Simbayi, Leickness Chisamu
Rehle, Thomas Michael
Human Sciences Research Council
Embargo End Date
Human Sciences Research Council
Centers for Disease Control and Prevention
Human Sciences Research Council
Schema: UK DATA ARCHIVE - HASSET
BIOGRAPHIC DATA; COMMUNITY PARTICIPATION; DISABILITIES; ELECTRICITY; GROUP MEMBERSHIP; HOUSEHOLD INCOME; RADIO; TELEPHONES; TELEVISION; TOILETS; WATER RESOURCES
This data set contains household information about the people who usually live at the visiting point and slept there the previous night as per the time of the interview. Information about their age, sex, marital status, race, language spoken, deaths in the household, education status, main source of drinking water, energy for cooking and type of toilet facility and socio-economic status information is also included in the visiting point data set.
The data set contains 312 variables and 15000 cases.
South Africa continues to have the largest number of people living with HIV/AIDS in the World. This study intends to understand the determinants that lead South Africans to be vulnerable and susceptible to HIV. This is the third in a series of household surveys conducted by Human Sciences Research Council (HSRC), that allow for tracking of HIV and associated determinants over time using a slightly same methodology used in 2002 and 2005 survey, making it the third national-level repeat survey. The 2002 and 2005 surveys included individuals aged 2+ years living in South Africa while 2008 survey included individuals of all ages living in South Africa, including infants younger than 2 years of age. The interval of three years since 2002 allows for an exploration of shifts over time against a complex of demographic and other variables, as well as allowing for investigation of the new areas. The survey provides the first nationally representative HIV incidence estimates.
The study key objectives were to: determine the prevalence of HIV infection in South Africa; examine the incidence of HIV infection in South Africa; assess the relationship between behavioural factors and HIV infection in South Africa; describe trends in HIV prevalence, HIV incidence, and risk behaviour in South Africa over the period 2002-2008; investigate the link between social, values, and cultural determinants and HIV infection in South Africa; assess the type and frequency of exposure to major national behavioural change communication programmes and assess their relationship to HIV prevention, AIDS treatment, care, and support; describe male circumcision practices in South Africa and assess its acceptability as a method of HIV prevention; collect data on the health conditions of South Africans; and contribute to the analysis of the impact of HIV/AIDS on society.
In the 13440 valid households or visiting points, 10856 agreed to participate in the survey, 23369 individuals (no more than 4 per household, including infants under 2 years) were eligible to be interviewed, and 20826 individuals completed the interview. Of the 23369 eligible individuals, 15031 agreed to provide a blood specimen for HIV testing and were anonymously linked to the behavioural questionnaires. the household response rate was 80.8%, the individual response rate was 89.1% and the overall response rate for HIV testing was 64.3%.
South African population of all individuals from urban formal, urban informal, rural formal (farms), rural informal (tribal area) settlements.
As in previous surveys, a multi-stage disproportionate, stratified sampling approach was used. A total of 1 000 census enumeration areas (EAs) from the 2001 population census were selected from a database of 86 000 EAs and mapped in 2007 using aerial photography to create a new updated Master Sample as a basis for sampling visiting points/households. The selection of EAs was stratified by province and locality type. Locality types were identified as urban formal, urban informal, rural formal (including commercial farms), and rural informal. In the formal urban areas, race was also used as a third stratification variable (based on the predominant race group in the selected EA at the time of the 2001 census). The allocation of EAs to different stratification categories was disproportionate; that means, over-sampling or over-allocation of EAs was done, for example, in areas that were dominated by Indian, coloured or white race groups to ensure that the minimum required sample size in those smaller race groups was obtained.
The Master Sample was designed to allow reporting of results (i.e. reporting domain) at a provincial, geotype and race level. A reporting domain is defined as that domain at which estimates of a population characteristic or variable should be of an acceptable precision for the presentation of survey results. A visiting point is defined as a separate (non-vacant) residential stand, address, structure, and flat in a block of flats or homestead. The 2001 estimate of visiting points was used as the Measure of Size (MOS) in the drawing of the sample. A maximum of four visits were made to each VP to optimise response. Fieldworkers enumerated household members, using a random number generator to select the respondent and then preceded with the interview.
All people in the households, resident at the visiting point were initially listed, after which the eligible individual was randomly selected in each of the following three age groups: under 2 years, 2-14 years, 15-24 years and 25+ years. These individuals constituted the USUs of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa. These PSUs were allocated to each of the explicit strata. With a view to obtaining an approximately self-weighting sample of visiting points (i.e. SSUs), (a) the EAs were drawn with probability proportional to the size of the EA using the 2001 estimate of the number of visiting points in the EA database as a measure of size (MOS) and (b) to draw an equal number of visiting points (i.e. SSUs) from each drawn EA. An acceptable precision of estimates per reporting domain requires that a sample of sufficient size be drawn from each of the reporting domains. Consequently, a cluster of 15 VP was systematically selected on the aerial photography produced for each of the EAs in the master sample. Since it is not possible to determine on an aerial photograph whether a 'dwelling unit' is indeed a residential structure or whether it was occupied (i.e. people sleeping there), it was decided to form clusters of 15 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 15 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. The VP questionnaire was administered by the fieldworker, and in follow-up, participant selection was made by the supervisor. Participants aged 12 years and older who consented were all interviewed and also asked to provide dried blood spots (DBS) specimens for HIV testing. In case of 0-11 years, parents/guardians were interviewed but DBS specimens were obtained from the children.
The sample size estimate for the 2008 survey was guided by the (1) requirement for measuring change over time in order to detect a change in HIV prevalence of 5 percentage points in each of the main reporting domains, namely gender, age-group, race, locality type, and province (5% level of significance, 80% power, two-sided test), and (2) the requirement of an acceptable precision of estimates per reporting domain; that is, to be able to estimate HIV prevalence in each of the main reporting domains with a precision level of less than 4%, which is equivalent to the expected width of the 95% confidence interval (z-score at the 95% level for two-sided test). A design effect of 2 was assumed.
Overall, a total of 20826 interviewed participants composed of 4981 children (0-14 years), 5344 youths (15-24 years) and 10501 adults (25+ years) were interviewed. The sample was designed with the view to enable reporting of the results on province level, on geography type area and on race of the respondent. The total sample size was limited by financial constraints, but based on other HSRC experience in sample surveys it was decided to aim at obtaining a minimum of 1 200 households per race group. The number of respondents per household for the study was expected to vary between one and three (one respondent in each of the three age groups). More females (68.9%) than males (62.02%) were tested for HIV. The 25+ years age group was the most compliant (68.8%), and 2-14 years the least (58.9%). The highest testing response rate was found in urban informal settlements (72.5%) and the lowest in urban formal areas (62.8%).
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