The Bungoma County Multiple Indicator Cluster Survey (MICS5) was conducted 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).The Kenya National Bureau of Statistics implemented (MICS5) in 2013-2014 in the three counties of Bungoma, Kakamega and Turkana as part of Global MICS round five.
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 programs and to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments. Technical and financial support were provided by the United Nations Children's Fund.
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 Bungoma County survey are: 1. To provide up-to-date information for assessing the situation of children and women in Bungoma 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.
National
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.
Sample survey data [ssd]
The primary objective of the sample design for the Bungoma County MICS was to produce statistically reliable estimates of indicators, at county level. The urban and rural areas in Bungoma County were the sampling strata. A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. MICS5 utilized the recently created fifth National Sample Survey and Evaluation Program (NASSEP V) frame which is a household based master sampling frame developed and maintained by KNBS. The frame was implemented using a multi-tiered structure, in which a set of 4 sub-samples (C1, C2, C3, C4) were developed. It is based on the list of enumeration areas (EAs) from the 2009 Kenya Population and Housing Census. The frame is stratified according to County and further into rural and urban. Each of the sub-samples is representative at county level and at national (i.e. Urban/rural) level and contains 1,340 clusters.
The Primary Sampling Units (PSUs) for the survey were clusters drawn from the NASSEP V sampling frame, so the first component of the probabilities and weights are based on that master sample. Within each stratum the PSUs for the MICS were selected independently from one of the subsamples of the master sample using Equal Probability Selection Method (EPSEM). A total of 50 clusters were selected from the master sample in this way.
Out of the 50 sample clusters selected for Bungoma County, it was established that 30 had been listed more than six months prior to the start of the survey. These listing for these clusters was updated prior to selection of households. For this purpose, listing teams visited each cluster, and listed all occupied households. For the remaining 20 sample clusters a more recent listing was available, so it was used for selecting the sample households.
Face-to-face [f2f]
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.
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 Bungoma 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.
Information was collected from a total of 1,246 households representing 95 percent response rate. The composition of these households was 5,983 household members comprising 2,797 males and 3,186 females. The mean household size was 4.8 persons. About 48 percent of the sampled households' population is below 15 years, 48 percent are between 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 digit preference for both weight and height, while for mortality, deaths especially among children under-five years were under reported. KDHS 2014 had similar shortcomings.
The sample of respondents selected in the Bungoma County 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 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 those 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
The Turkana County Multiple Indicator Cluster Survey (MICS5) was conducted 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).The Kenya National Bureau of Statistics implemented (MICS5) in 2013-2014 in the three counties of Bungoma, Kakamega and Turkana as part of Global MICS round five.
MICS is an international household survey program that 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 provides up-to-date information on the situation of children and women and measures key indicators that allow countries to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments. In Kenya, this information is important to guide the planning and implementation of new development plans targeting the new administrative county levels of governance. Technical and financial support were provided by the United Nations Children's Fund.
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 Turkana County survey are: 1. To provide up-to-date information for assessing the situation of children and women in Turkana 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.
National
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.
Sample survey data [ssd]
The primary objective of the sample design for the Turkana County MICS was to produce statistically reliable estimates of indicators, at county level. The urban and rural areas in Turkana County were the sampling strata. A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. MICS5 utilized the recently created fifth National Sample Survey and Evaluation Programe (NASSEP V) frame which is a household based master sampling frame developed and maintained by KNBS. The frame was implemented using a multi-tiered structure, in which a set of 4 sub-samples (C1, C2, C3, C4) were developed. It is based on the list of enumeration areas (EAs) from the 2009 Kenya Population and Housing Census. The frame is stratified according to County and further into rural and urban. Each of the sub-samples is representative at county level and at national (i.e. Urban/rural) level and contains 1,340 clusters.
The Primary Sampling Units (PSUs) for the survey were clusters drawn from the NASSEP V sampling frame, so the first component of the probabilities and weights are based on that master sample. Within each stratum the PSUs for the MICS were selected independently from one of the subsamples of the master sample using Equal Probability Selection Method (EPSEM). A total of 58 clusters were selected from the master sample in this way.
Out of the 58 clusters selected for Turkana County, it was established that 30 had been listed more than six months prior to the start of the survey. These listing for these clusters was updated prior to selection of households. For this purpose, listing teams visited each cluster, and listed all occupied households. For the remaining 28 sample clusters a more recent listing was available, so it was used for selecting the sample households.
Face-to-face [f2f]
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
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 Turkana 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.
Information was collected from a total of 1,277 households representing 93 percent response rate. The composition of these households was 6,594 household members comprising 3,274 males and 3,321 females. The mean household size was 5.2 persons. About 49 percent of the sampled households population is below 15 years, 48 percent are age 15-64 years and three 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 sample of respondents selected in the Turkana County 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 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 those 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
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The Bungoma County Multiple Indicator Cluster Survey (MICS5) was conducted 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).The Kenya National Bureau of Statistics implemented (MICS5) in 2013-2014 in the three counties of Bungoma, Kakamega and Turkana as part of Global MICS round five.
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 programs and to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments. Technical and financial support were provided by the United Nations Children's Fund.
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 Bungoma County survey are: 1. To provide up-to-date information for assessing the situation of children and women in Bungoma 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.
National
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.
Sample survey data [ssd]
The primary objective of the sample design for the Bungoma County MICS was to produce statistically reliable estimates of indicators, at county level. The urban and rural areas in Bungoma County were the sampling strata. A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. MICS5 utilized the recently created fifth National Sample Survey and Evaluation Program (NASSEP V) frame which is a household based master sampling frame developed and maintained by KNBS. The frame was implemented using a multi-tiered structure, in which a set of 4 sub-samples (C1, C2, C3, C4) were developed. It is based on the list of enumeration areas (EAs) from the 2009 Kenya Population and Housing Census. The frame is stratified according to County and further into rural and urban. Each of the sub-samples is representative at county level and at national (i.e. Urban/rural) level and contains 1,340 clusters.
The Primary Sampling Units (PSUs) for the survey were clusters drawn from the NASSEP V sampling frame, so the first component of the probabilities and weights are based on that master sample. Within each stratum the PSUs for the MICS were selected independently from one of the subsamples of the master sample using Equal Probability Selection Method (EPSEM). A total of 50 clusters were selected from the master sample in this way.
Out of the 50 sample clusters selected for Bungoma County, it was established that 30 had been listed more than six months prior to the start of the survey. These listing for these clusters was updated prior to selection of households. For this purpose, listing teams visited each cluster, and listed all occupied households. For the remaining 20 sample clusters a more recent listing was available, so it was used for selecting the sample households.
Face-to-face [f2f]
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.
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 Bungoma 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.
Information was collected from a total of 1,246 households representing 95 percent response rate. The composition of these households was 5,983 household members comprising 2,797 males and 3,186 females. The mean household size was 4.8 persons. About 48 percent of the sampled households' population is below 15 years, 48 percent are between 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 digit preference for both weight and height, while for mortality, deaths especially among children under-five years were under reported. KDHS 2014 had similar shortcomings.
The sample of respondents selected in the Bungoma County 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 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 those 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