一、论文摘要

Cohort health expectancy, rather than period health expectancy, is a more appropriate measure for describing the health trajectories of specific cohorts. Decomposing the differences in cohort health expectancy by cause (i.e., disease) and age helps us to better understand and alleviate health disparities between subcohorts. However, there is a lack of effective decomposition methods for cohort health expectancy. The key to such a decomposition is additively attributing disability and death to specific ages and causes, a step known as attribution. Existing attribution methods are usually designed for cross-sectional data and thus cannot effectively capture the temporal association between causes and disability or death in a cohort. We propose a novel longitudinal attribution method that calculates age‒cause-specific contributions to disability and death in a cohort during longitudinal follow-up. We then present a new longitudinal decomposition method for the differences in cohort health expectancies based on the attribution results. Finally, we illustrate the proposed methods by decomposing the sex difference in cohort health expectancy using a longitudinal dataset of older Chinese individuals. These methods were implemented in a user-friendly online application (https://zhenghp.shinyapps.io/PC-HE_decomp/) and the freely available R package {LongDecompHE}.

二、论文发表截图

三、论文题目

Decomposing Differences in Cohort Health Expectancy by Cause and Age With Longitudinal Data

四、作者介绍

孙韬，中国人民大学统计学院副教授，博士毕业于美国匹兹堡大学生物统计系。主要研究方向为复杂生存数据建模、健康老龄化统计方法、老年失能失智风险管理以及人工智能驱动的疾病风险预测。研究成果发表于Biometrics, Demography, Age and Ageing等统计学、人口学和老年学期刊。主持国家自然科学基金青年项目、面上项目及全国统计科学研究重点项目。

郑卉萍，中国人民大学统计学院2022级博士研究生。研究方向包括老年健康遗传机制、健康预期寿命建模、死亡率分析及人口统计方法。论文发表于Demography，Journal of Gerontology Series A，《中国人口科学》等期刊。

王晓军（通讯作者），中国人民大学吴玉章讲席教授，统计学院教授。国家统计专家咨询委员会委员，兼任中国统计教育学会副会长、国务院学位委员会统计学学科评议组召集人、全国应用统计专业学位研究生教育指导委员会秘书长、国家统计局-中国人民大学数据开发中心执行主任。主要从事人口统计、人寿保险、养老金、社会保障以及与健康相关的风险量化模型与应用研究。