Evidence map›Paper›PMID 39123109›Full record

ArticleBMC medical research methodology2024

School-level intra-cluster correlation coefficients and autocorrelations for children's accelerometer-measured physical activity in England by age and gender.

Ruth Salway, Russell Jago, Frank de Vocht, Danielle House, Alice Porter, Robert Walker, Ruth Kipping, Christopher G Owen, Mohammed T Hudda, Kate Northstone and 2 more

Abstract read
In one paragraph

Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Designing stepped wedge trials to evaluate physical activity interventions in schools: methodological considerations.The international journal of behavioral nutrition and physical activity · 2025
    Article
4 · The record

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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

12 authors.

Ruth SalwayPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK. Ruth.Salway@bristol.ac.uk.
Russell JagoPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Frank de VochtPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Danielle HousePopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Alice PorterPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Robert WalkerPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Ruth KippingPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Christopher G OwenPopulation Health Research Institute, St George's, University of London, London, UK.
Mohammed T HuddaDepartment of Population Health, Dasman Diabetes Institute, Kuwait City, Kuwait.
Kate NorthstonePopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Esther van SluijsMRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
International Children’s Accelerometry Database (ICAD) Collaborators

Funding

Medical Research Council G0701877Medical Research Council MC_UU_00006/5Medical Research Council MC_UU_12015/3Medical Research Council MC_UU_12015/7UK National Institute for Health Research (NIHR) 09/3005/04UK Research and Innovation EP/X023508/1Wellcome Trust 068362/Z/02/Z
6 · The paper itself

Abstract

backgroundRandomised, cluster-based study designs in schools are commonly used to evaluate children's physical activity interventions. Sample size estimation relies on accurate estimation of the intra-cluster correlation coefficient (ICC), but published estimates, especially using accelerometry-measured physical activity, are few and vary depending on physical activity outcome and participant age. Less commonly-used cluster-based designs, such as stepped wedge designs, also need to account for correlations over time, e.g. cluster autocorrelation (CAC) and individual autocorrelation (IAC), but no estimates are currently available. This paper estimates the school-level ICC, CAC and IAC for England children's accelerometer-measured physical activity outcomes by age group and gender, to inform the design of future school-based cluster trials.

methodsData were pooled from seven large English datasets of accelerometer-measured physical activity data between 2002-18 (> 13,500 pupils, 540 primary and secondary schools). Linear mixed effect models estimated ICCs for weekday and whole week for minutes spent in moderate-to-vigorous physical activity (MVPA) and being sedentary for different age groups, stratified by gender. The CAC (1,252 schools) and IAC (34,923 pupils) were estimated by length of follow-up from pooled longitudinal data.

resultsSchool-level ICCs for weekday MVPA were higher in primary schools (from 0.07 (95% CI: 0.05, 0.10) to 0.08 (95% CI: 0.06, 0.11)) compared to secondary (from 0.04 (95% CI: 0.03, 0.07) to (95% CI: 0.04, 0.10)). Girls' ICCs were similar for primary and secondary schools, but boys' were lower in secondary. For all ages, combined the CAC was 0.60 (95% CI: 0.44-0.72), and the IAC was 0.46 (95% CI: 0.42-0.49), irrespective of follow-up time. Estimates were higher for MVPA vs sedentary time, and for weekdays vs the whole week.

conclusionsAdequately powered studies are important to evidence effective physical activity strategies. Our estimates of the ICC, CAC and IAC may be used to plan future school-based physical activity evaluations and were fairly consistent across a range of ages and settings, suggesting that results may be applied to other high income countries with similar school physical activity provision. It is important to use estimates appropriate to the study design, and that match the intended study population as closely as possible.

Indexed as

AccelerometryExerciseSchoolsAdolescentAge FactorsChildCluster AnalysisEnglandFemaleHumansMaleSex FactorsAdolescentsChildrenCluster autocorrelationCluster randomised trialICADIntra-cluster correlation coefficientPhysical activitySample sizeSchools

Identifiers

PMID39123109
PMCPMC11313128

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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.