ArticleBMC public health2022
Background predictors of time to death in infancy: evidence from a survival analysis of the 2018 Nigeria DHS data.
Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Survival analysis of under-five mortality predictors: evidence from the 2011 and 2022/23 mozambique demographic and health surveys.BMC public health · 2026Article
- Timing of maternal antiretroviral therapy initiation and HIV status of children at 18 months in Ibadan, Nigeria.BMC infectious diseases · 2026Article
- Connecting the Dots: Mass Media, Maternal Exposure, and Child Health Outcomes in Benin.Public health challenges · 2025Article
- Modeling time to death for under-five children in Malawi using 2015/16 Demographic and Health Survey: a survival analysis.Journal of health, population, and nutrition · 2024Article
- Multiple high-risk fertility behaviours and children under five mortality survivors among ever-married women of reproductive age in Nigeria.Archives of public health = Archives belges de sante publique · 2023Article
- Article
- Time to Death and Its Predictors Among Infants in Ethiopia: Multilevel Mixed-Effects Parametric Survival Analysis Using the 2019 Ethiopian Mini Demographic Health Survey.Pediatric health, medicine and therapeutics · 2023Article
- Community and individual level determinants of infant mortality in rural Ethiopia using data from 2016 Ethiopian demographic and health survey.Scientific reports · 2022Article
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5 authors.
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Abstract
backgroundNigeria's child health profile is quite concerning with an infant mortality rate of 67 deaths per 1000 live births and a significant slowing down in progress towards improving child health outcomes. Nigeria's 2018 Demographic and Health Survey (DHS) suggests several bio-demographic risk factors for child death, including mother's poor education, poverty, sex of child, age of mother, and location (rural vs urban) but studies are yet to explore the predictive power of these variables on infant survival in Nigeria.
methodsThe study extracted data for all births in the last 12 months preceding the 2018 Nigeria DHS and used the Cox proportional hazard model to predict infant survival in Nigeria. Failure in this analysis is death with two possible outcomes - dead/alive - while the survival time variable is age at death. We censored infants who were alive at the time of the study on the day of the interview. Covariates in the analysis were: age of mother, education of mother, wealth quintile, sex of child, location, region, place of delivery, and age of pregnancy.
resultsThe study found that a higher education of a mother compared to no education (β = .429; p-value < 0.05); belonging to a household in the richer wealth quintile (β = .618; p-value < 0.05) or the highest quintile (β = .553; p-value < 0.05), compared to the lowest wealth quintile; and living in North West (β = 1.418; p-value < 0.05) or South East zone (β = 1.711; p-value < 0.05), significantly predict infant survival.
conclusionAddressing Nigeria's infant survival problem requires interventions that give attention to the key drivers - education, socio-economic status, and socio-cultural contextual issues. We therefore recommend full implementation of the universal basic education policy, and child health education programs targeted at mothers as long- and short-term solutions to the problem of poor child health outcomes in Nigeria. We also argue in favor of better use of evidence in policy and program development in Nigeria.
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