[Evaluation of predictive effect of some health-related indices on deaths among ageing residents through a 8-years' follow-up study in Beijing]

Zhonghua Liu Xing Bing Xue Za Zhi. 2004 Apr;25(4):325-8.
[Article in Chinese]

Abstract

Objective: To study the predictive effects of some health status indicators to deaths in the elderly population.

Methods: In 1992, a cohort of 3257 people older than 55 years old was formed from Beijing urban and suburb area. Demographic and information of activity of daily living (ADL), self-rated health (SRH), chronic diseases history and other related variables were collected at baseline survey in 1992. MMSE and CES-D were studied in 2101 on 3257 elderly people. Follow-up surveys were conducted in 1994, 1997 and 2000, to find that a total number of or= 75), resident place (suburb) and education level (illiteracy). The functional disability, poor self-rated health status, history of chronic diseases and abnormal cognition function were the major predictors of deaths. Multinomial logistic regression analysis showed that after adjustment for sex, age, residential place, education level and history of chronic diseases, functional disability, poor self-rated health status and abnormal cognition function remained as significant independent predictors to death.

Conclusions: Functional disability, poor self-rated health status and abnormal cognition function were the most valuable indicators of death. Not only they had joined predictive effects to death, but also remained relatively independent. They had important value in the evaluation on healthy prognosis and the life quality of the elderly.

Publication types

  • English Abstract

MeSH terms

  • Activities of Daily Living
  • Aged
  • Cause of Death*
  • China
  • Female
  • Follow-Up Studies
  • Health Status
  • Health Status Indicators*
  • Humans
  • Linear Models
  • Logistic Models
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Reproducibility of Results
  • Sex Factors
  • Surveys and Questionnaires / standards
  • Time Factors