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Updated: Jan 9, 2026
Comparative Analysis of Lower Limb Kinematics between the Initial and Terminal Phase of 5km Treadmill Running
Published on: July 17, 2020
Associations between the built environment and jogging behaviour based on voluntarily contributed tracking data: a
Dengkai Huang1, Wenjun Xu1, Marco Helbich2
1State Key Laboratory of Subtropical Building and Urban Science, School of Architecture and Urban Planning, Shenzhen University, Shenzhen, 518060, China.
Background:
Running is a widely promoted form of physical activity with significant public health benefits, yet the built environment influences its engagement. Existing evidence on the associations between the built environment and running behaviour remains heterogeneous, with prior reviews not quantifying the overall effect sizes. Additionally, gaps persist in understanding how emerging geospatial data, such as volunteered geographic information (VGI), can enhance insights into runnability.
Aim:
To provide (1) a comprehensive synthesis of the literature and meta-analysis of the evidence for the effects of the built environment on jogging behaviour, and (2) to identify methodological limitations and future research priorities for promoting running-inclusive cities.
Methods:
Three databases (the Web of Science Core Collection (WoS), Scopus, and PubMed) were systematically searched for English-language studies published up to December 31, 2024. Meta-analysis was conducted to obtain pooled elasticity values for the environmental factors.
Results:
Of the 1,884 studies identified, 39 studies fulfilled the inclusion criteria, and 14 studies were suitable for meta-analysis leveraging VGI-derived physical activity data. Meta-analysis revealed that floor area ratio had the largest effect size, followed by land use mix and blue space density. Distance to parks and public transport density showed minor effects. Natural environment features (e.g., blue space density and green view index) consistently correlated positively with running activity, while terrain slope exhibited context-dependent relationships. Critical methodological limitations included insufficient spatiotemporal analysis, overreliance on single-platform VGI data, and inconsistent geographic units.
Conclusions:
To advance runnability research, future studies should adopt dynamic spatiotemporal modelling, integrate multi-platform VGI with participatory GIS, and employ equity-focused metrics and demographic-stratified analyses. These strategies will inform evidence-based urban planning to create running-inclusive environments, ultimately supporting population health through targeted built environment interventions.
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