The association of depression and diabetes across methods, measures, and study contexts

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  • Hunter, Jaimie C
    • Affiliation: Gillings School of Global Public Health, Department of Health Behavior
    • Other Affiliation: Department of Social Sciences and Health Policy, Division of Public Health Sciences, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA
  • DeVellis, Brenda M.
    • Affiliation: Gillings School of Global Public Health, Department of Health Behavior
  • Jordan, Joanne
    • Affiliation: School of Medicine, Thurston Arthritis Research Center
  • Kirkman, M. Sue
    • Affiliation: School of Medicine, Department of Medicine, Division of Endocrinology and Metabolism
    • Other Affiliation: Diabetes Care Center Clinical Trials Unit
  • Linnan, Laura
    • Affiliation: Gillings School of Global Public Health, Department of Health Behavior
  • Rini, Christine
    • Other Affiliation: Cancer Prevention and Control, John Theurer Cancer Center, Hackensack University Medical Center, Hackensack, NJ, USA; Department of Biomedical Research, Hackensack University Medical Center, Hackensack, NJ, USA; Department of Oncology, Georgetown University School of Medicine, Washington DC, USA
  • Fisher, Edwin
    • Affiliation: Gillings School of Global Public Health, Department of Health Behavior
Abstract
  • Abstract Background Empirical research has revealed a positive relationship between type 2 diabetes mellitus and depression, but questions remain regarding timing of depression measurement, types of instruments used to measure depression, and whether “depression” is defined as clinical depression or depressive symptoms. The present study sought to establish the robustness of the depression-diabetes relationship across depression definition, severity of depressive symptoms, recent depression, and lifetime depression in a nationally representative dataset and a large rural dataset. Methods The present examination, conducted between 2014 and 2015, used two large secondary datasets: the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2008 (n = 3072) and the Arthritis, Coping, and Emotion Study (ACES) from 2002 to 2006 (n = 2300). Depressive symptoms in NHANES were measured using the Patient Health Questionnaire 9-item survey (PHQ-9). ACES used the Center for Epidemiologic Studies—Depression Scale (CES-D) to measure depressive symptoms and the Composite International Diagnostic Interview (CIDI) to measure diagnosable depression. Diabetes was modelled as the dichotomous outcome variable (presence vs. absence of diabetes). Logistic regression was used for all analyses, most of which were cross-sectional. Analyses controlled for age, ethnicity, sex, education, and body mass index, and NHANES analyses used sample weights to account for the complex survey design. Additional analyses using NHANES data focused on the addition of health behavior variables and inflammation to the model. Results NHANES. Every one-point increase in depressive symptoms was associated with a 5% increase in odds of having diabetes [OR: 1.05 (CI: 1.03, 1.07)]. These findings persisted after controlling for health behaviors and inflammation. ACES. For every one-point increase in depressive symptom score, odds of having diabetes increased by 2% [OR: 1.02 (CI: 1.01, 1.03)]. Recent (past 12 months) depression [OR: 1.49, (CI: 1.03, 2.13)] and lifetime depression [OR: 1.40 (CI: 1.09, 1.81)] were also significantly associated with having diabetes. Conclusions This study provides evidence for the robustness of the relationship between depression or depressive symptoms and diabetes and demonstrates that depression occurring over the lifetime can be associated with diabetes just as robustly as that which occurs more proximal to the time of study measurement.
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  • Article
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  • In Copyright
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  • The Author(s).
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  • English
Bibliographic citation
  • Clinical Diabetes and Endocrinology. 2018 Jan 04;4(1):1
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  • BioMed Central

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