Sociodemographic, Health and Lifestyle, Sampling, and Mental Health Determinants of 24-Hour Motor Activity Patterns: Observational Study

Background Analyzing actigraphy data using standard circadian parametric models and aggregated nonparametric indices may obscure temporal information that be a hallmark of the impairment in psychiatric disorders. Functional analysis (FDA) overcome such limitations by fully exploiting richness revealing important relationships with mental health outcomes. To our knowledge, no studies have extensively used FDA to study relationship between sociodemographic, lifestyle, sampling, clinical characteristics daily motor activity patterns assessed sample individuals without depression/anxiety. Objective We aimed association via (1) sampling factors, (2) (ie, presence severity depression/anxiety disorders). Methods obtained 14-day continuous from 359 participants Netherlands Study Depression Anxiety current (n=93), remitted (n=176), or (n=90) diagnosis, based on criteria Diagnostic Statistical Manual Mental Disorders, fourth edition. Associations activity, quantified functional principal component (fPCA), were generalized estimating equation regressions. For exploratory purposes, function-on-scalar regression (FoSR) was applied quantify time-varying activity. Results Four components captured 77.4% variability data: overall level (fPCA1, 34.3% variability), early versus late morning (fPCA2, 16.5% biphasic monophasic (fPCA3, 14.8% (fPCA4, 11.8% variability). A low associated number psychopathology variables: older age (P<.001), higher education (P=.005), BMI (P=.009), greater chronic diseases (P=.02), cigarettes smoked per day depressive and/or anxiety disorders (P=.05), symptoms (P<.001). high work/school days (P=.02) summer (reference: winter; P=.03). Earlier having partner autumn spring P=.02 P<.001, respectively). Monophasic (P=.005). Biphasic (P<.001) P<.001). P<.001 P=.005, In FoSR analyses, age, days, season main determinants (all P<.05). Conclusions Features extracted fPCA reflect commonly studied factors as intensity preference for morningness/eveningness. The found mainly lower pattern but not time Age, variables most strongly thus future epidemiological should take these into account.