人口研究 ›› 2014, Vol. 38 ›› Issue (2): 18-35.

• 论文 • 上一篇    下一篇

出生队列效应下老年人健康指标的生长曲线及其城乡差异

李婷1张闫龙2   

  1. 1 中国人民大学人口与发展研究中心,北京 100872;2 张闫龙,北京大学光华管理学院,北京 100871。
  • 出版日期:2014-03-29 发布日期:2014-06-30
  • 通讯作者: li.ting@ruc.edu.cn
  • 作者简介:1 李婷,中国人民大学人口与发展研究中心讲师; 2 张闫龙,北京大学光华管理学院讲师。
  • 基金资助:

    中国人民大学科学研究基金( 中央高校基本科研业务费专项资金资助) 项目( 项目批准号: 14XNF031)

Growth Curve Trajectories of Elderly People's Health Indicators in China: Cohort Variations and Rural-urban Disparities

Li Ting1; Zhang Yanlong2   

  1. 1 Center for Population and Development Studies, Renmin University, Beijing 100872; 2 Guanghua Management School, Beijing University, Beijing 100871.
  • Online:2014-03-29 Published:2014-06-30
  • Contact: li.ting@ruc.edu.cn
  • About author:1 Assistant Professor, Center for Population and Development Studies, Renmin University.; 2 Zhang Yanlong is Assistant Professor, Guanghua Management School, Beijing University.

摘要: 准确理解老年人重要健康指标的变化趋势及其影响因素,对合理估计养老医疗负担,提高老年人生活质量有重要意义。以往基于横截面或单个出生队列数据的研究,由于无法控制出生队列效应,可能造成对趋势估计的偏差。文章利用中国老年人口健康状况调查的多重队列纵向追踪数据( CLHLS ( 1998 ~ 2011) ) ,用生长曲线模型考察老年人的自我评估健康水平,日常活动功能,心理健康水平以及认知水平的变化规律及其在城乡居民之间的差异。结果显示这些健康指标的变化
和群体差异均与队列效应紧密相关: ( 1) 在没有控制队列效应下,可能会对估计的年龄趋势产生偏差; ( 2) 健康指标曲线在不同队列之间有区别; ( 3) 在同一出生队列下,城市和农村老年人的健康状况有显著差异; ( 4) 这种差异在ADL 和心理健康水平这两项指标中随着队列的不同而改变。

关键词: 健康指标, 队列效应, 城乡差异, 生长曲线模型

Abstract: Understanding the changing patterns of the health indicators of older population and the influencing factors is important for correctly estimating the healthcare burden and promoting the life quality for older population. Previous studies based on cross-sectional or single birth cohort data cannot distinguish or control the cohort effects,which may lead to biased estimation of the trend. Using the multi-cohort data of Chinese Longitudinal Healthy Longevity Survey ( CLHLS ( 1998—2011) ) ,this study investigates the growth curve trajectories of older people's self-rated health,Activities of Daily Living ( ADL) ,psychological wellbeing,and cognitive score; and explores their rural-urban disparities with full consideration of the cohort effects. The results suggest that the changing patterns of these health indicators and their population disparities are closely related to the cohort variations: ( 1) without controlling
the cohort effects,the estimation of age patterns would be biased; ( 2) there are cohort variations among the health trajectories; ( 3) within the same cohort,urban and rural elderly show significant differences in all of the health indicators; and ( 4) such differences in ADL and psychological wellbeing
change with cohort.

Keywords: Health Indicator, Cohort Effect, Rural-urban Disparity, Growth Curve Model