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(Stroke. 1999;30:2159-2166.)
© 1999 American Heart Association, Inc.
Original Contributions |
From the Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC (D.C.S., M.J.H., K.R.R.K.), and the Department of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC (G.L.B.).
Correspondence to David C. Steffens, MD, Duke University Medical Center, Box 3903, Durham, NC 27710. E-mail steff001{at}mc.duke.edu
Background and PurposeEvidence is mounting linking cerebrovascular disease with depressive symptoms in the elderly. Lesions in both white and gray matter have been associated with depressive symptoms and major depression. We sought to investigate the relationship between depressive symptoms and white and gray matter lesions in subjects participating in the Cardiovascular Health Study.
MethodsIn a sample of 3660 men and women who underwent a standardized interview, physical examination, and MRI scan, we examined the association between number of white and gray matter lesions and white matter grade (a measure of severity) and reported depressive symptoms using a modified version of the Centers for Epidemiologic Studies Depression (CES-D) scale. We controlled for a variety of demographic and medical variables as well as functional status and Modified Mini-Mental State Examination score.
ResultsThe number of small (<3 mm) basal ganglia lesions was significantly associated with reported depressive symptoms, but white matter grade was not. In subsequent logistic regression models, number of basal ganglia lesions remained a significant predictor after controlling for non-MRI variables and severity of white matter lesions.
ConclusionsOur findings extend previous reports that linked cerebrovascular changes to depressive symptoms in clinical populations to a large community-based population. This report provides further evidence of the importance of basal ganglia lesions in geriatric depression.
Key Words: cerebrovascular disorders depression health magnetic resonance imaging
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