Early childhood development (ECD) parenting interventions can improve child developmental outcomes in low-resource settings, but information about their implementation lags far behind evidence of their effectiveness, hindering their generalizability. This study presents results from an implementation evaluation of Msingi Bora (“Good Foundation” in Swahili), a group-based responsive stimulation and nutrition education intervention recently tested in a cluster randomized controlled trial across 60 villages in rural western Kenya. Msingi Bora successfully improved child cognitive, receptive language, and socioemotional outcomes, as well as parenting practices. We conducted a mixed methods implementation evaluation of the Msingi Bora trial between April 2018 and November 2019 following the Consolidated Advice for Reporting ECD implementation research (CARE) guidelines. We collected qualitative and quantitative data on program inputs, outputs, and outcomes, with a view to examining how aspects of the program's implementation, such as program acceptance and delivery fidelity, related to observed program impacts on parents and children. We found that study areas had initially very low levels of familiarity or knowledge of ECD among parents, community delivery agents, and even supervisory staff from our partner non-governmental organization (NGO). We increased training and supervision in response, and provided a structured manual to enable local delivery agents to successfully lead the sessions. There was a high level of parental compliance, with median attendance of 13 out of 16 fortnightly sessions over 8 months. For delivery agents, all measures of delivery performance and fidelity increased with program experience. Older, more knowledable delivery agents were associated with larger impacts on parental stimulation and child outcomes, and delivery agents with higher fidelity scores were also related to improved parenting practices. We conclude that a group-based parenting intervention delivered by local delivery agents can improve multiple child and parent outcomes. An upfront investment in training local trainers and delivery agents, and regular supervision of delivery of a manualized program, appear key to our documented success. Our results represent a promising avenue for scaling similar interventions in low-resource rural settings to serve families in need of ECD programming. This trial is registered at ClinicalTrials.gov, NCT03548558, June 7, 2018. https://clinicaltrials.gov/ct2/show/NCT03548558.

BackgroundGlobally, 350 million under-5s do not have adequate childcare. This may damage their health and development and undermine societal and economic development. Rapid urbanization is changing patterns of work, social structures, and gender norms. Parents, mainly mothers, work long hours for insecure daily wages. To respond to increasing demand, childcare centers have sprung up in informal settlements. However, there is currently little or no support to ensure they provide safe, nurturing care accessible to low-income families. Here, we present the process of co-designing an intervention, delivered by local government community health teams to improve the quality of childcare centers and ultimately the health and development of under-5 children in informal settlements in Kenya.MethodsThis mixed methods study started with a rapid mapping of the location and basic characteristics of all childcare centers in two informal settlements in Nairobi. Qualitative interviews were conducted with parents and grandparents (n = 44), childcare providers, and community health teams (n = 44). A series of 7 co-design workshops with representatives from government and non-governmental organizations (NGOs), community health teams, and childcare providers were held to design the intervention. Questionnaires to assess the knowledge, attitudes, and practices of community health volunteers (n = 22) and childcare center providers (n = 66) were conducted.ResultsIn total, 129 childcare centers were identified −55 in Korogocho and 77 in Viwandani. School-based providers dominated in Korogocho (73%) while home-based centers were prevalent in Viwandani (53%). All centers reported minimal support from any organization (19% supported) and this was particularly low among home-based (9%) and center-based (14%) providers. Home-based center providers were the least likely to be trained in early childhood development (20%), hence the co-designed intervention focused on supporting these centers. All co-design stakeholders agreed that with further training, community health volunteers were well placed to support these informal centers. Findings showed that given the context of informal settlements, support for strengthening management within the centers in addition to the core domains of WHO's Nurturing Care Framework was required as a key component of the intervention.ConclusionImplementing a co-design process embedded within existing community health systems and drawing on the lived experiences of childcare providers and parents in informal settlements facilitated the development of an intervention with the potential for scalability and sustainability. Such interventions are urgently needed as the number of home-based and small center-based informal childcare centers is growing rapidly to meet the demand; yet, they receive little support to improve quality and are largely unregulated. Childcare providers, and government and community health teams were able to co-design an intervention delivered within current public community health structures to support centers in improving nurturing care. Further research on the effectiveness and sustainability of support to private and informal childcare centers in the context of low-income urban neighborhoods is needed.

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized allowing comparison between and within countries over time.

The Education SDIs include teacher effort, teacher knowledge and ability, and the availability of key inputs (for example, textbooks, basic teaching equipment, and infrastructure such as blackboards and toilets). The indicators provide a snapshot of the learning environment and the key resources necessary for students to learn.

Kenya's Service Delivery Indicators Education Survey was implemented in May-July 2012 by the Economic Policy Research Center and Kimetrica, in close coordination with the World Bank SDI team. The data were collected from a stratified random sample of 239 public and 67 private schools to provide a representative snapshot of the learning environment in both public and private schools. The survey assessed the knowledge of 1,679 primary school teachers, surveyed 2,960 teachers for an absenteeism study, and observed 306 grade 4 lessons. In addition, learning outcomes were measured for almost 3,000 grade 4 students.

Geographic coverage

National

Analysis unit

Schools, teachers, students.

Universe

All primary schools

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.

The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). In the case of education, SDI surveys also aim to produce accurate information on grade four pupils’ performance through a student assessment. The multistage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.

Detailed information about the specific sampling process conducted for the 2012 Kenya Education SDI is available in the SDI Country Report (“SDI-Report-Kenya”) included as part of the documentation that accompanies these datasets.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Education Survey Questionnaire consists of six modules:

Module 1: School Information - Administered to the head of the school to collect information on school type, facilities, school governance, pupil numbers, and school hours. It includes direct observations of school infrastructure by enumerators.

Module 2a: Teacher Absence and Information - Administered to the headteacher and individual teachers to obtain a list of all school teachers, to measure teacher absence, and to collect information on teacher characteristics.

Module 2b: Teacher Absence and Information - Unannounced visit to the school to assess the absence rate.

Module 3: School Finances - Administered to the headteacher to collect information on school finances (this data is unharmonized)

Module 4: Classroom Observation - An observation module to assess teaching activities and classroom conditions.

Module 5: Pupil Assessment - A test of pupils to have a measure of pupil learning outcomes in mathematics and language in grade four. The test is carried out orally and one-on-one with each student by the enumerator.

Module 6: Teacher Assessment - A test of teachers covering mathematics and language subject knowledge and teaching skills.

Cleaning operations

Data entry was done using CSPro; quality control was performed in Stata.

Sampling error estimates

At the national level, an anticipated standard error of 1.6 percentage points for absenteeism, and 4.4 percentage points for pupil literacy were calculated. At the county level, an anticipated standard error of 3.1 percent for absenteeism and 9.0 percent for literacy were estimated.

Abstract

In 2022, the Ministry of Education collaborated with Zizi Afrique Foundation to implement the Policy Learning for Universal Secondary Education. PLUS aimed at documenting the levers of 100% transition in Kenya and designing a community accountability intervention through the Policy Learning for Universal Secondary (PLUS) education project. Adopting a different approach, the PLUS initiative sought to understand the potential for driving change by focusing on policy enforcement and accountability, rather than plugging gaps. The two-year initiative aims to achieve this through two objectives: I) generating evidence on the drivers and barriers to implementing Kenya's existing 100% transition policy and community accountability; ii) co-creating with the Ministry of Education and stakeholders and testing a community accountability intervention that tests identified successful drivers of 100% transition.

In the last one year, Zizi Afrique worked closely with the Directorate of Secondary Education (DSE) to codesign a survey to generate evidence on the 100% transition to secondary school in Kenya and actively track enrolment into secondary school for the 2022 Kenya Certificate of Secondary Education to observe the levers in action. The initiative is taking place in four sub-counties that were selected based on existing evidence from the MoE on the transition to secondary. The sub-counties include Kahuro in Muranga County, Sololo in Bungoma County, Sololo in Marsabit County and Dagoretti in Nairobi County.

In total 96 schools were sampled from the four sub-counties and had an enrolment of 6409 candidates enrolled for the 2022 Kenya Certificate of Primary Examination. Of these about 40% (2843) were sampled and included in a cross-sectional survey that involved their households, schools, and community leaders to understand potential levers of transition to secondary school.

The cross-sectional survey was followed by active tracking of all 6409 learners between January and March 2023 to monitor their transition to secondary school and document the enablers and barriers to secondary schools. The results of the tracking were compared with NEMIS for validation and to establish areas of improvement. The following key findings emerge from both the cross-sectional survey and tracking as well as from evidence synthesis from literature and secondary data analysis to provide lessons and recommendations that can guide the implementation of the 100% policy guidelines.

Apparent data gaps on secondary school retention and completion: From the review of evidence and secondary data analysis, evidence on retention and completion in secondary school is scarce and inconsistent. However, relying on the Kenya Economic Surveys (2014 to 2023) as well as form 1 admissions and subsequent candidature at form 4 shows almost 10% of the learners enrolled do not sit for their KCSE.

Higher transition observed during tracking than in NEMIS: The active tracking of the 6409 learners showed higher transition across the sub-counties than in NEMIS (Figure 2). For instance, overall, 95% of the students from the tracking had joined secondary school by April 2023, while NEMIS indicated 80%. Transition increased from 47% in Sololo in 2022 to 91% in 2023. Conversations with some of secondary school heads during data validation and dissemination underscored various challenges including but not limited to lack of birth certificates, workload, and internet connectivity as some of the reasons for not registering learners in NEMIS.

Barriers to secondary school transitions: Despite FSDE, schooling cost was underscored as the leading barrier to secondary school (Table 2). The cost included school meals and boarding costs for day scholars and boarders respectively as well as school uniforms - and this was consistent across the four participating sub-counties. Other barriers included substance use and peer pressure, cultural practices, and lack of interest in schooling by both parents and children.

Enablers of transition: The major enablers of secondary school transition were facilitation and support by parents or household members (over 91%) and financial support from existing national and county government bursaries and scholarships as well as from corporations. The NCDF and county government bursaries through common, but either benefited fewer learners or the amounts given were small to significantly reduce the schooling cost.

Multisectoral approach: The involvement of National Government Administration Officers (NGAO) at the community, sub-county and county levels was underscored as critical in marshalling learners to transition. Particularly, the chiefs and their assistants were said to hold power that when fully tapped can ensure all children transition. However, this power could be harnessed when connected with opportunities that address specific barriers that result in non-transition.

Geographic coverage

The PLUS study was conducted in four sub-counties in Kenya, namely Cheptais in Bungoma County, Kahuro in Muranga County, Sololo in Marsabit County, and Dagoretti in Nairobi County.

Universe

The PLUS study covered all usual household members (permanent residents) in the selected areas. Specifically, the study focused on:

Learners: All children enrolled in standard eight in 2022 in the participating public primary schools.

Household Heads: The primary respondents who provided insights into the barriers and enablers to secondary school transition.

School Headteachers: Headteachers of the participating public primary schools.

Village Elders: Village Elders of the selected zones linked to the selected primary schools

Sampling procedure

The PLUS study was conducted in 4 sub-counties in Kenya namely Cheptais in Bungoma County, Kahuro in Muranga County, Sololo in Marsabit County, and Dagoretti in Nairobi County. The sub-counties are spread across four regions, previously referred to as provinces (Western-Bungoma, Central-Muranga, Northeastern-Marsabit, and Nairobi-Dagoretti respectively) and therefore achieve a reasonable geographical coverage. The sub-counties were also selected based on their reported transition rates in secondary school - using the 2021 and 2022 transition rates as computed by the Ministry of Education, Directorate of Secondary Public primary schools with standard eight candidates in 2022 in each sub-county were profiled and a sample of 96 schools was drawn for inclusion in the study. A 40% (2934) sample of learners in each school was drawn for inclusion in the cross-sectional survey, with a minimum of 20 learners selected per school. This implies including all learners in schools that had 20 or fewer; this was common among schools in Kahuro sub-county in Muranga. The survey interviewed household heads, and school and village heads of sampled learners.

Mode of data collection

Face-to-face [f2f]

This dataset is produced from the randomized controlled trial (RCT), which was conducted to test for a causal impact of aflatoxin exposure on child growth. Participants were recruited from among households containing women in the last 5 months of pregnancy in 28 maize-growing villages within Meru and Tharaka-Nithi Counties in Kenya. Households in villages assigned to the intervention group are offered rapid testing of their stored maize for the presence of aflatoxin each month; any maize found to contain more than 10 ppb aflatoxin is replaced with an equal amount of maize that contains less than this concentration of the toxin. They are also offered the opportunity to buy maize that has been tested and found to contain less than 10 ppb aflatoxin at local shops. Clusters (villages) were allocated to the intervention group (28 villages containing 687 participating households) or control group (28 villages containing 536 participating households) using a random number generator. Data collection at baseline and follow-up were done at participants’ homes through face-to-face interviews. A pre-coded survey was administered to the expectant mother immediately after enrollment, her height and weight were measured, and self-reported month of pregnancy was recorded. Expectant mothers were also asked to provide a venous blood sample to be analyzed for serum aflatoxin. A similar survey was repeated during follow-up data collection at 24 months after enrollment. Participants enrolled in the fourth through sixth waves were additionally followed-up 24 months after the third enrollment wave. At each follow-up visit, the length and weight of the child in utero at baseline (reference child) were recorded, and a venous blood sample was taken from this child for serum aflatoxin analysis.

Kenya KE: Prevalence of Wasting: Weight for Height: % of Children Under 5 data was reported at 4.000 % in 2014. This records a decrease from the previous number of 7.000 % for 2009. Kenya KE: Prevalence of Wasting: Weight for Height: % of Children Under 5 data is updated yearly, averaging 7.100 % from Dec 1987 (Median) to 2014, with 9 observations. The data reached an all-time high of 9.400 % in 1994 and a record low of 4.000 % in 2014. Kenya KE: Prevalence of Wasting: Weight for Height: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Health Statistics. Prevalence of wasting is the proportion of children under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Four USAID-funded Kenya projects’ data are included in this folder covering the period from 2006 to 2022. The projects are: 1) Education for Marginalized Children (EMACK) II, 2) Kenya Youth Employment Survey (YES), 3) Primary Math & Reading (PRIMR), and 4) Tusome. Across the projects, the folder contains the following files and numbers of each: codebooks (43), consent (4), data files (31), instruments (9), reports (8).

Abstract

The Government of Kenya is interested in understanding how malaria prevention and treatment can improve the education of school children when it is combined with effective teaching. This project examines the impact of school-based malaria intermittent screening and treatment and enhanced literacy training and support for teachers on children's health and educational outcomes.

A cluster randomized trial was implemented with 5,233 children in 101 government primary schools on the south coast of Kenya in 2010-2012. The intervention was delivered to children randomly selected from classes 1 and 5 who were followed up for 24 months. Once a school term, children were screened by public health workers using malaria rapid diagnostic tests (RDTs), and children (with or without malaria symptoms) found to be RDT-positive were treated with a six dose regimen of artemether-lumefantrine (AL). Given the nature of the intervention, the trial was not blinded. The primary outcomes were anemia and sustained attention. Secondary outcomes were malaria parasitaemia and educational achievement. Data were analyzed on an intention to treat basis. The study is registered with ClinicalTrials.gov, NCT00878007.

The schools were randomly assigned to one of four experimental groups: some schools have been tested and treated for malaria; some schools have had extra support for teachers of English and Swahili; some schools have been both tested for malaria and received extra teacher support; and other schools have gotten neither of the two programs.

Following recruitment, baseline health and education surveys were undertaken in January-February 2010, which were followed by the first round of intermittent screening and treatment (IST) and the teacher training workshop. Classroom observations occurred in May 2010, followed by the second round of IST in June-July 2010. The third round of IST occurred in September 2010. The first follow-up education surveys were carried out in November 2010 and the first health surveys - in February and March 2011, followed by a round of IST as well as refresher teacher training for the literacy intervention. The final round of IST was conducted in September 2011 with the 24 months follow-up health and education survey in February-March 2012.

The data from the baseline and follow-up surveys is documented here.

Geographic coverage

Kwale and Msambweni districts

Analysis unit

Individuals, households, schools

Universe

The survey cover children in grades 1 and 5 in government schools in Kwale and Msambweni districts, their parents/guardians, head teaches of schools in above mentioned districts.

Kind of data

Sample survey data [ssd]

Sampling procedure

School selection was made from the 197 government primary schools in Kwale and Msambweni districts. In Kwale district, a separate study is evaluating the impact of an alternative literacy intervention in two of the four zones; therefore only 20 schools in this district were included in our study allowing the two interventions to proceed without leakage. In Msambweni district, 81 of 112 schools were selected; schools 70 km or further away from the project office, were excluded due to logistical constraints.

The randomization of the 101 schools into the four experimental groups was conducted in two stages, each involving public randomization ceremonies:

Stage 1 - Literacy intervention randomization a) Clusters of schools (groups of between 3-6 schools that meet and share information) were randomised either to receive the literacy intervention or to serve as a control schools. b) This randomization was stratified by (i) cluster size, to ensure equal numbers of schools in the experimental groups; and (ii) average primary school leaving exam scores across the cluster, to balance the two groups for school achievement. c) District officials and representatives from all 26 school clusters were invited to a meeting. Volunteers were asked to randomly draw envelopes each containing a cluster name from 10 pre-stratified ballot boxes and to sequentially place the envelopes in group A and group B.

Stage 2 - Health intervention randomization a) The health intervention was randomly allocated amongst the 51 schools assigned to the literacy intervention and the 50 schools allocated to serve as control schools during the first randomization. b) Schools were stratified by average primary school leaving exam scores into 5 quintiles and by literacy intervention group, producing 10 strata overall. c) Representatives from the 101 schools and local communities were invited to this randomization ceremony. Volunteers were asked to draw envelopes from the 10 pre-stratified ballot boxes and sequentially place the envelopes in group 1 and group 2.

During January and February 2010, schools were visited and a census of all children in classes 1 and 5 was conducted, including children absent on the day of visit. This census served as a basis for making a random selection of 25 children with consent from class 1 and 30 children with consent from class 5. Fewer children were selected from class 1 because of the extra educational assessments undertaken with these children and the practical feasibility of conducting the tests in a single day. Some of the classes were small, and this meant that in these classes all children with consent were recruited.

Of the 5,233 children enrolled initially, 4,446 (85.0%) were included in the 12 month follow-up health survey and 4201 (80.3%) were included in the 24 month health survey. Overall, 4,656 (89.0%) of children were included in the 9 month follow-up education survey and 4,106 (78.5%) in the 24 month follow-up survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following questionnaires and forms are available:

1) School Questionnaire The school questionnaire is administered to the head teachers of each school during the initial school selection; if absent, the deputy head was interviewed. Information is collected on the characteristics of the school such as the number of boys and girls enrolled in each class, examination results in English, mathematics and Kiswahili, school features such as number of desks and teachers, facilities available such as latrines and the presence of school health activities and materials. Locations of each school were mapped using a handheld Global Positioning System (GPS) receiver, (eTrex Garmin Ltd., Olathe, KS).

2) Parent questionnaire for class 1 students The parent questionnaire for class 1 students assesses the educational and socio-economic environment of the children's households. This is administered to the parent or guardian at the time of consent. Questions relate to their own reading ability, schooling, and involvement in their children's school, as well as questions on family composition, household construction, asset ownership and mosquito net ownership and use.

3) Parent questionnaire for class 5 students The parent questionnaire for class 5 students assesses the educational and socio-economic environment of the children's households. This is administered to the parent or guardian at the time of consent. The section on education environment is reduced as the literacy intervention was focused on the class 1 children, so a less extensive knowledge of attitudes to education was required for parents of class 5 children. Questions relate to their schooling level achieved, as well as questions on family composition, household construction, asset ownership, and mosquito net ownership and use.

4) Nurse survey form for classes 1 and 5 The child ID, child name, and parent name of the randomly selected children are already entered on the form before arrival at the school. The nurse records the attendance of each child, completing the reasons using the codes at the bottom of the form. Height, weight and temperature of each child is recorded on the form. The child is also asked their age, which is recorded.

5) Health Technician survey form for classes 1 and 5 The child ID, child name, and parent name of the randomly selected children are already entered on the form before arrival at the school. The technician notes whether the child is present, and then records the hemoglobin reading, whether or not a blood slide has been taken, and the timing and result of the malaria rapid diagnostic test (RDT). This form is for assessment of children in the intervention schools where P falciparum infection is assessed.

Kenya KE: Children Out of School: Male: % of Male Primary School Age data was reported at 18.678 % in 2012. This records a decrease from the previous number of 21.689 % for 2009. Kenya KE: Children Out of School: Male: % of Male Primary School Age data is updated yearly, averaging 28.873 % from Dec 1999 (Median) to 2012, with 12 observations. The data reached an all-time high of 39.074 % in 2002 and a record low of 18.678 % in 2012. Kenya KE: Children Out of School: Male: % of Male Primary School Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Education Statistics. Children out of school are the percentage of primary-school-age children who are not enrolled in primary or secondary school. Children in the official primary age group that are in preprimary education should be considered out of school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

A seven-year randomized evaluation suggests education subsidies reduce adolescent girls' dropout, pregnancy, and marriage but not sexually transmitted infection (STI). The government's HIV curriculum, which stresses abstinence until marriage, does not reduce pregnancy or STI. Both programs combined reduce STI more, but cut dropout and pregnancy less, than education subsidies alone. These results are inconsistent with a model of schooling and sexual behavior in which both pregnancy and STI are determined by one factor (unprotected sex), but consistent with a two-factor model in which choices between committed and casual relationships also affect these outcomes. This data was collected as a part of the study "Education, HIV, and Early Fertility: Experimental Evidence from Kenya." Details on sample construction and data collection for this survey data can be found in the paper. The 2012 version of the paper is available here: http://www.stanford.edu/~pdupas/DDK_EducFertHIV.pdf. Note that all sections of data collected for the study are not currently available and will be released in the future.

Background Nutrition and stimulation interventions may promote early childhood development, but little is known about the long-term benefits of such interventions, particularly in low- and middle-income countries. We now conducted a follow-up study on a cluster-randomized maternal education trial that was conducted when their children were 6–8 months old, to assess the sustainability of the developmental benefits eight years after the intervention. Methods and findings The intervention consisted of education in nutrition, hygiene, oral sanitation and child stimulation. In the current study, we assessed child processing and cognitive abilities using the Kaufman Assessment Battery for Children Second Edition (KABC-II) and attention and inhibitory control using the Test of Variables of Attention (TOVA). Using Stata version 17.0, t-tests and multi-level regression were employed to compare scores from KABC-II and TOVA tests in the two study groups adjusting for clustering effect. The data were analyzed by intention-to-treat. The original trial included 511 mother-child pairs (intervention n=263, control n=248), whereas in the current study, 361 (71%; intervention n=185, control n=176) pairs were available for analyses. The intervention group scored higher than the controls (all P-values<0.001) on all five KABC-II sub-scales, as well as on the KABC-II global score (mean difference: 14, 95% CI: 12–16; P<0.001). Furthermore, for all five TOVA variables, the intervention group scored higher than the controls in both the visual and auditory tasks (all P-values <0.05). The main limitation is that we were unable to determine the exact individual contribution of each component (nutrition, hygiene and stimulation) of the intervention to the developmental benefits since they were all delivered as a combined package. Conclusions The intervention group consistently scored markedly higher on both psychometric tests. Thus, even eight years after the original maternal education intervention, the developmental benefits that we observed at child age of one, two and three years, were sustained. Methods The data was collected through field-work where we approached the study participants in their home communitites. We then cleaned the data, analyzed them statistically and finally interpretated the findings. More details can be found in the Method-section of the paper.

Kenya KE: Adjusted Net Enrollment Rate: Primary: Male: % of Primary School Age Children data was reported at 81.322 % in 2012. This records an increase from the previous number of 78.311 % for 2009. Kenya KE: Adjusted Net Enrollment Rate: Primary: Male: % of Primary School Age Children data is updated yearly, averaging 71.127 % from Dec 1999 (Median) to 2012, with 12 observations. The data reached an all-time high of 81.322 % in 2012 and a record low of 60.926 % in 2002. Kenya KE: Adjusted Net Enrollment Rate: Primary: Male: % of Primary School Age Children data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Education Statistics. Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

UNICEF's country profile for Kenya, including under-five mortality rates, child health, education and sanitation data.

Enrolment in tertiary education, ISCED 8 programmes, female (number) in Kenya was reported at 4348 Persons in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Enrolment in tertiary education, ISCED 8 programmes, female - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Objective(s)Using nationally representative surveys conducted in Kenya, this study examined optimal health promoting childcare practices in 2003, 2008–9 and 2014. This was undertaken in the context of continuous child health promotion activities conducted by government and non-government organizations throughout Kenya. It was the aim of such activities to increase the prevalence of health promoting childcare practices; to what extent have there been changes in optimal childcare practices in Kenya during the 11-year period under study?MethodsCross-sectional data were obtained from the Kenya Demographic and Health Surveys conducted in 2003, 2008–9 and 2014. Women 15–49 years old with children 0–59 months were interviewed about a range of childcare practices. Logistic regression analysis was used to examine changes in, and correlates of, optimal childcare practices using the 2003, 2008–9 and 2014 data. Samples of 5949, 6079 and 20964 women interviewed in 2003, 2008–9 and 2014 respectively were used in the analysis.ResultsBetween 2003 and 2014, there were increases in all health facility-based childcare practices with major increases observed in seeking medical treatment for diarrhoea and complete child vaccination. Mixed results were observed in home-based care where increases were noted in the use of insecticide treated bed nets, sanitary stool disposal and use of oral rehydration solutions, while decreases were observed in the prevalence of urging more fluid/food during diarrhoea and consumption of a minimum acceptable diet. Logit models showed that area of residence (region), household wealth, maternal education, parity, mother's age, child’s age and pregnancy history were significant determinants of optimal childcare practices across the three surveys.ConclusionsThe study observed variation in the uptake of the recommended optimal childcare practices in Kenya. National, regional and local child health promotion activities, coupled with changes in society and in living conditions between 2003 and 2014, could have influenced uptake of certain recommended childcare practices in Kenya. Decreases in the prevalence of children who were offered same/more fluid/food when they had diarrhea and children who consumed the minimum acceptable diet is alarming and perhaps a red flag to stakeholders who may have focused more on health facility-based care at the expense of home-based care. Concerted efforts are needed to address the consistent inequities in the uptake of the recommended childcare practices. Such efforts should be cognizant of the underlying factors that affect childcare in Kenya, herein defined as region, household wealth, maternal education, parity, mother's age, child’s age and pregnancy history.

Primary education, duration (years) in Kenya was reported at 6 years in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Primary education, duration (years) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Actual value and historical data chart for Kenya Share Of Youth Not In Education Employment Or Training Total Percent Of Youth Population

School age population, primary education, both sexes (number) in Kenya was reported at 8318181 Persons in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Population of the official age for primary education, both sexes - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

The data consists of semi-structured interviews with teachers and principals in 4 schools in Kenya, including students with disabilities in mainstream classrooms is considered an important factor in meeting the needs and ensuring the rights of students with disabilities. In 2009 Kenya passed The National Special Needs Education Policy Framework which, while it made the inclusion of students with disabilities a formal policy, the strategies for inclusion remain unresolved. This study was conducted in two phases; the first used a Western methodology (Universal Design for Learning) and the second an Indigenous Gīkūyū methodology. Eight teachers and four principals were interviewed and eight classrooms were observed in four schools in Kenya to identify the inclusive strategies employed by the teachers. Results were analysed using thematic analysis. The findings of the study showed ways in which Kenyan teachers used Gīkūyū Indigenous strategies, drawn from Gīkūyū knowledges, to support students in inclusive classrooms. The study also highlighted the importance of revitalising Gīkūyū knowledges, values and practices in schools. The research adds to the scholarship on the place of Indigenous knowledges, values and practices in schools to support students with and without disabilities, and the place of family relationships and family-school partnerships among the Gīkūyū in inclusive education. This study has the potential to inform educational policy and practice in Kenya specifically and in Africa generally. It has created the space for the voices of Gīkūyū teachers and principals to be heard in their pursuit to preserve Gīkūyū knowledges that have for centuries supported the care and education of children with disabilities through strong family and group relationships.