TZA_2010_KHDS_v01_EN_M_v01_A_OCS
Kagera Health and Development Survey 2010
Name | Country code |
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United Republic of Tanzania | TZA |
Living Standards Measurement Study [hh/lsms]
The Kagera Health and Development Survey 2010 (KHDS 2010) took place in 2010 as the sixth survey wave. Earlier waves of the survey include the four waves from 1991-1994, and the fifth wave in 2004.
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” 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” 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.
Sample survey data [ssd]
Households
The scope of the KHDS 2010 includes the following topics that are also sections of the questionnaire:
(a) HOUSEHOLD QUETIONNAIRE
(b) CONSUMPTION AND PRICE QUESTIONNAIRE
(c) WEDDING QUESTIONNAIRE
Topic | Vocabulary |
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Health | FAO |
Financial Sector | FAO |
Access to Finance | FAO |
Migration & Remittances | FAO |
Nutrition | FAO |
Population & Reproductive Health | FAO |
Labor | FAO |
Agriculture & Rural Development | FAO |
Food (production, crisis) | FAO |
Land (policy, resource management) | FAO |
Regional
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.
Name |
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Economic Development Initiatives |
Name | Affiliation | Role |
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Vera Ngowi | Muhimbili University of Health and Allied Sciences | Technical assistance |
Gideon Kwesigabo | Muhimbili University of Health and Allied Sciences | Technical assistance |
Innocent Semali | Muhimbili University of Health and Allied Sciences | Technical assistance |
Respichius Mitti | Economic Development Initiatives | Technical assistance |
Leonard Kyaruzi | Economic Development Initiatives | Technical assistance |
Joachim De Weerdt | Economic Development Initiatives | Technical assistance |
Kathleen Beegle | World Bank | Technical assistance |
Helene Bie Lilleor | Rockwool Foundation | Technical assistance |
Kalle Hirvonen | University of Sussex | Technical assistance |
Sofya Krutikova | University of Oxford | Technical assistance |
Martina Kirchberger | University of Oxford | Technical assistance |
Name | Role |
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Rockwool Foundation | Financial assistance |
World Bank | Financial assistance |
Sample size of this study followed the KHDS 91-94 Household Sampling procedure:
(a) SAMPLE DESIGN AND SELECTION
Qualitative 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.
(b) SAMPLING PROCEDURE
The 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.
Because people have moved out of their original household, the new sample in KHDS 2004 consists of over 2,700 households from the baseline 832, which were re-contacted. Much of the success in re-contacting respondents was due to the effort to track people who had moved out of the baseline villages. One-half of all households interviewed were tracking cases, meaning they did not reside in the baseline communities. Of those households tracked, only 38 percent were located nearby the baseline community. Overall, 32 percent of all households were not located near the baseline communities. While tracking is costly, it is an important exercise because migration and dissolution of households are often hypothesized to be important responses to hardship. Excluding these households in the sample raises obvious concerns regarding the selectivity of attrition. In particular, out-migration from the village, dissolving of households, and even marriage, may be responses to adult mortality. At the same time, tracking will provide a unique opportunity to study these coping mechanisms: who uses them, what is the effect, do they get people out of poverty or do they themselves constitute a poverty trap. Turning to recontact rates of the sample of 6,204 respondents, Re-interview rates are monotonically decreasing with age, although the reasons (deceased or not located) vary by age group. The older respondents were much more likely to be located if living, which is consistent with higher migration rates among the young adults in the sample. Among the youngest respondents, over three-quarter were successfully re-interviewed. Excluding people who died, 82 percent of all respondents were re-interviewed. Without tracking, re-interview rates of surviving respondents would have fallen from 82 percent to 52 percent. Non-local migration is not trivial; restricting the tracking to nearby villages would have resulted in 63 percent recontact of survivors. Migration proved to be an important factor in determining whether someone was re-contacted. Respondents who were untraced were much more likely to be residing outside Kagera (52 percent) compare to their counterparts who were re-interviewed (9 percent). KHDS 2004 tracked international migrants for Uganda only. Although the location of those in other countries was known, they were not traced. For those respondents who were not re-interviewed, the KHDS 2004 gives some information about their interactions with the re-interviewed respondents. Survey modules on the frequency of contact with all previous household members inform on the cash, in-kind and labour interactions between former household members.
Start | End |
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2010-04 | 2010-10 |
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
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yes | 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 |
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:
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.
Three copies of all publications, conference papers, or other research reports based entirely or in part upon the requested data will be supplied to:
The World Bank
Development Economics Research Group
LSMS Database Administrator
MSN MC3-306
1818 H Street, NW
Washington, DC 20433, USA
tel: (202) 473-9041
fax: (202) 522-1153
e-mail: [email protected]
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).
Users who download the data may not pass the data to third parties.
The database cannot be used for commercial ends, nor can it be sold.
Use of the dataset must be acknowledged by including a citation which would include:
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
Name | Affiliation | URL | |
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LSMS Data Manager | The World Bank | [email protected] | surveys.worldbank.org/lsms |
DDI_TZA_2010_KHDS_v01_EN_M_v01_A_OCS_FAO
Name | Affiliation | Role |
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Office of Chief Statistician | Food and Agriculture Organization | Adoption of metadata for FAM |
Development Economics Data Group | The World Bank | Documentation of the DDI |
TZA_2010_KHDS_v01_EN_M_v01_A_OCS_v01