2009 Kenya Population and Housing Census DDI_KEN_2009_PHC_v01_M_v7.6_A_IPUMS IPUMS

Integrated Public Use Microdata Series (IPUMS) International

 IPUMS April 1, 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. 2009 Kenya Population and Housing Census - IPUMS Subset PHC ke2009a (IPUMS Harmonized Subset) KEN_2009_PHC_v01_M_v7.6_A_IPUMS Kenya National Bureau of Statistics IPUMS (c) Copyright 2009, 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 Other Household Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Fertility and Mortality Variables -- PERSON Nativity and Birthplace Variables -- PERSON Utilities Variables -- HOUSEHOLD Technical Household Variables -- HOUSEHOLD Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Work 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 Utilities Variables -- HOUSEHOLD Demographic Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Dwelling Characteristics Variables -- HOUSEHOLD Education Variables -- PERSON Technical Person Variables -- PERSON Geography: F-N Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Nativity and Birthplace Variables -- PERSON Fertility and Mortality Variables -- PERSON Disability Variables -- PERSON Education Variables -- PERSON Work Variables -- PERSON Other Person Variables -- PERSON Person Imputation Flags Variables -- PERSON August 24-25, 2009 Kenya District Persons, households, and dwellings UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: - Households: yes - Individuals: yes - Group quarters: no UNIT DESCRIPTIONS: - Dwellings: No - Households: A person or a group of persons who live together in the same dwelling unit or homestead and eat together. They may or may not be related by blood or marriage. - Group quarters: Group quarters consist of schools/colleges, barracks, prisons, hospitals and other 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 2009 MICRODATA SOURCE: Kenya National Bureau of Statistics SAMPLE SIZE (person records): 3841935. 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 and in institutions such as schools, colleges, barracks, prisons, and hospitals. The long form includes both individual and housing characteristics. A greatly abbreviated form was used for persons in transit or who slept outdoors, in hotels or boarding houses. de facto, CENSUS DAY: August 24-25, 2009 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. 2009 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 ke2009a, 2025 KEN2009_PHC-H-H.dat Household records 895,230 ascii Minnesota Population Center Version 7.5, IPUMS sample KEN2009_PHC-P-H.dat Person records 3841935 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 2009 [Level 1, GIS] GEO1_KE2009 identifies the household's province or national capital within Kenya in 2009. Provinces or national capital are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_KE2009 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 2009 [Level 2, GIS] GEO2_KE2009 identifies the household's district within Kenya in 2009. Districts are the second level administrative units of the country, after provinces. A GIS map (in shapefile format), corresponding to GEO2_KE2009 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. 001001 Nairobi West 001002 Nairobi East 001003 Nairobi North 001004 Westlands 002001 Nyandarua North 002002 Nyandarua South 002003 Nyeri North 002004 Nyeri South 002005 Kirinyaga 002006 Muranga North 002007 Muranga South 002008 Kiambu (Kiambaa) 002009 Kikuyu 002010 Kiambu West 002011 Lari 002012 Githunguri 002013 Thika East 002014 Thika West 002015 Ruiru 002016 Gatanga 002017 Gatundu 003001 Mombasa 003002 Kilindini 003003 Kwale 003004 Kinango 003005 Msambweni 003006 Kilifi 003007 Kaloleni 003008 Malindi 003009 Tana River 003010 Tana Delta 003011 Lamu 003012 Taita 003013 Taveta 004001 Marsabit 004002 Chalbi 004003 Laisamis 004004 Moyale 004005 Isiolo 004006 Garba Tulla 004007 Imenti Central 004008 Imenti North 004009 Imenti south 004010 Meru south 004011 Maara 004012 Igembe 004013 Tigania 004014 Tharaka 004015 Embu 004016 Mbeere 004017 Kitui North 004018 Kitui South (Mutomo) 004019 Mwingi 004020 Kyuso 004021 Machakos 004022 Mwala 004023 Yatta 004024 Kangundo 004025 Makueni 004026 Mbooni 004027 Kibwezi 004028 Nzaui 005001 Garissa 005002 Lagdera 005003 Fafi 005004 Ijara 005005 Wajir South 005006 Wajir North 005007 Wajir East 005008 Wajir West 005009 Mandera Central 005010 Mandera East 005011 Mandera West 006001 Siaya 006002 Bondo 006003 Rarieda 006004 Kisumu East 006005 Kisumu West 006006 Nyando 006007 Homa Bay 006008 Suba 006009 Rachuonyo 006010 Migori 006011 Rongo 006012 Kuria West 006013 Kuria East 006014 Kisii Central 006015 Kisii South 006016 Masaba 006017 Gucha 006018 Gucha South 006019 Nyamira 006020 Manga 006021 Borabu 007001 Turkana Central 007002 Turkana North 007003 Turkana South 007004 West Pokot 007005 Pokot North 007006 Pokot Central 007007 Samburu Central 007008 Samburu East 007009 Samburu North 007010 Trans Nzoia West 007011 Trans Nzoia East 007012 Kwanza 007013 Baringo 007014 Baringo North 007015 East Pokot 007016 Koibatek 007017 Eldoret West 007018 Eldoret East 007019 Wareng 007020 Marakwet 007021 Keiyo 007022 Nandi North 007023 Nandi Central 007024 Nandi East 007025 Nandi South 007026 Tinderet 007027 Laikipia North 007028 Laikipia East 007029 Laikipia West 007030 Nakuru 007031 Nakuru North 007032 Naivasha 007033 Molo 007034 Narok North 007035 Narok South 007036 Trans Mara 007037 Kajiado Central 007038 Loitoktok 007039 Kericho 007040 Kipkelion 007041 Buret 007042 Sotik 007043 Bomet 007044 Kajiado North 008001 Kakamega Central 008002 Kakamega South 008003 Kakamega North 008004 Kakamega East 008005 Lugari 008006 Vihiga 008007 Emuhaya 008008 Hamisi 008009 Mumias 008010 Butere 008011 Bungoma South 008012 Bungoma North 008013 Bungoma East 008014 Bungoma West 008015 Mt. Elgon 008016 Busia 008017 Teso North 008018 Samia 008019 Bunyala 008020 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 Telephone availability PHONE indicates the availability of a telephone in the dwelling. 0 NIU (not in universe) 1 No 2 Yes 9 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 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 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 Number of deaths in household last year MORTNUM indicates the number of deaths in the household in the past year. 0 None 1 1 death 2 2 deaths 3 3 deaths 4 4 deaths 5 5 deaths 6 6 deaths 7 7 or more deaths 8 Unknown 9 NIU (not in universe) Other Household Variables -- HOUSEHOLD Any deaths in household last year ANYMORT indicates whether there were any deaths in the household in the past year. 1 Yes 2 No 8 Unknown/missing 9 NIU (not in universe) Other Household 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 2009: All records This variable indicates the dwelling number. This is a 6-digit numeric variable with 0 implied decimal places Technical Household Variables -- HOUSEHOLD Number of persons in household Kenya 2009: All records This variable indicates the number of persons in the 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 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 Household Variables -- HOUSEHOLD Dwelling created by splitting apart a large dwelling or household Kenya 2009: All records This variable indicates that 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 <svar v="KE09A021 KE09A022 KE09A023 KE09A024 KE09A025 KE09A026 KE09A027 KE09A028 KE09A029 KE09A030 KE09A031 KE09A032" a="all">Province _ _<br />District _ _<br />Division _ _<br />Sub-Location _ _<br />E.A. Number _ _<br />E.A. Type _<br />E.A. Status _<br />Household No. _ _ _<br />Household type _<br />Constituency _ _ _<br />Structure No.: S _ _ _ _<br />Ward _ _<br /></svar> Kenya 2009: All households This variable indicates the enumeration area type in which the household is located. 1 Rural 2 Urban 3 Peri-urban Geography: F-N Variables -- HOUSEHOLD Enumeration area status <svar v="KE09A021 KE09A022 KE09A023 KE09A024 KE09A025 KE09A026 KE09A027 KE09A028 KE09A029 KE09A030 KE09A031 KE09A032" a="all">Province _ _<br />District _ _<br />Division _ _<br />Sub-Location _ _<br />E.A. Number _ _<br />E.A. Type _<br />E.A. Status _<br />Household No. _ _ _<br />Household type _<br />Constituency _ _ _<br />Structure No.: S _ _ _ _<br />Ward _ _<br /></svar> Kenya 2009: All households This variable indicates a household's enumeration area status. 1 Formal 2 Informal Other Household Variables -- HOUSEHOLD Constituency where houshold is located <svar v="KE09A021 KE09A022 KE09A023 KE09A024 KE09A025 KE09A026 KE09A027 KE09A028 KE09A029 KE09A030 KE09A031 KE09A032" a="all">Province _ _<br />District _ _<br />Division _ _<br />Sub-Location _ _<br />E.A. Number _ _<br />E.A. Type _<br />E.A. Status _<br />Household No. _ _ _<br />Household type _<br />Constituency _ _ _<br />Structure No.: S _ _ _ _<br />Ward _ _<br /></svar> Kenya 2009: All households This variable indicates the constituency where the household is located. 001 Makadara 002 Kamukunji 003 Starehe 004 Lang'ata 005 Dagoretti 006 Westlands 007 Kasarani 008 Embakasi 009 Changamwe 010 Kisauni 011 Likoni 012 Mvita 013 Msambweni 014 Matuga 015 Kinango 016 Bahari 017 Kaloleni 018 Ganze 019 Malindi 020 Magarini 021 Garsen 022 Galole 023 Bura 024 Lamu East 025 Lamu West 026 Taveta 027 Wundanyi 028 Mwatate 029 Voi 030 Dujis 031 Lagdera 032 Fafi 033 Ijara 034 Wajir North 035 Wajir West 036 Wajir East 037 Wajir South 038 Mandera West 039 Mandera Central 040 Mandera East 041 Moyale 042 North Horr 043 Saku 044 Laisamis 045 Isiolo North 046 Isiolo South 047 Igembe 048 Ntonyiri 049 Tigania West 050 Tigania East 051 North Imenti 052 Central Imenti 053 South Imenti 054 Nithi 055 Tharaka 056 Manyatta 057 Runyenjes 058 Gachoka 059 Siakago 060 Mwingi North 061 Mwingi South 062 Kitui West 063 Kitui Central 064 Mutito 065 Kitui South 066 Masinga 067 Yatta 068 Kangundo 069 Kathiani 070 Machakos Town 071 Mwala 072 Mbooni 073 Kilome 074 Kaiti 075 Makueni 076 Kibwezi 077 Kinangop 078 Kipipiri 079 Ol kalou 080 Ndaragwa 081 Tetu 082 Kieni 083 Mathira 084 Othaya 085 Mukurwe-ini 086 Nyeri Town 087 Mwea 088 Gichugu 089 Ndia 090 Kerugoya/kutus 091 Kangema 092 Mathioya 093 Kiharu 094 Kigumo 095 Maragwa 096 Kandara 097 Gatanga 098 Gatundu South 099 Gatundu North 100 Juja 101 Githunguri 102 Kiambaa 103 Kabete 104 Limuru 105 Lari 106 Turkana North 107 Turkana Central 108 Turkana South 109 Kacheliba 110 Kapenguria 111 Sigor 112 Samburu West 113 Samburu East 114 Kwanza 115 Saboti 116 Cheranganyi 117 Eldoret North 118 Eldoret East 119 Eldoret South 120 Marakwet East 121 Marakwet West 122 Keiyo North 123 Keiyo South 124 Mosop 125 Aldai 126 Emgwen 127 Tinderet 128 Baringo East 129 Baringo North 130 Baringo Central 131 Mogotio 132 Eldama Ravine 133 Laikipia West 134 Laikipia East 135 Naivasha 136 Nakuru Town 137 Kuresoi 138 Molo 139 Rongai 140 Subukia 141 Kilgoris 142 Narok North 143 Narok South 144 Kajiado North 145 Kajiado Central 146 Kajiado Aouth 147 Bomet 148 Chepalungu 149 Sotik 150 Konoin 151 Buret 152 Belgut 153 Ainamoi 154 Kipkelion 155 Malava 156 Lugari 157 Mumias 158 Matungu 159 Lurambi 160 Shinyalu 161 Ikolomani 162 Butere 163 Khwisero 164 Emuhaya 165 Sabatia 166 Vihiga 167 Hamisi 168 Mt. Elgon 169 Kimilili 170 Webuye 171 Sirisia 172 Kandunyi 173 Bumula 174 Amagoro 175 Nambale 176 Butula 177 Funyula 178 Budalangi 179 Ugenya 180 Alego 181 Gem 182 Bondo 183 Rarieda 184 Kisumu Town East 185 Kisumu Town West 186 Kisumu Rural 187 Nyando 188 Muhoroni 189 Nyakachi 190 Kasipul Kabondo 191 Karachuonyo 192 Rangwe 193 Ndhiwa 194 Rongo 195 Migori 196 Uriri 197 Nyatike 198 Mbita 199 Gwasi 200 Kuria 201 Bonchari 202 South Mugirango 203 Bomachoge 204 Bobasi 205 Nyaribari Masaba 206 Nyaribari Chache 207 Kitutu Chache 208 Kitutu Masaba 209 West Mugirango 210 N. Mugirango Borabu Geography: F-N Variables -- HOUSEHOLD Household Type <svar v="KE09A021 KE09A022 KE09A023 KE09A024 KE09A025 KE09A026 KE09A027 KE09A028 KE09A029 KE09A030 KE09A031 KE09A032" a="all">Province _ _<br />District _ _<br />Division _ _<br />Sub-Location _ _<br />E.A. Number _ _<br />E.A. Type _<br />E.A. Status _<br />Household No. _ _ _<br />Household type _<br />Constituency _ _ _<br />Structure No.: S _ _ _ _<br />Ward _ _<br /></svar> <svar v="KE09A032" a="all"><span class="em">9.2 Household</span><br /><br />9.2.1 A household is a person or group of persons who reside in the same homestead/compound but not necessarily in the same dwelling unit, have same cooking arrangement, and are answerable to the same household head. <br />There are three important questions used to identify a household.<br /><div class="i1">a) Do the persons reside in the same compound? (i.e. the persons in the household may reside under same roof or several roofs in the same compound)<br />b) Are they answerable to the same head? (i.e. persons in a household are answerable to a person they recognize to have authority)<br />c) Do they have the same cooking arrangement? (i.e. members of a household cook together)</div><br />If the answer to each of the above criteria is "yes", then you have adequately identified a household. If the answer to one or more of these criteria is "no", then there are more than one household.<br /><br />There are two types of households: conventional and non-conventional households.<br /><br />9.2.2 <span class="em">Conventional households</span><br /><br /><div class="i1">- Usually consist of a person or a group of persons who live together 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. It is important to remember that members of a household are not necessarily related (by blood or marriage).<br />- Determination of households may not be easy. However, the following examples should guide you in deciding who should form a household.<br />- A household may consist of one or more persons and may occupy a whole building or part of a building or many buildings in the same compound/homestead.<br />- If two or more groups of persons live in the same dwelling unit and have separate cooking arrangements, treat them as separate households.<br />- A domestic worker who lives and eats with the household should be included in the household. If the domestic worker cooks and eats separately, he/she should be enumerated as a separate household.<br />- The particulars of persons who will have spent the Census night with another household should be recorded in the questionnaire for that particular household where they were that night i.e. visitors. For people attending ceremonies such as burials and weddings etc. from the neighborhood, they should be enumerated with their usual households, if not from the neighborhood, enumerate them with this household.<br />- In a polygamous marriage, if the wives are living in separate dwelling units and have separate cooking arrangement treat the wives as separate households. Each wife with other persons who live with her will therefore constitute a separate household. The husband will be listed in the household where he will have spent the Census night. If the wives cook together and live in the same compound, and are answerable to one head then treat them as one "household".<br />- It is the custom in many parts of Kenya for boys to live in separate quarters between circumcision and marriage, while continuing to take their meals with their parents. Enumerate them with their parent's households. For those who "borrow sleep" they should be enumerated with their usual households.<br />- For census purposes, you will list only those persons who will have spent the Census night (the Night of 24/25 August 2009) with the household, whether visitors, servants, etc.</div><br /><br />9.2.3 <span class="em">Unconventional households</span><br /><br /><div class="i1">- There are cases where certain rules used to decide what a household is do not apply. Here are some guidelines to help you:<br />- Sometimes groups of people live together but cannot be said to belong to an "ordinary" household. Examples are hospital in-patients, people in police cells, travelers, guests in hotels, or prison inmates and outdoor sleepers. These are "special" population groups and will be covered separately, using short questionnaires. Students in boarding schools and colleges, military barracks and GSU camps will be enumerated using the main questionnaire. The name of the institution will be written at the top of the questionnaire form. The District Census Committees (DCC) will make arrangements to have this population enumerated. Some of the institutional managers may also be called upon to help with the enumeration of these "special" population groups (or non-conventional households). Such persons shall all be enumerated strictly on the Census night.<br />- Vagrants/outdoor sleepers will be enumerated using the relevant short questionnaire. You will be required to record the place/street of enumeration and collect details about all the persons at the place of enumeration. The required information include: name, sex, age, home district/country, tribe/nationality, and education level. Arrangements will be made to have some members of the street families to accompany enumerators during the census. The DCC will make the necessary arrangements to have them enumerated and such persons shall all be enumerated strictly on the Census night.<br />- A short questionnaire specific for the population in hotels/lodges and boarding houses, police cells, prison and hospital will also be issued. On the evening of the Census night, hotel managers, heads of hospitals, police stations and prisons, with the assistance of the supervisors and /or enumerators, will ensure that all persons who will spend the Census night in these institutions are enumerated. The DCC will make the necessary arrangements and such persons shall all be enumerated strictly on the Census night. Information to be collected include: name, sex, age, duration of stay, education level, home district/country, tribe/nationality. Duration of stay should be in months if less than one year. For example, people who have been in prison for 6 months should be recorded as '6' under the column for months and "0" under the column for years. Those who have stayed for over a year, say 2 years 5 months should be recorded as '5' in the column for months and '2' in the column for years.<br />- Persons working in institutions such as those listed above but who live in their own households should be enumerated with their own household members and not with the institution. Thus, a nurse on night duty should be enumerated with her household and not with patients at the hospital. Similarly, a teacher should be enumerated with his/her household and not with students or boarders at the school or training institution. The same applies to night workers of all kind such as watchmen, factory workers, policemen etc. Probe to establish whether this group of workers has households where they usually reside. If they don't, enumerate them as outdoor sleepers.<br />- All persons who will be on transit or travelling on the Census night by road, rail, water or air will be enumerated at the place of boarding or disembarkment. You will be issued with short questionnaires for the purpose of enumerating such people. You will also be supplied with Enumeration Cards to issue to such persons once you count them. Inform them that they are to keep the cards until the census is over to avoid being counted twice. The information required from such people include: name, sex, age, home district/country, and tribe/nationality. Do not spend a lot of time trying to establish the age of such respondents. A rough estimate will do. The DCC or the Divisional census committee will make the necessary arrangements to have them enumerated and such persons shall all be counted strictly on the Census night.</div><br /></svar> Kenya 2009: All households This variable indicates the household type. 1 Conventional 2 Unconventional 3 Refugee camp Other Household Variables -- HOUSEHOLD County Kenya 2009: All households This variable indicates the county in which the household is located. 101 Nairobi 201 Nyandarua 202 Nyeri 203 Kirinyaga 204 Murang'a 205 Kiambu 301 Mombasa 302 Kwale 303 Kilifi 304 Tanariver 305 Lamu 306 Taitataveta 401 Marsabit 402 Isiolo 403 Meru 404 Tharaka 405 Embu 406 Kitui 407 Machakos 408 Makueni 501 Garissa 502 Wajir 503 Mandera 601 Siaya 602 Kisumu 604 Homabay 603 Migori 605 Kisii 606 Nyamira 701 Turkana 702 Westpokot 703 Samburu 704 Transnzoia 705 Baringo 706 Uasingishu 707 Elgeyo-marakwet 708 Nandi 709 Laikipia 710 Nakuru 711 Narok 712 Kajiado 713 Kericho 714 Bomet 801 Kakamega 802 Vihiga 803 Bungoma 804 Busia Geography: F-N Variables -- HOUSEHOLD Number of births last 12 months <svar v="KE09A036" a="all"><span class="h3">G: Annual live births</span><br /><br />[Questions H-10 and H-11 were asked of all households.]<br /><br />H-10. How many live births occurred in this household between 24/08/2008 and 24/08/2009 (last 12 months)? _ _<br /></svar> <svar v="KE09A036">- <span class="em">Section G: Annual live births: </span> This section covers column H10 and seeks information on all the live births that occurred within the household between 24/8/2008 and 24/8/2009 (last 12 months).<br /></svar></p> <p><svar v="KE09A036" a="all"><span class="h3">36. Section G: Annual live births</span><br /><br />This section is about all births that occurred in the household in the last 12 months.<br /><span class="em">Ask</span>: How many live births have occurred in this household between 24/8/2008 and 24/8/2009. Record the responses in column H10. Births will be captured in the households where they occurred i.e. if a woman gave birth to child while still staying with her parents but has since moved from the household; the birth should be captured in the parent's household and not where she has moved to. Regardless of where the birth occurred (bush or hospital), it should be captured in the household where the woman was staying at the time of birth. Women who gave birth while visiting, the births should be recorded with the household they were visiting.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the number of live births in the household in the last 12 months. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 99 NIU (not in universe) Other Household Variables -- HOUSEHOLD Number of deaths last 12 months <svar v="KE09A037" a="all">H-11. How many deaths occurred in this household between 24/08/2008 and 24/08/2009 (last 12 months)? _ _ <br /><div class="i1">If '0' skip to H-17.</div><br /></svar> <svar v="KE09A037">- <span class="em">Section H</span>: Recent deaths in the household. This section covers columns H11 to H16. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><span class="h3">37. Section H: Recent deaths in the household</span></p> <p><span class="em">37.1 Introduction</span><div class="i1">- <span class="em">Purpose of the section</span>: This section seeks to capture information on recent deaths in the household. The duration being considered is the <span class="em">last 12 months </span>prior to the census reference night or the period between 24/8/2008 and 24/8/2009. The information collected will be crucial in the direct determination of current mortality levels in the country. Much of the section is devoted to questions relating to maternal deaths at household level. This is a key indicator in a nation's development status and has been emphasized by the UN, as one of the Millennium Development Goals (MDGs) i.e. on improvement of maternal health.<br />- <span class="em">Respondent: </span>The questions in this section (<span class="em">H11?H16</span>) should be answered by the household head or any other responsible household member. If the answer to question <span class="em">H11 </span>is 00, then move to the next section (i.e. information regarding livestock). 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 transferred directly from another district to a health facility in another district, that death should be captured in the household in the district of residence.</div><span class="em">Note: </span>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 <span class="em">'still birth' </span>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.</p> <p><span class="em">37.2 Column H11: Death of HH member</span></p> <p><span class="em">Ask the respondent: </span>"How many deaths occurred in this household between 24/8/2008 and 24/8/2009?" If there are deaths record the number, if none record "0"and skip to Section I. Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the number of deaths in the household in the last 12 months. 00 No deaths in the last 12 months 01 1 02 2 03 3 04 4 05 5+ 99 NIU (not in universe) Other Household Variables -- HOUSEHOLD Number of exotic cattle owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of exotic cattle owned by the household. 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+ Household Economic Variables -- HOUSEHOLD Number of indigenous cattle owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of indigenous cattle owned by the household. This is a 3-digit numeric variable with 0 implied decimal places Household Economic Variables -- HOUSEHOLD Number of sheep owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of sheep owned by the household. This is a 3-digit numeric variable with 0 implied decimal places Household Economic Variables -- HOUSEHOLD Number of goats owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of goats owned by the household. This is a 3-digit numeric variable with 0 implied decimal places Household Economic Variables -- HOUSEHOLD Number of camels owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of camels owned by the household. This is a 3-digit numeric variable with 0 implied decimal places Household Economic Variables -- HOUSEHOLD Number of donkeys owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of donkeys owned by the household. This is a 2-digit numeric variable with 0 implied decimal places Household Economic Variables -- HOUSEHOLD Number of pigs owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of pigs owned by the household. This is a 2-digit numeric variable with 0 implied decimal places Household Economic Variables -- HOUSEHOLD Number of indigenous chickens owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of indigenous chickens owned by the household. This is a 3-digit numeric variable with 0 implied decimal places Household Economic Variables -- HOUSEHOLD Number of commercial chickens owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of commercial chickens owned by the household. This is a 3-digit numeric variable with 0 implied decimal places Household Economic Variables -- HOUSEHOLD Number of bee hives owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of bee hives owned by the household. This is a 3-digit numeric variable with 0 implied decimal places Household Economic Variables -- HOUSEHOLD Number of other animals owned by the household <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all"><span class="h3">I: Information regarding livestock</span><br /> [Questions H-17 to H-29 were asked of all households.]<br /><br />H-17. How many of each of the following livestock are currently owned by this household?<br /><div class="i1">_ _ _ _ _ 1. Exotic cattle<br />_ _ _ _ _ 2. Indigenous cattle<br />_ _ _ _ _ 3. Sheep<br />_ _ _ _ _ 4. Goat<br />_ _ _ _ _ 5. Camels<br />_ _ _ _ _ 6. Donkeys<br />_ _ _ _ _ 7. Pigs<br />_ _ _ _ _ 8. Indigenous chicken<br />_ _ _ _ _ 9. Chicken commercial<br />_ _ _ _ _ 10. Bee hives<br />_ _ _ _ _ 11. Other</div><br /></svar> <svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048">- <span class="em">Section I</span>: Information regarding livestock: The section covers column H17 and captures data on types and number of livestock kept by the household members. The questions in this section should be posed to the head of the household or any other responsible member of the household.<br /></svar></p> <p><svar v="KE09A038 KE09A039 KE09A040 KE09A041 KE09A042 KE09A043 KE09A044 KE09A045 KE09A046 KE09A047 KE09A048" a="all">[Question 38 is asked of all persons.]<br /><br /><span class="em">38.1 Column H17: Type of livestock</span><br /><br />Establish the type and number of each type of livestock kept or managed by any member of the household. The animals listed should be within the district. Some institutions such as schools keep or rear livestock. For institutions which own livestock and where the special population is absent during enumeration, complete the identification details, write the name of the institution on top margin of the questionnaire and complete the livestock section only. <span class="em">The code "other" should be replaced with fish ponds.</span><br /></svar> Kenya 2009: All households This variable indicates the number of other animals owned by the household. 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+ Household Economic Variables -- HOUSEHOLD Number of dwelling units occupied by the household <svar v="KE09A049" a="all"><span class="em">Dwelling units</span><br />H-18. How many dwelling units does this household occupy? _ _<br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A049" a="all"><span class="em">39.1 Column H18: Dwelling units</span><br /><br /><div class="i1">- For purposes of this census, a dwelling unit is a structure which a household uses for sleeping, eating, entertaining guests, etc. A dwelling unit may be a whole structure or part of a structure, especially in the urban setting.<br />- Record the number of dwelling units available to a household in column H18.<br />- There are situations, especially in the rural areas, whereby the kitchen is a stand-alone structure. Such a kitchen must be counted as a dwelling unit in its own right.</div><br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the number of dwelling units occupied by the 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+ 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Number of habitable rooms in the dwelling <svar v="KE09A050" a="all"><span class="em">Habitable</span><br />H-19. How many habitable rooms do these units contain? _ _<br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A050" a="all"><span class="em">39.2 Column H19: Habitable rooms</span><br /><br /><div class="i1">- Record the number of habitable rooms available in all the dwelling units that belong to a household in column H19.<br />- Habitable rooms are rooms in the dwelling units 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 with the habitable rooms. The same applies to a store.</div><br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the number of habitable rooms in the dwelling occupied by the 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+ 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Tenure status <svar v="KE09A051" a="all"><span class="em">Tenure status of main dwelling unit</span><br />H-20. If owner occupied, state whether<br /><div class="i1">[] 1 Purchased<br />[] 2 Constructed<br />[] 3 Inherited</div><br /><br />If rented/provided, state whether<br /><div class="i1">[] 4 Government<br />[] 5 Local authority<br />[] 6 Parastatal<br />[] 7 Private company<br />[] 8 Individual<br />[] 9 Faith based organization/NGO<br />[] 10 Other form</div><br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A051" a="all"><span class="em">39.3 Column H20: Tenure status of main dwelling unit</span><br /><br />Column H20 seeks information on status of tenure i.e. whether the dwelling unit is owner occupied or rented by the household. 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 code the answers using the categories provided.<br /><div class="i1">- Owner occupied<br />Under owner occupied are listed:</div><br /><div class="i2">- 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><br /><div class="i1">- Rented/provided/donated<br />Under rented/provided are listed dwelling units either provided by the employer of a member of the household, rented by a member of the household or donated to a member of the household. This includes:</div><br /><div class="i2">- Government: Covers all houses rented or provided by the Government of Kenya<br />- Local Authority: Covers all houses rented or provided by local authorities<br />- Parastatal: Covers organizations like Kenya Railways, Kenya Power and Lighting Co., universities, KNBS, etc.<br />- Private Company: Covers private firms and foreign governments<br />- Individual: Covers private individuals only.<br />- Other forms of tenure: any other form of tenure not covered above.</div><br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the tenure status of the main dwelling unit. 01 Purchased 02 Constructed 03 Inherited 04 Provided by the government 05 Provided by the local authority 06 Parastatal 07 Provided by a private company 08 Individual 09 Provided by a faith-based organization/NGO 10 Other form of tenure 99 NIU (not in universe) Household Economic Variables -- HOUSEHOLD Main roof materials <svar v="KE09A052" a="all"><span class="em">Dominant construction material of main dwelling unit</span><br />H-21. Roof<br /><div class="i1">[] 1 Corrugated iron sheets<br />[] 2 Tiles<br />[] 3 Concrete<br />[] 4 Asbestos sheets<br />[] 5 Grass <br />[] 6 <span class="lang">Makuti</span><br />[] 7 Tin<br />[] 8 Mud/dung<br />[] 9 Other (specify)</div><br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A052" a="all"><span class="em">39.4 Columns H21: Dominant construction material of roof for main dwelling unit</span><br /><br />Code in column H21 the construction materials used to build the roof e.g. code "1" for roof with corrugated iron sheets, "4" for asbestos sheets, etc. Tiles include clay, wooden, fiber and cement tiles, etc.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the dominant construction material of the dwelling's roof. 01 Corrugated iron sheets 02 Tiles 03 Concrete 04 Asbestos sheets 05 Grass 06 Makuti 07 Tin 08 Mud/dung 09 Other 98 Unknown 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Main wall materials <svar v="KE09A053" a="all">H-22. Wall<br /><div class="i1">[] 1 Stone<br />[] 2 Brick/block<br />[] 3 Mud/wood<br />[] 4 Mud/cement<br />[] 5 Wood only<br />[] 6 Corrugated iron sheets<br />[] 7 Grass/reeds<br />[] 8 Tin<br />[] 9 Other (specify)</div><br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A053" a="all"><span class="em">39.5 Columns H22: Dominant construction material of walls for main dwelling unit</span><br /><br />Code in column H22 the construction materials used to build the walls e.g. code "3" for mud/wood etc. <span class="em">Consider the main material that bears the weight of the roof</span>. Code "9" for mud/dung.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the dominant construction material of the dwelling's walls. 01 Stone 02 Brick/block 03 Mud/wood 04 Mud/cement 05 Wood only 06 Corrugated iron sheets 07 Grass/reeds 08 Tin 09 Other 98 Unknown 99 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Main floor materials <svar v="KE09A054" a="all">H-23. Floor<br /><div class="i1">[] 1 Cement<br />[] 2 Tiles<br />[] 3 Wood<br />[] 4 Earth<br />[] 5 Other (specify)</div><br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A054" a="all"><span class="em">39.6 Columns H23: Dominant construction material of floor for main dwelling unit</span><br /><br />Code in column H23 the construction material used to build the floor e.g. code "1" for cement, "2" for tiles, "3" for wood, "4" for earth and "5" for other. Tiles include wooden tiles. Wood means wooden planks.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the dominant construction material of the dwelling's floor. 1 Cement 2 Tiles 3 Wood 4 Earth 5 Other 8 Unknown 9 NIU (not in universe) Dwelling Characteristics Variables -- HOUSEHOLD Main source of water <svar v="KE09A055" a="all">H-24. Main source of water<br /><div class="i1">[] 1 Pond<br />[] 2 Dam<br />[] 3 Lake<br />[] 4 Stream/river<br />[] 5 Protected spring water<br />[] 6 Unprotected spring<br />[] 7 Protected well<br />[] 8 Unprotected well<br />[] 9 Borehole<br />[] 10 Piped into dwelling<br />[] 11 Piped<br />[] 12 <span class="lang">Jabia</span><br />[] 13 Rain/harvested<br />[] 14 Water vendor<br />[] 15 Other (specify)</div><br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A055" a="all"><span class="em">39.7 Column H24: Main source of water</span><br /><br />In column H24, ask "what is the main source of water for this household?" You are required to code the main source of water. This is the source from which, for most part of the year, the household draws its water. For example, if during the wet season the household draws water from a tank but then the longer part of the year draws from a river, code "4" as main source of water.<br /><br />The main sources of water listed are:<br /><div class="i1">- <span class="em">Pond</span>: A small area of still water. Usually this water collects after rain or through an underground drainage.<br />- <span class="em">Dam</span>: A reservoir formed by building a barrier across a river to hold back water and control its flow. A lot of these dams are built in dry areas of Kenya.<br />- <span class="em">Lake</span>: Usually bigger than a pond but has water collecting in it through rain, rivers etc. It is different from a dam in that it is not man-made.<br />- <span class="em">Stream/river</span>: This is a naturally flowing source of water.<br />- <span class="em">Spring</span>: This is a place where water springs or wells up from earth or underground.<br />- <span class="em">Well</span>: This is a manmade shaft dug in the ground from which water is obtained. Water is drawn using buckets.<br />- <span class="em">Borehole</span>: Same as the well as defined above but deeper than a well and has pump for drawing the water into a tank, buckets etc.<br />- <span class="em">Piped</span>: Means water drawn through pipes installed in a dwelling unit and originating in a central (public) source.<br />- <span class="em">Jabias/Tanks</span>: Rainwater harnessed from any catchment into a hole/tank and used for domestic purposes.<br />- <span class="em">Vendor</span>: Refers to water purchased by households from mobile sellers or distributors. Examples of ferrying include cart, bicycle, individuals, truck etc. The source of the water may <span class="em">be known or not</span>, by the households.<br />- <span class="em">Other</span>: Any source that is not mentioned above</div><br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the main source of water for the household. 01 Pond 02 Dam 03 Lake 04 Stream/river 05 Protected spring 06 Unprotected spring 07 Protected well 08 Unprotected well 09 Borehole 10 Piped into dwelling 11 Piped 12 Jabia 13 Rain/harvested 14 Water vendor 15 Other 99 NIU (not in universe) Utilities Variables -- HOUSEHOLD Main type of human waste disposal <svar v="KE09A056" a="all">H-25. Main type of human waste disposal. <br /><div class="i1">[] 1 Main sewer<br />[] 2 Septic tank<br />[] 3 Cess pool<br />[] 4 VIP pit latrine<br />[] 5 Pit latrine covered<br />[] 6 Pit latrine uncovered<br />[] 7 Bucket latrine<br />[] 8 Bush<br />[] 9 Other (specify)</div><br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A056" a="all"><span class="em">39.8 Column H25: Main mode of human waste disposal</span><br /><br />In column H25 <span class="em">ask</span>, "where do members of this household dispose of human waste?" Code the answers according to the categories given e.g. code 4 for ventilated improved pit latrine (VIP), 3 for cesspool etc.<br />The categories of main type of sewage disposal are:<br /><div class="i1">- <span class="em">Main sewer</span>: 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 centers like Nairobi, Mombasa, etc.<br />- <span class="em">Septic tank</span>: This is a tank into which an individual 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 />- <span class="em">Bucket latrine</span>: 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 />- <span class="em">Cesspool</span>: This is a communal pool where liquid waste is drained into from the dwelling units until it is emptied.</div><br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates where the household disposes of waste. 01 Main sewer 02 Septic tank 03 Cesspool 04 VIP pit latrine 05 Pit latrine covered 06 Pit latrine uncovered 07 Bucket latrine 08 Bush 09 Other 99 NIU (not in universe) Utilities Variables -- HOUSEHOLD Cooking fuel <svar v="KE09A057" a="all">H-26. Main type of cooking fuel.<br /><div class="i1">[] 1 Electricity<br />[] 2 Paraffin<br />[] 3 LPG<br />[] 4 Biogas<br />[] 5 Firewood<br />[] 6 Charcoal<br />[] 7 Solar<br />[] 8 Other (specify)</div><br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A057" a="all"><span class="em">39.9 Column H26: Main type of cooking fuel</span><br /><br /><span class="em">Ask</span>: "What is the main cooking fuel used in this household?" In column H26, 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. Code the appropriate answer in column H26 from the provided code list.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the type of cooking fuel used by the household. 1 Electricity 2 Paraffin 3 LPG 4 Biogas 5 Firewood 6 Charcoal 7 Solar 8 Other 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Lighting fuel <svar v="KE09A058" a="all">H-27. Main type of lighting fuel.<br /><div class="i1">[] 1 Electricity<br />[] 2 Pressure lamp<br />[] 3 Lantern<br />[] 4 Tin lamp<br />[] 5 Gas lamp<br />[] 6 Fuel wood<br />[] 7 Solar<br />[] 8 Other (specify)</div><br /></svar> <svar v="KE09A049 KE09A050 KE09A051 KE09A052 KE09A053 KE09A054 KE09A055 KE09A056 KE09A057 KE09A058">- <span class="em">Section J</span>: Housing conditions and amenities. This section covers columns H18 to H27 on housing conditions and amenities. These questions are to be posed to the Head of the Household or any other responsible person.<br /></svar></p> <p><svar v="KE09A058" a="all"><span class="em">39.10 Column H27: Main type of lighting fuel</span><br /><br />In column H27, code the answer according to the categories given. Tin lamps include plastic or bottle lamps, which may be known by various local names like koroboi, tamambul, tadoba, nyangile, ngwatira etc.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the type of lighting fuel used by the household. 1 Electricity 2 Pressure lamp 3 Lantern 4 Tin lamp 5 Gas lamp 6 Fuel wood 7 Solar 8 Other 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Radio <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A059"><div class="i1">1. Radio</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a radio. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Television <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A060"><div class="i1">2. TV</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a television. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Mobile phone <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A061"><div class="i1">3. Mobile phone</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a mobile phone. 1 Yes 2 No 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Landline telephone <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A062"><div class="i1">4. Landline telephone</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a landline telephone. 1 Yes 2 No 9 NIU (not in universe) Utilities Variables -- HOUSEHOLD Computer <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A063"><div class="i1">5. Computer</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a computer. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Bicycle <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A064"><div class="i1">6. Bicycle</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a bicycle. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Motorcycle <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A065"><div class="i1">7. Motorcycle</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a motorcycle. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Car <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A066"><div class="i1">8. Car</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a car. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Truck/Lorry/Tractor/Bus <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A067"><div class="i1">9. Truck/lorry/tractor/bus</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a truck/lorry/tractor/bus. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Refrigerator <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A068"><div class="i1">10. Refrigerator</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a refrigerator. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Boat <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A069"><div class="i1">11. Boat</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a boat. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Animal drawn cart <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A070"><div class="i1">12. Animal drawn cart</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns an animal drawn cart. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Canoes <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A071"><div class="i1">13. Canoes</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a canoe. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Tuk tuk <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="h3">K: Ownership of household assets</span><br />H-28. Did the household own any of the following items?<br /></svar></p> <p><svar v="KE09A072"><div class="i1">14. <span class="lang">Tuk tuk </span>[type of motorized rickshaw]</div><br /><div class="i2">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A066 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072">- <span class="em">Section K</span>: Ownership of household assets: This section covers column H28 and seeks information on the ownership of common assets such as radio, television, mobile phone etc. This question is applicable to all households.<br /></svar></p> <p><span class="h3">40. Section K: Household assets</span></p> <p><svar v="KE09A059 KE09A060 KE09A061 KE09A062 KE09A063 KE09A064 KE09A065 KE09A067 KE09A068 KE09A069 KE09A070 KE09A071 KE09A072" a="all"><span class="em">40.1 Column H28: Ownership of household assets</span><br /><br />Establish if any member of the household owns any of the following items and code accordingly. Household assets: Radio, TV, Mobile phone, Landline telephone, computer, bicycle, motor cycle, bus, lorry, truck, tractor, refrigerator, boat, canoe, animal drawn cart, <span class="lang">tuk tuk</span>.<br /></svar> Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates whether the household owns a tuk tuk. 1 Yes 2 No 9 NIU (not in universe) Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Number of emigrants since 1995 <svar v="KE09A073" a="all"><span class="h3">L: Emigrants</span><br /><span class="em">Emigrants in the last 15 years (since 1995)</span><br /><br />H-29. How many members of this household have migrated to another country since 1995? _ _<br /><div class="i1">If none write "0" and end the interview.<br />If not "0" fill the Emigrant Short Questionnaire.</div><br /></svar> <svar v="KE09A073">- <span class="em">Section L: Emigrants</span>: This section covers column H29 and seeks information on any member of the household who may have migrated to another country since 1995. Details of emigrants will be captured using the emigrant short questionnaire.<br /></svar></p> <p><span class="h3">41. Section L: Emigrants</span></p> <p>Column H29 seeks information on any member of the household who may have migrated to another country since 1995. If there is any emigrant, detailed information should be captured in the emigrant short questionnaire. Kenya 2009: Conventional households or refugee camps [discrepancies: none] This variable indicates the number household members that migrated to another country in the last 15 years. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) Other Household Variables -- HOUSEHOLD Strata Kenya 2009: All households This variable is the strata identifier for the sample. Strata is a constructed variable that captures implicit geographic stratification resulting from the sample design. It is created by assigning a unique identifier to groups of between 10 and 19 adjacent households. Additional documentation is available on the Variance Estimation page. This is a 5-digit numeric variable with 0 implied decimal places Geography: F-N 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 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 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 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 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 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 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 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 Usual hours worked per week, categorized HRSUSUAL2 indicates the usual number of hours the respondent worked per week at all jobs or in their main job, categorized into intervals. 0 None 1 1 to 14 hours (except ca1971) 2 15 to 29 hours (except de1970, ca1971) 3 30 to 39 hours (except de1970) 4 40-48 hours (except il1972-1995, ca1971, pt1991-2011) 5 49 hours or more (except il1972 and ca1971) 7 Inconsistent or irregular work schedule 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 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 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 Person number (within household) Kenya 2009: 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 head of household <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A401" a="all"><span class="em">Relationship</span><br />P-10. What is [the person's] relationship to the head of this household?<br /><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 Unknown</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A401 KE09A402" a="all"><span class="em">25.3 Columns P10 and P11: Relationship and sex</span><br /></svar></p> <p><svar v="KE09A401">- After you have written all-the names in column P00, code relationship in column P10 and sex in column P11. For example: for head, code "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, that is "2" for <span class="em">spouse</span> (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, "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" relationship.<br />- You must probe to find out whether the children you have coded as sons and daughters are the head's biological children. If they are not, establish further whether they should fall under "10" (other-relative) or "11" (non-relative). Note that relatives like stepson or stepdaughter, parent-in- law, son or daughter-in-law, adopted son or daughter will be treated as "other relative" and will fall under category "10".<br />- There are several persons who may not be related by blood or marriage but constitutes a household, mostly in urban areas. Without telling them code one of them as 'head' (code "1 ") and the rest as 'non-relative' (code "11").<br />- Sometimes it may happen that members of the household are away and cannot be reached even after several visits, and the most responsible person you meet is a house-help or any other such person employed by the household. You must probe to establish the most senior member who will have spent the <span class="em">Census Night</span> in the household. This person must be made the household head. You may then proceed to ask the house help to provide information on the household members.<br />- There are certain communities where women are culturally allowed to "marry" other women. For purposes of the census, marriage should involve only partners of opposite sex. Whenever you encounter such cases where one woman (supposedly the head of the household) claims that another woman is her "spouse", code "10" (other-relative) rather than "2" (spouse) in P10.<br />- 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 01 (head). Ensure that the entry is strictly and legibly written within the boxes provided.<br /></svar> Kenya 2009: Persons in conventional households or refugee camps [discrepancies: none] This variable indicates the person's relationship to the head of the household. The enumeration form includes an "in-law" category. The enumeration instructions provide no information on which relationship codes to include in the in-law category, but state that children-in-law and parents-in-law should be included with other relatives. 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 Grandparent 10 Other relative 11 Unrelated 99 NIU (not in universe) Demographic Variables -- PERSON Sex <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A402" a="all"><span class="em">Sex</span><br />P-11. What is [the person's] sex?<br /><div class="i1">[] 1 Male<br />[] 2 Female</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A401 KE09A402" a="all"><span class="em">25.3 Columns P10 and P11: Relationship and sex</span><br /></svar></p> <p><svar v="KE09A402">- 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. <span class="em">You should ensure that everybody's sex is recorded.</span><br /></svar> Kenya 2009: All persons This variable indicates the person's sex. 1 Male 2 Female Demographic Variables -- PERSON Age in years <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A403" a="all"><span class="em">Age</span><br />P-12. How old is [person]? _ _<br /><div class="i1">Record age in completed years using two digits. If under 1 year, record "0". If 95 years and above code 95.</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A403" a="all"><span class="em">25.4 Column P12: Age</span><br /><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.<br /><br /><div class="i1">- How old is '[the respondent]'?<br />- 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. Write 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, write "0". Persons aged 95 years and over should be coded "95". Make sure always that your writing is legible and within the appropriate box.<br />- Be careful not to round ages up to the next birthday. A child who is aged four years and eleven months should, for example be entered as "4" and not "5". <br />- Many people do not know their ages. If a person's age is not known, you must make the best estimate possible.<br />- 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.<br />- 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 />- 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 />- 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 (<span class="em">see appendix 1</span>) which lists the dates of events in the history of districts. If the person can remember how old he/she was at the time of the event, you can work out the person's age.<br /><br />- How to use the historical calendar of events to estimate the respondent's age:</div><br /><div class="i2">- Ask for any historical event (national or local) which occurred around the time of the birth/childhood of the respondent.<br />- Ask how old the respondent was when that event occurred or how many years elapsed before his/her birth.<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 + 45 (i.e. 12th Dec. 1963 to 24th August 2009) = 60 years. If this method fails, you should try the following approach.</div><br /><div class="i1">- Simply estimate how old he/she may be.</div><br /><div class="i2">- Then select from your list of local, or district historical events, some events which occurred about the time when according to your estimate, he/she must have been born.<br />- Ask whether he/she has heard about any of those events.<br />- 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 />- Then, from this information, work out his/her age.<br />- Some tribes 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 tribes 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 />- 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 />- Determine the age of her oldest child.<br />- 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 />- 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 />- 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 />- Any estimate of age, however rough, is better than leaving the column blank. Do the best you can to report ages accurately.</div><br /></svar> Kenya 2009: All persons This variable indicates the person's age. 00 Less than 1 year 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 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 old and over Demographic Variables -- PERSON Line number of mother <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A404" a="all"><span class="em">Line number of mother</span><br />P-13. Please insert line number of [name's] biological mother. _ _<br /><div class="i1">Enter "0" if biological mother is not in household.</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A404" a="all"><span class="em">25.5 Column P13: Line number of mother</span><br /><br /><span class="em">Ask</span> to determine whether [the respondent]'s mother is alive and is a member of the household. <span class="em">For each household member listed in column P00, record the 'line number' of the biological mother if she is listed in the household. Record '0' if the biological mother is not in the household</span>.<br /></svar> Kenya 2009: Persons in conventional households or refugee camps [discrepancies: none] This variable indicates the line number of the person's mother. 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 33 33 34 34 35 35 38 38 47 47 49 49 99 NIU (not in universe) Constructed Family Interrelationship Variables -- PERSON Usual member of household <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A405" a="all"><span class="em">Usual member of household</span><br />P-14. Is [person] a usual member of this household?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A405" a="all"><span class="em">25.6 Column P14: Usual member of household</span><br /><br />"Usual residence" for purposes of 2009 census is defined as the place at which the person lives at the time of the census, and has been there for some time 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 categorizing them as "usual residents" should be clear.<br /><br /><span class="em">Ask</span>: "Is [the respondent] a usual member of this household?" 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, code "1", if the listed person is not a "<span class="em">usual</span>" member, then code "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.<br /></svar> Kenya 2009: Persons in conventional households or refugee camps [discrepancies: none] This variable indicates the whether the person is a usual member of household. 1 Yes 2 No 9 NIU (not in universe) Migration: Global Variables -- PERSON Marital status <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A408" a="all"><span class="em">Marital status</span><br />P-17. What is [person's] marital status?<br /><div class="i1">[] 1 Never married<br />[] 2 Married monogamous<br />[] 3 Married polygamous<br />[] 4 Widowed<br />[] 5 Divorced <br />[] 6 Separated<br />[] 9 Unknown</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A408" a="all"><span class="h3">26. Column P17: Marital status</span><br /><br />(Is this person monogamously or polygamously married, widowed, divorced or separated, or never married?)<br /><br />26.1 Persons who have never married including young children should be coded "1" (never married).<br /><br />26.2 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 /><br />26.3 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 /><br />26.4 If people think of themselves as divorced or separated, code them 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 /><br />26.5 Accept what people say about their marital status. Do not embarrass yourself or the respondent by inquiring into the nature of marriage or divorce.<br /></svar> Kenya 2009: All persons This variable indicates the person's marital status. 1 Never married 2 Married monogamous 3 Married polygamous 4 Widowed 5 Divorced 6 Separated Demographic Variables -- PERSON Country or district of birth <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A409" a="all"><span class="em">Birth place</span><br />P-18. Where was [person] born? _ _ _<br /><div class="i1">Write district code, if in Kenya, or country code, if outside Kenya. The code list is provided.</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A409" a="all"><span class="h3">27. Column P18: Birth place</span><br /><br /><span class="em">Ask</span>: Where was [the respondent] born?<br />Birthplace is the usual 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 the 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 Ruiru district moves to Nairobi to deliver her child, it will be assumed that the woman went to Nairobi purposely for maternity services. Thus the district of birth of the child will be recorded as Ruiru.<br /><br />27.1 For persons born in Kenya, code district using the list provided. For example, a person born in Kikuyu district, code "209" and for a person born in Tharaka district, code "414".<br /><br />27.2 Relate the person's birthplace to the present district's frontiers as far as possible. District boundaries have been changed over the years and we want to relate a person's place of birth to the district as it is constituted now. The codes must however be based on the code list provided.<br /><br />27.3 For districts that have been split, probe to find the actual district of birth and code the name by which it is currently known based on the code list provided.<br /><br />27.4 For persons born outside Kenya, code the country of birth. For example, a person born in Tanzania will be coded "987", Uganda "983", Somalia "962" etc.<br /><br />27.5 Code "<span class="em">888</span>" if district of birth is not known and "999" for not stated.<br /></svar> Kenya 2009: All persons This variable indicates the person's birth place. 021 Angola 022 Benin 023 Botswana 024 Burkina Faso 025 Burundi 026 Cameroon 027 Cape Verde 028 Central African Republic 029 Chad 030 Comoros 031 Congo, republic of the... 032 Côte d'ivoire 033 Democratic Republic of the Congo 034 Guinea-Bissau 035 Djibouti 036 Egypt 037 Equatorial Guinea 038 Eritrea 039 Ethiopia 040 Gabon 042 Ghana 053 Mozambique 056 Nigeria 057 Rwanda 060 Seychelles 062 Somalia 063 South Africa 064 Sudan 066 Togo 067 Tunisia 068 Uganda 069 United Republic of Tanzania 070 Zambia 071 Zimbabwe 090 Other African country 101 Nairobi West 102 Nairobi East 103 Nairobi North 104 Westlands 201 Nyandarua North 202 Nyandarua South 203 Nyeri North 204 Nyeri South 205 Kirinyaga 206 Murang'a North 207 Murang'a South 208 Kiambu 209 Kikuyu 210 Limuru 211 Lari 212 Githunguri 213 Thika East 214 Thika West 215 Ruiru 216 Gatanga 217 Gatundu 301 Mombasa 302 Kilindini 303 Kwale 304 Kinango 305 Msambweni 306 Kilifi 307 Kaloleni 308 Malindi 309 Tana river 310 Tana delta 311 Lamu 312 Taita 313 Taveta 401 Marsabit 402 Chalbi 403 Laisamis 404 Moyale 405 Isiolo 406 Garba Tulla 407 Imenti Central 408 Imenti North 409 Imenti South 410 Meru South 411 Maara 412 Igembe 413 Tigania 414 Tharaka 415 Embu 416 Mbeere 417 Kitui North 418 Kitui South 419 Mwingi 420 Kyuso 421 Machakos 422 Mwala 423 Yatta 424 Kangundo 425 Makueni 426 Mbooni 427 Kibwezi 428 Nzaui 501 Garisa 502 Lagdera 503 Fafi 504 Ijara 505 Wajir South 506 Wajir North 507 Wajir East 508 Wajir West 509 Mandera Central 510 Mandera East 511 Mandera West 601 Siaya 602 Bondo 603 Rarieda 604 Kisumu East 605 Kisumu West 606 Nyando 607 Homa Bay 608 Suba 609 Rachuonyo 610 Migori 611 Rongo 612 Kuria West 613 Kuria East 614 Kisii Central 615 Kisii South 616 Masaba 617 Gucha 618 Gucha South 619 Nyamira 620 Manga 621 Borabu 701 Turkana Central 702 Turkana North 703 Turkana South 704 West Pokot 705 Pokot North 706 Pokot Central 707 Samburu Central 708 Samburu East 709 Samburu North 710 Trans Nzoia West 711 Trans Nzoia East 712 Kwanza 713 Baringo 714 Baringo North 715 East Pokot 716 Koibatek 717 Eldoret West 718 Eldoret East 719 Wareng 720 Marakwet 721 Keiyo 722 Nandi North 723 Nandi Central 724 Nandi East 725 Nandi South 726 Tinderet 727 Laikipia North 728 Laikipia East 729 Laikipia West 730 Nakuru 731 Nakuru North 732 Naivasha 733 Molo 734 Narok North 735 Narok South 736 Trans Mara 737 Kajiado Central 738 Loitoktok 739 Kericho 740 Kipkelion 741 Buret 742 Sotik 743 Bomet 744 Kajiado North 801 Kakamega Central 802 Kakamega South 803 Kakamega North 804 Kakamega East 805 Lugari 806 Vihiga 807 Emuhaya 808 Hamisi 809 Mumias 810 Butere 811 Bungoma South 812 Bungoma North 813 Bungoma East 814 Bungoma West 815 Mt Elgon 816 Busia 817 Teso North 818 Samia 819 Bunyala 820 Teso South 858 China 860 India 864 Israel 865 Japan 879 Pakistan 882 Republic of Korea 884 Saudi Arabia 886 Sri Lanka 888 Surian Arab 891 United Arab Emirates 893 Yemen 900 Belgium 908 Finland 909 France 911 Germany 915 Ireland 916 Italy 927 Netherlands 928 Norway 941 Sweden 942 Switzerland 948 United Kingdom of Great Britain and Northern Ireland 954 Canada 970 United States of America 982 Australia 995 Other non-African country 999 Unknown Nativity and Birthplace Variables -- PERSON Country or district of residence one year ago <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A410" a="all"><span class="em">Previous residence</span><br />P-19. Where was [person] living in August 2008? _ _ _<br /><div class="i1">Write district code, if in Kenya, or country code, if outside Kenya. If aged under 1 year, write "0". The code list is provided.</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A410" a="all"><span class="h3">28. Column P19: Previous residence</span><br /><br /><span class="em">Ask</span>: Where was [the respondent] living in August 2008?<br /><br />28.1 If the person is aged below one year, code "000" in this column.<br />28.2 For persons who were living in Kenya in August 2008, indicate the district code in column P19 (district codes are the same as for P18). For example, for persons whose previous residence was Kisii Central district code "614".<br />28.3 For districts which have been split, probe to find the actual district of residence in August 2008 and code the name by which it is currently known based on the list provided.<br />28.4 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, 2008.<br />28.5 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 />28.6 If the person was living in another country in August 2008, use the code pertaining to the specific country.<br />28.7 Code "888" if district of previous residence is not known and' "999" for not stated.<br /></svar> Kenya 2009: Persons age 1+ [discrepancies: none] This variable indicates where the person was living in August 2008. 031 Congo 033 Democratic Republic of the Congo 036 Egypt 039 Ethiopia 056 Nigeria 057 Rwanda 062 Somalia 063 South Africa 064 Sudan 068 Uganda 069 United Republic of Tanzania 071 Zimbabwe 090 Other African country 101 Nairobi West 102 Nairobi East 103 Nairobi North 104 Westlands 201 Nyandarua North 202 Nyandarua South 203 Nyeri North 204 Nyeri South 205 Kirinyaga 206 Murang'a North 207 Murang'a South 208 Kiambu 209 Kikuyu 210 Limuru 211 Lari 212 Githunguri 213 Thika East 214 Thika West 215 Ruiru 216 Gatanga 217 Gatundu 301 Mombasa 302 Kilindini 303 Kwale 304 Kinango 305 Msambweni 306 Kilifi 307 Kaloleni 308 Malindi 309 Tana river 310 Tana delta 311 Lamu 312 Taita 313 Taveta 401 Marsabit 402 Chalbi 403 Laisamis 404 Moyale 405 Isiolo 406 Garba Tulla 407 Imenti Central 408 Imenti North 409 Imenti South 410 Meru South 411 Maara 412 Igembe 413 Tigania 414 Tharaka 415 Embu 416 Mbeere 417 Kitui North 418 Kitui South 419 Mwingi 420 Kyuso 421 Machakos 422 Mwala 423 Yatta 424 Kangundo 425 Makueni 426 Mbooni 427 Kibwezi 428 Nzaui 501 Garisa 502 Lagdera 503 Fafi 504 Ijara 505 Wajir South 506 Wajir North 507 Wajir East 508 Wajir West 509 Mandera Central 510 Mandera East 511 Mandera West 601 Siaya 602 Bondo 603 Rarieda 604 Kisumu East 605 Kisumu West 606 Nyando 607 Homa Bay 608 Suba 609 Rachuonyo 610 Migori 611 Rongo 612 Kuria West 613 Kuria East 614 Kisii Central 615 Kisii South 616 Masaba 617 Gucha 618 Gucha South 619 Nyamira 620 Manga 621 Borabu 701 Turkana Central 702 Turkana North 703 Turkana South 704 West Pokot 705 Pokot North 706 Pokot Central 707 Samburu Central 708 Samburu East 709 Samburu North 710 Trans Nzoia West 711 Trans Nzoia East 712 Kwanza 713 Baringo 714 Baringo North 715 East Pokot 716 Koibatek 717 Eldoret West 718 Eldoret East 719 Wareng 720 Marakwet 721 Keiyo 722 Nandi North 723 Nandi Central 724 Nandi East 725 Nandi South 726 Tinderet 727 Laikipia North 728 Laikipia East 729 Laikipia West 730 Nakuru 731 Nakuru North 732 Naivasha 733 Molo 734 Narok North 735 Narok South 736 Trans Mara 737 Kajiado Central 738 Loitoktok 739 Kericho 740 Kipkelion 741 Buret 742 Sotik 743 Bomet 744 Kajiado North 801 Kakamega Central 802 Kakamega South 803 Kakamega North 804 Kakamega East 805 Lugari 806 Vihiga 807 Emuhaya 808 Hamisi 809 Mumias 810 Butere 811 Bungoma South 812 Bungoma North 813 Bungoma East 814 Bungoma West 815 Mt Elgon 816 Busia 817 Teso North 818 Samia 819 Bunyala 820 Teso South 858 China 860 India 891 United Arab Emirates 911 Germany 916 Italy 948 United Kingdom of Great Britain and Northern Ireland 954 Canada 970 United States of America 995 Other non-African country 999 NIU (not in universe) Migration: Global Variables -- PERSON Month when person moved to current district <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A411 KE09A412" a="all"><span class="em">Duration of residence</span><br />P-20, P-21. When did [person] move to the current district?<br /><div class="i1">Month_ _<br />Year _ _ _ _<br /><br />For respondents enumerated in their district of birth, code month and year of birth. If date of movement is not known, write "99" for month and "9999" for year.</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A411 KE09A412" a="all"><span class="h3">29. Columns P20-P21: Duration of residence</span><br /><br /><span class="em">Ask</span>: When did [the respondent] move to the current district?<br /><br />29.1 Record the month in P20 (e.g. "05" for May) and year in P21 (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 />29.2 For all persons enumerated in their district of birth, write date of birth in the boxes in columns P20-P21.<br />29.3 If the date one moved is not known or not stated, write "99" for month in the columns P20 and "9999" for year in column P21<br /></svar> Kenya 2009: All persons This variable indicates the month in which the person moved to the district where they currently live. 01 January 02 February 03 March 04 April 05 May 06 June 07 July 08 August 09 September 10 October 11 November 12 December Migration: Global Variables -- PERSON Year when person moved to current district <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A411 KE09A412" a="all"><span class="em">Duration of residence</span><br />P-20, P-21. When did [person] move to the current district?<br /><div class="i1">Month_ _<br />Year _ _ _ _<br /><br />For respondents enumerated in their district of birth, code month and year of birth. If date of movement is not known, write "99" for month and "9999" for year.</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A411 KE09A412" a="all"><span class="h3">29. Columns P20-P21: Duration of residence</span><br /><br /><span class="em">Ask</span>: When did [the respondent] move to the current district?<br /><br />29.1 Record the month in P20 (e.g. "05" for May) and year in P21 (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 />29.2 For all persons enumerated in their district of birth, write date of birth in the boxes in columns P20-P21.<br />29.3 If the date one moved is not known or not stated, write "99" for month in the columns P20 and "9999" for year in column P21<br /></svar> Kenya 2009: All persons This variable indicates the year in which the person moved to the district where they currently live. 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 Migration: Global Variables -- PERSON Father alive <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A413" a="all">P-22. Is [person's] father alive?<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 9 Unknown</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A413 KE09A414" a="all"><span class="h3">30. Columns P22-P23: Orphanhood</span><br /><br /><span class="em">Ask</span>: Is [the respondent]'s father/mother alive?<br /><br />30.1 Enter the appropriate codes in column P-22 and P-23 in respect of the survival status of the respondent's biological father and mother respectively. Note that at times destitute children are brought up or adopted at a very young age by relatives. Such foster parents should not be considered as the biological parents of the respondent. Please always probe to establish the reality of the situation.<br />30.2 In some cases, a child's 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 code "9" for 'don't know'. You must always probe to ensure you obtain the most satisfactory answer.<br /></svar> Kenya 2009: All persons This variable indicates whether the person's father is alive. 1 Yes 2 No 8 Unknown Fertility and Mortality Variables -- PERSON Mother alive <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414"><span class="h3">A: Information regarding all persons</span><br />[Questions P-00 to P-23 were asked of all persons in conventional households or refugee camps].<br /></svar></p> <p><svar v="KE09A414" a="all">P-23. Is [person's] mother alive?<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 9 Unknown</div><br /></svar> <svar v="KE09A400 KE09A401 KE09A402 KE09A403 KE09A404 KE09A405 KE09A406 KE09A407 KE09A408 KE09A409 KE09A410 KE09A411 KE09A412 KE09A413 KE09A414">- <span class="em">Section A</span>: Information regarding all persons. This information is contained in columns P00 to P23. Questions in this section will apply to all persons.<br /></svar></p> <p><svar v="KE09A413 KE09A414" a="all"><span class="h3">30. Columns P22-P23: Orphanhood</span><br /><br /><span class="em">Ask</span>: Is [the respondent]'s father/mother alive?<br /><br />30.1 Enter the appropriate codes in column P-22 and P-23 in respect of the survival status of the respondent's biological father and mother respectively. Note that at times destitute children are brought up or adopted at a very young age by relatives. Such foster parents should not be considered as the biological parents of the respondent. Please always probe to establish the reality of the situation.<br />30.2 In some cases, a child's 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 code "9" for 'don't know'. You must always probe to ensure you obtain the most satisfactory answer.<br /></svar> Kenya 2009: All persons This variable indicates whether the person's mother is alive. 1 Yes 2 No 8 Unknown Fertility and Mortality Variables -- PERSON Number of boys born alive <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A415 KE09A416" a="all"><span class="em">Particulars of all live births</span><br />P-24, P-25. How many children have you ever born alive?<br /><div class="i1">_ _ Boys<br />_ _ Girls</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><span class="h3">31. Section B: Information regarding females aged 12 years and above</span></p> <p><svar v="KE09A415 KE09A416" a="all"><span class="em">31.2 Columns P24-P25: Children born alive</span><br /><br /><span class="em">Ask: </span>"Have you ever borne any children alive?" (How many children have you ever borne alive?).<br />A child born alive is one who shows one or more of the following signs of life immediately after birth:<br /><div class="i1">- Crying or similar sounds<br />- Movement of the limbs or any other parts of the body<br />- Any other tangible signs of life.</div><br />The census is concerned only with children born alive. Do not include <span class="em">stillbirths</span>, 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, write the number of boys in the boxes in <span class="em">P24</span> and the number of girls in <span class="em">P25</span>.<br /></svar> Kenya 2009: Females age 12+ [discrepancies: none] This variable indicates the number of boys a woman has had that were born alive. 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+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of girls born alive <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A415 KE09A416" a="all"><span class="em">Particulars of all live births</span><br />P-24, P-25. How many children have you ever born alive?<br /><div class="i1">_ _ Boys<br />_ _ Girls</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><span class="h3">31. Section B: Information regarding females aged 12 years and above</span></p> <p><svar v="KE09A415 KE09A416" a="all"><span class="em">31.2 Columns P24-P25: Children born alive</span><br /><br /><span class="em">Ask: </span>"Have you ever borne any children alive?" (How many children have you ever borne alive?).<br />A child born alive is one who shows one or more of the following signs of life immediately after birth:<br /><div class="i1">- Crying or similar sounds<br />- Movement of the limbs or any other parts of the body<br />- Any other tangible signs of life.</div><br />The census is concerned only with children born alive. Do not include <span class="em">stillbirths</span>, 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, write the number of boys in the boxes in <span class="em">P24</span> and the number of girls in <span class="em">P25</span>.<br /></svar> Kenya 2009: Females age 12+ [discrepancies: none] This variable indicates the number of girls a woman has had that were born alive. 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+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of boys born alive living in household <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A417 KE09A418" a="all">P-26, P-27. How many children have you born alive who usually live in this household?<br /><div class="i1">_ _ Boys<br />_ _ Girls</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><span class="h3">31. Section B: Information regarding females aged 12 years and above</span></p> <p><svar v="KE09A417 KE09A418" a="all"><span class="em">31.3 Columns P26-P27: Children Living in the Household</span><br /><br />If the woman has born children alive, ask, "of the children you have born alive, how many usually live with you in this household?" <span class="em">Remember that for all childless women you must enter '0' in the appropriate boxes</span>.<br />Write the number of boys and girls who usually live in the household in columns P26 and P27 respectively. If none of the boys or girls the woman has borne alive are living in the household, write "0" in the appropriate boxes. Children borne to the woman who are in boarding school should be included among the children who usually live in the household. In case of a visitor who spent the <span class="em">Census Night</span> with her children in the household, these children should not be captured in P26 and P27 but in P28 and P29.<br /></svar> Kenya 2009: Females age 12+ [discrepancies: none] This variable indicates the number of boys a woman has that were born alive and are living in the household. 00 0 01 1 02 2 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 Number of girls born alive living in household <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A417 KE09A418" a="all">P-26, P-27. How many children have you born alive who usually live in this household?<br /><div class="i1">_ _ Boys<br />_ _ Girls</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><span class="h3">31. Section B: Information regarding females aged 12 years and above</span></p> <p><svar v="KE09A417 KE09A418" a="all"><span class="em">31.3 Columns P26-P27: Children Living in the Household</span><br /><br />If the woman has born children alive, ask, "of the children you have born alive, how many usually live with you in this household?" <span class="em">Remember that for all childless women you must enter '0' in the appropriate boxes</span>.<br />Write the number of boys and girls who usually live in the household in columns P26 and P27 respectively. If none of the boys or girls the woman has borne alive are living in the household, write "0" in the appropriate boxes. Children borne to the woman who are in boarding school should be included among the children who usually live in the household. In case of a visitor who spent the <span class="em">Census Night</span> with her children in the household, these children should not be captured in P26 and P27 but in P28 and P29.<br /></svar> Kenya 2009: Females age 12+ [discrepancies: none] This variable indicates the number of girls a woman has that were born alive and are living in the household. 00 0 01 1 02 2 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 Number of boys born alive living elsewhere <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A419 KE09A420" a="all">P-28, P-29. How many children have you born alive who usually live elsewhere?<br /><div class="i1">_ _ Boys<br />_ _ Girls</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><span class="h3">31. Section B: Information regarding females aged 12 years and above</span></p> <p><svar v="KE09A419 KE09A420" a="all"><span class="em">31.4 Columns P28-P29: Children living elsewhere</span><br /><br /><span class="em">Next ask</span>: "Of the children you have born alive, how many usually live elsewhere?"<br />Write the number of boys who usually live elsewhere in column <span class="em">P28</span> and the number of girls in column <span class="em">P29</span>. If none of the boys or girls she has borne alive live elsewhere, write, "0" in the appropriate boxes.<br />Include in these columns <span class="em">(P28 and P29) </span>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. Ask further questions to probe - "are any of your children away?", "at work?", "with relatives?", etc.<br /></svar> Kenya 2009: Females age 12+ [discrepancies: none] This variable indicates the number of boys a woman has that were born alive and are living elsewhere. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of girls born alive living elsewhere <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A419 KE09A420" a="all">P-28, P-29. How many children have you born alive who usually live elsewhere?<br /><div class="i1">_ _ Boys<br />_ _ Girls</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><span class="h3">31. Section B: Information regarding females aged 12 years and above</span></p> <p><svar v="KE09A419 KE09A420" a="all"><span class="em">31.4 Columns P28-P29: Children living elsewhere</span><br /><br /><span class="em">Next ask</span>: "Of the children you have born alive, how many usually live elsewhere?"<br />Write the number of boys who usually live elsewhere in column <span class="em">P28</span> and the number of girls in column <span class="em">P29</span>. If none of the boys or girls she has borne alive live elsewhere, write, "0" in the appropriate boxes.<br />Include in these columns <span class="em">(P28 and P29) </span>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. Ask further questions to probe - "are any of your children away?", "at work?", "with relatives?", etc.<br /></svar> Kenya 2009: Females age 12+ [discrepancies: none] This variable indicates the number of girls a woman has had that were born alive and are living elsewhere. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of boys born alive who have died <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A421 KE09A422" a="all">P-30, P-31. How many children have you born alive who died?<br /><div class="i1">_ _ Boys<br />_ _ Girls</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><span class="h3">31. Section B: Information regarding females aged 12 years and above</span></p> <p><svar v="KE09A421 KE09A422" a="all"><span class="em">31.5 Columns P30-P31: Children who have died</span><br /><br /><span class="em">Then ask</span>, "of the children you have born alive, how many have died?"<br />Many people find it painful to talk about their dead children. It is best to ask this question in a matter of fact and without embarrassment. Please refer to <span class="em">section B</span> above for the definition of a live birth.<br /><br />Write the number of boys and girls who have died in columns P30 and P31 respectively. If none of the boys and girls she has borne alive has died, code "0" in the appropriate columns. If, in spite of your best efforts, you cannot obtain this information about the children who have died, leave columns <span class="em">P30</span> and <span class="em">P31</span> blank. <span class="em">However, this will not be encouraged.</span><br /><br />Before proceeding to columns <span class="em">P32-P36</span>, probe to confirm whether the number of children given in columns <span class="em">P26-P31 </span>is correct by comparing with the entries in columns <span class="em">P24</span> and <span class="em">P25</span>. If these totals differ, probe further and adjust your entries accordingly.<br /></svar> Kenya 2009: Females age 12+ [discrepancies: none] This variable indicates the number of boys a woman has had that were born alive and are now dead. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Number of girls born alive who have died <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A421 KE09A422" a="all">P-30, P-31. How many children have you born alive who died?<br /><div class="i1">_ _ Boys<br />_ _ Girls</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><span class="h3">31. Section B: Information regarding females aged 12 years and above</span></p> <p><svar v="KE09A421 KE09A422" a="all"><span class="em">31.5 Columns P30-P31: Children who have died</span><br /><br /><span class="em">Then ask</span>, "of the children you have born alive, how many have died?"<br />Many people find it painful to talk about their dead children. It is best to ask this question in a matter of fact and without embarrassment. Please refer to <span class="em">section B</span> above for the definition of a live birth.<br /><br />Write the number of boys and girls who have died in columns P30 and P31 respectively. If none of the boys and girls she has borne alive has died, code "0" in the appropriate columns. If, in spite of your best efforts, you cannot obtain this information about the children who have died, leave columns <span class="em">P30</span> and <span class="em">P31</span> blank. <span class="em">However, this will not be encouraged.</span><br /><br />Before proceeding to columns <span class="em">P32-P36</span>, probe to confirm whether the number of children given in columns <span class="em">P26-P31 </span>is correct by comparing with the entries in columns <span class="em">P24</span> and <span class="em">P25</span>. If these totals differ, probe further and adjust your entries accordingly.<br /></svar> Kenya 2009: Females age 12+ [discrepancies: none] This variable indicates the number of girls a woman has had that were born alive and are now dead. 00 0 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11+ 99 NIU (not in universe) Fertility and Mortality Variables -- PERSON Month of birth of the last child born alive <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><span class="em">Particulars of last live births</span></p> <p>P-32, P-33. When was your last child born?</p> <div class="i1">Month _ _<br />Year _ _ _ _<br /><br />If date of birth is not known code "99" for month and "9999" for year.</div> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><svar v="KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">[Questions 32 to 36 were asked of females 12 years old and over with at least one live birth.]<br /><br /><span class="em">31.6 Columns P32 to P36: Particulars of last live births</span><br /></svar></p> <p><svar v="KE09A423 KE09A424" a="all"><span class="em">31.7 Columns P32-P33: Last child born</span><br /><br /><span class="em">Ask, </span>"When was your last child born?"<br />Record the month and year of birth in columns <span class="em">P32</span> and <span class="em">P33</span> respectively. Code the month in column <span class="em">P32</span>, i.e. "01" for January, "02" for February, "12" for December and the year in column <span class="em">P33</span> i.e. "1980" (for 1980), "1989" (for 1989). This question should be asked regardless of the age of the last born child (he or she could be an adult by now).<br /></svar> Kenya 2009: Females age 12+ with at least one live birth [discrepancies: none] This variable indicates the month of birth of the woman's last 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 birth of the last child born alive <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><span class="em">Particulars of last live births</span></p> <p>P-32, P-33. When was your last child born?</p> <div class="i1">Month _ _<br />Year _ _ _ _<br /><br />If date of birth is not known code "99" for month and "9999" for year.</div> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><svar v="KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">[Questions 32 to 36 were asked of females 12 years old and over with at least one live birth.]<br /><br /><span class="em">31.6 Columns P32 to P36: Particulars of last live births</span><br /></svar></p> <p><svar v="KE09A423 KE09A424" a="all"><span class="em">31.7 Columns P32-P33: Last child born</span><br /><br /><span class="em">Ask, </span>"When was your last child born?"<br />Record the month and year of birth in columns <span class="em">P32</span> and <span class="em">P33</span> respectively. Code the month in column <span class="em">P32</span>, i.e. "01" for January, "02" for February, "12" for December and the year in column <span class="em">P33</span> i.e. "1980" (for 1980), "1989" (for 1989). This question should be asked regardless of the age of the last born child (he or she could be an adult by now).<br /></svar> Kenya 2009: Females age 12+ with at least one live birth [discrepancies: none] This variable indicates the year of birth of the woman's last child. 1934 1934 or earlier 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 9998 Unknown 9999 NIU (not in universe) Fertility and Mortality Variables -- PERSON Last birth notified <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A425" a="all">P-34. Was this last birth notified?<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 9 Unknown</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><svar v="KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">[Questions 32 to 36 were asked of females 12 years old and over with at least one live birth.]<br /><br /><span class="em">31.6 Columns P32 to P36: Particulars of last live births</span><br /></svar></p> <p><svar v="KE09A425" a="all"><span class="em">31.8 Column P34: Birth notification</span><br /><br /><span class="em">Ask, </span>'Was the last birth notified?'<br />Enter the correct code in column P-34 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 event (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 birth that occur at home are assistant chiefs while the events of birth that occur in health institutions are registered by personnel in those institutions.<br /></svar> Kenya 2009: Females age 12+ with at least one live birth [discrepancies: none] This variable indicates whether the last birth to the woman was notified. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Sex of last child <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A426" a="all">P-35. Was this child male or female?<br /><div class="i1">[] 1 Male<br />[] 2 Female<br />[] 3 Male twins<br />[] 4 Female twins<br />[] 5 Male-female twins<br />[] 6 Multiple births <br />[] 9 Unknown</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><svar v="KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">[Questions 32 to 36 were asked of females 12 years old and over with at least one live birth.]<br /><br /><span class="em">31.6 Columns P32 to P36: Particulars of last live births</span><br /></svar></p> <p><svar v="KE09A426" a="all"><span class="em">31.9 Column P35: Sex of the child</span><br /><br /><span class="em">Ask, </span>'Was the child a boy or a girl?'<br />Write the sex of the last borne child in column <span class="em">P35</span>. Code "1" for male, "2" for female, "3" for male twins, "4" for female twins, "5" for twins with one of either sex, and "6" for other multiple births and "9" for don't know.<br /></svar> Kenya 2009: Females age 12+ with at least one live birth [discrepancies: none] This variable indicates the sex of the last child born to the woman. 1 Male 2 Female 3 Male twins 4 Female twins 5 Male-female twins 6 Multiple births 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Last child born is alive <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427"><span class="h3">B: Information regarding females aged 12 years and above</span><br />[Questions P-24 to P-36 were asked of females age 12+ only.]<br /></svar></p> <p><svar v="KE09A427" a="all">P-36. Is this child still alive?<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 One of the twins<br />[] 4 Both twins<br />[] 5 One of the multiples<br />[] 6 Two of the multiples<br />[] 7 All of the multiples<br />[] 9 Unknown</div><br /></svar> <svar v="KE09A415 KE09A416 KE09A417 KE09A418 KE09A419 KE09A420 KE09A421 KE09A422 KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">- <span class="em">Section B</span>: Information regarding females 12 years old and above. This section covers columns P24 to P36. It pertains to live births and should be asked of all females aged 12 years and above and make appropriate entries for each. <span class="em">As much as possible, obtain the information directly from the female concerned</span>. Information should only be obtained from someone else if the respondent cannot be reached.<br /></svar></p> <p><svar v="KE09A423 KE09A424 KE09A425 KE09A426 KE09A427">[Questions 32 to 36 were asked of females 12 years old and over with at least one live birth.]<br /><br /><span class="em">31.6 Columns P32 to P36: Particulars of last live births</span><br /></svar></p> <p><svar v="KE09A427" a="all"><span class="em">31.10 Column P36: Survival status of last born child</span><br /><br />In column P36, indicate whether the child is still alive. For single births, code "1" if the child is still alive and "2" if dead. For twins code "3" if one of the twins is alive and "4" if both twins are alive. For multiple births, code "5" if one of the multiples is alive, "6" if two of the multiples are alive, "7" if all multiples are alive and "8" if none of the multiples is alive. Write "9" if the survival status of the last birth is not known.<br /></svar> Kenya 2009: Females age 12+ with at least one live birth [discrepancies: none] This variable indicates whether the last child born to a woman is alive. 1 Yes 2 No 3 Both twins 4 All of the multiples 5 One or more twin or multiple died 9 NIU (not in universe) Fertility and Mortality Variables -- PERSON Disability 1 <svar v="KE09A428 KE09A429 KE09A430 KE09A431"><span class="h3">C: Information regarding persons with disability</span><br />[Questions P-37 and P-38 were asked of all individuals.]<br /></svar></p> <p><svar v="KE09A428 KE09A429 KE09A430" a="all">P-37. What type of disability does [person] have?<br /><div class="i1">[] 1 Visual<br />[] 2 Hearing <br />[] 3 Speech<br />[] 4 Physical<br />[] 5 Mental<br />[] 6 Self care<br />[] 7 Others<br />[] 8 None<br /><br />List not more than three.</div><br /></svar> <span class="h3">32. Section C: Information regarding disability</span></p> <p><span class="em">Columns P37 to P38 contain questions pertaining to disabilities. These questions are to be asked of the head of the household or any other responsible person.</span></p> <p><span class="em">32.1 Introduction</span></p> <p>Questions regarding disabilities have to be asked very carefully and with caution. You should not ask "Do you have a disability, or are you disabled, or are you blind, or deaf" nor "are you lame?'. This will generate very low rates of response because you will not get the correct answer. The word "disability" is regarded negatively in most communities particularly in developing countries. People may feel stigmatized or be ashamed to be identified as having a disability. In some cultures, disability is seen as punishment for sins committed in previous lives. <br />Also, even if people do not feel stigmatized, the word "disability" often implies a very significant condition. Persons who can walk around their homes but are unable to walk to the market may perceive their situation as not severe enough to be considered as having a disability. <br />Disability is interpreted relative to what is considered normal functioning (or different). This may vary across various cultures, age groups, or social class.</p> <p><span class="em">32.2 Definition of disability</span></p> <p>The Disability Act 2003 defines disability as: physical, sensory, mental, or other impairment, including a visual, hearing or physical disability, which has a substantial long term adverse effect on a person's ability to carry out usual day to day activities. Disability is, therefore, viewed as a physical, mental, or psychological condition or impairment that substantially affects a person's daily activities or limits a person's ability to perform one or more basic life activities (referred to as activities of daily life- ADL) such as caring for oneself, performing manual tasks, walking, seeing, hearing, speaking, breathing, earning a living, or working and interacting with other persons. <br />In this context, activities refer to a wide range of deliberate actions performed by an individual as opposed to particular body functions or structures. These are basic deliberate actions undertaken in order to accomplish a task such as dressing or feeding oneself. <br />In the 2009 Kenya Population and Housing Census we will classify one as having a disability if they have any of the following: visual, hearing and speech impairment; physical, mental and other disabilities, and self-care difficulties.</p> <p><span class="em">32.3 Types of disabilities</span><div class="i1"><span class="em">- Visual impairment</span><br />Visual impairment describes the various degrees of vision loss. A person is considered to have an eyesight or vision disability if he/she doesn't have normal vision even if he/she wears eyeglasses or contact lenses. Visual impairments are caused by injury, disease, through accident, muscular degeneration or cataracts or are congenital. Congenital blindness could be noted at birth or within the first five years of life. Vision impairment can be treated by medicines and therapies though impairments caused by birth or accident are less likely to cure.<br /><br /><span class="em">- Hearing impairment</span><br />Hearing impairment refers to complete deafness or partial hearing in one or both ears. Hearing impairment can be caused by birth or are due to inheritance. In some cases extremely high frequency sound waves may also cause hearing disability. Persons who are able to hear well with the aid of devices are not considered to be having this disability.<br /><br /><span class="em">- Physical disability</span><br />Physical or mobility impairment refers to difficulties in moving (i.e. walking, climbing stairs, using hands, sitting upright or standing). This disability restricts one's physical movement, say body movement, or paralysis of legs, hands, or the whole body. Persons with this type of disability can use assistive equipment and supportive devices that assist them to move around.<br /><br /><span class="em">- Mental disability</span><br />Mental disability affects people's ability to perform activities like other people of similar age groups. They may have difficulty in remembering things or concentrating on what he/she is performing. It includes many different functions such as our abilities to pay attention, learn and retain information, solve problems, and use language to express thoughts. This disability hampers clear thoughts in the mind. It also exhibits problems in comprehending any new ideas or opinions or finding solutions and therefore restrains a person from learning or even coordinating functions/activities.<br /><br /><span class="em">- Self-care difficulties</span><br />This refers to difficulties in dressing, bathing, eating, grooming and hygiene, toileting or getting around the home or inside the home. The difficulties may have arisen as a result of other disabilities or impairments. These types of difficulties maybe present in most disabilities. It may be more pronounced in mental disabilities and severe physical disabilities. The question on self- care disability should be asked of all persons.<br /><br /><span class="em">- Speech impairment</span><br />Speech and language disorders refer to problems in communication or difficulties in producing oral speech sounds or problems with voice quality. They might be characterized by an interruption in the flow or rhythm of speech, such as stammering. These delays and disorders range from simple sound substitutions to the inability to understand or use language. Some causes of speech and language disorders include hearing loss, brain injury, learning disability, substance abuse, physical impairments such as cleft lip (deformed lip) or palate, and vocal abuse or misuse. Persons with speech disabilities are often not able to communicate well with others.<br /><br /><span class="em">- Other disabilities</span><br />This refers to any other disability not mentioned or covered above. These could be any of the following: albinism, epilepsy, autism, or chronic health conditions/ailments of more than six months etc. e.g. mental illnesses, cancer.</div> Kenya 2009: All persons This variable indicates the person's first reported disability. 1 Visual 2 Hearing 3 Speech 4 Physical 5 Mental 6 Selfcare 7 Others 8 None Disability Variables -- PERSON Disability 2 <svar v="KE09A428 KE09A429 KE09A430 KE09A431"><span class="h3">C: Information regarding persons with disability</span><br />[Questions P-37 and P-38 were asked of all individuals.]<br /></svar></p> <p><svar v="KE09A428 KE09A429 KE09A430" a="all">P-37. What type of disability does [person] have?<br /><div class="i1">[] 1 Visual<br />[] 2 Hearing <br />[] 3 Speech<br />[] 4 Physical<br />[] 5 Mental<br />[] 6 Self care<br />[] 7 Others<br />[] 8 None<br /><br />List not more than three.</div><br /></svar> <span class="h3">32. Section C: Information regarding disability</span></p> <p><span class="em">Columns P37 to P38 contain questions pertaining to disabilities. These questions are to be asked of the head of the household or any other responsible person.</span></p> <p><span class="em">32.1 Introduction</span></p> <p>Questions regarding disabilities have to be asked very carefully and with caution. You should not ask "Do you have a disability, or are you disabled, or are you blind, or deaf" nor "are you lame?'. This will generate very low rates of response because you will not get the correct answer. The word "disability" is regarded negatively in most communities particularly in developing countries. People may feel stigmatized or be ashamed to be identified as having a disability. In some cultures, disability is seen as punishment for sins committed in previous lives. <br />Also, even if people do not feel stigmatized, the word "disability" often implies a very significant condition. Persons who can walk around their homes but are unable to walk to the market may perceive their situation as not severe enough to be considered as having a disability. <br />Disability is interpreted relative to what is considered normal functioning (or different). This may vary across various cultures, age groups, or social class.</p> <p><span class="em">32.2 Definition of disability</span></p> <p>The Disability Act 2003 defines disability as: physical, sensory, mental, or other impairment, including a visual, hearing or physical disability, which has a substantial long term adverse effect on a person's ability to carry out usual day to day activities. Disability is, therefore, viewed as a physical, mental, or psychological condition or impairment that substantially affects a person's daily activities or limits a person's ability to perform one or more basic life activities (referred to as activities of daily life- ADL) such as caring for oneself, performing manual tasks, walking, seeing, hearing, speaking, breathing, earning a living, or working and interacting with other persons. <br />In this context, activities refer to a wide range of deliberate actions performed by an individual as opposed to particular body functions or structures. These are basic deliberate actions undertaken in order to accomplish a task such as dressing or feeding oneself. <br />In the 2009 Kenya Population and Housing Census we will classify one as having a disability if they have any of the following: visual, hearing and speech impairment; physical, mental and other disabilities, and self-care difficulties.</p> <p><span class="em">32.3 Types of disabilities</span><div class="i1"><span class="em">- Visual impairment</span><br />Visual impairment describes the various degrees of vision loss. A person is considered to have an eyesight or vision disability if he/she doesn't have normal vision even if he/she wears eyeglasses or contact lenses. Visual impairments are caused by injury, disease, through accident, muscular degeneration or cataracts or are congenital. Congenital blindness could be noted at birth or within the first five years of life. Vision impairment can be treated by medicines and therapies though impairments caused by birth or accident are less likely to cure.<br /><br /><span class="em">- Hearing impairment</span><br />Hearing impairment refers to complete deafness or partial hearing in one or both ears. Hearing impairment can be caused by birth or are due to inheritance. In some cases extremely high frequency sound waves may also cause hearing disability. Persons who are able to hear well with the aid of devices are not considered to be having this disability.<br /><br /><span class="em">- Physical disability</span><br />Physical or mobility impairment refers to difficulties in moving (i.e. walking, climbing stairs, using hands, sitting upright or standing). This disability restricts one's physical movement, say body movement, or paralysis of legs, hands, or the whole body. Persons with this type of disability can use assistive equipment and supportive devices that assist them to move around.<br /><br /><span class="em">- Mental disability</span><br />Mental disability affects people's ability to perform activities like other people of similar age groups. They may have difficulty in remembering things or concentrating on what he/she is performing. It includes many different functions such as our abilities to pay attention, learn and retain information, solve problems, and use language to express thoughts. This disability hampers clear thoughts in the mind. It also exhibits problems in comprehending any new ideas or opinions or finding solutions and therefore restrains a person from learning or even coordinating functions/activities.<br /><br /><span class="em">- Self-care difficulties</span><br />This refers to difficulties in dressing, bathing, eating, grooming and hygiene, toileting or getting around the home or inside the home. The difficulties may have arisen as a result of other disabilities or impairments. These types of difficulties maybe present in most disabilities. It may be more pronounced in mental disabilities and severe physical disabilities. The question on self- care disability should be asked of all persons.<br /><br /><span class="em">- Speech impairment</span><br />Speech and language disorders refer to problems in communication or difficulties in producing oral speech sounds or problems with voice quality. They might be characterized by an interruption in the flow or rhythm of speech, such as stammering. These delays and disorders range from simple sound substitutions to the inability to understand or use language. Some causes of speech and language disorders include hearing loss, brain injury, learning disability, substance abuse, physical impairments such as cleft lip (deformed lip) or palate, and vocal abuse or misuse. Persons with speech disabilities are often not able to communicate well with others.<br /><br /><span class="em">- Other disabilities</span><br />This refers to any other disability not mentioned or covered above. These could be any of the following: albinism, epilepsy, autism, or chronic health conditions/ailments of more than six months etc. e.g. mental illnesses, cancer.</div> Kenya 2009: All persons This variable indicates the person's second reported disability. 1 Visual 2 Hearing 3 Speech 4 Physical 5 Mental 6 Selfcare 7 Others 8 None Disability Variables -- PERSON Disability 3 <svar v="KE09A428 KE09A429 KE09A430 KE09A431"><span class="h3">C: Information regarding persons with disability</span><br />[Questions P-37 and P-38 were asked of all individuals.]<br /></svar></p> <p><svar v="KE09A428 KE09A429 KE09A430" a="all">P-37. What type of disability does [person] have?<br /><div class="i1">[] 1 Visual<br />[] 2 Hearing <br />[] 3 Speech<br />[] 4 Physical<br />[] 5 Mental<br />[] 6 Self care<br />[] 7 Others<br />[] 8 None<br /><br />List not more than three.</div><br /></svar> <span class="h3">32. Section C: Information regarding disability</span></p> <p><span class="em">Columns P37 to P38 contain questions pertaining to disabilities. These questions are to be asked of the head of the household or any other responsible person.</span></p> <p><span class="em">32.1 Introduction</span></p> <p>Questions regarding disabilities have to be asked very carefully and with caution. You should not ask "Do you have a disability, or are you disabled, or are you blind, or deaf" nor "are you lame?'. This will generate very low rates of response because you will not get the correct answer. The word "disability" is regarded negatively in most communities particularly in developing countries. People may feel stigmatized or be ashamed to be identified as having a disability. In some cultures, disability is seen as punishment for sins committed in previous lives. <br />Also, even if people do not feel stigmatized, the word "disability" often implies a very significant condition. Persons who can walk around their homes but are unable to walk to the market may perceive their situation as not severe enough to be considered as having a disability. <br />Disability is interpreted relative to what is considered normal functioning (or different). This may vary across various cultures, age groups, or social class.</p> <p><span class="em">32.2 Definition of disability</span></p> <p>The Disability Act 2003 defines disability as: physical, sensory, mental, or other impairment, including a visual, hearing or physical disability, which has a substantial long term adverse effect on a person's ability to carry out usual day to day activities. Disability is, therefore, viewed as a physical, mental, or psychological condition or impairment that substantially affects a person's daily activities or limits a person's ability to perform one or more basic life activities (referred to as activities of daily life- ADL) such as caring for oneself, performing manual tasks, walking, seeing, hearing, speaking, breathing, earning a living, or working and interacting with other persons. <br />In this context, activities refer to a wide range of deliberate actions performed by an individual as opposed to particular body functions or structures. These are basic deliberate actions undertaken in order to accomplish a task such as dressing or feeding oneself. <br />In the 2009 Kenya Population and Housing Census we will classify one as having a disability if they have any of the following: visual, hearing and speech impairment; physical, mental and other disabilities, and self-care difficulties.</p> <p><span class="em">32.3 Types of disabilities</span><div class="i1"><span class="em">- Visual impairment</span><br />Visual impairment describes the various degrees of vision loss. A person is considered to have an eyesight or vision disability if he/she doesn't have normal vision even if he/she wears eyeglasses or contact lenses. Visual impairments are caused by injury, disease, through accident, muscular degeneration or cataracts or are congenital. Congenital blindness could be noted at birth or within the first five years of life. Vision impairment can be treated by medicines and therapies though impairments caused by birth or accident are less likely to cure.<br /><br /><span class="em">- Hearing impairment</span><br />Hearing impairment refers to complete deafness or partial hearing in one or both ears. Hearing impairment can be caused by birth or are due to inheritance. In some cases extremely high frequency sound waves may also cause hearing disability. Persons who are able to hear well with the aid of devices are not considered to be having this disability.<br /><br /><span class="em">- Physical disability</span><br />Physical or mobility impairment refers to difficulties in moving (i.e. walking, climbing stairs, using hands, sitting upright or standing). This disability restricts one's physical movement, say body movement, or paralysis of legs, hands, or the whole body. Persons with this type of disability can use assistive equipment and supportive devices that assist them to move around.<br /><br /><span class="em">- Mental disability</span><br />Mental disability affects people's ability to perform activities like other people of similar age groups. They may have difficulty in remembering things or concentrating on what he/she is performing. It includes many different functions such as our abilities to pay attention, learn and retain information, solve problems, and use language to express thoughts. This disability hampers clear thoughts in the mind. It also exhibits problems in comprehending any new ideas or opinions or finding solutions and therefore restrains a person from learning or even coordinating functions/activities.<br /><br /><span class="em">- Self-care difficulties</span><br />This refers to difficulties in dressing, bathing, eating, grooming and hygiene, toileting or getting around the home or inside the home. The difficulties may have arisen as a result of other disabilities or impairments. These types of difficulties maybe present in most disabilities. It may be more pronounced in mental disabilities and severe physical disabilities. The question on self- care disability should be asked of all persons.<br /><br /><span class="em">- Speech impairment</span><br />Speech and language disorders refer to problems in communication or difficulties in producing oral speech sounds or problems with voice quality. They might be characterized by an interruption in the flow or rhythm of speech, such as stammering. These delays and disorders range from simple sound substitutions to the inability to understand or use language. Some causes of speech and language disorders include hearing loss, brain injury, learning disability, substance abuse, physical impairments such as cleft lip (deformed lip) or palate, and vocal abuse or misuse. Persons with speech disabilities are often not able to communicate well with others.<br /><br /><span class="em">- Other disabilities</span><br />This refers to any other disability not mentioned or covered above. These could be any of the following: albinism, epilepsy, autism, or chronic health conditions/ailments of more than six months etc. e.g. mental illnesses, cancer.</div> Kenya 2009: All persons This variable indicates the person's third reported disability. 1 Visual 2 Hearing 3 Speech 4 Physical 5 Mental 6 Selfcare 7 Others 8 None Disability Variables -- PERSON Difficulty working due to disability <svar v="KE09A428 KE09A429 KE09A430 KE09A431"><span class="h3">C: Information regarding persons with disability</span><br />[Questions P-37 and P-38 were asked of all individuals.]<br /></svar></p> <p><svar v="KE09A431" a="all">P-38. Because of the disability, does [person] have difficulties engaging in any economic activity?<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 NA<br />[] 9 Unknown</div><br /></svar> <svar v="KE09A428 KE09A429 KE09A430 KE09A431">- <span class="em">Section C</span>: Information regarding disability. It covers columns P37 and P38 and asks questions relating to disabilities. You are required to ask these questions to all persons unless where stated otherwise.<br /></svar></p> <p><svar v="KE09A431" a="all"><span class="em">32.4 Columns P37 to P38: Information regarding persons with disability</span><br /><br />Column P37 seeks information on the disabilities that greatly limit/restrict the household member's inclusion in the society. In circumstances where the respondent has more than one type of disability, record up to a maximum of 3, given in order of the most disabling. For instance if the respondent says he/she is mostly affected by physical disability, followed by hearing and self-care, then code '4' for physical, followed by '2' for hearing and lastly '6' for self-care.<br />Column P38: This question seeks to establish if [the respondent]'s economic activities are affected by his/her disability. Code "1" for "yes", "2" for "no", "3" for "N/A" and "9" for "DK". If the person is under 5 years, then code "3". If a person has one disability, code the disability and "8" in the subsequent boxes. <span class="em">Do not leave boxes blank.</span><br /></svar> Kenya 2009: Persons age 5+ reporting a disability [discrepancies: type I none; type II 0.2%] This variable indicates whether the person has difficulty working due to a disability. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Disability Variables -- PERSON School enrollment status <svar v="KE09A432 KE09A433 KE09A434"><span class="h3">D: Information regarding persons aged 3 years and above</span><br /> [Questions P-39 to P-41 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A432" a="all">P-39. What is the school/learning institution status of [person]?<br /><div class="i1">[] 1 At school/learning institution<br />[] 2 Left school/learning institution<br />[] 3 Never went to school/learning institution<br />[] 9 Unknown</div><br /></svar> <svar v="KE09A432 KE09A433 KE09A434">- <span class="em">Section D</span>: Information regarding education status for persons aged 3 years old and above. This section covers columns p39 to p41. Questions on education shall be asked of all persons aged 3 years and above.<br /></svar></p> <p><span class="h3">33. Section D: Education status for persons aged 3 years and above </span></p> <p><span class="em">33.1 Columns P39, P40 and P41: Education</span> <br />Questions on education are applicable to persons aged 3 years and above and refer to formal, non-formal and other education. The categories under formal education are; pre-primary, primary, secondary, middle level colleges and university. Non-formal education is any other form of education that does not follow the standard curriculum of the formal system but offers numeric and literacy skills e.g. adult education and youth/village polytechnic education. "Other" education refers to Madrassa and Duksis etc.</p> <p><span class="em">33.2 Definitions</span><div class="i1">- <span class="em">School/learning center: </span> This is an institution that offers learning to particular group of persons in a given level of education.<br />- <span class="em">Early childhood development (ECD): </span> This is an education program offered to provide holistic integrated services that create a strong foundation for the child's cognitive (talents), psycho-social, moral, spiritual, emotional and psychomotor (physical education-PE) needs. The official target group are the children aged 3 to 5 years.<br />- In this level of formal education, pupils attend schooling in three levels: baby class, nursery and pre-unit. In some regions the term used is kindergarten 1, kindergarten 2 and kindergarten 3.<br />- <span class="em">Primary: </span> This is the first 8 years of basic education in the formal system. In this level, pupils go through 8 grades: Std. 1 to Std. 8. At the end of the cycle, they sit the Kenya Certificate of Primary Education (KCPE). However, in the previous education system (7-4-2-3) there was the Certificate of Primary Education (CPE) at the end of primary in Standard 7.<br />- <span class="em">Secondary: </span> This is the education offered for 4 years after primary education. In this level, also referred to as Ordinary (O)-level, the students attend schooling in 4 grades: Form 1 to Form 4. At the end the cycle they sit the Kenya Certificate of Secondary Education (KCSE). In the previous education system, students attended O-level and Advanced (A)-level for 2 years in form 5 and form 6 after which they sat the Kenya Advanced Certificate of Education (KACE).<br />- <span class="em">Non-Formal Education (NFE): </span> This is an education program that offers flexible learning for adults and school going children who are not able to join the formal system of education. In this system, the learners are categorized into three levels: basic, post-literacy, and technical.<br />- Basic education involves mainly teaching numeric and literacy skills. A pupil is considered to have achieved basic level of education after sitting and passing the proficiency examination.<br />- Post Literacy education involves teaching of all the examinable subjects at primary education. The learner is also expected to sit for either a Proficiency examination or Kenya Certificate of Primary Education (KCPE)<br />- Technical education is offered to learners in NFE centers to provide life skills to the disadvantaged population.<br />- <span class="em">Non-formal schools: </span> These are schools that are not registered with the Ministry of Education but follow the formal primary school curriculum. They are registered by the office of the Attorney General/Ministry of Social Services to offer education services to needy population.<br />- <span class="em">Youth polytechnic: </span> This is a non-formal education program offered to primary school leavers or those with some secondary education who are interested in technical skills. They offer artisan courses lasting between 1 to 3 years such as artisan 1 and 2 followed by craft 1 and 2 such as carpentry, masonry, electrical, hair dressing and tailoring etc.<br />- <span class="em">Tertiary education (middle level colleges): </span> This is a post-secondary education program that offers various disciplines at certificate and diploma level. The program caters for the students who have completed secondary education and did not join university education. The institutions are of specific disciplines such as primary teacher training colleges that offer primary teaching certificate; medical training colleges offer certificate and diploma in nursing/clinical medicine etc. ; agriculture training colleges; media colleges; ICT colleges; technical training institutes; national polytechnics among others.<br />- <span class="em">University: </span> This is a formal education program that allows learners to move to the last cycle of formal education. The courses offered are varied in all the sectors leading to professionals. The students are also allowed to pursue further education in university postgraduate programs on masters for 2 years and doctorate for 3 years and above.</div><svar v="KE09A432" a="all"><span class="em">33.3 Column P39: School /learning institution attendance</span><br /><br /><span class="em">Ask: </span>What is the school/learning institution attendance status of [the respondent]?<br />Record "1" for persons attending school this year, "2" for persons who have left school, "3" for persons who have never been to school, and "9 for persons whose schooling status is not known. Leave the box blank if the respondent is below 3 years.<br /></svar> Kenya 2009: Persons age 3+ [discrepancies: none] This variable indicates the person's school enrollment status. 1 At school 2 Left school 3 Never went to school 8 Unknown 9 NIU (not in universe) Education Variables -- PERSON Highest education level <svar v="KE09A432 KE09A433 KE09A434"><span class="h3">D: Information regarding persons aged 3 years and above</span><br /> [Questions P-39 to P-41 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A433" a="all">P-40. What is the highest standard/form/level reached by [person]? _ _<br /><div class="i1">The code list is provided. Write "97" if P-39 equals 3 or 9.</div><br /></svar> <svar v="KE09A432 KE09A433 KE09A434">- <span class="em">Section D</span>: Information regarding education status for persons aged 3 years old and above. This section covers columns p39 to p41. Questions on education shall be asked of all persons aged 3 years and above.<br /></svar></p> <p><span class="h3">33. Section D: Education status for persons aged 3 years and above </span></p> <p><span class="em">33.1 Columns P39, P40 and P41: Education</span> <br />Questions on education are applicable to persons aged 3 years and above and refer to formal, non-formal and other education. The categories under formal education are; pre-primary, primary, secondary, middle level colleges and university. Non-formal education is any other form of education that does not follow the standard curriculum of the formal system but offers numeric and literacy skills e.g. adult education and youth/village polytechnic education. "Other" education refers to Madrassa and Duksis etc.</p> <p><span class="em">33.2 Definitions</span><div class="i1">- <span class="em">School/learning center: </span> This is an institution that offers learning to particular group of persons in a given level of education.<br />- <span class="em">Early childhood development (ECD): </span> This is an education program offered to provide holistic integrated services that create a strong foundation for the child's cognitive (talents), psycho-social, moral, spiritual, emotional and psychomotor (physical education-PE) needs. The official target group are the children aged 3 to 5 years.<br />- In this level of formal education, pupils attend schooling in three levels: baby class, nursery and pre-unit. In some regions the term used is kindergarten 1, kindergarten 2 and kindergarten 3.<br />- <span class="em">Primary: </span> This is the first 8 years of basic education in the formal system. In this level, pupils go through 8 grades: Std. 1 to Std. 8. At the end of the cycle, they sit the Kenya Certificate of Primary Education (KCPE). However, in the previous education system (7-4-2-3) there was the Certificate of Primary Education (CPE) at the end of primary in Standard 7.<br />- <span class="em">Secondary: </span> This is the education offered for 4 years after primary education. In this level, also referred to as Ordinary (O)-level, the students attend schooling in 4 grades: Form 1 to Form 4. At the end the cycle they sit the Kenya Certificate of Secondary Education (KCSE). In the previous education system, students attended O-level and Advanced (A)-level for 2 years in form 5 and form 6 after which they sat the Kenya Advanced Certificate of Education (KACE).<br />- <span class="em">Non-Formal Education (NFE): </span> This is an education program that offers flexible learning for adults and school going children who are not able to join the formal system of education. In this system, the learners are categorized into three levels: basic, post-literacy, and technical.<br />- Basic education involves mainly teaching numeric and literacy skills. A pupil is considered to have achieved basic level of education after sitting and passing the proficiency examination.<br />- Post Literacy education involves teaching of all the examinable subjects at primary education. The learner is also expected to sit for either a Proficiency examination or Kenya Certificate of Primary Education (KCPE)<br />- Technical education is offered to learners in NFE centers to provide life skills to the disadvantaged population.<br />- <span class="em">Non-formal schools: </span> These are schools that are not registered with the Ministry of Education but follow the formal primary school curriculum. They are registered by the office of the Attorney General/Ministry of Social Services to offer education services to needy population.<br />- <span class="em">Youth polytechnic: </span> This is a non-formal education program offered to primary school leavers or those with some secondary education who are interested in technical skills. They offer artisan courses lasting between 1 to 3 years such as artisan 1 and 2 followed by craft 1 and 2 such as carpentry, masonry, electrical, hair dressing and tailoring etc.<br />- <span class="em">Tertiary education (middle level colleges): </span> This is a post-secondary education program that offers various disciplines at certificate and diploma level. The program caters for the students who have completed secondary education and did not join university education. The institutions are of specific disciplines such as primary teacher training colleges that offer primary teaching certificate; medical training colleges offer certificate and diploma in nursing/clinical medicine etc. ; agriculture training colleges; media colleges; ICT colleges; technical training institutes; national polytechnics among others.<br />- <span class="em">University: </span> This is a formal education program that allows learners to move to the last cycle of formal education. The courses offered are varied in all the sectors leading to professionals. The students are also allowed to pursue further education in university postgraduate programs on masters for 2 years and doctorate for 3 years and above.</div><svar v="KE09A433" a="all"><span class="em">33.4 Column P40: Highest standard/form/level of education reached</span><br /><br /><span class="em">Ask: </span>What is the highest standard/form/level of education reached by [the respondent]?<br />Code in column P40 the highest level of formal education the person has reached from the provided code list: For example, if a person reached standard 4 and dropped out of school before completing, he/she should be coded "4". If a person is attending an adult education basic literacy class he/she should be coded "21". However, if the person is enrolled for standard 8 examinations in adult literacy center then he/she should be coded "8". If a person is attending a course in a youth polytechnic, he/she should be coded "23", if the person has completed the youth polytechnic code "24"etc. If a person is attending a course in a middle level college (post-secondary education), he/she should be coded "15", if the person has completed the Middle Level College code "16"etc. Code "25" if a person is attending madrassa/duksi, and "26" if the person has completed madrassa/duksi. If P39=3 or 9 then write 97. If a person completed for example form four and enrolled in four three, code level of education reached as form four and current level as four three.<br /></svar> Kenya 2009: Persons age 3+ [discrepancies: none] This variable indicates the highest education level that the person attended. 01 Standard 1 02 Standard 2 03 Standard 3 04 Standard 4 05 Standard 5 06 Standard 6 07 Standard 7 08 Standard 8 09 Form 1 10 Form 2 11 Form 3 12 Form 4 13 Form 5 14 Form 6 15 Incomplete tertiary college 16 Completed college 17 Incomplete undergraduate 18 Completed undergraduate 19 Incomplete Masters/PhD 20 Completed Masters/PhD 21 Incomplete basic literacy 22 Completed basic literacy 23 Incomplete polytechnic 24 Completed polytechnic 25 Incomplete Madrassa 26 Completed Madrassa 96 Pre-primary 97 Never attended 98 Unknown 99 NIU (not in universe) Education Variables -- PERSON Highest education level completed <svar v="KE09A432 KE09A433 KE09A434"><span class="h3">D: Information regarding persons aged 3 years and above</span><br /> [Questions P-39 to P-41 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A434" a="all">P-41. What is the highest standard/form/level completed by [person]? _ _<br /><div class="i1">The code list is provided. Write "97" if P-39 equals 3 or 9.</div><br /></svar> <svar v="KE09A432 KE09A433 KE09A434">- <span class="em">Section D</span>: Information regarding education status for persons aged 3 years old and above. This section covers columns p39 to p41. Questions on education shall be asked of all persons aged 3 years and above.<br /></svar></p> <p><svar v="KE09A434" a="all"><span class="em">33.5 Column P41: Highest standard/form/level of education completed</span><br /><br /><span class="em">Ask</span>: What is the highest standard/form/level completed by [the respondent]?<br />If a person was at school in standard 4 and left before completing, he/she should be coded as having completed standard 3 hence code "3". If a person is at school and is attending standard 4, he/she should be coded as having completed standard 3 hence code "3". Refer to the code list provided. If P39=3 or 9 then write 97.<br /><div class="i1">- The simple rule here is that for all persons attending school this year the highest level completed should be one level lower than the highest level reached and for persons not attending school during the year, the highest level completed may be the same as the highest level reached or one level below it, but not greater.<br />- For example: record the highest class or form the person has completed in the formal primary and secondary school system e.g. a person in form one will have completed standard 8 and therefore should be coded as having completed standard 8, while those who have completed form one should be coded "9".<br />- If a person has not gone to a formal school but has sat for KCPE/CPE or 'O' level or 'A' level exams, through correspondence or adult and continuing education classes code his/her highest level of education according to the highest exam he/she has sat and passed e.g. code "8" for KCPE exams passed or code "12" for 'O' level exams passed etc.<br />- If a person has attended youth polytechnic but never completed or is currently attending the youth polytechnic studies and he finished Std. 8 then code "8" or he finished Form 3 then code '11': If the person has completed the youth polytechnic studies then code "24".<br />- If a person has attended university but never completed or is currently attending undergraduate studies and his/her last level completed was Form 4 then code "12" and if his/her last level was Form 6, then code "14": If the person has completed undergraduate, then, code "18". If the person is attending a masters or a doctorate degree then his completed level is undergraduate, and code "19".</div><br /></svar> Kenya 2009: Persons age 3+ [discrepancies: type I none; type II 1.0%] This variable indicates the highest education level that the person completed. 01 Standard 1 02 Standard 2 03 Standard 3 04 Standard 4 05 Standard 5 06 Standard 6 07 Standard 7 08 Standard 8 09 Form 1 10 Form 2 11 Form 3 12 Form 4 13 Form 5 14 Form 6 16 Completed college 18 Completed undergraduate 20 Completed Masters/PhD 22 Completed basic literacy 24 Completed polytechnic 26 Completed Madrassa 96 Pre-primary 97 Never attended 98 Unknown 99 NIU (not in universe) Education Variables -- PERSON Economic activity in the last 7 days <svar v="KE09A435 KE09A436 KE09A437"><span class="h3">E: Labour force particulars</span><br /><span class="em">Economic activity</span><br /> [Question 42 was asked of all individuals age 5+.]<br /></svar></p> <p><svar v="KE09A435" a="all">P-42. What was [person] mainly doing during the last 7 days preceding the census night? _ _<br /><div class="i1">The code list is provided.</div><br /></svar> <svar v="KE09A435 KE09A436 KE09A437">- <span class="em">Section E</span>: Labor force particulars. This section covers columns p42 to p44 and should be asked of all persons 5 years old and above.<br /></svar></p> <p><svar v="KE09A435 KE09A436 KE09A437"><span class="h3">34. Section E: Labor force participation</span><br /><br />[Questions 42 to 44 are asked of all persons 5 years old and over.]<br /><br /><span class="em">34.1 Column P42 to P44:</span><br /><br />This section involves collection of labor statistics, mainly used for employment policies and programs and for projecting future labor force. The questions are asked to <span class="em">all persons aged 5 years and above</span> and refer to the <span class="em">last seven days preceding the Census night</span>. However, the reference period for those who held a job (on leave or on sick leave) falls outside the last seven days.<br /></svar></p> <p><svar v="KE09A435" a="all"><span class="em">34.2 Column P42: Main activity</span><br /><br /><span class="em">Ask: </span>What was [the respondent] mainly doing during the last seven days preceding the <span class="em">Census Night</span>?<br /><br />What the respondent was <span class="em">mainly</span> doing will denote the activity that occupied most of the respondent's time during the 7 days preceding the <span class="em">Census Night</span>. The codes for the possible responses in column P42 are provided, and are defined here below:<br /><div class="i1"><span class="em">- Worked for pay</span><br />This comprises persons who, during the 7 days preceding the <span class="em">Census Night</span>, 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).<br /><span class="em">- On leave</span><br />This group comprises all those with formal attachments to a job or business/enterprise but were not working during the reference period. This includes people on any of the following type of leave: annual, maternity, paternity, terminal, compulsory leave etc. A person who is on leave such as a teacher but worked on family holding in the past 7 days preceding <span class="em">Census Night</span>should be indicated as on leave.<br /><span class="em">- Sick leave</span><br />These are persons who during the reference period were sick and on leave with permission.<br /><span class="em">- Worked on own/family business</span><br />This category comprises of 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. Any member of the household working on the holding for pay will fall under code "1 ".<br /><span class="em">- Worked on own/family agricultural holding</span><br />A holding in this case is the unit of land, farm or shamba which is owned or leased by the family and is used for purposes of cultivation or rearing livestock. All the members of the household who are working on the holding without pay/profit will be coded "5" (i.e. working on own/family agricultural holding). Any member of the household working on the holding for pay will fall under code "1" (i.e. worked for pay).<br /><span class="em">NB</span>: You are to probe to find out whether unpaid family workers consider themselves as 'seeking work', etc. and code them accordingly. For example, if a young man helps his uncle to sell goods in a kiosk without receiving pay, probe whether he is 'seeking work' and code him appropriately; if he considers himself as working code him as "4".<br /><span class="em">- Apprentice/intern</span><br />An apprentice is a person whose training is done on the job for an agreed period of time. This includes students on attachment. This helps the apprentices learn their trade, in exchange for their labor. An intern on the other hand is one who works in a temporary position with an emphasis on on-the-job training rather than merely employment, making it similar to an apprenticeship. In most cases, an intern will have completed a certain level of education or training. Interns or apprentices are usually college or university students, but they can also be high school students or post graduate students seeking skills for a new career. Student internships/apprenticeship provide opportunities for students to gain experience in their field, determine if they have an interest in a particular career, create a network of contacts, or gain school credit. The person may be unpaid or partially paid (in the form of a stipend).<br /><span class="em">- Volunteer</span><br />This is a person who works for free in an organization primarily because they choose to do so. Many serve through a non-profit organization - sometimes referred to as formal volunteering, but a significant number also serve less formally, either individually or as part of a group. These people do not receive any compensation for services rendered other than reimbursement for out-of pocket expenses.<br /><span class="em">- Seeking work (action taken)</span><br />This refers to a person who, in the 7 days preceding the <span class="em">Census Night</span>, was neither working nor holding a job, but was available to take up a job and was actively looking for work. It should only include persons who have no work at all and are looking for work. It includes only persons who are available full time for work and hence are actively looking for it. This category should not include the under-employed (i.e. those who have paid work but wish to leave for better opportunities). If a person is working on the family holding but is seeking work, he/she should be coded as "seeking work" and not as "working on family holding".<br /><span class="em">- Seeking work (no action taken)</span><br />This refers to a person who, in the 7 days preceding the <span class="em">Census Night</span>, was neither working nor holding a job. The person should be available to take up a job but did not actively seek for work in the reference period.<br /><span class="em">- No work available</span><br />This is a person who is not working nor seeking for work because he/she is discouraged, but would usually take up a job when offered one.<br /><span class="em">- Retired</span><br />This is a person who reports that, during the 7 days preceding the <span class="em">Census Night </span>, 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 "1", "4" or "5". If he/she has retired and is actively seeking work he/she should be coded as "8".<br /><span class="em">- Homemaker</span><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 "1". If such a person worked on family business or agricultural holding they should be coded as "4" or "5" and not as "12". Please probe.<br /><span class="em">- Full-time student</span><br />This is a person who spent most of his/her time in a regular educational institution (primary, secondary, college, university etc.) and hence not available for work. If, for instance, a student was on holiday during the 7 days preceding the <span class="em">Census Night</span>and may have been engaged in gainful employment, he/she should be given the appropriate code (i.e. worked for pay, worked on own, family business etc.).<br /><span class="em">- Incapacitated</span><br />This is a person who cannot work. Do not assume that all physically disabled persons cannot work. For example, a blind person who is in wage employment will fall under category "1" and not "14". Similarly, lame/crippled persons working on the family business or agricultural holding should fall under category "4" or "5". Please probe.<br /><span class="em">- Other (specify)</span><br />This category includes any other persons not mentioned above. <br />NB: For persons aged below 5 years, leave column P42 blank. For respondents aged 5 years and above whose labor force participation status is not known or not stated, write "99".</div><br /></svar> Kenya 2009: Persons age 5+ [discrepancies: type I 2.7%; type II none] This variable indicates the person's main type of economic activity in the last 7 days. 01 Worked for pay 02 On leave 03 Sick leave 04 Own - family business 05 Own - family agriculture holding 06 Intern/Apprentice 07 Volunteer 08 Seeking work (action taken) 09 Seeking work (no action taken) 10 No work available 11 Retired 12 Homemaker 13 Full time student 14 Incapacitated 15 Other 99 NIU (not in universe) Work Variables -- PERSON Main employer <svar v="KE09A435 KE09A436 KE09A437"><span class="h3">E: Labour force particulars</span><br /><span class="em">Economic activity</span><br /> [Question 42 was asked of all individuals age 5+.]<br /></svar></p> <p><svar v="KE09A436 KE09A437">For those who worked or held a job (including those on leave/sick leave). <br /> [P-43 and P-44 were asked of all individuals age 5+ who worked or held a job in the 7 days preceding the census night.]<br /></svar></p> <p><svar v="KE09A436" a="all">P-43. Who was [person's] main employer? _ _<br /><div class="i1">The code list is provided. Code "99" for not applicable.</div><br /></svar> <svar v="KE09A435 KE09A436 KE09A437">- <span class="em">Section E</span>: Labor force particulars. This section covers columns p42 to p44 and should be asked of all persons 5 years old and above.<br /></svar></p> <p><svar v="KE09A435 KE09A436 KE09A437"><span class="h3">34. Section E: Labor force participation</span><br /><br />[Questions 42 to 44 are asked of all persons 5 years old and over.]<br /><br /><span class="em">34.1 Column P42 to P44:</span><br /><br />This section involves collection of labor statistics, mainly used for employment policies and programs and for projecting future labor force. The questions are asked to <span class="em">all persons aged 5 years and above</span> and refer to the <span class="em">last seven days preceding the Census night</span>. However, the reference period for those who held a job (on leave or on sick leave) falls outside the last seven days.<br /></svar></p> <p><svar v="KE09A436" a="all"><span class="em">34.3 Column 43: Main employer</span><br /><br />Each person who is working will be asked for whom they work for. This question applies to respondents whose response in column P42 is codes 1 - 7, and code 15. The code list for the main employer will be provided. To clarify:<br /><div class="i1">- Employment sector refers to whether the employment is public (governmental) or private (non-governmental).<br />- Public sector covers all activities and establishments of the Central Government, its statutory corporations (wholly owned corporations or parastatals), registered companies in which the Government is a majority shareholder, and all Local Government authorities.<br />- State owned enterprise refers to semi-public.<br />- Private sector is categorized into private company or private individual (or household).<br />- A Non-Governmental Organization (NGO) is a non-profit making body which mainly engages in charity work.<br />- A Faith-Based Organization (FBO) is a group that references God or Allah. It includes 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.<br />- Examples of self-employed modern sector includes doctors, lawyers in private practice etc. whose businesses are registered with the registrar of companies.<br />- International NGOs includes: CARE international, OXFAM, Plan International, ActionAid, Safe the Child UK, International Red Cross, GTZ etc.<br />- Local NGOs includes: Green Belt Movement, Family Health Options Kenya, Federation of Women Lawyers - Kenya chapter (FIDA) etc.<br /><br /><span class="em">Selected examples</span></div><br /><div class="i2">- A person employed by the Kenya National Bureau of Statistics (KNBS) as a cleaner will be classified as working in State owned enterprise (code "5")<br />- If KNBS outsourced cleaning services from a private company, the cleaner will be classified as working in Private owned enterprise (code "1").<br />- A person who works as a cleaning person in someone's home will be classified in Individual/Private household (code "16").<br />- A person working in a Parish or Mosque should be coded as working for an FBO (code "8").<br />- 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 registral of companies. (Code "11").</div><br /></svar> Kenya 2009: Persons age 5+ who had a job [discrepancies: none] This variable indicates the sector of the person's main employer. 01 Private sector 02 Local authorities 03 Central government 04 Teachers service commission (TSC) 05 State-owned enterprise 06 International NGO 07 Local NGO 08 Faith-based organisation 09 Self modern 10 Informal sector ('Jua Kali') 11 Self employed, informal 12 Small scale agriculture 13 Self small scale agriculture 14 Pastoralist employed 15 Self pastoralist 16 Private household 17 Other 99 NIU (not in universe) Work Variables -- PERSON Hours worked in the last 7 days <svar v="KE09A435 KE09A436 KE09A437"><span class="h3">E: Labour force particulars</span><br /><span class="em">Economic activity</span><br /> [Question 42 was asked of all individuals age 5+.]<br /></svar></p> <p><svar v="KE09A436 KE09A437">For those who worked or held a job (including those on leave/sick leave). <br /> [P-43 and P-44 were asked of all individuals age 5+ who worked or held a job in the 7 days preceding the census night.]<br /></svar></p> <p><svar v="KE09A437" a="all">P-44. How many hours did [person] work in the last 7 days preceding the census night? _ _<br /><div class="i1">Code "99" for not applicable.</div><br /></svar> <svar v="KE09A435 KE09A436 KE09A437">- <span class="em">Section E</span>: Labor force particulars. This section covers columns p42 to p44 and should be asked of all persons 5 years old and above.<br /></svar></p> <p><svar v="KE09A435 KE09A436 KE09A437"><span class="h3">34. Section E: Labor force participation</span><br /><br />[Questions 42 to 44 are asked of all persons 5 years old and over.]<br /><br /><span class="em">34.1 Column P42 to P44:</span><br /><br />This section involves collection of labor statistics, mainly used for employment policies and programs and for projecting future labor force. The questions are asked to <span class="em">all persons aged 5 years and above</span> and refer to the <span class="em">last seven days preceding the Census night</span>. However, the reference period for those who held a job (on leave or on sick leave) falls outside the last seven days.<br /></svar></p> <p><svar v="KE09A437" a="all"><span class="em">34.4 Column P44: Hours of work</span><br /><br />This question applies to respondents whose response in column P42 is code 1- 7 and code 15. Hours usually worked is the typical value of hours actually worked in a job per short reference period such as one week, over a long observation period of a month, quarter, season or year that comprises the short reference measurement period used. The hours usually worked provides a way to obtain regular hours worked above contractual hours. The enumerator in this case should seek to establish usual hours worked in the last seven days. If a person has worked 5 hours per day for six days in the last 7 days, then the enumerator should record 30 hours (for a 6 days worked period). Note that for those who did not work in the last seven days but held a job, the enumerator should ask "How many hours does [the respondent] usually work in a week?" The week in this case is refers to the last seven days.<br /></svar> Kenya 2009: Persons age 5+ who worked or were on leave [type I 0.6%; type II 5.8%] This variable indicates the number of hours that the person worked in the last 7 days. 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 38 039 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 98 998 Unknown 999 NIU (not in universe) Work Variables -- PERSON Radio service <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444" a="all"><span class="h3">F: Information regarding ICT</span><br />(To be asked of persons aged 3 years and above)<br />[Questions P-45 to P-51 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">Was [person] able to get a service from the following items within the last one month?<br /></svar></p> <p><svar v="KE09A438"><div class="i1">P.-45. Radio</div><br /><div class="i2">[] 1 Yes<br />[] 2 No<br />[] 3 Unknown</div><br /></svar> <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444">- <span class="em">Section F</span>: Information regarding ICT (information, communication and technology). It covers columns P45 to P51 and applies to all persons 3 years old and above<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">[Questions 45 to 49 are asked of all persons 3 years old and over.]<br /><br /><span class="em">35.2 Column P45 to P49: Accessibility</span><br /><br />This question seeks information on the ability of household members to get services from basic information and communication facilities within the past one month. The ICT facilities include radio, television (TV), mobile phone, landline telephone and a computer. Response to each of the question from eligible members of the household is either a yes =1 or no=2. Code in the appropriate box for all eligible members of the household i.e. those aged 3 years and above.<br /></svar></p> <p><svar v="KE09A438">- <span class="em">A Radio </span>is a device capable of receiving broadcast radio signals using common frequencies such as FM, AM, LW, and SW. Radios also include those combined with other equipment such as cassette players/recorders, portable radios such as transistor radios, and radios in motor vehicles.<br /></svar> Kenya 2009: Persons age 3+ [discrepancies: none] This variable indicates whether the person was able to get radio service in the past month. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON TV service <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444" a="all"><span class="h3">F: Information regarding ICT</span><br />(To be asked of persons aged 3 years and above)<br />[Questions P-45 to P-51 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">Was [person] able to get a service from the following items within the last one month?<br /></svar></p> <p><svar v="KE09A439"><div class="i1">P-46. TV set</div><br /><div class="i2">[] 1 Yes<br />[] 2 No<br />[] 3 Unknown</div><br /></svar> <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444">- <span class="em">Section F</span>: Information regarding ICT (information, communication and technology). It covers columns P45 to P51 and applies to all persons 3 years old and above<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">[Questions 45 to 49 are asked of all persons 3 years old and over.]<br /><br /><span class="em">35.2 Column P45 to P49: Accessibility</span><br /><br />This question seeks information on the ability of household members to get services from basic information and communication facilities within the past one month. The ICT facilities include radio, television (TV), mobile phone, landline telephone and a computer. Response to each of the question from eligible members of the household is either a yes =1 or no=2. Code in the appropriate box for all eligible members of the household i.e. those aged 3 years and above.<br /></svar></p> <p><svar v="KE09A439">- <span class="em">A Television </span>is a device capable of receiving broadcast television signals, using common access means such as over-the-air or satellite. A TV set may be a stand-alone device, or it may be integrated into another device such as a computer or a mobile phone. A TV set shows pictures on a screen in addition to the voice broadcast.<br /></svar> Kenya 2009: Persons age 3+ [discrepancies: none] This variable indicates whether the person was able to get TV service in the past month. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Mobile phone service <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444" a="all"><span class="h3">F: Information regarding ICT</span><br />(To be asked of persons aged 3 years and above)<br />[Questions P-45 to P-51 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">Was [person] able to get a service from the following items within the last one month?<br /></svar></p> <p><svar v="KE09A440"><div class="i1">P-47. Mobile Phone</div><br /><div class="i2">[] 1 Yes<br />[] 2 No<br />[] 3 Unknown</div><br /></svar> <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444">- <span class="em">Section F</span>: Information regarding ICT (information, communication and technology). It covers columns P45 to P51 and applies to all persons 3 years old and above<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">[Questions 45 to 49 are asked of all persons 3 years old and over.]<br /><br /><span class="em">35.2 Column P45 to P49: Accessibility</span><br /><br />This question seeks information on the ability of household members to get services from basic information and communication facilities within the past one month. The ICT facilities include radio, television (TV), mobile phone, landline telephone and a computer. Response to each of the question from eligible members of the household is either a yes =1 or no=2. Code in the appropriate box for all eligible members of the household i.e. those aged 3 years and above.<br /></svar></p> <p><svar v="KE09A440">- <span class="em">Mobile phone </span>(also called <span class="em">cell phone, hand phone, cellular phone, cell, mobile telephone or cell telephone</span>) is a long-range, electronic device used for mobile voice or data communication over a network of specialized base stations known as cell sites which are in turn interconnected to the public switched telephone network (PSTN).<br /></svar> Kenya 2009: Persons age 3+ [discrepancies: none] This variable indicates whether the person was able to get mobile phone service in the past month. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Landline telephone service <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444" a="all"><span class="h3">F: Information regarding ICT</span><br />(To be asked of persons aged 3 years and above)<br />[Questions P-45 to P-51 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">Was [person] able to get a service from the following items within the last one month?<br /></svar></p> <p><svar v="KE09A441"><div class="i1">P-48. Landline</div><br /><div class="i2">[] 1 Yes<br />[] 2 No<br />[] 3 Unknown</div><br /></svar> <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444">- <span class="em">Section F</span>: Information regarding ICT (information, communication and technology). It covers columns P45 to P51 and applies to all persons 3 years old and above<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">[Questions 45 to 49 are asked of all persons 3 years old and over.]<br /><br /><span class="em">35.2 Column P45 to P49: Accessibility</span><br /><br />This question seeks information on the ability of household members to get services from basic information and communication facilities within the past one month. The ICT facilities include radio, television (TV), mobile phone, landline telephone and a computer. Response to each of the question from eligible members of the household is either a yes =1 or no=2. Code in the appropriate box for all eligible members of the household i.e. those aged 3 years and above.<br /></svar></p> <p><svar v="KE09A441">- <span class="em">Landline telephone </span>refer to fixed telephone lines connecting to a customer's terminal equipment (e.g. telephone headset, facsimile machine etc.) to the PSTN and which have a dedicated port on a telephone exchange.<br /></svar> Kenya 2009: Persons age 3+ [discrepancies: none] This variable indicates whether the person was able to get landline telephone service in the past month. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Computer service <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444" a="all"><span class="h3">F: Information regarding ICT</span><br />(To be asked of persons aged 3 years and above)<br />[Questions P-45 to P-51 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">Was [person] able to get a service from the following items within the last one month?<br /></svar></p> <p><svar v="KE09A442"><div class="i1">P-49. Computer</div><br /><div class="i2">[] 1 Yes<br />[] 2 No<br />[] 3 Unknown</div><br /></svar> <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444">- <span class="em">Section F</span>: Information regarding ICT (information, communication and technology). It covers columns P45 to P51 and applies to all persons 3 years old and above<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">[Questions 45 to 49 are asked of all persons 3 years old and over.]<br /><br /><span class="em">35.2 Column P45 to P49: Accessibility</span><br /><br />This question seeks information on the ability of household members to get services from basic information and communication facilities within the past one month. The ICT facilities include radio, television (TV), mobile phone, landline telephone and a computer. Response to each of the question from eligible members of the household is either a yes =1 or no=2. Code in the appropriate box for all eligible members of the household i.e. those aged 3 years and above.<br /></svar></p> <p><svar v="KE09A442">- <span class="em">Computer</span> includes a desktop, portable (laptop) or handheld computer (PDA). It does not include equipment with enabled computing abilities such as a mobile phone or TV sets.<br /></svar> Kenya 2009: Persons age 3+ [discrepancies: none] This variable indicates whether the person was able to get computer service in the past month. 1 Yes 2 No 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Internet use <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444" a="all"><span class="h3">F: Information regarding ICT</span><br />(To be asked of persons aged 3 years and above)<br />[Questions P-45 to P-51 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">Was [person] able to get a service from the following items within the last one month?<br /></svar></p> <p><svar v="KE09A443" a="all">P-50. How often does [person] use internet (e.g. email, chatting, etc.)?<br /><div class="i1">[] 1 Daily<br />[] 2 Weekly<br />[] 3 Monthly<br />[] 4 Yearly<br />[] 5 Never<br />[] 9 Unknown</div><br /></svar> <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444">- <span class="em">Section F</span>: Information regarding ICT (information, communication and technology). It covers columns P45 to P51 and applies to all persons 3 years old and above<br /></svar></p> <p><svar v="KE09A443" a="all">[Questions 50 and 51 are asked of all persons 3 years old and over.]<br /><br /><span class="em">35.3 Column P50: Frequency of access to the internet services</span><br />The question seeks to establish how frequently eligible members of the household access and use internet services. Frequency of access could either be <span class="em">daily, weekly, monthly or yearly</span>. Record the response given by the respondent by entering the appropriate <span class="em">code: 1 to 4</span>. If a member of the household has <span class="em">never</span> used internet enter code 5.<br /></svar> Kenya 2009: Persons age 3+ [discrepancies: none] This variable indicates how often the person uses the internet. 1 Daily 2 Weekly 3 Monthly 4 Yearly 5 Never 8 Unknown 9 NIU (not in universe) Other Person Variables -- PERSON Main internet location <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444" a="all"><span class="h3">F: Information regarding ICT</span><br />(To be asked of persons aged 3 years and above)<br />[Questions P-45 to P-51 were asked of all individuals age 3+.]<br /></svar></p> <p><svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442" a="all">Was [person] able to get a service from the following items within the last one month?<br /></svar></p> <p><svar v="KE09A444" a="all">P-51. Where did [person] mainly use the internet?<br /><div class="i1">[Question P-51 was asked for all individuals age 3+ who indicated that they have used internet P-50 had a response of 1, 2, 3, or 4)]<br /><br />[] 1 Own house<br />[] 2 A friend's house<br />[] 3 Office/workplace<br />[] 4 Cyber café<br />[] 5 Community center<br />[] 6 Educational center<br />[] 7 Other<br />[] 8 Mobile phone <br />[] 9 Unknown</div><br /></svar> <svar v="KE09A438 KE09A439 KE09A440 KE09A441 KE09A442 KE09A443 KE09A444">- <span class="em">Section F</span>: Information regarding ICT (information, communication and technology). It covers columns P45 to P51 and applies to all persons 3 years old and above<br /></svar></p> <p><svar v="KE09A444" a="all">[Questions 50 and 51 are asked of all persons 3 years old and over.]<br /><br /><span class="em">35.4 Column P51: Place where internet was accessed</span><br />This question seeks to establish the location where services for internet are mainly accessed. Enter the appropriate codes for response given.<br /></svar> Kenya 2009: Persons age 3+ who used the internet [discrepancies: none] This variable indicates the location where the person mainly used the internet in the last month. 01 Own house 02 Friends house 03 Office/workplace 04 Cyber cafe 05 Community centre 06 Educational centre 07 Other 08 Mobile phones 98 Unknown 99 NIU (not in universe) Other Person Variables -- PERSON Imputation flag: age Kenya 2009: All persons This variable indicates if the person's age was imputed. 1 Imputed 2 Not imputed Person Imputation Flags Variables -- PERSON Imputation flag: school Kenya 2009: All persons This variable indicates whether the person's school enrollment status was imputed. 1 Imputed 2 Not imputed Person Imputation Flags Variables -- PERSON Imputation flag: fertility Kenya 2009: All persons This variable indicates if fertility was imputed for this person. 1 Imputed 2 Not imputed Person Imputation Flags Variables -- PERSON