Actigraphic predictors of depressed mood in a cohort of non-psychiatric adults.
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.


METHODS
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.


CONCLUSIONS
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.
Mendlowicz
M V
MV
Sleep and Circadian Rhythm Studies, University of California, San Diego, La Jolla 92037, USA.
Jean-Louis
G
G
von Gizycki
H
H
Zizi
F
F
Nunes
J
J
D000293:Adolescent; D000328:Adult; D000368:Aged; D000544:Alzheimer Disease / Q000175:diagnosis / Q000523:psychology; D002940:Circadian Rhythm; D003430:Cross-Sectional Studies; D003863:Depression / Q000175:diagnosis* / Q000523:psychology; D003865:Major Depressive Disorder / Q000175:diagnosis* / Q000523:psychology; D005260:Female; D006801:Humans; D008297:Male; D008609:Mental Status Schedule; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D009043:Motor Activity; D017286:Polysomnography / Q000295:instrumentation; D011569:Psychiatric Status Rating Scales; D012044:Regression Analysis; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*