Designing walkable streets: Exploring nonlinear effects of street-level built environment on older adults’ walking intention

The growing trend of older adults aging in their long-term residential settings has increased the demand for built environment designs that promote mobility, safety, and social engagement. Streets, as accessible and ubiquitous public spaces, play a critical role in shaping older adults’ walking intention and overall well-being, highlighting the importance of age-friendly street design. However, the relationship between the street-level built environment and older adults’ walking intention remains underexplored, especially regarding potential nonlinear effects. This study employed the DeepLabV3 semantic segmentation model to extract street-level built environment features from street view images. Older adults’ walking intention was quantitatively assessed by applying the Microsoft TrueSkill algorithm to convert pairwise image comparisons into ranked scores. Integrating a Gradient Boosting Decision Tree model with SHAP analysis, we examined the nonlinear and interaction effects of street-level built environment features on walking intention. Results showed that: (1) street-level built environment features were stronger determinants of older adults’ walking intention than socioeconomic factors, with green view index exerting the greatest influence; (2) the effects of street-level features exhibited nonlinear patterns, mainly power or exponential functions, with a threshold at GVI = 0.48 beyond which marginal gains diminished; (3) GVI, pedestrian path ratio, and colour richness were positively correlated with older adults’ walking intention, while building-to-street ratio, proportion of walls, and crowd concentration index showed negative correlations; and (4) significant interaction effects were observed among street-level built environment features. This study advances theoretical understanding of how microscale built environment shapes human behavior through nonlinear and synergistic mechanisms, providing actionable insights for designing age-friendly and walkable communities.

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Publication Details

Journal
Humanities and Social Sciences Communications
Published
2026-09-25
DOI
https://doi.org/10.1057/s41599-026-08905-2
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
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Designing walkable streets: Exploring nonlinear effects of street-level built environment on older adults’ walking intention

Chang Xia, J. Li, Huagui Guo, Shuyu Zhang et al.
Humanities and Social Sciences Communications
Urban Transport and Accessibility
article

Designing walkable streets: Exploring nonlinear effects of street-level built environment on older adults’ walking intention

Chang Xia, J. Li, Huagui Guo, Shuyu Zhang, Wenkui Wang, Lingtong Zhang
article en

Abstract

The growing trend of older adults aging in their long-term residential settings has increased the demand for built environment designs that promote mobility, safety, and social engagement. Streets, as accessible and ubiquitous public spaces, play a critical role in shaping older adults’ walking intention and overall well-being, highlighting the importance of age-friendly street design. However, the relationship between the street-level built environment and older adults’ walking intention remains underexplored, especially regarding potential nonlinear effects. This study employed the DeepLabV3 semantic segmentation model to extract street-level built environment features from street view images. Older adults’ walking intention was quantitatively assessed by applying the Microsoft TrueSkill algorithm to convert pairwise image comparisons into ranked scores. Integrating a Gradient Boosting Decision Tree model with SHAP analysis, we examined the nonlinear and interaction effects of street-level built environment features on walking intention. Results showed that: (1) street-level built environment features were stronger determinants of older adults’ walking intention than socioeconomic factors, with green view index exerting the greatest influence; (2) the effects of street-level features exhibited nonlinear patterns, mainly power or exponential functions, with a threshold at GVI = 0.48 beyond which marginal gains diminished; (3) GVI, pedestrian path ratio, and colour richness were positively correlated with older adults’ walking intention, while building-to-street ratio, proportion of walls, and crowd concentration index showed negative correlations; and (4) significant interaction effects were observed among street-level built environment features. This study advances theoretical understanding of how microscale built environment shapes human behavior through nonlinear and synergistic mechanisms, providing actionable insights for designing age-friendly and walkable communities.

Humanities and Social Sciences Communications
Hunan University (CN), Fuzhou University (CN), Fujian University of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 7%
Urban Transport and Accessibility
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