Diabetes and depression have become two major public health challenges. Depression can reduce the treatment adherence of patients with diabetes, exacerbate diabetic complications and mortality, and severely affect the quality of life of patients. However, currently, clinicians tend to focus on biological factors while neglecting psychological factors. As a result, the diagnosis rate of depression in diabetic patients is low. Therefore, it is of great clinical significance to actively identify and screen type 2 diabetic patients at risk of depression and to conduct in-depth analysis of various influencing factors.

With the increasing incidence of diabetes, the related psychological problems are also becoming more and more concerned. In order to overcome the limitations of selection bias in single-center surveys, we conducted a nationwide multicenter survey to investigate the prevalence of depression and its influencing factors among patients with type 2 diabetes mellitus (T2DM) in China, and to provide a basis for developing mental health intervention strategies for diabetic patients.

A nationwide multicenter observational study was conducted using a probability proportional to size (PPS) sampling method. A total of 2 137 patients with T2DM were recruited from 52 hospitals across China. The Patient Health Questionnaire-9 (PHQ-9) was used to assess depressive symptoms (PHQ-9≥10 indicated depression). Through a review of the literature, 29influential factors were identified: fasting blood glucose, 2-hour postprandial blood glucose, glycated hemoglobin, and lipid profiles, triglyceride-glucose index (TyG), diabetes duration, diabetes complications, anddiabetes comorbidities. Multivariate logistic regression analysis was performed to identify factors associated with depression in T2DM patients. Use the statistical software R package to analyze whether there is a nonlinear relationship between age, TyG, and depression and calculate the inflection point.

Among 1 659 patients with type 2 diabetes, the prevalence of depression was 13.3% (220 cases). Multivariate logistic regression analysis identified the following independent risk factors for depression in type 2 diabetes patients: gender (female OR=1.815, 95%CI=1.220-2.701), age (OR=0.969, 95%CI=0.952-0.987), education level (below high school: OR=1.488, 95%CI=1.049-2.11), marital status (unmarried and others: OR=1.864, 95%CI=1.068-3.254), BMI (OR=0.936, 95%CI=0.896-0.977), ecomomic difficulties (OR=3.654, 95%CI=2.403-5.558), duration of disease (OR=1.031, 95%CI=1.006-1.057), diabetic peripheral neuropathy (OR=2.17, 95%CI=1.275-3.693), cardiovascular disease (OR=1.844, 95%CI=1.248-2.723), hypertension (OR=1.625, 95%CI=1.163-2.271), and TyG (OR=1.717, 95%CI=1.026-2.874)(P<0.05). After controlling for confounding factors, TyG showed a linear positive correlation with depression (P_nonlinear=0.191), while age exhibited a linear negative correlation with depression in the male population (P_nonlinear=0.946). The age of women was not linearly related to depression (P_nonlinear=0.013), and the time inflection point of the relationship was 49 years old (OR=0.921, 95%CI=0.857-0.99, P_nonlinear=0.025; OR=1.036, 95%CI=1.003-1.07, P_nonlinear=0.0323).

The prevalence of depression among Chinese patients with T2DM was 13.3%. Patients with low education levels, non-marital status, financial difficulties, high TyG index, and comorbid conditions such as diabetic peripheral neuropathy, cardiovascular disease, and hypertension were more likely to develop depression. Among male patients, the prevalence of depression decreased with increasing age. Among female patients, the relationship between age and the incidence of depression in the diabetic population followed a J-shaped curve, The risk of depression increases again after the age of 49. Early screening and intervention for depression are recommended for these high-risk groups to improve the overall health status and quality of life of T2DM patients.