Detection and Quantification of the Relationship between the Ratio of Triglycerides over High-Density Lipoprotein Cholesterol and the Level of Serum Uric Acid: One Cross-Sectional Study

Abstract

Background. Hyperuricemia acts as an independently known risk factor for diabetes, cardiovascular disease, and gout. It was previously reported that the ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) is not only an important marker of cardiovascular disease, stroke, atherosclerosis, and insulin resistance but is also associated with an elevated level of serum uric acid. However, it is still poorly understood what the association is between TG/HDL-C and serum uric acid levels. Hence, the aim of this research was to determine this association. Methods. A total of 5,402 participants who underwent physical examinations in 2021 were analyzed during our cross-sectional research. In order to verify this correlation between TG/HDL-C and uric acid, we performed both a generalized additive model (GAM) and a smoothing curve fit. We also performed receiver operating characteristic (ROC) curves for evaluation of differences in clinical risk factor models in identifying hyperuricemia risk before and after the introduction of TG/HDL-C. Results. Upon adjustment for confounders, we found that there was a nonlinear positive correlation between TG/HDL-C and the level of uric acid, and the inflection point was 1.41. When TG/HDL-C was less than 1.41, the effect size was 40.56 (19.08-62.04, P = 0.0002), whereas when TG/HDL-C was more than 1.41 the effect size was 17.18 (3.70-30.65, P=0.0125). As shown by the ROC curve, a significant increase in the area under the curve (AUC) was observed upon the introduction of TG/HDL-C into the established risk factor model which elevated from 0.7206(0.7053-0.7359, P<0.05) to 0.8291 (0.8175-0.8407, P<0.05). Conclusion. Therefore, TG/HDL-C is positively and nonlinearly correlated to the level of uric acid, and the inflection point is 1.41. Furthermore, TG/HDL-C leads to an improvement in hyperuricemia risk stratification.