Evidence map›Paper›PMID 39870707›Full record

ArticleScientific reports2025

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

Giorgos Ioannou, George Pallis, Marios Dikaiakos, Christos Nicolaides

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. The social environment and cognitive aging over the life course: laying out critical concepts and research gaps.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Giorgos IoannouDepartment of Computer Science, University of Cyprus, 2109, Aglantzia, Nicosia, Cyprus.
George PallisDepartment of Computer Science, University of Cyprus, 2109, Aglantzia, Nicosia, Cyprus.
Marios DikaiakosDepartment of Computer Science, University of Cyprus, 2109, Aglantzia, Nicosia, Cyprus.
Christos NicolaidesSchool of Economics and Management, University of Cyprus, 2109, Aglantzia, Nicosia, Cyprus. nicolaides.christos@ucy.ac.cy.

Funding

H2020 Marie Skłodowska-Curie Actions 813162
6 · The paper itself

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.

Indexed as

ExerciseAdultFemaleFitness CentersHumansMaleMiddle AgedExercise habitsGPS devicesHuman mobilitySocial networks

Identifiers

PMID39870707
PMCPMC11772751

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.