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

Krista S. Leonard, Abigail M. Pauley, Emily E. Hohman, Penghong Guo, Daniel E. Rivera, Jennifer S. Savage, Matthew P. Buman, Danielle Symons Downs

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1197-1201
Number of pages5
JournalJournal of Science and Medicine in Sport
Volume23
Issue number12
DOIs
StatePublished - Dec 2020

All Science Journal Classification (ASJC) codes

  • Orthopedics and Sports Medicine
  • Physical Therapy, Sports Therapy and Rehabilitation

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