{"doc_desc":{"title":"TZA_2004_KHDS_v01_EN_M_v01_A_OCS","idno":"DDI_TZA_2004_KHDS_v01_EN_M_v01_A_OCS_FAO","producers":[{"name":"Office of Chief Statistician","abbreviation":"OCS","affiliation":"Food and Agriculture Organization","role":"Adoption of metadata for FAM"},{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Documentation of the DDI"}],"version_statement":{"version":"TZA_2004_KHDS_v01_EN_M_v01_A_OCS_v01"}},"study_desc":{"title_statement":{"idno":"TZA_2004_KHDS_v01_EN_M_v01_A_OCS","title":"Kagera Health and Development Survey 2004","alt_title":"KHDS 2004"},"authoring_entity":[{"name":"Economic Development Initiatives","affiliation":""}],"production_statement":{"funding_agencies":[{"name":"Danish Agency for Development Assistance","abbreviation":"DANIDA","role":""},{"name":"Knowledge for Change Trust Fund at the World Bank","abbreviation":"","role":""}]},"distribution_statement":{"contact":[{"name":"LSMS Data Manager","affiliation":"The World Bank","email":"lsms@worldbank.org","uri":"surveys.worldbank.org\/lsms"}]},"series_statement":{"series_name":"Living Standards Measurement Study [hh\/lsms]","series_info":"The Kagera Health and Development Survey 2004 (KHDS 2004) took place in 2004 as the fifth survey wave. Earlier waves of the survey include the four waves from 1991 till 1994."},"study_info":{"topics":[{"topic":"Health","vocab":"FAO","uri":""},{"topic":"Agriculture & Rural Development","vocab":"FAO","uri":""},{"topic":"Food (production, crisis)","vocab":"FAO","uri":""},{"topic":"Migration & Remittances","vocab":"FAO","uri":""},{"topic":"Livestock","vocab":"FAO","uri":""},{"topic":"Population & Reproductive Health","vocab":"FAO","uri":""},{"topic":"Nutrition","vocab":"FAO","uri":""},{"topic":"Prices statistics","vocab":"FAO","uri":""},{"topic":"Financial Sector","vocab":"FAO","uri":""},{"topic":"Access to Finance","vocab":"FAO","uri":""}],"abstract":"The Kagera Health and Development Survey was conducted to estimate the economic impact of the death of prime-age adults on surviving household members. This impact was primarily measured as the difference in well-being between households with and without the death of a prime-age adult (15-50), over time. An additional hypothesis was that households in communities with high mortality rates might be less successful in coping with a prime-age adult death. Thus, the research design called for collecting extensive socioeconomic information from households with and without adult deaths in communities with high and low adult mortality rates. Data collected by the KHDS can be used to estimate the \"direct costs\u201d of illness and mortality in terms of out-of-pocket expenditures, the \"indirect costs\" in terms of foregone earnings of the patient, and the \"coping costs\u201d in terms of changes in the well-being of other household members and in the allocation on of time and resources within the household as these events unfold. The KHDS was an economic survey. It did not attempt to measure knowledge, attitudes, behaviours or practices related to HIV infection or AIDS in households or communities. It also did not collect blood samples or attempt to measure HIV seroprevalence; this would have substantially affected the costs and complexity of the research and possibly the willingness of households to participate. Information on the cause of death in the KHDS household survey is based on the reports of surviving household members; the researchers maintained that household coping will respond to the perceived cause of death, irrespective of whether the deceased actually died of AIDS. Lastly, the KHDS did not attempt to measure the psycho-social impact of HIV infection or AIDS deaths.","coll_dates":[{"start":"2004-01","end":"2004-08","cycle":""}],"nation":[{"name":"United Republic of Tanzania","abbreviation":"TZA"}],"geog_coverage":"Regional","analysis_unit":"Households","universe":"The KHDS attempts to re-interview all respondents interviewed in the original KHDS 1991-1994, irrespective of whether the respondent had moved out of the original village, region or country or was residing in a new household.","data_kind":"Sample survey data [ssd]","notes":"(a) HOUSEHOLD QUESTIONNAIRE\n\nSection 0 Basic Survey information \nSection 1 Household Roster \nSection 2 Previous Children Residing Elsewhere \nSection 3 Main Activities of the Household \nSection 4 Information on Parents \nSection 5 Education\nSection 6 Health \nSection 7 Activities and Non-Labour Income \nSection 8 Individual Expenditures \nSection 9 Migration \nSection 10 Shocks Experienced in the Past 10 Years \nSection 11 Farming \nSection 11 Agriculture \nSection 12 Livestock \nSection 13 Non-Farm Self-Employment \nSection 14 Housing \nSection 15 Durable Goods, Expenditures, Inheritance, and Bride Price\nSection 16 Food Consumption and Expenditures \nSection 17 Informal Organizations, Ability to Cope, Assistance from Organizations\nSection 18 Gifts and Loans Received\/Sent \nSeparate Form Anthropometry \nSeparate Form Mortality of Previous Household Members \n\n(b) COMMUNITY QUESTIONNAIRE\n\nGPS coordinates\nSection 0 Selecting respondents \nSection 1 Demographic information \nSection 2 Economy and Infrastructure \nSection 3 Education \nSection 4 Health \nSection 5 Agriculture \nSection 6 Culture \nSection 7 Shocks in the past 10 years \n\n(c) PRICE QUESTIONNAIRE\n\nGPS coordinates\nPart I Food Prices \nPart II Pharmaceutical Prices \nPart III Non-Food Prices \n\n(d) SCHOOL QUESTIONNAIRE\n\nPart A School characteristics, enrolment and fees \nPart B Textbooks, Standard 7 completion, number of teachers employed and assistance or contributions"},"method":{"data_collection":{"sampling_procedure":"Sample size of this study was 900 households following the KHDS 91-94 Household Sampling procedure:\n\n(a) SAMPLE DESIGN AND SELECTION \n\nQualitative studies of small samples of households can point to hypotheses about the ways in which fatal adult illness affects households. However, policymakers need to know which households are suffering the most, the size of the impact, the extent to which they suffer more than other households in a poor country, and the potential costs and effects of assistance programs. For this purpose, the sample of households must be representative of the population, a random sample for which the probability of selecting each household from the whole population is known. The KHDS used a random sample that was stratified geographically and according to several measures of adult mortality risk. This strategy allowed the team to ensure an adequate number of households with an adult death in the sample while retaining the ability to extrapolate the results to the entire population. The results from the household survey show that stratification of the sample on mortality risk at both the community and household level proved to be worthwhile. Among the 816 households in the original sample that began the survey in the first passage, 91 had an adult death in the course of the survey-more than three times the expected number (25) had the households been drawn at random with no stratification. The 816 households that began the survey in the first passage were observed, on average, for 1.6 years, generating a total of 1,322.7 years of observation. The average probability of an adult death per household per year, according to the 1988 Tanzania Census, is 0.0188. Thus, the expected number of deaths from a random sample of 816 households observed for 1.6 years is 25. Because households were added to the sample to compensate for attrition, a total of 918 households were eventually interviewed at least once. Between the first and last interview, 102 of these households had an adult death, compared to 27 households that would have been expected to have a death from a non-stratified sample. \n\n(b) SAMPLING PROCEDURE \n\nThe KHDS household sample was drawn in two stages, with stratification based on geography in the first stage and mortality risk in both stages. It used a two-stage stratified random sampling procedure.","coll_mode":["Face-to-face [f2f]"]},"analysis_info":{"response_rate":"96 percent"}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO","required":"yes","form_no":"","uri":""}],"cit_req":"Use of the dataset must be acknowledged by including a citation which would include: \n- Identification of the Primary Investigator \n- Title of the survey (including the country name and year of implementation)\n- Survey reference number\n- Source and date of download \n\nExample: \nKagera Health and Development Survey 2004. Ref. TZA_2004_KHDS_v01_M. The World Bank.","conditions":"In receiving these data it is recognized that the data are supplied for use within my organization, and I agree to the following stipulations as conditions for the use of the data:\n\n1. The data are supplied solely for the use described in this form and will not be made available to other organizations or individuals. Other organizations or individuals may request the data directly.\n\n2. Three copies of all publications, conference papers, or other research reports based entirely or in part upon the requested data will be supplied to:\n   \nThe World Bank\nDevelopment Economics Research Group\nLSMS Database Administrator\nMSN MC3-306\n1818 H Street, NW\nWashington, DC 20433, USA\n\ntel: (202) 473-9041\nfax: (202) 522-1153\ne-mail: lsms@worldbank.org\n\n3. The researcher will refer to the 2004 Kagera, Tanzania Health and Development Survey as the source of the information in all publications, conference papers, and manuscripts. At the same time, the World Bank is not responsable for the estimations reported by the analyst(s).\n\n4. Users who download the data may not pass the data to third parties.\n\n5. The database cannot be used for commercial ends, nor can it be sold.","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"}