What factors influence the willingness and intensity of regular mobile physical activity?- A machine learning analysis based on a sample of 290 cities in China.

Journal: Frontiers in public health
PMID: 39916701

Abstract

INTRODUCTION: This study, based on Volunteered Geographic Information (VGI) and multi-source data, aims to construct an interpretable macro-scale analytical framework to explore the factors influencing urban physical activities. Using 290 prefecture-level cities in China as samples, it investigates the impact of socioeconomic, geographical, and built environment factors on both overall physical activity levels and specific types of mobile physical activities.

Authors

  • Hao Shen
  • Bo Shu
    School of Design, Southwest Jiaotong University, Chengdu, China.
  • Jian Zhang
    College of Pharmacy, Ningxia Medical University, Yinchuan, NingxiaHui Autonomous Region, China.
  • Yaoqian Liu
    ENT Institute and Otorhinolaryngology Department of Eye and ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
  • Ali Li
    Information and Network Management Center, Xihua University, Chengdu, China.

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