RESEARCH ARTICLE


The Effect of Socioeconomic Drivers on Under-five Mortality Rates: A Survey Bayesian Meta-analysis Study



Welcome J. Dlamini1, *, Sileshi F. Melesse2, Henry G. Mwambi2
1 Department of Mathematical Sciences, KwaDlangezwa Campus, University of Zululand, Private Bag X1001 KwaDlangezwa 3886, South Africa
2 School of Mathematics, Statistics, and Computer Science, Pietermaritzburg Campus, University of KwaZulu-Natal, Private Bag X01 Scottsville 3209, South Africa


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Creative Commons License
© 2024 The Author(s). Published by Bentham Open..

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Mathematical Sciences, KwaDlangezwa Campus, University of Zululand, Private Bag X1001 KwaDlangezwa 3886, South Africa; E-mail: dlaminwel@gmail.com


Abstract

Background

Studies on approaches for combining information from related studies have been well-documented in the literature. However, limited research has been conducted to focus on the issue of combining parameter estimates in the context of under-five mortality.

Objectives

The objective of this study was to study the overall effect of socioeconomic factors on under-five mortality, considering the censoring problem and survey design features.

Methods

This study estimates the overall effect of risk factors on under-five mortality in four countries from the sub-Saharan African region using Bayesian hierarchical meta-analysis. The data used in the study is from the previous four demographics and health surveys for a research area.

Results

The results obtained using the Bayesian Meta Cox PH model are almost similar to those using the extended Cox except for one key finding. A child from a rural area has an increased risk of dying compared to a child from an urban area. Whereas it is insignificant when using the extended Cox model.

Conclusion

The study has demonstrated drivers of child mortality using Bayesian hierarchical meta-analysis.

Keywords: Mortality, Bayesian, Weighting, Clustering, Stratification, Meta-analysis, Cox model, Sub-saharan african region.