摘要
随着人口老龄化进程的加速,老年健康成为学界关注的一大领域。探究老年健康不平等及其影响机理,准确理解老年人健康指标的变化趋势,对于实现健康老龄化的目标具有积极的意义。本文采用中国健康与养老追踪调查(China Health and Retirement Longitudinal Study,CHARLS)数据,运用分层线性模型考察老年人健康水平的影响因素和群际差异。本文还利用SF-36量表,基于主成分分析方法构建涵盖主客观健康指标,在地区和社区层面重点探究教育程度、个人收入等因素对于健康不平等的影响机理。分析结果显示,个人和家庭的社会经济条件对于老年健康有积极的作用,物质资源越丰富的老人越健康;地区层面,经济发展给健康带来了正向的外部性,经济越发达老年人健康指数越高;社区层面,老年人生活的社区经济水平越高,其健康水平分化越严重。从受教育水平来看,老年健康体现为社区层面"低度平均,高度不均",个体层面"低度不均,高度平均",收入水平在个体层面和社区层面产生了相反的影响。
With accelerating aging process of the population, health of the elderly is attracting more and more attention of the academia. It is meaningful to explore the mechanism of health inequality and precisely understand the variation of elderly health. Moreover, it is crucial to achieve the goal of Healthy Aging. In this study, we apply hierarchical linear model to explore the influence factors of elderly health and health disparity between regions and communities. The data used here comes from China Health and Retirement Longitudinal Study. We transform the SF-36 scale and construct an indicator which include subjective and objective factors by using principal components analysis method. This study mainly focuses on education and personal income＇ s influence on elderly health and health inequality on regional and community level. The result turns that better socio-economic conditions of individual and household indicate higher health index. On regional and community level, the boom of the economy presents positive externality to health. However, on community level, higher income refers to more serious differentiation of health level. Education level performs different roles in different elderly groups. In low income level groups, education brings convergence to health index, while, in high income groups, education brings divergence to health index.
出处
《人口学刊》
CSSCI
北大核心
2017年第2期57-67,共11页
Population Journal
基金
国家自然科学基金:健康老龄化--老年人口健康影响因素及有效干预的基础科学问题研究(71490732)
教育部人文社会科学重点研究基地重大项目:实现人口经济社会健康老龄化的对策研究(16JJD840004)
关键词
地区和社区
老年健康
不平等
HLM
Region and Community, Heahh of Elderly, Inequality, HLM
