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Substance use and mental diagnoses among adults with and without type 2 diabetes: Results from electronic health records data.

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Date
2015-11
Authors
Wu, Li-Tzy
Ghitza, Udi E
Batch, Bryan C
Pencina, Michael J
Rojas, Leoncio Flavio
Goldstein, Benjamin A
Schibler, Tony
Dunham, Ashley A
Rusincovitch, Shelley
Brady, Kathleen T
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Abstract
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.
Type
Journal article
Subject
Humans
Diabetes Mellitus, Type 2
Substance-Related Disorders
Diagnosis, Dual (Psychiatry)
Prevalence
Mental Disorders
Anxiety Disorders
Mood Disorders
Personality Disorders
Schizophrenia
Age Factors
International Classification of Diseases
Adolescent
Adult
Aged
Aged, 80 and over
Middle Aged
Ethnic Groups
Female
Male
Young Adult
Electronic Health Records
Permalink
https://hdl.handle.net/10161/19948
Published Version (Please cite this version)
10.1016/j.drugalcdep.2015.09.003
Publication Info
Wu, 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.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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Scholars@Duke

Batch

Bryan Courtney Batch

Associate Professor of Medicine
Type 2 Diabetes, Obesity/Overweight, Behavior change, Non-pharmacologic intervention, Health disparities
Goldstein

Benjamin Alan Goldstein

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/
Pencina

Michael J Pencina

Professor of Biostatistics & Bioinformatics
As Vice Dean for Data Science, 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. Dr. Pencina is a Professor of Biostatistics and Bioinformatics at Duke University and Director of Duke AI Health. Previously, he served as Director of Biostatistics at the Duke Clinical Research Institute. Dr. Pencina is an internati
Rusincovitch

Shelley Rusincovitch

Senior Dir, IT
Wu

Li-Tzy Wu

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, Opio
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