Evidence map›Paper›PMID 37950859›Full record

ArticleEuropean heart journal2024

Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium.

Joanna M Blodgett, Matthew N Ahmadi, Andrew J Atkin, Sebastien Chastin, Hsiu-Wen Chan, Kristin Suorsa, Esmee A Bakker, Pasan Hettiarcachchi, Peter J Johansson, Lauren B Sherar and 14 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in European heart journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 4 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

76 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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16 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

24 authors.

Joanna M BlodgettInstitute of Sport Exercise and Health, Division of Surgery and Interventional Sciences, University College London, London , UK.ORCID 0000-0001-7684-3571
Matthew N AhmadiMackenzie Wearables Research Hub, Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-3115-338X
Andrew J AtkinSchool of Health Sciences and Norwich Epidemiology Centre, University of East Anglia, Norwich, UK.
Sebastien ChastinSchool of Health and Life Science Glasgow Caledonian University, Glasgow, UK.
Hsiu-Wen ChanSchool of Public Health, The University of Queensland, Brisbane, Queensland, Australia.
Kristin SuorsaDepartment of Public Health, University of Turku and Turku University Hospital, Turku, Finland.ORCID 0000-0002-3520-8069
Esmee A BakkerDepartment of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain.
Pasan HettiarcachchiOccupational and Environmental Medicine, Department of Medical Sciences, Uppsala University, Sweden.
Peter J JohanssonOccupational and Environmental Medicine, Department of Medical Sciences, Uppsala University, Sweden.
Lauren B SherarSchool of Sport, Exercise and Health Sciences, Loughborough University, UK.
Vegar RangulHUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Norway.
Richard M PulsfordFaculty of Health and Life Sciences, University of Exeter, UK.
Gita MishraSchool of Public Health, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0001-9610-5904
Thijs M H EijsvogelsDepartment of Medical BioSciences, Exercise Physiology ResearchGroup, Radboud University Medical Center, Nijmegen, The Netherlands.
Sari StenholmSchool of Public Health, The University of Queensland, Brisbane, Queensland, Australia.
Alun D HughesMRC Unit for Lifelong Health and Ageing, UCL Institute of Cardiovascular Science, UCL, UK.ORCID 0000-0001-5432-5271
Armando M Teixeira-PintoSchool of Public Health, Faculty of Medicine and Health, University of Sydney, Australia.
Ulf EkelundDepartment of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Norway.
I-Min LeeDivision of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Andreas HoltermannNational Research Centre for the Working Environment, Copenhagen, Denmark.
Annemarie KosterDepartment of Social Medicine, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands.
Emmanuel StamatakisMackenzie Wearables Research Hub, Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia.ORCID 0000-0001-7323-3225
Mark HamerInstitute of Sport Exercise and Health, Division of Surgery and Interventional Sciences, University College London, London , UK.ORCID 0000-0002-8726-7992
ProPASS Collaboration

Funding

British Heart Foundation SP/F/20/150002Wellcome Trust
6 · The paper itself

Abstract

BACKGROUND AND

aimsPhysical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers.

methodsCross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours.

resultsThe average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with -0.63 (95% confidence interval -0.48, -0.79), -0.43 (-0.25, -0.59), -0.40 (-0.25, -0.56), and -0.15 (0.05, -0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day.

conclusionsCompositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.

Indexed as

Cardiovascular DiseasesSitting PositionAdultCholesterol, HDLCross-Sectional StudiesExerciseFemaleGlycated HemoglobinHumansMaleMiddle AgedProspective StudiesSleepTriglyceridesCholesterol, HDLGlycated HemoglobinTriglyceridesCardiometabolic outcomesCohort consortiumCompositional data analysisPhysical activitySedentary behaviourSleepStanding

Identifiers

PMID37950859
PMCPMC10849343

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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.