Decoding the spatial effects of walkability on walking behavior among older adults by integrating big data and small data

Abstract

While a walkable environment promotes older adults' walking, few studies have incorporated big and small data to examine the relationship between walkability and older adults' walking behaviors. Using Shenzhen in China as the study area, this study explores walkability's effects on senior walking behaviors by integrating big and small data. The walkability framework is developed regarding four pedestrian needs: safety, convenience, continuity, and attractiveness. The walkability elements are extracted from street view images and diverse open data sources. We quantify the importance of walkability elements from 459 questionnaires across the city as weights to calculate elderly walkability scores. More than 27 million senior walking trips were identified from 6 months of mobile phone data in 2021. We used a geographically weighted Poisson regression model to examine the spatial effects of walkability on senior walking trips. The results show that the most important pedestrian need for seniors is safety, followed in order by attractiveness, convenience, and continuity. Areas with high elderly walkability scores are largely in urban areas and suburban subcenters. Walkability exerts a strong positive role on senior walking trips in the inner suburbs. Based on the findings, we tailor intervention strategies to foster age-friendly walking environments.