OBJECTIVE:This study aimed to investigate the association between novel inflammatory markers (NIMs) and non-alcoholic fatty liver disease (NAFLD). METHODS:A total of 6306 subjects were enrolled in this cross-sectional study. NIMs, including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), C-reactive protein to albumin ratio (CAR), lymphocyte to monocyte ratio (LMR), systemic immune-inflammation index (SII) and prognostic nutritional index (PNI), were calculated. The prevalence of NAFLD and its association with NIMs were assessed by multivariable logistic regression analysis. Subgroup analysis were performed based on age, sex and BMI. RESULTS:The prevalence of NAFLD was 52.5% in the study population. Compared with non-NAFLD subjects, NAFLD patients were older and more frequent in females. The prevalence of NAFLD progressively increased among the higher quartile groups of CAR, LMR, SII and PNI ( P -trend < 0.05), whereas it progressively decreased among the higher quartile group of NLR and PLR ( P -trend < 0.05). According to multivariable logistic regression analysis, the highest quartile (Q4) had a significantly higher risk of NAFLD compared with Q1 in LMR [odds ratio (OR): 1.43; 95% confidence interval (CI): 1.17-1.75; P -trend < 0.001] and PNI (OR: 1.92; 95% CI: 1.57-2.35; P -trend < 0.001). The subgroup analysis showed a stronger association of PNI with NAFLD. CONCLUSION:The study highlights the association between NIMs and NAFLD, with LMR and PNI identified as potential non-invasive markers of inflammation in NAFLD. Specifically, PNI exhibited the strongest association and may serve as a valuable marker for assessing inflammation in NAFLD.

Background:Limited research has been conducted to quantitatively assess the impact of systemic inflammation in metabolic dysfunction-associated fatty liver disease (MAFLD) and sub-clinical carotid atherosclerosis (SCAS). The systemic immune-inflammation index (SII), which integrates inflammatory cells, has emerged as a reliable measure of local immune response and systemic inflammation Therefore, this study aims to assess the mediating role of SII in the association between MAFLD and SCAS in type 2 diabetes mellitus (T2DM). Method:This study prospectively recruited 830 participants with T2DM from two centers. Unenhanced abdominal CT scans were conducted to evaluate MAFLD, while B-mode carotid ultrasonography was performed to assess SCAS. Weighted binomial logistic regression analysis and restricted cubic splines (RCS) analyses were employed to analyze the association between the SII and the risk of MAFLD and SCAS. Mediation analysis was further carried out to explore the potential mediating effect of the SII on the association between MAFLD and SCAS. Results:The prevalence of both MAFLD and SCAS significantly increased as the SII quartiles increased (0.05). MAFLD emerged as an independent factor for SCAS risk across three adjusted models, exhibiting odds ratios of 2.15 (95%CI: 1.31-3.53, < 0.001). Additionally, increased SII quartiles and Ln (SII) displayed positive associations with the risk of MAFLD and SCAS ( < 0.05). Furthermore, a significant dose-response relationship was observed ( for trend <0.001). The RCS analyses revealed a linear correlation of Ln (SII) with SCAS and MAFLD risk ( for nonlinearity0.05). Importantly, SII and ln (SII) acted as the mediators in the association between MAFLD and SCAS following adjustments for shared risk factors, demonstrating a proportion-mediated effect of 7.8% and 10.9%. Conclusion:SII was independently correlated with MAFLD and SCAS risk, while also acting as a mediator in the relationship between MAFLD and SCAS.

BACKGROUND:Non-alcoholic fatty liver disease (NAFLD) is a growing health crisis in the general population of the United States (U.S.), but the relationship between systemic immune-inflammation (SII) index and NAFLD is not known. METHODS:We collected data from the National Health and Nutrition Examination Survey 2017-2018. Next, propensity score matching (PSM), collinearity analysis, restricted cubic spline (RCS) plot, logistic regression, quantile regression analysis, subgroup analysis, mediation analysis, and population attributable fraction were used to explore the association of the SII with risk of NAFLD. RESULTS:A total of 665 participants including the 532 Non-NAFLD and 133 NAFLD were enrolled for further analysis after PSM analysis. The RCS results indicated that there was a linear relationship between the SII and controlled attenuation parameter (p for nonlinear = 0.468), the relationship also existed after adjustment for covariates (p for nonlinear = 0.769). The logistic regression results indicated that a high SII level was an independent risk factor for NAFLD (OR = 3.505, 95% CI: 1.092-11.249, P < 0.05). The quantile regression indicated that at higher quantiles (0.90, and 0.95) the SII was significantly associated with NAFLD (p < 0.05). Mediation analysis indicated that alanine aminotransferase (ALT), triglycerides, and blood urea nitrogen (BUN) were partially contribute to the relationship between SII and NAFLD. The population attributable fractions indicated that 23.19% (95% CI: 8.22%, 38.17%) of NAFLD cases could be attributed to SII corresponding to 133 NAFLD cases. CONCLUSION:There was a positive linear relationship between the SII and the risk of NAFLD. The ALT, triglycerides, and BUN had a partial mediating effect on the relationship between the SII and NAFLD.

Objective:This study explored the potential association between the Prognostic Nutritional Index (PNI) and the incidence of non-alcoholic fatty liver disease (NAFLD) and advanced liver fibrosis (AF) in the adult population of the United States. Methods:Information on 6409 participants ≥18 years old was downloaded from the U.S. National Health and Nutrition Examination Survey (NHANES) from 2017 to 2020. Multivariate analysis was combined with demographic factors to assess the relationships between PNI, NAFLD, and AF. A restricted cubic spline (RCS) was used to characterise the nonlinear association between the PNI and NAFLD and AF. Results:Patients without NAFLD had substantially lower mean values for parameters such as age, lymphocyte count, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), total cholesterol, triglycerides, HbA1c, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) than patients with NAFLD. Interestingly, non-NAFLD patients showed a pronounced increase in serum albumin levels compared to their NAFLD counterparts. In the subset without AF, there were discernibly lower measures of NLR, age, AST, ALT, γ-glutamyl transferase, triglycerides, neutrophil count, and body mass index (BMI) than in patients with AF. It was evident that those without AF had markedly elevated mean albumin and PNI levels in comparison to AF-affected individuals. In the comprehensive multivariable framework, a direct correlation was observed between PNI and NAFLD (adjusted odds ratio[aOR] = 1.07, 95% confidence interval [CI]: 1.05-1.09; p < 0.001), whereas PNI and AF were inversely correlated (aOR = 0.92; 95% CI: 0.88-0.96; p < 0.001). Within the RCS model, a swift ascendancy was noted in the relationship between the PNI and NAFLD, peaking at approximately 52. Conversely, a non-linear inverse association was observed between PNI and AF. Conclusion:Our analytical results indicate that elevated PNI levels are positively associated with an increased risk of NAFLD, but inversely related to the risk of AF. For robust validation of these observations, further research is required.

Background:Systemic immune-inflammatory biomarkers including systemic immune inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) have been demonstrated to be associated with the risk and severity of various liver diseases. However, studies on their role and clinical significance in metabolic diseases, especially in nonalcoholic fatty liver disease (NAFLD), are limited and results are inconsistent. Methods:10821 adults aged 20 years or older were enrolled in this cross-sectional study, sourced from six cycles of the National Health and Nutrition Examination Survey (NHANES). Survey-weighted logistic regression was employed to investigate the correlation between systemic immune-inflammatory biomarkers (SII, NLR, PLR, and LMR) and NAFLD risk. Restricted cubic spline regression models and segmented regression models were used to describe nonlinear relationships and threshold effects. Subgroup and sensitivity analyses were also conducted. Results:After adjusting for all confounding variables, there was a significant positive association observed between ln-transformed SII (OR= 1.46, 95% CI: 1.27-1.69, 0.001), NLR (OR= 1.25, 95% CI: 1.05-1.49, =0.015), LMR (OR= 1.39, 95% CI: 1.14-1.69, = 0.002) with NAFLD. A nonlinear dose-response relationship with an inverted "U"-shaped threshold of 4.64 was observed between ln(PLR) and NAFLD risk. When ln(PLR) was below 4.64, each unit increase in ln(PLR) was associated with a 0.55-fold increase in the risk of NAFLD (OR= 1.55, 95% CI: 1.05-2.31, 0.05). Conversely, when ln(PLR) exceeded 4.64, each unit increase in ln(PLR) was associated with a 0.40-fold decrease in the risk of NAFLD (OR= 0.60, 95% CI. 0.44-0.81, 0.05). Conclusion:ln-transformed SII, NLR, and LMR were linearly associated with NAFLD risk. ln(PLR) showed an inverted "U"-shaped nonlinear dose-response relationship with the risk of NAFLD.

OBJECTIVE:Metabolic-associated fatty liver disease (MAFLD) is of concern in employed adults, while the crucial indicators in predicting MAFLD are understudied in this population. We aimed to investigate and compare the prediction performance of a set of indicators for MAFLD in employed adults. METHODS:A cross-sectional study recruiting 7968 employed adults was conducted in southwest China. MAFLD was assessed by abdominal ultrasonography and physical examination. Comprehensive indicators of demographics, anthropometric, lifestyle, psychological, and biochemical indicators were collected by questionnaire or physical examination. All indicators were evaluated for importance in predicting MAFLD by random forest. A prognostic model based on multivariate regression model was constructed to obtain a prognostic index. All indicators and prognostic index were compared to evaluate their prediction performance in predicting MAFLD by the receiver operating characteristic (ROC) curve, calibration plot, and Decision curve analysis (DCA). RESULTS:Triglyceride Glucose-Body Mass Index (TyG-BMI), BMI, TyG, triglyceride (TG)/high-density lipoprotein-cholesterol (HDL-C), and TG ranked the top five important indicators, and TyG-BMI performed the most accurate prediction of MAFLD according to the ROC curve, calibration plot and DCA. The area under the ROC curves (AUCs) of the five indicators were all over 0.7, with TyG-BMI (cut-off value: 218.284, sensitivity: 81.7%, specificity: 78.3%) suggesting the most sensitive and specific indicator. All five indicators showed higher prediction performance and net benefit than the prognostic model. CONCLUSION:This epidemiological study firstly compared a set of indicators to evaluate their prediction performance in predicting MAFLD risk among employed adults. Intervention targeting powerful predictors can be helpful to reduce the MAFLD risk among employed adults.

Objective:This study aims to investigate the predictive value of non-traditional blood lipid indices for metabolism dysfunction-associated fatty liver disease (MAFLD) in non-overweight/obese patients with type 2 diabetes mellitus (T2DM). Methods:A retrospective observational study was conducted, including non-overweight/obese patients with T2DM who visited the Fourth Hospital of Hebei Medical University between August 2018 and August 2022. The low-density lipoprotein cholesterol (LDL-C)/high-density lipoprotein cholesterol (HDL-C) ratio, the triacylglycerol-glucose index (TyG) multiplied by body mass index (BMI), and TyG/HDL-C ratio were calculated. Results:The study involved 190 participants, of whom 34 were diagnosed with MAFLD (24 males and 10 females), while 156 did not have MAFLD (64 males and 92 females). Multivariable analysis revealed that aspartate transaminase (AST) (OR=1.216, 95% CI: 1.059-1.374, P=0.006), blood uric acid (BUA) (OR=1.017, 95% CI: 1.002-1.032, P=0.022), TyG*BMI (OR=1.231, 95% CI: 1.051-1.442, P=0.010), and TyG/HDL-C (OR=3.162, 95% CI: 1.228-8.141, P=0.017) were independently associated with MAFLD. The TyG*BMI index exhibited an area under the ROC curve (AUC) of 0.812, with 91.2% sensitivity and 69.2% specificity for MAFLD. The TyG/HDL-C index had an AUC of 0.929, with 85.3% sensitivity and 88.5% specificity for MAFLD. Conclusion:The results indicate that TyG*BMI and TyG/HDL-C are independently associated with MAFLD in non-overweight/obese patients with T2DM.

OBJECTIVES:This study aimed to evaluate the performance of the triglyceride glucose (TyG) index and its related markers in predicting metabolic-associated fatty liver disease (MAFLD) in healthy Chinese participants. DESIGN:This was a cross-sectional study. SETTING:The study was conducted at Health Management Department of the Affiliated Hospital of Xuzhou Medical University. PARTICIPANTS:A total of 20 922 asymptomatic Chinese participants (56% men) were enrolled. OUTCOME MEASURES:Hepatic ultrasonography was performed to diagnose MAFLD based on the latest diagnostic criteria. The TyG, TyG-body mass (TyG-BMI) and TyG-waist circumference indices were calculated and analysed. RESULTS:Compared with the lowest quartile of the TyG-BMI, the adjusted ORs and 95% CIs for MAFLD were 20.76 (14.54 to 29.65), 92.33 (64.61 to 131.95) and 380.87 (263.25 to 551.05) in the second, third and fourth quartiles, respectively. According to the subgroup analysis, the TyG-BMI in the female and the lean groups (BMI<23 kg/m) showed the strongest predictive value, with optimal cut-off values for MAFLD of 162.05 and 156.31, respectively. The areas under the receiver operating characteristic curves in female and lean groups were 0.933 (95% CI 0.927 to 0.938) and 0.928 (95% CI 0.914 to 0.943), respectively, with 90.7% sensitivity and 81.2% specificity in female participants with MAFLD and 87.2% sensitivity and 87.1% specificity in lean participants with MAFLD. The TyG-BMI index demonstrated superior predictive ability for MAFLD compared with other markers. CONCLUSIONS:The TyG-BMI is an effective, simple and promising tool for predicting MAFLD, especially in lean and female participants.

BACKGROUND:The absence of distinct symptoms in the majority of individuals with metabolic dysfunction-associated fatty liver disease (MAFLD) poses challenges in identifying those at high risk, so we need simple, efficient and cost-effective noninvasive scores to aid healthcare professionals in patient identification. While most noninvasive scores were developed for the diagnosis of nonalcoholic fatty liver disease (NAFLD), consequently, the objective of this study was to systematically assess the diagnostic ability of 12 noninvasive scores (METS-IR/TyG/TyG-WC/TyG-BMI/TyG-WtHR/VAI/HSI/FLI/ZJU/FSI/K-NAFLD) for MAFLD. METHODS:The study recruited eligible participants from two sources: the National Health and Nutrition Examination Survey (NHANES) 2017-2020.3 cycle and the database of the West China Hospital Health Management Center. The performance of the model was assessed using various metrics, including area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), decision curve analysis (DCA), and subgroup analysis. RESULTS:A total of 7398 participants from the NHANES cohort and 4880 patients from the Western China cohort were included. TyG-WC had the best predictive power for MAFLD risk in the NHANES cohort (AUC 0.863, 95% CI 0.855-0.871), while TyG-BMI had the best predictive ability in the Western China cohort (AUC 0.903, 95% CI 0.895-0.911), outperforming other models, and in terms of IDI, NRI, DCA, and subgroup analysis combined, TyG-WC remained superior in the NAHANES cohort and TyG-BMI in the Western China cohort. CONCLUSIONS:TyG-BMI demonstrated satisfactory diagnostic efficacy in identifying individuals at a heightened risk of MAFLD in Western China. Conversely, TyG-WC exhibited the best diagnostic performance for MAFLD risk recognition in the United States population. These findings suggest the necessity of selecting the most suitable predictive models based on regional and ethnic variations.

OBJECTIVE:Our study aimed to explore the diagnostic value of triglyceride-glucose (TyG) and its related parameters in metabolism-associated fatty liver disease (MAFLD). DESIGN:A cross-sectional study of residents who attended medical checkups at the First Hospital of Nanping City, Fujian Medical University, between 2015 and 2017. SETTING:One participation centre. PARTICIPANTS:2605 subjects met the inclusion-exclusion criteria and were grouped according to whether they had MAFLD. RESULTS:The TyG index and its associated parameters are positively associated with the risk of developing MAFLD (p<0.001). Restriction cube spline analysis showed a significant dose-response relationship between the TyG index and MAFLD. The risk of developing MAFLD increases significantly with a higher TyG index. After adjusting for confounders, this relationship remains (OR: 4.89, 95% CI 3.98 to 6.00). The areas under the receiver operating characteristic curves of the TyG index for MAFLD detection were 0.793 (0.774 to 0.812). The areas under the curve (AUC) of TyG-related parameters were improved, among which TyG-waist circumference (TyG-WC) showed the largest AUC for MAFLD detection (0.873, 95% CI 0.860 to 0.887). In addition, the best cut-off value of the TyG-WC was 716.743, with a sensitivity and specificity of 88.7% and 71.4%, respectively. CONCLUSION:The TyG index effectively identifies MAFLD, and the TyG-related parameters improved the identification and diagnosis of MAFLD, suggesting that TyG-related parameters, especially TyG-WC, may be a useful marker for diagnosing MAFLD.

Introduction:Metabolic dysfunction-associated fatty liver disease (MAFLD) is newly proposed nomenclature, and its diagnosis involves an algorithm that can be complicated and impractical for clinicians in real-world clinical settings. Thus, we investigated the association between MAFLD and modified triglyceride-glucose index (TyG) indices to find a more concise, feasible method for predicting MAFLD in everyday clinical care. Methods:Data were obtained from people who voluntarily underwent health check-ups at the Health Promotion Centre of Gangnam Severance Hospital, Yonsei University College of Medicine, from January 2017 to October 2020. Four indices were analyzed: TyG-body to mass index (BMI), TyG-waist circumference (WC), TyG, and the fatty liver index (FLI). The odds ratios for MAFLD according to each index were calculated using multiple logistic regression analyses, and the receiver operating characteristics curve (ROC) and area under the ROC were obtained to find the predictive powers of each index. Results:The final number of study participants was 22,391, 8,246 with MAFLD and 14,145 without MAFLD. The odds ratios (95% confidence intervals) from TyG-WC and TyG-BMI after adjusting for confounding variables were 12.484 (9.962-15.644) and 12.494 (9.790-15.946), respectively, for quartile 2, 54.332 (43.131-68.442) and 51.580 (40.495-65.699) for quartile 3, and 165.804 (130.243-211.076) and 128.592 (100.601-164.371) for quartile 4. The area under the ROC curve values for TyG-WC and TyG-BMI were 0.862 (0.857-0.867) and 0.867 (0.862-0.872), respectively. Conclusion:The modified TyG indices are highly reliable markers for predicting MAFLD that clinicians can easily and practically apply in everyday, real-world, clinical care settings.

Metabolic dysfunction-associated fatty liver disease (MAFLD) has been related to a series of harmful health consequences. The triglyceride-glucose index (TyG index) appears to be associated with MAFLD. However, no consistent conclusions about the TyG index and incident MAFLD have been reached. PubMed, MEDLINE, Web of Science, EMBASE and the Cochrane Library were searched. Sensitivities, specificities and the area under the receiver operating characteristic (AUC) with a random-effects model were used to assess the diagnostic performance of the TyG index in NAFLD/MAFLD participants. Potential threshold effects and publication bias were evaluated by Spearman’s correlation and Deeks’ asymmetry test, respectively. A total of 20 studies with 165725 MAFLD participants were included. The summary receiver operator characteristic (SROC) curve showed that the sensitivity, specificity and AUC were 0.73 (0.69−0.76), 0.67 (0.65, 0.70) and 0.75 (0.71−0.79), respectively. Threshold effects (r = 0.490, p < 0.05) were confirmed to exist. Subgroup analyses and meta-regression showed that some factors including country, number of samples, age and disease situation were the sources of heterogeneity (p < 0.05). Our meta-analysis suggests that the TyG index can diagnose and predict MAFLD patients with good accuracy. The number of studies remains limited, and prospective studies are needed.

PURPOSE:To explore the association between γ-glutamyl transpeptidase to high-density lipoprotein ratio (GGT/HDL), triglyceride glucose-body mass index (TYG-BMI), and metabolic associated fatty liver disease (MAFLD) in a Chinese population with type 2 diabetes (T2DM) by cross-sectional analysis. To investigate the role of GGT/HDL played in MAFLD by TYG-BMI. PATIENTS AND METHODS:A total of 1434 adult patients hospitalized with T2DM at Hebei General Hospital (Shijiazhuang, China) were included in the study. Patients' demographic and clinical data were collected. Spearman correlation was used to test for an association between GGT/HDL or TYG-BMI and related risk factors of MAFLD among T2DM patients. Multiple logistic regression analyses were performed to investigate the association between GGT/HDL or TYG-BMI and MAFLD. Mediation analysis was used to explore whether TYG-BMI mediated the association between GGT/HDL and MAFLD. RESULTS:A total of 1434 T2DM patients were enrolled, the MAFLD group showed a higher level of GGT/HDL compared to the non-MAFLD group. There was a progressive increase in the prevalence of MAFLD with increasing tertiles of GGT/HDL. After adjusting for confounding factors, multivariate logistic regression analysis revealed that high levels of GGT/HDL were independent risk factors for MAFLD in T2DM patients. BMI further grouped the patients: ≤ 23kg/m2,>23kg/m2. GGT/HDL was found to be an independent risk factor for MAFLD but only in T2DM patients with a BMI greater than 23 kg/m2. Mediation analysis indicated that GGT/HDL had a significant direct effect on MAFLD. CONCLUSION:GGT/HDL was positively associated with MAFLD incidence in T2DM patients with a BMI greater than 23 Kg/m2, and TYG-BMI partly mediated the association.

Importance:Homeostatic model assessment for insulin resistance (HOMA-IR) and triglyceride glucose (TyG) index-related parameters [TyG index, triglyceride glucose-waist circumference (TyG-WC), triglyceride glucose-waist-to-height ratio (TyG-WHtR), and triglyceride glucose-body mass index (TyG-BMI)] are gradually considered as convenient and alternative indicators for insulin resistance in various metabolic diseases, but the specific diagnostic capacity and the comparison of the parameters in non-alcoholic fatty liver disease (NAFLD), metabolic-associated fatty liver disease (MAFLD), and liver fibrosis remain uncertain. Objective:To comprehensively assess and compare the diagnostic accuracy of the above parameters in NAFLD, MAFLD, and liver fibrosis and identify the appropriate indicators. Methods:A total of 1,727 adults were enrolled from the 2017-2018 National Health and Nutrition Examination Surveys. Logistic regressions were used to identify the parameters significantly associated with NAFLD, MAFLD, and liver fibrosis; receiver operating characteristic (ROC) curves were used to evaluate and compare their diagnostic capacity. Subgroup analyses were conducted to validate the concordance, and the optimal cutoff values were determined according to the Youden's indexes. Results:Significant differences were observed between quartile-stratified HOMA-IR and TyG index-related parameters across the NAFLD, MAFLD, and liver fibrosis ( < 0.05). All variables were significantly predictive of different disease states ( < 0.05). The top three AUC values are TyG-WC, TyG-WHtR, and TyG-BMI with AUCs of 0.815, 0.809, and 0.804 in NAFLD. The optimal cutoff values were 822.34, 4.94, and 237.77, respectively. Similar values and the same trend of the above three indexes could be observed in MAFLD and liver fibrosis. Subgroup analyses showed consistent results with the primary research, despite some heterogeneity. Conclusions:TyG-WC, TyG-WHtR, and TyG-BMI can be used for early screening of NAFLD and MAFLD. These three parameters and HOMA-IR were more suitable for assessing metabolic risks and monitoring disease progression in patients with NAFLD.

Introduction:Metabolic dysfunction-associated fatty liver disease (MAFLD), formerly known as non-alcoholic fatty liver disease (NAFLD), has become the most common chronic liver disease worldwide. We aimed to explore the gender-related association between nine indexes (BMI/WC/VAI/LAP/WHtR/TyG/TyG-BMI/TyG-WC/TyG-WHtR) and MAFLD/NAFLD and examine their diagnostic utility for these conditions. Methods:Eligible participants were screened from the 2017-2018 cycle data of National Health and Nutrition Examination Survey (NHANES). Logistic regression and receiver operating characteristic (ROC) curve were used to assess the predictive performance of 9 indexes for MAFLD/NAFLD. Results:Among the 809 eligible individuals, 478 had MAFLD and 499 had NAFLD. After adjusting for gender, age, ethnicity, FIPR and education level, positive associations with the risk of MAFLD/NAFLD were found for all the nine indexes. For female, TyG-WHtR presented the best performance in identifying MAFLD/NAFLD, with AUC of 0.845 (95% CI = 0.806-0.879) and 0.831 (95% CI = 0.791-0.867) respectively. For male, TyG-WC presented the best performance in identifying MAFLD/NAFLD, with AUC of 0.900 (95% CI = 0.867-0.927) and 0.855 (95% CI = 0.817-0.888) respectively. Conclusion:BMI/WC/VAI/LAP/WHtR/TyG/TyG-BMI/TyG-WC/TyG-WHtR are important indexes to identify the risk of MAFLD and NAFLD.