Evidence map›Paper›PMID 38744444›Full record

ArticleJournal of epidemiology and community health2024

Socioeconomic gradients in 24-hour movement patterns across weekends and weekdays in a working-age sample: evidence from the 1970 British Cohort Study.

Joanna M Blodgett, David Bann, Sebastien F M Chastin, Matthew Ahmadi, Emmanuel Stamatakis, Rachel Cooper, Mark Hamer

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Article in Journal of epidemiology and community health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Joanna M BlodgettInstitute of Sport, Exercise and Health, UCL, London, UK joanna.blodgett@ucl.ac.uk.ORCID 0000-0001-7684-3571
David BannCentre for Longitudinal Studies, Social Research Institute, UCL, London, UK.ORCID 0000-0002-6454-626X
Sebastien F M ChastinSchool of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UK.ORCID 0000-0003-1421-9348
Matthew AhmadiMackenzie Wearables Research Hub, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Emmanuel StamatakisMackenzie Wearables Research Hub, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Rachel CooperAGE Research Group, Newcastle University, Newcastle upon Tyne, UK.ORCID 0000-0003-3370-5720
Mark HamerInstitute of Sport, Exercise and Health, UCL, London, UK.

Funding

British Heart FoundationMedical Research Council
6 · The paper itself

Abstract

backgroundSocioeconomic differences in movement behaviours may contribute to health inequalities. The aim of this descriptive study was to investigate socioeconomic patterns in device-measured 24-hour movement and assess whether patterns differ between weekdays and weekends.

methods4894 individuals aged 46 years from the 1970 British Cohort Study were included. Participants wore thigh-worn accelerometers for 7 days. Movement behaviours were classified in two 24-hour compositions based on intensity and posture, respectively: (1) sleep, sedentary behaviour, light-intensity activity and moderate-vigorous activity; and (2) sleep, lying, sitting, standing, light movement, walking and combined exercise-like activity. Four socioeconomic measures were explored: education, occupation, income and deprivation index. Movement behaviours were considered compositional means on a 24-hour scale; isometric log ratios expressed per cent differences in daily time in each activity compared with the sample mean.

resultsAssociations were consistent across all socioeconomic measures. For example, those with a degree spent more time in exercise-like activities across weekdays (10.8%, 95% CI 7.3 to 14.7; ref: sample mean) and weekends (21.9%, 95% CI 17.2 to 26.9). Other patterns differed markedly by the day of the week. Those with no formal qualifications spent more time standing (5.1%, 95% CI 2.3 to 7.1), moving (10.8%, 95% CI 8.6 to 13.1) and walking(4.0%, 95% CI 2.2 to 6.1) during weekdays, with no differences on weekends. Conversely, those with no formal qualifications spent less time sitting during weekdays (-6.6%, 95% CI -7.8 to -4.8), yet more time lying on both weekends (8.8%, 95% CI 4.9 to 12.2) and weekdays (7.5%, 95% CI 4.0 to 11.5).

conclusionsThere were strong socioeconomic gradients in 24-hour movement behaviours, with notable differences between weekdays/weekends and behaviour type/posture. These findings emphasise the need to consider socioeconomic position, behaviour type/posture and the day of the week when researching or designing interventions targeting working-age adults.

Indexed as

ExerciseSedentary BehaviorSocioeconomic FactorsAccelerometryCohort StudiesFemaleHealth BehaviorHumansMaleMiddle AgedMovementSleepTime FactorsUnited KingdomWalkingCOHORT STUDIESEDUCATIONEPIDEMIOLOGYEXERCISESOCIAL CLASS

Identifiers

PMID38744444
PMCPMC11287567

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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.