Scholarlink

Background <p>Housing is a critical component of age-friendly environments and may influence intrinsic capacity (IC), a multidimensional indicator of healthy ageing defined by the World Health Organization. However, longitudinal evidence on how housing characteristics relate to IC across diverse contexts remains limited.</p> Methods <p>Data were collected from the China Health and Retirement Longitudinal Study (CHARLS) (<i>N</i> = 5,691) and the English Longitudinal Study of Ageing (ELSA) (<i>N</i> = 5,218). IC was measured across five domains including cognition, locomotor, vitality, sensory, and psychological well-being. Housing characteristics covered living space, basic utilities and infrastructure, communication access, housing problems, and accessibility/adaptation features. The relationship between housing characteristics and IC was assessed using multivariable linear mixed-effects growth-curve models adjusted for socio-demographic and health-related covariates. Sensitivity analyses additionally modelled post-baseline IC while adjusting for baseline IC and baseline covariates.</p> Results <p>In the primary models, most housing characteristics were associated with baseline differences in IC, whereas evidence for differential IC trajectories over follow-up was limited. In CHARLS, greater living space, utility access, and communication access were associated with higher baseline IC. In ELSA, fewer housing indicators were associated with baseline IC, and computer ownership was the only housing characteristic associated with a more favourable IC trajectory in the primary models; this association attenuated after adjustment for baseline IC. In the baseline-IC adjusted sensitivity analyses, home adaptation in ELSA was associated with a less favourable IC trajectory.</p> Conclusions <p>Housing characteristics were associated primarily with IC level differences, with limited evidence of differential IC decline over follow-up. Adequate living space and communication access were consistently related to better IC levels, while utility-related associations were more evident in CHARLS than in ELSA. These findings support the relevance of housing within healthy-ageing policy, while also indicating that the meaning and implications of specific housing characteristics differ across settings and should be interpreted cautiously.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Living space, utilities, and communication access as determinants of intrinsic capacity: longitudinal findings from England and China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月24日

查看全文
  • Eric TC Lai,
  • Ziting Huang,
  • Jean Woo

摘要

Background

Housing is a critical component of age-friendly environments and may influence intrinsic capacity (IC), a multidimensional indicator of healthy ageing defined by the World Health Organization. However, longitudinal evidence on how housing characteristics relate to IC across diverse contexts remains limited.

Methods

Data were collected from the China Health and Retirement Longitudinal Study (CHARLS) (N = 5,691) and the English Longitudinal Study of Ageing (ELSA) (N = 5,218). IC was measured across five domains including cognition, locomotor, vitality, sensory, and psychological well-being. Housing characteristics covered living space, basic utilities and infrastructure, communication access, housing problems, and accessibility/adaptation features. The relationship between housing characteristics and IC was assessed using multivariable linear mixed-effects growth-curve models adjusted for socio-demographic and health-related covariates. Sensitivity analyses additionally modelled post-baseline IC while adjusting for baseline IC and baseline covariates.

Results

In the primary models, most housing characteristics were associated with baseline differences in IC, whereas evidence for differential IC trajectories over follow-up was limited. In CHARLS, greater living space, utility access, and communication access were associated with higher baseline IC. In ELSA, fewer housing indicators were associated with baseline IC, and computer ownership was the only housing characteristic associated with a more favourable IC trajectory in the primary models; this association attenuated after adjustment for baseline IC. In the baseline-IC adjusted sensitivity analyses, home adaptation in ELSA was associated with a less favourable IC trajectory.

Conclusions

Housing characteristics were associated primarily with IC level differences, with limited evidence of differential IC decline over follow-up. Adequate living space and communication access were consistently related to better IC levels, while utility-related associations were more evident in CHARLS than in ELSA. These findings support the relevance of housing within healthy-ageing policy, while also indicating that the meaning and implications of specific housing characteristics differ across settings and should be interpreted cautiously.