Association between uric acid to high-density lipoprotein ratio and mental health symptoms in people with type 2 diabetes

BACKGROUND The association between the uric acid-to-high-density lipoprotein cholesterol ratio (UHR) and mental health among individuals with type 2 diabetes mellitus (T2DM) has not been thoroughly investigated. AIM To examine the link between UHR and symptoms of depression and anxiety in patients with T2DM. METHODS A cross-sectional analysis was carried out from March 2023 to April 2024, involving participants diagnosed with T2DM. Data on sociodemographic characteristics, clinical parameters, and UHR values were systematically gathered. The Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS) were utilized to evaluate depressive and anxiety symptoms, respectively. To assess the relationships between UHR and SDS/SAS scores, linear regression models were employed, incorporating adjustments for potential confounding variables. Additionally, smooth curve fitting and threshold effect analyses were conducted to explore potential nonlinear relationships. RESULTS A total of 285 patients with T2DM were included. Initial univariate analysis demonstrated a significant positive correlation between elevated UHR levels and higher SDS and SAS scores. Multivariate regression analysis revealed that a one-unit rise in UHR was associated with a 1.13-point increase in SDS scores (95%CI: 0.69-1.58) and a 0.57-point increase in SAS scores (95%CI: 0.20-0.93). After controlling for confounders, UHR remained positively correlated with SDS (β = 1.55, 95%CI: 0.57-2.53) and SAS (β = 0.72, 95%CI: 0.35-1.09). Nonlinear analysis identified critical thresholds at UHR values of 5.02 for SDS and 4.00 for SAS, beyond which the relationships between UHR and psychological symptom scores became markedly stronger (P < 0.05). CONCLUSION Higher UHR levels are significantly linked to exacerbated depressive and anxiety symptoms in patients with T2DM. These results indicate that UHR may function as a promising biomarker to identify individuals at greater risk of mental health complications within this population.