Unveiling hidden heterogeneity and inequalities in the continuum of care for reproductive, maternal, and child health services in sub-Saharan Africa: A multilevel latent class analysis approach.

Improving reproductive, maternal, newborn, and child health (RMNCH) services is vital for achieving the Sustainable Development Goals (SDGs) for maternal and child survival. This study utilized multilevel latent class analysis (MLCA) on Demographic and Health Surveys (DHS) data from 29 sub-Saharan African (sSA) countries to identify RMNCH service utilization patterns, examine covariate effects, and assess coverage inequalities. Secondary data from the most recent DHS conducted in 29 sSA countries from 2015 to 2024 were used. MLCA was performed on 12 RMNCH service indicators to account for the hierarchical structure of the data. Summary inequality indicators were used to assess differences in posterior class membership for lower-level classes across wealth quintiles, maternal education, maternal occupation, and place of residence. Women's RMNCH service utilization was divided into two categories: optimal and suboptimal users, and two higher-level categories: high and low coverage. Higher maternal education, household wealth, media access, and early antenatal care were related to a higher likelihood of being in the optimal utilizer class. In contrast, rural location and a longer distance to health services were associated with a lower likelihood. Inequality indices revealed significant differences among optimal utilizers, particularly in terms of mother education and household wealth. Targeted interventions are urgently required to promote RMNCH service utilization in sSA by addressing persistent socioeconomic disparities, particularly among women with no education, lower incomes, and low access to health care.