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The Physical Behaviour Intensity Spectrum and Body Mass Index in School-Aged Youth: A Compositional Analysis of Pooled Individual Participant Data

Author

Listed:
  • Stuart J. Fairclough

    (Movement Behaviours, Nutrition, Health & Wellbeing Research Group, Department Sport & Physical Activity, Edge Hill University, St Helens Road, Ormskirk L39 4QP, UK)

  • Liezel Hurter

    (Research Institute of Sport and Exercise Science, Liverpool John Moores University, Liverpool L3 3AF, UK)

  • Dorothea Dumuid

    (Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, SA 5001, Australia
    Centre for Adolescent Health, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia)

  • Ales Gába

    (Faculty of Physical Culture, Palacký University Olomouc, CZ 779 00 Olomouc, Czech Republic)

  • Alex V. Rowlands

    (Diabetes Research Centre, Leicester General Hospital, University of Leicester, Gwendolen Road, Leicester LE5 4PW, UK
    National Institute for Health Research (NIHR) Leicester Biomedical Research Centre (BRC), University Hospitals of Leicester NHS Trust and the University of Leicester, Leicester LE5 4PW, UK)

  • Borja del Pozo Cruz

    (Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, 5230 Odense, Denmark)

  • Ashley Cox

    (Movement Behaviours, Nutrition, Health & Wellbeing Research Group, Department Sport & Physical Activity, Edge Hill University, St Helens Road, Ormskirk L39 4QP, UK)

  • Matteo Crotti

    (Research Institute of Sport and Exercise Science, Liverpool John Moores University, Liverpool L3 3AF, UK)

  • Lawrence Foweather

    (Research Institute of Sport and Exercise Science, Liverpool John Moores University, Liverpool L3 3AF, UK)

  • Lee E. F. Graves

    (Research Institute of Sport and Exercise Science, Liverpool John Moores University, Liverpool L3 3AF, UK)

  • Owen Jones

    (Research Institute of Sport and Exercise Science, Liverpool John Moores University, Liverpool L3 3AF, UK)

  • Deborah A. McCann

    (Research Institute of Sport and Exercise Science, Liverpool John Moores University, Liverpool L3 3AF, UK)

  • Robert J. Noonan

    (Department of Psychology, University of Liverpool, Liverpool L69 7ZA, UK)

  • Michael B. Owen

    (Department of Applied Health and Social Care and Social Work, Faculty of Health, Social Care and Medicine, Edge Hill University, Ormskirk L39 4QP, UK)

  • James R. Rudd

    (Department of Teacher Education and Outdoor Studies, Norwegian School of Sport Sciences, 0863 Oslo, Norway)

  • Sarah L. Taylor

    (Research Institute of Sport and Exercise Science, Liverpool John Moores University, Liverpool L3 3AF, UK)

  • Richard Tyler

    (Movement Behaviours, Nutrition, Health & Wellbeing Research Group, Department Sport & Physical Activity, Edge Hill University, St Helens Road, Ormskirk L39 4QP, UK)

  • Lynne M. Boddy

    (Research Institute of Sport and Exercise Science, Liverpool John Moores University, Liverpool L3 3AF, UK)

Abstract

We examined the compositional associations between the intensity spectrum derived from incremental acceleration intensity bands and the body mass index (BMI) z-score in youth, and investigated the estimated differences in BMI z-score following time reallocations between intensity bands. School-aged youth from 63 schools wore wrist accelerometers, and data of 1453 participants (57.5% girls) were analysed. Nine acceleration intensity bands (range: 0–50 mg to ≥700 mg) were used to generate time-use compositions. Multivariate regression assessed the associations between intensity band compositions and BMI z-scores. Compositional isotemporal substitution estimated the differences in BMI z-score following time reallocations between intensity bands. The ≥700 mg intensity bandwas strongly and inversely associated with BMI z-score ( p < 0.001). The estimated differences in BMI z-score when 5 min were reallocated to and from the ≥700 mg band and reallocated equally among the remaining bands were −0.28 and 0.44, respectively (boys), and −0.39 and 1.06, respectively (girls). The time in the ≥700 mg intensity band was significantly associated with BMI z-score, irrespective of sex. When even modest durations of time in this band were reallocated, the asymmetrical estimated differences in BMI z-score were clinically meaningful. The findings highlight the utility of the full physical activity intensity spectrum over a priori-determined absolute intensity cut-point approaches.

Suggested Citation

  • Stuart J. Fairclough & Liezel Hurter & Dorothea Dumuid & Ales Gába & Alex V. Rowlands & Borja del Pozo Cruz & Ashley Cox & Matteo Crotti & Lawrence Foweather & Lee E. F. Graves & Owen Jones & Deborah , 2022. "The Physical Behaviour Intensity Spectrum and Body Mass Index in School-Aged Youth: A Compositional Analysis of Pooled Individual Participant Data," IJERPH, MDPI, vol. 19(14), pages 1-15, July.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:14:p:8778-:d:866227
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    References listed on IDEAS

    as
    1. Sarah L. Taylor & Whitney B. Curry & Zoe R. Knowles & Robert J. Noonan & Bronagh McGrane & Stuart J. Fairclough, 2017. "Predictors of Segmented School Day Physical Activity and Sedentary Time in Children from a Northwest England Low-Income Community," IJERPH, MDPI, vol. 14(5), pages 1-16, May.
    2. Sarah L. Taylor & Robert J. Noonan & Zoe R. Knowles & Michael B. Owen & Bronagh McGrane & Whitney B. Curry & Stuart J. Fairclough, 2018. "Evaluation of a Pilot School-Based Physical Activity Clustered Randomised Controlled Trial—Active Schools: Skelmersdale," IJERPH, MDPI, vol. 15(5), pages 1-18, May.
    3. Nikola Štefelová & Jan Dygrýn & Karel Hron & Aleš Gába & Lukáš Rubín & Javier Palarea-Albaladejo, 2018. "Robust Compositional Analysis of Physical Activity and Sedentary Behaviour Data," IJERPH, MDPI, vol. 15(10), pages 1-18, October.
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