Background The relationship between nonalcoholic fatty liver disease (NAFLD) and obesity-related indices has been analyzed separately thus far, and evidence comparing these indices together is still lacking, especially in China. This study aimed to comprehensively evaluate the predictive performance of anthropometric and metabolic indices to identify NAFLD in Chinese adults. Methods This study recruited a total of 1748 participants who were 18 years or older in southeastern China. The systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG), total cholesterol (TC), triglycerides (TGs), low-density lipoprotein (LDL), waist circumference (WC), a body shape index (ABSI), atherogenic index of plasma (AIP), abdominal volume index (AVI), body adiposity index (BAI), body mass index (BMI), body roundness index (BRI), conicity index (CI), triglyceride glucose (TyG), waist hip ratio (WHR), and waist height ratio (WHtR) were measured. The association between these indices and NAFLD was analyzed via logistic analyses with odds ratios (ORs). Receiver operating characteristic (ROC) curves and areas under the curve (AUCs) were used to compare the predictive performance of these indices to identify NAFLD. Results BMI had the greatest total AUC (AUC = 0.841) in the ROC curve analysis. However, BRI and BMI both had the best diagnostic ability in males (AUC = 0.812), and BRI had the best diagnostic ability in females (AUC = 0.849). Furthermore, AVI had the greatest AUC for patients who were ~ 20 (AUC = 0.892) and ~ 40 years old (AUC = 0.831), while TyG showed a higher predictive ability than AVI in those who were ~ 60 years old (AUC = 0.766). Conclusion This study identified sex- and age-specific indices for predicting NAFLD in Chinese subjects. Compared with indices for all age groups, sex- and age-specific indices can provide more accurate assistance for clinical diagnosis and treatment.

Background: The association between anthropometric and metabolic indices and fatty liver (FL) remain not fully elucidated. We aimed to determine the role of these anthropometric and metabolic indices on FL prediction and regulation via cross-sectional study, thus providing clues for further research in FL field. Methods: A total of 658 participants aged over 18 years were included in this study. Anthropometric and metabolic indices (including WC, WHR, BMI, BFM, VFA, TG/HDL, AST/ALT, SBP, DBP and FBG) were measured. Difference analyses, logistic and predictive analyses were used to evaluate the association and discrimination ability between these indices and FL. Results: Compared with non-FL, anthropometric and metabolic indices in FL and mild FL people showed a significant increase after adjustment. In the multivariate ranked logistic regression analysis, WC, TG/HDL, AST/ALT and FBG have a strong association with FL (β = 0.03, 0.19, 0.41, -1.89 and 0.28, P<0.05). And AST/ALT showed the lowest predicted power with an AUC of 0.22 among all indices. WC showed to be the best predictors with an AUC of 0.86 in participants.Conclusions: This is a comprehensive profile for FL related indices. These can enhance our understanding of the mechanisms for hepatic on inflammation and fat and is also important for the prevention and treatment of FL.

Background: This study aimed to comprehensively evaluate the predictive performance anthropometric and metabolic indices in identifying fatty liver (FL) diseases in Chinese adults. Indices including Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), Total Cholesterol (TC), Triglyceride (TG), Low Density Lipoprotein (LDL), Fasting Blood Glucose (FBG), Alanine aminotransferase (ALT and AST), Waist Circumference (WC), Waist–hip Ratio (WHR), Waist-to-Height Ratio (WHtR), Body Mass Index (BMI), Abdominal Volume Index (AVI), Atherogenic Index of Plasma (AIP), Triglyceride Glucose (TyG), and ALT/AST were selected. Methods: A total of 1748 participants aged over 18 years were included in this study. Univariate analyses were performed to determine the associations between these indices and FL with odds ratio (ORs). The predictive performance of these indices to identify FL was compared using receiver operating characteristic (ROC) curves and areas under curves (AUCs). Results: WHtR had the greatest AUC in males (AUC = 0.81) and females (AUC = 0.85). Furthermore, WC and AVI had the greatest AUC in 20-40 years (AUC = 0.96), while TyG had the greatest AUC in 40- years (AUC = 0.80) of females. And WHtR had the second diagnostic ability in both two decades of age (20-40 and 40- years) of females. Conclusions: WHtR might be the best for predicting FL in males and females, while WC and AVI might be best for identifying FL for males aged 20-40 years, while TyG for those aged over 40 years.