Abstract
Introduction There are 47 semi-autonomous counties in Kenya that are in-charge of financing and delivery of healthcare. Although reports exist that demonstrate how the counties differ in socioeconomic status, disease burden, and health outcomes, such reports often fail to show where the greatest inequities lie, and what actually drives them. This analysis is meant to guide better targeting of resources to achieve a greater impact on maternal and child health outcomes. Methods Secondary data sources were analyzed to determine the variations in inequities in Kenyan counties. The inequities and their distribution in the 47 counties were assessed using a Lorenz curve and principal component analysis (PCA). A regression analysis evaluated the relationship between key outcomes- maternal mortality, under-five mortality, full immunization coverage (DPT3), the incidence of diarrhea, and under-five stunting, as the dependent variables, and years of education for women 15 – 49 years, county health financing per capita, public insurance coverage, population per facility, public nurses/100000, doctors/100000 people, poverty headcount rate, and gender inequality index (GII), as the independent variables. Findings Vaccine coverage (Gini Index 0.063) is the most equitably distributed outcome in the country, followed by under-five mortality (GI=0.124). Maternal mortality has the highest inequity (GI=0.381), followed by the distribution of public sector nurses (GI=0.317). County government funding of health per capita also shows wide variations between counties (GI= 0.230) suggesting different levels of expenditure and prioritization. Vaccine coverage and U-5 mortality are the most evenly distributed across the counties. The key drivers of maternal mortality are education of women of reproductive age (p= 0.001), gender inequality (p=0.002), and congestion at health facilities (0.001). Conclusion Promising approaches and interventions to reduce inequity do exist, which includes UHC whose focus should be on reducing geographical, economic, sociocultural, and gender barriers to healthcare.
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