{"type":"survey","study_desc":{"title_statement":{"idno":"ZAF_1998_DHS_v01_M","title":"Demographic and Health Survey 1998","alt_title":"SADHS 1998"},"authoring_entity":[{"name":"Department of Health","affiliation":""},{"name":"Medical Research Council","affiliation":""}],"oth_id":[{"name":"Health Systems Research","affiliation":"","email":"","role":"Coordination"},{"name":"Research Co-ordination and Epidemiology Directorate","affiliation":"","email":"","role":"Coordination"},{"name":"Centre for Health Systems Research and Development","affiliation":"","email":"","role":"Technical assistance in field work"},{"name":"University of the Orange Free State","affiliation":"","email":"","role":"Technical assistance in field work"}],"production_statement":{"producers":[{"name":"Macro International inc.","affiliation":"","role":"Technical assistance"}],"funding_agencies":[{"name":"U.S. Agency for International Development","abbreviation":"USAID","role":"Funding"}]},"distribution_statement":{"contact":[{"name":"General Inquiries","affiliation":"","email":"info@measuredhs.com","uri":"www.measuredhs.com"},{"name":"Data and Data Related Resources","affiliation":"","email":"archive@measuredhs.com","uri":"www.measuredhs.com"},{"name":"Department of Health","affiliation":"","email":"dg@health.gov.za","uri":"http:\/\/www.doh.gov.za\/"},{"name":"Medical Research Council","affiliation":"","email":"info@mrc.ac.za","uri":"http:\/\/www.mrc.ac.za\/"}]},"series_statement":{"series_name":"Demographic and Health Survey (standard) - DHS III","series_info":"The 1998 South Africa Demographic and Health Survey (SADHS) is the first study of its kind to be conducted in South Africa."},"study_info":{"abstract":"The 1998 South Africa Demographic and Health Survey (SADHS) is the first study of its kind to be conducted in South Africa and heralds a new era of reliable and relevant information in South Africa. The SADHS, a nation-wide survey has collected information on key maternal and child health indicators, and in a first for international demographic and health surveys, the South African survey contains data on the health and disease patterns in adults. \n\nPlans to conduct the South Africa Demographic and Health Survey go as far back as 1995, when the Department of Health National Health Information Systems of South Africa (NHIS\/SA) committee, recognised serious gaps in information required for health service planning and monitoring. \n\nFieldwork was conducted between late January and September 1998, during which time 12,247 households were visited, 17,500 people throughout nine provinces were interviewed and 175 interviewers were trained to interview in 11 languages.\n\nThe aim of the 1998 South Africa Demographic and Health Survey (SADHS) was to collect data as part of the National Health Information System of South Africa (NHIS\/SA). The survey results are intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving health services in the country. A variety of demographic and health indicators were collected in order to achieve the following general objectives: \n\n(i) To contribute to the information base for health and population development programme management through accurate and timely data on a range of demographic and health indicators. \n(ii) To provide baseline data for monitoring programmes and future planning. \n(iii) To build research and research management capacity in large-scale national demographic and health surveys.  \n\nThe primary objective of the SADHS is to provide up-to-date information on: \n- basic demographic rates, particularly fertility and childhood mortality levels, \n- awareness and use of contraceptive methods, \n- breastfeeding practices, \n- maternal and child health, \n- awareness of HIV\/AIDS, \n- chronic health conditions among adults, \n- lifestyles that affect the health status of adults, and \n- anthropometric indicators.","coll_dates":[{"start":"1998-01","end":"1998-09","cycle":""}],"nation":[{"name":"South Africa","abbreviation":"ZAF"}],"geog_coverage":"It was designed principally to produce reliable estimates of demographic rates (particularly fertility and childhood mortality rates), of maternal and child health indicators, and of contraceptive knowledge and use for the country as a whole, the urban and the non-urban areas separately, and for the nine provinces.","analysis_unit":"- Household\n- Women age 15-49\n- Men age 15 and above","universe":"The 1998 South African Demographic and Health Survey (SADHS) covered the population living in private households in the country.","data_kind":"Sample survey data","notes":"The South African Demographic and Health Survey 1998 covers the following topics:\n- basic demographic rates, particularly fertility and childhood mortality levels, \n- awareness and use of contraceptive methods, \n- breastfeeding practices, \n- maternal and child health, \n- awareness of HIV\/AIDS, \n- chronic health conditions among adults, \n- lifestyles that affect the health status of adults\n- anthropometric indicators\n- domestic violence","study_scope":"The South African Demographic and Health Survey 1998 covers the following topics:\n- basic demographic rates, particularly fertility and childhood mortality levels, \n- awareness and use of contraceptive methods, \n- breastfeeding practices, \n- maternal and child health, \n- awareness of HIV\/AIDS, \n- chronic health conditions among adults, \n- lifestyles that affect the health status of adults\n- anthropometric indicators\n- domestic violence"},"method":{"data_collection":{"data_collectors":[{"name":"University of the Orange Free State","abbreviation":"","affiliation":""},{"name":"Centre for Health Systems Research and Development","abbreviation":"","affiliation":""}],"sampling_procedure":"The 1998 South African Demographic and Health Survey (SADHS) covered the population living in private households in the country. The design for the SADHS called for a representative probability sample of approximately 12,000 completed individual interviews with women between the ages of 15 and 49. It was designed principally to produce reliable estimates of demographic rates (particularly fertility and childhood mortality rates), of maternal and child health indicators, and of contraceptive knowledge and use for the country as a whole, the urban and the non-urban areas separately, and for the nine provinces. As far as possible, estimates were to be produced for the four South African population groups.  Also, in the Eastern Cape province, estimates of selected indicators were required for each of the five health regions. \n\nIn addition to the main survey of households and women 15-49 that followed the DHS model, an adult health module was administered to a sample of adults aged 15 and over in half of the households selected for the main survey.  The adult health module collected information on oral health, occupational hazard and chronic diseases of lifestyle. \n\nSAMPLING FRAME \n\nThe sampling frame for the SADHS was the list of approximately 86,000 enumeration areas (EAs) created by Central Statistics (now Statistics South Africa, SSA) for the Census conducted in October 1996. The EAs, ranged from about 100 to 250 households, and were stratified by province, urban and non-urban residence and by EA type. The number of households in the EA served as a measure of size of the EA. \n\nCHARACTERISTICS OF THE SADHS SAMPLE \n\nThe sample for the SADHS was selected in two stages.  Due to confidentiality of the census data, the sampling was carried out by experts at the CSS according to specifications developed by members of the SADHS team. Within each stratum a two stage sample was selected. The primary sampling units (PSUs), corresponded  to the EAs and will be selected with probability proportional to size (PPS), the size being the number of households residing in the EA, or where this was not available, the number of census visiting points in the  EA. This led to 972 PSUs being selected for the SADHS (690 in urban areas and 282 in non-urban areas.  Where provided by SSA, the lists of visiting points together with the households found in these visiting points, or alternatively a map of the EA which showed the households, was used as the frame for second-stage sampling to select the  households to be visited by the SADHS interviewing teams during the main survey fieldwork.  This sampling was carried out by the MRC behalf of the SADHS working group.  If a list of visiting points or a map was not available from SSA, then the survey team took a systematic sample of visiting points in the field.  In an urban EA ten visiting points were sampled, while in a non-urban EA twenty visiting points were sampled. The survey team then interviewed the household in the selected visiting point.  If there were two households in the selected visiting point, both households were interviewed.  If there were three or more households, then the team randomly selected one household for interview. In each selected household, a household questionnaire was administered; all women between the ages of 15 and 49 were identified and interviewed with a woman questionnaire.  In half of the selected households (identified by the SADHS working group), all adults over 15 years of age were  also identified and interviewed with an adult health questionnaire.\n\nSAMPLE ALLOCATION \n\nExcept for Eastern Cape, the provinces were stratified by urban and non-urban areas, for a total of 16 sampling strata.  Eastern Cape was stratified by the five health regions and urban and non-urban within each region, for a total of 10 sampling strata.  There were thus 26 strata in total. \n\nOriginally, it was decided that a sample of 9,000 women 15-49 with complete interviews allocated equally to the nine provinces would be adequate to provide estimates for each province separately; results of other demographic and health surveys have shown that a minimum sample of 1,000 women is required in order to obtain estimates of fertility and childhood mortality rates at an acceptable level of sampling errors.  Since one of the objectives of the SADHS was to also provide separate estimates for each of the four population groups, this allocation of 1,000 women per province would not provide enough cases for the Asian population group since they represent only 2.6 percent of the population (according to the results of the 1994 October Household Survey conducted by SSA).  The decision was taken to add an additional sample of 1,000 women to the urban areas of KwaZulu-Natal and Gauteng to try to capture as many Asian women as possible as Asians are found mostly in these areas.  A more specific sampling scheme to obtain an exact number of Asian women was not possible for two reasons: the population distribution by population group was not yet available from the 1996 census and the sampling frame of EAs cannot be stratified by population group according to SSA as the old system of identifying EAs by population group has been abolished. \n\nAn additional sample of 2,000 women was added to Eastern Cape at the request of the Eastern Cape province who funded this additional sample.  In Eastern Cape, results by urban and non-urban areas can be given.  Results of selected indicators such as contraceptive knowledge and use can also be produced separately for each of the five health regions but not for urban\/non-urban within health region. \n\nResult shows the allocation of the target sample of 12,000 women by province and by urban\/non\u00adurban residence.  Within each province, the sample is allocated proportionately to the urban\/non-urban areas.\n\nIn the above allocation, the urban areas of KwaZulu-Natal have been oversampled by about 57 percent while those of Gauteng have been oversampled by less than 1 percent. For comparison purposes, it shows a proportional allocation of the 12,000 women to the nine provinces that would result in a completely self-weighting sample but does not allow for reliable estimates for at least four provinces (Northern Cape, Free State, Mpumalanga and North-West). \n\nThe number of households to be selected for each stratum was calculated as follows: \n\n- According to the 1994 October Household Survey, the estimated number of women 15-49 per households is 1.2. The overall response rate was assumed to be 80 percent, i.e., of the households selected for the survey only 90 percent would be successfully interviewed, and of the women identified in the households with completed interviews, only 90 percent would have a complete woman questionnaire.  Using these two parameters in the above equation, we would expect to select approximately 12,500 households in order to yield the target sample of women.  \n\n- The number of sample points (or clusters) to be selected for each stratum is calculated by dividing the number of households in the stratum by the average \"take\" in the cluster.  In SADHS, each cluster will correspond to a census EA.  Analytical studies of surveys of the same nature suggest that the optimum number of women to be interviewed is around 20-25 in each urban cluster and 30-35 in each non-urban cluster.  However it was decided that these numbers would be lower for the SADHS, given the practice of small cluster \"take\" in surveys conducted in South Africa and that the field cost is generally reasonable. If we selected 10 households in each urban cluster and 20 households in each non-urban cluster, the distribution of sample points or EAs would be as follows: \n\n- Some rearrangement was then necessary so that in each stratum there was an even number of EAs. This is recommended for the purpose of calculating sampling errors using Taylor linearization in which the first step is to form pairs of homogeneous clusters. \nIn the Eastern Cape, the sample was distributed equally among the five health regions since estimates are required at the level of health region. Within each health region the sample was distributed proportionally to urban\/non-urban according to the distribution of population in 1993.  Table A7 shows the proposed number of EAs to be selected. \n\n- In allocating the number of EAs to the five health regions of the Eastern Cape, we tried to follow the rule of an even number of clusters per sampling stratum while aiming for a regional sample of approximately 600 households (resulting in about 600 women aged 15-49). \n\nSTRATIFICATION AND SYSTEMATIC SELECTION OF EAS \n\nStratification and selection of the EAs for the SADHS was done by CSS according to the following specifications.  Explicit stratification of the EAs was by province and by urban\/non-urban within province except in Eastern Cape where the strata were the urban and non-urban areas of each of the five health regions.  EAs that contain only institutions such as prisons and mine hostels were excluded from the sampling frame.  Within each EA type, the EAs were ordered according to geographic or administrative units as adopted by SSA for the census.  The number of EAs were then selected independently within each explicit stratum and with probability proportional to size. The measure of size used for selection was the number of households enumerated in each EA by the census. \nThe selection procedure that SSA used in each explicit stratum was as follows: \n1. calculating the selection interval for the EAs: \nwhere Mi is the size of the stratum (total number of households or population in the stratum according to the census) and a is the number of EAs to be selected in the stratum; \n2. calculating the cumulated size of each EA; \n3. calculating the series of sampling numbers R, R+I, R+2I, ..., R+(a-1)I, where R is a random number between 1 and I; \n4. comparing each sampling number with the cumulated sizes. \n\nThe first EA to be selected was the first EA on the list whose cumulated size was equal or greater than the first sampling number.  The second EA to be selected was the next EA on the list (after the first selected one) whose cumulated size was equal or greater than the second sampling number, and so on.","coll_mode":"Face-to-face","research_instrument":"The survey utilised three questionnaires: a) a Household Questionnaire, b) a Woman's Questionnaire and c) an Adult Health Questionnaire. The contents of the first two were adapted from the DHS Model Questionnaires to meet the needs of the national and provincial Departments of Health. The Adult Health Questionnaire was developed to obtain information regarding the health of adults. Indicators listed in the preliminary Year 2000 Goals, Objectives and Indicators document were included where a household survey was the appropriate mechanism for collecting the information. \n\na) The Household Questionnaire was used to list all the usual members and visitors in the selected households. Basic information was collected on the characteristics of each person listed, including his\/her age, sex, education and relationship to the head of the household. Information was collected about social grants, work status and injuries experienced in the last month. An important purpose of the Household Questionnaire was to identify women and adults who were eligible for interview.  In addition, information was collected about the dwelling itself, such as the source of water, type of toilet facilities, material used to construct the house and ownership of various consumer goods. \n\nb) The Woman's Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following topics: \n- Background characteristics (age, education, race, etc.) \n- Pregnancy history \n- Knowledge and use of contraceptive methods \n- Antenatal and delivery care \n- Breastfeeding and weaning practices \n- Child health and immunisation \n- Marriage and recent sexual activity \n- Fertility preferences \n- Violence against women \n- Knowledge of HIV\/AIDS \n- Maternal mortality \n- Husband's background and respondent's work \n\nc) In every second household, all men and women aged 15 and above were eligible to be interviewed with the Adult Health Questionnaire. The respondents were asked questions on: \n- Recent utilisation of health services, \n- Family medical history, \n- Clinical conditions, \n- Dental health, \n- Occupational health, \n- Medications taken, \n- Habits and lifestyles, Anthropometric measurements, and, Blood pressure and lung function test.","coll_situation":"PILOT STUDY \n\nPilot studies were carried out in November 1996 in non-urban and urban areas. The questionnaires were adapted and finalised on the basis of the results of the pilot study. The instructions and questions in the questionnaires were translated and produced in all official languages in South Africa (English, Afrikaans, isiXhosa, isiZulu, Sesotho, Setswana, Sepedi, SiSwati, TshiVenda, Xitsonga and isiNdebele). \n\nTRAINING\n\nThe training of field workers was conducted by personnel from the MRC, HSRC, Free State University (Centre for Health Systems Research and Development) and Macro International. Training consisted of plenary sessions on more general issues like contraceptive methods conducted for the whole group in one venue and more specific discussions by section for each of the nine provinces in separate venues. There was also intensive training in adult anthropometric measurements, taking blood pressure and measuring lung capacity.   \n\nSome 175 candidates were recruited for field work. Each province had 1 or 2 managers who were responsible, under the supervision of 2 part-time regional managers, for the fieldwork operation in that province. Each province had 3 teams of female interviewers who were selected on the basis of education, maturity, field experience and language spoken. The Eastern Cape had 7 teams and KwaZulu-Natal  had 5 teams as they had larger sample sizes. Team leaders supervised the teams and ensured the work flow. Each province had 2 centrally based editors who screened all the questionnaires before they were submitted to the office for processing.  \n\nFIELDWORK \n\nFieldwork commenced in late January 1998 and was completed in September 1998. Immediately before the fieldwork, information about the survey was released through the national media including TV, radio and newspapers. A community liaison strategy was developed in each province using local media to precede work in the different areas. \n\nFieldwork for the SADHS was carried out by 33 interviewing teams. Each province had three teams, with the exception of the Eastern Cape, which had seven teams and KwaZulu-Natal which had five teams. Each team consisted of 2-5 female interviewers, a supervisor, and a field editor. In each province there was a provincial manager who was an overall supervisor of the fieldwork operations. In addition, two fieldwork co-ordinators, based at the University of the Free state, provided logistical and management support for the field operations. In many provinces, staff from the provincial Department of Health offices, who had attended the training course, formed fieldwork quality control teams to check on the field work teams and to conduct revisits. Finally staff from the MRC, the HSRC and Macro International conducted periodic quality control visits during fieldwork. Fieldwork commenced in late January 1998 and was completed in september 1998.","act_min":"In the course of the fieldwork, quality control measures were instituted at three levels. First, field team leaders and editors were trained to identify the enumerator areas included in the sample and guide interviewers in the selection of dwellings for interviews. Secondly, approximately 10 percent of the sample were re-visited in the months of the interview to ensure that the appropriate dwellings were selected and interviewed. Thirdly, a team consisting of staff from the HSRC carried out independent quality control visits to check questionnaires for errors, quality of identification and interviews at the enumerator area and dwelling levels.","cleaning_operations":"All completed questionnaires for the SADHS were submitted to the provincial offices of King Finance (who were in partnership with the Centre for Health Systems Research at the University of the Free State), which then forwarded them to the MRC for data processing. The questionnaires were processed at the Medical Research Council offices in Cape Town. \n\nThe processing operation consisted of office editing, coding of open-ended questions, initial data entry and subsequent re-entry of all questionnaires to ensure correct data-capture, and finally editing inconsistencies found by the computer program. The SADHS data entry and editing programs were written using ISSA (Integrated System for Survey Analysis) by staff from Macro International. A small proportion of the questionnaires were returned to the field to complete missing information. Data processing commenced in mid-March 1998 and was completed in October 1998."},"analysis_info":{"response_rate":"Of the total 972 PSUs that were selected, fieldwork was not implemented in three PSUs due to concerns about the safety of the interviewers and the questionnaires for another three PSUs  were lost in transit. The data file contains information for a total of 966 PSUs. A total of 12,860 households was selected for the sample and 12,247 were successfully interviewed. The shortfall is primarily due to refusals and to dwellings that were vacant or in which the inhabitants had left for an extended period at the time they were visited by interviewing teams. \n\nOf the 12,638 households occupied 97 percent were successfully interviewed. In these households, 12,327 women were identified as eligible for the individual women's interview (15-49) and interviews were completed with 11,735 or 95 percent of them. In the one half of the households that were selected for inclusion in the adult health survey 14,928 eligible adults age 15 and over were identified of which 13,827 or 93 percent were interviewed. The principal reason for non-response among eligible women and men was the failure to find them at home despite repeated visits to the household. The refusal rate was about 2 percent.","sampling_error_estimates":"Sampling errors, on the other hand, can be evaluated statistically.  The sample of respondents selected in the SADHS is only one of many samples that could have been selected from the same population, using the same design and expected 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 SADHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the SADHS is the ISSA Sampling Error Module.  This module used the Taylor linearisation method of 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 Jackknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample, and calculates standard errors for these estimates using simple formulae.  Each replication considers all but one clusters in the calculation of the estimates.  Pseudo-independent replications are thus created.  In the SADHS, there were 966 non-empty clusters.  Hence, 965 replications were created.  \n\nSampling errors for the SADHS are calculated for selected variables considered to be of primary interest. The results are presented in an appendix to the Final Report for the country as a whole, for urban and rural areas,  for each of the 9 provinces, and for each of the four population groups.  For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1 of the Final Report.  Tables B.2 to B.17 present the value of the statistic (R), its standard error (SE), the number of unweighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE\/R), and the 95 percent confidence limits (R\u00b12SE), for each variable.  The DEFT is considered undefined when the standard error considering simple random sample is zero (when the estimate is close to 0 or 1).  In the case of the total fertility rate, the number of unweighted cases is not relevant since there is no known unweighted value for woman-years of exposure to childbearing. \n\nThe confidence interval (e.g., as calculated for children ever born to women age 15-49) can be interpreted as follows:  the overall average from the national sample is 1.939 and its standard error is .024.  Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 1.939\u00b12\u00d7.024.  There is a high probability (95 percent) that the true average number of children ever born to all women aged 15 to 49 is between 1.891 and 1.987.  Sampling errors are analysed for the national sample and for two separate groups of estimates: (1) means and proportions, and (2) complex demographic rates.  The relative standard errors (SE\/R) for the means and proportions range between 0 percent and 34 percent with an average of 4.6 percent; the highest relative standard errors are for estimates of very low values (e.g., currently using periodic abstinence among currently married women).  If estimates of very low values (less than 10 percent) were removed, then the average drops to 2.1 percent.  So in general, the relative standard error for most estimates for the country as a whole is small, except for estimates of very small proportions.   The relative standard error for the total fertility rate is small, 2.7 percent.  However, for the mortality rates, the average relative standard error is  higher, 8.2 percent.\n\nThere are differentials in the relative standard error for the estimates of sub-populations.  For example, for the variable with standard 6 or higher, the relative standard errors as a percent of the estimated mean for the whole country, for the rural areas, and for Northern Cape Province are 1.0 percent, 2.3 percent, and 4.9 percent, respectively. \n\nFor the total sample, the value of the design effect (DEFT) averaged over all variables is 1.33, which means that due to multi-stage clustering of the sampling error is increased by a factor of 1.33 over that in an equivalent simple random sample.","data_appraisal":"Non-sampling 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 SADHS to minimise this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically."}},"data_access":{"dataset_use":{"contact":[{"name":"MEASURE DHS","affiliation":"ICF International","email":"archive@measuredhs.com","uri":"www.measuredhs.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","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 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