Demographic and Health Survey 2014
Kenya, 2014
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Reference ID
KEN_2014_DHS_v01_M
Producer(s)
Kenya National Bureau of Statistics
Collection(s)
Metadata
Created on
Jan 20, 2016
Last modified
Oct 01, 2019
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Identification
Survey ID Number
KEN_2014_DHS_v01_M
Title
Demographic and Health Survey 2014
Country/Economy
| Name | Country code |
|---|---|
| Kenya | KEN |
Study type
Demographic and Health Survey (Standard) - DHS VII
Series Information
The 2014 Kenya Demographic and Health Survey is the fifth of its kind and follows similar surveys conducted in 1989, 1993, 1998, 2003, and 2008-09. The 2014 KDHS provides information to help monitor and evaluate population and health status in Kenya. In 2014 KDHS, new indicators not collected in previous KDHS surveys, such as noncommunicable diseases, fistula, and men’s experience of domestic violence, are included. Also, it is the first national survey to provide estimates for demographic and health indicators at the county level. Following adoption of a constitution in Kenya in 2010 and devolution of administrative powers to the counties, the new 2014 KDHS data should be valuable to managers and planners.
The 2014 KDHS has specifically collected data to estimate fertility, to assess childhood, maternal, and adult mortality, to measure changes in fertility and contraceptive prevalence, to examine basic indicators of maternal and child health, to estimate nutritional status of women and children, to describe patterns of knowledge and behaviour related to the transmission of HIV and other sexually transmitted infections, and to ascertain the extent and pattern of domestic violence and female genital cutting. Unlike the 2003 and 2008-09 KDHS surveys, this survey did not include HIV and AIDS testing. HIV prevalence estimates are available from the 2012 Kenya AIDS Indicator Survey (KAIS), completed prior to the 2014 KDHS.
The 2014 KDHS has specifically collected data to estimate fertility, to assess childhood, maternal, and adult mortality, to measure changes in fertility and contraceptive prevalence, to examine basic indicators of maternal and child health, to estimate nutritional status of women and children, to describe patterns of knowledge and behaviour related to the transmission of HIV and other sexually transmitted infections, and to ascertain the extent and pattern of domestic violence and female genital cutting. Unlike the 2003 and 2008-09 KDHS surveys, this survey did not include HIV and AIDS testing. HIV prevalence estimates are available from the 2012 Kenya AIDS Indicator Survey (KAIS), completed prior to the 2014 KDHS.
Abstract
The 2014 Kenya Demographic and Health Survey (KDHS) was designed to provide information to monitor and evaluate population and health status in Kenya and to be a follow-up to the previous KDHS surveys. In addition, it provides new information on indicators previously not collected in KDHS surveys, such as fistula and men’s experience of domestic violence. The survey also aims to provide estimates for selected demographic and health indicators at the county level.
The specific objectives of the 2014 KDHS were to:
• Estimate fertility and childhood, maternal, and adult mortality
• Measure changes in fertility and contraceptive prevalence
• Examine basic indicators of maternal and child health
• Collect anthropometric measures for children and women
• Describe patterns of knowledge and behaviour related to transmission of HIV and other sexually transmitted infections
• Ascertain the extent and pattern of domestic violence and female circumcision
The specific objectives of the 2014 KDHS were to:
• Estimate fertility and childhood, maternal, and adult mortality
• Measure changes in fertility and contraceptive prevalence
• Examine basic indicators of maternal and child health
• Collect anthropometric measures for children and women
• Describe patterns of knowledge and behaviour related to transmission of HIV and other sexually transmitted infections
• Ascertain the extent and pattern of domestic violence and female circumcision
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Household
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15-54
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15-54
Version
Version Date
2019-09-27
Version Notes
Corrections have been made to the Kenya 2014 Recode data files. The changes implemented in the new version of the data are as follows:
• SH08 - variable added as country specific.
• SQVERSION - this variable was added as part of the individual women questionnaire. This variable defines the subsample for the two types of women questionnaires applied in Kenya DHS 2014: short version questionnaire and long version.
• New assignment for V104 = Q101B. V104 was not applicable.
• New assignment for V105 = Q101C. V105 was not applicable.
• V216 was “Not applicable” - values are now correctly assigned.
• S408A-X - problem with logic, now corrected.
• S413D and S413D were assigned to M42A and M42B and the country specific were deleted.
• Q425C was not part of the recode - it's assigned to M49C.
• S433E was added as country specific.
• S459C was added as country specific
• H45 was set to not applicable and S524B was set as country specific
• H37N, H37O, and H37P variables were added
• S554A, S556A and S556D were added as country specific (alpha variables)
• V762BW was set to NA
• S716A, S716B and S716C were added as country specific
• S804 was added as country specific
• V704 and V716 - Occupation value labels were added
• S931B added as country specific
• S1208A-X variables were set incorrectly. Fixed
• SH08 - variable added as country specific.
• SQVERSION - this variable was added as part of the individual women questionnaire. This variable defines the subsample for the two types of women questionnaires applied in Kenya DHS 2014: short version questionnaire and long version.
• New assignment for V104 = Q101B. V104 was not applicable.
• New assignment for V105 = Q101C. V105 was not applicable.
• V216 was “Not applicable” - values are now correctly assigned.
• S408A-X - problem with logic, now corrected.
• S413D and S413D were assigned to M42A and M42B and the country specific were deleted.
• Q425C was not part of the recode - it's assigned to M49C.
• S433E was added as country specific.
• S459C was added as country specific
• H45 was set to not applicable and S524B was set as country specific
• H37N, H37O, and H37P variables were added
• S554A, S556A and S556D were added as country specific (alpha variables)
• V762BW was set to NA
• S716A, S716B and S716C were added as country specific
• S804 was added as country specific
• V704 and V716 - Occupation value labels were added
• S931B added as country specific
• S1208A-X variables were set incorrectly. Fixed
Scope
Notes
The 2014 Kenya Demographic and Health Survey covered the following topics:
HOUSEHOLD
• Identification
• Usual members and visitors in the selected households
• Background information on each person listed, such as relationship to head of the household, age, sex, marital status, survivorship and residence of bilogical parents, and highest educational attainment
• Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor, roof and walls of the house, and ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status)
• Household food consumption
• Weight and height measurement for children age 0-5
• Weight and height measurement for women age 15-49
INDIVIDUAL WOMAN
• Background characteristics (education, marital status, media exposure, etc.)
• Reproductive history
• Knowledge and use of family planning methods
• Fertility preferences
• Antenatal and delivery care
• Breastfeeding and infant feeding practices
• Vaccinations and childhood illnesses
• Marriage and sexual activity
• Women’s work and husbands’ background characteristics
• Childhood mortality
• Awareness and behaviour regarding HIV and other sexually transmitted infections
• Adult mortality, including maternal mortality
• Domestic violence
• Female circumcision
• Fistula
INDIVIDUAL MAN
• Respondent background characteristics
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
HOUSEHOLD
• Identification
• Usual members and visitors in the selected households
• Background information on each person listed, such as relationship to head of the household, age, sex, marital status, survivorship and residence of bilogical parents, and highest educational attainment
• Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor, roof and walls of the house, and ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status)
• Household food consumption
• Weight and height measurement for children age 0-5
• Weight and height measurement for women age 15-49
INDIVIDUAL WOMAN
• Background characteristics (education, marital status, media exposure, etc.)
• Reproductive history
• Knowledge and use of family planning methods
• Fertility preferences
• Antenatal and delivery care
• Breastfeeding and infant feeding practices
• Vaccinations and childhood illnesses
• Marriage and sexual activity
• Women’s work and husbands’ background characteristics
• Childhood mortality
• Awareness and behaviour regarding HIV and other sexually transmitted infections
• Adult mortality, including maternal mortality
• Domestic violence
• Female circumcision
• Fistula
INDIVIDUAL MAN
• Respondent background characteristics
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
Coverage
Geographic Coverage
National coverage
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Kenya National Bureau of Statistics | Government of Kenya |
Producers
| Name | Role |
|---|---|
| Ministry of Health | Collaborated in the implementation of the study |
| National AIDS Control Council | Collaborated in the implementation of the study |
| National Council for Population and Development | Collaborated in the implementation of the study |
| Kenya Medical Research Institute | Collaborated in the implementation of the study |
| ICF International | Provided technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Government of Kenya | GovKEN | Funded the study |
| United States Agency for International Development | USAID | Funded the study |
| United Nations Population Fund | UNFPA | Funded the study |
| United Kingdom Department for International Development | DfID | Funded the study |
| The World Bank Group | WBG | Funded the study |
| Danish International Development Agency | DANIDA | Funded the study |
| United Nations Children’s Fund | UNICEF | Funded the study |
| German Development Bank | KfW | Funded the study |
| Clinton Health Access Initiative | CHAI | Funded the study |
| World Food Programme | WFP | Funded the study |
| Micronutrient Initiative | MI | Funded the study |
Sampling
Sampling Procedure
The sample for the 2014 KDHS was drawn from a master sampling frame, the Fifth National Sample Survey and Evaluation Programme (NASSEP V). This is a frame that the KNBS currently operates to conduct household-based surveys throughout Kenya. Development of the frame began in 2012, and it contains a total of 5,360 clusters split into four equal subsamples. These clusters were drawn with a stratified probability proportional to size sampling methodology from 96,251 enumeration areas (EAs) in the 2009 Kenya Population and Housing Census. The 2014 KDHS used two subsamples of the NASSEP V frame that were developed in 2013. Approximately half of the clusters in these two subsamples were updated between November 2013 and September 2014. Kenya is divided into 47 counties that serve as devolved units of administration, created in the new constitution of 2010. During the development of the NASSEP V, each of the 47 counties was stratified into urban and rural strata; since Nairobi county and Mombasa county have only urban areas, the resulting total was 92 sampling strata.
The 2014 KDHS was designed to produce representative estimates for most of the survey indicators at the national level, for urban and rural areas separately, at the regional (former provincial) level, and for selected indicators at the county level. In order to meet these objectives, the sample was designed to have 40,300 households from 1,612 clusters spread across the country, with 995 clusters in rural areas and 617 in urban areas. Samples were selected independently in each sampling stratum, using a two-stage sample design. In the first stage, the 1,612 EAs were selected with equal probability from the NASSEP V frame. The households from listing operations served as the sampling frame for the second stage of selection, in which 25 households were selected from each cluster.
The interviewers visited only the preselected households, and no replacement of the preselected households was allowed during data collection. The Household Questionnaire and the Woman's Questionnaire were administered in all households, while the Man's Questionnaire was administered in every second household. Because of the non-proportional allocation to the sampling strata and the fixed sample size per cluster, the survey was not self-weighting. The resulting data have, therefore, been weighted to be representative at the national, regional, and county levels.
For further details on sample selection, see Appendix A of the final report.
The 2014 KDHS was designed to produce representative estimates for most of the survey indicators at the national level, for urban and rural areas separately, at the regional (former provincial) level, and for selected indicators at the county level. In order to meet these objectives, the sample was designed to have 40,300 households from 1,612 clusters spread across the country, with 995 clusters in rural areas and 617 in urban areas. Samples were selected independently in each sampling stratum, using a two-stage sample design. In the first stage, the 1,612 EAs were selected with equal probability from the NASSEP V frame. The households from listing operations served as the sampling frame for the second stage of selection, in which 25 households were selected from each cluster.
The interviewers visited only the preselected households, and no replacement of the preselected households was allowed during data collection. The Household Questionnaire and the Woman's Questionnaire were administered in all households, while the Man's Questionnaire was administered in every second household. Because of the non-proportional allocation to the sampling strata and the fixed sample size per cluster, the survey was not self-weighting. The resulting data have, therefore, been weighted to be representative at the national, regional, and county levels.
For further details on sample selection, see Appendix A of the final report.
Response Rate
A total of 39,679 households were selected for the sample, of which 36,812 were found occupied at the time of the fieldwork. Of these households, 36,430 were successfully interviewed, yielding an overall household response rate of 99 percent. The shortfall of households occupied was primarily due to structures that were found to be vacant or destroyed and households that were absent for an extended period of time.
As noted, the 2014 KDHS sample was divided into halves, with one half of households receiving the full Household Questionnaire, the full Woman’s Questionnaire, and the Man’s Questionnaire and the other half receiving the short Household Questionnaire and the short Woman’s Questionnaire. The household response rate for the full Household Questionnaire was 99 percent, as was the household response rate for the short Household Questionnaire.
In the households selected for and interviewed using the full questionnaires, a total of 15,317 women were identified as eligible for the full Woman’s Questionnaire, of whom 14,741 were interviewed, generating a response rate of 96 percent. A total of 14,217 men were identified as eligible in these households, of whom 12,819 were successfully interviewed, generating a response rate of 90 percent.
In the households selected for and interviewed with the short questionnaires, a total of 16,855 women were identified as eligible for the short Woman’s Questionnaire, of whom 16,338 were interviewed, yielding a response rate of 97 percent.
Response rates are lower in the urban sample than in the rural sample, more so for men. The principal reason for non-response among both eligible men and eligible women was failure to find them at home despite repeated visits to the household. The lower response rates for men reflect the more frequent and longer absences of men from the household
As noted, the 2014 KDHS sample was divided into halves, with one half of households receiving the full Household Questionnaire, the full Woman’s Questionnaire, and the Man’s Questionnaire and the other half receiving the short Household Questionnaire and the short Woman’s Questionnaire. The household response rate for the full Household Questionnaire was 99 percent, as was the household response rate for the short Household Questionnaire.
In the households selected for and interviewed using the full questionnaires, a total of 15,317 women were identified as eligible for the full Woman’s Questionnaire, of whom 14,741 were interviewed, generating a response rate of 96 percent. A total of 14,217 men were identified as eligible in these households, of whom 12,819 were successfully interviewed, generating a response rate of 90 percent.
In the households selected for and interviewed with the short questionnaires, a total of 16,855 women were identified as eligible for the short Woman’s Questionnaire, of whom 16,338 were interviewed, yielding a response rate of 97 percent.
Response rates are lower in the urban sample than in the rural sample, more so for men. The principal reason for non-response among both eligible men and eligible women was failure to find them at home despite repeated visits to the household. The lower response rates for men reflect the more frequent and longer absences of men from the household
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2014-05-07 | 2014-10-20 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
Main Training of Field Staff
Several categories of personnel were recruited and trained to undertake the 2014 KDHS. These included 48 supervisors, 48 field editors, 144 female interviewers, 48 male interviewers, 28 quality assurance personnel, and 20 reserves.
The training for these personnel took place from March 24 to April 17, 2014, in Nakuru. Trainees were divided into six classrooms, each managed by three trainers. The training consisted of a detailed, question-by-question explanation of the questionnaires, accompanied by explanations from the interviewer’s manual, demonstration through role-plays, group discussions, and in-class practice interviewing in pairs. Several graded take-home assignments and quizzes were administered, the results of which were used both to enhance understanding of key terms and concepts and to identify candidates for further strengthening or elimination from the field teams. A number of guest speakers were invited to give lectures on specific topics relevant to the KDHS.
Anthropometry training provided all trainees with instruction, demonstration, and practice in length/height and weight measurements for children and adults. Trainees completed a standardisation exercise measuring children, intended to gauge and improve measurement accuracy and precision. In this exercise, 175 children age 0-59 months and their caregivers were invited to the training site in groups of 50 child-caregiver pairs assigned throughout the day to one of three classrooms. Fifteen nutrition specialists from partnering organisations were trained to support the exercise; they provided a reference measurement for children and monitored the standardisation activity. Each of the 336 trainees served as both measurers and assistants and measured the same 10 children twice. Results were recorded and analysed using Software for Emergency Nutrition Assessment (ENA for SMART); more than 70 percent of trainees’ scores were acceptable or higher. A debriefing session was held the following day to provide feedback and correction to trainees.
Three field practice sessions were held throughout the main training. Trainees were organised into teams with a team leader selected from the pretest trainees. Team leaders assisted with logistics, guided trainees through fieldwork, monitored trainees’ performance, edited trainees’ questionnaires for errors, and debriefed their team on errors/corrections. The first field practice occurred early in the training and focused only on the Household Questionnaire. The final two days of field practice occurred at the end of training and covered the full KDHS protocol: all questionnaires, salt testing, and anthropometry.
FIELDWORK
Fieldwork for the main survey took place from May 7 to October 20, 2014. Field staff were divided into 48 teams according to counties and languages spoken in the areas where they conducted the interviews. Each team had one supervisor, one field editor, three female interviewers, one male interviewer, a driver, and a vehicle. Data collection was overseen by 18 coordinators who had also served as trainers during the pretest and main training and by a staff of 28 quality assurance personnel. Coordinators were each assigned two to three teams for which they were responsible for observing and monitoring data collection quality, ensuring uniformity in data collection procedures and fidelity to the survey protocol, providing moral support to the field teams, and replenishing field team supplies. Coordinators met in person and via phone with teams throughout the fieldwork, spending a total of 70 days in the field. Quality control staff fulfilled similar responsibilities and spent a total of 60 days in the field.
Several categories of personnel were recruited and trained to undertake the 2014 KDHS. These included 48 supervisors, 48 field editors, 144 female interviewers, 48 male interviewers, 28 quality assurance personnel, and 20 reserves.
The training for these personnel took place from March 24 to April 17, 2014, in Nakuru. Trainees were divided into six classrooms, each managed by three trainers. The training consisted of a detailed, question-by-question explanation of the questionnaires, accompanied by explanations from the interviewer’s manual, demonstration through role-plays, group discussions, and in-class practice interviewing in pairs. Several graded take-home assignments and quizzes were administered, the results of which were used both to enhance understanding of key terms and concepts and to identify candidates for further strengthening or elimination from the field teams. A number of guest speakers were invited to give lectures on specific topics relevant to the KDHS.
Anthropometry training provided all trainees with instruction, demonstration, and practice in length/height and weight measurements for children and adults. Trainees completed a standardisation exercise measuring children, intended to gauge and improve measurement accuracy and precision. In this exercise, 175 children age 0-59 months and their caregivers were invited to the training site in groups of 50 child-caregiver pairs assigned throughout the day to one of three classrooms. Fifteen nutrition specialists from partnering organisations were trained to support the exercise; they provided a reference measurement for children and monitored the standardisation activity. Each of the 336 trainees served as both measurers and assistants and measured the same 10 children twice. Results were recorded and analysed using Software for Emergency Nutrition Assessment (ENA for SMART); more than 70 percent of trainees’ scores were acceptable or higher. A debriefing session was held the following day to provide feedback and correction to trainees.
Three field practice sessions were held throughout the main training. Trainees were organised into teams with a team leader selected from the pretest trainees. Team leaders assisted with logistics, guided trainees through fieldwork, monitored trainees’ performance, edited trainees’ questionnaires for errors, and debriefed their team on errors/corrections. The first field practice occurred early in the training and focused only on the Household Questionnaire. The final two days of field practice occurred at the end of training and covered the full KDHS protocol: all questionnaires, salt testing, and anthropometry.
FIELDWORK
Fieldwork for the main survey took place from May 7 to October 20, 2014. Field staff were divided into 48 teams according to counties and languages spoken in the areas where they conducted the interviews. Each team had one supervisor, one field editor, three female interviewers, one male interviewer, a driver, and a vehicle. Data collection was overseen by 18 coordinators who had also served as trainers during the pretest and main training and by a staff of 28 quality assurance personnel. Coordinators were each assigned two to three teams for which they were responsible for observing and monitoring data collection quality, ensuring uniformity in data collection procedures and fidelity to the survey protocol, providing moral support to the field teams, and replenishing field team supplies. Coordinators met in person and via phone with teams throughout the fieldwork, spending a total of 70 days in the field. Quality control staff fulfilled similar responsibilities and spent a total of 60 days in the field.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Kenya National Bureau of Statistics | KNBS | Government of Kenya |
Questionnaires
Questionnaires
The 2014 KDHS used a household questionnaire, a questionnaire for women age 15-49, and a questionnaire for men age 15-54. These instruments were based on the model questionnaires developed for The DHS Program, the questionnaires used in the previous KDHS surveys, and the current information needs of Kenya. During the development of the questionnaires, input was sought from a variety of organisations that are expected to use the resulting data. A two-day workshop involving key stakeholders was held to discuss the questionnaire design.
A total of five questionnaires were used in the 2014 KDHS: (1) a full Household Questionnaire, (2) a short Household Questionnaire, (3) a full Woman’s Questionnaire, (4) a short Woman’s Questionnaire, and (5) a Man’s Questionnaire. The 2014 KDHS sample was divided into halves. In one half, households were administered the full Household Questionnaire, the full Woman’s Questionnaire, and the Man’s Questionnaire. In the other half, households were administered the short Household Questionnaire and the short Woman’s Questionnaire. Selection of these subsamples was done at the household level - within a cluster, one in every two households was selected for the full questionnaires, and the remaining households were selected for the short questionnaires.
The Household Questionnaire was used to list all of the usual members of the household and visitors who stayed in the household the night before the survey. One of the main purposes of the Household Questionnaire was to identify women and men who were eligible for the individual interview. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor and roof of the house, ownership of various durable goods, and ownership and use of mosquito nets. In addition, this questionnaire was used to record height and weight measurements of women age 15-49 and children under age 5.
The Woman’s Questionnaires were used to collect information from women age 15-49.
The Man’s Questionnaire was administered to men age 15-54 living in every second household in the sample. The Man’s Questionnaire collected information similar to that contained in the Woman’s Questionnaire but was shorter because it did not contain questions on maternal and child health, nutrition, adult and maternal mortality, or experience of female circumcision or fistula.
A total of five questionnaires were used in the 2014 KDHS: (1) a full Household Questionnaire, (2) a short Household Questionnaire, (3) a full Woman’s Questionnaire, (4) a short Woman’s Questionnaire, and (5) a Man’s Questionnaire. The 2014 KDHS sample was divided into halves. In one half, households were administered the full Household Questionnaire, the full Woman’s Questionnaire, and the Man’s Questionnaire. In the other half, households were administered the short Household Questionnaire and the short Woman’s Questionnaire. Selection of these subsamples was done at the household level - within a cluster, one in every two households was selected for the full questionnaires, and the remaining households were selected for the short questionnaires.
The Household Questionnaire was used to list all of the usual members of the household and visitors who stayed in the household the night before the survey. One of the main purposes of the Household Questionnaire was to identify women and men who were eligible for the individual interview. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor and roof of the house, ownership of various durable goods, and ownership and use of mosquito nets. In addition, this questionnaire was used to record height and weight measurements of women age 15-49 and children under age 5.
The Woman’s Questionnaires were used to collect information from women age 15-49.
The Man’s Questionnaire was administered to men age 15-54 living in every second household in the sample. The Man’s Questionnaire collected information similar to that contained in the Woman’s Questionnaire but was shorter because it did not contain questions on maternal and child health, nutrition, adult and maternal mortality, or experience of female circumcision or fistula.
Data Processing
Data Editing
Completed questionnaires were sent to the KNBS Data Processing Centre in Nairobi. Office editors who received the questionnaires verified cluster and household numbers to ensure that they were consistent with the sampled list. They also ensured that each cluster had 25 households and that all questionnaires for a particular household were packaged together.
Data entry began on May 28, 2014, with a four-day training session and continued until November 21, 2014. All data were double entered (100 percent verification) using CSPro software. The data processing team included 42 keyers, three office editors, two secondary editors, four supervisors, and one data manager. Secondary editing, which included further data cleaning and validation, ran simultaneously with data entry and was completed on January 28, 2015, in collaboration with ICF International. The KDHS Key Indicators Report was prepared and launched in April 2015.
Data entry began on May 28, 2014, with a four-day training session and continued until November 21, 2014. All data were double entered (100 percent verification) using CSPro software. The data processing team included 42 keyers, three office editors, two secondary editors, four supervisors, and one data manager. Secondary editing, which included further data cleaning and validation, ran simultaneously with data entry and was completed on January 28, 2015, in collaboration with ICF International. The KDHS Key Indicators Report was prepared and launched in April 2015.
Data Appraisal
Estimates of Sampling Error
The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2014 Kenya Demographic and Health Survey (2014 KDHS) to minimise this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2014 KDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2014 KDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. Sampling errors are computed in either ISSA or SAS, using programs developed by ICF Macro. These programs use the Taylor linearisation method of variance estimation for survey estimates that are means, proportions or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
The Taylor linearisation method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.
Note: A more detailed description of estimate of sampling error is presented in APPENDIX B of the survey report.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2014 KDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2014 KDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. Sampling errors are computed in either ISSA or SAS, using programs developed by ICF Macro. These programs use the Taylor linearisation method of variance estimation for survey estimates that are means, proportions or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
The Taylor linearisation method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.
Note: A more detailed description of estimate of sampling error is presented in APPENDIX B of the survey report.
Data Appraisal
Data Quality Tables
- Household age distribution
- Age distribution of eligible and interviewed women
- Age distribution of eligible and interviewed men
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Nutritional status of children based on the NCHS/CDC/WHO International Reference Population
- Completeness of information on siblings
- Sibship size and sex ratio of siblings
Note: See detailed data quality tables in APPENDIX C of the report.
- Household age distribution
- Age distribution of eligible and interviewed women
- Age distribution of eligible and interviewed men
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Nutritional status of children based on the NCHS/CDC/WHO International Reference Population
- Completeness of information on siblings
- Sibship size and sex ratio of siblings
Note: See detailed data quality tables in APPENDIX C of the report.
Access policy
Contacts
Access conditions
Request Dataset Access
The following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV).
To request dataset access, you must first be a registered user of the website. You must then create a new research project request. The request must include a project title and a description of the analysis you propose to perform with the data.
The requested data should only be used for the purpose of the research or study. To request the same or different data for another purpose, a new research project request should be submitted. The DHS Program will normally review all data requests within 24 hours (Monday - Friday) and provide notification if access has been granted or additional project information is needed before access can be granted.
DATASET ACCESS APPROVAL PROCESS
Access to DHS, MIS, AIS and SPA survey datasets (Surveys, HIV, and GPS) is requested and granted by country. This means that when approved, full access is granted to all unrestricted survey datasets for that country. Access to HIV and GIS datasets requires an online acknowledgment of the conditions of use.
Required Information
A dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.
Restricted Datasets
A few datasets are restricted and these are noted. Access to restricted datasets is requested online as with other datasets. An additional consent form is required for some datasets, and the form will be emailed to you upon authorization of your account. For other restricted surveys, permission must be granted by the appropriate implementing organizations, before The DHS Program can grant access. You will be emailed the information for contacting the implementing organizations. A few restricted surveys are authorized directly within The DHS Program, upon receipt of an email request.
When The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP.
GPS/HIV Datasets/Other Biomarkers
Because of the sensitive nature of GPS, HIV and other biomarkers datasets, permission to access these datasets requires that you accept a Terms of Use Statement. After selecting GPS/HIV/Other Biomarkers datasets, the user is presented with a consent form which should be signed electronically by entering the password for the user's account.
Dataset Terms of Use
Once downloaded, the datasets must not be passed on to other researchers without the written consent of The DHS Program. All reports and publications based on the requested data must be sent to The DHS Program Data Archive in a Portable Document Format (pdf) or a printed hard copy.
Download Datasets
Datasets are made available for download by survey. You will be presented with a list of surveys for which you have been granted dataset access. After selecting a survey, a list of all available datasets for that survey will be displayed, including all survey, GPS, and HIV data files. However, only data types for which you have been granted access will be accessible. To download, simply click on the files that you wish to download and a "File Download" prompt will guide you through the remaining steps.
The following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV).
To request dataset access, you must first be a registered user of the website. You must then create a new research project request. The request must include a project title and a description of the analysis you propose to perform with the data.
The requested data should only be used for the purpose of the research or study. To request the same or different data for another purpose, a new research project request should be submitted. The DHS Program will normally review all data requests within 24 hours (Monday - Friday) and provide notification if access has been granted or additional project information is needed before access can be granted.
DATASET ACCESS APPROVAL PROCESS
Access to DHS, MIS, AIS and SPA survey datasets (Surveys, HIV, and GPS) is requested and granted by country. This means that when approved, full access is granted to all unrestricted survey datasets for that country. Access to HIV and GIS datasets requires an online acknowledgment of the conditions of use.
Required Information
A dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.
Restricted Datasets
A few datasets are restricted and these are noted. Access to restricted datasets is requested online as with other datasets. An additional consent form is required for some datasets, and the form will be emailed to you upon authorization of your account. For other restricted surveys, permission must be granted by the appropriate implementing organizations, before The DHS Program can grant access. You will be emailed the information for contacting the implementing organizations. A few restricted surveys are authorized directly within The DHS Program, upon receipt of an email request.
When The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP.
GPS/HIV Datasets/Other Biomarkers
Because of the sensitive nature of GPS, HIV and other biomarkers datasets, permission to access these datasets requires that you accept a Terms of Use Statement. After selecting GPS/HIV/Other Biomarkers datasets, the user is presented with a consent form which should be signed electronically by entering the password for the user's account.
Dataset Terms of Use
Once downloaded, the datasets must not be passed on to other researchers without the written consent of The DHS Program. All reports and publications based on the requested data must be sent to The DHS Program Data Archive in a Portable Document Format (pdf) or a printed hard copy.
Download Datasets
Datasets are made available for download by survey. You will be presented with a list of surveys for which you have been granted dataset access. After selecting a survey, a list of all available datasets for that survey will be displayed, including all survey, GPS, and HIV data files. However, only data types for which you have been granted access will be accessible. To download, simply click on the files that you wish to download and a "File Download" prompt will guide you through the remaining steps.
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Access authority
| Name | URL | |
|---|---|---|
| The DHS Program | archive@dhsprogram.com | Link |
Location of Data Collection
The DHS Program
Archive where study is originally stored
The DHS Program
http://dhsprogram.com/data/available-datasets.cfm
Cost: None
http://dhsprogram.com/data/available-datasets.cfm
Cost: None
Disclaimer and copyrights
Disclaimer
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.
Metadata production
DDI Document ID
DDI_KEN_2014_DHS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | The World Bank | Documentation of the DDI |
DDI Document version
Version 01 (January 2016). Metadata is excerpted from "Kenya Demographic and Health Survey 2014" Report.