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

  • Junrui DiEmail author
  • Adam Spira
  • Jiawei Bai
  • Jacek Urbanek
  • Andrew Leroux
  • Mark Wu
  • Susan Resnick
  • Eleanor Simonsick
  • Luigi Ferrucci
  • Jennifer Schrack
  • Vadim Zipunnikov


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.


Multi-domain Physical activity Sleep Circadian rhythmicity JIVE Dimension reduction 



This study was supported in part by the Intramural Research Program (IRP), National Institute on Aging (NIA), National Institutes of Health (NIH), and by Research and Development Contract HHSN-260-2004-00012C. Dr. Adam Spira was supported in part by R01AG050507 from the National Institute on Aging. Dr Adam Spira received an honorarium from Springer Nature Switzerland AG for Guest Editing a Special Issue of Current Sleep Medicine Reports. Dr. Mark Wu was supported by R01AG054771. Dr. Jennifer Schrack was supported by U01AG057545 and R21AG053198.


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Copyright information

© International Chinese Statistical Association 2019

Authors and Affiliations

  • Junrui Di
    • 1
    Email author
  • Adam Spira
    • 2
    • 3
    • 4
  • Jiawei Bai
    • 5
  • Jacek Urbanek
    • 6
  • Andrew Leroux
    • 1
  • Mark Wu
    • 7
  • Susan Resnick
    • 8
  • Eleanor Simonsick
    • 8
  • Luigi Ferrucci
    • 8
  • Jennifer Schrack
    • 2
    • 9
  • Vadim Zipunnikov
    • 2
    • 10
  1. 1.Department of BiostatisticsJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  2. 2.Johns Hopkins Center on Aging and HealthBaltimoreUSA
  3. 3.Department of Mental HealthJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  4. 4.Department of Psychiatry and Behavioral SciencesJohns Hopkins School of MedicineBaltimoreUSA
  5. 5.Department of BiostatisticsJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  6. 6.Division of Geriatric Medicine and Gerontology, Department of MedicineJohns Hopkins University School of MedicineBaltimoreUSA
  7. 7.Department of Neurology and NeuroscienceJohns Hopkins University School of MedicineBaltimoreUSA
  8. 8.Intramural Research ProgramNational Institute on Aging, National Institutes of HealthBaltimoreUSA
  9. 9.Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  10. 10.Department of BiostatisticsJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA

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