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  Vol. 53 No. 2, February 1996 TABLE OF CONTENTS
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Electroencephalographic Sleep Profiles During Depression

Effects of Episode Duration and Other Clinical and Psychosocial Factors in Older Adults

Mary Amanda Dew, PhD; Charles F. Reynolds III, MD; Daniel J. Buysse, MD; Patricia R. Houck, MS; Carolyn C. Hoch, PhD; Timothy H. Monk, PhD; David J. Kupfer, MD

Arch Gen Psychiatry. 1996;53(2):148-156.


Abstract

Background
Limited evidence suggests that polysomnographic alterations may be more prominent early in a depressive episode. Whether the effects of episode duration extend beyond middle age and appear in late-life depression as well has important implications for treatment decisions and for understanding depressive illness across the life span. Furthermore, the impact of episode duration on sleep has not been examined in the context of other factors related to clinical history and psychosocial status.

Methods
Eighty-three persons aged 60 years or older with recurrent depression were studied: 34 had been depressed for 2 to 16 weeks and 49 for longer periods. An age- and gender-matched group of 48 persons with no history of major depression served as controls. Initial univariate analyses examined duration effects on electroencephalographic (EEG) sleep measurements. Multivariate analyses considered the combined effects of episode duration, clinical variables, and psychosocial variables on EEG sleep profile.

Results
Episode duration was strongly associated with sleep continuity, architecture, and rapid eye movement: subjects who were earlier in their depressive episodes had their sleep impaired more than those later in their episodes, who, in turn, were more impaired than controls. Moreover, clinical characteristics of subjects' depressive illness, demographic variables, and psychosocial stressors and supports had unique effects on the EEG sleep profile.

Conclusion
Episode duration appears to be a potent factor to consider when evaluating sleep during depression. The additional contribution of clinical and psychosocial characteristics to the prediction of the EEG sleep profile demonstrates the importance of incorporating these variables into models of the psychobiologic characteristics of depression. The results are relevant to the timing and focus of therapeutic interventions.



Author Affiliations

From the Departments of Psychiatry (Drs Dew, Reynolds, Buysse, Hoch, Monk, and Kupfer and Ms Houck), Epidemiology (Dr Dew), and Psychology (Dr Dew), University of Pittsburgh School of Medicine and Western Psychiatric Institute and Clinic, Pittsburgh, Pa.



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THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES

Healthy Older Adults' Sleep Predicts All-Cause Mortality at 4 to 19 Years of Follow-Up
Dew et al.
Psychosom. Med. 2003;65:63-73.
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Temporal Profiles of the Course of Depression During Treatment: Predictors of Pathways Toward Recovery in the Elderly
Dew et al.
Arch Gen Psychiatry 1997;54:1016-1024.
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