Evidence map›Paper›PMID 40929102›Full record

ArticlePloS one2025

Age-related change in children's physical activity and sedentary time: The International Children's Accelerometry Database (ICAD).

Andrew J Atkin, Lauren B Sherar, Ulf Ekelund, Bjorge H Hansen, Lars Bo Andersen, Sigmund Anderssen, Susi Kriemler, Soyang Kwon, Peter L Kristensen, Niels Wedderopp and 8 more

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. 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

18 authors.

Andrew J AtkinSchool of Health Sciences, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, United Kingdom.ORCID https://orcid.org/0000-0002-3819-3448
Lauren B SherarSchool of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom.
Ulf EkelundDepartment of Sport Medicine, Norwegian School of Sport Science, Oslo, Norway.
Bjorge H HansenDepartment of Sport Science and Physical Education, University of Agder, Kristiansand, Norway.
Lars Bo AndersenFaculty of Teacher Education and Sport, Western Norway University of Applied Sciences, Sogndal, Norway.
Sigmund AnderssenDepartment of Sport Medicine, Norwegian School of Sport Science, Oslo, Norway.
Susi KriemlerEpidemiology, Biostatistics and Prevention Institute, University of Zürich, Zürich, Switzerland.
Soyang KwonDepartment of Emergency Medicine, Buehler Center for Health Economics and Policy, Northwestern University, Chicago, United States of America.
Peter L KristensenDepartment of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
Niels WedderoppDepartment of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
Kate NorthstonePopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Russell JagoPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Russell PateDepartment of Exercise Science, University of South Carolina, Columbia, United States of America.
Jardena J PuderObstetric Service, Department Woman-Mother-Child, Lausanne University Hospital, Lausanne, Switzerland.
Jo SalmonInstitute for Physical Activity and Nutrition Research, Deakin University, Melbourne, Australia.ORCID https://orcid.org/0000-0002-4734-6354
Luis B SardinhaExercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal.
Esther M F van SluijsMRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom.
International Children’s Accelerometry Database (ICAD) collaborators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany young people fail to achieve the minimum recommended amount of physical activity to benefit their health. Understanding the nature of age-related changes in behaviour and how this varies for population sub-groups is informative for intervention design. The aim of this study was to describe age-related changes in physical activity and sedentary time and examine variability in patterns of change across demographic sub-groups.

methodsData are from 13 studies in the International Children's Accelerometry Database (ICAD), all of which provided ≥2 waves of waist-worn accelerometer data. Annual change in sedentary time, light intensity physical activity (LPA) and moderate to vigorous intensity physical activity (MVPA) were estimated using three level mixed effects linear regression models, using participant age as the exposure variable. In interaction models, we examined whether changes in behaviour differed by day of the week (weekday/ weekend), age at baseline assessment (<10/ ≥ 10 years), sex, weight category, maternal education and ethnicity.

resultsIn total, 6567 participants provided two or more waves of valid accelerometer data (44.5% boys, mean (SD) baseline age 10.6 (2.1) years (range 4.1-15.8 years)). Across the week and for all studied sub-groups, sedentary time increased by approximately 25 minutes/day/year of age, LPA decreased by approximately 22 minutes/day/year of age and MVPA decreased by approximately 3 minutes/day/year of age. The annual increase in sedentary time was greater in girls compared to boys (β (95% confidence interval) change (min) for each additional year of age: girls, 25.9 (25.4, 26.4); boys, 23.6 (23.0, 24.2)) and in adolescents compared to children (adolescents, 27.0 (26.5, 27.6); children, (23.5 (22.9, 24.2)). The annual decrease in MVPA was greater in boys compared to girls (boys, -2.7 (-3.0, -2.5); girls, -2.2 (-2.4, -2.0)) and at the weekend compared to during the week (weekend, -3.0 (-3.3, -2.8); weekday -2.3 (-2.5, -2.1)).

conclusionAccelerometer assessed sedentary time increased whilst LPA and MVPA decreased during childhood and adolescence. This overall pattern was observed across the week and in all studied sub-groups, but small differences in the magnitude of changes can be used to guide the timing and targeting of behaviour change interventions, such as designing physical activity interventions which focus on weekends where a child's time is less structured.

Indexed as

AccelerometryExerciseSedentary BehaviorAdolescentAge FactorsChildChild, PreschoolDatabases, FactualFemaleHumansMale

Identifiers

PMID40929102
PMCPMC12422510

What OpenQuestion holds

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LicenceCC BY
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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.