Association between street greenery and physical activity among Chinese older adults in Beijing, China

Although numerous studies have investigated the impact of urban green spaces on health, the association between street-level greenery and domain-specific physical activity (PA) among older adults remains underexplored. This study employed Baidu Street View imagery and deep learning techniques to objectively evaluate street greenery exposure and its relationship with various types of PA among older adults in China. We conducted a cross-sectional study involving 1326 older adults (aged 60 years and above) residing in Beijing, China. The Physical Activity Scale for the Elderly (PASE) was used to assess participants' PA levels. Street greenery was measured within a 500 m buffer around each participant's residence using Baidu Street View images and deep learning algorithms. Data were analyzed using ANOVA, Chi-square tests, and multilevel linear regression models. Correlation analyses revealed that street greenery within a 500 m buffer of participants' residences was significantly and positively associated with transportation PA among older adults (p < 0.05), particularly with bicycling (p < 0.01). After adjusting for individual characteristics, annual household income, and other potential confounders, multilevel linear regression analysis indicated that street greenery remained a significant positive predictor of transportation PA (β = 0.08, p < 0.01). No significant associations were found between street greenery and either leisure PA or household PA (p > 0.05). Street greenery around residential areas is significantly associated with transportation PA among older adults in China. Urban green space planning should prioritize enhancing street greenery and creating safe, pleasant walking and cycling environments to support active aging in high-density cities.