Predictive factors and risk model for depression in patients with type 2 diabetes mellitus: a comprehensive analysis of comorbidities and clinical indicators - Duan, Chengzheng; Luo, Cheng; Jiang, Weifeng; Xu, Hui; Chen, Yexing; Xu, Shiyu; Zhang, Xiaofang; Chen, Xiaoli; He, Dongjuan (Frontiers in Endocrinology, 2025)
ObjectiveDepression is highly prevalent among individuals with type 2 diabetes mellitus (T2DM), often compounded by multiple chronic conditions. This study aimed to identify the key factors influencing depression in this population, with a particular focus on the relationship between the Cumulative Illness Rating Scale (CIRS) score and depression, and to evaluate the predictive value of a model incorporating sex, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), and CIRS score.MethodsA total of 308 hospitalized patients with type 2 diabetes from Quzhou Hospital, Wenzhou Medical University were enrolled. Their clinical and biochemical data were collected, alongside assessments of comorbidities and depressive symptoms using the CIRS and Self-Rating Depression Scale (SDS), respectively. LASSO regression with 10-fold cross-validation was used to identify the optimal variables for the predictive model. Multivariate analysis was performed to assess the independent associations between sex, BMI, LDL-C, and CIRS score with depression. The relationship between CIRS scores and depression was further explored across various subgroups. The predictive model’s value was assessed through ROC curve analysis.ResultsFemale sex (OR: 2.48, 95% CI: 1.50-4.10, p < 0.001), lower BMI (OR: 0.92, 95% CI: 0.86-0.98, p = 0.015), lower LDL-C (OR: 0.77, 95% CI: 0.61-0.98, p = 0.031), and higher CIRS scores (OR: 1.11, 95% CI: 1.05-1.18, p < 0.001) were independently linked to depression after adjusting for clinical variables. A strong association between CIRS score and depression was observed, particularly in males, patients under 60 years old, those with a disease duration of less than 5 years, and individuals with no history of smoking or alcohol consumption. Additionally, a predictive model incorporating sex, BMI, LDL-C, and CIRS score demonstrated high accuracy in identifying patients at risk for depression.ConclusionsFemale, lower BMI, lower LDL-C and higher CIRS score were independently associated with depression in patients with type 2 diabetes. The CIRS score appeared to be more effective in predicting depression risk in people who were male, younger, shorter DM duration, no smoking or no drinking. A more comprehensive prediction model could help clinicians identify patients with type 2 diabetes who are at risk for depression.