Bayesian multilevel model application on determinants of perinatal mortality in Ethiopia using 2011 and 2016 EDHS data

  • Berhanu Bekele Debelu Wolkite University, Department of Statistics, Wolkite, Ethiopia
  • Denekew Bitew Belay Bahir Dar University, Department of Statistics, Bahir Dar, Ethiopia
  • Nigatu Degu Terye Hawassa University, Department of Statistics, Hawassa, Ethiopia
Keywords: Perinatal Mortality, Regional Variations, Bayesian Multilevel Modeling

Abstract

Perinatal mortality is the death of a fetus after the age of viability until the 7th day of life. Perinatal mortality is estimated by the addition of stillbirths plus the early neonatal mortality, which represents deaths occurring during the first 7 days after delivery. Perinatal mortality remains a great burden in Ethiopia. The purpose of this study was to assess and compare the demographic and socio-economic determinant factors of perinatal mortality in Ethiopia using the 2011 and 2016 Ethiopian Demographic Health Surveys (EDHS). For data analysis, the Bayesian multilevel  Model was used in this study. The study revealed that there is a regional variation in perinatal mortality and this variation was high in 2011 EDHS than in 2016 EDHS data. Factors like sex of the child, age of mother, wealth index, family size, birth order, source of drinking water, place of residence, place of delivery, and child twin were found to be the determinant factors of perinatal mortality in both 2011 and 2016 EDHS. In this study, we found that perinatal mortality variation across regions has decreased from 2011 to 2016 surveys which shows the promising progress of health intervention in the country.

Published
2021-01-30
Section
Articles

Journal Identifiers


eISSN: 2312-6019
print ISSN: 1816-3378