Comparison of Bayesian and Classical Methods for Exploring the Important Factors regarding Maternal and Child Health Care

Abstract

The literature contains a number of studies to analyze the important factors relating to maternal and child health care (MCH). However, the earlier contributions have employed classical models for the analysis. We have proposed Bayesian models for exploring the factors regarding MCH in Pakistan. The latest data, from Pakistan Demographic and Heath Survey (PDHS) conducted in 2017-18, have been used for analysis. The performance of Bayesian methods have been compared with classical methods based on various goodness-of-fit criteria. The performance of Bayesian methods was observed to be better than the classical methods. The results advocated that 86.20% of mothers received antenatal care (ANC), while only 51.40% of the mothers received it at least for ANC visits during the whole pregnancy period. Further, 68.90% of the mothers were protected against neonatal tetanus. More than 30% of women neither delivered in the health facility place nor they were in receipt of postnatal checkups. Additionally, only three out of five newborns were availed with postnatal checkup (PNC) within two days of their births. About 66.89% of women reported problems in accessing the MCH in the country. The study also suggested the presence of severe disparities among different socio-economic groups in availing MCH. There is immediate need to reduce these disparities among various socio-economic groups in the country.