Applying Average Real Variability to Quantifying Day–Day Physical Activity and Sedentary Postures Variability: A Comparison With Standard Deviation
Author:
Shivgulam Madeline E.1ORCID, O’Brien Myles W.23ORCID
Affiliation:
1. Division of Kinesiology, Dalhousie University, Halifax, NS, Canada 2. Division of Geriatric Medicine, Department of Medicine, Faculty of Health, School of Physiotherapy, Dalhousie University, Halifax, NS, Canada 3. Geriatric Medicine Research, Dalhousie University & Nova Scotia Health, Halifax, NS, Canada
Abstract
Intraindividual activity variability is often overlooked, with some existing work using SD as a variability metric. However, average real variability (ARV) may be a more suitable metric as it accounts for temporal variability. The purpose of this exploratory study was to (a) apply ARV analyses to habitual activity outcomes; (b) assess the agreement between ARV and SD for habitual step counts, standing time, and sedentary time; and (c) determine the relationship between activity variability (SD and ARV) with average activity values. One hundred and eighty-nine participants (37 ± 22 years, 109 females) wore the activPAL inclinometer on their thigh 24 hr/day for 6.4 ± 0.9 days. SD and ARV were calculated for each participant across their wear time. A Wilcoxon signed-rank test revealed that ARV was significantly higher than SD for step count, standing time, and sedentary time (all, p < .001). Equivalence testing demonstrated mixed equivalence for step counts (10%), standing time (12%), and sedentary time (14%). SD and ARV were highly correlated to each other for all activity metrics (all, ρ > .857, p < .001). SD was moderately (ρ = .601, p < .001) and weakly (ρ = .296, p < .001) correlated with average step count and standing time, respectively. ARV was weakly correlated with average step count and standing time (both: ρ < .499, p < .001). However, average sedentary time was not associated with SD or ARV (both, p > .177). While the two measurements of variability were strongly correlated, they cannot be used interchangeably. More monitoring research should consider intraindividual activity variability and use methods, such as ARV, that consider the temporal nature of day–day activity.
Subject
Public Health, Environmental and Occupational Health,Statistics, Probability and Uncertainty,General Psychology,General Engineering,General Computer Science
Reference29 articles.
1. Recovery from training: A brief review;Bishop, P.A.,2008 2. A power primer;Cohen, J.,1992 3. cocor: A comprehensive solution for the statistical comparison of correlations;Diedenhofen, B.,2015 4. A primer on the use of equivalence testing for evaluating measurement agreement;Dixon, P.M.,2018 5. Considerations when using the activPAL monitor in field-based research with adult populations;Edwardson, C.L.,2017
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