Obesity and depression are major public health concerns that have substantial impacts on medical morbidity, health care expenditures, and quality of life. In 2002, the prevalence of obesity (defined as a body mass index [BMI, calculated as weight in kilograms divided by the square of height in meters] of e 30) among US adults was 31% and the lifetime prevalence of DSM-IV major depressive disorder was 13%. The co-occurrence of obesity and depression is also common and adults with both conditions may have even greater health risks. Notably, the risk of obesity may be heavily influenced by the choice of antidepressant drug therapy. The potential impact of antidepressant treatment on the risk of weight gain is a pressing issue for public health and clinical practice given that antidepressant agents are now the most commonly prescribed drugs in the United States. Between 1988 and 2002, the prevalence of antidepressant use more than tripled, from 2.5% to 8.1%;and, over the same time frame, the prevalence of obesity increased from 23% to 31%. These overlapping secular trends have prompted some investigators to propose pharmaceutical iatrogenesis as a significant contributor to the obesity epidemic. The primary objective of our proposed research is to examine the relationship between the choice of depression treatment, including pharmacotherapy as well as psychotherapy, and the long-term risk of weight gain on the population level. It would be prohibitively expensive to conduct a prospective randomized trial to address this objective. Therefore, we propose a retrospective observational study of more than 50,000 individuals with a new diagnosis of depression in an integrated health plan and care-delivery system from 2005 to 2009. The study will take advantage of our health care system's provision of comprehensive patient care with sophisticated electronic data systems that allow efficient identification of large populations with depression and obesity as well as assessments of long-term changes in body weight, health status, and health care use.
Our specific aims will describe the natural history of body weight change among adults with a new diagnosis of depression, examine the association between obesity and processes of depression care among adults with a new diagnosis of depression, and assess for differences in the trajectory of body weight change across individual antidepressants in a cohort of new antidepressant users. The analyses will integrate the disciplines of psychiatry, pharmacoepidemiology, primary care, biostatistics, and health services research to comprehensively address the relationship between obesity and depression care. This project will make novel use of the health care delivery system to investigate the epidemiology of weight gain in ways that could have broad-reaching implications for depression treatment in primary and specialty settings as well as future epidemiological studies of obesity.
Obesity and depression are major public health concerns that have substantial impacts on medical morbidity, health care expenditures, and quality of life. This project will make novel use of data from an integrated health plan and health care delivery system to investigate the hypothesis that the risk of long-term weight gain is related to the choice of antidepressant treatment among adults with depression.
Our specific aims will integrate the disciplines of psychiatry, pharmacoepidemiology, primary care, biostatistics, and health services research to comprehensively address the relationship between obesity and depression care.
| Haneuse, Sebastien; Bogart, Andy; Jazic, Ina et al. (2016) Learning About Missing Data Mechanisms in Electronic Health Records-based Research: A Survey-based Approach. Epidemiology 27:82-90 |
| Arterburn, David; Sofer, Tamar; Boudreau, Denise M et al. (2016) Long-Term Weight Change after Initiating Second-Generation Antidepressants. J Clin Med 5: |
| Haneuse, Sebastien (2016) Distinguishing Selection Bias and Confounding Bias in Comparative Effectiveness Research. Med Care 54:e23-9 |
| Haneuse, Sebastien; Daniels, Michael (2016) A General Framework for Considering Selection Bias in EHR-Based Studies: What Data Are Observed and Why? EGEMS (Wash DC) 4:1203 |
| Boudreau, Denise M; Arterburn, David; Bogart, Andy et al. (2013) Influence of body mass index on the choice of therapy for depression and follow-up care. Obesity (Silver Spring) 21:E303-13 |
