Quantifying the Life-Time Circadian Rhythm of Physical Activity: A Covariate-Dependent Functional Approach

• Activity Number: 161
• Type: Topic Contributed
• Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Korean International Statistical Society
• Author(s): Luo Xiao*+ and Lei Huang and Jennifer Schrack and Luigi Ferrucci and Vadim Zipunnikov and Ciprian Crainiceanu
• Companies: Cornell University and Johns Hopkins University and Johns Hopkins University/National Institute on Aging and National Institute on Aging and Johns Hopkins University and Johns Hopkins University
• Keywords: Accelerometer ; Bivariate smoothing ; BLSA ; Covariance ; Functional data ; Sandwich smoother

Abstract

Objective measurement of physical activity using wearable devices such as accelerometers can provide tantalizing new insights into the association between activity and health outcomes. Accelerometers can record quasi-continuous activity information for many days on the same individual for hundreds of individuals. For example, in the Baltimore Longitudinal Study on Aging (BLSA) physical activity was recorded every minute for 622 adults for an average of 7.3 days per adult. An important scientific problem is to separate and quantify the systematic and random circadian patterns of physical activity as functions of time of day, age, and gender. The systematic circadian pattern is captured by a practical bivariate smoother and the age-dependent random subject-specific patterns are modeled by covariate-dependent covariance operators. Results reveal several interesting, previously unknown, circadian patterns associated with human aging and gender.