Equality in Maternal and Newborn Health: Modelling Geographic Disparities in Utilisation of Care in Five East African Countries

Abstract

Background: Geographic accessibility to health facilities represents a fundamental barrier to utilisation of maternal and newborn health (MNH) services, driving historically hidden spatial pockets of localized inequalities. Here, we examine utilisation of MNH care as an emergent property of accessibility, highlighting high-resolution spatial heterogeneity and sub-national inequalities in receiving care before, during, and after delivery throughout five East African countries.

Methods: We calculated a geographic inaccessibility score to the nearest health facility at 300 x 300 m using a dataset of 9,314 facilities throughout Burundi, Kenya, Rwanda, Tanzania and Uganda. Using Demographic and Health Surveys data, we utilised hierarchical mixed effects logistic regression to examine the odds of: 1) skilled birth attendance, 2) receiving 4+ antenatal care visits at time of delivery, and 3) receiving a postnatal health check-up within 48 hours of delivery. We applied model results onto the accessibility surface to visualise the probabilities of obtaining MNH care at both high-resolution and sub-national levels after adjusting for live births in 2015.

Results: Across all outcomes, decreasing wealth and education levels were associated with lower odds of obtaining MNH care. Increasing geographic inaccessibility scores were associated with the strongest effect in lowering odds of obtaining care observed across outcomes, with the widest disparities observed among skilled birth attendance. Specifically, for each increase in the inaccessibility score to the nearest health facility, the odds of having skilled birth attendance at delivery was reduced by over 75% (0.24; CI: 0.19-0.3), while the odds of receiving antenatal care decreased by nearly 25% (0.74; CI: 0.61-0.89) and 40% for obtaining postnatal care (0.58; CI: 0.45-0.75).

Conclusions: Overall, these results suggest decreasing accessibility to the nearest health facility significantly deterred utilisation of all maternal health care services. These results demonstrate how spatial approaches can inform policy efforts and promote evidence-based decision-making, and are particularly pertinent as the world shifts into the Sustainable Goals Development era, where sub-national applications will become increasingly useful in identifying and reducing persistent inequalities.

Fig 1. Mapping inaccessibility to the nearest health facility.

A) Impedance surface representing the difficulty in traversing a given 300 x 300 m cell. B) Health facility locations used as destinations. C) Accessibility surface generated via cost-distance analysis using inputs A) and B), representing the least accumulative geographic “cost” value for a 300 x 300 m cell in accessing the nearest health facility.

Fig 2. Hierarchical covariates included in the mixed-effects logistic regression analysis.

Covariates are listed in boxes with corresponding hierarchy and fixed versus random effect #.

Fig 3. Boxplots of modelled probabilities of skilled birth attendance (SBA), antenatal care (ANC), and postnatal care (PNC).

Fig 4. Births adjusted probability maps representing the probability of obtaining MNH care for a given birth at the administrative II unit.

a) Delivery with a skilled birth attendant (SBA) present, b) Four or more antenatal care (ANC) visits at time of delivery, and c) Postnatal care (PNC) received within 48 hours of delivery.