Current Trends in Child Mortality in India: A Spatial, Survival and Regression Analysis

To investigate the multi-dimensional determinants of child mortality in India, focusing on subnational burden, socioeconomic inequalities, maternal care, and environmental factors.

Age-specific mortality indicators were estimated at the state and district levels using normalised survey weights. Under-Five Mortality (U5M) determinants were evaluated using Logistic Regression (LR) and the Cox Proportional Hazard (CPH) model, incorporating the complex survey design to characterise mortality risk over time.

The highest mortality burden is concentrated in socioeconomically deprived regions. Maternal age, education, higher birth order, low birth weight or size, place of delivery, and multiple births were crucially associated with higher mortality. The Survival and Regression (SAR) model findings demonstrate that maternal healthcare utilisation, continuity of antenatal and intrapartum care, early postnatal practices, and overall socio-demographic factors remained as independent predictors.

Enhancing maternal and neonatal care, accessible and quality healthcare, improving household conditions, and prioritising high-burden and high-risk states and districts are crucial to achieve Sustainable Development Goal (SDG 3.2). This analysis provides a robust and scalable analytical framework for determining child mortality disparities. It provides evidence-based recommendations for precisely targeted interventions and policy implications to reduce child mortality.