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Spatial inequalities in quality antenatal care in India: a district-level analysis
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DOI：10.3389/fpubh.2026.1878310.png)
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Abstract
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The study examines the spatial distribution and determinants of quality antenatal care (Q-ANC) utilization across districts of India using data from the National Family Health Survey (NFHS-5; 2019–21). Q-ANC is operationalized as the receipt of at least five out of seven essential antenatal care components; capturing the adequacy of service content during pregnancy. District-level estimates were analyzed using spatial statistical techniques; including Global and Local Moran’s I; spatial regression models; and geographically weighted regression (GWR); to identify clustering patterns and spatial heterogeneity in determinants. The findings reveal substantial regional disparities in Q-ANC utilization; with higher coverage concentrated in southern India and lower levels in northern and northeastern districts. Significant positive spatial autocorrelation (Moran’s I ≈ 0.60; p < 0.001) indicates strong geographic clustering. Spatial regression results show that intended pregnancy; adverse pregnancy outcomes; mass media exposure; and utilization of public healthcare facilities are positively associated with Q-ANC; whereas higher parity and greater concentration of socially disadvantaged and minority populations are negatively associated. The GWR model demonstrates considerable spatial variation in these relationships; explaining up to 80% of the observed variation across districts. These findings highlight that the determinants of maternal healthcare utilization are not spatially uniform and are shaped by localized socio-demographic and health system factors. The study underscores the need for geographically targeted policy interventions to address persistent regional inequalities in maternal healthcare access and quality in India.
Keywords:
geographically weighted regression
spatial analysis
spatial error model
spatial lag model
maternal healthcare utilization
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