Publication: Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance
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AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FPU17%2F04802
Abstract
The benefits of physical activity (PA) and sleep for health, accurate and objective population-based surveillance is important. Monitor-based surveillance has potential, but the main challenge is the need for replicable outcomes from different monitors. This study investigated the agreement of movement behavior outcomes assessed with four research-grade activity monitors (i.e., Movisens Move4, ActiGraph GT3X+, GENEActiv, and Axivity AX3) in adults. Twenty-three participants wore four monitors on the non-dominant wrist simultaneously for seven days. Open-source software (GGIR) was used to estimate the daily time in sedentary, light, moderate-to-vigorous PA (MVPA), and sleep (movement behaviors). The prevalence of participants meeting the PA and sleep recommendations were calculated from each monitor's data. Outcomes were deemed equivalent between monitors if the absolute standardized difference and its 95% confidence intervals (CI95%) fell within ± 0.2 standard deviations (SD) of the mean of the differences. The participants were mostly men (n = 14, 61%) and aged 36 (SD = 14) years. Pairwise confusion matrices showed that 83-87% of the daily time was equally classified into the movement categories by the different pairs of monitors. The between-monitor difference in MVPA ranged from 1 (CI95%:- 6, 7) to 8 (CI95%: 1, 15) min/day. Most of the PA and sleep metrics could be considered equivalent. The prevalence of participants meeting the PA and the sleep guidelines was 100% consistent across monitors (22 and 5 participants out of the 23, respectively). Our findings indicate that the various research-grade activity monitors investigated show high inter-instrument reliability with respect to sedentary, PA and sleep-related estimates when their raw data are processed in an identical manner. These findings may have important implications for advancement towards monitor-based PA and sleep surveillance systems.
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