He DH, Zhang YZ, Xu L, Pei JJ, Zhang Y, Yan ZF. Relationship between metabolic associated fatty liver disease and body fat ratio, visceral fat area, and resting metabolic rate estimated by bioelectrical impedance analysis.
Shijie Huaren Xiaohua Zazhi 2023;
31:56-65. [DOI:
10.11569/wcjd.v31.i2.56]
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Abstract
BACKGROUND
It is very important to identify the risk of metabolic associated fatty liver disease (MAFLD) in early stage, and body components measured by bioelectrical impedance analysis (BIA) would be a new way to achieve the prediction safely and noninvasively.
AIM
To measure the body composition by BIA, and explore the association of body fat ratio (BFR), visceral fat area (VFA), and resting metabolic rate (RMR) with MAFLD.
METHODS
A total of 509 subjects were divided into either a MAFLD group or a non-MAFLD group. Indicators of anthropo-metric measurements, BIA, and laboratory tests were collected. Spearman correlation analysis, receiver operating characteristic (ROC) curve analysis, and binary logistic regression analysis were used to explore the relationship of BFR, VFA, and RMR with MAFLD.
RESULTS
The differences in BFR, VFA, and RMR between the MAFLD group and the non-MAFLD group were statisti-cally significant both in male and female subjects (P < 0.05), and BFR, VFA, and RMR were significantly correlated with alanine aminotransferase, total bilirubin, triglyceride (TG), total cholesterol, fasting blood-glucose (FBG), and postprandial blood glucose (P < 0.05). The area under the ROC curve (AUC) values of BFR, VFA, and RMR were 0.800 (95% confidence interval [CI]: 0.752-0.875), 0.894 (95%CI: 0.847-0.941), and 0.715 (95%CI: 0.639-0.790), respectively, and VFA was the best indicator with a cutoff value of 87.10 cm2 (87.25 cm2 in males and 117.05 cm2 in females). The odds ratio values of BFR, VFA, and RMR were 1.357 (95%CI: 1.214-1.517), 1.079 (95%CI: 1.049-1.111), and 1.009 (95%CI: 1.005-1.014), respectively, after adjsuting for gender, age, FBG, and TG.
CONCLUSION
BFR, VFA, and RMR estimated by BIA method can be well applied in the risk prediction of MAFLD, with VFA being the best indicator.
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