The 2006-07 Swaziland Demographic and Health Survey (SDHS) is a nationally representative survey of 4,843 households, 4,987 women age 15-49, and 4,156 men age 15-49. The SDHS also included individual interviews with boys and girls age 12-14 and older adults age 50 and over. The survey of persons age 12-14 and age 50 and over was carried out in every other household selected in the SDHS. Interviews were completed for 459 girls and 411 boys age 12-14, and 661 women and 456 men age 50 and over.
The 2006-07 SDHS is the first national survey conducted in Swaziland as part of the Demographic and Health Surveys (DHS) programme. The data are intended to furnish programme managers and policymakers with detailed information on levels and trends in fertility; nuptiality; sexual activity; fertility preferences; awareness and use of family planning methods; breastfeeding practices; nutritional status of mothers and young children; early childhood mortality and maternal mortality; maternal and child health; and awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections. The survey also collected information on malaria prevention and treatment.
The 2006-07 SDHS is the first nationwide survey in Swaziland to provide population-based prevalence estimates for anaemia and HIV. Children age 6 months and older as well as adults were tested for anaemia. Children age 2 years and older as well as adults were tested for HIV.
The principal objective of the 2006-07 Swaziland Demographic and Health Survey (SDHS) was to provide up-to-date information on fertility, childhood mortality, marriage, fertility preferences, awareness, and use of family planning methods, infant feeding practices, maternal and child health, maternal mortality, HIV/AIDS-related knowledge and behaviour and prevalence of HIV and anaemia.
More specifically the 2006-07 SDHS was aimed at achieving the following;
- Determine key demographic rates, particularly fertility, under-five mortality, and adult mortality rates
- Investigate the direct and indirect factors which determine the level and trends of fertility
- Measure the level of contraceptive knowledge and practice of women and men by method
- Determine immunization coverage and prevalence and treatment of diarrhoea and acute respiratory diseases among children under five
- Determine infant and young child feeding practices and assess the nutritional status of children 6-59 months, women age 15-49 years, and men aged 15-49 years
- Estimate prevalence of anaemia
- Assess knowledge and attitudes of women and men regarding sexually transmitted infections and HIV/AIDS, and evaluate patterns of recent behaviour regarding condom use
- Identify behaviours that protect or predispose the population to HIV infection
- Examine social, economic, and cultural determinants of HIV
- Determine the proportion of households with orphans and vulnerable children (OVCs)
- Determine the proportion of households with sick people taken care at household level
- Determine HIV prevalence among males and females age 2 years and older
- Determine the use of iodized salt in households
- Describe care and protection of children age 12-14 years, and their knowledge and attitudes about sex and HIV/AIDS.
This information is intended to provide data to assist policymakers and programme implementers to monitor and evaluate existing programmes and to design new strategies for demographic, social and health policies in Swaziland. The survey also provides data to monitor the country's achievement towards the Millenium Development Goals.
- Fertility in Swaziland has been declining rapidly, with the TFR falling from 6.4 births per woman in 1986 to 3.8 births at the time of the SDHS. As expected, fertility is higher in rural areas (4.2 births per woman) than in urban areas (3.0 births per woman). Fertility differentials by education and wealth are substantial. Women with no education have on average 4.9 children compared with 2.4 children for women with tertiary education. Fertility varies widely according to household wealth. Women in the highest wealth quintile have 2.9 children fewer than women in the lowest quintile (2.6 and 5.5 births per woman, respectively).
- Knowledge of family planning is universal in Swaziland. The most widely known method is the male condom (99 percent for both males and females). Among women, other widely known methods include injectables (96 percent), the pill (95 percent), and the female condom (91 percent). For men, the best known methods besides the male condom are the female condom (94 percent) and the pill and injectables (84 percent each).
- Children are considered fully vaccinated when they receive one dose of BCG vaccine, three doses each of DPT and polio vaccines, and one dose of measles vaccine. BCG coverage among children age 12-23 months is nearly universal (97 percent); coverage is also high for the first doses of DPT (96 percent) and polio (97 percent). The proportion of children receiving subsequent doses of DPT and polio vaccines drops slightly, with 92 percent of children receiving the third dose of DPT and 87 percent receiving the third dose of polio. Ninety-two percent of children had received a measles vaccination by the time of the SDHS. Overall, 82 percent of children age 12-23 months are fully immunised.
- In Swaziland, almost all women who had a live birth in the five years preceding the survey received antenatal care from health professionals (97 percent); 9 percent received care from a doctor, and 88 percent received care from a trained nurse or midwife. Only 3 percent of mothers did not receive any antenatal care
- Overall, 87 percent of children in Swaziland are breastfed for some period of time (ever breastfed). The median duration of any breast-feeding in Swaziland is almost 17 months. However, the median duration of exclusive breast-feeding is much shorter (0.7 months).
- In interpreting the malaria programme indicators in Swaziland, it is important to recognise that the disease affects an estimated 30 percent of the population where malaria is most prevalent (the Lubombo Plateau, the lowveld, and parts of the middleveld). Malaria is also seasonal, occurring mainly during or after the rainy season (from November to March). A substantial part of the SDHS fieldwork took place outside of this period.
- Results from the HIV testing component in the 2006-07 SDHS indicate that 26 percent of Swazi adults age 15-49 are infected with HIV. Among women, the HIV rate is 31 percent, compared with 20 percent among men. HIV prevalence peaks at 49 percent for women age 25-29, which is almost five times the rate among women age 15-19 and more than twice the rate observed among women age 45-49. HIV prevalence increases from 2 percent among men in the 15-19 age group to 45 percent in the age group 35-39 and then decreases to 28 percent among men age 45-49. HIV prevalence for women and men age 50 or over is 12 percent and 18 percent, respectively. Among the population age 2-14 years, 4 percent of girls and boys are infected.
Kind of data
Sample survey data
The 2006-07 Swaziland Demographic and Health Survey (SDHS) is a nationally representative survey. It was designed to provide estimates of health and demographic indicators at the national level, for urban-rural areas, and for the four regions of Manzini, Hhohho, Lubombo, and Shiselweni.
Unit of analysis
- Women age 15-49
- Men age 15-49
- Young adults age 12-14
- adults age 50 and over
The population covered by the 2006 SWZDHS is defined as the universe of all women Ever-married women in the reproductive ages (i.e., women 15-49).
Producers and sponsors
Central Statistical Office (CSO)
Macro International Inc.
Government of the Kingdom of Eswatini
U.S. Agency for International Development
Ministry of Health and Social Welfare (MOHSW)
Human Sciences Research Council (HSRC)
Technical support for design phase of the survey
Global Clinical and Viral Laboratory (GCVL)
Technical support for the training and laboratory processing for the HIV testing component of the survey
National Emergency Response Council on HIV/AIDS (NERCHA)
HIV/AIDS Prevention and Care (HAPAC)
World Health Organisation
Population Services International (PSI)
Centres for Disease Control and Prevention (CDC)-Global AIDS Programme
The 2006-07 SDHS was designed to provide estimates of health and demographic indicators at the national level, for urban-rural areas, and for the four regions of Manzini, Hhohho, Lubombo, and Shiselweni. Standard DHS sampling policy recommends a minimum of 1,000 to 1,200 women per major domain. To meet this criterion, the number of households selected in each of the various domains, particularly urban areas, was not proportional to the actual size of the population in the domain. As a result, the SDHS sample is not self-weighting at the national level, and weights must be applied to the data to obtain the national-level estimates.
The 2006-07 SDHS sample points (clusters) were selected from a list of enumeration areas (EAs) defined in the 1997 Swaziland Population and Housing Census. A total of 275 clusters were drawn from the census sample frame, 111 in the urban areas and 164 in the rural areas.
CSO staff conducted an exhaustive listing of households in each of the SDHS clusters in August and September 2005. From these lists, a systematic sample of households was drawn for a total of 5,500 households. All women and men age 15-49 identified in these households were eligible for individual interview. In addition, a sub-sample of half of these households (2,750 households) was selected randomly in which all boys and girls age 12-14 and persons age 50 and older were eligible for individual interview. In the SDHS households where youth and older adults were interviewed, all individuals age 6 months and older were eligible for anaemia testing and all individuals age 2 and older were eligible for HIV testing. In the SDHS households where only women and men age 15-49 were interviewed, children age 6 months to 5 years were eligible for the anaemia testing and women and men age 15-49 were eligible for anaemia and HIV testing.
During the household listing, field staff used Global Positioning System (GPS) receivers to establish and record the geographic coordinates of each of the SDHS clusters.
The response rates are important because they may affect the reliability of the results. Of a total of 5,500 households selected in the sample, 5,086 were occupied at the time of the fieldwork. This difference between the number of selected households and the number of occupied households is due to structures being vacated or destroyed. Successful interviews were conducted in 4,843 households, yielding a response rate of 95 percent.
In the households interviewed in the survey, a total of 5,301 eligible women age 15-49 were identified. Interviews were completed with 4,987 of these women, yielding a 94 percent response rate. In the same households, a total of 4,675 eligible men age 15-49 were identified and interviews were completed with 4,156 of these men, yielding a male response rate of 89 percent. The response rates are slightly lower in the urban sample than in the rural sample, and lower among men than women. The principal reasons for non-response among both eligible men and women were refusal and the failure to find individuals at home despite repeated visits to the households. Men have lower response rates than women due to higher refusal rates, and more frequent and longer absence from the households, principally due to employment and their lifestyle.
A total of 2,750 households were selected in the sample, of which 2,543 were occupied at the time of the fieldwork. This difference between the number of selected households and the number of occupied households is due to structures being vacated or destroyed. Successful interviews were conducted in 2,410 households, yielding a response rate of 95 percent.
In the households selected for the youth and older adult survey, a total of 477 eligible girls and 439 eligible boys age 12-14 were identified. Interviews were completed with 459 girls and 411 boys, yielding response rates of 96 percent and 94 percent, respectively. The response rates for girls are the same for urban and rural areas. For boys, the response rate is slightly lower in urban than in rural areas (89 percent compared with 94 percent).
A total of 693 eligible women age 50 and over were identified. Interviews were completed with 661 of these women, yielding a 95 percent response rate. In the same households, a total of 492 eligible men age 50 and over were identified and interviews were completed with 456 of these men, yielding a male response rate of 93 percent. The response rates are slightly lower in urban than in rural areas, and lower among men than women.
Dates of collection
Mode of data collection
Five types of questionnaires were used for the SDHS: a) the Household Questionnaire, b) the Woman's Questionnaire, c) the Man's Questionnaire, d) the Youth Questionnaire, and the e) Older Adult Questionnaire. The contents of the questionnaires were based on questionnaires developed for the MEASURE DHS programme. The Youth Questionnaire was adapted from the 2002 Nelson Mandela/HSRC Study of HIV/AIDS in South Africa. The SDHS questionnaires were developed in collaboration with a wide range of stakeholders. After the SDHS survey instruments were drafted, they were translated into and printed in the local language, Siswati, for pretesting.
a) 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 age, sex, education, and relationship to the head of the household. The Household Questionnaire was also used to identify persons eligible for the individual interview. In addition, information was collected about the dwelling, such as the source of water; type of toilet facilities; materials used to construct the house; ownership of various consumer goods; use of bed nets; and care and free external support received by chronically ill household members and orphans and vulnerable children. The results of anthropometric measurement and anaemia testing were recorded in the Household Questionnaire, as was the information on the consent of eligible household members for the HIV testing.
b) The Woman's Questionnaire was used to collect information from all women age 15-49 and covered the following topics:
- Background characteristics (age, education, religion, etc.)
- Birth history
- Knowledge and use of family planning methods
- Antenatal and delivery care
- Infant feeding practices including patterns of breastfeeding
- Childhood illnesses and treatment
- Marriage and sexual activity
- Fertility preferences
- Husband's background and woman's work status
- Adult (maternal) mortality
- HIV/AIDS-related knowledge, attitudes, and behaviour.
c) The Man's Questionnaire was shorter than the Woman's Questionnaire, but covered many of the same topics, excluding the reproductive history and sections dealing with maternal and child health.
d) The Older Adult Questionnaire obtained limited information on the background characteristics of the population age 50 and over and on HIV/AIDS knowledge, attitudes, and risk behaviour.
e) The Youth Questionnaire included questions on knowledge and attitudes about sex, and factors exposing youth to risk of abuse.
Central Statistical Office
All questionnaires for the SDHS were returned to CSO central office for data processing. The processing operation consisted of office editing, coding of open-ended questions, data entry, double-entry verification, and resolving inconsistencies found by computer programmes developed for the SDHS. The SDHS data entry and editing programmes used CSPro, a computer software package specifically designed for processing survey data such as that produced by DHS surveys. Data processing commenced in August 2006 and was completed in April 2007.
The HIV testing was carried out at the NRL between August 2006 and June 2007.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2006-07 SDHS 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.
A 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.
If 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 2006-07 SDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2006-07 SDHS is the ISSA Sampling Error Module. This module used the Taylor linearization 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.
The 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 cluster in the calculation of the estimates. Pseudo-independent replications are thus created. In the 2006-07 NDHS, there were 275 non-empty clusters. Hence, 275 replications were created.
In addition to the standard error, ISSA computes the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design. ISSA also computes the relative error and confidence limits for the estimates.
Sampling errors for the 2006-07 SDHS are calculated for selected variables considered to be of primary interest for woman's survey and for man's surveys, respectively. The results are presented in an appendix to the Final Report for the country as a whole, for urban and rural areas, and for each of the eleven regions. 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.8 present the value of the statistic (R), its standard error (SE), the number of unweighted (N-UNWE) and weighted (N-WEIG) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95 percent confidence limits (R±2SE), 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, as there is no known unweighted value for woman-years of exposure to child-bearing.
The confidence interval (e.g., as calculated for children ever born to women aged 40-49) can be interpreted as follows: the overall average from the national sample is 5.339 and its standard error is 0.118. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 5.339 ± 2 × 0.118. There is a high probability (95 percent) that the true average number of children ever born to all women aged 40 to 49 is between 5.103 and 5.575. Sampling errors are analyzed for two separate groups of estimates: (1) means and proportions, and (2) complex demographic rates. At the national level, mostly relative standard error values (SE/R) for the means and proportions are below 10 percent, however the highest relative standard error values are for indicators with very low values (i.e. less than 2 percent). So in general, the relative standard errors for most estimates for the country as a whole are small, except for indicators with very small values, i.e. for estimates which are rare in the population. For example, the relative standard error for the total fertility rate (TFR 0-3 years) is small (2.9 percent) since births are a fairly common event. However, for the mortality rates which are rarer events, the average relative standard error value is higher; for example, the relative standard error for the 0-4 year estimate of mortality rates is 9.4 percent. The relative standard error varies across sub-populations. For example, for the variable children ever born to women aged 40-49, the relative standard errors as a percent of the estimated mean for the whole country, for the urban areas and for the rural areas are 2.2 percent, 4.2 percent and 2.5 percent, respectively. For the total sample, the value of the design effect (DEFT), averaged over all selected variables, is 1.15 which means that, due to multi-stage clustering of the sample, the average standard error is increased by a factor of 1.15 over that in an equivalent simple random sample.
Other forms of 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 2006-07 Swaziland Demographic and Health Survey (SDHS) to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
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.