{"type":"survey","study_desc":{"title_statement":{"idno":"KGZ_2012_DHS_v01_M","title":"Demographic and Health Survey 2012","alt_title":"DHS 2012 \/ KgDHS 2012"},"authoring_entity":[{"name":"National Statistical Committee (NSC)","affiliation":"Government of Kyrgyz Republic"},{"name":"Ministry of Health","affiliation":"Government of Kyrgyz Republic"}],"production_statement":{"producers":[{"name":"ICF International","affiliation":"","role":"Technical assistance"}],"funding_agencies":[{"name":"Government of Kyrgyz Republic","abbreviation":"GovKGZ","role":"Funded the study"},{"name":"United States Agency for International Development","abbreviation":"USAID","role":"Funded the study"},{"name":"United Nations Population Fund, Kyrgyz Republic office","abbreviation":"UNFPA","role":"Funded the study"}]},"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 VI","series_info":"The 2012 Kyrgyz Republic Demographic and Health Survey (2012 KgDHS) is the second DHS survey conducted in the Kyrgyz Republic, following the country\u2019s first DHS conducted in 1997, and the Multiple Cluster Indicator Survey (MICS) conducted in 2005. A nationally representative sample of about 8,216 households was selected. All women age 15-49 who were usual members of the selected households or who spent the night before the survey in the households were eligible. In addition, among all women age 15-49 eligible for individual interview in all selected households, only one woman per household was selected for the domestic violence module."},"study_info":{"abstract":"The 2012 Kyrgyz Demographic and Health Survey (KgDHS) is a nationally representative sample survey designed to provide information on population and health issues in the Kyrgyz Republic. The 2012 KgDHS, the country\u2019s second DHS survey, was conducted by the National Statistical Committee (NSC) and the Ministry of Health of the Kyrgyz Republic from August through December 2012.\n\nThe purpose of the 2012 KgDHS was to collect national and regional data on fertility and contraceptive use, maternal and child health and nutrition, childhood mortality, domestic violence against women, and knowledge and behavior regarding tuberculosis, HIV infection, and other sexually transmitted infections. The survey obtained detailed information on these issues from women and men of reproductive age. Data are presented by region (oblast) when sample sizes permit such calculations.\n\nThe 2012 KgDHS results are intended to provide the information needed to evaluate existing social programs and to design new strategies for improving the health status of the country\u2019s women and children and enhancing their access to health services. The survey also contributes to the growing international database on demographic and health-related indicators.","coll_dates":[{"start":"2012-08","end":"2012-12","cycle":""}],"nation":[{"name":"Kyrgyz Republic","abbreviation":"KGZ"}],"geog_coverage":"National coverage","analysis_unit":"- Household\n- Individual\n- Children age 0-5\n- Woman age 15-49\n- Man age 15-59","universe":"The survey covered all de jure household members (usual residents), women age 15-49 years and men age 15-59 years resident in the household.","data_kind":"Sample survey data [ssd]","notes":"The 2012 Kyrgyz Republic 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, survivorship and residence of bilogical parents, school attendance, highest educational attainment, and birth registration\n\u2022 Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, 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 ownership of livestock.\n\nINDIVIDUAL WOMAN\n\u2022 Background characteristics\n\u2022 Pregnancy history\n\u2022 Antenatal, delivery, and postnatal care\n\u2022 Knowledge and use of contraception\n\u2022 Reproductive and adult health\n\u2022 Childhood mortality\n\u2022 Health status and health care utilization\n\u2022 Vaccinations of children under age 5\n\u2022 Episodes of diarrhea and respiratory illness among children under age 5\n\u2022 Breastfeeding and weaning practices\n\u2022 Marriage and recent sexual activity\n\u2022 Fertility preferences\n\u2022 Knowledge of and attitudes toward AIDS and other sexually transmitted diseases\n\u2022 Knowledge of and attitudes toward tuberculosis\n\u2022 Women\u2019s work and husbands\u2019 background characteristics\n\u2022 Other women\u2019s health issues\n\u2022 Domestic violence\n\nINDIVIDUAL MAN\n\u2022 Background characteristics\n\u2022 Health status and health care utilization\n\u2022 Contraception\n\u2022 Marriage and recent sexual activity\n\u2022 Attitudes toward and use of condoms\n\u2022 Knowledge of and attitudes toward AIDS and other sexually transmitted diseases\n\u2022 Attitudes toward women\u2019s status\n\u2022 Other health issues","study_scope":"The 2012 Kyrgyz Republic 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, survivorship and residence of bilogical parents, school attendance, highest educational attainment, and birth registration\n\u2022 Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, 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 ownership of livestock.\n\nINDIVIDUAL WOMAN\n\u2022 Background characteristics\n\u2022 Pregnancy history\n\u2022 Antenatal, delivery, and postnatal care\n\u2022 Knowledge and use of contraception\n\u2022 Reproductive and adult health\n\u2022 Childhood mortality\n\u2022 Health status and health care utilization\n\u2022 Vaccinations of children under age 5\n\u2022 Episodes of diarrhea and respiratory illness among children under age 5\n\u2022 Breastfeeding and weaning practices\n\u2022 Marriage and recent sexual activity\n\u2022 Fertility preferences\n\u2022 Knowledge of and attitudes toward AIDS and other sexually transmitted diseases\n\u2022 Knowledge of and attitudes toward tuberculosis\n\u2022 Women\u2019s work and husbands\u2019 background characteristics\n\u2022 Other women\u2019s health issues\n\u2022 Domestic violence\n\nINDIVIDUAL MAN\n\u2022 Background characteristics\n\u2022 Health status and health care utilization\n\u2022 Contraception\n\u2022 Marriage and recent sexual activity\n\u2022 Attitudes toward and use of condoms\n\u2022 Knowledge of and attitudes toward AIDS and other sexually transmitted diseases\n\u2022 Attitudes toward women\u2019s status\n\u2022 Other health issues"},"method":{"data_collection":{"data_collectors":[{"name":"National Statistical Committee","abbreviation":"NSC","affiliation":"Government of Kyrgyz Republic"}],"sampling_procedure":"The 2012 KgDHS sample was designed to permit detailed analyses, including estimation of fertility, infant\/child mortality, and abortion rates, at the national level and separately for urban and rural areas. Many indicators can also be estimated at the regional (oblast) level. A representative probability sample of 8,216 households was selected for the 2012 KgDHS. The sample was selected in two stages. In the first stage, 316 clusters were selected from the sampling frame, which is a complete list of enumeration areas created for the 2009 Population and Housing Census. In the second stage, before the main survey, a household listing operation was conducted in each of the selected clusters. Households were then randomly selected from the newly updated listing for participation in the survey.\n\nAll women age 15-49 who either were permanent residents of the households in the 2012 KgDHS sample or were visitors present in the household on the night before the survey were eligible to be interviewed. Interviews were completed with 8,208 women. In addition, in a subsample of one-third of the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey. Interviews were completed with 2,413 men.\n\nFor further details on sample design and implementation, see Appendix A of the final report.","coll_mode":"Face-to-face [f2f]","research_instrument":"Three questionnaires were used in the 2012 KgDHS: the Household Questionnaire, the Woman\u2019s Questionnaire, and the Man\u2019s Questionnaire. The questionnaires were based on model survey instruments developed in the MEASURE DHS program. The DHS model questionnaires were adapted for use in the Kyrgyz Republic by experts from the National Statistical Committee and the Ministry of Health of the Kyrgyz Republic. Suggestions were also sought from USAID; a number of UN agencies, including the United Nations Development Program (UNDP), UNICEF, and UNFPA; and other international and nongovernmental organizations. All three questionnaires were developed in English and translated into Russian and Kyrgyz. The questionnaires were pretested in May 2012.","coll_situation":"Nine teams collected the survey data; each team consisted of four female interviewers, one male interviewer, a field editor, and a team supervisor. Fieldwork began in early August 2012 and concluded in December 2012. Senior KgDHS technical staff members visited teams regularly to review their work and monitor data quality. MEASURE DHS staff also assisted with field supervision.","weight":"A spreadsheet containing all sampling parameters and selection probabilities is prepared to facilitate the calculation of the design weight. Next, the design weight is adjusted for household nonresponse and individual nonresponse to get the sampling weights for households and for women and men, respectively. Nonresponse is adjusted at the sampling stratum level. For the household sampling weight, the household design weight is multiplied by the inverse of the household response rate, by stratum. For the women\u2019s individual sampling weight, the household sampling weight is multiplied by the inverse of the women\u2019s individual response rate, by stratum. For the men\u2019s individual sampling weight, the household sampling weight is multiplied by the inverse of the men\u2019s individual response rate, by stratum. After adjusting for nonresponse, the sampling weights are normalized to get the final standard weights that appear in the data files. The normalization process is done to obtain a total number of unweighted cases equal to the total number of weighted cases at the national level, for the total number of households, women, and men. Normalization is done by multiplying the sampling weight by the estimated sampling fraction obtained from the survey for the household weight, the individual woman\u2019s weight, and the individual man\u2019s weight. The normalized weights are relative weights, which are valid for estimating means, proportions, ratios, and rates, but which are not valid for estimating population totals or for pooled data.\n\nFor further details on sampling weights, see Appendix A.4 of the final report.","cleaning_operations":"The processing of the KgDHS results began shortly after fieldwork commenced. Completed questionnaires were returned regularly from the field to NSC headquarters in Bishkek, where they were entered and edited by data processing personnel specially trained for this task. The data processing personnel included a supervisor, a questionnaire administrator (who ensured that the expected number of questionnaires from all clusters was received), several office editors, 13 data entry operators, and a secondary editor. The concurrent processing of the data was an advantage because the senior DHS technical staff could advise field teams of problems detected during data entry. In particular, tables were generated to check various data quality parameters, and the results were used to provide specific feedback to the teams to improve performance. The data entry and editing phase of the survey was completed in February 2013."},"analysis_info":{"response_rate":"A total of 8,208 households were selected for the sample, of which 8,083 were occupied at the time of the fieldwork and 8,040, or over 99 percent, were successfully interviewed. In these households, 8,286 women age 15-49 were identified. Interviews were completed with 99 percent of these women. Of the 2,495 eligible men identified, 97 percent were successfully interviewed.","sampling_error_estimates":"Estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors result from mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions by either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2012 Kyrgyz Republic Demographic and Health Survey (KgDHS) 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 2012 KgDHS 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 among all possible samples. Although the exact degree of variability is unknown, 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 percent 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 2012 KgDHS 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 Macro. This program uses the Taylor linearization method for variance estimation for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.\n\nNote: A more detailed description of estimates of sampling errors are presented in Appendix B of the final report.","data_appraisal":"Data Quality Tables\n- Household age distribution\n- Age distribution of eligible and interviewed women\n- Age distribution of eligible and interviewed men\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- Nutritional status of children based on the NCHS\/CDC\/WHO International Reference Population\n\nNote: See details of the data quality tables in Appendix C of the 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."}}},"data_files":[{"file_id":"F1","file_name":"RECH0","description":"HOUSEHOLD \n- Household's basic data","case_count":"8208","var_count":"38","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F2","file_name":"RECH1","description":"HOUSEHOLD \n- Household Schedule","case_count":"35805","var_count":"31","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F3","file_name":"RECH2","description":"HOUSEHOLD \n- Household Characteristics","case_count":"8040","var_count":"92","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F4","file_name":"RECH3","description":"HOUSEHOLD \n- Survey specific Household variables","case_count":"8040","var_count":"32","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F5","file_name":"RECH4","description":"HOUSEHOLD \n- Survey specific Household Schedule variables","case_count":"35805","var_count":"11","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F6","file_name":"RECH5","description":"HOUSEHOLD \n- Women Height\/Weight\/Hemoglobin","case_count":"8436","var_count":"38","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F7","file_name":"RECH6","description":"HOUSEHOLD \n- Children 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Breastfeeding","case_count":"8208","var_count":"171","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F16","file_name":"REC43","description":"WOMAN\n - Child's Health and Vaccinations","case_count":"4363","var_count":"169","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F17","file_name":"REC44","description":"WOMAN\n - Child's Height and Weight","case_count":"4363","var_count":"32","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F18","file_name":"REC51","description":"WOMAN\n - Marriage and Sexual Exposure","case_count":"8208","var_count":"29","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F19","file_name":"REC61","description":"WOMAN\n - Fertility Preferences","case_count":"8208","var_count":"29","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F20","file_name":"REC71","description":"WOMAN\n - Partner's Characteristics","case_count":"8208","var_count":"34","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F21","file_name":"REC75","description":"WOMAN\n - AIDS, STIs and Condom Use","case_count":"8208","var_count":"139","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F22","file_name":"REC80","description":"WOMAN\n - HIV, STIs and Condom Use (continued)","case_count":"8208","var_count":"70","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F23","file_name":"REC81","description":"WOMAN\n - Characteristics of 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variables","case_count":"4363","var_count":"24","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F28","file_name":"REC95","description":"WOMAN\n - Country specific Health and Vaccination variables","case_count":"4363","var_count":"40","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F29","file_name":"REC97","description":"WOMAN\n - Country specific Pregnancy history","case_count":"20331","var_count":"25","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F30","file_name":"REC98","description":"WOMAN\n - Country specific Vaccination data from clinics","case_count":"4363","var_count":"75","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F31","file_name":"RECDV","description":"WOMAN\n - Domestic 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