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Depression, Obesity, and Metabolic Syndrome: Prevalence and Risks of Comorbidity in a Population-Based #03#

J Clin Psychiatry 2015;76(10):e1300–e1305

Introduction: We examined the prevalence of depression, obesity, and metabolic syndrome and associations between them in a population-based representative cohort of Mexican Americans living on the United States–Mexico border.

Method: The sample in this cross-sectional analysis consisted of 1,768 Mexican American adults ( 18 years of age) assessed between the years 2004 and 2010, with whom we tested our central hypothesis of a significant relationship between obesity and depression. Depression was measured using the Center for Epidemiologic Studies-Depression scale (CES-D) with a cutoff score of 16 for depression and a cutoff score of 27 for severe depression. We categorized body mass index (BMI) values as obese ( 30kg/m2) and later subdivided the obese subjects into obese (30–39 kg/m2[inclusive]) and morbidly obese ( 40 kg/m2). Metabolic syndrome was defined using the American Heart Association definition requiring at least 3 of the following: increased waist circumference, elevated triglycerides, reduced high-density lipoprotein (HDL) cholesterol, elevated blood pressure, and elevated fasting glucose. Weighted data were analyzed to establish prevalence of depression, obesity, and metabolic syndrome. Univariate and multivariable weighted regression models were used to test potential associations between these disorders.

Results: Using weighted prevalence, we observed high rates of depression (30%), obesity (52%), and metabolic syndrome (45%). Univariate models revealed female gender (P = .0004), low education (P = .003), low HDL level (P = .009), and increased waist circumference (P = .03) were associated with depression. Female gender (P = .01), low education (P = .003), and morbid obesity (P = .002) were risk factors for severe depression and remained significant in multivariable models.

Conclusions: In this large cohort of Mexican Americans, obesity, female gender, and low education were identified risk factors for depression. These indicators may serve as targets for early detection, prevention, and intervention in this population.