Geographic inequities in neonatal survival in Nigeria: a cross-sectional evidence from spatial and artificial neural network analyses.

Abstract

This study was conducted to provide empirical evidence of geographical variations of neonatal mortality and its associated social determinants with a view to improving neonatal survival at the subnational level in Nigeria. With a combination of spatial analysis and artificial intelligence techniques, this study analysed data from the 2016/2017 Nigeria Multiple Indicator Cluster Survey. The analysis focused on the neonatal period of a weighted national representative population of 30,924 live births delivered five years before the survey commencement. Global Moran's I index and local indicator of spatial autocorrelation cluster maps were used to determine hot and cold spots. A multilayer perceptron neural network was used to identify the key determinants of neonatal mortality across the states and geopolitical zones in Nigeria. The overall neonatal mortality rate was 38 deaths per 1000 live births. There is evidence of geographic clustering of neonatal mortality across Nigeria (worse in the North-Central and North-West zones), majorly driven by poor maternal access to mass media (which plays a critical role in promoting positive health behaviours), short birth interval, a higher position in a family birth order, and young maternal age at child's birth. This study highlights the need for a policy shift towards implementing state and region-specific strategies in Nigeria. Gender-responsive, culturally, and regionally appropriate reproductive, maternal, and child health-targeted interventions may address geographical inequity in neonatal survival.