Journal
HEALTH AND QUALITY OF LIFE OUTCOMES
Volume 9, Issue -, Pages -Publisher
BMC
DOI: 10.1186/1477-7525-9-90
Keywords
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Funding
- AHRQ
- Mayo Foundation for Medical Education and Research
- Pfizer
- National Alliance for Schizophrenia and Depression (NARSAD)
- National Institute of Mental Health (NIMH)
- National Institute of Alcohol Abuse and Alcoholism (NIAAA)
- Mayo Foundation
- Astra-Zeneca
- Bristol-Myers Squibb
- Eli Lilly and Co.
- GlaxoSmithKline
- Merck
- Otsuka Pharmaceuticals
- Sanofi-Aventis
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Background: Existing literature on mood disorders suggests that the demographic distribution of bipolar disorder may differ from that of unipolar depression, and also that bipolar disorder may be especially disruptive to personal functioning. Yet, few studies have directly compared the populations with unipolar depressive and bipolar disorders, whether in terms of demographic characteristics or personal limitations. Furthermore, studies have generally examined work-related costs, without fully investigating the extensive personal limitations associated with diagnoses of specific mood disorders. The purpose of the present study is to compare, at a national level, the demographic characteristics, work productivity, and personal limitations among individuals diagnosed with bipolar disorder versus those diagnosed with unipolar depressive disorders and no mood disorder. Methods: The Medical Expenditure Panel Survey 2004-2006, a nationally representative survey of the civilian, non-institutionalized U.S. population, was used to identify individuals diagnosed with bipolar disorder and unipolar depressive disorders based on ICD-9 classifications. Outcomes of interest were indirect costs, including work productivity and personal limitations. Results: Compared to those with depression and no mood disorder, higher proportions of the population with bipolar disorder were poor, living alone, and not married. Also, the bipolar disorder population had higher rates of unemployment and social, cognitive, work, and household limitations than the depressed population. In multivariate models, patients with bipolar disorder or depression were more likely to be unemployed, miss work, and have social, cognitive, physical, and household limitations than those with no mood disorder. Notably, findings indicated particularly high costs for bipolar disorder, even beyond depression, with especially large differences in odds ratios for non-employment (4.6 for bipolar disorder versus 1.9 for depression, with differences varying by gender), social limitations (5.17 versus 2.85), cognitive limitations (10.78 versus 3.97), and work limitations (6.71 versus 3.19). Conclusion: The bipolar disorder population is distinctly more vulnerable than the population with depressive disorder, with evidence of fewer personal resources, lower work productivity, and greater personal limitations. More systematic analysis of the availability and quality of care for patients with bipolar disorder is encouraged to identify effectively tailored treatment interventions and maximize cost containment.
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