{"type":"survey","study_desc":{"title_statement":{"idno":"RWA_2014_DHS_v01_M","title":"Demographic and Health Survey 2014 - 2015","alt_title":"DHS 2014-15 \/ RDHS 2014-15"},"authoring_entity":[{"name":"National Institute of Statistics of Rwanda (NISR)","affiliation":"Government of Rwanda"}],"production_statement":{"producers":[{"name":"Ministry of Health","affiliation":"","role":"Collaboration"},{"name":"IFC International","affiliation":"","role":"Provided technical assistance"}],"funding_agencies":[{"name":"Government of Rwanda","abbreviation":"GovRWA","role":"Funded the study"},{"name":"United States Agency for International Development","abbreviation":"USAID","role":"Funded the study"},{"name":"One United Nations","abbreviation":"ONE UN","role":"Funded the study"},{"name":"Global Fund","abbreviation":"GF","role":"Funded the study"},{"name":"World Vision International","abbreviation":"WVI","role":"Funded the study"},{"name":"Partners in Health","abbreviation":"PIH","role":"Funded the study"},{"name":"Suisse Development Cooperation","abbreviation":"SDC","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":"The 2014-15 Rwanda Demographic and Health Survey (RDHS) is the fifth survey of its kind, following standard DHS surveys conducted in 1992, 2000, 2005, and 2010. In addition in Rwanda interim RDHS was conducted in 2007-08. A nationally representative sample of 12,800 households, was selected. All women age 15-49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for the survey. A survey of men was also conducted in a subsample consisting of every second household. All men age 15-59 who were usual residents or who slept in the subsampled households the night before the survey were eligible to be interviewed. Altogether, 13,497 women age 15-49 and 6,217 men age 15-59 were interviewed. As with prior surveys, the main objectives of the 2014-15 RDHS are 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; knowledge and attitudes toward HIV\/AIDS and other sexually transmitted infections (STIs); and prevalence of HIV among the population.\n\nThe survey was designed to produce representative estimates for the main demographic and health indictors for the country as a whole, for the urban and rural areas, and for each of the five provinces. For some indicators, representative results may be available for each of the thirty districts."},"study_info":{"abstract":"From 2014 to 2015, with the aim of collecting data to monitor progress across Rwanda\u2019s health programs and policies, the Government of Rwanda (GOR) conducted the Rwanda Demographic and Health Survey (RDHS) through the Ministry of Health (MOH) and the National Institute of Statistics of Rwanda (NISR) with the members of the national steering committee to the DHS and the technical assistance of ICF International.\n\nThe main objectives of the 2014-15 RDHS were to:\n\u2022 Collect data at the national level to calculate essential demographic indicators, especially fertility and infant and child mortality, and analyze the direct and indirect factors that relate to levels and trends in fertility and child mortality\n\u2022 Measure levels of knowledge and use of contraceptive methods among women and men\n\u2022 Collect data on family health, including immunization practices; prevalence and treatment of diarrhea, acute upper respiratory infections, and fever among children under age 5; antenatal care visits; assistance at delivery; and postnatal care\n\u2022 Collect data on knowledge, prevention, and treatment of malaria, in particular the possession and use of treated mosquito nets among household members, especially children under age 5 and pregnant women\n\u2022 Collect data on feeding practices for children, including breastfeeding\n\u2022 Collect data on the knowledge and attitudes of women and men regarding sexually transmitted infections (STIs) and HIV and evaluate recent behavioral changes with respect to condom use \n\u2022 Collect data for estimation of adult mortality and maternal mortality at the national level\n\u2022 Take anthropometric measurements to evaluate the nutritional status of children, men, and women\n\u2022 Assess the prevalence of malaria infection among children under age 5 and pregnant women using rapid diagnostic tests and blood smears\n\u2022 Estimate the prevalence of HIV among children age 0-14 and adults of reproductive age\n\u2022 Estimate the prevalence of anemia among children age 6-59 months and adult women of reproductive age\n\u2022 Collect information on early childhood development\n\u2022 Collect information on domestic violence","coll_dates":[{"start":"2014-11","end":"2015-04","cycle":""}],"nation":[{"name":"Rwanda","abbreviation":"RWA"}],"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), all women age 15-49 years and all men age 15-59 who were usual residents in the household.","data_kind":"Sample survey data [ssd]","notes":"The 2014-2015 Rwanda 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, and highest educational attainment\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 ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status) \n\u2022 Weight, height, hemoglobin measurements and malaria testing for children age 0-5\n\u2022 Weight, height, hemoglobin measurements and malaria testing for women age 15-49\n\u2022 HIV testing for women age 15-49\n\u2022 Weight, height, measurement and HIV testing for men age 15-59\n\u2022 HIV testing for children age 0-14\n\nINDIVIDUAL WOMAN\n\u2022 Background characteristics (education, religion, media exposure, etc.)\n\u2022 Reproduction\n\u2022 Contraception\n\u2022 Pregnancy and postnatal care\n\u2022 Child immunization, health and nutrition\n\u2022 Marriage and sexual activity\n\u2022 Fertility preferences\n\u2022 Husband's background and woman's work\n\u2022 HIV\/AIDS\n\u2022 Other health issues\n\u2022 Adult mortality\n\u2022 Female domestic violence\n\nINDIVIDUAL MAN\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\u2022 Male domestic violence","study_scope":"The 2014-2015 Rwanda 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, and highest educational attainment\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 ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status) \n\u2022 Weight, height, hemoglobin measurements and malaria testing for children age 0-5\n\u2022 Weight, height, hemoglobin measurements and malaria testing for women age 15-49\n\u2022 HIV testing for women age 15-49\n\u2022 Weight, height, measurement and HIV testing for men age 15-59\n\u2022 HIV testing for children age 0-14\n\nINDIVIDUAL WOMAN\n\u2022 Background characteristics (education, religion, media exposure, etc.)\n\u2022 Reproduction\n\u2022 Contraception\n\u2022 Pregnancy and postnatal care\n\u2022 Child immunization, health and nutrition\n\u2022 Marriage and sexual activity\n\u2022 Fertility preferences\n\u2022 Husband's background and woman's work\n\u2022 HIV\/AIDS\n\u2022 Other health issues\n\u2022 Adult mortality\n\u2022 Female domestic violence\n\nINDIVIDUAL MAN\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\u2022 Male domestic violence"},"method":{"data_collection":{"data_collectors":[{"name":"National Institute of Statistics of Rwanda","abbreviation":"NISR","affiliation":"Government of Rwanda"}],"sampling_procedure":"Sample Design\nThe sampling frame used for the 2014-15 RDHS was the 2012 Rwanda Population and Housing Census (RPHC). The sampling frame consisted of a list of enumeration areas (EAs) covering the entire country, provided by the National Institute of Statistics of Rwanda, the implementing agency for the RDHS. An EA is a natural village or part of a village created for the 2012 RPHC; these areas served as counting units for the census.\n\nThe 2014-15 RDHS followed a two-stage sample design and was intended to allow estimates of key indicators at the national level as well as for urban and rural areas, five provinces, and each of Rwanda's 30 districts (for some limited indicators). The first stage involved selecting sample points (clusters) consisting of EAs delineated for the 2012 RPHC. A total of 492 clusters were selected, 113 in urban areas and 379 in rural areas.\n\nThe second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected EAs from July 7 to September 6, 2014, and households to be included in the survey were randomly selected from these lists. Twenty-six households were selected from each sample point, for a total sample size of 12,792 households. However, during data collection, one of the households was found to actually be two households, which increased the total sample to 12,793. Because of the approximately equal sample sizes in each district, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.\n\nAll women age 15-49 who were either permanent residents of the household or visitors who stayed in the household the night before the survey were eligible to be interviewed. In half of the households, all men age 15-59 who either were permanent household residents or were visiting the night before the survey were eligible to be interviewed.\n\nIn the subsample of households not selected for the male survey, anemia and malaria testing were performed among eligible women who consented to being tested. With the parent's or guardian's consent, children aged 6-59 months were tested for anemia and malaria in this subsample. Height and weight information was collected from eligible women, and children (age 0-5) in the same subsample. In the subsample of households selected for male survey, blood spot samples were collected for laboratory testing of HIV from eligible women and men who consented. Height and weight information was collected from eligible men. In one-third of the same subsample (or 15 percent of the entire sample), blood spot samples were collected for laboratory testing of children age 0-14 for HIV.\n\nThe domestic violence module was implemented in the households selected for the male survey: The domestic violence module for men was implemented in 50 percent of the household selected for male survey and domestic violence for women was conducted in the remaining 50 percent of household selected for male survey (or 25 percent of the entire sample, each).\n\nFor further details on sample selection, see Appendix A of the final report.","coll_mode":"Face-to-face [f2f]","research_instrument":"Three types of questionnaires were used in the 2014-15 RDHS: the Household Questionnaire, the Woman\u2019s Questionnaire, and the Man\u2019s Questionnaire. They are based on questionnaires developed by the worldwide DHS Program and on questionnaires used during the 2010 RDHS. To reflect relevant issues in population and health in Rwanda, the questionnaires were adapted during a series of technical meetings with various stakeholders from government ministries and agencies, nongovernmental organizations, and international donors. The questionnaires were translated from English into Kinyarwanda.\n\nThe Household Questionnaire was used to list all of the usual members and visitors in the selected households as well as to identify women and men eligible for individual interviews. Basic information was collected on the characteristics of each person listed, including relationship to the head of the household, sex, residence status, age, and marital status along with survival status of children\u2019s parents, education, birth registration, health insurance coverage, and tobacco use.\n\nThe Woman\u2019s Questionnaire was administered to all women age 15-49 living in the sampled households.\n\nThe Man\u2019s Questionnaire was administered to all men age 15-59 living in every second household in the sample. It was similar to the Woman\u2019s Questionnaire but did not include questions on use of contraceptive methods or birth history; pregnancy and postnatal care; child immunization, health, and nutrition; or adult and maternal mortality.","coll_situation":"PRETEST\nA pretest was conducted from August 25 to September 22, 2014. Thirty-four individuals (17 women and 17 men) participated in the four-week pretest training and fieldwork practice for the 2014-15 RDHS. The majority of participants had worked in previous RDHS surveys. Training was conducted by representatives from the NISR, the MOH, the RBC Malaria and Other Parasitic Diseases Division, the RBC HIV division, and the RBC NRL, with technical assistance from ICF International. UNICEF provided training on the early childhood development module. Classroom instruction was provided during the first three weeks, and pretest fieldwork took place over five days in three rural villages and two urban villages. After the fieldwork, a debriefing session was held with the pretest field staff, and modifications to the questionnaires were made based on lessons drawn from the exercise.\n\nTRAINING OF FIELD STAFF\nThe main training for the 2014-15 RDHS started on October 5, 2014, and ended on November 2, 2014. A total of 136 participants from across the country were invited to participate in the training. They were selected based on merit. Eighty-eight of the participants were female, and 48 were male. From October 6-25, the training focused on the questionnaires. These sessions were conducted by NISR trainers with support from ICF International. Class presentations by trainers were followed by mock interviews, group practice, and role playing among participants in the classroom. Guest speakers and experts (e.g., from the MOH, the RBC, and UNICEF) made brief presentation son the national health strategies related to nutrition, contraception, malaria, maternal and child health, the HIV voluntary counseling and testing component, and early childhood development before the questionnaire training session corresponding to each of these topics. This led to an understanding among fieldworkers that items included in the questionnaire would be useful in evaluating these health topics.\n\nAll participants were trained on the questionnaires through October 26. From October 27-30, 34 participants identified as health technicians were separated and trained on biomarkers. Meanwhile, the remaining participants continued to be trained on the questionnaires. Training on biomarkers was provided by representatives from the NRL with support from ICF International. Health technicians learned how to withdrawal blood samples for HIV testing, how to prepare blood slides for malaria testing, and how to conduct anemia and rapid malaria testing. In addition, procedures for handling and packaging dried blood spots and slides were reviewed and demonstrated. Training on taking anthropometry measurements (weight and height) was also covered in detail. Training included PowerPoint presentations to illustrate procedures and emphasized practice among lab technicians in order to ensure accuracy.\n\nAt the end of the main training, 17 teams were formed, each consisting of a team leader, a field editor, a health technician, a male interviewer, and three female interviewers. Team leaders received additional training on how to identify the selected households and different subsamples, data quality control procedures, and fieldwork coordination. Field editors received additional training on how to edit the questionnaires and on data quality control procedures.\n\nFIELDWORK\nData collection for the 2014-15 RDHS was carried out by 17 field teams from November 9, 2014, to April 8, 2015. Each team was provided a vehicle with a driver. All questionnaires and blood specimens were transferred to the NISR office every 3-4 days by 10 supervisors from the NISR and NRL\/RBC who also coordinated and supervised fieldwork activities. ICF International provided technical assistance during the entire five months of data collection period.","weight":"Due to the non-proportional allocation of the sample to the different provinces and to their districts and the possible differences in response rates, sampling weights are required for any analysis using the 2014-15 RDHS-V data to ensure the actual representative of the survey results at national level and as well as at domain level. Since the RDHS sample is a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities separately for each sampling stage and for each cluster.\n\nThe final sampling weights were normalized in order to give the total number of un-weighted cases equal to the total number of weighted cases at national level, for both household weights and individual weights. 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. The sampling weights for HIV testing were calculated in a similar way, but the normalization of the HIV testing weights is different compared to the individual survey weights. The HIV testing weights are normalized for women and men together at the national level, in order that the HIV prevalence rates calculated for both sexes combined are valid. Sampling weights for the domestic violence surveys were calculated based on the number of eligible respondents in the households selected for domestic violence module, for male and female surveys respectively.\n\nA number of sets of weights were calculated:\n\u2022 one set for all households selected for the survey\n\u2022 one set for the women\u2019s individual survey\n\u2022 one set for households selected for the male survey\n\u2022 one set for the male individual survey\n\u2022 one set for women selected for the domestic violence survey\n\u2022 one set for men selected for the domestic violence survey\n\u2022 one set for women\u2019s HIV testing\n\u2022 one set for men\u2019s HIV testing\n\u2022 one set for HIV testing for children 0-14 years\n\nAlso the number of weighted cases by using the normalized weight has no direct relationship with the survey precision because it is relative. Especially for oversampled areas, the number of weighted cases is much smaller than the number of un-weighted cases which is directly related to survey precision.\n\nFor further details on sampling weight, see Appendix A.4 of the final report.","cleaning_operations":"The processing of the 2014-15 RDHS data began as soon as questionnaires were received from the field. Completed questionnaires were returned to NISR headquarters. The numbers of questionnaires and blood samples (DBS and malaria slides) were verified by two receptionists. Questionnaires were then checked, and open-ended questions were coded by four editors who had been trained for this task and who had also attended the questionnaire training sessions for the field staff. Blood samples (DBS and malaria slides) with transmittal sheets were sent respectively to the RBC\/NRL and Parasitological and Entomology Laboratory to be screened for HIV and tested for malaria.\n\nQuestionnaire data were entered via the CSPro computer program by 17 data processing personnel who were specially trained to execute this activity. Data processing was coordinated by the NISR data processing officer. ICF International provided technical assistance during the entire data processing period.\n\nProcessing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were generated regularly during data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue in areas of high quality and to correct areas of needed improvement. Feedback was individually tailored to each team. Data entry, which included 100 percent double entry to minimize keying errors, and data editing were completed on April 26, 2015. Data cleaning and finalization were completed on May 15, 2015."},"analysis_info":{"response_rate":"A total of 6,249 men age 15-59 were identified in this subsample of households. Of these men, 6,217 completed individual interviews, yielding a response rate of 99.5 percent.","sampling_error_estimates":"The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and 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 2014-15 Rwanda Demographic and Health Survey (RDHS) 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 2014-15 RDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.\n\nA 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 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 2014-15 RDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2014-15 RDHS is a SAS program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.\n\nThe Taylor linearization method treats any percentage or average as a ratio estimate, r = y\/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.\n\nNote: A more detailed description of estimate of sampling error is presented in APPENDIX B of the survey 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- Nutritional status of children based on the NCHS\/CDC\/WHO International Reference Population\n- Prevalence of anemia in children in 2005\n- Prevalence of anemia in women in 2005\n- Prevalence of anemia in children in 2007-08\n- Prevalence of anemia in women in 2007-08\n- Rotavirus and pneumococcal vaccinations by source of information\n- Rotavirus and pneumococcal vaccinations by background characteristics\n- Support for learning\n- Adult mortality rates\n- Smoking\n\nNote: See detailed data quality tables in APPENDIX C of the report."}},"data_access":{"dataset_availability":{"access_place":"The DHS Program","access_place_uri":"http:\/\/dhsprogram.com\/data\/available-datasets.cfm","original_archive":"The DHS Program\nhttp:\/\/dhsprogram.com\/data\/available-datasets.cfm\nCost: None"},"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":"12793","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":"54905","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":"12699","var_count":"91","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":"12699","var_count":"15","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":"54905","var_count":"12","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":"13765","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 Height\/Weight\/Hemoglobin","case_count":"3928","var_count":"42","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":"6437","var_count":"37","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F9","file_name":"RECHMH","description":"HOUSEHOLD \n- Malaria: by Household Member","case_count":"54905","var_count":"25","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F10","file_name":"RECHMH2","description":"HOUSEHOLD \n- Malaria: by Household Member - Country Specific","case_count":"54905","var_count":"4","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F11","file_name":"RECHML","description":"HOUSEHOLD \n- Malaria: by Mosquito Bed 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