The Kakamega County Multiple Indicator Cluster Survey (MICS) was carried out in collaboration with the Population Studies and Research Institute (PSRI) of the University of Nairobi, the Kenya National Bureau of Statistics (KNBS) and the United Nations Children's Fund (UNICEF) as part of the global MICS program. Technical and financial support were provided by the United Nations Children's Fund.
The global MICS program was developed by UNICEF in the 1990s as an international household survey program to support countries in the collection of internationally comparable data on a wide range of indicators on the situation of children and women. MICS surveys measure key indicators that allow countries to generate data for use in policies and program, and to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments.
The results of this survey provided requisite baseline information that can be used to facilitate evidence-based planning, budgeting and programming by policymakers and stakeholders at the county levels. The survey will go a long way in encouraging increased demand for use of statistics by policy makers at devolved levels and will ensure that resources at both county and national levels are used most effectively through well-planned projects/programs that will benefit especially the women and children of the three counties.The MICS5 results were critical in gauging milestones achieved in the field of education, nutrition, child development, health for women and children in the three counties and in evaluating the various health based policies that the government has formulated over the years towards achieving the national welfare objectives.
The 2013-14 MICS5 data was critical in informing the future planning for the three counties, especially in view of the new constitutional dispensation and Vision 2030. It was anticipated that MICS5 would supplement the data collected during the 2014 Kenya Demographic and Health Survey (KDHS). In addition the information collected would inform strategic communication for social and behavior change interventions by government and partners including UNICEF. Furthermore the data contributed to the improvement of data and monitoring systems in the three counties. The primary objectives of the Kakamega County survey are:
1. To provide up-to-date information for assessing the situation of children and women in Kakamega County.
2. To generate data for the critical assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention.
3. To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, and other internationally agreed upon goals, as a basis for future action.
4. To collect disaggregated data for the identification of disparities, to allow for evidence based policy-making aimed at social inclusion of the most vulnerable.
5. To contribute to the generation of baseline data for the post-2015 agenda.
6. To validate data from other sources and the results of focused interventions.
7. To contribute to the improvement of data and monitoring systems in Kenya and to strengthen technical expertise in the design, implementation, and analysis of such systems.
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 and all children under 5 living in the household.
Producers and sponsors
Population Studies and Research Institute
University of Nairobi
Kenya National Bureau of Statistics
United Nations Children’s Fund
Financial and technical support
The sample for the Kakamega County MICS, 2013-14 was designed to provide estimates for a large number of indicators on the situation of children and women at the county level. The urban and rural areas within the county were the main sampling strata. The sample was selected in two stages: cluster and household. The survey utilized the fifth National Sample Survey and Evaluation Program (NASSEP V) household-based master sampling frame which is created and maintained by the Kenya National Bureau of Statistics (KNBS). The primary sampling unit for the frame is a cluster, which constitutes one or more EAs, with an average of 100 households.
For the NASSEP V master sample the EAs were selected within each stratum using systematic sampling with probabilities proportion to size (PPS). For the MICS, within each stratum a specified number of census enumeration areas was selected from the master sample using an equal probability selection method (EPSEM). After a household listing was carried out in the selected clusters, a systematic sample of 30 households was drawn in each sampled cluster. In total, 50 clusters were selected for the survey in Kakamega County. The sample was stratified by urban and rural areas, and was not self-weighting. All selected clusters were visited during fieldwork. For reporting county level results, sample weights are used. A more detailed description of the sample design is provided in Appendix C.
The Kenya MICS 2013 was based on a representative sample of 1,221 households representing a 92 percent response rate. The composition of these households was 5,666 household members comprising 2,752 males and 2,914 females. The mean household size was 4.6 persons. About 46 percent of the sampled households' population is below 15 years, 50 percent are age 15-64 years, and four percent are age 65 years and above.
Due to data quality issues, data relating to mortality and anthropometric measures were not analyzed and reported. Anthropometric data suffered from digit preference for both weight and height, while for mortality, deaths especially among under-5 years old were under reported. KDHS 2014 had similar shortcomings.
The MICS5 sample was not self-weighting and thus a weighting process was required to provide estimates representative of the target population. Two main sampling weights were calculated: household weights and individual (women and children) weights. The base weights incorporated the probabilities of selection of the clusters from the census EAs database into the NASSEP V sample frame, the probabilities of selection of the MICS clusters from NASSEP V frame and the probabilities of selection of the households from each of the NASSEP V frame clusters.
Base weights were then adjusted for cluster and household non-response by multiplying them by the inverse of the clusters and households response rates. The individual weight of a woman or child was calculated as the household weight multiplied by the inverse of the individual response rate. Given that the MICS5 sample was a two-stage stratified cluster sample, sampling probabilities were calculated separately for each sampling stage.
Dates of collection
Mode of data collection
A set of three questionnaires was used in the survey:
1. A household questionnaire which was administered to the household head or any other responsible member of the household.
2. A questionnaire for individual women administered in each household to all women age 15-49 years.
3. An under-5 questionnaire administered to mothers (or caretakers) for all children under-5 years living in the household.
Kenya National Bureau of Statistics
Data were entered into the computers using the Census and Surveys Processing System (CSPro) software package, Version 5.0. Data entry was done by a trained team of 14 data entry operators, one archivist/system administrator and one data entry supervisor. For quality assurance purposes, all questionnaires were double-entered and internal consistency checks performed.
Procedures and standard programs developed under the global MICS program and adapted to the Kakamega County MICS questionnaire were used throughout. Data processing began simultaneously with data collection in November 2013 and was completed in February 2014. Data were analyzed using the Statistical Package for Social Sciences (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF were customized and used for this purpose.
The sample of respondents selected in the Kakamega Multiple Indicator Cluster Survey 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 the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data.
The following sampling error measures are presented in this appendix for each of the selected indicators:
- Standard error (se): Standard error is the square root of the variance of the estimate. For survey indicators that are means, proportions or ratios, the Taylor series linearization method is used for the estimation of standard errors. For more complex statistics, such as fertility and mortality rates, the Jackknife repeated replication method is used for standard error estimation.
- Coefficient of variation (se/r) is the ratio of the standard error to the value (r) of the indicator, and is a measure of the relative sampling error.
- 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 based on the same sample size. The square root of the design effect (deft) is used to show the efficiency of the sample design in relation to the precision. A deft value of 1.0 indicates that the sample design of the survey is as efficient as a simple random sample for a particular indicator, while a deft value above 1.0 indicates an 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, with a specified level of confidence. For any given statistic calculated from the survey, the value of that statistic will fall within a range of plus or minus two times the standard error (r + 2.se or r - 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, programs developed in CSPro Version 5.0, SPSS Version 21 Complex Samples module and CMRJack116 have 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. Given the use of normalized weights, by comparing the weighted and unweighted counts it is possible to determine whether a particular domain has been under-sampled or over-sampled compared to the average sampling rate. If the weighted count is smaller than the unweighted count, this means that the particular domain had been over-sampled. As explained later in the footnote of Table SE.1, there is an exception in the case of indicators 4.1 and 4.3, for which the unweighted count represents the number of sample households, and the weighted counts reflect the total population.
Sampling errors are calculated for indicators of primary interest, at the county level, and for urban and rural areas within Kakamega County. Three of the selected indicators are based on household's members, eight are based on women, and two are based on children under 5. Table SE.1 shows the list of indicators for which sampling errors are calculated, including the base population (denominator) for each indicator. Tables SE.2 to SE.4 show the calculated sampling errors for selected domains.
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United Nations Children's Fund, Kenya National Bureau of Statistics. Kenya Multiple Indicator Cluster Survey (MICS) 2013, Ref. KEN_2013_MICS-KC_v01_M. Dataset downloaded from [url] on [date]
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