Evidence map›Paper›PMID 41608541›Full record

ArticleFrontiers in sports and active living2025

The self-selected intensity of physical activity during real-life e-bike commuting.

Amund Riiser, Eivind Aadland, Solveig Nordengen

Abstract read
In one paragraph

Article in Frontiers in sports and active living, 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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0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Amund RiiserDepartment of Sport, Food and Natural Sciences, Faculty of Education, Arts and Sports, Western Norway University of Applied Sciences, Sogndal, Norway.
Eivind AadlandDepartment of Sport, Food and Natural Sciences, Faculty of Education, Arts and Sports, Western Norway University of Applied Sciences, Sogndal, Norway.
Solveig NordengenDepartment of Sport, Food and Natural Sciences, Faculty of Education, Arts and Sports, Western Norway University of Applied Sciences, Sogndal, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Decreasing physical activity levels present a major public health challenge. The use of e-bikes has risen substantially over the past decade, presenting a potential solution to common barriers associated with physical activity and conventional cycling. However, the intensity of e-bike commuting in real-life settings remains unknown. This study aimed to investigate the self-selected intensity and the impact of topography on intensity during regular e-bike commuting. Methods: In this cross-sectional study, oxygen consumption, power output, heart rate, perceived exertion, and positional data were recorded from 19 commuters [mean (standard deviation) age 41 (8) years] during their regular commutes on their own e-bikes. Data were summarized and analyzed in 10, 30, and 60 s epochs, and adjusted for the duration of the commutes. Intensity of the commutes was compared between downhill, flat, or uphill segments using linear mixed models. The intensity of physical activity was defined as light <3 metabolic equivalents (METs), moderate 3-5.9 METs, or vigorous ≥6 METs. Results: Oxygen consumption during e-bike commuting was mean (standard deviation) 20.8 (5.0) mL/kg/min [5.9 (1.4) METs]. Depending on epoch lengths, 44%-48% of the commutes were classified as vigorous physical activity. Across epoch lengths, the mean intensity of the commutes was classified as moderate (4.6-4.8 METs) during downhill, moderate (5.5-5.9 METs) during flat, and vigorous (7.0-7.5 METs) during uphill riding ( Conclusions: Our findings suggest that e-bike commuters self-selected moderate to vigorous intensities during real-life commutes, aligning with international physical activity guidelines for improving public health. Therefore, policies promoting a shift from car use to e-biking could have significant public health benefits.

Indexed as

active travelelectric bikeshealthpedelecphysical activity

Identifiers

PMID41608541
PMCPMC12834821

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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.