Evidence map›Paper›PMID 32423404›Full record

ArticleThe international journal of behavioral nutrition and physical activity2020

Tracking of total sedentary time and sedentary patterns in youth: a pooled analysis using the International Children's Accelerometry Database (ICAD).

Evi van Ekris, Katrien Wijndaele, Teatske M Altenburg, Andrew J Atkin, Jos Twisk, Lars B Andersen, Kathleen F Janz, Karsten Froberg, Kate Northstone, Angie S Page and 4 more

Open access · goldAbstract read
In one paragraph

Article in The international journal of behavioral nutrition and physical activity, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 4 pooled it
8.1field-weighted citation impact, top 2% of its field
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

25 citing papers in PubMed, 4 syntheses or guidelines pooled it, 62 citations in OpenAlex.

  1. Pooled it
  2. Interventions to prevent obesity in children aged 2 to 4 years old.The Cochrane database of systematic reviews · 2025
    Pooled it
  3. Pooled it
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  16. Gender differences in the distribution of children's physical activity: evidence from nine countries.The international journal of behavioral nutrition and physical activity · 2023
    Article
  17. Article
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  19. Review
  20. Assessment of Motor Abilities and Physical Fitness in Youth in the Context of Talent Identification-OSF Test.International journal of environmental research and public health · 2022
    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

14 authors at 8 institutions in 6 countries.

Evi van EkrisDepartment of Public and Occupational Health, Amsterdam Public Health research institute, VU University Medical Center, van der Boechorststraat 7, 1081BT, Amsterdam, the Netherlands. e.vanekris@vumc.nl.
Katrien WijndaeleMRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
Teatske M AltenburgDepartment of Public and Occupational Health, Amsterdam Public Health research institute, VU University Medical Center, van der Boechorststraat 7, 1081BT, Amsterdam, the Netherlands.ORCID 0000-0002-8764-5631
Andrew J AtkinCentre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
Jos TwiskDepartment of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands.
Lars B AndersenFaculty of Teacher Education and Sport, Western Norway University of Applied Sciences, Sogndal, Norway.
Kathleen F JanzDepartment of Health and Human Physiology, University of Iowa, Iowa City, USA.
Karsten FrobergResearch of Childhood Health, University of Southern Denmark, Odense, Denmark.
Kate NorthstoneDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Angie S PageCentre for Exercise, Nutrition and Health Sciences, University of Bristol, Bristol, UK.
Luis B SardinhaExercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal.
Esther M F van SluijsCentre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
Mai ChinapawDepartment of Public and Occupational Health, Amsterdam Public Health research institute, VU University Medical Center, van der Boechorststraat 7, 1081BT, Amsterdam, the Netherlands.
International Children’s Accelerometry Database (ICAD) Collaborators
University of Cambridge · GBAmsterdam UMC Location Vrije Universiteit Amsterdam · NLUniversity of Iowa · USUniversity of Lisbon · PTUniversity of Bristol · GBUniversity of East Anglia · GBUniversity of Southern Denmark · DKWestern Norway University of Applied Sciences · NO

Funding

British Heart Foundation FS/12/58/29709Cancer Research UKChief Scientist OfficeDepartment of HealthMedical Research Council G0701877Medical Research Council MC_PC_15018Medical Research Council MC_PC_19009Medical Research Council MC_UU_00006/4Medical Research Council MC_UU_00006/5Medical Research Council MC_UU_12015/3Medical Research Council MC_UU_12015/ 7Medical Research Council MC_UU_12015/7Medical Research Council MR/K023187/1Wellcome Trust 102215/2/13/2Wellcome Trust MR/K023187/1
6 · The paper itself

Abstract

backgroundTo gain more understanding of the potential health effects of sedentary time, knowledge is required about the accumulation and longitudinal development of young people's sedentary time. This study examined tracking of young peoples' total and prolonged sedentary time as well as their day-to-day variation using the International Children's Accelerometry Database.

methodsLongitudinal accelerometer data of 5991 children (aged 4-17y) was used from eight studies in five countries. Children were included if they provided valid (≥8 h/day) accelerometer data on ≥4 days, including ≥1 weekend day, at both baseline and follow-up (average follow-up: 2.7y; range 0.7-8.2). Tracking of total and prolonged (i.e. ≥10-min bouts) sedentary time was examined using multilevel modelling to adjust for clustering of observations, with baseline levels of sedentary time as predictor and follow-up levels as outcome. Standardized regression coefficients were interpreted as tracking coefficients (low: < 0.3; moderate: 0.3-0.6; high: > 0.6).

resultsAverage total sedentary time at study level ranged from 246 to 387 min/day at baseline and increased annually by 21.4 min/day (95% confidence interval [19.6-23.0]) on average. This increase consisted almost entirely of prolonged sedentary time (20.9 min/day [19.2-22.7]). Total (standardized regression coefficient (B) = 0.48 [0.45-0.50]) and prolonged sedentary time (B = 0.43 [0.41-0.45]) tracked moderately. Tracking of day-to-day variation in total (B = 0.04 [0.02-0.07]) and prolonged (B = 0.07 [0.04-0.09]) sedentary time was low.

conclusionYoung people with high levels of sedentary time are likely to remain among the people with highest sedentary time as they grow older. Day-to-day variation in total and prolonged sedentary time, however, was rather variable over time.

Indexed as

AccelerometryDatabases, FactualFitness TrackersSedentary BehaviorAdolescentChildChild, PreschoolData Interpretation, StatisticalFemaleHumansMaleAccelerometerAdolescentsChildrenICADObjective assessmentSedentary timeTracking

Identifiers

PMID32423404
PMCPMC7236462
OpenAlexW3026213813

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.