超重或肥胖人群合并非酒精性脂肪性肝病与TyG的相关性研究

doi:10.3760/cma.j.issn.1007-1245.2022.01.022

摘要/Abstract

摘要： 目的　探讨伴或不伴非酒精性脂肪性肝病（NAFLD）的超重或肥胖人群与三酰甘油-葡萄糖指数（TyG）的关系。方法　本文研究设计类型属于横断面研究。选取2020年1月至10月于川北医学院附属医院健康管理中心体检的年龄18岁以上的男性和女性共5 685例，根据体质量指数（BMI）分为正常体质量组（NG组，2 397例）和超重或肥胖组（OG组，3 288例）。同时依据是否合并NAFLD把OG组分为无NAFLD组（Non-NAFLD组，1 670例）以及合并NAFLD组（NAFLD组，1 618例），计算TyG，比较各组间TyG、一般资料及临床生化指标的差异。符合正态分布的计量资料以均数±标准差（x±s）表示，不符合正态分布的计量资料数据使用M（P₂₅，P₇₅）表示，组间比较采用独立样本t检验或非参数秩和检验，相关性采用Pearson或Spearman相关分析和多元线性逐步回归分析，二元logistic回归分析超重或肥胖人群合并NAFLD的影响因素。结果　与NG组和Non-NAFLD组比较，OG组及NAFLD组的年龄、腰臀比（WHR）、血压、空腹血糖（FPG）、糖化血红蛋白（HbA_1C）、肝肾功能、血脂和TyG水平比较差异均有统计学意义（均P<0.05）。相关性分析发现，TyG与年龄、收缩压（SBP）、舒张压（DBP）、FPG、HbA_1C、门冬氨酸氨基转移酶（AST）、丙氨酸氨基转移酶（ALT）、碱性磷酸酶（ALP）、谷氨酰转肽酶（GGT）、总蛋白、白蛋白、肌酐（Cr）、尿酸（UA）、三酰甘油（TG）、总胆固醇（TC）和极低密度脂蛋白胆固醇（VLDL-C）呈正相关（r=0.044、0.190、0.245、0.512、0.449、0.144、0.232、0.183、0.392、0.081、0.187、0.075、0.256、0.836、0.355、0.718，均P<0.05），而与球蛋白（r=-0.040，P=0.021）和高密度脂蛋白胆固醇（HDL-C）（r=-0.408，P<0.001）呈负相关。多元线性逐步回归分析发现，年龄、DBP、FPG、GGT、白蛋白、UA、TG、TC、HDL-C和VLDL-C均是TyG的独立影响因素；二元logistic回归分析显示，TyG、HbA_1C、ALT、白蛋白、UA和LDL-C均是超重或肥胖人群合并NAFLD的危险因素（均OR>1，均P<0.05），而FPG、Cr和TC均是其保护因素（均OR<1，均P<0.05）。结论　TyG与超重或肥胖合并NAFLD关系密切。

关键词: 超重或肥胖, 非酒精性脂肪性肝病, 胰岛素抵抗, 三酰甘油-葡萄糖指数

Abstract: Objective　To investigate the correlation between the triglyceride glucose index (TyG) and overweight or obese people with or without non-alcoholic fatty liver disease (NAFLD). Methods　A total of 5 685 over 18 years old males and females who underwent physical examination in Affiliated Hospital of North Sichuan Medical College from January to October 2020 were selected and divided into a normal body mass group (an NG group; 2 397 cases) and an overweight or obese group (an OG group; 3 288 cases) according to body mass index (BMI). At the same time, the OG group was divided into a non-NAFLD group (1 670) and an NAFLD group (1 618) according to whether they had NAFLD or not. TyG was calculated and the differences in TyG, general data and clinical biochemical indexes were compared between the groups. The measurement data of normal distribution were expressed as (x±s) and compared between the groups by independent-sample t test. The measurement data not of normal distribution were expressed as M (P₂₅, P₇₅) and compared between the groups by Mann-Whitney U test. The correlations were analyzed by Pearson correlation analysis, Spearman correlation analysis, or stepwise linear regression analysis. The influencing factors of overweight or obese people with NAFLD were analyzed by binary logistic regression analysis. Results　Compared with those in the NG group and the non-NAFLD group, the ages, waist-hip ratios (WHR), blood pressures, fasting blood glucose (FPG), glycated hemoglobin (HbA_1C), liver and kidney function, blood lipid and TyG levels in the OG group and the NAFLD group were statistically different (all P<0.05). Correlation analysis showed that TyG was positively correlated with age, systolic blood pressure (SBP), diastolic blood pressure (DBP), FPG, HbA_1C, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), glutamyl transpeptidase (GGT), total protein, albumin, creatinine (Cr), uric acid (UA), triglyceride (TG), total cholesterol (TC), and very low density lipoprotein cholesterol (VLDL-C) (r=0.044, 0.19, 0.245, 0.512, 0.449, 0.144, 0.232, 0.183, 0.392, 0.081, 0.187, 0.075, 0.256, 0.836, 0.355, and 0.718; all P<0.05), and negatively with globulin (r=-0.04, P=0.021) and high density lipoprotein cholesterol (HDL-C) (r=-0.408, P<0.001). Multiple linear stepwise regression analysis showed that age, DBP, FPG, GGT, albumin, UA, TG, TC, VLDL-C, and HDL-C were the independent influencing factors of TyG. Binary logistic regression analysis showed that TyG, HbA_1C, ALT, albumin, UA and LDL-C were the risk factors for NAFLD in the overweight or obese patients (all OR>1, all P<0.05), while FPG, Cr, and TC were the protective factors (all OR<1, all P<0.05). Conclusion　TyG is closely related to overweight or obesity combined with NAFLD.

Key words: Overweight or obese, Non-alcoholic fatty liver disease, Insulin resistance, Triglyceride glucose index

杨丹, 周小燕, 江毅敏, 雷蓉, 柳弥. 超重或肥胖人群合并非酒精性脂肪性肝病与TyG的相关性研究[J]. 国际医药卫生导报, 2022, 28(1): 90-95.

Yang Dan, Zhou Xiaoyan, Jiang Yimin, Lei Rong, Liu Mi. Correlation between non-alcoholic fatty liver disease and TyG in overweight or obese people [J]. International Medicine and Health Guidance News, 2022, 28(1): 90-95.

参考文献

[1] Younossi ZM. Non-alcoholic fatty liver disease - A global public health perspective[J]. J Hepatol, 2019,70(3): 531-544. DOI: 10.1016/j.jhep.2018.10.033.

[2] Muniyappa R, Lee S, Chen H, et al. Current approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage[J]. Am J Physiol Endocrinol Metab, 2008, 294(1): E15-E26. DOI: 10.1152/ajpendo.00645.2007.

[3] Guerrero-Romero F, Simental-Mendía LE, González-Ortiz M, et al. The product of triglycerides and glucose, a simple measure of insulin sensitivity. Comparison with the euglycemic-hyperinsulinemic clamp[J]. J Clin Endocrinol Metab, 2010,95(7): 3347-3351. DOI: 10.1210/jc. 2010- 0288.

[4] Lim J, Kim J, Koo SH, et al. Comparison of triglyceride glucose index, and related parameters to predict insulin resistance in Korean adults: an analysis of the 2007-2010 Korean National Health and Nutrition Examination Survey[J]. PLoS ONE, 2019, 14(3): e0212963. DOI: 10.1371/journal.pone.0212963.

[5] 郑卉,程阳,尹冬华,等. 非高密度脂蛋白胆固醇和三酰甘油葡萄糖乘积指数及三酰甘油高密度脂蛋白胆固醇比值评估代谢综合征的价值研究[J]. 中国全科医学,2021,24(3):322-326, 332. DOI:10.12114/j.issn.1007-9572. 2020. 00.564.

[6] Li X, Li G, Cheng T, et al. Association between triglyceride-glucose index and risk of incident diabetes: a secondary analysis based on a Chinese cohort study: TyG index and incident diabetes[J]. Lipids Health Dis, 2020,19(1): 236. DOI: 10.1186/s12944-020-01403-7.

[7] 张燕华,唐奇志,陈聪,等. TyG指数与2型糖尿病患者非酒精性脂肪肝相关性研究[J].中国医药科学,2019,9(7): 12-15. DOI:10.3969/j.issn.2095-0616.2019.07.004.

[8] 中华医学会肝病学分会脂肪肝和酒精性肝病学组, 中国医师协会脂肪性肝病专家委员会. 非酒精性脂肪性肝病防治指南(2018 年更新版)[J]. 实用肝脏病杂志, 2018, 34(5): 947-957. DOI:10.3969/j.issn.1672-5069.2018.02.007.

[9] 中国超重肥胖医学营养治疗专家共识编写委员会. 中国超重/肥胖医学营养治疗专家共识(2016年版)[J]. 中华糖尿病杂志, 2016,24(10):525-540. DOI:10.3760/cma.j.issn.1674-5809.2016.09.004.

[10] Haslam DW, James WP. Obesity[J]. Lancet, 2005,366(9492):1197-1209. DOI: 10.1016/S0140-6736(05)67483-1.

[11] Facchini FS, Hua N, Abbasi F, et al. Insulin resistance as a predictor of age-related diseases[J]. J Clin Endocrinol Metab, 2001,86(8): 3574-3578. DOI: 10.1210/jcem. 86.8.7763.

[12] Watt MJ, Miotto PM, De Nardo W, et al. The liver as an endocrine organ-linking NAFLD and insulin resistance[J]. Endocr Rev,2019,40(5):1367-1393. DOI: 10.1210/er.2019-00034.

[13] Vasques A, Novaes FS, Oliveira M, et al. TyG index performs better than HOMA in a Brazilian population: a hyperglycemic clamp validated study[J]. Diabetes Res Clin Pract, 2011,93(3): e98-e100. DOI: 10.1016/j.diabres. 2011.05.030.

[14] Park K, Ahn CW, Lee SB, et al. Elevated TyG index predicts progression of coronary artery calcification[J]. Diabetes Care, 2019,42(8):1569-1573. DOI: 10.2337/dc18-1920.

[15] 孙洁,周卫红,顾天伟, 等. 南京鼓楼医院体检人群超重率和肥胖率及其与心血管疾病风险因素的关联研究[J]. 中华内分泌代谢杂志,2021,37(1):39-44. DOI: 10.3760/cma.j.cn311282-20200430-00318.

[16] Younossi Z, Anstee QM, Marietti M, et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention[J]. Nat Rev Gastroenterol Hepatol, 2018,15(1): 11-20. DOI: 10.1038/nrgastro.2017.109.

[17] 张婷,谢雪,刘玉萍,等. 四川地区中老年体检人群非酒精性脂肪性肝病患病率调查及与代谢相关指标的相关性分析[J]. 现代预防医学,2020,47(12):2267-2271.

[18] Musso G, Gambino R, Tabibian JH, et al. Association of non-alcoholic fatty liver disease with chronic kidney disease: a systematic review and meta-analysis[J]. PLoS Med, 2014, 11(7): e1001680. DOI: 10.1371/journal.pmed.1001680.

[19] Mantovani A, Zaza G, Byrne CD, et al. Nonalcoholic fatty liver disease increases risk of incident chronic kidney disease: a systematic review and meta-analysis[J]. Metabolism, 2018, 79(2): 64-76. DOI: 10.1016/j.metabol. 2017.11.003.

[20] 魏文志,王力,温晓华,等. TyG指数与体检人群非酒精性脂肪性肝病相关性分析[J].中华保健医学杂志, 2019,21(3): 212-215. DOI: 10.3969/.issn.1674-3245.2019.03.006.