{"type":"survey","study_desc":{"title_statement":{"idno":"NPL_2016_DHS_v01_M","title":"Demographic and Health Survey 2016","alt_title":"DHS \/ NDHS 2016"},"authoring_entity":[{"name":"Ministry of Health (MOH)","affiliation":"Government of Nepal"}],"production_statement":{"producers":[{"name":"ICF","affiliation":"The DHS Program","role":"Provided technical assistance through The DHS Program"}],"funding_agencies":[{"name":"Government of Nepal","abbreviation":"USAID","role":"Funded the study"},{"name":"United States Agency for International Development","abbreviation":"USAID","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 VII","series_info":"Demographic and Health Surveys (DHS) are nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, and nutrition.\n\nThe 2016 Nepal Demographic and Health Survey (2016 NDHS) is the fifth in a series of Demographic and Health Surveys conducted in Nepal in 1996, 2001, 2006, and 2011. As with the prior surveys, the main objective of the 2016 NDHS was to provide up-to-date information on fertility and childhood mortality levels; fertility preferences; awareness, approval, and use of family planning methods; maternal and child health; domestic violence; and knowledge and attitudes toward HIV\/AIDS and other sexually transmitted infections (STIs).\n\nThe sample for the 2016 NDHS was designed to provide estimates of population and health indicators including fertility and mortality rates for the country as a whole, for the urban and rural areas separately, and for each of the three ecological zones (terai, hills, and mountains) and the development regions. Unlike the previous DHS surveys, the 2016 NDHS will not provide estimates for the eco-development regions of the country, however the survey was designed to provide results for each of the newly created seven provinces (Province 1, Province 2, Province 3, Province 4, Province 5, Province 6, and Province 7)."},"study_info":{"abstract":"The primary objective of the 2016 Nepal Demographic and Health Survey (NDHS) is to provide up-to-date estimates of basic demographic and health indicators. The NDHS provides a comprehensive overview of population, maternal, and child health issues in Nepal. Specifically, the 2016 NDHS:\n- Collected data that allowed calculation of key demographic indicators, particularly fertility and under-5 mortality rates, at the national level, for urban and rural areas, and for the country\u2019s seven provinces\n- Collected data that allowed for calculation of adult and maternal mortality rates at the national level\n- Explored the direct and indirect factors that determine levels and trends of fertility and child mortality\n- Measured levels of contraceptive knowledge and practice\n- Collected data on key aspects of family health, including immunization coverage among children, prevalence and treatment of diarrhea and other diseases among children under age 5, maternity care indicators such as antenatal visits and assistance at delivery, and newborn care\n- Obtained data on child feeding practices, including breastfeeding\n- Collected anthropometric measures to assess the nutritional status of children under age 5 and women and men age 15-49\n- Conducted hemoglobin testing on eligible children age 6-59 months and women age 15-49 to provide information on the prevalence of anemia in these groups\n- Collected data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV\/AIDS and evaluated potential exposure to the risk of HIV infection by exploring high-risk behaviors and condom use\n- Measured blood pressure among women and men age 15 and above\n- Obtained data on women\u2019s experience of emotional, physical, and sexual violence\n\nThe information collected through the 2016 NDHS is intended to assist policymakers and program managers in the Ministry of Health and other organizations in designing and evaluating programs and strategies for improving the health of the country\u2019s population. The 2016 NDHS also provides data on indicators relevant to the Nepal Health Sector Strategy (NHSS) 2016-2021 and the Sustainable Development Goals (SDGs).","coll_dates":[{"start":"2016-06","end":"2017-01","cycle":""}],"nation":[{"name":"Nepal","abbreviation":"NPL"}],"geog_coverage":"National coverage","analysis_unit":"- Household\n- Individual\n- Children age 0-5\n- Woman age 15-49\n- Man age 15-49","universe":"The survey covered all de jure household members (usual residents), women age 15-49 years and men age 15-49 years resident in the household.","data_kind":"Sample survey data [ssd]","notes":"The 2016 Nepal 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, current school attendance, birth registration, and migration\n\u2022 Characteristics of the household's dwelling unit, such as the source of water, type of toilet facility, type of fuel used for cooking, number of rooms, materials used for the floor, roof and walls of the house, and possessions of durable goods (including land) and mosquito nets.\n\u2022 Household food security\n\nINDIVIDUAL WOMAN\n\u2022 Identification\n\u2022 Background characteristics (including age, education, and media exposure)\n\u2022 Pregnancy history and child mortality\n\u2022 Knowledge, use, and source of family planning methods\n\u2022 Fertility preferences (including desire for more children and ideal number of children)\n\u2022 Antenatal, delivery, and postnatal care\n\u2022 Breastfeeding and infant feeding practices\n\u2022 Vaccinations and childhood illnesses\n\u2022 Women\u2019s work and husbands\u2019 background characteristics\n\u2022 Domestic violence\n\u2022 Knowledge, awareness, and behavior regarding HIV\/AIDS and other sexually transmitted infections (STIs)\n\u2022 Adult mortality, including maternal mortality\n\u2022 Knowledge, attitudes, and behavior related to other health issues (e.g., tuberculosis)\n\nINDIVIDUAL MAN\n\u2022 Identification\n\u2022 Respondent background\n\u2022 Reproduction\n\u2022 Contraception\n\u2022 Marriage and sexual activity\n\u2022 Fertility preferences\n\u2022 Employment and gender roles\n\u2022 HIV\/AIDS\n\u2022 Other health issues\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 and above\n\u2022 Weight, height, and blood pressure measurement for men age 15 and above\n\nVERBAL AUTOPSY (for neonatal deaths, 0-28 days of age)\n\u2022 Identification\n\u2022 Respondent's background\n\u2022 Information on the deceased\/ stillbirths\n\u2022 Respondent's account of illness\/ events leading to death\n\u2022 Vital registration and certification\n\u2022 General signs and symptoms associated with final illness\n\u2022 History of injuries\/ accidents\n\u2022 Health service utilization\n\u2022 Background and context\n\u2022 Death certificate","study_scope":"The 2016 Nepal 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, current school attendance, birth registration, and migration\n\u2022 Characteristics of the household's dwelling unit, such as the source of water, type of toilet facility, type of fuel used for cooking, number of rooms, materials used for the floor, roof and walls of the house, and possessions of durable goods (including land) and mosquito nets.\n\u2022 Household food security\n\nINDIVIDUAL WOMAN\n\u2022 Identification\n\u2022 Background characteristics (including age, education, and media exposure)\n\u2022 Pregnancy history and child mortality\n\u2022 Knowledge, use, and source of family planning methods\n\u2022 Fertility preferences (including desire for more children and ideal number of children)\n\u2022 Antenatal, delivery, and postnatal care\n\u2022 Breastfeeding and infant feeding practices\n\u2022 Vaccinations and childhood illnesses\n\u2022 Women\u2019s work and husbands\u2019 background characteristics\n\u2022 Domestic violence\n\u2022 Knowledge, awareness, and behavior regarding HIV\/AIDS and other sexually transmitted infections (STIs)\n\u2022 Adult mortality, including maternal mortality\n\u2022 Knowledge, attitudes, and behavior related to other health issues (e.g., tuberculosis)\n\nINDIVIDUAL MAN\n\u2022 Identification\n\u2022 Respondent background\n\u2022 Reproduction\n\u2022 Contraception\n\u2022 Marriage and sexual activity\n\u2022 Fertility preferences\n\u2022 Employment and gender roles\n\u2022 HIV\/AIDS\n\u2022 Other health issues\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 and above\n\u2022 Weight, height, and blood pressure measurement for men age 15 and above\n\nVERBAL AUTOPSY (for neonatal deaths, 0-28 days of age)\n\u2022 Identification\n\u2022 Respondent's background\n\u2022 Information on the deceased\/ stillbirths\n\u2022 Respondent's account of illness\/ events leading to death\n\u2022 Vital registration and certification\n\u2022 General signs and symptoms associated with final illness\n\u2022 History of injuries\/ accidents\n\u2022 Health service utilization\n\u2022 Background and context\n\u2022 Death certificate"},"method":{"data_collection":{"data_collectors":[{"name":"New ERA","abbreviation":"","affiliation":""}],"sampling_procedure":"The sampling frame used for the 2016 NDHS is an updated version of the frame from the 2011 National Population and Housing Census (NPHC), conducted by the Central Bureau of Statistics (CBS).\n\nThe sampling frame contains information about ward location, type of residence (urban or rural), estimated number of residential households, and estimated population. In rural areas, the wards are small in size (average of 104 households) and serve as the primary sampling units (PSUs). In urban areas, the wards are large, with average of 800 households per ward. The CBS has a frame of enumeration areas (EAs) for each ward in the original 58 municipalities. However, for the 159 municipalities declared in 2014 and 2015, each municipality is composed of old wards, which are small in size and can serve as EAs.\n\nThe 2016 NDHS sample was stratified and selected in two stages in rural areas and three stages in urban areas. In rural areas, wards were selected as primary sampling units, and households were selected from the sample PSUs. In urban areas, wards were selected as PSUs, one EA was selected from each PSU, and then households were selected from the sample EAs.\n\nFor further details on sample design, see Appendix A of the final report.","coll_mode":"Face-to-face [f2f]","research_instrument":"Six questionnaires were administered in the 2016 NDHS: the Household Questionnaire, the Woman\u2019s Questionnaire, the Man\u2019s Questionnaire, the Biomarker Questionnaire, the Fieldworker Questionnaire, and the Verbal Autopsy Questionnaire (for neonatal deaths). The first five questionnaires, based on The DHS Program\u2019s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Nepal. The Verbal Autopsy Questionnaire was based on the recent 2014 World Health Organization (WHO) verbal autopsy instruments (WHO 2015a).","coll_situation":"The fieldwork for the 2016 NDHS was launched under close supervision on June 19, 2016, in the clusters in Kathmandu. Sixteen teams consisting of one supervisor, one male interviewer, and three female interviewers were spread across the different Kathmandu clusters. The teams were closely monitored by the trainers and quality controllers. After completion of the fieldwork in Kathmandu in the first week, teams were brought back to the central office for a review session in which they had an opportunity to clarify any questions they had. The teams were then dispatched to their respective districts. Data collection lasted until January 31, 2017. The fieldwork in some districts took longer than expected due to the monsoon season, during which flooding and landslides impacted the mobility of the field teams.\n\nFieldwork monitoring was an integral part of the 2016 NDHS, and several rounds of monitoring were carried out by the NDHS core team, the quality controllers, and ICF staff. The technical team from the Ministry of Health and the Nepal Health Research Council also monitored the fieldwork. The monitors were provided with guidelines for overseeing the fieldwork. Weekly field check tables were generated from the completed interviews that were sent to the central office to monitor progress in the fieldwork, and regular feedback was sent out to the teams.","weight":"A spreadsheet containing all sampling parameters and selection probabilities was prepared to facilitate the calculation of the design weight. Design weight was adjusted for household non-response and also for individual non-response to get the sampling weights for households, for women\u2019s and men\u2019s surveys, respectively. The differences of the household sampling weight and the individual sampling weights were introduced by individual non-response. The final sampling weights were normalized in order to give the total number of unweighted cases equal to the total number of weighted cases at national level, for both household weight and individual weight, respectively. The normalized weights are relative weights, which are valid for estimating means, proportions, and ratios, but not valid for estimating population totals and for pooled data.\n\nFor further details on sampling weights, see Appendix A.4 of the final report.","cleaning_operations":"The processing of the 2016 NDHS data began simultaneously with the fieldwork. As soon as data collection was completed in each cluster, all electronic data files were transferred via the IFSS to the New ERA central office in Kathmandu. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The biomarker paper questionnaires were compared with the electronic data files to check for any inconsistencies in data entry. Data entry and editing were carried out using the CSPro software package. The secondary editing of the data was completed in the second week of February 2017. The final cleaning of the data set was carried out by The DHS Program data processing specialist and was completed by the end of February 2017."},"analysis_info":{"response_rate":"A total of 11,473 households were selected for the sample, of which 11,203 were occupied. Of the occupied households, 11,040 were successfully interviewed, yielding a response rate of 99%.\n\nIn the interviewed households, 13,089 women age 15-49 were identified for individual interviews; interviews were completed with 12,862 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 4,235 men age 15-49 were identified and 4,063 were successfully interviewed, yielding a response rate of 96%.\n\nResponse rates were lower in urban areas than in rural areas. The difference was slightly more prominent for men than for women, as men in urban areas were often away from their households for work.","sampling_error_estimates":"The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Non-sampling errors result from mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding 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 2016 Nepal DHS (NDHS) 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 2016 NDHS 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 between 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 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 2016 NDHS 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 either ISSA or SAS, using programs developed by ICF. These programs use the Taylor linearization method of 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\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- 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- Sibling size and sex ratio of siblings\n- Pregnancy-related mortality trends\n\nSee details of the data quality tables in Appendix C of the survey final report."}},"data_access":{"dataset_use":{"spec_perm":[{"txt":"","required":"no","form_no":"","uri":""}],"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":"11473","var_count":"52","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":"49064","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":"11040","var_count":"97","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":"11473","var_count":"50","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":"49064","var_count":"7","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":"9163","var_count":"64","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F7","file_name":"RECH6","description":"HOUSEHOLD\n- Children Height\/Weight\/Hemoglobin","case_count":"2618","var_count":"46","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F8","file_name":"RECHMA","description":"HOUSEHOLD\n- Men Height\/Weight\/Hemoglobin","case_count":"6589","var_count":"63","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F9","file_name":"RECHMG","description":"HOUSEHOLD\n- Migration","case_count":"8996","var_count":"10","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F10","file_name":"REC01","description":"WOMAN\n- Respondent's basic data","case_count":"13089","var_count":"45","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F11","file_name":"REC4A","description":"WOMAN\n- Child's health","case_count":"5038","var_count":"119","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F12","file_name":"REC11","description":"WOMAN\n- Respondent's basic data (continued)","case_count":"12862","var_count":"64","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F13","file_name":"REC21","description":"WOMAN\n- Reproduction and Birth History","case_count":"26028","var_count":"24","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F14","file_name":"REC22","description":"WOMAN\n- Reproduction (continued)","case_count":"12862","var_count":"45","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F15","file_name":"REC31","description":"WOMAN\n- Contraception 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vaccinations","case_count":"2994","var_count":"138","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F20","file_name":"REC44","description":"WOMAN\n- Child's Height and Weight","case_count":"5038","var_count":"32","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F21","file_name":"REC51","description":"WOMAN\n- Marriage and Sexual Exposure","case_count":"12862","var_count":"29","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F22","file_name":"REC61","description":"WOMAN\n- Fertility Preferences","case_count":"12862","var_count":"30","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F23","file_name":"REC71","description":"WOMAN\n- Partner's Characteristics","case_count":"12862","var_count":"37","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F24","file_name":"REC75","description":"WOMAN\n- AIDS, STIs and Condom Use","case_count":"12862","var_count":"144","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F25","file_name":"REC80","description":"WOMAN\n- HIV, STIs and Condom Use (continued)","case_count":"12862","var_count":"77","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F26","file_name":"REC81","description":"WOMAN\n- Characteristics of Interview","case_count":"12862","var_count":"15","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F27","file_name":"REC82","description":"WOMAN\n- Calendar","case_count":"77172","var_count":"4","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F28","file_name":"REC83","description":"WOMAN\n- Maternal Mortality","case_count":"59437","var_count":"19","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F29","file_name":"REC84","description":"WOMAN\n- Maternal Mortality (suite)","case_count":"12862","var_count":"6","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F30","file_name":"REC91","description":"WOMAN\n- Country specific variables","case_count":"13089","var_count":"217","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F31","file_name":"REC92","description":"WOMAN\n- Country specific Birth History variables","case_count":"26028","var_count":"6","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F32","file_name":"REC94","description":"WOMAN\n- Country specific Maternity variables","case_count":"5038","var_count":"61","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F33","file_name":"REC95","description":"WOMAN\n- Country specific Health and Vaccination variables","case_count":"4949","var_count":"6","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F34","file_name":"REC97","description":"WOMAN\n- Country specific Pregnancy history","case_count":"29822","var_count":"31","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F35","file_name":"RECDV","description":"WOMAN\n- Domestic 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