Understanding spatiotemporal patterns of walking behavior of older people via mobile phone big data

The characteristics of older adults’ walking behavior can provide insights for developing an age-friendly future. However, minimal attention has been given to the walking behavior of older adults on a large spatial and temporal scale. This study leveraged big data from mobile phones to decode the spatiotemporal patterns of seniors’ walking behavior, using Shenzhen, China, as a case study. We identified over 27 million elderly walking trips from April to September 2021 and utilized census data to validate the representativeness of older adults’ mobile phone data. The results showed that older adults’ walking trips were largely clustered in urban areas and suburban subcenters. The average number of senior walking trips in urban neighborhoods was 3.8 times higher than in suburbs. We quantified the differences in walking spatial patterns of seniors and younger adults, and found a prominent disparity in urban areas, where 88% of urban neighborhoods had a higher proportion of walking trips for seniors. Regarding temporal patterns, elderly walking trips generally started and ended earlier than those of younger people, and did not have significant peak hours. The unique spatiotemporal patterns of walking behavior of older adults highlight the need for targeted efforts to design walkable and inclusive cities.