Association Between Street Greenery And Physical Activity Among Chinese Older Adults In Beijing, China

PURPOSE: Previous research suggests that urban green spaces may influence residents' physical activity (PA), but assessments of green space exposure have paid little attention to street greenery around neighborhoods and human-environment interactions. Streetscape imagery can reflect individuals' visual perceptions of street greenery at the eye level. The purpose of this study was to objectively assess street greenery exposure based on eye level using Baidu Street View images and deep learning, and to explore the association between street greenery levels and PA among Chinese older adults. METHODS: This study investigated 667 older adults (aged 60 or above, male% = 39.43) living in Beijing, China. Physical Activity Scale for the Elderly (PASE) was used to assess the physical activity level of older adults. Baidu Street View images and deep learning were used to assess the level of street greenery in the 500-meter buffer zone around the community. ANOVA and Chi-square tests were used to compare whether differences between groups were significant, and multilevel linear regression models were used to estimate the association between residential street greenery and PA among Chinese older adults. RESULTS: After controlling for individual factors (i.e., age, sex, height, weight), household economic income, and other confounder factors, a multilevel linear regression model showed that street greenery was significantly and positively associated with transportation PA (β = 0.10, p < 0.01) , especially for cycling (β = 0.12, p < 0.01) among older adults. CONCLUSIONS: The level of street greenery around the community is significantly associated with transportation PA, especially cycling PA, among Chinese older adults. This is informative for the planning and management of urban green space systems.