Clustering of home delivery in Bangladesh and its predictors: evidence from the linked household and health facility level survey data

Abstract

AbstractBackgroundAround half of births in Bangladesh occur at home without skilled birth personnel. This study aims to identify the geographical hot spots and cold spots of home delivery in Bangladesh and associated factors.MethodsWe analyzed data from the 2017/2018 Bangladesh Demographic and Health Survey and the 2017 Bangladesh Health Facility Survey. The outcome variable was home delivery without skilled personnel supervision (yes, no). Explanatory variables included individual, household, community, and healthcare facility factors. Moran’s I was used to determine hot spots and cold spots of home delivery. Geographically weighted regression models were used to identify cluster-specific predictors of home delivery.ResultsThe prevalence of non-supervised and unskilled supervised home delivery was 53.18%. Hot spots of non-supervised and unskilled supervised home delivery were primarily in Dhaka, Khulna, Rajshahi, and Rangpur divisions. Cold spots of home delivery were mainly in Mymensingh and Sylhet divisions. Predictors of higher home births in hot spot areas included women’s illiteracy, lack of formal job engagement, higher number of children ever born, partner’s agriculture occupation, higher community-level illiteracy, and greater distance to the nearest healthcare facility from women’s homes.ConclusionsUnskilled supervised home delivery is prevalent in Bangladesh, and the distance between women’s homes and healthcare facilities plays a significant role. Awareness-building programs should emphasize the importance of skilled and supervised hospital deliveries, particularly among the poor and disadvantaged groups.