Joint and Individual Representation of Domains of Physical Activity, Sleep, and Circadian Rhythmicity

Junrui Di (), Adam Spira, Jiawei Bai, Jacek Urbanek, Andrew Leroux, Mark Wu, Susan Resnick, Eleanor Simonsick, Luigi Ferrucci, Jennifer Schrack and Vadim Zipunnikov
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Junrui Di: Johns Hopkins Bloomberg School of Public Health
Adam Spira: Johns Hopkins Center on Aging and Health
Jiawei Bai: Johns Hopkins Bloomberg School of Public Health
Jacek Urbanek: Johns Hopkins University School of Medicine
Andrew Leroux: Johns Hopkins Bloomberg School of Public Health
Mark Wu: Johns Hopkins University School of Medicine
Susan Resnick: National Institute on Aging, National Institutes of Health
Eleanor Simonsick: National Institute on Aging, National Institutes of Health
Luigi Ferrucci: National Institute on Aging, National Institutes of Health
Jennifer Schrack: Johns Hopkins Center on Aging and Health
Vadim Zipunnikov: Johns Hopkins Center on Aging and Health

Statistics in Biosciences, 2019, vol. 11, issue 2, No 9, 402 pages

Abstract: Abstract Developments in wearable technology have enabled researchers to continuously and objectively monitor various aspects and physiological domains of real life including levels of physical activity, quality of sleep, and strength of circadian rhythm in many epidemiological and clinical studies. Current analytical practice is to summarize each of these three domains individually via a standard inventory of interpretable features, and explore individual associations between the features and clinical variables. However, the features often exhibit significant interaction and correlation both within and between domains. Integration of features across multiple domains remains methodologically challenging. To address this problem, we propose to use joint and individual variation explained, a dimension reduction technique that efficiently deals with multivariate data representing multiple domains. In this paper, we review the most frequently used features to characterize the domains of physical activity, sleep, and circadian rhythmicity and illustrate the approach using wrist-worn actigraphy data from 198 participants of the Baltimore Longitudinal Study of Aging.

Keywords: Multi-domain; Physical activity; Sleep; Circadian rhythmicity; JIVE; Dimension reduction (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s12561-019-09236-4

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