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A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance

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posted on 09.07.2019 by Alex V. Rowlands, Lauren Sherar, Stuart J. Fairclough, Thomas E. Yates, Charlotte L. Edwardson, Deirdre M. Harrington, Melanie J. Davies, Fehmidah Munir, Kamlesh Khunti, Victoria H. Stiles
Objectives: Our aim is to demonstrate how a data-driven accelerometer metric, the acceleration above which a person’s most active minutes are accumulated, can (a) quantify the prevalence of meeting current physical activity guidelines for global surveillance and (b) moving forward, could inform accelerometer-driven physical activity guidelines. Unlike cut-point methods, the metric is population-independent (e.g. age) and potentially comparable across datasets. Design: Cross-sectional, secondary data analysis. Methods: Analyses were carried out on five datasets using wrist-worn accelerometers: children (N = 145), adolescent girls (N = 1669), office workers (N = 114), pre- (N = 1218) and post- (N = 1316) menopausal women, and adults with type 2 diabetes (N = 475). Open-source software (GGIR) was used to generate the magnitude of acceleration above which a person’s most active 60, 30 and 2 min are accumulated: M60ACC; M30ACC and M2ACC, respectively. Results: The proportion of participants with M60ACC (children) and M30ACC (adults) values higher than accelerations representative of brisk walking (i.e., moderate-to-vigorous physical activity) ranged from 17 to 68% in children and 15 to 81% in adults, tending to decline with age. The proportion of pre-and post-menopausal women with M2ACC values meeting thresholds for bone health ranged from 6 to 13%. Conclusions: These metrics can be used for global surveillance of physical activity, including assessing prevalence of meeting current physical activity guidelines. As accelerometer and corresponding health data accumulate it will be possible to interpret the metrics relative to age- and sex- specific norms and derive evidence-based physical activity guidelines directly from accelerometer data for use in future global surveillance. This is where the potential advantages of these metrics lie.

Funding

The Active Schools: Skelmersdale (ASSK) physical activity intervention study was funded by West Lancashire Sport Partnership UK, West Lancashire Community Leisure UK, and Edge Hill University Ormskirk UK. The adolescent girls’ data are from the Girls Active evaluation, which was funded by the NIHR Public Health Research Programme (13/90/30). The adult office workers data are from the SMArT Work trial, which was sponsored by Loughborough University. The project was funded by the Department of Health Policy Research Programme (project No PR-R5-0213-25004). The pre- and post-menopausal data are from UK Biobank. The processing and analysis of these data was supported by an internal grant from the University of Exeter (UK) Project Development Fund (Science). University of Leicester authors are supported by the NIHR Leicester Biomedical Research Centre, and the Collaboration for leadership in Applied Health Research and Care (CLAHRC) East Midlands.

History

School

  • Sport, Exercise and Health Sciences

Published in

Journal of Science and Medicine in Sport

Volume

22

Issue

10

Pages

1132 - 1138

Citation

ROWLANDS, A.V. ... et al, 2019. A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance. Journal of Science and Medicine in Sport, 22 (10), pp.1132-1138.

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Rights holder

© Sports Medicine Australia

Publisher statement

This paper was accepted for publication in the journal Journal of Science and Medicine in Sport and the definitive published version is available at https://doi.org/10.1016/j.jsams.2019.06.016.

Acceptance date

21/06/2019

Publication date

2019-07-01

Copyright date

2019

ISSN

1440-2440

Language

en

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