Caesarean Delivery Use in Ethiopia: A Spatial and Hierarchical Bayesian Analysis

Abstract Background: Access to emergency obstetric care (EmOC) is very important for reducing maternal mortality. A geographically linked data analysis using population and health facility data is potentially valuable to map caesarean delivery use, and to identify inequalities in service access and provision. Thus, this study aimed to assess the spatial patterns of caesarean delivery use, and to identify associated factors among pregnant women in Ethiopia. Method: A secondary data analysis of the 2016 Ethiopia Demographic and Health Survey linked with the 2014 Ethiopian Service Provision Assessment was conducted. A hierarchical Bayesian analysis was carried out using the SAS MCMC procedure. A spatial analysis was performed to identify the hot spot areas of caesarean delivery use with ArcGIS. Results: Women who had four or more ANC visits were 4.077 (95% Credible Interval (CrI): 1.909, 8.179) times more likely to use caesarean delivery compared to those who had no ANC visits. Pregnant women living in rural areas were 60% less likely to deliver via caesarean section. About 50% of the variability in the rate of caesarean delivery was accounted for by location. The spatial analysis found that Addis Ababa, Dire Dawa and the Harari region had clusters of high caesarean delivery rates. Conclusion: There were significant variations in the use of caesarean delivery services across the different regions of Ethiopia. The findings have important policy implications. The Ethiopian government has to increase the distribution of EmOC facilities and/or to establish a faster transportation system to allow pregnant women to reach EmOC facilities when caesarean delivery is indicated.