KINGSNORTH, Andrew P, MOLTCHANOVA, Elena, THOMAS, Jonah JC, WHELAN, Maxine E, ORME, Mark W, ESLIGER, Dale W and HOBBS, Matthew (2023). Interchangeability of Research and Commercial Wearable Device Data for Assessing Associations With Cardiometabolic Risk Markers. Journal for the Measurement of Physical Behaviour, 6 (3), 169-175. [Article]
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35634:914607
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Abstract
<h4>Introduction</h4>
While there is evidence on agreement, it is unknown whether commercial wearables can be used as surrogates for research-grade devices when investigating links with markers of cardiometabolic risk. Therefore, the aim of this study was to investigate whether data from a commercial wearable device could be used to assess associations between behavior and cardiometabolic risk markers, compared with physical activity from a research-grade monitor.
<h4>Methods</h4> Forty-five adults concurrently wore a wrist-worn Fitbit Charge 2 and a waist-worn ActiGraph wGT3X-BT during waking hours over 7 consecutive days. Log-linear regression models were fitted, and predictive fit via a one-out cross-validation was performed for each device between behavioral (steps, and light and moderate-to-vigorous physical activity) and cardiometabolic variables (body mass index, weight, body fat percentage, systolic and diastolic blood pressure, glycated haemoglobin, grip strength, estimated maximal oxygen uptake, and waist circumference).
<h4> Results</h4
> Overall, step count was the most consistent predictor of cardiometabolic risk factors, with negative associations across both Fitbit and ActiGraph devices for body mass index (−0.017 vs. −0.020, <jats:italic>p</jats:italic> < .01), weight (−0.014 vs. −0.017, <jats:italic>p</jats:italic> < .05), body fat percentage (−0.021 vs. −0.022, <jats:italic>p</jats:italic> < .01), and waist circumference (−0.013 vs. −0.015, <jats:italic>p</jats:italic> < .01). Neither device was found to provide a consistently better prediction across all included cardiometabolic risk markers. <h4>Conclusions</h4> Step count data from a commercial-grade wearable device showed similar associations and predictive relationships with cardiometabolic risk markers compared with a research-grade wearable device, providing preliminary support for their use in health research
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