This report presents results of the 2010 the Kingdom of Eswatini MICS, carried out by CSO in collaboration with UNICEF and other partners. Since its launch in the mid-1990s, MICS has become one of the largest sources of information on a range of indicators including child health, nutrition, water and sanitation, reproductive health, education, child protection and HIV/AIDS. The 2010 Kingdom of Eswatini MICS was implemented to assess the current situation of the Swazi population, particularly children and women, as well as to measure progress towards goals and targets emanating from international agreements: the Millennium Declaration, adopted by all 191 United Nations Member States in September 2000, and the WFFC Plan of Action, adopted by 189 Member States at the United Nations (UN) Special Session on Children in May 2002. Both of these commitments build upon promises made by the international community at the 1990 World Summit for Children.
The 2010 Kingdom of Eswatini MICS is based on a nationally representative sample of 5,475 households selected from 365 enumeration areas distributed in the four regions of the country. It is an important source of information for measuring progress towards targets set by these various strategic plans, as well international declarations including the MDGs, the United Nations General Assembly Special Session Declaration of Commitment on HIV/AIDS (UNGASS) and others commitments.
Kind of data
Sample survey data [ssd]
- v01: Edited, anonymous datasets for public distribution.
Unit of analysis
The survey covered all de jure household members (usual residents), all women aged between 15-49 years, all children under 5 living in the household, and all men aged 15-59 years.
Producers and sponsors
United Nations Children’s Fund
Central Statistical Office
Deputy Prime Minister’s Office
Ministry of Health
Ministry of Education and Training
Ministry of Natural Resources and Energy
National Emergency Response Council on HIV/AIDS (NERCHA)
United Nations agencies
Government of the Kingdom of Swaziland
United Nations Children’s Fund
United Nations Population fund
National Emergency Response Council on HIV/AIDS
Joint United Nations Programme on HIV/AIDS
The primary objective of the sample design for the 2010 Kingdom of Eswatini MICS was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, and for the four regions of the country (Hhohho, Manzini, Shiselweni and Lubombo).
A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The 2006/07 Swaziland Demographic Health Survey (SDHS) collected many of the indicators in the MICS. Therefore, the results of the 2006/07 SDHS and the sample design were used as a reference in finalizing the sample design for the 2010 Swaziland MICS. In the survey, most of the indicators will be tabulated at the national level, urban and rural domains, and for the four regions as in the case of the 2006/07 SDHS.
The sampling frame for MICS comes from the recent Kingdom of Eswatini Census of Population and Housing data collected in 2007. The primary sampling units (PSUs) are the census enumeration areas (EAs). The EAs were created for the 2007 Census operations with well-defined boundaries identified on sketch maps. The number of households in an EA is based on the expected workload for one enumerator. According to the 2007 Census, the average number of households per EA is 103 (274 for rural EAs and 34 for urban EAs).
The sample size for a good household survey, such as the 2010 Kingdom of Eswatini MICS, is determined by the accuracy required for the estimates for each domain, as well as by the resource and operational constraints. The allocation of the sample EAs in each region to the rural and urban strata will be proportional to the number of households. Based on these criteria, the proposed allocation of sample EAs and households by region and rural and urban stratum results in a total sample of 365 EAs and 5,475 households.
The sampling procedures are more fully described in "Swaziland Multiple Indicator Cluster Survey 2010 - Final Report" pp.A1-A6.
Of the 5,475 households selected for the sample nationally, 5,074 households were found to be occupied. Of these, 4,834 households were interviewed successfully yielding a household response rate of 95 percent. Among the interviewed households, 4,956 women age 15–49 years and 4,646 men age 15–59 years were identified. Of this number, 4,688 women and 4,179 men were successfully interviewed, yielding a response rate of 95 percent and 90 percent respectively. In addition, 2,711 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 2,647, corresponding to a response rate of 98 percent. Overall response rates of 90, 86 and 93 percent are calculated for under-five’s, women’s and men’s interviews respectively.
Responses varied slightly by residence with higher rates for women and men in rural areas than in urban areas. The situation was the reverse for children under-five where rural areas had higher response rates than urban areas. The overall response rate for women, men and children under five years in rural areas were, however, higher than in urban areas. The main reason for non-response among households and eligible individuals was the failure to find these individuals at home despite several visits to the households. Regional differentials also exist with all the regions having a 90 percent or higher response rate for all the questionnaires with the exception of Hhohho and Shiselweni regions that had 88 and 89 percent response rate, respectively, for the men’s questionnaire.
The basic weight for each sample household is equal to the inverse of its probability of selection (calculated by multiplying the probabilities at each sampling stage). To make the estimates from the 2010 Swaziland MICS sample to be representative of the population, it is necessary to multiply the data by a sampling weight, or expansion factor.
As indicated in the previous section, the 365 EAs sampled for the 2010 Swaziland MICS were selected using the PPS methodology from the total 2,065 EAs in the Census 2007, separately for each stratum. At the second stage 15 sample households are selected with equal probability from the listing for each sampled EA.
Computation and implementation of sample weights for the 2010 Swaziland MICS were carried out at the stratum level. This has been done to have a smoothed weight at the stratum level catering for the non-response and variations in the number of households at that level, and also to avoid unusual inflation or deflation in the weights due to variations in small number of cases at the EA level.
The sample weights were calculated as the stratum (11 sample domains) base, so each cluster within the same domain will take the same weights (of course different for household, women, men and children level). The weight variable was added to each dataset. This was performed by using the statistical software SPSS with an add variables feature under the data/merge files, the data sets were sorted by domain variable and were taken as a key variable during the process.
Although the weights were calculated by 11 domains, including three company towns/estates of Hhohho, Manzini and Lubombo, they are already the part of three of four main regions. These three ‘company towns/estates’ domains will be regarded as a part of the Hhohho, Manzini and Lubombo regions.
Dates of collection
Mode of data collection
Data collection supervision
There is one supovisor for each of the 6 survey teams in the field.
The 2010 Kingdom of Eswatini MICS consists of four main questionnaires including a household questionnaire, women’s and men’s questionnaires and a questionnaire for children under age five. The survey includes information on key indicators on the following topics:
Household questionnaire: age, sex, urban vs. rural residency, household composition, education of household members, household assets, water and sanitation, use of iodized salt, use of insecticidetreated nets (ITNs), orphanhood and vulnerability of children, child labor and child discipline.
Questionnaire for children under five: birth registration, early childhood development, infant and young child feeding, care of illness (including diarrhoea and pneumonia), malaria, immunization and anthropometry.
Women’s questionnaire: child mortality, birth history, desire for last birth, maternal an newborn health, illness symptoms, contraception, unmet need, marriage/union, sexual behaviour, HIV/AIDS, sexually transmitted infections (STIs), and attitudes towards domestic violence.
Men’s questionnaire: marriage/union, attitudes towards contraception, sexual behaviour, HIV/AIDS, STIs, male circumcision and attitudes towards domestic violence.
Central Statistical Office
Data entry commenced on 3 September after an initial training and ended on 17 December 2010. Data were entered on 10 computers by 10 data entry operators and two data entry supervisors using the CSPro software. In order to ensure quality control, all questionnaires were double entered and two secondary editors complemented the efforts of entry supervisors to perform internal consistency checks. Procedures and standard programmes developed under the global MICS4 survey were adapted, based on the modified Swaziland MICS questionnaires, and used throughout the processing. Data were analyzed using the Statistical Package for Social Sciences (SPSS) software programme, and syntax and tabulation plans developed for the global MICS4 were customized for this purpose.
The sample of respondents selected in the 2010 Kingdom of Eswatini MICS is only one of the samples that could have been selected from the same population, using the same design and 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. The extent of variability is not known exactly, but can be estimated statistically from the survey results.
The following sampling error measures are presented in this appendix for each of the selected indicators:
Standard error (se): Sampling errors are usually measured in terms of standard errors for particular indicators (means, proportions etc). A standard error is the square root of the variance. The Taylor linearization method is used for the estimation of standard errors.
Coefficient of variation (se/r) is the ratio of the standard error to the value of the indicator.
Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling. The square root of the design effect, called the design factor (deft) is used to show the efficiency of the sample design. A deft value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a deft value above 1.0 indicates the increase in the standard error due to the use of a more complex sample design.
Confidence limits are calculated to show the interval within which the true value for the population can be reasonably assumed to fall. For any given statistic calculated from the survey, the value of that statistics will fall within a range of plus or minus two times the standard error (p + 2.se or p – 2.se) of the statistic in 95 percent of all possible samples of identical size and design. For the calculation of sampling errors from the MICS data, the SPSS Complex Samples module has been used. The results are shown in the tables that follow. In addition to the sampling error measures described above, the tables also include weighted and unweighted counts of denominators for each indicator.
Sampling errors are calculated for indicators of primary interest, for the national total, for the regions, and for urban and rural areas. Two of the selected indicators are based on households, eight are based on household members, 21 are based on women, 19 are based on children under five and 12 are based on men. All indicators presented here are in the form of proportions.
Other forms of data appraisal
A series of data quality tables are available to review the quality of the data and include the following:
- Age distribution of household population
- Age distribution of eligible and interviewed women
- Age distribution of eligible and interviewed men
- Age distribution of under-fives in household and under-5 questionnaires
- Women's completion rates by socio-economic characteristics of households
- Men's completion rates by socio–economic characteristics of households
- Completion rates for under-5 questionnaires by socio-economic characteristics of households
- Completeness of reporting
- Completeness of information for anthropometric indicators
- Heaping in anthropometric measurements
- Observation of bednets and places for hand washing
- Observation of women's health cards
- Observation of vaccination cards
- Presence of mother in the household and the person interviewed for the under-5 questionnaire
- Selection of children age 2-14 years for the child discipline module
- School attendance by single age
- Sex ratio at birth among children ever born and living
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
The results of each of these data quality tables are shown in appendix D in document "Swaziland Multiple Indicator Cluster Survey 2011 - Final Report" pp.A38-A55.
Users of the data agree to keep confidential all data contained in these datasets and to make no attempt to identify, trace or contact any individual whose data is included in these datasets.
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
United Nations Children's Fund, Central Statistical Office of the Kingdom of Eswatini. Kingdom of Eswatini Multiple Indicator Cluster Survey (MICS) 2010, Ref. SWZ_2010_MICS_v01_M. Dataset downloaded from [url] on [date].
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.