Correlation between Chinese visceral adiposity index and serum uric acid levels in type 2 diabetes mellitus patients - Araújo Intchasso Adotey, Swailla Amina; Zhang, Qian; Chen, Mengxue; Jiao, Yang; Zhang, Yin; Butoyi, Claudette; Wang, Dong; Yang, Ling; Yuan, Guoyue; Jia, Jue (Frontiers in Endocrinology, 2025)
PurposeThe Chinese Visceral Adiposity Index (CVAI), a measure of visceral adiposity dysfunction, is used to assess visceral fat (VFA) malfunction. This research was performed to evaluate the relationship between CVAI and serum uric acid levels in type 2 diabetes mellitus (T2DM) patients.MethodsA total of 2268 patients with T2DM were enrolled in this study. We collected the general clinical information of patients, measured the basic anthropometric indicators, tested glycolipid metabolism and biochemical indicators, and measured the visceral and subcutaneous fat area with bioelectrical impedance technology. According to the quartiles of the CVAI, the T2DM patients were classified into four groups: group A (CVAI ≤ 94.43), group B (94.43<CVAI ≤ 118.75), group C (118.75<CVAI ≤ 143.95), and group D (CVAI≥143.95), each group has 567 participants. Participants were divided into hyperuricemia (HUA) and non-HUA groups, and the clinical data between the two groups was compared.ResultsAmong quartiles of CVAI, as CVAI increased, the proportion of patients with HUA gradually increased. The correlation analysis showed that the majority of basal measures, glycolipid metabolism and biochemical indicators were positively correlated with CVAI. By comparison, the level of CVAI in the HUA group was significantly higher than non-HUA group. Meanwhile, through using the ROC curve, our study observed the more predictive value of CVAI than other obesity indicators for T2DM with HUA.ConclusionCVAI is a simple but effective indicator, which is significantly correlated with HUA in T2DM and can reflect the incidence of HUA in T2DM patients. As CVAI increased, the risk of HUA in T2DM patients increased. Therefore, we should pay more attention to the application of CVAI in T2DM.