Substance use and mental diagnoses among adults with and without type 2 diabetes: Results from electronic health records data.
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BACKGROUND:Comorbid diabetes and substance use diagnoses (SUD) represent a hazardous combination, both in terms of healthcare cost and morbidity. To date, there is limited information about the association of SUD and related mental disorders with type 2 diabetes mellitus (T2DM). METHODS:We examined the associations between T2DM and multiple psychiatric diagnosis categories, with a focus on SUD and related psychiatric comorbidities among adults with T2DM. We analyzed electronic health record (EHR) data on 170,853 unique adults aged ≥18 years from the EHR warehouse of a large academic healthcare system. Logistic regression analyses were conducted to estimate the strength of an association for comorbidities. RESULTS:Overall, 9% of adults (n=16,243) had T2DM. Blacks, Hispanics, Asians, and Native Americans had greater odds of having T2DM than whites. All 10 psychiatric diagnosis categories were more prevalent among adults with T2DM than among those without T2DM. Prevalent diagnoses among adults with T2MD were mood (21.22%), SUD (17.02%: tobacco 13.25%, alcohol 4.00%, drugs 4.22%), and anxiety diagnoses (13.98%). Among adults with T2DM, SUD was positively associated with mood, anxiety, personality, somatic, and schizophrenia diagnoses. CONCLUSIONS:We examined a large diverse sample of individuals and found clinical evidence of SUD and psychiatric comorbidities among adults with T2DM. These results highlight the need to identify feasible collaborative care models for adults with T2DM and SUD related psychiatric comorbidities, particularly in primary care settings, that will improve behavioral health and reduce health risk.
Diabetes Mellitus, Type 2
Diagnosis, Dual (Psychiatry)
International Classification of Diseases
Aged, 80 and over
Electronic Health Records
Published Version (Please cite this version)10.1016/j.drugalcdep.2015.09.003
Publication InfoWu, Li-Tzy; Ghitza, Udi E; Batch, Bryan C; Pencina, Michael J; Rojas, Leoncio Flavio; Goldstein, Benjamin A; ... Brady, Kathleen T (2015). Substance use and mental diagnoses among adults with and without type 2 diabetes: Results from electronic health records data. Drug and alcohol dependence, 156. pp. 162-169. 10.1016/j.drugalcdep.2015.09.003. Retrieved from https://hdl.handle.net/10161/19948.
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Associate Professor of Medicine
Type 2 Diabetes, Obesity/Overweight, Behavior change, Non-pharmacologic intervention, Health disparities
Associate Professor of Biostatistics & Bioinformatics
I study the meaningful use of Electronic Health Records data. My research interests sit at the intersection of biostatistics, biomedical informatics, machine learning and epidemiology. I collaborate with researchers both locally at Duke as well as nationally. I am interested in speaking with any students, methodologistis or collaborators interested in EHR data.Please find more information at: https://sites.duke.edu/bgoldstein/
Professor of Biostatistics & Bioinformatics
As vice dean of data science and information technology, Dr. Pencina is responsible for developing and implementing quantitative science strategies as they pertain to the education and training, and laboratory, clinical science, and data science missions of the School of Medicine. He leads the School’s IT strategic direction and investments, working in collaboration with the vice presidents and chief information officers of Duke Health and Duke University’s Office of Information T
Assoc Dir, IT
Professor in Psychiatry and Behavioral Sciences
Education/Training: Pre- and post-doctoral training in mental health service research, psychiatric epidemiology (NIMH T32), and addiction epidemiology (NIDA T32) from Johns Hopkins University School of Public Health (Maryland); Fellow of the NIH Summer Institute on the Design and Conduct of Randomized Clinical Trials.Director: Duke Community Based Substance Use Disorder Research Program.Research interests: COVID-19, Opioid misuse, Opioid overdose, Opioid use disorder
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