{"doc_desc":{"title":"TJK_2017_DHS_v01_M","idno":"DDI_TJK_2017_DHS_v01_M_WB","producers":[{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Documentation of the DDI"}],"prod_date":"2018-12-18","version_statement":{"version":"Version 01 (December 2018). Metadata is excerpted from \"Tajikistan Demographic and Health Survey 2017\" Report."}},"study_desc":{"title_statement":{"idno":"TJK_2017_DHS_v01_M","title":"Demographic and Health Survey 2017","alt_title":"DHS\/ TjDHS 2017"},"authoring_entity":[{"name":"Statistical Agency under the President of the Republic of Tajikistan","affiliation":"Government of Republic of Tajikistan"}],"production_statement":{"producers":[{"name":"Ministry of Health and Social Protection of Population","affiliation":"Government of Republic of Tajikistan","role":"Collaborated implementing the survey"},{"name":"ICF","affiliation":"The DHS Program","role":"Provided technical assistance through The DHS Program"}],"funding_agencies":[{"name":"Government of Republic of Tajikistan","abbreviation":"GovTJK","role":"Funded the survey"},{"name":"United States Agency for International Development","abbreviation":"USAID","role":"Funded the survey"},{"name":"United Nations Population Fund","abbreviation":"UNFPA","role":"Provided additional funds for the survey"},{"name":"United Nations Children\u2019s Fund","abbreviation":"UNICEF","role":"Provided additional funds for the survey"}]},"distribution_statement":{"contact":[{"name":"Information about The DHS Program","affiliation":"The DHS Program","email":"reports@DHSprogram.com","uri":"http:\/\/www.DHSprogram.com"},{"name":"General Inquiries","affiliation":"The DHS Program","email":"info@dhsprogram.com","uri":"http:\/\/www.DHSprogram.com"},{"name":"Data and Data Related Resources","affiliation":"The DHS Program","email":"archive@dhsprogram.com","uri":"http:\/\/www.DHSprogram.com"}]},"series_statement":{"series_name":"Demographic and Health Survey (Standard) - DHS VII","series_info":"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."},"version_statement":{"version_notes":"The data dictionary was generated from hierarchical data that was downloaded from the The DHS Program website (http:\/\/dhsprogram.com)."},"study_info":{"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).\n\nThe 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.\n\nThe 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\u2019s population.","coll_dates":[{"start":"2017-08-08","end":"2017-11-11","cycle":""}],"nation":[{"name":"Tajikistan","abbreviation":"TJK"}],"geog_coverage":"National coverage","analysis_unit":"- Household\n- Individual\n- Children age 0-5\n- Woman age 15-49","universe":"The survey covered all de jure household members (usual residents) and all women age 15-49 years resident in the sample household.","data_kind":"Sample survey data [ssd]","notes":"The 2017 Tajikistan Demographic and Health Survey covered the following topics:\n\nHOUSEHOLD\n\u2022 Identification\n\u2022 Usual members and visitors in the selected households\n\u2022 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\n\u2022 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).\n\u2022 Child discipline\n\u2022 Domestic violence\n\nINDIVIDUAL WOMAN\n\u2022 Identification\n\u2022 Background characteristics (including age, education, and media exposure)\n\u2022 Pregnancy history, reasons for abortion, and child mortality\n\u2022 Contraception\n\u2022 Antenatal, delivery, and postnatal care\n\u2022 Vaccinations and childhood illnesses\n\u2022 Maternal and child health and nutrition\n\u2022 Marriage and sexual activity\n\u2022 Fertility preferences\n\u2022 Women\u2019s work and husbands\u2019 background characteristics\n\u2022 Knowledge, awareness, and behaviors regarding HIV\/AIDS and other sexually transmitted infections (STIs)\n\u2022 Knowledge, attitudes, and behaviors related to other health issues (e.g., injections, smoking, childhood illnesses, and pregnancy and childbirth)\n\u2022 History of high blood pressure and blood pressure measurement\n\u2022 Domestic violence\n\nBIOMARKER\n\u2022 Identification\n\u2022 Weight, height, and hemoglobin measurement for children age 0-5\n\u2022 Weight, height, and hemoglobin measurement for women age 15-49\n\u2022 Weight, height, hemoglobin measurement and HIV testing for women age 15-49\n\nFIELDWORKER\n\u2022 Collect basic background information on the people who were collecting data"},"method":{"data_collection":{"data_collectors":[{"name":"Statistical Agency","abbreviation":"SA","affiliation":"Government of Republic of Tajikistan"}],"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\u2019s 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.\n\nThe 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.\n\nThe 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.\n\nThe 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.\n\nFor further details on sample design, see Appendix A of the final report.","coll_mode":"Face-to-face [f2f]","research_instrument":"Three questionnaires were used in the 2017 TjDHS: the Household Questionnaire, the Woman\u2019s Questionnaire, and the Biomarker Questionnaire. These questionnaires, based on The DHS Program\u2019s 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.","coll_situation":"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.\n\nFieldwork 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.","weight":"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.\n\nTwo sets of general weights were calculated for the 2017 TjDHS:\n- one set for all households selected for the survey\n- one set for women\n\nIn 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.","cleaning_operations":"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."},"analysis_info":{"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%.\n\nIn 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.","sampling_error_estimates":"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.\n\nSampling 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.\n\nSampling 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.\n\nIf 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.\n\nA more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.","data_appraisal":"Data Quality Tables\n- Household age distribution\n- Age distribution of eligible and interviewed women\n- Completeness of reporting\n- Births by calendar years\n- Reporting of age at death in days\n- Reporting of age at death in months\n- Height and weight data completeness and quality for children\n\nSee details of the data quality tables in Appendix C of the survey final report."}},"data_access":{"dataset_use":{"contact":[{"name":"The DHS Program","affiliation":"","email":"archive@dhsprogram.com","uri":"http:\/\/www.DHSprogram.com"}],"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n- the Identification of the Primary Investigator\n- the title of the survey (including country, acronym and year of implementation)\n- the survey reference number\n- the source and date of download","conditions":"Request Dataset Access\nThe following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV). \nTo 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. \n\nThe 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. \n\nDATASET ACCESS APPROVAL PROCESS\nAccess 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.\n\nRequired Information\nA dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.\n\nRestricted Datasets\nA 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. \n\nWhen The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP. \n\nGPS\/HIV Datasets\/Other Biomarkers\nBecause 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.\n\nDataset Terms of Use\nOnce 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. \n\nDownload Datasets\nDatasets 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.","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."}}},"schematype":"survey","tags":[{"tag":"noDOI"}]}