收稿日期: 2024-12-01
网络出版日期: 2025-04-30
基金资助
河北省医学科学研究重点研究计划基金资助项目(20230287);河北省政府资助临床医学优秀人才项目(ZF2025021)
The comparative study of TyG and TyG⁃BMI index with occurrence of hyperuricemia in physical examination population
Received date: 2024-12-01
Online published: 2025-04-30
目的 探讨甘油三酯-葡萄糖指数（TyG）和甘油三酯-葡萄糖-体质量指数（TyG-BMI）对健康体检人群高尿酸血症（HUA）发生的预测能力，筛选出合适指标作为HUA 风险评价工具。 方法 本研究最终纳入12 004名参加健康体检的研究对象，根据血清尿酸（SUA）水平分为正常组（n = 9 952）和HUA组（n = 2 052），计算TyG、TyG-BMI，根据二者水平的四分位数将研究对象分为Q1—Q4 4个组。通过二元logistic回归分析比较TyG、TyG-BMI与HUA之间的相关性；采用受试者工作特征（ROC）曲线和ROC曲线下面积（AUC）评估TyG、TyG-BMI及两者联合时对HUA的预测价值并进行不同性别和年龄的亚组分析。 结果 HUA组TyG、TyG-BMI均较正常组明显升高。TyG-Q4、TyG-BMI-Q4组中HUA的患病率明显高于其他相应3组。二元logistic回归显示TyG、TyG-BMI水平与HUA风险正相关。TyG、TyG-BMI及两者联合预测HUA的AUC分别为0.700、0.747和0.822；男性TyG、TyG-BMI及两者联合的AUC分别为0.641、0.674、0.709，女性分别为0.742、0.776、0.829，< 60岁人群TyG、TyG-BMI及两者联合的AUC分别为0.716、0.759、0.835，≥ 60岁人群分别为0.614、0.645、0.731。 结论 TyG、TyG-BMI与HUA发生风险显著相关，TyG-BMI较TyG更优，两者联合可进一步提升预测效能，尤其是在女性人群和中青年人群中。
关键词： 甘油三酯葡萄糖指数; 甘油三酯-葡萄糖-体质量指数; 高尿酸血症; 胰岛素抵抗; 疾病风险
聂倩 , 张雪梅 , 郝志华 , 谢若琳 , 刘焕欣 , 吴晓倩 , 任路平 . 甘油三酯-葡萄糖指数、甘油三酯-葡萄糖-体质量指数与健康体检人群高尿酸血症发生的关系[J]. 实用医学杂志, 2025 , 41(8) : 1192 -1198 . DOI: 10.3969/j.issn.1006-5725.2025.08.015
Objective To investigate the predictive capacity of the Triglyceride-Glucose （TyG） index and the Triglyceride-Glucose-Body Mass Index （TyG-BMI） for the development of hyperuricemia （HUA） in a health examination population， and to identify suitable indicators as risk assessment tools for HUA. Methods This study ultimately included 12 004 participants from a health examination cohort. According to SUA levels， the participants were categorized into a normal group （n = 9 952） and a hyperuricemia （HUA） group （n = 2 052）. The TyG index and TyG-BMI index were calculated， and participants were further stratified into four groups （Q1—Q4） based on the quartiles of these indices. Binary logistic regression analysis was performed to assess the association between TyG， TyG-BMI， and HUA. The predictive value of TyG， TyG-BMI， and their combination for HUA was evaluated using Receiver Operating Characteristic （ROC） curves and the Area Under the Curve （AUC）. Subgroup analyses were carried out by gender and age. Results The TyG and TyG-BMI indices were significantly elevated in the HUA group compared to the normal group. The prevalence of HUA was markedly higher in the TyG-Q4 and TyG-BMI-Q4 groups than in the other three corresponding quartile groups. Binary logistic regression analysis revealed a positive association between TyG， TyG-BMI levels， and the risk of HUA. The AUC values for predicting HUA using TyG， TyG-BMI， and their combination were 0.700， 0.747， and 0.822， respectively. Specifically， for males， the AUC values were 0.641， 0.674， and 0.709， respectively， whereas for females， they were 0.742， 0.776， and 0.829， respectively. Among individuals younger than 60 years old， the AUC values were 0.716， 0.759， and 0.835， respectively， while for those aged 60 years or older， the values were 0.614， 0.645， and 0.731， respectively. Conclusions TyG and TyG-BMI are significantly associated with the risk of HUA. Specifically， TyG-BMI demonstrates superior predictive performance compared to TyG alone. Moreover， the combination of TyG and TyG-BMI further improves predictive accuracy， particularly among female and middle-aged or younger populations.
Key words： TyG; TyG-BMI; hyperuricemia; insulin resistance; disease risk
| 1 | 中华医学会内分泌学分会. 中国高尿酸血症与痛风诊疗指南（2019）［J］. 中华内分泌代谢杂志， 2020，36（1）：1-13. |
| 2 | DAWSON J， WYSS A. Chicken or the Egg？ Hyperuricemia， Insulin Resistance， and Hypertension［J］. Hypertension， 2017，70（4）：698-699. doi:10.1161/hypertensionaha.117.09685 |
| 3 | RUDVIK A， MANSSON M. Evaluation of surrogate measures of insulin sensitivity-Correlation with gold standard is not enough［J］. BMC Med Res Methodol， 2018，18（1）：64. doi:10.1186/s12874-018-0521-y |
| 4 | SANCHEZ-GARCIA A， RODRIGUEZ-GUTIERREZ R， MANCILLAS-ADAME L， et al. Diagnostic Accuracy of the Triglyceride and Glucose Index for Insulin Resistance： A Systematic Review［J］. Int J Endocrinol， 2020，2020：4678526. doi:10.1155/2020/4678526 |
| 5 | LUO Y， LIU L， LIU M， et al. Relationship Between Body Composition and Insulin Resistance Evaluated by the TyG Index： A Retrospective Study Among Chinese Population［J］. Clin Endocrinol （Oxf）， 2025， 102（3）：264-272. doi:10.1111/cen.15171 |
| 6 | JOG K S， EAGAPPAN S， SANTHARAM R K， et al. Comparison of Novel Biomarkers of Insulin Resistance With Homeostasis Model Assessment of Insulin Resistance， Its Correlation to Metabolic Syndrome in South Indian Population and Proposition of Population Specific Cutoffs for These Indices［J］. Cureus， 2023，15（1）：e33653. |
| 7 | PARK H M， LEE H S， LEE Y J， et al. The triglyceride-glucose index is a more powerful surrogate marker for predicting the prevalence and incidence of type 2 diabetes mellitus than the homeostatic model assessment of insulin resistance［J］. Diabetes Res Clin Pract， 2021，180：109042. doi:10.1016/j.diabres.2021.109042 |
| 8 | KHAN S H， SOBIA F， NIAZI N K， et al. Metabolic clustering of risk factors： Evaluation of Triglyceride-glucose index （TyG index） for evaluation of insulin resistance［J］. Diabetol Metab Syndr， 2018，10：74. doi:10.1186/s13098-018-0376-8 |
| 9 | 宦丽君， 王鹏云. 甘油三酯葡萄糖指数及相关内脏肥胖指标对老年人群高尿酸血症发生风险的预测价值［J］. 检验医学与临床， 2023，20（10）：1345-1348， 1353. |
| 10 | 赵美茹， 朱迪， 刘琳， 等. 简易胰岛素抵抗指标与698例2型糖尿病患者发生高尿酸血症风险的关联［J］. 山东大学学报（医学版）， 2022，60（12）：44-51. |
| 11 | LIU X Z， XU X， ZHU J Q， et al. Association between three non-insulin-based indexes of insulin resistance and hyperuricemia［J］. Clin Rheumatol， 2019，38（11）：3227-3233. doi:10.1007/s10067-019-04671-6 |
| 12 | 杨玉环，王军，马茂. 2型糖尿病患者血清尿酸水平与颈动脉粥样硬化斑块及10年心血管疾病风险分析［J］. 中国循证心血管医学杂志，2023，15（12）：1322-1324，1333. |
| 13 | NIE Q， ZHANG X， HAO Z， et al. Impact of Serum Uric Acid Concentration on the Risk of Cardiovascular Disease： A Cohort Study Conducted in Northern China［J］. Arq Bras Cardiol， 2021，117（4）：666-675. |
| 14 | OLOFSSON C， ANDERSTAM B， BRAGFORS-HELIN A C， et al. Effects of acute fructose loading on levels of serum uric acid-a pilot study［J］. Eur J Clin Invest， 2019，49（1）：e13040. doi:10.1111/eci.13040 |
| 15 | 陈发胜，余俊文，周茹，等. 佛山市三水区中老年人群尿酸水平的相关危险因素分析［J］. 热带医学杂志，2015，15（4）：539-541. |
| 16 | KUANG M， YANG R， HUANG X， et al. Assessing temporal differences in the predictive power of baseline TyG-related parameters for future diabetes： An analysis using time-dependent receiver operating characteristics［J］. J Transl Med， 2023，21（1）：299. doi:10.1186/s12967-023-04159-7 |
| 17 | GAO Q， LIN Y， XU R， et al. Positive association of triglyceride-glucose index with new-onset hypertension among adults： A national cohort study in China［J］. Cardiovasc Diabetol， 2023，22（1）：58. doi:10.1186/s12933-023-01795-7 |
| 18 | 汪宇， 缪莹， 林强， 等. 甘油三酯葡萄糖指数联合腰围对泸州地区中老年人群10年新发冠心病的前瞻性队列研究［J］. 实用医学杂志， 2024，40（12）：1731-1736. |
| 19 | 张冰， 孙秋， 杜丽明， 等. 前瞻性队列研究—甘油三酯葡萄糖指数与急性胰腺炎发病风险［J］. 实用医学杂志， 2023，39（23）：3116-3119. doi:10.3969/j.issn.1006-5725.2023.23.016 |
| 20 | ADNAN E， RAHMAN I A， FARIDIN H P. Relationship between insulin resistance， metabolic syndrome components and serum uric acid［J］. Diabetes Metab Syndr， 2019，13（3）：2158-2162. doi:10.1016/j.dsx.2019.04.001 |
| 21 | ZHANG X， NIE Q， ZHANG Z， et al. Resveratrol affects the expression of uric acid transporter by improving inflammation［J］. Mol Med Rep， 2021，24（2）：564. doi:10.3892/mmr.2021.12203 |
| 22 | MIAO Z， YAN S， WANG J， et al. Insulin resistance acts as an independent risk factor exacerbating high-purine diet induced renal injury and knee joint gouty lesions［J］. Inflamm Res， 2009，58（10）：659-668. doi:10.1007/s00011-009-0031-9 |
| 23 | CUI N， CUI J， SUN J， et al. Triglycerides and Total Cholesterol Concentrations in Association with Hyperuricemia in Chinese Adults in Qingdao， China［J］. Risk Manag Healthc Policy， 2020，13：165-173. doi:10.2147/rmhp.s243381 |
| 24 | KOJTA I， CHACINSKA M， BLACHNIO-ZABIELSKA A. Obesity， Bioactive Lipids， and Adipose Tissue Inflammation in Insulin Resistance［J］. Nutrients， 2020，12（5）：1305. doi:10.3390/nu12051305 |
| 25 | 蒋绒，李永霞. 甘油三酯葡萄糖乘积指数联合肥胖指标对阻塞性睡眠呼吸暂停患者发生非酒精性脂肪性肝病的预测价值［J］. 临床肝胆病杂志，2023，39（3）：546-551. |
| 26 | RAMIREZ-VELEZ R， PEREZ-SOUSA M A， GONZALEZ-RUIZ K， et al. Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association： An Analysis of the 2015 Health， Well-Being， and Aging Study［J］. Nutrients， 2019，11（11） ：2654. doi:10.3390/nu11112654 |
| 27 | WAN H， ZHANG K， WANG Y， et al. The Associations Between Gonadal Hormones and Serum Uric Acid Levels in Men and Postmenopausal Women With Diabetes［J］. Front Endocrinol （Lausanne）， 2020，11：55. doi:10.3389/fendo.2020.00055 |
| 28 | WU X， ZHOU M， BU J， et al. Prevalence and Risk Factors of Hyperuricemia in the Urban Health Checkup Population in Xinjiang， China： A Cross-Sectional Study［J］. Risk Manag Healthc Policy. 2023，14；16：1531-1544. doi:10.2147/rmhp.s423794 |
| 29 | YANG Y， ZHOU W， WANG Y， et al. Gender-specific association between uric acid level and chronic kidney disease in the elderly health checkup population in China［J］. Ren Fail， 2019，41（1）：197-203. doi:10.1080/0886022x.2019.1591994 |
| 30 | 冯颖倩，王梦君，张海雄，等. 不同年龄高尿酸血症患者临床特征及其发病影响因素分析［J］. 临床和实验医学杂志，2024，23（2）：149-153. |
| 31 | XIONG J， ZHENG X， LUO J， et al. A follow-up study to explore factors associated with rapid kidney function decline and new-onset kidney disease among Chinese elderly population［J］. Geriatr Gerontol Int， 2022，22（11）：968-975. doi:10.1111/ggi.14480 |
/
| 〈 |
|
〉 |