Journal
INTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY
Volume 30, Issue 7, Pages 677-685Publisher
WILEY-BLACKWELL
DOI: 10.1002/gps.4204
Keywords
depression; comorbidity; older adults
Categories
Funding
- National Institute on Alcohol Abuse and Alcoholism (NIAAA)
- United States Department of Veterans Affairs National Center for Posttraumatic Stress Disorder
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BackgroundPopulation-based data are lacking on the prevalence and comorbidity of subsyndromal depression (SSD) and its associated risk for incident psychiatric disorders in older adults. MethodsUsing nationally representative data from 10,409 US adults aged 55years and older who participated in the National Epidemiologic Survey on Alcohol and Related Conditions, we evaluated associations between lifetime SSD at Wave 1, and lifetime and incident mood, anxiety, and substance use disorders over a 3-year period. ResultsSome 13.8% of older adults met criteria for SSD, and 13.7% met criteria for major depressive disorder (MDD). After adjustment for sociodemographic characteristics, older adults with SSD at Wave 1 had significantly increased odds of lifetime mood (adjusted odds ratios (AORs)=3.65-10.55), anxiety (AORs=1.61-2.50), and any personality (AOR=1.62) disorders. After adjustment for sociodemographic characteristics and comorbid psychiatric disorders, older adults with SSD at Wave 1 had significantly increased odds of developing new-onset MDD (AOR=1.44, 95% confidence interval (CI)=1.01-2.05), as well as an anxiety disorder (AOR=1.52, 95% CI=1.04-2.20) at Wave 2. ConclusionIn addition to the 13.7% of US older adults with lifetime MDD, an additional 13.8% have lifetime SSD, which is not a formally recognized diagnosis. In addition to its high prevalence, SSD is associated with elevated rates of comorbid mood, anxiety, and personality disorders, as well as the development of a new-onset MDD and anxiety disorder. These results underscore the importance of dimensional approaches to assessing depressive symptoms in older persons, as diagnostic approaches that rely on rigorous categorical classifications may fail to identify a substantial proportion of at-risk individuals. Copyright (c) 2014 John Wiley & Sons, Ltd.
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