Abstract

ABSTRACTBackground: Despite global achievements in reducing early childhood mortality, disparities remain. There have been empirical studies of inequalities conducted in low- and middle-income countries. However, there have been no epidemiological studies on socioeconomic inequalities and early childhood survival in Myanmar.Objective: To estimate associations between two measures of parental socioeconomic status – household wealth and education – and age-specific early childhood mortality in Myanmar.Methods: Using cross-sectional data obtained from the Myanmar Demographic Health Survey (2015–2016), univariate and multiple logistic regressions were performed to investigate associations between household wealth and highest attained parental education, and under-5, neonatal, post-neonatal and child mortality. Data for 10,081 children born to 5,932 married women (aged 15–49 years) 10 years prior to the survey, were analysed.Results: Mortality during the first five years was associated with household wealth. In multiple logistic models, wealth was protective for post-neonatal mortality. After adjusting for individual proximate determinants, the odds of post-neonatal mortality in the richest households were 85% lower (95% CI: 50–96%) than in the poorest households. However, significant association was not found between wealth and neonatal mortality. Parental education was important for early childhood mortality; the highest benefit from parental education was for child mortality in the one- to five-year age bracket. After adjusting for proximate determinants, children with a higher educated parent had 95% (95% CI 77–99%) lower odds of death in this age group compared with children whose parents’ highest educational attainment was at primary level. The association between parental education and neonatal mortality was not significant.Conclusions: In Myanmar, household wealth and parental education are important for childhood survival before five years of age. This study identified nuanced age-related differences in associations. Health policy must take socioeconomic determinants into account in order to address unfair inequalities in early childhood mortality.

Highlights

  • Despite global achievements in reducing early childhood mortality, disparities remain

  • Children in Sub-Saharan African (SSA) countries have a 20 times higher risk of dying before the age of five, compared to children living in the Australasian Region (Australia and New Zealand), and more than 90% of deaths in children under-5 occur in low- and middle-income countries (LMICs) [5,6]

  • A systematic analysis by the Global Burden of Disease (GBD) Collaboration showed that between 1970 and 2016, neonatal mortality in countries classified as having a low socio-demographic index (SDI) was 24.3 deaths per 1,000 live births compared with 2.7 deaths per 1,000 live births in high SDI countries

Read more

Summary

Introduction

Despite global achievements in reducing early childhood mortality, disparities remain. Objective: To estimate associations between two measures of parental socioeconomic status – household wealth and education – and age-specific early childhood mortality in Myanmar. Methods: Using cross-sectional data obtained from the Myanmar Demographic Health Survey (2015–2016), univariate and multiple logistic regressions were performed to investigate associations between household wealth and highest attained parental education, and under-5, neonatal, post-neonatal and child mortality. A systematic analysis by the GBD Collaboration showed that between 1970 and 2016, neonatal mortality in countries classified as having a low socio-demographic index (SDI) was 24.3 deaths per 1,000 live births compared with 2.7 deaths per 1,000 live births in high SDI countries. The comparable rates for post-neonatal mortality (one month to one year) in low versus high SDI countries, were 23.2 and 1.4 deaths per 1,000 live births, and among children aged between one and five years, 24.4 and 0.8 deaths per 1,000 live births, respectively [2].

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call