Demographic and Health Survey 2022
Kenya, 2022
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Reference ID
KEN_2022_DHS_v01_M
Producer(s)
Kenya National Bureau of Statistics (KNBS)
Collection(s)
Metadata
Created on
Jul 06, 2023
Last modified
Jul 06, 2023
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Identification
Survey ID Number
KEN_2022_DHS_v01_M
Title
Demographic and Health Survey 2022
Country/Economy
| Name | Country code |
|---|---|
| Kenya | KEN |
Study type
Demographic and Health Survey [hh/dhs]
Series Information
The 2022 Kenya Demographic and Health Surveys (KDHS) is the 7th survey of its kind to be carried out in Kenya. Previous Demographic and Health Surveys were implemented in 1989, 1993, 1998, 2003 and 2008–09 and 2014. The 2022 KDHS incorporated a nationally representative sample of 42,300 households. All women age 15–49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for for the interviews.
Abstract
The 2022 Kenya Demographic and Health Survey (2022 KDHS) was implemented by the Kenya National Bureau of Statistics (KNBS) in collaboration with the Ministry of Health (MoH) and other
stakeholders. The survey is the 7th KDHS implemented in the country.
The primary objective of the 2022 KDHS is to provide up-to-date estimates of basic sociodemographic, nutrition and health indicators. Specifically, the 2022 KDHS collected information on:
• Fertility levels and contraceptive prevalence
• Childhood mortality
• Maternal and child health
• Early Childhood Development Index (ECDI)
• Anthropometric measures for children, women, and men
• Children’s nutrition
• Woman’s dietary diversity
• Knowledge and behaviour related to the transmission of HIV and other sexually transmitted diseases
• Noncommunicable diseases and other health issues
• Extent and pattern of gender-based violence
• Female genital mutilation.
The information collected in the 2022 KDHS will assist policymakers and programme managers in monitoring, evaluating, and designing programmes and strategies for improving the health of Kenya’s population. The 2022 KDHS also provides indicators relevant to monitoring the Sustainable Development Goals (SDGs) for Kenya, as well as indicators relevant for monitoring national and subnational development agendas such as the Kenya Vision 2030, Medium Term Plans (MTPs), and County Integrated Development Plans (CIDPs).
stakeholders. The survey is the 7th KDHS implemented in the country.
The primary objective of the 2022 KDHS is to provide up-to-date estimates of basic sociodemographic, nutrition and health indicators. Specifically, the 2022 KDHS collected information on:
• Fertility levels and contraceptive prevalence
• Childhood mortality
• Maternal and child health
• Early Childhood Development Index (ECDI)
• Anthropometric measures for children, women, and men
• Children’s nutrition
• Woman’s dietary diversity
• Knowledge and behaviour related to the transmission of HIV and other sexually transmitted diseases
• Noncommunicable diseases and other health issues
• Extent and pattern of gender-based violence
• Female genital mutilation.
The information collected in the 2022 KDHS will assist policymakers and programme managers in monitoring, evaluating, and designing programmes and strategies for improving the health of Kenya’s population. The 2022 KDHS also provides indicators relevant to monitoring the Sustainable Development Goals (SDGs) for Kenya, as well as indicators relevant for monitoring national and subnational development agendas such as the Kenya Vision 2030, Medium Term Plans (MTPs), and County Integrated Development Plans (CIDPs).
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 Notes
The data dictionary was generated from hierarchical data that was downloaded from the The DHS Program website (http://dhsprogram.com).
- Contract Phase: DHS-VIII
- Recode Structure: DHS-VIII
- Contract Phase: DHS-VIII
- Recode Structure: DHS-VIII
Scope
Notes
The 2022 Kenya Demographic and Health Survey covered the following topics:
HOUSEHOLD
• Basic information on each person in the household (name, sex, age, education, relationship to the household head, survival of parents for children under age 18)
• Disability
• Assets, land ownership, and housing characteristics
• Sanitation, water, and other environmental health issues
• Health expenditures
• Traffic accident and injury
• COVID-19 (prevalence, vaccination, and related deaths)
• Household food consumption
WOMAN
• Sociodemographic characteristics
• Reproduction
• Family planning
• Maternal health care and breastfeeding
• Vaccination and health of children
• Children’s nutrition
• Woman’s dietary diversity
• Early childhood development
• Marriage and sexual activity
• Fertility preferences
• Husband’s background characteristics and woman’s employment activity
• HIV/AIDS, other STIs, and TB
• Other health issues
• Chronic diseases
• Female genital mutilation
• Gender-based violence
MAN
• Sociodemographic characteristics
• Reproduction
• Family planning
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS, other STIs, and TB
• Other health issues
• Chronic diseases
• Female genital mutilation
• Gender-based violence
BIOMARKER
• Weight and height measurement for children age 0-4
• Weight and height measurement for women age 15-49
• Weight and height measurement for women age 15-54
FIELDWORKER
• Background information on each fieldworkers
HOUSEHOLD
• Basic information on each person in the household (name, sex, age, education, relationship to the household head, survival of parents for children under age 18)
• Disability
• Assets, land ownership, and housing characteristics
• Sanitation, water, and other environmental health issues
• Health expenditures
• Traffic accident and injury
• COVID-19 (prevalence, vaccination, and related deaths)
• Household food consumption
WOMAN
• Sociodemographic characteristics
• Reproduction
• Family planning
• Maternal health care and breastfeeding
• Vaccination and health of children
• Children’s nutrition
• Woman’s dietary diversity
• Early childhood development
• Marriage and sexual activity
• Fertility preferences
• Husband’s background characteristics and woman’s employment activity
• HIV/AIDS, other STIs, and TB
• Other health issues
• Chronic diseases
• Female genital mutilation
• Gender-based violence
MAN
• Sociodemographic characteristics
• Reproduction
• Family planning
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS, other STIs, and TB
• Other health issues
• Chronic diseases
• Female genital mutilation
• Gender-based violence
BIOMARKER
• Weight and height measurement for children age 0-4
• Weight and height measurement for women age 15-49
• Weight and height measurement for women age 15-54
FIELDWORKER
• Background information on each fieldworkers
Coverage
Geographic Coverage
National coverage
Universe
The survey covered all de jure household members (usual residents), all women aged 15-49, men ageed 15-54, and all children aged 0-4 resident in the household.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Kenya National Bureau of Statistics (KNBS) | Government of Kenya |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Ministry of Health | Government of Kenya | Collaborate in the implementation of the survey |
| ICF | The DHS Program | Provided technical assistance through The DHS Program |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Government of Kenya | Govt. KEN | Funding the study |
| United States Agency for International Development | USAID | Funding the study |
| Bill & Melinda Gates Foundation | Funding the study | |
| World Bank | WB | Funding the study |
| United Nations Children’s Fund | UNICEF | Funding the study |
| United Nations Population Fund | UNFPA | Funding the study |
| Nutrition International | Funding the study | |
| World Food Programme | WFP | Funding the study |
| United Nations Entity for Gender Equality and the Empowerment of Women | UN Women | Funding the study |
| World Health Organization | WHO | Funding the study |
| Clinton Health Access Initiative | CHAI | Funding the study |
| Joint United Nations Programme on HIV/AIDS | UNAIDS | Funding the study |
Sampling
Sampling Procedure
The sample for the 2022 KDHS was drawn from the Kenya Household Master Sample Frame (K-HMSF). This is the frame that KNBS currently uses to conduct household-based sample surveys in Kenya. The frame is based on the 2019 Kenya Population and Housing Census (KPHC) data, in which a total of 129,067 enumeration areas (EAs) were developed. Of these EAs, 10,000 were selected with probability proportional to size to create the K-HMSF. The 10,000 EAs were randomised into four equal subsamples. A survey can utilise a subsample or a combination of subsamples based on the sample size requirements. The 2022 KDHS sample was drawn from subsample one of the K-HMSF. The EAs were developed into clusters through a process of household listing and geo-referencing. The Constitution of Kenya 2010 established a devolved system of government in which Kenya is divided into 47 counties. To design the frame, each of the 47 counties in Kenya was stratified into rural and urban strata, which resulted in 92 strata since Nairobi City and Mombasa counties are purely urban.
The 2022 KDHS was designed to provide estimates at the national level, for rural and urban areas separately, and, for some indicators, at the county level. The sample size was computed at 42,300 households, with 25 households selected per cluster, which resulted in 1,692 clusters spread across the country, 1,026 clusters in rural areas, and 666 in urban areas. The sample was allocated to the different sampling strata using power allocation to enable comparability of county estimates.
The 2022 KDHS employed a two-stage stratified sample design where in the first stage, 1,692 clusters were selected from the K-HMSF using the Equal Probability Selection Method (EPSEM). The clusters were selected independently in each sampling stratum. Household listing was carried out in all the selected clusters, and the resulting list of households served as a sampling frame for the second stage of selection, where 25 households were selected from each cluster. However, after the household listing procedure, it was found that some clusters had fewer than 25 households; therefore, all households from these clusters were selected into the sample. This resulted in 42,022 households being sampled for the 2022 KDHS. Interviews were conducted only in the pre-selected households and clusters; no replacement of the preselected units was allowed during the survey data collection stages.
For further details on sample design, see APPENDIX A of the survey report.
The 2022 KDHS was designed to provide estimates at the national level, for rural and urban areas separately, and, for some indicators, at the county level. The sample size was computed at 42,300 households, with 25 households selected per cluster, which resulted in 1,692 clusters spread across the country, 1,026 clusters in rural areas, and 666 in urban areas. The sample was allocated to the different sampling strata using power allocation to enable comparability of county estimates.
The 2022 KDHS employed a two-stage stratified sample design where in the first stage, 1,692 clusters were selected from the K-HMSF using the Equal Probability Selection Method (EPSEM). The clusters were selected independently in each sampling stratum. Household listing was carried out in all the selected clusters, and the resulting list of households served as a sampling frame for the second stage of selection, where 25 households were selected from each cluster. However, after the household listing procedure, it was found that some clusters had fewer than 25 households; therefore, all households from these clusters were selected into the sample. This resulted in 42,022 households being sampled for the 2022 KDHS. Interviews were conducted only in the pre-selected households and clusters; no replacement of the preselected units was allowed during the survey data collection stages.
For further details on sample design, see APPENDIX A of the survey report.
Response Rate
A total of 42,022 households were selected for the survey, of which 38,731 (92%) were found to be occupied. Among the occupied households, 37,911 were successfully interviewed, yielding a response rate of 98%. The response rates for urban and rural households were 96% and 99%, respectively. In the interviewed households, 33,879 women age 15-49 were identified as eligible for individual interviews. Of these, 32,156 women were interviewed, yielding a response rate of 95%. The response rates among women selected for the full and short questionnaires were similar (95%). In the households selected for the men’s survey, 16,552 men age 15-54 were identified as eligible for individual interviews and 14,453 were successfully interviewed, yielding a response rate of 87%.
Weighting
A spreadsheet containing all sampling parameters and selection probabilities was prepared to help calculate the design weights. Design weights were adjusted for household nonresponse and individual nonresponse to obtain the sampling weights for households and for women. Nonresponse is adjusted at the sampling stratum level. For the household sampling weight, the household design weight is multiplied by the inverse of the household response rate, by stratum. For the women’s individual sampling weight, the household sampling weight is multiplied by the inverse of the women’s individual response rate, by stratum. After adjusting for nonresponse, the sampling weights are normalised to get the final standard weights that appear in the data files. The normalisation process is aimed at obtaining a total number of unweighted cases equal to the total number of weighted cases using normalised weights at the national level, for the total number of households and for women. Normalisation is done by multiplying the sampling weight by the estimated total sampling fraction obtained from the survey for the household weight and for the individual woman’s weight and men’s weight, respectively. The normalised weights are relative weights that are valid for estimating means proportions, ratios, and rates, but they are not valid for estimation population totals and nor for pooled data for any analysis.
For further details on sample weights, see APPENDIX A.4 of volume 2 report.
For further details on sample weights, see APPENDIX A.4 of volume 2 report.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2022-02-17 | 2022-07-13 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collection Notes
A total of 314 personnel (48 supervisors, 48 biomarker technicians, 144 female interviewers, 48 male interviewers, and 26 reserves) were trained at a central location from 17 January to 13 February 2022. The training included a detailed question-by-question explanation of the questionnaires, accompanied by explanations from the interviewer’s manual, role-play demonstrations, group discussions, in-class practice interviewing in pairs, and assessment tests.
Anthropometry training provided the biomarker technicians with instruction, demonstrations, and practice in length/height and weight measurements for children and adults. The technicians completed a standardisation exercise with measurements of children that were intended to gauge and improve accuracy
and precision. Restandardisation exercises were conducted for those who did not pass the standardisation exercises.
Data collection for the 2022 KDHS was conducted by 48 teams from 17 February to 13 July 2022. Each team included one supervisor, one biomarker technician, three female interviewers, one male interviewer, and a driver. At the county level, the KDHS field teams were assisted by KNBS county statistical officers who provided links to National Government Administration Officers (NGAOs). Prior to the data collection, a county mobilisation team conducted targeted publicity within the clusters to prepare for the fieldwork. The KNBS field staff and village elders assisted in identifying the sampled clusters and households. Monitoring of data collection was undertaken by Technical Working Committee and Steering Committee members throughout the data collection period. The aim of monitoring was to ensure that the survey was conducted according to protocol and to provide real-time solutions to any challenges that were encountered.
Anthropometry training provided the biomarker technicians with instruction, demonstrations, and practice in length/height and weight measurements for children and adults. The technicians completed a standardisation exercise with measurements of children that were intended to gauge and improve accuracy
and precision. Restandardisation exercises were conducted for those who did not pass the standardisation exercises.
Data collection for the 2022 KDHS was conducted by 48 teams from 17 February to 13 July 2022. Each team included one supervisor, one biomarker technician, three female interviewers, one male interviewer, and a driver. At the county level, the KDHS field teams were assisted by KNBS county statistical officers who provided links to National Government Administration Officers (NGAOs). Prior to the data collection, a county mobilisation team conducted targeted publicity within the clusters to prepare for the fieldwork. The KNBS field staff and village elders assisted in identifying the sampled clusters and households. Monitoring of data collection was undertaken by Technical Working Committee and Steering Committee members throughout the data collection period. The aim of monitoring was to ensure that the survey was conducted according to protocol and to provide real-time solutions to any challenges that were encountered.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Kenya National Bureau of Statistics | KNBS | Government of Kenya |
Questionnaires
Questionnaires
Four questionnaires were used in the 2022 KDHS: Household Questionnaire, Woman’s Questionnaire, Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Kenya. In addition, a self-administered Fieldworker Questionnaire was used to collect information about the survey’s fieldworkers.
Data Processing
Data Editing
CAPI was used during data collection. The devices used for CAPI were Android-based computer tablets programmed with a mobile version of CSPro. The CSPro software was developed jointly by the U.S. Census Bureau, Serpro S.A., and The DHS Program. Programming of questionnaires into the Android application was done by ICF, while configuration of tablets was completed by KNBS in collaboration with ICF. All fieldwork personnel were assigned usernames, and devices were password protected to ensure the integrity of the data.
Work was assigned by supervisors and shared via Bluetooth® to interviewers’ tablets. After completion, assigned work was shared with supervisors, who conducted initial data consistency checks and edits and then submitted data to the central servers hosted at KNBS via SyncCloud. Data were downloaded from the central servers and checked against the inventory of expected returns to account for all data collected in the field. SyncCloud was also used to generate field check tables to monitor progress and identify any errors, which were communicated back to the field teams for correction.
Secondary editing was done by members of the KNBS and ICF central office team, who resolved any errors that were not corrected by field teams during data collection. A CSPro batch editing tool was used for cleaning and tabulation during data analysis.
Work was assigned by supervisors and shared via Bluetooth® to interviewers’ tablets. After completion, assigned work was shared with supervisors, who conducted initial data consistency checks and edits and then submitted data to the central servers hosted at KNBS via SyncCloud. Data were downloaded from the central servers and checked against the inventory of expected returns to account for all data collected in the field. SyncCloud was also used to generate field check tables to monitor progress and identify any errors, which were communicated back to the field teams for correction.
Secondary editing was done by members of the KNBS and ICF central office team, who resolved any errors that were not corrected by field teams during data collection. A CSPro batch editing tool was used for cleaning and tabulation during data analysis.
Data Appraisal
Estimates of Sampling Error
The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) 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 2022 Kenya Demographic and Health Survey (2022 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 2022 KDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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.
A 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 2022 KDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2022 KDHS is a SAS program. This program used the Taylor linearisation method for 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.
A more detailed description of estimates of sampling errors are 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 2022 KDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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.
A 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 2022 KDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2022 KDHS is a SAS program. This program used the Taylor linearisation method for 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.
A more detailed description of estimates of sampling errors are 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
- Age displacement at age 14/15
- Age displacement at age 49/50
- Pregnancy outcomes by years preceding the survey
- Completeness of reporting
- Standardization exercise results from anthropometry training
- Height and weight data completeness and quality for children
- Height measurements from random subsample of measured children
- Interference in height and weight measurements of children
- Interference in height and weight measurements of women and men
- Heaping in anthropometric measurements for children (digit preference)
- Food insecurity data completeness, infit and outfit model statistics, and Rasch reliability
- Observation of mosquito nets
- Observation of handwashing facility
- School attendance by single year of age
- Vaccination cards photographed
- Number of enumeration areas completed by month and region
See details of the data quality tables in Appendix C of the survey report.
- Household age distribution
- Age distribution of eligible and interviewed women
- Age distribution of eligible and interviewed men
- Age displacement at age 14/15
- Age displacement at age 49/50
- Pregnancy outcomes by years preceding the survey
- Completeness of reporting
- Standardization exercise results from anthropometry training
- Height and weight data completeness and quality for children
- Height measurements from random subsample of measured children
- Interference in height and weight measurements of children
- Interference in height and weight measurements of women and men
- Heaping in anthropometric measurements for children (digit preference)
- Food insecurity data completeness, infit and outfit model statistics, and Rasch reliability
- Observation of mosquito nets
- Observation of handwashing facility
- School attendance by single year of age
- Vaccination cards photographed
- Number of enumeration areas completed by month and region
See details of the data quality tables in Appendix C of the survey report.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Information about The DHS Program | The DHS Program | reports@DHSprogram.com |
| General Inquiries | The DHS Program | info@dhsprogram.com |
| Data and Data Related Resources | The DHS Program | archive@dhsprogram.com |
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
Recommended citations are available at https://www.dhsprogram.com/publications/Recommended-Citations.cfm
Access authority
| Name | URL |
|---|---|
| The DHS Program | Link |
Metadata production
DDI Document ID
DDI_KEN_2022_DHS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | The World Bank | Documentation of the DDI |
Date of Metadata Production
2023-07-06
DDI Document version
Version 01 (July 2023). Metadata is excerpted from "Kenya Demographic and Health Survey 2022" Volume 1 and Volume 2 reports.