Demographic and Health Survey and Malaria Indicator Survey 2022
Tanzania, 2022
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TZA_2022_DHS-MIS_v01_M
Demographic and Health Survey and Malaria Indicator Survey 2022
| Name | Country code |
|---|---|
| Tanzania | TZA |
Demographic and Health Survey [hh/dhs]
The 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHSMIS) is the sixth survey of its kind following those implemented in 1991–92 (TDHS), 1996 (TDHS), 2004–05 (TDHS), 2010 (TDHS), and 2015–16 (TDHS-MIS). The survey used a nationally representative sample of about 16,350 households selected randomly from a random sample of 629 clusters. 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 to be interviewed. The survey was expected to result in about 16,280 interviews of women age 15–49.
The information collected through the 2022 TDHS-MIS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of Tanzania’s population. The 2022 TDHS-MIS also provides indicators to monitor and evaluate international, regional, and national programmes, such as the Global Agenda 2030 on Sustainable Development Goals (2030 SDGs), Tanzania Development Vision 2025, the Third National Five-Year Development Plan (FYDP III 2021/22–2025/26), East Africa Community Vision 2050 (EAC 2050), and Africa Development Agenda 2063 (ADA 2063).
Sample survey data [ssd]
- Household
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15-49
Version
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
Scope
The 2022 Tanzania Demographic and Health Survey and Malaria Indicator 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 health insurance
• Characteristics of the household's dwelling unit, such as the source of water for drinking and other purposes such as cleaning and handwashing, water source location and how long it takes to get water, type of toilet facilities and where it is located, type of fuel used for cooking, main source of light for the home, type of fuel or energy used for heating the home, number of rooms, ownership of livestock, possessions of durable goods, and main material for the floor, roof and walls of the dwelling.
• Disability
• Mosquito nets
INDIVIDUAL WOMAN
• Identification
• Background characteristics (age, education, media exposure, etc.)
• Birth history and childhood mortality
• Knowledge and use of family planning methods
• Fertility preferences, antenatal, delivery, and postnatal care
• Breastfeeding and infant feeding practices
• Vaccinations and childhood illnesses
• Marriage and sexual activity
• Women’s work and husband’s background characteristics
• Other health issues
• Adult mortality, including maternal mortality
• Female genital cutting
• Early childhood development
• Malaria
• Domestic violence
INDIVIDUAL MAN
• Identification
• Respondent's background
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV and AIDS
• Other health issues
• NCD 01-05 and third blood pressure measurement
• Averaging blood pressure measures
• Malaria knowledge and beliefs
BIOMARKER
• Identification
• Weight, height, malaria testing and hemoglobin measurement for children age 0-4
• Weight, height, urine collection and hemoglobin measurement for women age 15-49
• Weight, height, and hemoglobin measurement for women age 15-49
• Weight and height measurement for men age 15-49
FIELDWORKER
• Background information on each fieldworkers
Coverage
National coverage
The survey covered all de jure household members (usual residents), all women aged 15-49, men aged 15-49, and all children aged 0-4 resident in the household.
Producers and sponsors
| Name | Affiliation |
|---|---|
| National Bureau of Statistics (NBS) | Government of Tanzania |
| Office of the Chief Government Statistician Zanzibar (OCGS) | Government of Tanzania |
| Name | Affiliation | Role |
|---|---|---|
| Ministries of Health | Government of Tanzania | Collaborated in the implementation of the survey |
| Tanzania Food and Nutrition Centre | Government of Tanzania | Collaborated on several aspects of the survey, especially biomarkers |
| ICF | The DHS Program | Provided technical assistance through The DHS Program |
| Name | Role |
|---|---|
| Government of Tanzania | Funding the study |
| United States Agency for International Development | Financial support |
| President’s Malaria Initiative | Financial support |
| Canadian International Development Agency | Financial support |
| Centers for Disease Control and Prevention | Financial support |
| Foreign, Commonwealth and Development Office | Financial support |
| Deutsche Gesellschaft für Internationale Zusammenarbeit | Financial support |
| Hilton Foundation | Financial support |
| Irish AID | Financial support |
| Legal and Human Rights Centre | Financial support |
| Nutrition International | Financial support |
| Royal Norwegian Embassy | Financial support |
| United Nations Children’s Fund | Financial support |
| World Food Programme | Financial support |
Sampling
The sample design for the 2022 TDHS-MIS was carried out in two stages and was intended to provide estimates for the entire country, for urban and rural areas in Tanzania Mainland, and for Zanzibar. For specific indicators such as contraceptive use, the sample design allows for estimation of indicators for each of the 31 regions—26 regions in Tanzania Mainland and 5 regions in Zanzibar.
The sampling frame excluded institutional populations, such as persons in hospitals, hotels, barracks, camps, hostels, and prisons. The 2022 TDHS-MIS followed a stratified two-stage sample design. The first stage involved selection of sampling points (clusters) consisting of enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census (2012 PHC). The EAs were selected with a probability proportional to their size within each sampling stratum. A total of 629 clusters were selected. Among the 629 EAs, 211 were from urban areas and 418 were from rural areas.
In the second stage, 26 households were selected systematically from each cluster, for a total anticipated sample size of 16,354 households for the 2022 TDHS-MIS. A household listing operation was carried out in all the selected EAs before the main survey. During the household listing operation, field staff visited each of the selected EAs to draw location maps and detailed sketch maps and to list all residential households found in each EA with addresses and the names of the heads of the households. The resulting list of households served as a sampling frame for the selection of households in the second stage. During the listing operation, field teams collected global positioning system (GPS) data—latitude, longitude, and altitude readings—to produce one GPS point per EA. To estimate geographic differentials for certain demographic indicators, Tanzania was divided into nine geographic zones. Although these zones are not official administrative areas, this classification system is also used by the Reproductive and Child Health Section of the Ministry of Health. Grouping of regions into zones allows for larger denominators and smaller sampling errors for indicators at the zonal level.
For further details on sample design, see APPENDIX A of the final report.
A total of 16,312 households were selected for the 2022 TDHS-MIS sample. This number is slightly less than the targeted sample size of 16,354 because one EA could not be reached due to security reasons, while a few EAs had less than the targeted 26 households. Of the 16,312 households selected, 15,907 were found to be occupied. Of the occupied households, 15,705 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 15,699 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 15,254 women, yielding a response rate of 97%. In the subsample (50% of households) of households selected for the male questionnaire, 6,367 men age 15–49 were identified as eligible for individual interviews, and 5,763 were successfully interviewed, yielding a response rate of 91%.
Survey instrument
Five questionnaires were used for the 2022 TDHS-MIS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Micronutrient Questionnaire. The questionnaires, based on The DHS Program’s Model Questionnaires, were adapted to reflect the population and health issues relevant to Tanzania. In addition, a self-administered Fieldworker’s Questionnaire collected information about the survey’s fieldworkers.
Data collection
| Start | End |
|---|---|
| 2022-02-14 | 2022-07-21 |
- Computer Assisted Personal Interview [capi]
| Name | Affiliation |
|---|---|
| Tanzania National Bureau of Statistics | Government of Tanzania |
Data collection was carried out by 18 field teams, 3 teams for Zanzibar and 15 teams for Tanzania Mainland. Each team was provided with two vehicles (four-wheel drive trucks) with two drivers. Each team consisted of a team supervisor, a CAPI supervisor, three female interviewers, one male interviewer, and four biomarker technicians (two for standard biomarkers and two for micronutrients). During fieldwork, EA maps, listing forms, and local leaders assisted the field staff in identifying the sampled clusters and households. The team leaders and CAPI supervisors were responsible for data quality in the field.
Fieldwork monitoring was an integral part of the 2022 TDHS-MIS. Quality control teams consisted of staff from NBS, OCGS, TFNC, and the ministry responsible for health from both Tanzania Mainland and Zanzibar. Fieldwork monitoring involved visiting teams regularly to ensure that the survey was conducted according to the survey protocol and providing real time solutions to field challenges by observing the biomarker measurements of eligible respondents. All biomarker questionnaires and urine specimens were sent to the nearest TFNC laboratory every week. Field check tables were generated regularly from Syncloud to monitor data quality and fieldwork progress. For field teams with specific problems, quality control staff provided specific instructions to help those teams to improve their performance, otherwise feedback was regularly provided to all field teams. ICF provided technical assistance during the entire 5-month data collection period, which ran from 24 February to 21 July 2022. All teams completed their first cluster in Kilimanjaro region. Data collection in other regions started in March 2022.
Data processing
In the 2022 TDHS-MIS survey, CAPI was used during data collection. The devices used for CAPI were Android-based computer tablets programmed using a mobile version of CSPro. Programming of questionnaires into the android application was done by ICF, while configuration of tablets was done by NBS and OCGS in collaboration with ICF. All fieldwork personnel were assigned usernames, and devices were password protected to ensure the integrity of the data collected. Selected households were assigned to CAPI supervisors, whereas households were assigned to interviewers’ tablets via Bluetooth. The data for all interviewed households were sent back to CAPI supervisors, who were responsible for initial data consistency and editing, before being sent to the central servers hosted at NBS Headquarters via Syncloud.
The data processing of the 2022 TDHS-MIS ran concurrently with the data collection exercise. The electronic data files from each completed cluster were transferred via Syncloud to the NBS central office server in Dodoma. The data files were registered and checked for inconsistencies, incompleteness, and outliers. Errors and inconsistencies were communicated to the field teams for review and correction. Secondary central data editing was done by NBS and OCGS survey staff at the central office. A CSPro batch editing tool was used for cleaning data and included coding of open-ended questions and resolving inconsistencies.
The Biomarker paper questionnaires were collected by field supervisors and compared with the electronic data files to check for any inconsistencies that may have occurred during data entry. The concurrent data collection and processing offered an advantage because it maximised the likelihood of having error-free data. Timely generation of field check tables allowed effective monitoring. The secondary data editing exercise was completed in October 2022.
Data appraisal
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in 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 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHS-MIS) to minimize this type of error, nonsampling 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 TDHS-MIS 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% 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 TDHS-MIS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2022 TDHS-MIS is an SAS program. This program uses the Taylor linearization method to estimate variances 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 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
- Reporting of age at death in days
- Reporting of age at death in months
- Standardisation 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)
- Coverage of testing for anaemia in children: Capillary blood sample
- Coverage of testing for anaemia in children: Venous blood sample
- Coverage of testing for anaemia in women: Capillary blood sample
- Coverage of testing for anaemia in women: Venous blood sample
- Comparison of haemoglobin concentration and anaemia by type of blood sample: Children and women
- Coverage of urine testing for iodine among women
- Observation of mosquito nets
- Number of enumeration areas completed by month and region
- School attendance by single year of age
- Vaccination cards photographed
- 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
Disclaimer and copyrights
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.
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_TZA_2022_DHS-MIS_v01_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Data Group | The World Bank | Documentation of the DDI |
2023-06-06
Metadata version
Version 01 (October 2023). Metadata is excerpted from "Tanzania Demographic and Health Survey and Malaria Indicator Survey 2022" Report.
2023-06-06