Demographic and Health Survey 2017
Tajikistan, 2017
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Reference ID
TJK_2017_DHS_v01_M
Producer(s)
Statistical Agency under the President of the Republic of Tajikistan
Collection(s)
Metadata
Created on
Dec 19, 2018
Last modified
Jul 10, 2019
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74895
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Identification
Survey ID Number
TJK_2017_DHS_v01_M
Title
Demographic and Health Survey 2017
Country/Economy
| Name | Country code |
|---|---|
| Tajikistan | TJK |
Study type
Demographic and Health Survey (Standard) - DHS VII
Series Information
The 2017 Tajikistan Demographic and Health Survey (TjDHS) is the second DHS survey conducted in Tajikistan, following the 2012 survey. A nationally representative sample of approximately 8,052 households was selected for the 2017 TjDHS from 366 clusters. All women age 15-49 who were usual members of the selected households or who spent the night before the survey in the selected households were eligible for an interview.
Abstract
The 2017 Tajikistan Demographic and Health Survey (TjDHS) is the second Demographic and Health Survey conducted in Tajikistan. It was implemented by the Statistical Agency under the President of the Republic of Tajikistan (SA) in collaboration with the Ministry of Health and Social Protection of Population (MOHSP).
The primary objective of the 2017 TjDHS is to provide current and reliable information on population and health issues. Specifically, the TjDHS collected information on fertility and contraceptive use, maternal and child health and nutrition, childhood mortality, domestic violence against women, child discipline, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking and high blood pressure. The 2017 TjDHS follows the 2012 TjDHS survey and provides updated estimates of key demographic and health indicators.
The information collected through the TjDHS is intended to assist policy makers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population.
The primary objective of the 2017 TjDHS is to provide current and reliable information on population and health issues. Specifically, the TjDHS collected information on fertility and contraceptive use, maternal and child health and nutrition, childhood mortality, domestic violence against women, child discipline, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking and high blood pressure. The 2017 TjDHS follows the 2012 TjDHS survey and provides updated estimates of key demographic and health indicators.
The information collected through the TjDHS is intended to assist policy makers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Household
- Individual
- Children age 0-5
- Woman age 15-49
- Individual
- Children age 0-5
- Woman age 15-49
Version
Version Notes
The data dictionary was generated from hierarchical data that was downloaded from the The DHS Program website (http://dhsprogram.com).
Scope
Notes
The 2017 Tajikistan 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, health insurance, birth registration, survivorship and residence of biological parents, and school attendance
• Characteristics of the household's dwelling unit, such as main source of water, type of toilet facility and location, type of fuel used for cooking, materials used for the floor, roof and walls of the house, and possessions of durable goods (including land and livestock).
• Child discipline
• Domestic violence
INDIVIDUAL WOMAN
• Identification
• Background characteristics (including age, education, and media exposure)
• Pregnancy history, reasons for abortion, 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 behaviors regarding HIV/AIDS and other sexually transmitted infections (STIs)
• Knowledge, attitudes, and behaviors related to other health issues (e.g., injections, smoking, childhood illnesses, and pregnancy and childbirth)
• History of high blood pressure and blood pressure measurement
• Domestic violence
BIOMARKER
• Identification
• Weight, height, and hemoglobin measurement for children age 0-5
• Weight, height, and hemoglobin measurement for women age 15-49
• Weight, height, hemoglobin measurement and HIV testing for women age 15-49
FIELDWORKER
• Collect basic background information on the people who were collecting data
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, health insurance, birth registration, survivorship and residence of biological parents, and school attendance
• Characteristics of the household's dwelling unit, such as main source of water, type of toilet facility and location, type of fuel used for cooking, materials used for the floor, roof and walls of the house, and possessions of durable goods (including land and livestock).
• Child discipline
• Domestic violence
INDIVIDUAL WOMAN
• Identification
• Background characteristics (including age, education, and media exposure)
• Pregnancy history, reasons for abortion, 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 behaviors regarding HIV/AIDS and other sexually transmitted infections (STIs)
• Knowledge, attitudes, and behaviors related to other health issues (e.g., injections, smoking, childhood illnesses, and pregnancy and childbirth)
• History of high blood pressure and blood pressure measurement
• Domestic violence
BIOMARKER
• Identification
• Weight, height, and hemoglobin measurement for children age 0-5
• Weight, height, and hemoglobin measurement for women age 15-49
• Weight, height, hemoglobin measurement and HIV testing for women age 15-49
FIELDWORKER
• Collect basic background information on the people who were collecting data
Coverage
Geographic Coverage
National coverage
Universe
The survey covered all de jure household members (usual residents) and all women age 15-49 years resident in the sample household.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Statistical Agency under the President of the Republic of Tajikistan | Government of Republic of Tajikistan |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Ministry of Health and Social Protection of Population | Government of Republic of Tajikistan | Collaborated implementing the survey |
| ICF | The DHS Program | Provided technical assistance through The DHS Program |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Government of Republic of Tajikistan | GovTJK | Funded the survey |
| United States Agency for International Development | USAID | Funded the survey |
| United Nations Population Fund | UNFPA | Provided additional funds for the survey |
| United Nations Children’s Fund | UNICEF | Provided additional funds for the survey |
Sampling
Sampling Procedure
The sampling frame used for the 2017 TjDHS is the 2010 Tajikistan Population and Housing Census conducted by the SA. Administratively, Tajikistan is divided into five regions: Dushanbe, Districts of Republican Subordination (DRS), Sughd, Khatlon, and Gorno-Badakhshan Autonomous Oblast (GBAO). Each region is subdivided into urban and rural areas. The country is divided into districts distributed over the country’s regions. Each district is further divided into census divisions, which are subdivided into instruction areas. Each instruction area is divided into urban enumeration areas (EAs) or rural villages. The sampling frame of the 2017 TjDHS is a list of EAs and natural villages covering all urban and rural areas of the country, with the primary sampling units (PSUs) being EAs in urban areas and natural villages in rural areas. An EA is a geographical area, usually a city block, consisting of the minimum number of households required for efficient counting; each EA serves as a counting unit for the population census.
The sample was designed to yield representative results for the urban and rural areas separately, and for each of the four administrative regions and Dushanbe. In addition, as in the previous TjDHS survey, the sample was designed to allow certain indicators to be presented for the 12 districts in Khatlon covered under the Feed the Future program (FTF); these 12 districts have been combined as a single FTF domain. The sampling frame excluded institutional populations such as persons in hotels, barracks, and prisons.
The 2017 TjDHS followed a stratified two-stage sample design. The first stage involved selecting sample PSUs (clusters) with a probability proportional to their size within each sampling stratum. A total of 366 clusters were selected, 166 in urban areas and 200 in rural areas.
The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 22 households was selected from each cluster with an equal probability systematic selection process, for a total sample of just over 8,000 households.
For further details on sample design, see Appendix A of the final report.
The sample was designed to yield representative results for the urban and rural areas separately, and for each of the four administrative regions and Dushanbe. In addition, as in the previous TjDHS survey, the sample was designed to allow certain indicators to be presented for the 12 districts in Khatlon covered under the Feed the Future program (FTF); these 12 districts have been combined as a single FTF domain. The sampling frame excluded institutional populations such as persons in hotels, barracks, and prisons.
The 2017 TjDHS followed a stratified two-stage sample design. The first stage involved selecting sample PSUs (clusters) with a probability proportional to their size within each sampling stratum. A total of 366 clusters were selected, 166 in urban areas and 200 in rural areas.
The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 22 households was selected from each cluster with an equal probability systematic selection process, for a total sample of just over 8,000 households.
For further details on sample design, see Appendix A of the final report.
Response Rate
All 8,064 households in the selected housing units were eligible for the survey, of which 7,915 were occupied. Of the occupied households, 7,843 were successfully interviewed, yielding a response rate of 99%.
In the interviewed households, 10,799 women age 15-49 were identified for subsequent individual interviews; interviews were completed with 10,718 women, yielding a response rate of 99%, which is the same response rate achieved in the 2012 survey.
In the interviewed households, 10,799 women age 15-49 were identified for subsequent individual interviews; interviews were completed with 10,718 women, yielding a response rate of 99%, which is the same response rate achieved in the 2012 survey.
Weighting
A spreadsheet containing all of the sampling parameters and selection probabilities was prepared to facilitate the calculation of the design weights. Design weights were adjusted for nonresponse to obtain sampling weights for households and for women. In turn, the sampling weights were normalized so that, at the national level, the total number of weighted cases would be equal to the total number of unweighted cases. Normalized weights are relative weights that are valid for estimating means, proportions, and ratios but not for estimating population totals and pooled data. In addition, the number of cases obtained by applying the normalized weights has no direct relation with survey precision because it is relative; therefore, especially for oversampled areas, the number of weighted cases will be much smaller than the number of unweighted cases, which is directly related to survey precision.
Two sets of general weights were calculated for the 2017 TjDHS:
- one set for all households selected for the survey
- one set for women
In addition, there were two sets of special weights that applied to the subsample of women age 15-49 selected randomly for the domestic violence module and the subsample of children age 1-14 selected for the child discipline module.
Two sets of general weights were calculated for the 2017 TjDHS:
- one set for all households selected for the survey
- one set for women
In addition, there were two sets of special weights that applied to the subsample of women age 15-49 selected randomly for the domestic violence module and the subsample of children age 1-14 selected for the child discipline module.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2017-08-08 | 2017-11-11 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
Data collection was carried out by 14 field teams, each consisting of one female team supervisor, four female interviewers, and one health investigator. Fieldwork started in most regions by August 8, 2017, and ended on November 11, 2017.
Fieldwork monitoring was an integral part of the survey. Senior TjDHS technical staff from SA, including the biomarker quality control field supervisor and IT specialists, visited teams regularly to review the work and monitor data quality. The DHS Program representatives also visited teams to monitor data collection and to observe the anemia testing and height and weight measurements of women and children under age 5. During field visits, staff provided teams they visited (supervisor, interviewers, and health investigator) with critical feedback to improve their performance. In addition, they used the TjDHS field-check tables based on data from the completed clusters to illustrate problems specific to each team visited.
Fieldwork monitoring was an integral part of the survey. Senior TjDHS technical staff from SA, including the biomarker quality control field supervisor and IT specialists, visited teams regularly to review the work and monitor data quality. The DHS Program representatives also visited teams to monitor data collection and to observe the anemia testing and height and weight measurements of women and children under age 5. During field visits, staff provided teams they visited (supervisor, interviewers, and health investigator) with critical feedback to improve their performance. In addition, they used the TjDHS field-check tables based on data from the completed clusters to illustrate problems specific to each team visited.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Statistical Agency | SA | Government of Republic of Tajikistan |
Questionnaires
Questionnaires
Three questionnaires were used in the 2017 TjDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Biomarker Questionnaire. These questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Tajikistan. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire. Suggestions were solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. After all questionnaires were finalized in English, they were translated into Russian and Tajik.
Data Processing
Data Editing
All electronic data files were transferred via a secure internet file streaming system (IFSS) to the SA central office in Dushanbe, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by two IT specialists and one secondary editor who took part in the main fieldwork training; they were supervised remotely by The DHS Program staff. Data editing was accomplished using CSPro software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in August 2017 and completed in February 2018.
Data Appraisal
Estimates of Sampling Error
The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling 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 2017 Tajikistan Demographic and Health Survey (TjDHS) 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 2017 TjDHS 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 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 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 2017 TjDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use 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 final report.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017 TjDHS 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 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 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 2017 TjDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use 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 final report.
Data Appraisal
Data Quality Tables
- Household age distribution
- Age distribution of eligible and interviewed women
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Height and weight data completeness and quality for children
See details of the data quality tables in Appendix C of the survey final report.
- Household age distribution
- Age distribution of eligible and interviewed women
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Height and weight data completeness and quality for children
See details of the data quality tables in Appendix C of the survey final 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 |
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_TJK_2017_DHS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
Date of Metadata Production
2018-12-18
DDI Document version
Version 01 (December 2018). Metadata is excerpted from "Tajikistan Demographic and Health Survey 2017" Report.