Modelling Unequal Progress in Reproductive, Maternal, and Newborn Health Coverage, Using Fractional Logit Generalised Estimating Equations (GEE) Analysis

Francis Ayiah-Mensah *

Department of Mathematics, Statistics and Actuarial Science, Takoradi Technical University, Takoradi, Ghana.

Felix Ilesanmi Alao

Department of Mathematical Sciences, Federal University of Technology, Ondo State, Nigeria.

Senyefia Bosson-Amedenu

Department of Mathematics, Statistics and Actuarial Science, Takoradi Technical University, Takoradi, Ghana.

Francis Eyiah Bediako

Department of Statistics, University of Cape Coast, Cape Coast, Ghana.

Mohammed Frempong

Department of Mathematics, Statistics and Actuarial Science, Takoradi Technical University, Takoradi, Ghana.

*Author to whom correspondence should be addressed.


Abstract

Background: Universal health is advancing; however, information regarding the distribution of regional expansion in reproductive, maternal, and newborn health services across population groups remains limited.

Aims: This study compared the levels of various coverage indicators at the regional level and across socioeconomic groups at baseline (2013) and follow-up (2023).

Methods: The analysis used population-averaged fractional-logit generalised estimating equations (GEE) with robust sandwich standard errors. Year-by-indicator and year-by-stratum interactions were used to test for heterogeneity, and average marginal effects were used to estimate year-to-year percentage-point differences.

Results: Mean coverage increased from 58.22% in 2013 to 70.08% in 2023, and observations below 80% declined from 73.68% to 58.35%. Birth before age 18 was the only category with an adjusted decrease, declining by 2.93 percentage points (95% CI: −3.91 to −1.95), while the largest adjusted increase was observed for newborn postnatal care (38.37 percentage points; 95% CI: 37.23–39.51). Although there was partial convergence across population groups, increases in the second wealth quintile (15.46 points), poorest quintile (14.84 points), and rural populations (13.07 points) were greater than the increase in urban populations (7.75 points).

Conclusions: Coverage increased significantly, but not equally. Aggregate-level monitoring is complemented by monitoring at the individual-stratum level, with an equity focus, given the persistent monitoring gaps among poorer, rural, and adolescent strata.

Keywords: Reproductive health, maternal health, newborn health, health inequalities, service coverage, socioeconomic inequality, fractional logit, average marginal effects, universal health coverage


How to Cite

Ayiah-Mensah, Francis, Felix Ilesanmi Alao, Senyefia Bosson-Amedenu, Francis Eyiah Bediako, and Mohammed Frempong. 2026. “Modelling Unequal Progress in Reproductive, Maternal, and Newborn Health Coverage, Using Fractional Logit Generalised Estimating Equations (GEE) Analysis”. Asian Journal of Pregnancy and Childbirth 9 (1):477-94. https://doi.org/10.9734/ajpcb/2026/v9i1225.

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