Jacek K Urbanek1, Vadim Zipunnikov1, Tamara Harris2, Ciprian Crainiceanu1, Jaroslaw Harezlak3, Nancy W Glynn4. 1. Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. 2. Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, Maryland. 3. Department of Epidemiology and Biostatistics, School of Public Health, Indiana University, Bloomington. 4. Department of Epidemiology, Center for Aging and Population Health, Graduate School of Public Health, University of Pittsburgh, Pennsylvania.
Abstract
Background: Data collected by wearable accelerometry devices can be used to identify periods of sustained harmonic walking. This report aims to establish whether the features of walking identified in the laboratory and free-living environments are associated with each other as well as measures of physical function, mobility, fatigability, and fitness. Methods: Fifty-one older adults (mean age 78.31) enrolled in the Developmental Epidemiologic Cohort Study were included in the analyses. The study included an "in-the-lab" component as well as 7 days of monitoring "in-the-wild" (free living). Participants were equipped with hip-worn Actigraph GT3X+ activity monitors, which collect raw accelerometry data. We applied a walking identification algorithm and defined features of walking, including participant-specific walking acceleration and cadence. The association between these walking features and physical function, mobility, fatigability, and fitness was quantified using linear regression analysis. Results: Acceleration and cadence estimated from "in-the-lab" and "in-the-wild" data were significantly associated with each other (p < .05). However, walking acceleration "in-the-lab" was on average 96% higher than "in-the-wild," whereas cadence "in-the-lab" was on average 20% higher than "in-the-wild." Acceleration and cadence were associated with measures of physical function, mobility, fatigability, and fitness (p < .05) in both "in-the-lab" and "in-the-wild" settings. In addition, "in-the-wild" daily walking time was associated with fitness (p < .05). Conclusions: The quantitative difference in proposed walking features indicates that participants may overperform when observed "in-the-lab." Also, proposed features of walking were significantly associated with measures of physical function, mobility, fatigability, and fitness, which provides evidence of convergent validity.
Background: Data collected by wearable accelerometry devices can be used to identify periods of sustained harmonic walking. This report aims to establish whether the features of walking identified in the laboratory and free-living environments are associated with each other as well as measures of physical function, mobility, fatigability, and fitness. Methods: Fifty-one older adults (mean age 78.31) enrolled in the Developmental Epidemiologic Cohort Study were included in the analyses. The study included an "in-the-lab" component as well as 7 days of monitoring "in-the-wild" (free living). Participants were equipped with hip-worn Actigraph GT3X+ activity monitors, which collect raw accelerometry data. We applied a walking identification algorithm and defined features of walking, including participant-specific walking acceleration and cadence. The association between these walking features and physical function, mobility, fatigability, and fitness was quantified using linear regression analysis. Results: Acceleration and cadence estimated from "in-the-lab" and "in-the-wild" data were significantly associated with each other (p < .05). However, walking acceleration "in-the-lab" was on average 96% higher than "in-the-wild," whereas cadence "in-the-lab" was on average 20% higher than "in-the-wild." Acceleration and cadence were associated with measures of physical function, mobility, fatigability, and fitness (p < .05) in both "in-the-lab" and "in-the-wild" settings. In addition, "in-the-wild" daily walking time was associated with fitness (p < .05). Conclusions: The quantitative difference in proposed walking features indicates that participants may overperform when observed "in-the-lab." Also, proposed features of walking were significantly associated with measures of physical function, mobility, fatigability, and fitness, which provides evidence of convergent validity.
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