There is now growing evidence of dysregulation of physical activity, sleep and/or circadian rhythms in people with major depression. However, few studies of large population cohorts have examined associations between the full range of features that can be derived from actigraphy. Here, we examine the interaction and inter-correlations among the three major domains extracted from actigraphy including sleep (SL), physical activity (PA) and circadian rhythm (CR) to quantify their joint and individual variations. The sample included 2317 participants from a cohort study and clinical diagnoses were obtained through a comprehensive diagnostic interview to ascertain lifetime history of mood and other disorders. There are a total of 1153 people with MDD and 1164 with no history of MDD. The mean age is 61.79 years (range: 45 to 86 years), and 54.42% of participants are female. Features of SL, PA and CR were assessed from using Actigraphy collected with a wrist-worn triaxial accelerometer for an average of 12 days. JIVE (joint and individual variation explained) method was applied to derive the joint and individual variance of the features in SL, PA and CR. Findings indicate that the greater amount of joint variation was explained by PA and lower amounts by SL and CR. Regression analyses of the JIVE components show that participants with MDD differed significantly from controls on the first and second joint JIVE scores, but not on the individual JIVE scores. These results demonstrate how the JIVE method enabled us to examine the joint and individual components of the actigraphy domains of SL, PA, and CR. JIVE regression allowed us to separate domain-specific sources of variability while addressing possible multicollinearity.
Dr. Sun Jung Kang is currently a staff scientist at Genetic Epidemiology Branch at NIMH/NIH. She worked at Albany Stratton VA Medical Center and SUNY Downstate Medical Center before she joined NIMH in 2016. She received her B.A. in Mathematics from University of Virginia, M.S. in Applied Mathematics from New York University, Ph.D. in Applied Mathematics and Statistics from State University of New York Stony Brook and post-doctoral training from Duke University and Case Western Reserve University. As a statistician, she has been working on the development of translational studies to identify the regulatory systems underlying motor activity and sleep across species by joint analysis of the multiple domains.