Association of Long-Term HbA1c Variability with Anxiety and Depression in Patients with Type 2 Diabetes: A Cross-Sectional Retrospective Study.

Abstract

To explore the relationship between long-term glycemic variability and anxiety and depression in patients with type 2 diabetes. A cohort comprising 214 individuals diagnosed with type 2 diabetes participated in this study. Comprehensive demographic and laboratory information was gathered for them. The evaluation of anxiety relied on the 7-item Generalized Anxiety Disorder Scale (GAD-7), while depression was assessed utilizing the 9-item Health Questionnaire (PHQ-9). Based on the presence or absence of anxiety and depression, participants were categorized into either the mood disorder or control groups. Subsequently, univariate and stepwise multiple binary logistic regression analyses were conducted to investigate the potential correlations between factors and the presence of anxiety and depression. The prevalence of anxiety disorders is 23%, and depression is 32%. The prevalence of smoking, diabetic autonomic neuropathy, stroke, and osteoporosis in the mood disorder group was significantly higher than that in the control group (P < 0.05), the glycated hemoglobin A1c variability score (HVS), mean hemoglobin A1c value, total cholesterol, urinary albumin/creatinine and systemic immune-inflammatory index (SII) were significantly higher in the control group (P < 0.05). The level of high-density lipoprotein in the mood disorder group was significantly lower than the control group (P < 0.05). In stepwise multiple binary logistic regression analyses, the main factors associated with anxiety were depression (P < 0.001, OR=117.581) and gender (P < 0.001, OR=9.466), and the main factors related to depression included anxiety (P < 0.001, OR=49.424), smoking (P=0.042, OR=2.728), HVS (P=0.004, OR=8.664), and SII (P=0.014, OR=1.002). Persistent fluctuations in blood glucose levels have been linked to anxiety and depression. Consequently, maintaining an optimal level of glycemic control and minimizing fluctuations becomes imperative in the comprehensive management of diabetes.