Evidence map›Paper›PMID 40398408›Full record

ArticleMedicine and science in sports and exercise2025

Tracking and Trajectory Analysis of Active Commuting from Childhood to Midlife.

Xiaolin Yang, Tuomas Kukko, Kasper Salin, Janne Kulmala, Suvi P Rovio, Katja Pahkala, Terho Lehtimäki, Olli T Raitakari, Tuija H Tammelin

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Article in Medicine and science in sports and exercise, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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9 authors.

Xiaolin YangLikes, School of Health and Social Studies, Jamk University of Applied Sciences, Jyväskylä, FINLAND.
Tuomas KukkoLikes, School of Health and Social Studies, Jamk University of Applied Sciences, Jyväskylä, FINLAND.
Kasper SalinFaculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND.
Janne KulmalaLikes, School of Health and Social Studies, Jamk University of Applied Sciences, Jyväskylä, FINLAND.
Suvi P Rovio
Katja Pahkala
Terho LehtimäkiDepartment of Clinical Chemistry, Fimlab Ltd., and Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center-Tampere, Tampere University, Tampere, FINLAND.
Olli T Raitakari
Tuija H TammelinLikes, School of Health and Social Studies, Jamk University of Applied Sciences, Jyväskylä, FINLAND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo examine the tracking and trajectories of active commuting (AC) from childhood to midlife and their association with physical activity (PA) levels over 35 yr.

methodsSelf-rated AC and PA data were extracted from the Young Finns Study across six phases (1983-2018) for tracking ( n = 2851) and trajectories ( n = 1220). Accelerometer-derived PA was quantified in 2018-2020 ( n = 1371). AC tracking was analyzed using Spearman's correlation, percentage agreements, and kappa statistics. Latent class analysis was used to identify distinct AC trajectories, and their associations with adult PA were subsequently evaluated.

resultsTracking correlations of AC over 3-4, 6-7, 15, 18, and 35 yr for both sexes were 0.40-0.43, 0.30-0.33, 0.25-0.32, 0.20-0.23, and 0.15-0.22 in summer, and 0.38-0.42, 0.35-0.41, 0.30-0.40, 0.25-0.33, and 0.23-0.31 in winter, respectively. Percentage agreements exceeded 54%, with kappa statistics ranging from slight to fair over time. Based on AC trajectories, four classes were identified for men (M) and five for women (W): stable car commuting (M: 58.9%, W: 37.4%), decreasing AC (M: 16.5%, W: 22.2%), increasing AC (M: 12.8%, W: 17.3%), and stable AC (M: 11.8%), stable active walking (W: 12.2%), and stable active summer cycling (W: 10.8%). Compared with stable car-commuting ones, women who consistently walked or cycled in summer had higher adult moderate-to-vigorous PA and step counts. Men with consistent AC accumulated more steps and higher self-reported PA. Increasing AC in men also reported higher total PA. Stable AC participants were more physically active on weekdays, whereas men in the increased AC group were more active on weekends.

conclusionsTracking of AC from childhood to mid-adulthood was low to moderately high. Stable and increasing AC trajectories predicted higher adult PA levels during weekdays or weekends.

Indexed as

BicyclingExerciseTransportationAccelerometryAdolescentAdultChildFemaleFinlandHumansMaleMiddle AgedSeasonsSelf ReportWalkingYoung AdultACCELEROMETERADULTCYCLINGFOLLOW-UPWALKINGYOUTH

Identifiers

PMID40398408
PMCPMC13007902

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LicenceCC BY-NC-ND
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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.