AI Insight
This study analyzed 34 years of maternal healthcare data from Ghana (1988-2022) and found that while access to skilled antenatal care (ANC) increased nationally from 83.1% to 97.7% and regional inequality declined by 87.9%, significant fertility-related disparities persist. The Northern Belt regions continue to lag behind urban areas like Greater Accra in care efficiency, with machine learning models identifying that regions with total fertility rates above 5.90 historically showed declining ANC coverage. A novel Care Efficiency Index revealed that despite convergence in basic ANC access, the ratio of care to fertility needs remains substantially lower in rural northern regions.
Why it matters
The findings highlight that improving raw healthcare access alone does not eliminate health inequities when fertility patterns differ regionally. The Care Efficiency Index and identified fertility thresholds provide data-driven tools for policymakers to target maternal health investments toward areas where population needs outpace healthcare capacity.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
This study focuses on the relationship between access to Advanced Neonatal Care (ANC) and fertility across the regions in Ghana between 1988 and 2022. It builds on previous studies focused on inequity in maternal health across subnational levels and incorporates spatial analytics, machine learning, and a welfare-adjusted fertility care metric. Nine waves of the Ghana Demographic and Health Survey (DHS) were analyzed, with 94 region-by-year units across 8 to 16 regions in each survey wave in the 16 Ghana administrative regions. Skilled ANC along with the Total Fertility Rate (TFR) and demographic control variables were extracted for the analysis. The methodologies employed include decomposition of the Gini coefficient of inequality, bivariate z-score risk stratification, Random Forest (RF), and Decision Tree (DT) regression, partial dependence, Local Indicators of Spatial Association (LISA), global Moran’s I with permutation inference and a novel Care Efficiency Index (CEI = ANC% / TFR). Care for the outcomes employed region aggregations along with district boundary geometries for the display of the choropleth maps. National skilled ANC coverage increased from 83.1% (1988) to 97.7% (2022), with inter-regional Gini declining 87.9% (0.070 to 0.008). The North-South gap narrowed from 32.4 to 0.9 percentage points. Northern region showed the greatest absolute gain (+43.0pp). Machine learning identified an exploratory RF partial-dependence inflection near TFR=5.90, above which predicted ANC coverage declined in the historical data. Survey year was the dominant RF predictor (43.7%), followed by TFR (38.8%). TFR spatial clustering intensified by 2022 (Moran’s I=0.606, p=0.001). Greater Accra led the Care Efficiency Index (CEI=31.9); Northern Belt regions lagged (CEI=14.5-16.5). Risk stratification classified 23 observations as Critical (Low ANC/High TFR), predominantly from Northern Belt regions in earlier survey waves. ANC coverage converged substantially, yet fertility-related spatial inequities persisted, especially in the Northern Belt. The Care Efficiency Index and exploratory TFR inflection provide hypothesis-generating tools for targeting health-system investment. They should not be interpreted as causal thresholds.