Relationship Between Six Insulin Resistance Surrogates and Nonalcoholic Fatty Liver Disease Among Older Adults: A Cross-Sectional Study

被引:11
作者
Li, Haojie [1 ]
Shi, Zhan [2 ]
Chen, Xuejiao [1 ]
Wang, Junjie [1 ]
Ding, Jiacheng [1 ]
Geng, Shuoji [1 ]
Sheng, Xinyuan [1 ]
Shi, Songhe [1 ,3 ]
机构
[1] Zhengzhou Univ, Coll Publ Hlth, Dept Epidemiol & Hlth Stat, Zhengzhou, Henan, Peoples R China
[2] Zhengzhou Peoples Hosp, Dept Pharm, Zhengzhou, Henan, Peoples R China
[3] Zhengzhou Univ, Coll Publ Hlth, Dept Epidemiol & Hlth Stat, 100 Sci Ave, Zhengzhou, Henan, Peoples R China
来源
DIABETES METABOLIC SYNDROME AND OBESITY | 2023年 / 16卷
关键词
non-alcoholic fatty liver disease; insulin resistance surrogates; triglyceride-glucose index with body mass index; metabolic score for insulin resistance; PRODUCT;
D O I
10.2147/DMSO.S409983
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Non-alcoholic fatty liver disease (NAFLD) represents a large and growing public health problem. Insulin resistance (IR) plays a crucial role in the pathogenesis of NAFLD. The aim of this study was to determine the association of triglyceride-glucose (TyG) index, TyG index with body mass index (TyG-BMI), lipid accumulation product (LAP), visceral adiposity index (VAI), triglycerides/high-density lipoprotein cholesterol ratio (TG/HDL-c) and metabolic score for IR (METS-IR) with NAFLD in older adults and to compare the discriminatory abilities of these six IR surrogates for NAFLD.Methods: This cross-sectional study included 72,225 subjects aged >= 60 years living in Xinzheng, Henan Province, from January 2021 to December 2021. The data were collected from the annual health examination dataset. Logistic regression models were used to examine the relationships between the six indicators and NAFLD risk. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different IR surrogates for NAFLD under the influence of potential risk factors.Results: After adjusting for multiple covariates, compared with the first quintile, the odds ratios (ORs) and 95% confidence intervals (CIs) of the highest quintiles of TyG-BMI were the most obvious (OR:43.02, 95% CI:38.89-47.72), followed by the METS-IR (OR:34.49, 95% CI:31.41-37.95). Restricted cubic spline analysis reported that there were non-linear positive association and dose-response relationship between 6 IR surrogates and NAFLD risk. Compared with other IR-related indicators (LAP, TyG, TG/HDL-c and VAI), TyG-BMI showed the highest AUC (AUC:0.8059;95% CI:0.8025-0.8094). Additionally, METS-IR also had a high predictive performance for NAFLD, and the AUC was greater than 0.75 (AUC:0.7959;95% CI:0.7923-0.7994). Conclusion: TyG-BMI and METS-IR had pronounced discrimination ability to NAFLD, which are recommended as complementary markers for the assessment of NAFLD risk both in clinic and in future epidemiological studies.
引用
收藏
页码:1685 / 1696
页数:12
相关论文
共 41 条
  • [31] Systematic review with meta-analysis: risk factors for non-alcoholic fatty liver disease suggest a shared altered metabolic and cardiovascular profile between lean and obese patients
    Sookoian, S.
    Pirola, C. J.
    [J]. ALIMENTARY PHARMACOLOGY & THERAPEUTICS, 2017, 46 (02) : 85 - 95
  • [32] Comparison of several blood lipid-related indexes in the screening of non-alcoholic fatty liver disease in women: a cross-sectional study in the Pearl River Delta region of southern China
    Wang, Jingrui
    Su, Zhenzhen
    Feng, Yijin
    Xi, Ruihan
    Liu, Jiamin
    Wang, Peixi
    [J]. BMC GASTROENTEROLOGY, 2021, 21 (01)
  • [33] Usefulness of the triglyceride glucose-body mass index in evaluating nonalcoholic fatty liver disease: insights from a general population
    Wang, Rongsheng
    Dai, Longlong
    Zhong, Yanjia
    Xie, Guobo
    [J]. LIPIDS IN HEALTH AND DISEASE, 2021, 20 (01)
  • [34] Lipid accumulation product is a powerful index for recognizing insulin resistance in non-diabetic individuals
    Xia, C.
    Li, R.
    Zhang, S.
    Gong, L.
    Ren, W.
    Wang, Z.
    Li, Q.
    [J]. EUROPEAN JOURNAL OF CLINICAL NUTRITION, 2012, 66 (09) : 1035 - 1038
  • [35] Visceral adiposity index as a predictor of NAFLD: A prospective study with 4-year follow-up
    Xu, Chaonan
    Ma, Zhimin
    Wang, Yunfeng
    Liu, Xiangtong
    Tao, Lixin
    Zheng, Deqiang
    Guo, Xiuhua
    Yang, Xinghua
    [J]. LIVER INTERNATIONAL, 2018, 38 (12) : 2294 - 2300
  • [36] Association between the non-HDL-cholesterol to HDL-cholesterol ratio and non-alcoholic fatty liver disease in Chinese children and adolescents: a large single-center cross-sectional study
    Yang, Shouxing
    Zhong, Jinwei
    Ye, Mengsi
    Miao, Lei
    Lu, Guangrong
    Xu, Changlong
    Xue, Zhanxiong
    Zhou, Xinhe
    [J]. LIPIDS IN HEALTH AND DISEASE, 2020, 19 (01)
  • [37] METS-IR, a novel score to evaluate insulin sensitivity, is predictive of visceral adiposity and incident type 2 diabetes
    Yaxmehen Bello-Chavolla, Omar
    Almeda-Valdes, Paloma
    Gomez-Velasco, Donaji
    Viveros-Ruiz, Tannia
    Cruz-Bautista, Ivette
    Romo-Romo, Alonso
    Sanchez-Lazaro, Daniel
    Meza-Oviedo, Dushan
    Vargas-Vazquez, Arsenio
    Arellano Campos, Olimpia
    del Rocio Sevilla-Gonzalez, Magdalena
    Martagon, Alexandro J.
    Munoz Hernandez, Liliana
    Mehta, Roopa
    Rodolfo Caballeros-Barragan, Cesar
    Aguilar-Salinas, Carlos A.
    [J]. EUROPEAN JOURNAL OF ENDOCRINOLOGY, 2018, 178 (05) : 533 - 544
  • [38] Non-alcoholic fatty liver disease - A global public health perspective
    Younossi, Zobair M.
    [J]. JOURNAL OF HEPATOLOGY, 2019, 70 (03) : 531 - 544
  • [39] Molecular mechanisms of hepatic insulin resistance in nonalcoholic fatty liver disease and potential treatment strategies
    Zhang, Chang-hua
    Zhou, Bu-gao
    Sheng, Jun-qing
    Chen, Yang
    Cao, Ying-qian
    Chen, Chen
    [J]. PHARMACOLOGICAL RESEARCH, 2020, 159
  • [40] Unexpected Rapid Increase in the Burden of NAFLD in China From 2008 to 2018: A Systematic Review and Meta-Analysis
    Zhou, Feng
    Zhou, Jianghua
    Wang, Wenxin
    Zhang, Xiao-Jing
    Ji, Yan-Xiao
    Zhang, Peng
    She, Zhi-Gang
    Zhu, Lihua
    Cai, Jingjing
    Li, Hongliang
    [J]. HEPATOLOGY, 2019, 70 (04) : 1119 - 1133