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The Triaxial Physical Activity Signature Associated with Metabolic Health in Children


Medicine & Science in Sports & Exercise: October 2019 - Volume 51 - Issue 10 - p 2173–2179
doi: 10.1249/MSS.0000000000002021
SPECIAL COMMUNICATIONS: Methodological Advances

Purpose The use of uniaxial summary measures from accelerometry (i.e., counts per minute or minutes spent in moderate-to-vigorous intensity) substantially restricts information about physical activity (PA), and is probably a result of reliance on analytic approaches that cannot handle collinear variables. In the present study, we aimed to determine the multivariate triaxial PA intensity signature related to metabolic health in children, by investigating associations of the whole spectra of PA intensities from all axes using multivariate pattern analysis.

Methods We included 841 children (age, 10.2 ± 0.3 yr; body mass index, 18.0 ± 3.0; 50% boys) from the Active Smarter Kids study conducted in Norway 2014 to 2015 providing valid data on accelerometry (ActiGraph GT3X+) and several indices of metabolic health (aerobic fitness, abdominal fatness, insulin sensitivity, lipid metabolism, blood pressure) that were used to create a composite metabolic health score. We created intensity spectra from 0 to 100 to ≥10,000 counts per minute for separate axes and used multivariate pattern analysis to analyze the data.

Results The explained variance of metabolic health was 3.2% for counts per minute from the vertical axis, 17.0% for the vertical axis intensity spectrum, and 29.5% for the full model including all axes. Thus, including full triaxial intensity spectra improved the model for metabolic health tenfold compared with using overall PA (counts per minute) from the vertical axis only. The intensity signature associated with metabolic health differed across the axes.

Conclusions Our findings show that the three different axes carry distinct information about children’s PA and the relation of PA to their health and demonstrate a great potential for triaxial accelerometry and a multivariate analytic approach to advance the field of PA epidemiology.

1Faculty of Education, Arts and Sports, Western Norway University of Applied Sciences, Sogndal, NORWAY

2Department of Chemistry, University of Bergen, Bergen, NORWAY

3Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, NORWAY

Address for correspondence: Eivind Aadland, Ph.D., Western Norway University of Applied Sciences, Faculty of Education, Arts and Sports, Campus Sogndal, Box 133, 6851 Sogndal, Norway; E-mail:

Submitted for publication October 2018.

Accepted for publication April 2019.

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Online date: May 4, 2019

© 2019 American College of Sports Medicine