肥胖代谢指数与武汉市新洲区成年人高尿酸血联研究

doi:10.12183/j.scjpm.2026.1141

摘要/Abstract

摘要： 目的分析武汉市新洲区成年人群中肥胖代谢指数与高尿酸血症（HUA）的关联,比较不同肥胖代谢指数对HUA的预测价值,为HUA高风险人群的早期识别和制定针对性的干预措施提供依据。方法选取武汉市新洲区18岁及以上成年人作为研究对象,通过问卷调查、体格检查和实验室检测收集数据。采用logistic回归分析不同肥胖代谢指数包括甘油三酯与高密度脂蛋白胆固醇比值（TG/HDL-C）、甘油三酯-葡萄糖指数（TyG）、甘油三酯葡萄糖-身体质量指数（TyG-BMI）、甘油三酯葡萄糖-腰围指数（TyG-WC）、胰岛素抵抗代谢评分（METS-IR）、内脏脂肪代谢评分（METS-VF）、体脂率（BFP）、腰围身高比（WHtR）、身体圆度指数（BRI）、中国内脏肥胖指数（CVAI））与HUA的相关性,并利用限制性立方样条分析剂量-反应关系。通过受试者操作特征曲线计算曲线下面积（AUC）并比较肥胖代谢指数对HUA的预测价值。结果本研究共纳入741名调查对象,平均年龄（49.11±15.74）岁,HUA患病率为26.5%（196例）。在调整协变量后,不同肥胖代谢指数均与HUA患病风险呈显著正相关。其中,TG/HDL-C、TyG-WC与HUA存在非线性剂量-反应关系（P_总趋势<0.001,P_非线性<0.05）。TyG-WC是预测成年人HUA的最佳指标（AUC=0.721,P<0.001）。结论肥胖代谢指数与成年人HUA患病风险显著相关。其中TyG-WC是预测HUA的最佳指标。因此,监测肥胖代谢指数对于成年人HUA预防有重要意义。

关键词: 高尿酸血症, 肥胖代谢指数, 预测价值

Abstract: Objective To investigate the association between obesity metabolic indices and hyperuricemia (HUA) among adults in Xinzhou District, Wuhan, and to compare the predictive value of different obesity metabolic indices for HUA, thus providing a basis for early identification of high-risk population and the development of targeted interventions. Methods A cross-sectional study was conducted among adults aged 18 years and older in Xinzhou District, Wuhan. Data were collected through questionnaires, physical examinations, and laboratory tests. Logistic regression analysis was employed to assess the correlations between various obesity metabolic indices, including the triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C), triglyceride-glucose index (TyG), triglyceride-glucose-body mass index (TyG-BMI), triglyceride-glucose-waist circumference (TyG-WC), insulin resistance metabolic score (METS-IR), visceral fat metabolic score (METS-VF), body fat percentage (BFP), waist-to-height ratio (WHtR), body roundness index (BRI), and the Chinese visceral adiposity index (CVAI), and HUA. The dose-response relationship was explored using restricted cubic splines. The predictive value of the obesity metabolic indices for HUA was further evaluated through the calculation of the area under the receiver operating characteristic curve (AUC). Results A total of 741 participants were included, with a mean age of (49.11 ± 15.74) years. The prevalence of HUA was 26.5% (196 cases). After adjusting for covariates, all obesity metabolic indices were significantly associated with an increased risk of HUA. Notably, TG/HDL-C and TyG-WC demonstrated nonlinear dose-response relationships with HUA (P_{for trend} < 0.001, P_{for nonlinearity} < 0.05). Among these indices, TyG-WC exhibited the highest predictive capability for HUA in adults, with an AUC of 0.721 (P < 0.001). Conclusion Obesity metabolic indices were significantly associated with the risk of HUA in adults. Among them, TyG-WC was the most effective predictor of HUA. Therefore, it is of great importance to monitor obesity metabolic indices for the prevention of HUA in adults.

Key words: Hyperuricemia, Obesity metabolic index, Predictive value

中图分类号:

R195.4

胡永峰, 陈海燕, 刘嘉雯, 李鑫锐, 何启强. 肥胖代谢指数与武汉市新洲区成年人高尿酸血联研究[J]. 华南预防医学, 2026, 52(10): 1141-1147.

Hu Yongfeng, Chen Haiyan, Liu Jiawen, Li XinRui, He Qiqiang. Association between obesity metabolic index and hyperuricemia among adults of Xinzhou District, Wuhan[J]. South China Journal of Preventive Medicine, 2026, 52(10): 1141-1147.

参考文献

[1] Li Y, Yi S, Jiang W, et al.Exploring the relationship between different obesity metabolism indices and hyperuricemia in patients with hypertension and coronary heart disease[J]. Diabetes Metab Syndr Obes, 2024, 17: 3817-3832.
[2] Yanai H, Adachi H, Hakoshima M, et al.Molecular biological and clinical understanding of the pathophysiology and treatments of hyperuricemia and its association with metabolic syndrome, cardiovascular diseases and chronic kidney disease[J]. Int J Mol Sci, 2021, 22(17): 9211.
[3] 梁恒妙, 黄锶哲, 陈玉婷, 等. 健康体检人群血尿酸水平与胰岛素抵抗程度关系的研究[J]. 中国全科医学, 2025, 28(21): 2635-2642.
[4] Gu X, Gao P, Shen Y, et al.Non-linear association between visceral adipose tissue area and serum uric acid concentration in US adults: Findings from NHANES 2011-2018[J]. BMC Public Health, 2025, 25(1): 1405.
[5] Gui J, Li Y, Liu H, et al.Obesity-and lipid-related indices as a predictor of obesity metabolic syndrome in a national cohort study[J]. Front Public Health, 2023, 11: 1073824.
[6] Gou R, Dou D, Tian M, et al.Association between triglyceride glucose index and hyperuricemia: A new evidence from China and the United States[J]. Front Endocrinol(Lausanne), 2024, 15: 1403858.
[7] Kahaer M, Zhang B, Chen W, et al.Triglyceride glucose index is more closely related to hyperuricemia than obesity indices in the medical checkup population in Xinjiang, China[J]. Front Endocrinol(Lausanne), 2022, 13: 861760.
[8] Zhou S, Yu Y, Zhang Z, et al.Association of obesity, triglyceride-glucose and its derivatives index with risk of hyperuricemia among college students in Qingdao, China[J]. Front Endocrinol(Lausanne), 2022, 13: 1001844.
[9] 中华医学会风湿病学分会. 高危高尿酸血症药物降尿酸治疗专家共识(2025版)[J]. 中华医学杂志, 2025, 105(29): 2469-2482.
[10] Bello-chavolla OY, Antonio-villa NE, Vargas-vázquez A, et al. Metabolic score for visceral fat(METS-VF), a novel estimator of intra-abdominal fat content and cardio-metabolic health[J]. Clin Nutr, 2020, 39(5): 1613-1621.
[11] Feng X, Zhu J, Hua Z, et al.Comparison of obesity indicators for predicting cardiovascular risk factors and multimorbidity among the Chinese population based on ROC analysis[J]. Sci Rep, 2024, 14(1): 20942.
[12] Simonavičius E, Perman-howe PR, Robson D, et al. Psychological distress, tobacco smoking and alcohol use: A population survey in Great Britain[J]. Addict Behav Rep, 2025, 21: 100604.
[13] Robert Lourdes TG, Abd Hamid HA, Riyadzi MR, et al.Findings from a nationwide study on alcohol consumption patterns in an upper middle-income country[J]. Int J Environ Res Public Health, 2022, 19(14) :8851.
[14] World Health Organization.WHO guidelines on physical activity and sedentary behaviour[M]. Geneva: World Health Organization, 2020.
[15] Im PK, Kartsonaki C, Kakkoura MG, et al.Hyperuricemia, gout and the associated comorbidities in China: Findings from a prospective study of 0.5 million adults[J]. Lancet Reg Health West Pac, 2025, 58: 101572.
[16] Wan Z, Song L, Hu L, et al.Temporal trends in hyperuricaemia among adults in Wuhan city, China, from 2010 to 2019: A cross-sectional study[J]. BMJ Open, 2021, 11(3): e043917.
[17] 郑雯, 段绍杰, 陈佳良, 等. 体脂指标对高尿酸血症发生风险的预测价值[J]. 中国临床保健杂志, 2022, 25(6): 779-784.
[18] 王迪, 王希, 尹福在, 等. 中国人内脏脂肪指数与2型糖尿病合并高尿酸血症的相关性研究[J]. 河北医药, 2022, 44(11): 1699-1701, 1705.
[19] Zhang Q, Liu J, Zhang R, et al.TyG-WC index as a superior predictor of hyperuricemia risk in the hypertensive population: A prospective cohort study[J]. Diabetes Metab Syndr Obes, 2025, 18: 679-689.
[20] Panlu K, Zhou Z, Huang L, et al.Associations between obesity and hyperuricemia combing mendelian randomization with network pharmacology[J]. Heliyon, 2024, 10(6): e27074.
[21] 刘文清, 熊昱鹏, 李丽华, 等. 肥胖引发心血管疾病的相关机制研究进展[J]. 临床医学进展, 2023, 13(8): 12887-12893.
[22] Fujii W, Yamazaki O, Hirohama D, et al.Gene-environment interaction modifies the association between hyperinsulinemia and serum urate levels through SLC22A12[J]. J Clin Invest, 2025, 135(10) :e186633.
[23] Mandal AK, Leask MP, Sumpter NA, et al.Genetic and physiological effects of Insulin-Like Growth Factor-1 (IGF-1) on human urate homeostasis[J]. J Am Soc Nephrol, 2023, 34(3): 451-466.
[24] 梁盛兴, 邹俐爱, 邱恒, 等. 1990—2021年中国归因于高BMI的慢性肾病疾病负担研究[J]. 卫生经济研究, 2025, 42(4): 42-46, 52.