使用生存分析方法对五岁以下儿童死亡率和相关危险因素进行生存分析。

IF 2.5
PLOS global public health Pub Date : 2025-09-12 eCollection Date: 2025-01-01 DOI:10.1371/journal.pgph.0005179
Abdul-Karim Iddrisu, Emmanuel Boanyo
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引用次数: 0

摘要

五岁以下儿童死亡风险是衡量卫生保健系统绩效的一项重要指标,直接反映了在实现可持续发展目标3.2方面取得的进展,该目标旨在消除新生儿和五岁以下儿童中可预防的死亡,到2030年将死亡率降至至少每1000例活产死亡25例。虽然加纳近几十年来在降低儿童死亡率方面取得了显著进展,但目前的死亡率仍高于这一基准。因此,确定五岁以下儿童死亡率的预测因素对于制定循证政策和有针对性的干预措施至关重要,从而加快实现可持续发展目标3的进程并改善儿童健康结果。为了探索这些预测因素,我们采用了先进的生存建模技术。传统的Cox-proportional hazards (Cox-PH)模型假设随时间的协变量效应是恒定的,但违反这一假设可能导致有偏差的结果。为了解决这个问题,我们使用了扩展的Cox-PH模型,该模型可以适应时变效应。数据来自2022年加纳人口与健康调查(GDHS),基于分层两阶段整群抽样设计。由于五岁以下儿童的死亡相对较少(
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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

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

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.

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