MODELLING THE DETERMINANTS OF UNDER-FIVE CHILD MORTALITY RATES USING COX PROPORTIONAL HAZARDS REGRESSION MODEL

M C Musa,S S Sani,H G Dikko,M Usman,O E Asiribo

doi:10.33003/fjs-2020-0404-496

Abstract

An under-five childhood mortality rates in Nigeria is still high, despite efforts of government at all levels to combat the menace. This study examined some factors that significantly affect under-five child mortality. A sample of mothers with children under the age of five from Nigeria Demographic and Health Survey data (NDHS, 2013 & 2018) was used to assess the effect of some selected predictor variables (or covariates) on childhood survival. Cox proportional hazards model is essentially a regression model popularly used for investigating the association between the survival time and one or more predictor variables. The results from final fitted Cox proportional hazards regression model that the covariates, contraceptive used by the mother, state of residence, birth weight of child and type of toilet facility used by the h-ousehold were found to be significantly associated with under-five survival in the North Central Region of Nigeria. All the calculations are performed using the R software for statistical analysis.

Highlights

Under-five childhood mortality is an important demographic health and developmental issue for a number of reasons
Antai et al, (2009) argued that, the number of health facilities notwithstanding, the use of maternal and child health services is largely determined by mother's indigenous religious affiliation and this significantly influences the risk of infant and child mortality
The Cox proportional-hazards model or Cox regression (Cox, 1972) is essentially a regression model commonly used in statistics and medical research for investigating the association between the survival time of patients and one or more predictor variables

Summary

Introduction

Under-five childhood mortality is an important demographic health and developmental issue for a number of reasons. Income of the household, birth order, mother’s age at birth and In this study, we employed Cox proportional hazards mother’s health care were important determinants of infant and regression model to investigate the predictor variables of child mortality in India. The study reported that birth interval, mother’s literacy, household wealth, mother’s age at Kaplan-Meier (K-M) Estimator birth, mother’s exposure to mass media, sex of the child, The Kaplan-Meier (KM) method is a non-parametric method religion, family size, birth order and residence were important used to estimate the survival probability from observed predictors of infant and child mortality.

Results

Conclusion