Utilizing large-scale human mobility data to identify determinants of physical activity

Analyzing the habits of exercisers is crucial for developing targeted interventions that can effectively promote long-term physical activity behavior. While much of existing literature has focused on individual-level factors, there is a growing recognition of the importance of examining how broader determinants impact physical activity. In this study, we analyze large-scale human mobility data from over 20 million individuals to investigate how visits to various locations, such as cafes and restaurants, influence visits to fitness centers. In particular, we (i) rank categories of locations that exercisers prefer to visit, (ii) compare visiting patterns between individuals who visit fitness centers and those who do not, (iii) investigate how exercisers replace fitness visits on non-exercise days, and (iv) identify location categories mainly visited before or after fitness sessions. We show that individuals engaging in physical exercise prefer to visit "Non-Alcoholic Beverage Bars" (e.g., Starbucks) in conjunction with their exercise sessions. On their rest days, they often substitute exercise with visits to full-service restaurants and parks. Moreover, they tend to visit grocery stores immediately after their exercise session. Our findings can help public health policy towards a more targeted promotion of exercise and well-being.

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Publication Details

Journal
Scientific Reports
Published
2025-01-27
DOI
https://doi.org/10.1038/s41598-025-87017-4
Citations
2
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
4.35

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article

Utilizing large-scale human mobility data to identify determinants of physical activity

Marios D. Dikaiakos, Christos Nicolaides, George Pallis, Giorgos Ioannou
2 citations
Scientific Reports
Human Mobility and Location-Based Analysis
4.35
article

Utilizing large-scale human mobility data to identify determinants of physical activity

Marios D. Dikaiakos, Christos Nicolaides, George Pallis, Giorgos Ioannou
article en
2 citations

Abstract

Analyzing the habits of exercisers is crucial for developing targeted interventions that can effectively promote long-term physical activity behavior. While much of existing literature has focused on individual-level factors, there is a growing recognition of the importance of examining how broader determinants impact physical activity. In this study, we analyze large-scale human mobility data from over 20 million individuals to investigate how visits to various locations, such as cafes and restaurants, influence visits to fitness centers. In particular, we (i) rank categories of locations that exercisers prefer to visit, (ii) compare visiting patterns between individuals who visit fitness centers and those who do not, (iii) investigate how exercisers replace fitness visits on non-exercise days, and (iv) identify location categories mainly visited before or after fitness sessions. We show that individuals engaging in physical exercise prefer to visit "Non-Alcoholic Beverage Bars" (e.g., Starbucks) in conjunction with their exercise sessions. On their rest days, they often substitute exercise with visits to full-service restaurants and parks. Moreover, they tend to visit grocery stores immediately after their exercise session. Our findings can help public health policy towards a more targeted promotion of exercise and well-being.

Scientific ReportsVol. 15(1)
University of Cyprus (CY)
European Commission, HORIZON EUROPE Framework Programme, H2020 Marie Skłodowska-Curie Actions
Reduced inequalities
Openalex Percentile: Top 9%
Human Mobility and Location-Based Analysis
4.35
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Utilizing large-scale human mobility data to identify determinants of physical activity — Marios D. Dikaiakos, Christos Nicolaides, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS