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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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>Five thousand three hundred forty subjects were included in this research, with 30% randomly selected for the validation set (<jats:italic>n\u2009<\/jats:italic>=\u20091602) and 70% for the Training set (<jats:italic>n<\/jats:italic>\u2009=\u20093738). 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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>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 cm<jats:sup>2<\/jats:sup> for women and 178.35 cm<jats:sup>2<\/jats:sup> 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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>VFA was an independent predictive factor for MAFLD, and the ideal cutoff of VFA to predict MAFLD was 115.55 cm<jats:sup>2<\/jats:sup> in women and 178.35 cm<jats:sup>2<\/jats:sup> in men.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12944-022-01763-2","type":"journal-article","created":{"date-parts":[[2022,12,31]],"date-time":"2022-12-31T02:03:48Z","timestamp":1672452228000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Gender differences in the ideal cutoffs of visceral fat area for predicting MAFLD in China"],"prefix":"10.1186","volume":"21","author":[{"given":"Pingping","family":"Yu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huachao","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoya","family":"Qi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruixue","family":"Bai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shouqin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianping","family":"Gong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Mei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,12,31]]},"reference":[{"key":"1763_CR1","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.jhep.2020.03.039","volume":"73","author":"M Eslam","year":"2020","unstructured":"Eslam M, Newsome PN, Sarin SK, et al. 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