IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i7p1296-d153563.html
   My bibliography  Save this article

Wear-Time Compliance with a Dual-Accelerometer System for Capturing 24-h Behavioural Profiles in Children and Adults

Author

Listed:
  • Scott Duncan

    (School of Sport and Recreation, Auckland University of Technology, Auckland 1142, New Zealand)

  • Tom Stewart

    (School of Sport and Recreation, Auckland University of Technology, Auckland 1142, New Zealand)

  • Lisa Mackay

    (School of Sport and Recreation, Auckland University of Technology, Auckland 1142, New Zealand)

  • Jono Neville

    (School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1142, New Zealand)

  • Anantha Narayanan

    (School of Sport and Recreation, Auckland University of Technology, Auckland 1142, New Zealand)

  • Caroline Walker

    (Centre for Longitudinal Research, University of Auckland, Auckland 1142, New Zealand)

  • Sarah Berry

    (Centre for Longitudinal Research, University of Auckland, Auckland 1142, New Zealand)

  • Susan Morton

    (Centre for Longitudinal Research, University of Auckland, Auckland 1142, New Zealand)

Abstract

To advance the field of time-use epidemiology, a tool capable of monitoring 24 h movement behaviours including sleep, physical activity, and sedentary behaviour is needed. This study explores compliance with a novel dual-accelerometer system for capturing 24 h movement patterns in two free-living samples of children and adults. A total of 103 children aged 8 years and 83 adults aged 20-60 years were recruited. Using a combination of medical dressing and purpose-built foam pouches, participants were fitted with two Axivity AX3 accelerometers—one to the thigh and the other to the lower back—for seven 24 h periods. AX3 accelerometers contain an inbuilt skin temperature sensor that facilitates wear time estimation. The median (IQR) wear time in children was 160 (67) h and 165 (79) h (out of a maximum of 168 h) for back and thigh placement, respectively. Wear time was significantly higher and less variable in adults, with a median (IQR) for back and thigh placement of 168 (1) and 168 (0) h. A greater proportion of adults (71.6%) achieved the maximum number of complete days when compared to children (41.7%). We conclude that a dual-accelerometer protocol using skin attachment methods holds considerable promise for monitoring 24-h movement behaviours in both children and adults.

Suggested Citation

  • Scott Duncan & Tom Stewart & Lisa Mackay & Jono Neville & Anantha Narayanan & Caroline Walker & Sarah Berry & Susan Morton, 2018. "Wear-Time Compliance with a Dual-Accelerometer System for Capturing 24-h Behavioural Profiles in Children and Adults," IJERPH, MDPI, vol. 15(7), pages 1-12, June.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:7:p:1296-:d:153563
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/7/1296/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/7/1296/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aiden Doherty & Dan Jackson & Nils Hammerla & Thomas Plötz & Patrick Olivier & Malcolm H Granat & Tom White & Vincent T van Hees & Michael I Trenell & Christoper G Owen & Stephen J Preece & Rob Gillio, 2017. "Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-14, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marieke De Craemer & Vera Verbestel, 2021. "Comparison of Outcomes Derived from the ActiGraph GT3X+ and the Axivity AX3 Accelerometer to Objectively Measure 24-Hour Movement Behaviors in Adults: A Cross-Sectional Study," IJERPH, MDPI, vol. 19(1), pages 1-8, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Clark, Stephen & Birkin, Mark & Lomax, Nik & Morris, Michelle, 2020. "Developing a whole systems obesity classification for the UK Biobank Cohort," OSF Preprints 7nqgd, Center for Open Science.
    2. Marta Karas & Jiawei Bai & Marcin Strączkiewicz & Jaroslaw Harezlak & Nancy W. Glynn & Tamara Harris & Vadim Zipunnikov & Ciprian Crainiceanu & Jacek K. Urbanek, 2019. "Accelerometry Data in Health Research: Challenges and Opportunities," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(2), pages 210-237, July.
    3. Xinyue Li & Hongyu Zhao, 2020. "Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms," PLOS Genetics, Public Library of Science, vol. 16(10), pages 1-22, October.
    4. Bernadette Nakabazzi & Lucy-Joy M Wachira & Adewale L Oyeyemi & Ronald Ssenyonga & Vincent O Onywera, 2020. "Prevalence and socio-demographic correlates of accelerometer measured physical activity levels of school-going children in Kampala city, Uganda," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-18, July.
    5. Jin Luo & Raymond Y. W. Lee, 2022. "Opposing patterns in self-reported and measured physical activity levels in middle-aged adults," European Journal of Ageing, Springer, vol. 19(3), pages 567-573, September.
    6. Thomas G. Brooks & Nicholas F. Lahens & Gregory R. Grant & Yvette I. Sheline & Garret A. FitzGerald & Carsten Skarke, 2023. "Diurnal rhythms of wrist temperature are associated with future disease risk in the UK Biobank," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    7. Pietro Luigi Invernizzi & Gabriele Signorini & Raffaele Scurati & Giovanni Michielon & Stefano Benedini & Andrea Bosio & Walter Staiano, 2022. "The UP150: A Multifactorial Environmental Intervention to Promote Employee Physical and Mental Well-Being," IJERPH, MDPI, vol. 19(3), pages 1-26, January.
    8. Esmonde, Katelyn & Roth, Stephen & Walker, Alexis, 2023. "A social and ethical framework for providing health information obtained from combining genetics and fitness tracking data," Technology in Society, Elsevier, vol. 74(C).
    9. Luiza Isnardi Cardoso Ricardo & Andrea Wendt & Leony Morgana Galliano & Werner de Andrade Muller & Gloria Izabel Niño Cruz & Fernando Wehrmeister & Soren Brage & Ulf Ekelund & Inácio Crochemore M. Sil, 2020. "Number of days required to estimate physical activity constructs objectively measured in different age groups: Findings from three Brazilian (Pelotas) population-based birth cohorts," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-13, January.
    10. Pontin, Francesca & Lomax, Nik & Clarke, Graham & Morris, Michelle A., 2021. "Socio-demographic determinants of physical activity and app usage from smartphone data," Social Science & Medicine, Elsevier, vol. 284(C).
    11. Hongliang Feng & Lulu Yang & Yannis Yan Liang & Sizhi Ai & Yaping Liu & Yue Liu & Xinyi Jin & Binbin Lei & Jing Wang & Nana Zheng & Xinru Chen & Joey W. Y. Chan & Raymond Kim Wai Sum & Ngan Yin Chan &, 2023. "Associations of timing of physical activity with all-cause and cause-specific mortality in a prospective cohort study," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    12. Grégory Hammad & Mathilde Reyt & Nikita Beliy & Marion Baillet & Michele Deantoni & Alexia Lesoinne & Vincenzo Muto & Christina Schmidt, 2021. "pyActigraphy: Open-source python package for actigraphy data visualization and analysis," PLOS Computational Biology, Public Library of Science, vol. 17(10), pages 1-16, October.
    13. Leonie Heron & Mark A. Tully & Frank Kee & Ciaran O’Neill, 2023. "Inpatient care utilisation and expenditure associated with objective physical activity: econometric analysis of the UK Biobank," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(4), pages 489-497, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:15:y:2018:i:7:p:1296-:d:153563. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.