Bayesian Multilevel Analysis of Postnatal Care Utilization in Ethiopia

Abstract

The postnatal period is defined as the first six weeks after birth; it is critical to the health and survival. The study was conducted to determine the key factors of maternal postnatal care using Bayesian multilevel analysis using 7,192 mothers aged between 15-49 of EDHS 2016 data. Descriptive statistics revealed that 675 (9.4%) women received postnatal care. The Bayesian multilevel model used to analyze postnatal care utilization of woman. The predictor variables like mother's age, region, place of residence, media exposure, religion, wealth index, parents' education level, and mothers' occupation were found to be significant determinants of variation in women postnatal care utilization in Ethiopia. The Bayesian multilevel logistic regression analysis also estimates the variance of random effect at the regional level. Thus, the value of var (u0j) = δ2= 0.127 is significant at the 5% level of significance. In order to convey policies, it is important not only to comprehend the effect of reforms on the issues, but also on the how it diverges with demographic and economic characteristics.