Demographic and Health Survey 2024
Zambia, 2024
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ZMB_2024_DHS_v01_M
Demographic and Health Survey 2024
DHS/ ZDHS 2024
| Name | Country code |
|---|---|
| Zambia | ZMB |
Demographic and Health Survey [hh/dhs]
Zambia Demographic and Health Survey 2024 (ZDHS 2024) was the seventh survey of its kind following the ones completed in 1992, 1996, 2001–2002, 2007, 2013–2014 and 2018. The survey was nationwide calling for a nationally representative sample of 13,625 households. All women age 15–49 and all men age 15–59 living in the selected households or stayed in the households the night before the survey were eligible for the individual interview.
The Government of the Republic of Zambia conducted the 2024 Zambia Demographic and Health Survey (2024 ZDHS). The survey was implemented by the Zambia Statistics Agency (ZamStats) in partnership with the Ministry of Health (MoH), the University Teaching Hospital Virology Laboratory (UTH-VL), the National Health Research and Training Institute (NHRTI) formerly the Tropical Diseases Research Centre (TDRC), and the Department of Demography, Population Sciences, Monitoring and Evaluation at the University of Zambia (UNZA).
The primary objective of the 2024 ZDHS is to provide up-to-date estimates of basic demographic and health indicators as well as indicators related to the Sustainable Development Goals (SDGs). Specifically, the ZDHS collected information on:
- Fertility levels, fertility preferences, and contraceptive use
- Maternal health, including antenatal and delivery care and maternal mortality
- Child mortality and child heath, including childhood diseases and vaccination coverage
- Nutritional status of children under age 5 and women age 15–49 (via weight and height measurements)
- Anemia prevalence among children age 6–59 months and women age 15–49
- Availability of, access to, and use of insecticide-treated nets (ITNs)
- Awareness of HIV and behavioral risk factors
- HIV prevalence among men age 15–59, women age 15–49, and children age 2–14
- Gender-based violence
The information collected through the 2024 ZDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of Zambia’s population.
Sample survey data [ssd]
- Household
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15 to 59
Version
The data dictionary was generated from hierarchical data that was downloaded from the The DHS Program website (http://dhsprogram.com).
- Contract Phase: DHS-8
- Recode Structure: DHS-8
Scope
The 2024 Zambia 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 biological parents, educational attainment, birth registration, and disability.
- Characteristics of the household's dwelling unit, such as the source of drinking water and where it is located, type of toilet facilities and where it is located, type of fuel used for cooking, main source of energy for heater and light, number of rooms, ownership of livestock, possessions of durable goods, and main material for the floor, roof and walls of the dwelling.
- Mosquito nets
WOMAN
- Identification
- Background characteristics (including age, education, and media exposure)
- Reproduction and child mortality
- Contraception
- Antenatal, delivery, and postnatal care
- Vaccinations and childhood illnesses
- Maternal and child health and nutrition
- Marriage and sexual activity
- Fertility preferences
- Women’s work and husbands’ background characteristics
- Knowledge, awareness, and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs)
- Other health issues and chronic diseases (including hypertension and diabetes)
- Fistula
- Mental health and well-being
- Adult mortality, including maternal mortality
- Domestic violence
- Women’s empowerment
MAN
- Identification
- Background characteristics
- Reproduction
- Contraception
- Marriage and sexual activity
- Fertility preferences
- Employment and gender roles
- Knowledge, awareness, and behavior regarding HIV/AIDS and other STIs
- Other health issues and chronic diseases (including hypertension and diabetes)
- Mental health and well-being
BIOMARKER
- Identification
- Weight, height, hemoglobin measurement and DBC collection for children age 0-14
- Weight, height, hemoglobin and HIV testing for women age 15-49
- HIV testing for men age 15-59
FIELDWORKER
- Background information on each fieldworkers
Coverage
National
The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-59, and all children aged 0-4 resident in the household.
Producers and sponsors
| Name | Affiliation |
|---|---|
| Zambia Statistics Agency (ZamStats) | Government of Zambia |
| Name | Abbreviation | Role |
|---|---|---|
| Ministry of Health | Collaborated in the implementation of the survey | |
| University Teaching Hospital Virology Laboratory | UTHVL | Collaborated in the implementation of the survey |
| Tropical Diseases Research Centre | TDRC | Collaborated in the implementation of the survey |
| University of Zambia | UNZA | Collaborated in the implementation of the survey |
| ICF | Provided technical assistance through The DHS Program |
| Name | Abbreviation | Role |
|---|---|---|
| Government of Zambia | Govt. ZMB | Funding the study |
| United States Agency for International Development | USAID | Funding the study |
| Global Fund to Fight AIDS, Tuberculosis and Malaria (The Global Fund) | GF | Funding the study |
| United Nations Children’s Fund | UNICEF | Funding the study |
| Gates Foundation | Funding the study |
Sampling
The sampling frame used for the 2024 ZDHS was based on the 2022 Census of Population and Housing of the Republic of Zambia (2022 CPH), conducted by the Zambia Statistics Agency. Zambia is administratively divided into 10 provinces, with each province subdivided into districts, each district into constituencies, and each constituency into wards. There are in total 116 districts, 156 constituencies, and 1,858 wards. In addition to these administrative units, during the 2022 CPH each ward was subdivided into enumeration areas (EA) that served as counting units for the population census. There are in total 36,770 EAs. EAs are classified into two types, urban EAs and rural EAs. Among the 36,770 EAs, 13,273 are urban and 23,497 are rural. Each EA has two measures of size, the size of the population and the number of households in the EA. The average EA size is 111 households; urban EAs are larger on average than rural EAs (143 households and 93 households, respectively).
The 2024 ZDHS sample was stratified and selected in two stages. The first stage involved selecting sample points (clusters) consisting of EAs. Each province was stratified into urban and rural areas, yielding 20 sampling strata in total. EAs were selected with a probability proportional to their size within each sampling stratum. A total of 545 clusters were selected. The second stage involved systematic sampling of households. A household listing exercise was undertaken in all of the selected clusters. During the listing, an average of 111 households were found in each cluster, from which a fixed number of 25 households were selected through an equal probability systematic selection process, to obtain a total sample size of 13,625 households. Results from this sample are representative at the national, urban and rural, and provincial levels. All women age 15–49 and men age 15–59 who were either permanent residents of the selected households or were visitors who stayed in the households the night before the survey were eligible to be interviewed.
For further details on sample design, see APPENDIX A of the final report.
A total of 13,625 households were selected for the ZDHS sample, of which 12,877 were found to be occupied. Of the occupied households, 12,808 were successfully interviewed, yielding a response rate of almost 100%. In the interviewed households, 14,362 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 13,951 women, yielding a response rate of 97%. Also, 13,424 men age 15–59 in the interviewed households were identified as eligible for individual interviews and 12,585 were successfully interviewed, yielding a response rate of 94%.
A spreadsheet containing all sampling parameters and selection probabilities was prepared to facilitate the calculation of the design weights. Design weights were adjusted for household nonresponse and as well as for individual non-response to get the sampling weights, for households, women and men surveys respectively. All the nonresponse adjustments will be done at sampling stratum level. The differences between the household sampling weights and the individual sampling weights were introduced by individual non-response. The final sampling weights were normalized in order to give the total number of un-weighted cases equal to the total number of weighted cases at national level, for both household weights and individual weights, respectively. The sampling weights for HIV testing were calculated in a similar way, with correction of nonresponse for both individual survey and for HIV testing, but the normalization of the sampling weights was different. The HIV testing weights were normalized for male and female together at national level, in order that the HIV prevalence calculated for male and female together are valid. Sampling weights for the domestic violence survey were calculated based on the number of eligible respondents in the households. A total number of six sets of weights were calculated:
- one set for all households selected for the survey
- one set for women individual survey
- one set for male individual survey
- one set for women domestic violence survey
- one set for adult HIV testing
- one set for HIV testing for children 2–14
It is important to note that normalized weights are relative weights which are valid for estimating means, proportions and ratios, but not valid for estimating population totals and for pooled data. Also, the number of weighted cases using the normalized weight has no direct relation with the survey precision because it is relative, especially for oversampled areas, the number of weighted cases will be much smaller than the number of un-weighted cases, only the later one is directly related to survey precision.
For further details on sample weights, see APPENDIX A.4 of the final report.
Survey instrument
Four questionnaires were used for the 2024 ZDHS: the Household Questionnaire, the Woman’s Questionnaire, the 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 Zambia. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers. The Household, Man’s, and Woman’s Questionnaires were administered in eight major languages: English, Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja, and Tonga.
Data collection
| Start | End |
|---|---|
| 2024-01-17 | 2024-07-07 |
- Face-to-face computer-assisted interviews [capi]
| Name | Affiliation | Abbreviation |
|---|---|---|
| Zambia Statistics Agency | Government of Zambia | ZamStats |
Data collection was carried out from 17 January to 7 July 2024 by 22 teams, each composed of 12 members: one supervisor, three female interviewers, two male interviewers, four biomarker technicians, and two drivers. Fieldwork monitoring was a crucial part of the 2024 ZDHS. Senior technical staff from ZamStats; the Department of Demography, Population Sciences, Monitoring and Evaluation at the University of Zambia (UNZA); and UTH-VL regularly visited teams to review their work and monitor data quality.
ZamStats organized three groups of fieldwork monitors:
- Provincial coordinators: Ten coordinators, each responsible for supervising teams in one province. Their assignments shifted with different visits to ensure comprehensive coverage and to balance the strengths of the monitors across provinces. They helped teams resolve any issues that arose in accessing clusters or while conducting their work, and they supported the technical work of the interviewers.
- Biomarker monitors: Ten monitors, each overseeing biomarker technicians in one province. Biomarker monitors also rotated across provinces and observed biomarker technician consent and testing procedures using the technical checklists provided.
- Information technology (IT) staff: Four IT staff members deployed as needed to resolve CAPI related issues.
Additionally, two staff members from The DHS Program independently visited teams to monitor data and biomarker collection. One local DHS Program staff member also served as a rotating field monitor for ZamStats. During field visits, monitors provided critical feedback to improve team performance. They used ZDHS field-check tables, based on data from completed clusters, to highlight specific issues for each team.
Data processing
The survey data were collected using tablet computers running the Android operating system and Census and Survey Processing System (CSPro) software, jointly developed by the United States Census Bureau, ICF, and Serpro S.A.
The CAPI programme was used for data collection. The programme accepted only valid responses, automatically performed checks on ranges of values, skipped to the appropriate question based on the responses given, and checked the consistency of the data collected. Answers to the survey questions were entered into the tablets by each interviewer. Supervisors downloaded interview data from interviewers’ tablets to their tablet via Bluetooth, checked the data for completeness, and monitored fieldwork progress. Each day, after completion of interviews, field supervisors submitted data to the central server. Data were sent to the central office via secure internet data transfer. The data processing monitors monitored the quality of the data received and downloaded completed data files for completed clusters into the system. ICF provided the CSPro software for data processing and offered technical assistance in the preparation of the data capture, data management, and data editing programmes. Secondary editing was conducted simultaneously with data collection and was completed following data collection on 28 August 2024. Technical support for data processing was provided by ICF.
Data appraisal
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 2024 Zambia Demographic and Health Survey (2024 ZDHS) to minimize 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 2024 ZMDHS is only one of many samples that could have been selected from the same population, using the same design and sample 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 among 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 and minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.
If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2024 ZMDHS sample was the result of a multistage stratified cluster design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS programmes developed by ICF International. These programmes use the Taylor linearization method to estimate variances for survey estimates that are means, medians, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility rates and mortality rates.
A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.
Data Quality Tables
- Household age distribution
- Age distribution of eligible and interviewed women
- Age distribution of eligible and interviewed men
- Age displacement at ages 14/15
- Age displacement at ages 49/50
- Pregnancy outcomes by years preceding the survey
- Completeness of reporting
- 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
- Heaping in anthropometric measurements for children (digit preference)
- Observation of mosquito nets
- Observation of handwashing facility
- School attendance by single year of age
- Vaccination cards photographed
- Prevalence of anaemia in children based on 2011 WHO guidelines
- Prevalence of anaemia in women based on 2011 WHO guidelines
- Completeness of information on siblings
- Sibship size and sex ratio of siblings
- Pregnancy-related mortality trends
See details of the data quality tables in Appendix C of the final report.
Data Access
| Name | URL |
|---|---|
| The DHS Program | https://dhsprogram.com |
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.
Recommended citations are available at https://www.dhsprogram.com/publications/Recommended-Citations.cfm
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 |
Metadata production
DDI_ZMB_2024_DHS_v01_M
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank Group | Documentation of the survey |
2025-11-19T05:00:00.000Z
Metadata version
Version 01 (November 2025). Metadata is excerpted from "Zambia Demographic and Health Survey 2024" final report.