Actigraphic Predictors of Depressed Mood in a Cohort of Non-Psychiatric Adults

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Abstract
Objective: Depressed mood is one of the essential features for the diagnosis of major depression. Evidence from the three-site Epidemiologic Catchment Area study (EcA, Baltimore, Durham and Los Angeles) suggests a prevalence of 4.4% of depressive symptoms in the community. In this study, we examined whether depressed mood, as coded in the Alzheimer's Disease Assessment Scale, would be correlated with actigraphic-derived daytime activity and sleep/wake parameters in a non-psychiatric sample. Method: Consenting volunteers were monitored at home for 5 days with a wrist actigraph. On the last day of the recording, they were given a neuropsychological battery including the Alzheimer's Disease Assessment Scale. Results: Daytime activity level was the best predictor of depressed mood as indicated by a logistic regression analysis. The regression model further suggested that sleep onset latency, total time asleep, and time in bed were also significant predictors of depressed mood. Conclusion: This investigation demonstrates that daytime activity level could be used as an index of depressed mood even in a non-psychiatric sample. Further, the results support the notion that depression should be considered more as a continuum rather than as a set of rigid categories.