Association between the triglyceride-glucose index and hyperuricemia in an apparently healthy population with zero
Xing Guan1, Yu-Qiang Zuo2, Zhi-Hong Gao2
1Department of Physical Examination Center, People's Hospital of Shijiazhuang City, Shijiazhuang, Hebei, China.
Objective:
To investigate the association between the triglyceride-glucose (TyG) index and hyperuricemia (HUA) in an apparently healthy population, specifically defined as individuals presenting with zero components of metabolic syndrome (MetS) components. Unlike previous studies on general populations, this study focuses on a "metabolically clean" cohort to explore the early predictive value of the TyG index.
Methods:
This cross-sectional study included 1,181 metabolically healthy participants who did not meet even a single criterion for MetS (median age of 38.00 years; interquartile range: 33.00 - 47.00 years). Participants were stratified by TyG index quartiles (Q1-Q4). Multivariable logistic regression models were constructed to assess the association between the TyG index (as both a continuous and categorical variable) and HUA. Subgroup analyses were conducted to evaluate the robustness of this association across various clinical strata, and restricted cubic splines (RCS) were employed to characterize dose-response relationships.
Results:
The prevalence of HUA increased significantly across TyG quartiles (Q1: 4.01%; Q4: 11.50%, P for trend <0.001). In the fully-adjusted model (correcting for sex, age, body mass index, smoking status, drinking status, low-density lipoprotein cholesterol and estimated glomerular filtration rate), each unit increase in the TyG index was associated with a 2.208-fold increased risk of HUA [odds ratio (OR) =2.208; 95% confidence interval (CI): 1.088-4.481, P = 0.021]. Compared to Q1, participants in Q4 exhibited a significantly higher risk (OR = 1.916; 95% CI: 0.908-4.044, P = 0.088). Importantly, RCS analysis revealed a linear dose-response relationship between the TyG index and HUA risk (P for overall association =0.053, P for non-linearity =0.217). Receiver operating characteristic analysis demonstrated a modest discriminatory ability of the TyG index (area under curve=0.631) for HUA prediction.
Conclusion:
In an apparently healthy population with zero MetS components, the TyG index is independently and positively associated with HUA in linear dose-response manner. Our findings highlight the potential of the TyG index as a tool for risk stratification in primary prevention settings, particularly for ruling out HUA, even in individuals without overt metabolic disorders.
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