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
  • [1] Lipid accumulation product (LAP) as a potential index to predict risk of insulin resistance in young, non-obese Asian Indian males from Southern India: observations from hyperinsulinemic-euglycemic clamp studies
    Anoop, Shajith S.
    Dasgupta, Riddhi
    Rebekah, Grace
    Jose, Arun
    Inbakumari, Mercy Prem
    Finney, Geethanjali
    Thomas, Nihal
    [J]. BMJ OPEN DIABETES RESEARCH & CARE, 2021, 9 (01)
  • [2] Bril F, 2017, HEPATOLOGY, V65, P1132, DOI [10.1002/hep.28985, 10.1002/hep.2]
  • [3] Dose-Response Associations of Metabolic Score for Insulin Resistance Index with Nonalcoholic Fatty Liver Disease among a Nonobese Chinese Population: Retrospective Evidence from a Population-Based Cohort Study
    Cai, Xintian
    Gao, Jing
    Hu, Junli
    Wen, Wen
    Zhu, Qing
    Wang, Mengru
    Liu, Shasha
    Hong, Jing
    Wu, Ting
    Yang, Shunfan
    Tuerxun, Guzailinuer
    Li, Nanfang
    [J]. DISEASE MARKERS, 2022, 2022
  • [4] Non-Alcoholic Fatty Liver Disease
    Engin, Atilla
    [J]. OBESITY AND LIPOTOXICITY, 2017, 960 : 443 - 467
  • [5] Modeling NAFLD disease burden in China, France, Germany, Italy, Japan, Spain, United Kingdom, and United States for the period 2016-2030
    Estes, Chris
    Anstee, Quentin M.
    Teresa Arias-Loste, Maria
    Bantel, Heike
    Bellentani, Stefano
    Caballeria, Joan
    Colombo, Massimo
    Craxi, Antonio
    Crespo, Javier
    Day, Christopher P.
    Eguchi, Yuichiro
    Geier, Andreas
    Kondili, Loreta A.
    Kroy, Daniela C.
    Lazarus, Jeffrey V.
    Loomba, Rohit
    Manns, Michael P.
    Marchesini, Giulio
    Nakajima, Atsushi
    Negro, Francesco
    Petta, Salvatore
    Ratziu, Vlad
    Romero-Gomez, Manuel
    Sanyal, Arun
    Schattenberg, Joern M.
    Tacke, Frank
    Tanaka, Junko
    Trautwein, Christian
    Wei, Lai
    Zeuzem, Stefan
    Razavi, Homie
    [J]. JOURNAL OF HEPATOLOGY, 2018, 69 (04) : 896 - 904
  • [6] Non-alcoholic fatty liver disease and type 2 diabetes mellitus: The liver disease of our age?
    Firneisz, Gabor
    [J]. WORLD JOURNAL OF GASTROENTEROLOGY, 2014, 20 (27) : 9072 - 9089
  • [7] The Product of Triglycerides and Glucose, a Simple Measure of Insulin Sensitivity. Comparison with the Euglycemic-Hyperinsulinemic Clamp
    Guerrero-Romero, Fernando
    Simental-Mendia, Luis E.
    Gonzalez-Ortiz, Manuel
    Martinez-Abundis, Esperanza
    Ramos-Zavala, Maria G.
    Hernandez-Gonzalez, Sandra O.
    Jacques-Camarena, Omar
    Rodriguez-Moran, Martha
    [J]. JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM, 2010, 95 (07) : 3347 - 3351
  • [8] Metabolic-associated fatty liver disease and lipoprotein metabolism
    Heeren, Joerg
    Scheja, Ludger
    [J]. MOLECULAR METABOLISM, 2021, 50
  • [9] The triglyceride glucose-body mass index: a non-invasive index that identifies non-alcoholic fatty liver disease in the general Japanese population
    Hu, Haofei
    Han, Yong
    Cao, Changchun
    He, Yongcheng
    [J]. JOURNAL OF TRANSLATIONAL MEDICINE, 2022, 20 (01)
  • [10] Risk stratification of non-alcoholic fatty liver disease across body mass index in a community basis
    Huang, Jee-Fu
    Tsai, Pei-Chien
    Yeh, Ming-Lun
    Huang, Chung-Feng
    Huang, Ching-, I
    Hsieh, Meng-Hsuan
    Dai, Chia-Yen
    Yang, Jeng-Fu
    Chen, Shinn-Chern
    Yu, Ming-Lung
    Chuang, Wan-Long
    Chang, Wen-Yu
    [J]. JOURNAL OF THE FORMOSAN MEDICAL ASSOCIATION, 2020, 119 (01) : 89 - 96