ArticleFrontiers in public health2025
Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- From Health to Environment: Exploring the Associations Among Health Status, Health-Related Lifestyle, and Campus Environment in Chinese Universities.Healthcare (Basel, Switzerland) · 2026Article
- Unraveling nonlinear impacts of seasonal climate and built environments on exercise walking in high-density cities via a modified machine learning approach.International journal of health geographics · 2026Article
- Built environment determinants of residents' running activity in Guangzhou, China: what are the nonlinear relationship and pathways?BMC public health · 2025Article
- Socioeconomic status influences the relationship between residential green space and the risk of osteoporosis among rural adults: a large-scale population-based study.Frontiers in public health · 2025Observational
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Authors and funding
4 authors.
Funding
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Abstract
Introduction: University campuses, with their abundant natural resources and sports facilities, are essential in promoting walking activities among students, faculty, and nearby communities. However, the mechanisms through which campus environments influence walking activities remain insufficiently understood. This study examines universities in Wuhan, China, using crowdsourced data and machine learning methods to analyze the nonlinear and interactive effects of campus built environments on exercise walking. Methods: This study utilized crowdsourced exercise walking data and incorporated diverse campus characteristics to construct a multidimensional variable system. By applying the XGBoost algorithm and SHAP (SHapley Additive exPlanations), an explainable machine learning framework was established to evaluate the importance of various factors, explore the nonlinear relationships between variables and walking activity, and analyze the interaction effects among these variables. Results: The findings underscore the significant impact of several key factors, including the proportion of sports land, proximity to water bodies, and Normalized Difference Vegetation Index NDVI, alongside the notable influence of six distinct campus area types. The analysis of nonlinear effects revealed distinct thresholds and patterns of influence that differ from other urban environments, with some variables exhibiting fluctuated or U-shaped effects. Additionally, strong interactions were identified among variable combinations, highlighting the synergistic impact of elements like sports facilities, green spaces, and waterfront areas when strategically integrated. Conclusion: This research contributes to the understanding of how campus built environments affect walking activities, offering targeted recommendations for campus planning and design. Recommendations include optimizing the spatial configuration of sports facilities, green spaces, and water bodies to maximize their synergistic impacts on walking activity. These insights can foster the development of inclusive, health-promoting, and sustainable campuses.
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