Peer-reviewed article
Geographic inequalities, and social-demographic determinants of reproductive, maternal and child health at sub-national levels in Kenya
Janette Karimi, Anitah Cherono, Victor A. Alegana, Martin Kavao Mutua, Hellen Kiarie et al. ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study analyzed routine health data from Kenya's 47 counties between 2018 and 2021 to map geographic inequalities in reproductive, maternal and child health services. Using statistical modeling, researchers found that north-eastern, eastern and coastal regions had the poorest performance, with full immunization coverage at 79.3% and facility maternal mortality ratio at 105.4 per 100,000 live births. Health facility density, maternal education, and wealth were identified as key factors affecting service coverage and outcomes across regions.
Key points
- Full immunization coverage at 1 year was highest at 79.3% (77.8-80.5%), while family planning commodities for women of reproductive age was lowest at 38.6% (38.2-38.9%)
- North-eastern, eastern and coastal regions had the lowest overall reproductive, maternal and child health index due to low service coverage and high facility maternal mortality
- Facility maternal mortality ratio was estimated at 105.4 per 100,000 live births (67.3-177.1)
- Health facility density was an important determinant across all five indicators studied
- Maternal education was positively correlated with immunization coverage, while wealthier sub-counties paradoxically had higher maternal mortality ratios
Limitations
This is an observational analysis of routine administrative data that shows associations, not causal relationships. The study cannot explain why certain determinants (such as wealth being associated with higher maternal mortality) show unexpected directions, or identify specific interventions to address inequalities.
Abstract
BACKGROUND: Global initiatives have emphasized tracking indicators to monitor progress, particularly in countries with the highest maternal and child mortality. Routine data can be used to monitor indicators for improved target setting at national and subnational levels. Our objective was to assess the geographic inequalities in estimates of reproductive, maternal and child health indicators from routine data at the subnational level in Kenya. METHODS: Monthly data from 47 counties clustered in 8 regions, from January 2018 to December 2021 were assembled from the District Health Information Software version 2 (DHIS2) in Kenya. This included women of reproductive age receiving family planning commodities, pregnant women completing four antenatal care visits, deliveries conducted by skilled birth attendants, fully immunized children at 1 year and number of maternal deaths at health facilities, from which five indicators were constructed with denominators. A hierarchical Bayesian model was used to generate estimates of the five indicators at the at sub-national levels(counties and sub counties), adjusting for four determinants of health. A reproductive, maternal, and child health (RMCH) index was generated from the 5 indicators to compare overall performance across the continuum of care in reproductive, maternal and child health across the different counties. RESULTS: The DHIS2 data quality for the selected 5 indicators was acceptable with detection of less than 3% outliers for the Facility Maternal Mortality Ratio (FMMR) and less than 1% for the other indicators. Overall, counties in the north-eastern, eastern and coastal regions had the lowest RMCH index due to low service coverage and high FMMR. Full immunization coverage at 1 year (FIC) had the highest estimate (79.3%, BCI: 77.8-80.5%), while Women of Reproductive age receiving FP commodities had the lowest estimate (38.6%, BCI: 38.2-38.9%). FMMR was estimated at 105.4, (BCI 67.3-177.1)Health facility density was an important determinant in estimating all five indicators. Maternal education was positively correlated with higher FIC coverage, while wealthier sub counties had higher FMMR. CONCLUSIONS: Tracking of RMCH indicators revealed geographical inequalities at the County and subcounty level, often masked by national-level estimates. These findings underscore the value of routine monitoring indicators as a potential for evidence-based sub-national planning and precision targeting of interventions to marginalized populations.