Catchment-Level Spatial Inequities in Antenatal Care Utilization and Malaria Prevention in Akwa Ibom State, Nigeria.

Equitable maternal health and malaria prevention coverage depends on aligning service delivery with spatially heterogeneous population demand. In Nigeria, routine health indicators are rarely evaluated within fine-scale spatial frameworks that account for demographic pressure and open catchment dynamics. This study examines spatial inequities in antenatal care (ANC) utilization and malaria prevention among pregnant women in Akwa Ibom State using a catchment-based GIS approach. Health-facility catchment polygons (n = 654) were used as the primary analytical unit. First antenatal care attendance (ANC1_2025) were obtained from the national DHIS2 platform. Population denominators, including total population, women aged 15–45 years, and children aged 0–12 months were derived from WorldPop and aggregated to catchments. Annual pregnancies and pregnancy stock for 2025 were estimated using a demographic reconstruction model adjusted for infant survival and pregnancy loss. Service utilization indicators were standardized against pregnancy burden and women-of-reproductive-age density. Demand-adjusted log-linear regression and spatial autocorrelation analyses (Global Moran’s I and Local Indicators of Spatial Association) were applied. Demographic demand was highly concentrated, with the top 10% of catchments accounting for 29.6% of estimated pregnancies and pregnancy stock. Catchment-level ANC utilization relative to pregnancy stock ranged from 0 to over 1,200 per 100 pregnant women, indicating pronounced spatial inequities and cross-boundary service use. The demand-adjusted model explained a meaningful share of spatial variation in ANC utilization (adjusted R² = 0.169). Spatial analysis revealed weak global autocorrelation in residuals (Moran’s I = 0.034, p = 0.064) but identified localized clusters of under-utilization. Maternal health and malaria prevention services in Akwa Ibom State exhibit strong fine-scale spatial inequities that are masked by aggregated statistics. Catchment-based, demand-adjusted spatial analysis provides actionable evidence for equity-oriented planning aligned with Sustainable Development Goals 3, 10, and 11.