Cited by 828Physical Activity and HealthObesity, Physical Activity, DietContext-Aware Activity Recognition Systems

The DOI matches its Crossref record; 37 of the 39 references it cites were found in a registry or an index; none of the 6 sources its claims cite is checked for support yet.

Objectively measured physical activity and sedentary time in youth: the International Children's Accelerometry Database (ICAD)

Open access

Abstract

BACKGROUND: Physical activity and sedentary behaviour in youth have been reported to vary by sex, age, weight status and country. However, supporting data are often self-reported and/or do not encompass a wide range of ages or geographical locations. This study aimed to describe objectively-measured physical activity and sedentary time patterns in youth. METHODS: The International Children's Accelerometry Database (ICAD) consists of ActiGraph accelerometer data from 20 studies in ten countries, processed using common data reduction procedures. Analyses were conducted on 27,637 participants (2.8-18.4 years) who provided at least three days of valid accelerometer data. Linear regression was used to examine associations between age, sex, weight status, country and physical activity outcomes. RESULTS: Boys were less sedentary and more active than girls at all ages. After 5 years of age there was an average cross-sectional decrease of 4.2% in total physical activity with each additional year of age, due mainly to lower levels of light-intensity physical activity and greater time spent sedentary. Physical activity did not differ by weight status in the youngest children, but from age seven onwards, overweight/obese participants were less active than their normal weight counterparts. Physical activity varied between samples from different countries, with a 15-20% difference between the highest and lowest countries at age 9-10 and a 26-28% difference at age 12-13. CONCLUSIONS: Physical activity differed between samples from different countries, but the associations between demographic characteristics and physical activity were consistently observed. Further research is needed to explore environmental and sociocultural explanations for these differences.

Overview

AI snapshot

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TL;DR

This pooled analysis of ActiGraph accelerometer data from 20 studies in ten countries described physical activity and sedentary time in 27,637 youth aged 2.8–18.4 years. It found consistent sex, age, and weight-status differences, plus substantial between-country variation, despite use of common data-reduction procedures.

Key findings

  • Boys were less sedentary and more active than girls at all ages. After age 5, total physical activity decreased cross-sectionally by an average of 4.2% per additional year (3.7% in boys, 4.6% in girls), mainly through lower light-intensity activity and greater sedentary time.
  • Physical activity did not differ by weight status in the youngest children, but from age seven onwards overweight/obese participants were less active than normal-weight peers; this showed a dose–response relationship in both sexes and was particularly large in boys.
  • Between-country differences were substantial: at age 9–10 the difference between the least active population (Madeira) and most active (Oslo, Norway) was 15–20% (156 cpm in boys, 613 vs. 769; 99 cpm in girls, 561 vs. 660), and at age 12–13 it was 26–28%.
  • Among 5–17 year olds in ICAD, only 9.0% of boys and 1.9% of girls achieved ≥60 min MVPA every valid day; ≥60 min MVPA was accumulated on 46% of valid days for boys and 22% for girls, with Norwegian boys aged 9–10 recording the highest values (60.5% of measured days).

Methods

  • ICAD pooled ActiGraph accelerometer data from 20 studies in ten countries using a standard data-reduction procedure. Analyses included 27,637 participants (92% of 29,967 potential participants) aged 2.8–18.4 years with at least 3 valid days (mean 5.3, range 3–7), providing 188,416 valid days across 35,360 time points.
  • Linear regression examined cross-sectional associations between age, sex, weight status, and physical activity outcomes, adjusted for study and season; robust standard errors accounted for repeated measures within participants. Country comparisons were restricted to ages 9–15 and ten studies from eight countries, using standardized within-country outcomes and random-effects meta-analysis.
  • Physical activity outcomes included average accelerometer counts per minute (cpm) and percentage time sedentary (≤100 cpm), light (101–2295 cpm), and moderate-to-vigorous (≥2296 cpm). Guideline achievement was presented as ≥60 min MVPA on every valid day and as the percentage of valid days with ≥60 min MVPA.

Limitations

  • The paper states that the sample was skewed toward ages 9–15 (82% of measurement time points) and the UK and USA (73% of measurement time points); some countries had too few participants for country-level analysis, countries were not globally representative, and low- and middle-income countries were underrepresented. Most samples were not nationally representative, though generally at least regionally representative.
  • The paper states accelerometer limitations: waist-worn accelerometers poorly record upper-body activity and cycling, potentially underestimating activity in high-cycling countries such as Denmark; they misclassify motionless-standing as sedentary, potentially overestimating sedentary time; and the MVPA thresholds perform poorly for ages 4–6 and are not validated under age 4.
  • The paper notes that direction of causation between weight status and physical activity was not investigated and may be bidirectional, and that individual, social, and environmental explanations for between-country differences were not explored. Evident from the text: girls were over-represented (59%, falling to 52% after excluding one large study of adolescent girls), which may affect descriptive proportions.

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Integrity signals

Registry

Crossref · 10.1186/s12966-015-0274-5

Cites

37 of 37 references verified0 citation errors · 0 not checkable

Statistics

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Figures

Fig. 1 Physical activity level by age and sex, according to different activity metrics. a Total physical activity (accelerometer counts per minute); b Percentage time in Moderate to Vigorous Physical activity (MVPA); c Percentage time in light intensity physical activity; d Percentage time sedentary. CI = confidence interval, cpm = counts per minute. In all graphs, boys aged 5–6 are the reference population. All graphs present mean differences in physical activity variables, adjusting for study population and season.
Fig. 1 Physical activity level by age and sex, according to different activity metrics. a Total physical activity (accelerometer counts per minute); b Percentage time in Moderate to Vigorous Physical activity (MVPA); c Percentage time in light intensity physical activity; d Percentage time sedentary. CI = confidence interval, cpm = counts per minute. In all graphs, boys aged 5–6 are the reference population. All graphs present mean differences in physical activity variables, adjusting for study population and season.CC BY · PubMed Central
Fig. 2 Association between weight status and physical activity. a Total physical activity (accelerometer counts per minute) by age, sex and weight status; b Dose response relationship between total physical activity and BMI by sex CI = confidence interval, owt = overweight, cpm = counts per minute
Fig. 2 Association between weight status and physical activity. a Total physical activity (accelerometer counts per minute) by age, sex and weight status; b Dose response relationship between total physical activity and BMI by sex CI = confidence interval, owt = overweight, cpm = counts per minuteCC BY · PubMed Central
Fig. 3 Average activity counts per minute across selected countries. a Level of physical activity across selected countries at age 9–10. b Level of physical activity across selected countries at age 12–13. CI = confidence interval. The Australian sample pools the two ICAD studies collected in Melbourne; both produced similar findings when analysed separately
Fig. 3 Average activity counts per minute across selected countries. a Level of physical activity across selected countries at age 9–10. b Level of physical activity across selected countries at age 12–13. CI = confidence interval. The Australian sample pools the two ICAD studies collected in Melbourne; both produced similar findings when analysed separatelyCC BY · PubMed Central
Fig. 4 Achievement of physical activity guidelines across selected countries. a Average percentage of participants achieving ≥60 min of MVPA each measurement day. b Average percentage of days on which ≥60 min of MVPA were recorded
Fig. 4 Achievement of physical activity guidelines across selected countries. a Average percentage of participants achieving ≥60 min of MVPA each measurement day. b Average percentage of days on which ≥60 min of MVPA were recordedCC BY · PubMed Central
Fig. 5 Comparison between selected countries of the relative effect of sex, age and weight status. a Difference in physical activity by sex in selected countries at ages 9–10 and 12–13. b Longitudinal change in physical activity per year of increasing age. c Difference in physical activity associated with higher BMI in selected countries at ages 9–10 and 12–13. SD = standard deviation. Forest plots display random-effects meta-analysis. The estimates for each country were calculated from regression models adjusted for age, sex and season, fitted to each country in turn
Fig. 5 Comparison between selected countries of the relative effect of sex, age and weight status. a Difference in physical activity by sex in selected countries at ages 9–10 and 12–13. b Longitudinal change in physical activity per year of increasing age. c Difference in physical activity associated with higher BMI in selected countries at ages 9–10 and 12–13. SD = standard deviation. Forest plots display random-effects meta-analysis. The estimates for each country were calculated from regression models adjusted for age, sex and season, fitted to each country in turnCC BY · PubMed Central

Verification

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    No prior child and adolescent physical activity data pooling study had incorporated samples from such a diverse range of countries using consistent measures and methodology.

    “No child and adolescent physical activity data pooling studies have incorporated samples from such a diverse range of countries using consistent measures and methodology.”
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  1. WHO. Global recommendations on physical activity for health. Geneva: World Health Organisation; 2010.

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Metadata

Authors
Cooper, A. R., Goodman, A., Page, A. S., Sherar, L. B., Esliger, D. W., van Sluijs, E. M., Andersen, L. B., Anderssen, S., Cardon, G., Davey, R., Froberg, K., Hallal, P., Janz, K. F., Kordas, K., Kreimler, S., Pate, R. R., Puder, J. J., Reilly, J. J., Salmon, J., Sardinha, L. B., Timperio, A., & Ekelund, U.
Affiliations
  • National Institute for Health and Care Research (GB)
  • London School of Hygiene & Tropical Medicine (GB)
  • University of Bristol (GB)
  • Loughborough University (GB)
  • University of Southern Denmark (DK)
  • Norwegian School of Sport Sciences (NO)
  • Ghent University (BE)
  • University of Canberra (AU)
  • Universidade Federal de Pelotas (BR)
  • University of Iowa (US)
  • University of Zurich (CH)
  • Centre Hospitalier Universitaire Vaudois (CH)
  • University of Strathclyde (GB)
  • Deakin University (AU)
Corresponding author
Cooper, Ashley R.
Venue
International Journal of Behavioral Nutrition and Physical Activity
Published
2015-09-17
Volume
12
Issue
1
Pages
113-113
ISSN
1479-5868 (ISSN-L)
OpenAlex
W2143709617
Cited by
828
References
39
Citations by year
2026: 28 · 2025: 55 · 2024: 79 · 2023: 86 · 2022: 91 · 2021: 106 · 2020: 119 · 2019: 108 · 2018: 71 · 2017: 51 · 2016: 31 · 2015: 1
FWCI
37.83
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • International Journal of Behavioral Nutrition and Physical Activity (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Bristol Research (University of Bristol) (publishedVersion, cc-by)
  • University of Southern Denmark Research Portal (University of Southern Denmark) (publishedVersion, cc-by)
  • SERVAL (Université de Lausanne) (publishedVersion, other-oa)
  • Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) (acceptedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • Ghent University Academic Bibliography (Ghent University) (submittedVersion, other-oa)
  • IRIS (submittedVersion)
  • University of Canberra Research Portal (submittedVersion, cc-by)
  • Loughborough University Institutional Repository (Loughborough University) (submittedVersion, cc-by)
  • Figshare (submittedVersion)
  • Loughborough University Research Repository (Loughborough University) (submittedVersion, cc-by)
  • NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
  • Explore Bristol Research (submittedVersion, cc-by)
  • Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by)
Funders
Medical Research Council (G0701877)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords
physical activity, sedentary behavior, youth, children, adolescents, accelerometer-measured activity, sex differences, age differences, overweight and obesity, cross-national variation, light physical activity
MeSH terms
Adolescent, Body Weight, Child, Child, Preschool, Cross-Sectional Studies, Family, Female, Humans, Male, Motor Activity, Obesity, Time Factors, Databases, Factual, Age Distribution, Sex Distribution, Internationality, Overweight, Sedentary Behavior, Self Report, Accelerometry

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