Association between Age-Friendliness of Communities and Frailty among Older Adults: A Multilevel Analysis

Int J Environ Res Public Health. 2022 Jun 20;19(12):7528. doi: 10.3390/ijerph19127528.

Abstract

An age-friendly environment is one of the measures of healthy aging. However, there is scarce evidence of the relationship between the age-friendliness of communities (AFC) and frailty status among Chinese older adults. This study aims to examine this relationship using a multilevel analysis with the data of a cross-sectional study conducted among 10,958 older adults living in 43 communities in four cities in China. The validated Age-friendly Community Evaluation Scale and Chinese frailty screening-10 Scale (CFS-10) were used to measure AFC and Frailty. Multilevel regression analyses were performed to examine the relationship between the AFC in two assessments of individual- and community-level and frailty status. After controlling for individual-level socio-demographic, health status, and lifestyle variables, compared with older adults in the lowest quartile of the individual-level perception of AFC, the frailty odds ratios for those in the top three quartiles were 0.69 (95% confidence interval [CI]: 0.56-0.83), 0.75 (95% CI: 0.61-0.91), and 0.56 (95% CI: 0.48-0.74). However, there was no association between the community-level AFC and frailty. A higher level of age-friendliness in the community is associated with lower frailty odds. Therefore, building age-friendly communities may be an important measure to prevent frailty among Chinese older adults.

Keywords: age-friendly community; frailty; multilevel analysis; older adults.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • China / epidemiology
  • Cross-Sectional Studies
  • Frail Elderly
  • Frailty* / epidemiology
  • Health Status
  • Humans
  • Independent Living
  • Multilevel Analysis

Grants and funding

This research was funded by the National key Research and Development Program of China [grant number 2018YFC2002000, 2018YFC2002001]; and the National Natural Science Foundation of China [grant number no. 82173634].