Abstract
An effective response to population ageing is crucial for ensuring global social sustainability. Improving the age-friendliness of neighbourhoods and maintaining the functional ability of older adults are key strategies in addressing the challenges posed by population ageing. However, the nonlinear effect of neighbourhood environments on the functional ability of older adults is largely unexplored. This study performed empirical analysis using multi-source geospatial data and questionnaire survey data from Guangzhou, China. Results of generalized additive mixed models revealed that the population density, branch road proportion, and street traffic volume exerted a positive influence on the older adults' functional ability, and when the values were outside the optimal range, the positive association became negative. In addition, the accessibility of facilities, street safety, visible sky features, and water areas exerted a positive impact on functional ability. Meanwhile, high-density urban environment characteristics, namely building density, road density, and the number of public transportation stops, exerted a negative impact. This study contributes to person–environment fit theory by revealing the optimal levels of environmental attributes for the functional ability among older adults, as well as by comprehensively examining impacts from two spatial scales – neighbourhood and streetscape environments – and by revealing the heterogeneous effects from income and age. Furthermore, it recommends evidence-based planning and targeted governance strategies for building age-friendly neighbourhoods in China and other high-density Asian cities. © 2025 Elsevier Inc.
| Original language | English |
|---|---|
| Article number | 108115 |
| Number of pages | 16 |
| Journal | Environmental Impact Assessment Review |
| Volume | 116 |
| Online published | 26 Aug 2025 |
| DOIs | |
| Publication status | Published - Jan 2026 |
Funding
This study was supported by the National Natural Science Foundation of China (Grant No. 42301215 ), Young Elite Scientists Sponsorship Program by CAST (No. 2022QNRC001 ), and Natural Science Foundation of Guangdong Province , China (No. 2024A1515012607 ).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Research Keywords
- Age groups
- Functional ability
- Generalized additive mixed models
- Income groups
- Neighbourhood environments
- Nonlinear effects
- Older adults
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