Evidence map›Paper›PMID 40938878›Full record

ArticlePLOS global public health2025

Survival analysis of under-five mortality and associated risk factors using survival analysis approaches.

Abdul-Karim Iddrisu, Emmanuel Boanyo

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Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Abdul-Karim IddrisuDepartment of Statistics, School of Social Sciences, Faculty of Social Sciences, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0000-0002-6751-2516
Emmanuel BoanyoDepartment of Mathematics and Statistics, School of Science, University of Energy and Natural Resources, Sunyani, Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The risk of under-five mortality is a vital measure of healthcare system performance and directly reflects progress toward Sustainable Development Goal (SDG) 3.2, which targets the elimination of preventable deaths among newborns and children under-five, aiming to reduce mortality rates to at least 25 per 1,000 live births by 2030. While Ghana has made notable progress in lowering child mortality in recent decades, the current rates remain above this benchmark. Identifying the predictors of under-five mortality is therefore critical for shaping evidence-based policies and targeted interventions that can accelerate progress toward SDG 3 and improve child health outcomes. To explore these predictors, we employed advanced survival modeling techniques. The conventional Cox-proportional hazards (Cox-PH) model assumes constant covariate effects over time, but violations of this assumption can lead to biased results. To address this, we used the extended Cox-PH model, which accommodates time-varying effects. Data were drawn from the 2022 Ghana Demographic and Health Survey (GDHS), based on a stratified two-stage cluster sampling design. Since under-five deaths are relatively rare (<10%), traditional models may yield unstable hazard ratios. We therefore applied Bayesian survival analysis to obtain more stable estimates and incorporated multilevel survival modeling to account for unobserved heterogeneity within the DHS sampling structure. Results showed that male children (HR = 1.20, 95% CI: 1.11-1.30) and twins (HR = 2.90, 95% CI: 2.51-3.34) faced higher mortality risk. Caesarean delivery (HR = 1.60, 95% CI: 1.08-2.37) and larger birth size also increased hazards. In contrast, term birth (HR = 0.16, 95% CI: 0.14-0.19), maternal education, and higher household wealth were protective. Children requiring special attention after delivery had improved survival (HR = 0.57, 95% CI: 0.38-0.89). Strengthening maternal and newborn care, coupled with addressing socioeconomic inequalities, is essential to reducing child mortality and achieving Ghana's SDG 3.2 targets.

Identifiers

PMID40938878
PMCPMC12431492

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.