Identification
Survey ID Number
KEN-KNBS-MICS-2008-V01
Title
Multiple Indicator Cluster Survey North Eastern Province 2008
Country
| Name | Country code |
|---|---|
| Kenya | KEN |
Study type
Multiple Indicator Cluster Survey - Round 3 [hh/mics-3]
Abstract
The Kenya Multiple Indicator Cluster Survey (MICS 3) was conducted in North Eastern Province (NEP) which is currently made up of the districts of Garissa, Mandera Wajir and Ijara. However, the survey coverage did not include Ijara as a separate entity. During the time of preparing the sampling frame upon which the survey was based, Ijara was part of Garissa district. The province together with the other ASAL areas is one of the most disadvantaged provinces in terms of social-economic development in Kenya. It is inhabited predominantly by nomadic pastoralists who are resource poor and who suffer frequent incidents of famine, drought, occasional floods and other disasters and emergencies which require massive humanitarian relieve assistance.
The main objective of the survey was to obtain the statistical data that are needed to monitor progress towards development goals defined not only in the MDG and WFFC platforms but also in development programmes such as Poverty Reduction Strategy (PRS), Economic Recovery Strategy (ERS) and Free Primary School Programme (FPSP).
The survey was designed in accordance with the guidelines of the global MICS 3 except for the sample size which was smaller than recommended. As a result, there are subclasses which had few reported cases. In the tables, percentages calculated on the basis of fewer than 25 cases have not been shown but asterisked while those based on between 25 and 49 cases have been put in parenthesis. This is supposed to alert the reader to be circumspect when drawing conclusions from such data. Areas used as PSUs were drawn from the National Sample Survey and Evaluation Programme (NASSEP IV) master sampling frame maintained by the Kenya National Bureau of Statistics (KNBS). Since this frame has few clusters at the district level in ASAL areas, all available clusters were surveyed and a much bigger number of households per cluster (15) were selected compared to 10 selected for MICS 2.
Overall, the data presented in this report indicate that the situation of under five children who live in the NEP is still precarious and in need of assistance compared to the rest of the country. There still remains much more to be done in the province if the declared national and international goals mainly affecting children are to be achieved.
With regard to indicators for the nutritional status of young children, namely stunting, wasting and underweight, the KDHS estimates for NEP are 24, 27 and 34 percent respectively while MICS 3 estimates for the same indicators are respectively 34, 17 and 33 percent. At the household level, 85.7 percent were using appropriately iodized salt which compares with the national estimate of 91 percent obtained from MICS 2. Overall, the survey data reveal high levels of child malnutrition with the consequent need for more specific and focused interventions aimed at reducing the high levels of morbidity and mortality associated with the equally high levels of chronic malnutrition.
In the area of disease prevention, the proportion of children aged 12-23 months who were fully immunized by their first birthday was only 7.4 percent compared with 57 percent nationally obtained from the 2003 KDHS for the children in the same age group. Immunization against tuberculosis was better at 72.5 percent while full DPT3 immunization coverage stood at an unimpressive 30 percent and measles at 44 percent.
The proportion of households that were using improved drinking water sources was 45.3 percent while the use of improved sanitation facilities was lower at only 12.6 percent. This highlights the need to enhance the availability of clean drinking water and appropriate sanitation facilities especially in these disadvantaged areas. It is well known that social investment in the area of water and sanitation promotes economic and social advancement by reducing levels of morbidity in the general population.
Despite the introduction of free primary education in Kenya, progress in school attendance in NEP is still weak. Net attendance ratios at primary and secondary school levels are respectively 51.2 percent and 3.5 percent. The gender parity index (GPI) for primary school is 0.73. The situation is much worse in secondary school where boys outnumber girls and the GPI was 0.54. This suggests that many young girls leave primary school to presumably get married. With respect to child protection, while the rate of birth registration is still low at 19.3 percent, the level of child labour stood at 6.7 percent.
The survey also collected data on knowledge of HIV/AIDS as well as attitude towards people living with the condition. Overall, the indicators related to HIV/AIDS, show a relatively low level of awareness about the scourge. While 93.2 percent of the women had heard about HIV/AIDS only 7.7 percent of women aged 15-49 were found to have comprehensive knowledge of HIV/AIDS transmission. With regard to attitudes towards people living wit HIV/AIDS, nearly 90 percent of the women agree with at least one discriminatory statement against people living with AIDS while only 10 percent do not agree with any of the discriminatory statements contained in the questionnaire.
Finally, the survey collected data on orphaned and vulnerable children who find themselves in this situation as a result of adult morbidity and mortality. The prevalence of orphanhood stood at 20.8 percent while that of vulnerability at 13 percent. The percentage of households with children orphaned and made vulnerable by HIV/AIDS who received assistance is 31.4 percent.
In conclusion, the statistics presented in this report should be viewed as being baseline data which will need to be corroborated by data from well representative follow-up surveys and studies in order to establish a true trend.
The main objective of the survey was to obtain the statistical data that are needed to monitor progress towards development goals defined not only in the MDG and WFFC platforms but also in development programmes such as Poverty Reduction Strategy (PRS), Economic Recovery Strategy (ERS) and Free Primary School Programme (FPSP).
The survey was designed in accordance with the guidelines of the global MICS 3 except for the sample size which was smaller than recommended. As a result, there are subclasses which had few reported cases. In the tables, percentages calculated on the basis of fewer than 25 cases have not been shown but asterisked while those based on between 25 and 49 cases have been put in parenthesis. This is supposed to alert the reader to be circumspect when drawing conclusions from such data. Areas used as PSUs were drawn from the National Sample Survey and Evaluation Programme (NASSEP IV) master sampling frame maintained by the Kenya National Bureau of Statistics (KNBS). Since this frame has few clusters at the district level in ASAL areas, all available clusters were surveyed and a much bigger number of households per cluster (15) were selected compared to 10 selected for MICS 2.
Overall, the data presented in this report indicate that the situation of under five children who live in the NEP is still precarious and in need of assistance compared to the rest of the country. There still remains much more to be done in the province if the declared national and international goals mainly affecting children are to be achieved.
With regard to indicators for the nutritional status of young children, namely stunting, wasting and underweight, the KDHS estimates for NEP are 24, 27 and 34 percent respectively while MICS 3 estimates for the same indicators are respectively 34, 17 and 33 percent. At the household level, 85.7 percent were using appropriately iodized salt which compares with the national estimate of 91 percent obtained from MICS 2. Overall, the survey data reveal high levels of child malnutrition with the consequent need for more specific and focused interventions aimed at reducing the high levels of morbidity and mortality associated with the equally high levels of chronic malnutrition.
In the area of disease prevention, the proportion of children aged 12-23 months who were fully immunized by their first birthday was only 7.4 percent compared with 57 percent nationally obtained from the 2003 KDHS for the children in the same age group. Immunization against tuberculosis was better at 72.5 percent while full DPT3 immunization coverage stood at an unimpressive 30 percent and measles at 44 percent.
The proportion of households that were using improved drinking water sources was 45.3 percent while the use of improved sanitation facilities was lower at only 12.6 percent. This highlights the need to enhance the availability of clean drinking water and appropriate sanitation facilities especially in these disadvantaged areas. It is well known that social investment in the area of water and sanitation promotes economic and social advancement by reducing levels of morbidity in the general population.
Despite the introduction of free primary education in Kenya, progress in school attendance in NEP is still weak. Net attendance ratios at primary and secondary school levels are respectively 51.2 percent and 3.5 percent. The gender parity index (GPI) for primary school is 0.73. The situation is much worse in secondary school where boys outnumber girls and the GPI was 0.54. This suggests that many young girls leave primary school to presumably get married. With respect to child protection, while the rate of birth registration is still low at 19.3 percent, the level of child labour stood at 6.7 percent.
The survey also collected data on knowledge of HIV/AIDS as well as attitude towards people living with the condition. Overall, the indicators related to HIV/AIDS, show a relatively low level of awareness about the scourge. While 93.2 percent of the women had heard about HIV/AIDS only 7.7 percent of women aged 15-49 were found to have comprehensive knowledge of HIV/AIDS transmission. With regard to attitudes towards people living wit HIV/AIDS, nearly 90 percent of the women agree with at least one discriminatory statement against people living with AIDS while only 10 percent do not agree with any of the discriminatory statements contained in the questionnaire.
Finally, the survey collected data on orphaned and vulnerable children who find themselves in this situation as a result of adult morbidity and mortality. The prevalence of orphanhood stood at 20.8 percent while that of vulnerability at 13 percent. The percentage of households with children orphaned and made vulnerable by HIV/AIDS who received assistance is 31.4 percent.
In conclusion, the statistics presented in this report should be viewed as being baseline data which will need to be corroborated by data from well representative follow-up surveys and studies in order to establish a true trend.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Lists of household had been prepared by the listing teams in the field for each enumeration area way back in 2005. The households were then sequentially numbered from 1 to n (the total number of households in each enumeration area) at the KNBS Office, where selection of 15 households in each cluster was carried out using systematic selection procedures.
Version
Version Description
Version 01
Version Date
2008-05-28
Scope
Notes
The scope of the Multiple Indicator Cluster Survey( North Eastern Province) 2008 includes:
- HOUSEHOLD: Household characteristics, household listing, orphaned and vulnerable children, education, child labour, water and sanitation, household use of insecticide treated mosquito nets, and salt iodization, with optional modules for child discipline, child disability, maternal mortality and security of tenure and durability of housing.
- WOMEN: Women's characteristics, child mortality, tetanus toxoid, maternal and newborn health, marriage, polygyny, female genital cutting, contraception, and HIV/AIDS knowledge, with optional modules for unmet need, domestic violence, and sexual behavior.
- CHILDREN: Children's characteristics, birth registration and early learning, vitamin A, breastfeeding, care of illness, malaria, immunization, and anthropometry, with an optional module for child development.
- HOUSEHOLD: Household characteristics, household listing, orphaned and vulnerable children, education, child labour, water and sanitation, household use of insecticide treated mosquito nets, and salt iodization, with optional modules for child discipline, child disability, maternal mortality and security of tenure and durability of housing.
- WOMEN: Women's characteristics, child mortality, tetanus toxoid, maternal and newborn health, marriage, polygyny, female genital cutting, contraception, and HIV/AIDS knowledge, with optional modules for unmet need, domestic violence, and sexual behavior.
- CHILDREN: Children's characteristics, birth registration and early learning, vitamin A, breastfeeding, care of illness, malaria, immunization, and anthropometry, with an optional module for child development.
Coverage
Geographic Coverage
The survey covered four districts in North Eastern province: namely Garissa, Wajir, Ijaara and Mandera. Ijaara at the time was part of Garissa District.
Universe
The resulting number of households from this exercise was 1,205 from 82 clusters. In each of the 4 districts, all operational NASSEP clusters were included in the sample. In each cluster 15 households were selected using pps systematic method of selection.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Kenya National Bureau of Statistics | Ministry of Planning National Development and Vision 2030 |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Kenya National Bureau of Statistics | Ministry of Planning National Development and Vision 2030 | Conducting and Documentantion of the Survey |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| United Nation Children's Fund | UNICEF | Funding of the Survey |
Sampling
Sampling Procedure
District-level stratified probability sample was used. The frame was ready in the form of the National Sample Survey and Evaluation Programme (NASSEP IV) created by KNBS in 2002. It was decided to cover all operational clusters in the four study districts.
Weighting
The Kenya Multiple Indicator Cluster Survey sample is not self-weighted. Essentially, by allocating equal numbers of households to each of the regions, different sampling fractions were used in each region since the size of the regions varied. For this reason, sample weights were calculated and these were used in the subsequent analyses of the survey data.
The major component of the weight is the reciprocal of the sampling fraction employed in selecting the number of sample households in that particular sampling domain:
Wh = 1 / fh
The term fh, the sampling fraction at the h-th stratum, is the product of probabilities of selection at every stage in each sampling domain:
fh = P1h * P2h * P3h
where Pih is the probability of selection of the sampling unit in the i-th stage for the h-th sampling domain.
Since the estimated numbers of households per enumeration area prior to the first stage selection (selection of primary sampling units) and the updated number of households per enumeration area were different, individual sampling fractions for households in each enumeration area (cluster) were calculated. The sampling fractions for households in each enumeration area (cluster) therefore included the probability of selection of the enumeration area in that particular sampling domain and the probability of selection of a household in the sample enumeration area (cluster).
A second component which has to be taken into account in the calculation of sample weights is the level of non-response for the household and individual interviews. The adjustment for household non-response is equal to the inverse value of:
RR = Number of interviewed households / Number of occupied households listed
After the completion of fieldwork, response rates were calculated for each sampling domain. These were used to adjust the sample weights calculated for each cluster. Response rates in the Kenya Multiple Indicator Cluster Survey are shown in Table 1 in this report.
Similarly, the adjustment for non-response at the individual level (women and under-5 children) is equal to the inverse value of:
RR = Completed women's (or under-5's) questionnaires / Eligible women (or under-5s)
Numbers of eligible women and under-5 children were obtained from the household listing in the Household Questionnaire in households where interviews were completed.
The unadjusted weights for the households were calculated by multiplying the above factors for each enumeration area. These weights were then standardized (or normalized), one purpose of which is to make the sum of the interviewed sample units equal the total sample size at the national level. Normalization is performed by multiplying the aforementioned unadjusted weights by the ratio of the number of completed households to the total unadjusted weighted number of households. A similar standardization procedure was followed in obtaining standardized weights for the women's and under-5's questionnaires.
Sample weights were appended to all data sets and analyses were performed by weighting each household, woman or under-5 with these sample weights.
The major component of the weight is the reciprocal of the sampling fraction employed in selecting the number of sample households in that particular sampling domain:
Wh = 1 / fh
The term fh, the sampling fraction at the h-th stratum, is the product of probabilities of selection at every stage in each sampling domain:
fh = P1h * P2h * P3h
where Pih is the probability of selection of the sampling unit in the i-th stage for the h-th sampling domain.
Since the estimated numbers of households per enumeration area prior to the first stage selection (selection of primary sampling units) and the updated number of households per enumeration area were different, individual sampling fractions for households in each enumeration area (cluster) were calculated. The sampling fractions for households in each enumeration area (cluster) therefore included the probability of selection of the enumeration area in that particular sampling domain and the probability of selection of a household in the sample enumeration area (cluster).
A second component which has to be taken into account in the calculation of sample weights is the level of non-response for the household and individual interviews. The adjustment for household non-response is equal to the inverse value of:
RR = Number of interviewed households / Number of occupied households listed
After the completion of fieldwork, response rates were calculated for each sampling domain. These were used to adjust the sample weights calculated for each cluster. Response rates in the Kenya Multiple Indicator Cluster Survey are shown in Table 1 in this report.
Similarly, the adjustment for non-response at the individual level (women and under-5 children) is equal to the inverse value of:
RR = Completed women's (or under-5's) questionnaires / Eligible women (or under-5s)
Numbers of eligible women and under-5 children were obtained from the household listing in the Household Questionnaire in households where interviews were completed.
The unadjusted weights for the households were calculated by multiplying the above factors for each enumeration area. These weights were then standardized (or normalized), one purpose of which is to make the sum of the interviewed sample units equal the total sample size at the national level. Normalization is performed by multiplying the aforementioned unadjusted weights by the ratio of the number of completed households to the total unadjusted weighted number of households. A similar standardization procedure was followed in obtaining standardized weights for the women's and under-5's questionnaires.
Sample weights were appended to all data sets and analyses were performed by weighting each household, woman or under-5 with these sample weights.
Data Collection
Dates of Data Collection
| Start |
|---|
| 2008 |
Data Collection Mode
Face-to-face [f2f]
Questionnaires
Questionnaires
Three sets of questionnaires were used in the survey:
(1) a household questionnaire which was used to collect information on all de jure household members, the household and the dwelling;
(2) a women's questionnaire administered in each household to women aged 15-49 years; and
(3) an under-5 questionnaire, administered to mothers or caretakers of all children under 5 children living in the household.
(1) a household questionnaire which was used to collect information on all de jure household members, the household and the dwelling;
(2) a women's questionnaire administered in each household to women aged 15-49 years; and
(3) an under-5 questionnaire, administered to mothers or caretakers of all children under 5 children living in the household.
Data Processing
Data Editing
Data were entered on six microcomputers using the CSPRO software. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Customized versions of procedures and standard programs developed under the Global MISC3 project were used throughout.
Data processing began after data collection in March, 2007 and finished in April 2007. Data were analyzed using SPSS software program and the model syntax and tabulation plans with the associated changes/amendments developed for this purpose
Data processing began after data collection in March, 2007 and finished in April 2007. Data were analyzed using SPSS software program and the model syntax and tabulation plans with the associated changes/amendments developed for this purpose
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Director General | Kenya National Bureau of Statistics | DirectorGeneral@knbs.or.ke |
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
(c) 2008, Kenya National Bureau of Statistics
Metadata production
DDI Document ID
KEN-KNBS-MICS-2008-V01
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Kenya National Bureau of Statistics | KNBS | Ministry of Planning National Development and Vision 2030 | Documentation of survey |
Date of Metadata Production
2013-03-27
DDI Document version
Version 1.1 (March 2013)