IntroductionThe Nurturing Care Framework (NCF) describes “nurturing care” as the ability of nations and communities to support caregivers and provide an environment that ensures children's good health and nutrition, protects them from threats, and provides opportunities for early learning through responsive and emotionally supportive interaction. We assessed the extent to which Kenyan government policies address the components of the NCF and explored policy/decision makers' views on policy gaps and emerging issues.MethodsA search strategy was formulated to identify policy documents focusing on early childhood development (ECD), health and nutrition, responsive caregiving, opportunities for early learning and security and safety, which are key components of the NCF. We limited the search to policy documents published since 2010 when the Kenya constitution was promulgated and ECD functions devolved to county governments. Policy/decision-maker interviews were also conducted to clarify emerging gaps from policy data. Data was extracted, coded and analyzed based on the components of the NCF. Framework analysis was used for interview data with NCF being the main framework of analysis. The Jaccard's similarity coefficient was used to assess similarities between the themes being compared to further understand the challenges, successes and future plans of policy and implementation under each of the NCF domains.Results127 policy documents were retrieved from government e-repository and county websites. Of these, n = 91 were assessed against the inclusion criteria, and n = 66 were included in final analysis. The 66 documents included 47 County Integrated Development Plans (CIDPs) and 19 national policy documents. Twenty policy/decision-maker interviews were conducted. Analysis of both policy and interview data reveal that, while areas of health and nutrition have been considered in policies and county level plans (coefficients >0.5), the domains of early learning, responsive caregiving and safety and security face significant policy and implementation gaps (coefficients ≤ 0.5), particularly for the 0–3 year age group. Inconsistencies were noted between county level implementation plans and national policies in areas such as support for children with disabilities and allocation of budget to early learning and nutrition domains.ConclusionFindings indicate a strong focus on nutrition and health with limited coverage of responsive caregiving and opportunities for early learning domains. Therefore, if nurturing care goals are to be achieved in Kenya, policies are needed to support current gaps identified with urgent need for policies of minimum standards that provide support for improvements across all Nurturing Care Framework domains.

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.

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.

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

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]

Kenya KE: Trained Teachers in Primary Education: % of Total Teachers data was reported at 96.807 % in 2009. This records a decrease from the previous number of 98.416 % for 2008. Kenya KE: Trained Teachers in Primary Education: % of Total Teachers data is updated yearly, averaging 98.696 % from Dec 2003 (Median) to 2009, with 7 observations. The data reached an all-time high of 99.435 % in 2006 and a record low of 96.807 % in 2009. Kenya KE: Trained Teachers in Primary Education: % of Total Teachers 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: Education Statistics. Trained teachers in primary education are the percentage of primary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.; ; 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).

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).

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 September of 2025.

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.

Share of youth not in education, employment or training, total (% of youth population) in Kenya was reported at 27.78 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Share of youth not in education, employment or training, total - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

The 2022 Kenya Demographic and Health Survey (2022 KDHS) was implemented by the Kenya National Bureau of Statistics (KNBS) in collaboration with the Ministry of Health (MoH) and other
stakeholders. The survey is the 7th KDHS implemented in the country.

The primary objective of the 2022 KDHS is to provide up-to-date estimates of basic sociodemographic, nutrition and health indicators. Specifically, the 2022 KDHS collected information on:
• Fertility levels and contraceptive prevalence
• Childhood mortality
• Maternal and child health
• Early Childhood Development Index (ECDI)
• Anthropometric measures for children, women, and men
• Children’s nutrition
• Woman’s dietary diversity
• Knowledge and behaviour related to the transmission of HIV and other sexually transmitted diseases
• Noncommunicable diseases and other health issues
• Extent and pattern of gender-based violence
• Female genital mutilation.

The information collected in the 2022 KDHS will assist policymakers and programme managers in monitoring, evaluating, and designing programmes and strategies for improving the health of Kenya’s population. The 2022 KDHS also provides indicators relevant to monitoring the Sustainable Development Goals (SDGs) for Kenya, as well as indicators relevant for monitoring national and subnational development agendas such as the Kenya Vision 2030, Medium Term Plans (MTPs), and County Integrated Development Plans (CIDPs).

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 September of 2025.

Enrolment in tertiary education, ISCED 8 programmes, both sexes (number) in Kenya was reported at 10215 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, both sexes - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

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

Abstract

This was a prospective population based study comparing education outcomes and education services among slum and non-slum settlements in Nairobi. The study was being conducted in two slum settlements of Korogocho and Viwandani, and two non-slum settlements of Jericho and Harambee. Korogocho is situated within Korogocho administrative location, Viwandani in Viwandani administrative location, and Jericho and Harambee in Makadara administrative location. The study identified households who had children aged between 5 and 19 years old and living within the boundaries of the study sites. The households were followed untl 2010. New households fitting the inclusion criteria were enrolled each year, while the upper age limit increased by a single year for each additional year. By 2010, the study wa following about 16400 individuals aged bewteen 5 and 24 years. The study targetted also schools where the idenfied pupils attended. Several questionnaires were administered and included schooling history to capture schooling information for the current schooling years and 5 years backwards. Afterwards, an update questionnaire was introduced to capture prospective schooling information. The second questionnaire captured information from the parents on their perceptions towards free primary education and support for their children schooling. In addition, individuals who were 12 years and above responded to a behvaior questionnaires. In the schools, a school characteristics questionniare was administred.

The objectives of the ERP I were:

· What is the impact of free primary education on school enrolment patterns and dropout rates among urban slum and non-slum children?

· What factors are associated with school participation (enrolment, attendance, repetition, performance and dropout) among urban slum and non-slum children?

· What are the (causal) linkages between school participation and the onset and extent of indulgence in risky behaviors in children?

Geographic coverage

Two slums of Nairobi (Korogocho and Viwandani) and two non-slums of Nairobi (Harambee and Jericho)

Analysis unit

1. HOUSEHOLDS

2. INDIVIDUALS WITHIN THE AGE OF STUDY. AVERAGE OF 2.7 INDIVIDIDUALS PER HOUSEHOLD

3. SCHOOLS

Universe

The data covers individuals aged 5 and 19 years in 2005 who were by 2010 aged between 5 and 24 years. It also covered primary schools within Nairobi, where majority of the pupils were reported to be enrolled.

Sampling procedure

Selection of study sites

Using the Kenya 1999 housing and population census, and the 1997 Welfare Monitoring Survey III collected by the Central Bureau of Statistics (Government of Kenya 2000), all the 49 locations of Nairobi were ranked into five groups according to the percentage of the population below the poverty line. NUHDSS slum locations of both Viwandani and Korogocho were in the poorest percentile (ranked 48th and 44th, respectively). Those in the richest quintile were excluded because most children in the wealthy communities go to formal private schools which are scattered all over the city. The majority of the locations in the 4th quintile have a mixture of formal and informal settlement features. In order to have a formal residential area in the middle income category where most children are likely to go to public schools, three locations were explored in the second quintile (i.e. the second richest set of locations). During discussion of the project's design, participants, who were mainly Kenyans with comprehensive knowledge of the areas, recommended carrying out the study in Bahati, as opposed to Umoja or Kariokor, the other locations in the second quintile. APHRC researchers visited the three communities to assess their suitability as a comparison site for the project. Bahati (Harambee and Jericho) was chosen because it is relatively stable, is mostly inhabited by middle-income parents with school-going children who mostly go to public schools in the area. In Bahati, 26% of the population lived below the poverty line while in Korogocho and Viwandani, the corresponding percentages were 60% and 76%, respectively. Having Bahati as the comparison area was therefore to enable the study to assess factors affecting schooling among some relatively poor households that did not reside in slum settlements.

Sampling of households

All households included in the NUHDSS database and with individuals aged between 5 and 19 years in 2005 were included in the study. thereafter they were followed until 2010. In between those who entered into the system or reach the aged of 5 years were also included and followed prospectively.

Sampling of schools

Schools were the pupils under serveillance were reported to be enrolled formed part of the sampling frame for schools. The inclusion criteria for the schools survey was that the school should be located within Nairobi and that it should have a minimum of five pupils in oyr household survey enrolled in it.

Mode of data collection

Face-to-face [f2f]; FGD

Research instrument

The Questionnaires

The questionnaires hereafter are referred to as modules. There are several modules since the beginning of the education project:

1) Household module

2) Primary school module

3) Parent guardian module

4) Education child update (schooling history) module

5) Child school status update questionnaire

6) Education child update module

7) Primary school questionnaire

8) Child Behavior Questionnaire

9) Supplementary primary school module

The household module

The household module served as a starting point of the interview. It identified the respondent's household. The module was administered to the owner of the household or any other adult who was credible and who usually lives in the household. It served to identify individual households and its occupants and thus served as a basis for the other modules to be administered. It contains a complete list of the household members and some basic information on age, sex, parental survivorship, education, and labor force participation.

For each of the household, information on water source and trash disposal methods, type of toilet facility used by the household, materials for the house (roof, floor, and walls), fuel for lighting and cooking, and ownership of assets was collected.

The Primary schools module:

This module serves to generate indicators on schooling participation. The module is meant for headmasters or teachers knowledgeable enough to provide information on the school. It comprises of the following sections:

Background

This serves to identify the name of the school, the date and time of the interview and the location of the school.

Particulars of respondent

This section of the module collected information on the respondent and establishes the respondent's full names, position held by respondent in the school and how long the respondent has been working in the school.

School background

This section sets to establish whether the school is registered, if registered under which ministry the school is registered(ministry of culture or ministry of education), its registration number, the type of curriculum followed by the school and the management of the school. The understanding is that the name of the school being used maybe different from the one under which the school is registered. The information is important especially if we are to link the school to the Ministry of Education or Ministry of Culture records. This information will most probably be obtained from the school records (if they exist).

School facilities

This section sets to collect information on the school facilities, such as textbooks provided by the school to the pupils in each grade they include Mathematics, Science ,Kiswahili and English, a library, science lab for pupils use ,a playground for outdoor sports pupils use and inventory of all school's equipment e.g. desks. For purposes of this project, a library is considered to be a room which has reference books where pupils can go to read.

This section also offers information on the school ownership of a toilet facility for use by the pupils and whether there are separate toilets provided for boys and girls. It also offers information on the school's water source and the availability of electricity in the school.

In addition the module in this section probes the respondent on whether the inspector of schools has visited the school in the current schooling year and requests for the date and year of visit. The inspector of school is from the City Council education department or from the Ministry of Education.

Enrollment for the current school year

Enrollment refers to children who are current registered for specific grades/classes in the school.

The objective of this section is to provide information on the number of boys and girls in each of the streams in the school in the current school year. It also sets to establish whether there were any pupils who were turned away during enrollment in the current year and the approximate number of pupils who were turned away from enrolling in the school.

Expenditure on schooling

The module here asks questions on the school fee structure, it seeks to establish whether the pupils are required to pay fees and how much (Kenya shillings) they pay for the following: tuition, construction fund, Parents Teachers Association (PTA), extra classes, examination fees, school meals and other items.

This was required to be filled for all grades in the school and whether paid annually, termly, monthly and weekly.

It also provides information on whether the pupils are required to wear uniform in order to be allowed in class and the source of purchase of the

Secondary 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 - Secondary education, duration (years) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

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.

Share of youth not in education, employment or training, male (% of male youth population) in Kenya was reported at 22.67 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Share of youth not in education, employment or training, male - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

Public spending on education as a share of GDP of Kenya dropped by 12.16% from 4.5 % in 2022 to 4.0 % in 2023. Since the 0.97% upward trend in 2019, public spending on education as a share of GDP plummeted by 26.26% in 2023. Public expenditure on education as % of GDP is the total public expenditure (current and capital) on education expressed as a percentage of the Gross Domestic Product (GDP) in a given year. Public expenditure on education includes government spending on educational institutions (both public and private), education administration, and transfers/subsidies for private entities (students/households and other privates entities).