.7. Column P53 (a): Occupation in main job <br />Ask: What specific work does [the respondent] usually do within the main job / business that he/she had during the 7 days preceding the census night? (Enter the job title and briefly describe the main tasks) <br />Occupation is a major component of national labour market information and the data is important for policy formulation and evaluation for, labour market programmes, educational planning and work-related migration.</p> <p>Occupation refers to the type of work done by the person employed irrespective of where (the industry), or under what status in employment, it is being done. It is a "set of jobs whose main tasks and duties are characterized by a high degree of similarity" and should not be confused with the Economic activity/Industry or Status in Employment as described above. <br />This question seeks to establish the occupations of persons who worked or held a job in the reference period (last 7 days). A person will be associated with an occupation through the main job currently held.</p> <p>Examples: <br />- Security guard at a supermarket/shop <br />- Security guard at an airport <br />- Primary school teacher or teacher of primary school children <br />- Secondary school teacher <br />- Cashier in a bank <br />- Labourer in a construction site ("Mtu wa mkono") <br />- Accountant at a hotel <br />- Bus driver who drives passengers to the aircraft at an airport <br />- Subsistence farmer <br />- Farm hand on a farm <br />- Househelp in a private home Kenya 2019: Persons age 5+ who worked or had a job [discrepancies: type I none; type II trace] This variable indicates the person's occupation (3-digit). 010 Armed forces 111 Legislative and constitutional officials 112 Local authority officials 121 Government administrators 122 Senior officials of special interest organizations 131 Directors and chief executives 132 Specialized departmental managers 133 Other departmental managers 141 Non-departmental managers 151 Other administrators and managers 211 Physicists and related professionals 212 Chemists 221 Mathematicians and related professionals 222 Statisticians 223 Computing professionals 231 Architects and town planners 232 Surveyors and cartographers 233 Civil engineers 234 Mechanical engineers 235 Chemical engineers and technologists 236 Mining engineers metallurgists and related technologists 237 Electrical electronics and telecommunications engineers 238 Production and related engineers 241 Health professionals 242 Nursing and mid-wifely professionals 243 Life science professionals 244 Agriculturalists and related professionals 251 University and post-secondary teachers or lecturers 252 Secondary and technical institute teachers and instructors 253 Special education teaching professionals 254 Education methods advisers and assessors 259 Other teaching professionals 261 Lawyers 262 Jurists or judges 271 Economists 272 Psychologists 273 Sociologists anthropologists and related professionals 274 Historians and political scientists 275 Philologists translators and interpreters 279 Other social science and related professionals 281 Accountants auditors and tax assessors 282 Personnel and occupational professionals 289 Other business professionals 291 Archivists librarians and related professionals 292 Religious professionals 293 Authors journalists and related professionals 294 Sculptors painters and related professionals 295 Composers musicians and singers 296 Choreographers 311 Technical draughts-men 312 Civil engineering and related technicians 313 Mechanical engineering and related technicians 314 Mining and metallurgical technicians 315 Electrical engineering technicians 316 Electronics and telecommunications engineering technicians 317 Chemical engineering technicians 318 Photographers image and sound recording equipment controllers 319 Broadcasting and telecommunications equipment controllers 321 Auxiliary nurses 322 Medical or clinical officers 323 Sanitarians 324 Optometrists and opticians 325 Dental technicians 326 Physiotherapists and related associate professionals 327 Veterinary officers 328 Pharmaceutical officers 329 Other associate medical nursing and nutrition workers 331 Physical science technicians 332 Life science technicians 333 Agronomy and forestry technicians 334 Farming advisors 341 Ships engineer or air traffic controller 342 Ships deck officers and pilots 343 Aircraft pilots and related workers 351 Securities and finance dealers 352 Insurance brokers and agents 353 Real estate agents 354 Business service agents 355 Buyers appraisers auctioneers 361 Police inspectors detectives customs and border officials 362 Government tax and excise officials 363 Welfare and pension officials 364 Government licensing officials 365 Business and public service middle level personnel 366 Statistical and planning officials 367 Fisheries wildlife and tourist officials 368 Lands agricultural and livestock officials 369 Other middle level personnel 371 Primary education teachers 372 Pre-primary education teachers 373 Other teachers and instructors 391 Non-ordained religion assistants 392 Social workers and helpers 393 Athletes sportsmen and related workers 394 Decorators and other commercial workers 395 Radio television and other announcers 396 Street nightclub and related musicians 397 Acrobats clowns magicians and related workers 398 Safety health and quality inspector or controllers; mechanical electrical building and fire inspectors 411 Secretaries stenographers and typists 412 Key board and office machine operators 413 Numerical clerks 414 Material recording and transport clerks 415 Library mail and related clerks 416 Coding proofreading and related clerks 417 General office clerks 421 Cashiers tellers and related clerks 422 Information and other client oriented clerks 511 Fashion and other model 512 Shop assistants and demonstrators 521 Hairdressers barbers beauticians and related workers 522 Undertakers and embalmers 523 Fortune tellers astrologers and related workers 524 Protective service workers 531 House stewards and housekeepers 532 Cooks and other catering service workers 533 Waiters bartenders 541 Ship and flight attendants and travel stewards 542 Transport conductors 543 Travel guides and ground attendants 611 Field crop vegetable and horticultural farm workers 612 Poultry dairy and livestock producers 613 Crop and animal producers 621 Fishery workers 631 Subsistence agricultural and fishery workers 641 Forestry and related workers 651 Hunting and wildlife workers 711 Mining blasting stone cutting and related workers 712 Building trades workers 721 Metal molders welders structural-metal preparers and related trades workers 722 Blacksmiths toolmakers and related trades workers 723 Machinery mechanics and fitters 724 Electrical equipment fitters and installers 725 Electrical equipment fitters and services 726 Electrical linesmen and cable jointers 727 Solar equipment fitters and installers 731 Precision workers in metal and related materials 732 Potters glassmakers and related trades workers 733 Handicraft workers 741 Compositors and type-setters 743 Printing engravers and etchers 749 Printing and related trades workers, not specified 751 Butchers fishmongers and related food preparers 752 Bakers pastry-cooks and confectionery makers 753 Dairy products makers 754 Fruit nut and related preservers 755 Brewers distiller and related workers 758 Other food processing and related workers 761 Wood treating cabinetmaking and related trades workers 762 Woodworking-machine setters and setter-operators 772 Weavers knitters and related workers; fibre preparers 773 Tailors dressmakers and related workers 781 Upholsters 782 Fell mongers tanners and pelt dressers 783 Shoe-making and related trades workers 811 Well drillers and borers 812 Mining plant operators 813 Stone clay cement and other mineral products machine operators 821 Metal smelting converting and refining furnace operators 822 Metal melters casters and rolling mill operators 824 Machine -tool and other metal-working machine operators 831 Wood processing and pulp plant operators 832 Wood products machine operators 833 Printing and bidding machine operator; paper products machine operators 835 Rubber and plastic products machine operators 846 Pharmaceutical and toiletry products machine operators 849 Other chemical processing plant operators 851 Power generating plant operators 852 Steam turbine boiler and engine operators 861 Meat and fishing processing machine operators 863 Grain and spice-milling machine operators 865 Fruit vegetable and nut processing machine 867 Tea coffee and cocoa processing machine operators 868 Brewers wine and other beverage machine operators 869 Food and related products machine operators, not specified 871 Mechanical machinery assemblers 879 Assemblers 881 Railway engine drivers and related workers 882 Motor vehicle drivers 883 Agricultural and materials _ handling machinery 884 Ships deck crews and related workers 891 Glass and ceramics kiln and related plant 892 Textile preparing spinning and winding machine operators 893 Weaving knitting and sewing machine operators 894 Textile bleaching dyeing and cleaning 899 Plant and machine operators and assemblers not elsewhere classified 911 Street vendors and related workers 912 Shoe cleaning and other street services elementary occupation 913 Cleaners launders and domestic workers 914 Building caretakers 915 Messengers porters watchmen and related workers 916 Other sales and service labour(er)s 921 Farm- hand and related labour(er)s 923 Fishery, hunting, trapping, and forestry labour(er) 931 Mining and quarrying labour(er)s 932 Construction and maintenance labour(er)s 933 Manufacturing labour(er)s 934 Transport labour(er)s and handlers 998 Unknown 999 NIU (not in universe) Work: Occupation Variables -- PERSON