South African National HIV Prevalence, HIV Incidence, Behaviour and Communication Survey (SABSSM) 2012: Combined - All provinces
Simbayi, Leickness Chisamu;
Rehle, Thomas Michael;
Human Sciences Research Council
Description: In the combined data set four individual data sets were combined, guardians for children to 11 years, children 12 to 14 years, youths and adults 15 years and older and individual's information from the visiting point data set. The data set contains information on:...
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This project used the updated 2007-2011 HSRC's master sample. Aerial photographs drawn from Google Earth were utilised to ensure that the most up-to-date information was available sample. the master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the Master Sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so-called special institutions (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs) and the Secondary Sampling Units (SSUs) were the visiting points (VPs) or households (HHs). The Ultimate Sampling Units (USUs) were the individuals eligible to be selected for the survey. Any member of the household "who slept here last night", including visitors was an eligible household member for the interview. This sampling approach was used in the 2001 census and is a standard demographic household survey procedure.
The sample was designed with two main explicit strata, the provinces and the geography types (geotype) of the EA. In the 2001 census, the four geotypes were urban formal, urban informal, rural formal (including commercial farms) and tribal areas (rural informal) (i.e. the deep rural areas). In the formal urban areas, race was used as a third stratification variable. What this means is that 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 invited to participate in the study. 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 2012 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 38 431 interviewed participants composed of 29.7% children (0-14 years), 19.3% youths (15-24 years), 35.6% adults (25-49 years), and 15.4% adults (50+ 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 (70.3%) than males (64.2%) were tested for HIV. The 15-24 year's age group was the most compliant (71.6%), and less than 2 years the least (51.6%). The highest testing response rate was found in rural formal settlements (80.8%) and the least in urban formal areas (59.7%).
In the combined data set four individual data sets were combined, guardians for children to 11 years, children 12 to 14 years, youths and adults 15 years and older and individual's information from the visiting point data set.
The data set contains information on: biographical data, media, communication and norms, knowledge and perceptions of HIV/AIDS, male circumcision, sexual debut, partners and partner characteristics, condoms, vulnerability, HIV testing, alcohol and substance use, general perceptions about government, health and violence in the community.
The data set contains 917 variables and 44029 cases.
Subsequent to the dissemination of version 1 of the Combined data set the skip patterns for the Adult and Child data sets were corrected and updated in the Combined data set which is disseminated as Version 2.
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 fourth 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 2008 survey, making it the fourth national-level repeat survey. The 2002 and 2005 surveys included individuals aged 2+ years living in South Africa while 2008 and 2012 survey included individuals of all ages living in South Africa, including infants less than 2 years of age. The 2008 study included only four people per household, while in 2012 all members of the households participated. 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 surveys provide the nationally representative HIV incidence estimates showing changes over time.
The 2012 study key objectives were:
to determine the proportion of PLHIV who are on Antiretroviral treatment (ART) in South Africa;
to determine the prevalence and incidence of HIV infection in South Africa in relation to social and behavioural determinants;
to determine the proportion of males in South Africa who are circumcised;
to investigate the link between social values, and cultural determinants and HIV infection in South Africa;
to determine the extent to which mother-child pairs include HIV-negative mothers and HIV-positive infants;
to describe trends in HIV prevalence, HIV incidence, and risk behaviour in South Africa over the period 2002 to 2012
collect data on the health conditions of South Africans; and
contribute to the analysis of the impact of HIV/AIDS on society.
In 2012, of the 15000 selected households or visiting points, 11079 agreed to participate in the survey, 42950 individuals (all household members were included) were eligible to be interviewed, and 38431 individuals completed the interview. Of the 38431 eligible individuals, 28997 agreed to provide a blood specimen for HIV testing and were anonymously linked to the behavioural questionnaires. The household response rate was 87.2% , the individual response rate was 89.5% and the overall response rate for HIV testing was 67.5%
Shisana, Olive; Simbayi, Leickness Chisamu; Rehle, Thomas Michael; Human Sciences Research Council (2018): South African National HIV Prevalence, HIV Incidence, Behaviour and Communication Survey (SABSSM) 2012: Combined - All provinces. Version: 2.0. HSRC - Human Science Research Council SA.Dataset. https://doi.org/10.14749/1517402043