打印

作者

Haoran Zhang;Jinyu Chen;Qi Chen;Tianqi Xia;Xin Wang;Wenjing Li;Xuan Song;Ryosuke Shibasaki

来源

CITIES,Vol.120,Issue1,Article 103452

语言

英文

关键字

Mobility-based indicator;Regional health level;Mobility behavior;Built environment

作者单位

Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan;School of Geography and Information Engineering, China University of Geosciences (Wuhan), 338 Lumo Road, Hongshan District, Wuhan City, Hubei Province, China;MOE Joint International Research Lab of Eco Urban Design, College of Architecture and Urban Planning, Tongji University, No.1239 Siping Rd., Shanghai 200092, China;SUSTech-UTokyo Joint Research Center on Super Smart City, Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China;Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan;School of Geography and Information Engineering, China University of Geosciences (Wuhan), 338 Lumo Road, Hongshan District, Wuhan City, Hubei Province, China;MOE Joint International Research Lab of Eco Urban Design, College of Architecture and Urban Planning, Tongji University, No.1239 Siping Rd., Shanghai 200092, China;SUSTech-UTokyo Joint Research Center on Super Smart City, Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China

摘要

Human mobility is attracting more attention in public health research; however, the existing paradigms typically lack a universal indicator to reveal the underlying mechanism for both urban and rural cases. Based on the large-scale datasets, including national survey, census, and billions of GPS trajectories, we found that the preference for choosing vehicles for travel can be a powerful and universal indicator for regional health levels. Firstly, we showed reliable evidence on the correlation among travel environment, travel behaviors, and health level. Then, we proposed a new travel inverse preference index that is a reliable measurement of unhealthy lifestyle levels and the age-corrected mortality rates within a particular region. The result further showed that multiple spatial environment factors, such as urbanization level, climates, and local walkability, are also strongly related to the indicator. Additionally, we conducted a comprehensive spatial analysis to develop strategic policies that the government could adopt for potential social improvement.