Combined obesity- and lipid-related indices are associated with hypogonadism in Chinese male patients with type 2 diabetes: a cross-sectional study - Yu, Yongzhuo; Wang, Yunyang; Xu, Lili; Li, Wenxuan (Frontiers in Endocrinology, 2024)
BackgroundThere is insufficient attention to hypogonadism in Chinese males with type 2 diabetes mellitus (T2DM). We evaluated the relationship between Combined obesity- and lipid-related indices [Visceral Adiposity Index (VAI), Chinese Visceral Adiposity Index (CVAI), Triglyceride Glucose Index (TyG) and Lipid Accumulation Product (LAP)] with total testosterone (TT) and analyzed the predictive capability of the respective cut-off values.MethodsWe recruited 958 hospitalized male patients with T2DM at the Affiliated Hospital of Qingdao University, collected baseline data and four calculated indices, and obtained their dominance ratio (OR) and corresponding 95% confidence intervals (CI) with TT by multivariate logistic regression. Receiver operating characteristic (ROC) curves were then used to determine cutoff values in predicting hypogonadism (TT< 12 nmol/L), and we also analyzed the combinations between the different indices.ResultsVAI, CVAI, TyG, and LAP all have satisfactory predictive capabilities. The test capability (sensitivity and specificity) of all four indices was better or not worse than that of body mass index (BMI), homeostasis model assessment of insulin resistance (HOMA-IR) and waist circumference (WC). All four indices were effective predictors of hypogonadism at their respective cutoff values (VAI ≥ 2.284, CVAI ≥ 145.779, TyG ≥ 4.308, and LAP ≥ 59.850). Of these, LAP had the largest area under the curve (AUC, AUC = 0.852, Std. Error = 0.014, 95% CI = 0.818-0.873). However, the predictive capability of the combined indices was not significantly improved over the individual indices.ConclusionsVAI, CVAI, TyG, and LAP are sensitive indices for predicting hypogonadism in Chinese male patients with T2DM. Considering the need for concise and accurate indices in clinical practice, we suggest LAP as a commonly used index.