Diabetes, Metabolic Syndrome and Obesity (Nov 2023)

Sex-Specific Contribution of Cardiometabolic Index in Predicting Metabolic Dysfunction-Associated Fatty Liver Disease: Insights from a General Population

  • Gu D,
  • Lu Y,
  • Xu B,
  • Tang X

Journal volume & issue
Vol. Volume 16
pp. 3871 – 3883

Abstract

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Dongxing Gu,1,* Yayun Lu,1,* Baiqing Xu,1 Xuefeng Tang2 1Health Examination Center, Huadong Sanatorium, Wuxi, People’s Republic of China; 2Department of Health Nursing, Huadong Sanatorium, Wuxi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Baiqing Xu; Xuefeng Tang, Huadong Sanatorium, No. 67 Jinyuan Road, Wuxi, 214065, People’s Republic of China, Email [email protected]; [email protected] and Objective: Evidence suggests that cardiometabolic index (CMI) has been identified as a novel obesity-related index associated with diabetes, hypertension, and cardiovascular disease. Current evidence suggests that the differences in sex hormones and regional fat distribution in both sexes are directly correlated with metabolic dysfunction-associated fatty liver disease (MAFLD) risk. This study aimed to investigate the diagnostic value of CMI in MAFLD in both sexes.Methods: This retrospective study included 6107 subjects who underwent annual health check-ups from March 2021 to January 2022. CMI was calculated by multiplying the ratio of triglycerides and high-density lipoprotein cholesterol (TG/HDL-C) by waist-to-height ratio (WHtR). Multivariable logistic regression analysis and restricted cubic spline were used to investigate the association of CMI and MAFLD risk. Receiver operating characteristic curve analysis was conducted for the exploration of the diagnostic accuracies of obesity-related indicators. Areas under the curves (AUCs) with 95% CIs were calculated.Results: Prevalence of MAFLD increased with elevated quartiles of CMI in both sexes. The median (IQR) age was 46.00 (18.00) years. Multivariate logistic regression analyses showed that higher CMI was independently associated with MAFLD, in which every additional standard deviation (SD) of CMI increased the risk of MAFLD (OR=2.72, 95% CI:2.35– 3.15 for males; OR=3.26, 95% CI:2.36– 4.51 for females). Subjects in the fourth quartile of CMI had the highest odds of MAFLD for males (OR=15.82, 95% CI:11.84– 21.14) and females (OR=22.60, 95% CI:9.52– 53.65)(all P for trend< 0.001). Besides, CMI had a non-linearity association with MAFLD (all P for non-linearity< 0.001). Furthermore, CMI exhibited the largest AUC compared to other obesity-related indexes in terms of discriminating MAFLD in males (AUC=0.796, 95% CI:0.782– 0.810) and females (AUC=0.853, 95% CI:0.834– 0.872).Conclusion: CMI was a convenient indicator for the screening of MAFLD among Chinese adults. Females with high CMI had a better diagnostic value for MAFLD than males.Keywords: metabolic dysfunction-associated fatty liver disease, cardiometabolic index, sex, general population, predicting value

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