Identifying the effect of street network system on activity behaviours near the homes of older adults: An analytical framework integrating transportation, social, and natural attributes

Extensive research has explored the relationship between street characteristics and the activity behavior of older adults, yet the exploration of non-linear relationships in this context remains limited. Additionally, natural street attributes, such as blue and green spaces, have been largely understudied. This paper fills these gaps by exploring the nonlinear relationships between street network features and activity behaviors near older adults' homes, using a gradient boosting decision tree model, with a focus on Dalian, China. The study highlights three key findings. First, street network characteristics have a stronger influence on activity behaviors than socio-demographic factors. Second, the relationship between street network features and activity behaviors is often nonlinear, emphasizing the need for nonlinear analysis methods. Third, the study reveals that strategies aimed at enhancing street network closeness, improving service facilities, increasing public transport accessibility and enhancing the quality of green and blue spaces may motivate older adults to engage in activity behaviours. The interaction between key street network indicators reveals significant effects, requiring identification of their effective ranges and interaction values. These insights offer practical recommendations for urban planning and promote strategies to support healthier lifestyles for older adults, ultimately contributing to the development of sustainable transportation systems.