Pilar Laborde-Lahoz1,2, Renée El-Gabalawy3,4, Jolene Kinley3,4, Paul D Kirwin5,6, Jitender Sareen3,4, Robert H Pietrzak5,6,7. 1. Baylor College of Medicine, Houston, TX, USA. 2. Michael E. DeBakey VA Medical Center, Houston, TX, USA. 3. Department of Psychology, University of Manitoba, Winnipeg, Manitoba, Canada. 4. Department of Psychiatry, University of Manitoba, Winnipeg, Manitoba, Canada. 5. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA. 6. VA Connecticut Healthcare System, New Haven, CT, USA. 7. United States Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, VA Connecticut Healthcare System, West Haven, CT, USA.
Abstract
BACKGROUND: Population-based data are lacking on the prevalence and comorbidity of subsyndromal depression (SSD) and its associated risk for incident psychiatric disorders in older adults. METHODS: Using nationally representative data from 10,409 US adults aged 55 years 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. RESULTS: Some 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. CONCLUSION: In 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.
BACKGROUND: Population-based data are lacking on the prevalence and comorbidity of subsyndromal depression (SSD) and its associated risk for incident psychiatric disorders in older adults. METHODS: Using nationally representative data from 10,409 US adults aged 55 years 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. RESULTS: Some 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. CONCLUSION: In 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.
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