Diagnostic criteria for depression in type 2 diabetes: A data-driven approach

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10 Citations (Scopus)


©2014 Starkstein et al. Background: While depression is a frequent psychiatric comorbid condition in diabetes and has significant clinical impact, the syndromal profile of depression and anxiety symptoms has not been examined in detail. Aims: To determine the syndromal pattern of the depression and anxiety spectrum in a large series of patients with type 2 diabetes, as determined using a data-driven approach based on latent class analysis (LCA). Method: Type 2 diabetes participants from the observational community-based Fremantle Diabetes Study Phase II underwent assessment of lifetime depression using the Brief Lifetime Depression Scale, the Patient Health Questionnaire 9- item version (PHQ-9) for current depression symptoms, and the Generalized Anxiety Disorder Scale that was specifically developed and validated for this study. The main outcome measure was classes of patients with a specific syndromal profile of depression and anxiety symptoms based on LCA. Results: LCA identified four classes that were interpreted as "major anxious depression", "minor anxious depression", "subclinical anxiety", and "no anxious depression". All nine DSM-IV/5 diagnostic criteria for major depression identified a class with a high frequency of major depression. All symptoms of anxiety had similar high probabilities as symptoms of depression for the "major depression-anxiety" class. There were significant differences between classes in terms of history of depression and anxiety, use of psychoactive medication, and diabetes-related variables. Conclusions: Patients with type 2 diabetes show specific profiles of depression and anxiety. Anxiety symptoms are an integral part of major depression in type 2 diabetes. The different classes identified here provide empirically validated phenotypes for future research.
Original languageEnglish
Pages (from-to)1-9
JournalPLoS One
Issue number11
Publication statusPublished - 2014


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