Liwei Ji,1,* Wencai Jiang,2,* Jinglin Huang,3,* Yan Xu,1,* Li Zhou,1,* Zeng Zhao,4 Chunling Jiang1 

1Department of Anesthesiology, West China Hospital, Sichuan University & The Research Units of West China (2018RU012), Chinese Academy of Medical Sciences, Chengdu, People’s Republic of China; 2Department of Cardiology, Suining Central Hospital, Suining, People’s Republic of China; 3Department of Cardiology, People’s Hospital of Leshan, Leshan, People’s Republic of China; 4Department of Cardiology, Jintang County First People’s Hospital, Chengdu, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Chunling Jiang, Department of Anesthesiology, West China Hospital, Sichuan University & The Research Units of West China (2018RU012), Chinese Academy of Medical Sciences, No. 37 Wainan Guoxue Road, Chengdu, 610400, People’s Republic of China, Email jiangchunling@scu.edu.cn Zeng Zhao, Department of Cardiology, Jintang County first People’s Hospital, No. 37 Wainan Guoxue Road, No. 886 Jin Guang Road, Chengdu, 610400, People’s Republic of China, Email 284439901@qq.com

Background: Gout, a rheumatic disease precipitated by hyperuricemia, has become a global health concern due to its increasing prevalence, especially in China. Hyperuricemia and hypertension are significant risk factors for gout, and their coexistence amplifies this risk. Visceral adipose tissue (VAT) plays a crucial role in cardiometabolic diseases, and the metabolic score for visceral fat (METS-VF) is a non-invasive tool for estimating VAT and predicting cardiometabolic risk.
Methods: We conducted a multicenter cross-sectional study involving 8877 patients with hypertension and hyperuricemia from three Chinese medical centers between March 2021 and September 2024. We calculated the METS-VF and other obesity indices and analyzed their associations with gout risk using logistic regression models. The predictive performance of these indices was evaluated using receiver operating characteristic (ROC) curve analysis and clinical decision curve analysis (DCA).
Results: The METS-VF demonstrated a significant positive association with gout risk, independent of traditional risk factors. Each 1-standard deviation increase in the METS-VF was associated with an 82% higher odds of gout (OR=1.82, 95% CI: 1.62 to 2.03). The METS-VF outperformed other obesity indices in predicting gout risk, with a higher area under the ROC curve (AUC) value. DCA indicated that the METS-VF provided a significant net benefit across a wide range of threshold probabilities for predicting gout risk in both genders.
Conclusion: The METS-VF’s robust association with gout risk in our multicenter study, independent of conventional risk factors, positions it as a potent predictor for gout. Further investigation is warranted to clarify the underlying mechanisms and the long-term predictive validity of the METS-VF across diverse populations.

Keywords: metabolic score for visceral fat, hypertension, hyperuricemia, gout, multicenter cross-sectional study