应用基于群体的轨迹模型,了解低收入和中低收入国家五岁以下儿童死亡率趋势和决定因素。

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Kavita Singh, Gustavo Angeles, H Luz McNaughton Reyes, Elizabeth Simmons, Alison Swiatlo, William Weiss
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引用次数: 0

摘要

背景:降低五岁以下儿童死亡率是一项全球卫生优先事项。各国需要关于哪些干预措施最有可能带来改善的具体数据,以便为其规划和政策提供信息。方法:应用基于群体的轨迹模型来确定78个低收入和中低收入国家2000年至2019年五岁以下儿童死亡率的不同轨迹。健康和非健康变量作为轨迹组成员的时间稳定协变量和组内死亡率的时间变化协变量进行了研究。结果:我们确定了四个不同的群体,主要是根据轨迹水平而不是形状来区分的——低死亡率、中等死亡率、中高死亡率和高死亡率。所有四组的五岁以下轨迹都随着时间的推移而下降,死亡率最高的组下降幅度最大。我们进行了两组双变量分析。第一次分析是为了了解哪些因素将不同的群体区分开来(时间稳定协变量分析),第二次分析是为了了解在一个群体中哪些因素是显著的(时间变化协变量分析)。结果表明,与死亡率最高的组相比,处于低、中、中高组的所有三种比较都与五个因素有关。这些因素是生育率、获得改善水源的人口百分比、女性中学入学率、白喉、百日咳、破伤风三联疫苗(DPT3)的覆盖率和卫生支出占国内生产总值(GDP)的百分比。具有时变因素的组内分析的建模结果表明,在所有四组中,较高的生育率和较高的自付费用与较高的死亡率显著相关。三联破伤风三联疫苗的高覆盖率、更大的政治稳定性、在卫生机构分娩的高覆盖率以及国内生产总值占卫生支出的更高百分比与所有四组五岁以下儿童死亡率的降低显著相关。结论:我们的研究结果揭示了在了解五岁以下儿童死亡率轨迹时考虑健康和非健康因素的重要性。特别是,在轨迹组成员分析(时间稳定协变量)的所有三个比较中,生育率和GDP占卫生支出的百分比都是显著的,并且在组内分析(时间变化协变量)的所有四个组中都是显著的。其他因素在一些比较和群体中也很重要。将重点放在与其群体相关的一些关键因素上,可以帮助各国进一步改善幼儿的健康。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying group-based trajectory modeling to understand under-five mortality trends and determinants in low-and lower-middle income countries.

Background: Reducing under-five mortality is a global health priority. Countries need specific data on which interventions have the most potential to lead to improvements to inform their programs and policies.

Methods: Group-based trajectory modeling was applied to identify distinct trajectories of under-five mortality from 2000 to 2019 in 78 low and lower-middle income countries. Both health and non-health variables were studied as time-stable covariates of trajectory group membership and as time-varying covariates of mortality rates within groups.

Results: We identified four distinct groups that were primarily distinguished based on trajectory level rather than shape-low mortality, medium mortality, medium-high mortality and high mortality. All four groups had under-five trajectories that declined over time with the highest mortality group having the largest declines. We conducted two sets of bivariate analyses. The first analysis was conducted to understand what factors distinguished the different groups from one another (time stable covariate analysis), and the second analysis was done to understand what factors were significant within a group (time vaying covariate analysis). Results indicated that five factors were associated with all three comparisons of being in the low, medium and medium high groups compared to the highest mortality group. These factors were fertility rate, % of population with an improved water source, female secondary school enrollment rate, diphtheria, pertussis, tetanus dose 3 (DPT3) coverage and % of gross domestic product (GDP) on health expenditures. Results of the modeling of the within group analysis with time-varying factors indicated that higher fertility rates and higher out-of-pocket expenditures were significantly associated with greater mortality rates for all four groups. High DPT3 coverage, greater political stability, high coverage of births in a health facility and a greater % GDP on health expenditures were significantly associated with reduced under-five mortality for all four groups.

Conclusion: Findings from our study revealed the importance of considering both health and non-health factors in understanding trajectories of under-five mortality. In particular the fertility rate and % of GDP on health expenditures were signicant for all three comparisons of the trajectory group membership analysis (time-stable covariates) and were significant for all four groups in the within group analysis (time varying covariates). Other factors were significant for some comparisons and groups. Focusing on a number of key factors relevant to their group could help countries to further improve the health of young children.

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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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