Gender differences in the ideal cutoffs of visceral fat area for predicting MAFLD in China

Author:

Yu Pingping,Yang Huachao,Qi Xiaoya,Bai Ruixue,Zhang Shouqin,Gong Jianping,Mei Ying,Hu Peng

Abstract

Abstract Background Since the discovery of metabolic-associated fatty liver disease (MAFLD) in 2020, no report on the connection between the visceral fat area (VFA) and MAFLD has been published in China, and the ideal cutoffs of VFA for predicting MAFLD has not been determined so far. Thus, the purpose of this research was to clarify the relationship between VFA and MAFLD and the ideal cutoffs of VFA to predict MAFLD in the Chinese population. Methods Five thousand three hundred forty subjects were included in this research, with 30% randomly selected for the validation set (n = 1602) and 70% for the Training set (n = 3738). The association between VFA and MAFLD was determined by multiple logistic regression. ROC curves were used to evaluate the prediction effect of VFA on MAFLD. Results Multiple logistic regression analysis revealed that the VFA ORs (95% CIs) were 1.25 (1.20, 1.29) for women and 1.15 (1.12, 1.17) for men. Meanwhile, the VFA quartile OR (95% CI) were 3.07 (1.64, 5.75), 7.22 (3.97, 13.14), 18.91 (10.30, 34.71) for women and 3.07 (1.64, 5.75), 7.22 (3.97, 13.14),18.91 (10.30, 34.71) for men in the Q2, Q3, and Q4 groups compared with Q1. The ROC curve showed the VFA, WC, WHR, and WHtR to predict MAFLD, the AUC value of VFA was the highest and the prediction effect was the best. The ideal cutoffs of VFA to predict MAFLD was 115.55 cm2 for women and 178.35 cm2 for men, and the AUC was 0.788 and 0.795, respectively. Finally, the AUC was 0.773 for women and 0.800 for men in the validation set. Conclusion VFA was an independent predictive factor for MAFLD, and the ideal cutoff of VFA to predict MAFLD was 115.55 cm2 in women and 178.35 cm2 in men.

Funder

Chongqing Science and Technology Commission Joint Medical Project

Chongqing Talents Project

Publisher

Springer Science and Business Media LLC

Subject

Biochemistry (medical),Clinical Biochemistry,Endocrinology,Endocrinology, Diabetes and Metabolism

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