Identifying ActiGraph non-wear time in pregnant women with overweight or obesity.

J Sci Med Sport

Exercise Psychology Laboratory, Department of Kinesiology, The Pennsylvania State University, United States; Department of OBGYN, College of Medicine, The Pennsylvania State University, United States. Electronic address:

Published: December 2020

Objectives: Non-wear time algorithms have not been validated in pregnant women with overweight/obesity (PW-OW/OB), potentially leading to misclassification of sedentary/activity data, and inaccurate estimates of how physical activity is associated with pregnancy outcomes. We examined: (1) validity/reliability of non-wear time algorithms in PW-OW/OB by comparing wear time from five algorithms to a self-report criterion and (2) whether these algorithms over- or underestimated sedentary behaviors.

Design: PW-OW/OB (N = 19) from the Healthy Mom Zone randomized controlled trial wore an ActiGraph GT3x + for 7 consecutive days between 8-12 weeks gestation.

Methods: Non-wear algorithms (i.e., consecutive strings of zero acceleration in 60-second epochs) were tested at 60, 90, 120, 150, and 180-min. The monitor registered sedentary minutes as activity counts 0-99. Women completed daily self-report logs to report wear time.

Results: Intraclass correlation coefficients for each algorithm were 0.96-0.97; Bland-Altman plots revealed no bias; mean absolute percent errors were <10%. Compared to self-report (M = 829.5, SD = 62.1), equivalency testing revealed algorithm wear times (min/day) were equivalent: 60- (M = 816.4, SD = 58.4), 90- (M = 827.5, SD = 61.4), 120- (M = 830.8, SD = 65.2), 150- (M = 833.8, SD = 64.6) and 180-min (M = 837.4, SD = 65.4). Repeated measures ANOVA showed 60- and 90-min algorithms may underestimate sedentary minutes compared to 150- and 180-min algorithms.

Conclusions: The 60, 90, 120, 150, and 180-min algorithms are valid and reliable for estimating wear time in PW-OW/OB. However, implementing algorithms with a higher threshold for consecutive zero counts (i.e., ≥150-min) can avoid the risk of misclassifying sedentary data.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606752PMC
http://dx.doi.org/10.1016/j.jsams.2020.08.003DOI Listing

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