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Association of insulin resistance surrogate indices, lipid metabolism, and obesity-related indicators with hyperuricemia in middle-aged and elderly adults in Guangxi, China
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Mo-qi ZHANG, Yuan YANG, Chao-fan XIE, Ze-yan YE, Zhi-yong ZHANG
Modern Preventive Medicine | 2026, 53(15) : 2699 - 2705
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Modern Preventive Medicine | 2026, 53(15): 2699-2705
• Epidemiology and Statistical Method •
Association of insulin resistance surrogate indices, lipid metabolism, and obesity-related indicators with hyperuricemia in middle-aged and elderly adults in Guangxi, China
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Mo-qi ZHANG, Yuan YANG, Chao-fan XIE, Ze-yan YE, Zhi-yong ZHANG
Affiliations
  • School of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
Published: 2026-08-10 doi: 10.20043/j.cnki.MPM.202601444
Outline
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Objective

To explore the associations of nine indices related to insulin resistance, lipid metabolism, and obesity,including estimated glucose disposal rate (eGDR), triglyceride glucose index (TyG), metabolic score for insulin resistance(METS-IR), triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C ratio), TyG-waist circumference (TyG-WC),TyG-body mass index (TyG-BMI), TyG-waist-to-height ratio (TyG-WHtR), a body shape index (ABSI), and conicity index(CI), with hyperuricemia (HUA) among middle-aged and elderly individuals in a county in Guangxi, to screen for key indicators, and to validate them through a cohort study.

Methods

A combined cross-sectional and prospective cohort study design was employed. Multivariable logistic regression analysis was used to evaluate the association between each index and HUA. Five machine learning models, including XGBoost, were constructed to evaluate the performance of these indices and screen for key indices. In the prospective cohort, modified Poisson regression and restricted cubic splines (RCS) were utilized to analyze the association and dose-response relationship between the most critical index and the risk of incident HUA.

Results

Multivariable logistic regression showed that after adjusting for covariates, TyG, METS-IR, TG/HDL-C ratio, TyG-WC, TyG-BMI, TyG-WHtR, ABSI, and CI were positively associated with HUA, whereas eGDR was negatively associated with HUA (P<0.001). The machine learning model results indicated that the TG/HDL-C ratio was the most critical index for identifying HUA.A non-linear association was observed between the TG/HDL-C ratio and the risk of incident HUA (P<0.001), with a threshold of 2.971 for the TG/HDL-C ratio in relation to HUA.

Conclusion

All nine indices were associated with HUA in middle-aged and elderly people. The TG/HDL-C ratio was the most critical index for identifying HUA, which holds important public health significance for the early identification of individuals with hyperuricemia.

Hyperuricemia  /  Insulin resistance  /  Machine learning  /  Prospective cohort study
张墨奇, 杨远, 谢超凡, 叶泽严, 张志勇. 广西中老年人胰岛素抵抗替代指数、脂质代谢及肥胖相关指数与高尿酸血症的关联性研究. 现代预防医学, 2026 , 53 (15) : 2699 -2705 . DOI: 10.20043/j.cnki.MPM.202601444
Mo-qi ZHANG, Yuan YANG, Chao-fan XIE, Ze-yan YE, Zhi-yong ZHANG. Association of insulin resistance surrogate indices, lipid metabolism, and obesity-related indicators with hyperuricemia in middle-aged and elderly adults in Guangxi, China[J]. Modern Preventive Medicine, 2026 , 53 (15) : 2699 -2705 . DOI: 10.20043/j.cnki.MPM.202601444
Year 2026 volume 53 Issue 15
244
103
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doi: 10.20043/j.cnki.MPM.202601444
  • Receive Date:2026-01-25
  • Online Date:2026-09-28
  • Published:2026-08-10
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  • Received:2026-01-25
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    School of Public Health, Guilin Medical University, Guilin, Guangxi 541199, China
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表12种不同金属材料的力学参数
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Family
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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