改编和验证对数二次方模型,得出五岁以下儿童年龄和原因死亡率(U5ACSM):初步分析。

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Population Health Metrics Pub Date : 2022-01-10 DOI:10.1186/s12963-021-00277-w
Jamie Perin, Yue Chu, Francisco Villavicencio, Austin Schumacher, Tyler McCormick, Michel Guillot, Li Liu
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引用次数: 0

摘要

背景:众所周知,从出生到五岁期间的死亡模式因死亡的根本原因而异,这在多个实例中都有记录。然而,迄今为止,五岁以下儿童的死亡原因只针对广泛的年龄类别进行了描述,如新生儿(0-27 天)、婴儿(0-11 个月)和 12-59 个月的儿童:我们将五岁以下儿童死亡率模式的对数二次方模型调整为全因儿童死亡率,然后再调整为年龄和特定原因死亡率(U5ACSM)。我们将这些方法应用于 1996 年至 2015 年中国的实证样本登记系统死亡率数据。基于这些经验数据,我们模拟了在已知年龄与不同原因死亡率之间真实关系的情况下的死亡率概率:根据中国抽样登记系统构建的生命表,我们估算出 U5ACSM 的预测误差在 0.1-0.7 之间,而使用标准方法的预测误差为 1.2。U5ACSM 预测误差的改善在全因死亡率以及肺炎和损伤特异性死亡率方面得到了一致的证明。我们还在模拟的死亡情景中持续发现了特定病因的死亡模式:结论:根据模拟和经验结果,对数二次方模型在得出 U5ACSM 的标准方法上有显著改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Adapting and validating the log quadratic model to derive under-five age- and cause-specific mortality (U5ACSM): a preliminary analysis.

Background: The mortality pattern from birth to age five is known to vary by underlying cause of mortality, which has been documented in multiple instances. Many countries without high functioning vital registration systems could benefit from estimates of age- and cause-specific mortality to inform health programming, however, to date the causes of under-five death have only been described for broad age categories such as for neonates (0-27 days), infants (0-11 months), and children age 12-59 months.

Methods: We adapt the log quadratic model to mortality patterns for children under five to all-cause child mortality and then to age- and cause-specific mortality (U5ACSM). We apply these methods to empirical sample registration system mortality data in China from 1996 to 2015. Based on these empirical data, we simulate probabilities of mortality in the case when the true relationships between age and mortality by cause are known.

Results: We estimate U5ACSM within 0.1-0.7 deaths per 1000 livebirths in hold out strata for life tables constructed from the China sample registration system, representing considerable improvement compared to an error of 1.2 per 1000 livebirths using a standard approach. This improved prediction error for U5ACSM is consistently demonstrated for all-cause as well as pneumonia- and injury-specific mortality. We also consistently identified cause-specific mortality patterns in simulated mortality scenarios.

Conclusion: The log quadratic model is a significant improvement over the standard approach for deriving U5ACSM based on both simulation and empirical results.

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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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