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Background It is known that measuring the triglyceride glucose (TyG) index and TyG-related parameters [triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist circumference (TyG-WC), and triglyceride glucose-waist to height ratio (TyG-WHtR)] can predict diabetes; this study aimed to compare the predictive value of the baseline TyG index and TyG-related parameters for the onset of diabetes at different future periods. Methods We conducted a longitudinal cohort study involving 15,464 Japanese people who had undergone health physical examinations. The subject’s TyG index and TyG-related parameters were measured at the first physical examination, and diabetes was defined according to the American Diabetes Association criteria. Multivariate Cox regression models and time-dependent receiver operating characteristic (ROC) curves were constructed to examine and compare the risk assessment/predictive value of the TyG index and TyG-related parameters for the onset of diabetes in different future periods. Results The mean follow-up period of the current study cohort was 6.13 years, with a maximum of 13 years, and the incidence density of diabetes was 39.88/10,000 person-years. In multivariate Cox regression models with standardized hazard ratios (HRs), we found that both the TyG index and TyG-related parameters were significantly and positively associated with diabetes risk and that the TyG-related parameters were stronger in assessing diabetes risk than the TyG index, with TyG-WC being the best parameter (HR per SD increase: 1.70, 95% CI 1.46, 1.97). In addition, TyG-WC also showed the highest predictive accuracy in time-dependent ROC analysis for diabetes occurring in the short-term (2–6 years), while TyG-WHtR had the highest predictive accuracy and the most stable predictive threshold for predicting the onset of diabetes in the medium- to long-term (6–12 years). Conclusions These results suggest that the TyG index combined with BMI, WC, and WHtR can further improve its ability to assess/predict the risk of diabetes in different future periods, where TyG-WC was not only the best parameter for assessing diabetes risk but also the best risk marker for predicting future diabetes in the short-term, while TyG-WHtR may be more suitable for predicting future diabetes in the medium- to long-term.

Non-alcoholic fatty liver disease (NAFLD) constitutes a substantial proportion of cases among the non-obese population, yet it is frequently overlooked. Studies investigating the association between triglyceride-glucose (TyG) - related parameters (TyG-BMI, TyG-WC, TyG-WHtR) and NAFLD in non-obese individuals is limited. Thus, this study aims to investigate the association between TyG-related parameters and NAFLD in non-obese individuals to improve early detection and intervention strategies for NAFLD in this population. A cross-sectional analysis was conducted using data from the NAFLD database, including 11,987 participants who underwent health examinations between 2004 and 2015. Logistic regression models were employed to evaluate the relationship between TyG-related parameters and NAFLD risk, incorporating cubic spline functions and smooth curve fitting to identify potential nonlinear relationships. ROC curve analysis was conducted to assess the predictive performance of thee parameters. After controlling for confounding variables, the incidence of NAFLD in non-obese individuals increased with higher TyG-related parameters. Notably, nonlinear relationships between the TyG index and its related parameters regarding NAFLD risk were identified. The areas under the ROC curve for the TyG index and its related parameters were 0.7984, 0.8553, 0.8584, and 0.8353, respectively. Importantly, the predictive ability of the TyG index and its related parameters was stronger in the female population than in that of males. A positive and nonlinear relationship exists between the TyG-related parameters in relation to the risk of NAFLD. The TyG-related parameters exhibit predictive capabilities for NAFLD, with TyG-related parameters demonstrating greater strength than the TyG index itself.

Purpose Although a significant proportion of type 2 diabetes mellitus (T2DM) cases arose from normal-weight individuals, studies on indicators of T2DM in normal-weight people are limited. Accordingly, this study aims to investigate the predictive value of obesity indices and triglyceride glucose-related parameters (TyG-related parameters) in T2DM among normal-weight Chinese elderly. Methods A total of 24,215 normal-weight Chinese elderly (age ≥ 60 years) [body mass index–BMI (18.5–23.9 kg/m 2 )] were included. Obesity indices and triglyceride glucose-related parameters (TyG-related parameters) included waist circumference (WC), waist-to-height ratio (WHtR), visceral adiposity index (VAI), lipid accumulation product (LAP), and TyG-related parameters (TyG, TyG-BMI, TyG-WC, and TyG-WHtR). Multivariate logistic regression analysis was performed to examine the associations between obesity- and TyG-related indices and T2DM. The areas under the curve (AUC) of the receiver-operating characteristic (ROC) curve analyses were used to evaluate and compare the predictive value of the different indices. Results The prevalence of T2DM was 14.2% in normal-weight individuals. Among the indices, TyG was significantly associated with T2DM among men and women, respectively, (adjusted odds ratio–aOR per SD 3.46; 95% CI 3.23–3.71) and (aOR per SD 3.64; 95% CI 3.43–3.86). Compared with other indices, TyG had the highest AUC value for T2DM in men (AUC: 0.818, 95% CI 0.810–0.825) and women (AUC: 0.824, 95% CI 0.814–0.833). Conclusions TyG is an effective marker and outperforms other indices when predicting T2DM in the normal-weight Chinese elderly population. Level of evidence Level V: Opinions of authorities, based on descriptive studies, narrative reviews, clinical experience, or reports of expert committees.

The metabolic syndrome (Mets) is a multiplex risk factor for atherosclerotic cardiovascular diseases. The aims of the study were to assess the association of the Mets with TyG index and TyG-related parameters in an urban Chinese population. The data were collected in 1992 and then again in 2007 from the same group of 590 individuals (363 males and 227 females) without Mets in 1992. The fasting lipid profile and blood glucose were measured. TyG index and related parameters were calculated, and Mets defined according to the harmonized criteria. The area under the curve (AUC) of receiver operating characteristic curves was used to evaluate TyG index and related parameters for their diagnostic ability to identify people with Mets. Odd ratios (OR) for Mets prediction were calculated using stepwise logistic regression analyses. The incidence of Mets was 18.64% over the 15-year follow-up period.During 15 years' follow-up, TyG-waist to height ratio (TyG-WHtR) shows the largest AUC for Mets detection (0.686) followed by TyG-waist circumference (TyG-WC) (0.660), TyG-waist-to-hip ratio (TyG-WHpR) (0.564), and TyG index (0.556) in all participants. Gender analysis revealed that TyG-WHtR and TyG-WC have the largest AUC in both genders. TyG-WHtR significantly predicted Mets in all participants, with an unadjusted odds ratio of 5.63 (95% CI 3.23-9.83 P < 0.001). Associations remained significant after adjustment for smoking, drinking, physical exercise and components of Mets. TyG-WHtR might be a strong and independent predictor for Mets in all participants in an urban Chinese population. TyG-related markers that combine obesity markers with TyG index are superior to other parameters in identifying Mets in both genders.

Background The triglyceride-glucose (TyG) index is an important determinant influencing the incidence of cardiometabolic multimorbidity (CMM). However, it remains unclear whether combining the TyG index with novel obesity indices (CVAI/BRI/ABSI/WWI) can improve the risk stratification of CMM. This study aimed to systematically compare the incremental risk assessment and predictive value of the TyG index, TyG-traditional obesity indices (TyG-WC/TyG-WHtR/TyG-BMI), and TyG-novel obesity indices (TyG-CVAI/TyG-BRI/TyG-ABSI/TyG-WWI) for CMM. Methods Trajectory changes and cumulative exposure of TyG-related parameters were quantified using repeated measurements from the CHARLS cohort ( n  = 3,885). The study endpoint CMM was defined as a comorbid condition encompassing two or more cardiometabolic diseases, namely diabetes, stroke and heart diseases. A multi-model analytical strategy was employed to evaluate the associations between TyG-related parameters and CMM, as well as the contribution of their components. The net reclassification index and integrated discrimination improvement were employed to evaluate the improvement in predictive performance of these indices. Results Over a median follow-up period of 8 years, we identified a linear positive association between TyG-related parameters and CMM, with the cumulative effects of glucose and obesity emerging as the key drivers. Compared with the baseline TyG index, the incremental risk assessment value for CMM improved by 10%-17% (baseline) and 12%-20% (cumulative exposure) for TyG-traditional obesity indices, while the improvement for TyG-novel obesity indices ranged from − 1% to 16% and 5%-19%, respectively. In summary, all TyG-traditional obesity indices demonstrated strong associations with CMM, whereas among the TyG-novel obesity indices, only TyG-CVAI showed a similarly strong association. Furthermore, all TyG-related parameters showed significantly increased hazard ratios in their highest-exposure or poor-control status versus the reference (lowest exposure or good control): TyG-index (1.69/2.05), TyG-WC (2.24/2.28), TyG-WHtR (1.92/2.05), TyG-BMI (1.85/2.27), TyG-CVAI (1.89/2.07), TyG-BRI (1.94/2.08), TyG-ABSI (1.70/1.85), and TyG-WWI (1.97/1.95). Predictive analyses showed that, except for TyG index, TyG-ABSI and TyG-WWI, all other TyG-related parameters provided a certain degree of net improvement compared with the baseline risk model. Conclusion All eight TyG-related parameters can predict the incidence of CMM. Given their relative simplicity, the TyG-traditional obesity indices demonstrate superior incremental risk assessment and predictive value for CMM compared to the TyG-novel obesity indices and the TyG index, positioning them as promising and more practical tools for clinical practice. Graphical Abstract

Background Conicity index, body-shape index, lipid accumulation product (LAP), waist circumference (WC), triglyceride, triglyceride-glucose (TyG) index, hepatic steatosis index (HSI), waist-to-height ratio (WHtR), TyG index-related parameters (TyG-WHtR, TyG-BMI, TyG-WC), body mass index (BMI), visceral adiposity index, triglyceride to high-density lipoprotein cholesterol ratio and body roundness index have been reported as reliable markers of non-alcoholic fatty liver disease (NAFLD). However, there is debate about which of the above obesity and lipid-related indices has the best predictive performance for NAFLD risk. Methods This study included 6870 female and 7411 male subjects, and 15 obesity and lipid-related indices were measured and calculated. NAFLD was diagnosed by abdominal ultrasound. The area under the curve (AUC) of 15 obesity and lipid-related indices were calculated by receiver operating characteristic (ROC) analysis. Results Among the 15 obesity and lipid-related indices, the TyG index-related parameters had the strongest association with NAFLD. ROC analysis showed that except for ABSI, the other 14 parameters had high predictive value in identifying NAFLD, especially in female and young subjects. Most notably, TyG index-related parameters performed better than other parameters in predicting NAFLD in most populations. In the female population, the AUC of TyG-WC for predicting NAFLD was 0.9045, TyG-BMI was 0.9084, and TyG-WHtR was 0.9071. In the male population, the AUC of TyG-WC was 0.8356, TyG-BMI was 0.8428, and TyG-WHtR was 0.8372. In addition, BMI showed good NAFLD prediction performance in most subgroups (AUC>0.8). Conclusions Our data suggest that TyG index-related parameters, LAP, HSI, BMI, and WC appear to be good predictors of NAFLD. Of these parameters, TyG index-related parameters showed the best predictive potential.

This study aimed to investigate the correlation and predictive value of TyG and related parameters with metabolic dysfunction-associated fatty liver disease (MAFLD) MAFLD. This study retrospectively included individuals who underwent health examinations and abdominal ultrasound from July 2021 to June 2024 at the Affiliated Hospital of Southwest Medical University, Sichuan Province, China. A total of 71,299 subjects’ clinical and laboratory data were extracted, the correlation between TyG and related parameters and MAFLD was analyzed via univariate and multivariate logistic regression methods, and the nonlinear relationship between the TyG index and the risk of MAFLD was explored via restricted cubic spline (RCS) analysis. The predictive value of TyG and related parameters for MAFLD was assessed using the receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC). TyG and related parameters were positively correlated with MAFLD, and the results remained unchanged after adjustment for the corresponding parameters. RCS analysis revealed a significant dose‒response relationship between TyG and related parameters and MAFLD. ROC curve analysis revealed AUC values of 0.83 (0.82–0.83), 0.92 (0.91–0.92), 0.90 (0.90–0.91), and 0.87 (0.87–0.88) for TyG, TyG-BMI, TyG-WC, and TyG-WHR, respectively. Subgroup analyses revealed that the TyG index and related parameters had greater predictive value in the female, younger, and BMI < 23.7 populations.

Background The triglyceride-glucose (TyG) index and related parameters, as well as the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), have been developed as insulin resistance markers to identify individuals at risk for non-alcoholic fatty liver disease (NAFLD). However, its use for predicting NAFLD in patients with type 2 diabetes mellitus (T2DM) remains unclear. In this study, we aimed to observe the performance of insulin resistance indices in diagnosing NAFLD combined with T2DM and to compare their diagnostic values in clinical practice. Patients and methods Overall, 268 patients with T2DM from the Endocrinology Department of Jiangsu Provincial Hospital of Traditional Chinese Medicine were enrolled in this study and divided into two groups: an NAFLD group (T2DM with NAFLD) and a T2DM group (T2DM without NAFLD). General information and blood indicators of the participants were collected, and insulin resistance indices were calculated based on these data. Receiver operating characteristic (ROC) analysis was conducted to calculate the area under the curve (AUC) for insulin resistance-related indices, aiming to assess their ability to discriminate between T2DM patients with and without NAFLD. Results ROC analysis revealed that among the five insulin resistance-related indices, four parameters (TyG, TyG-body mass index [BMI], TyG-waist circumference [WC], and TyG- (waist–hip ratio [WHR]) exhibited high predictive performance for identifying NAFLD, except for HOMA-IR (AUCs:0.710,0.738,0.737 and 0.730, respectivly). TyG-BMI demonstrated superior predictive value, especially in males. For males, the AUC for TyG-BMI was 0.764 (95% confidence interval [CI] 0.691–0.827). The sensitivity and specificity for male NAFLD were 90.32% and 47.89%, respectively. Moreover, in the Generalized linear regression models, there were positive associations of TyG, TyG-BMI, TyG-WC, TyG-WHR, and HOMA-IR with controlled attenuation parameter (CAP), with β values of 21.30, 0.745, 0.247, and 2.549 (all P  < 0.001), respectively. Conclusion TyG-BMI is a promising predictor of NAFLD combined with T2DM, particularly in lean male patients.

Background Visceral adiposity indicators and the product of triglyceride and fasting plasma glucose (TyG) index-related parameters are effective surrogate markers for insulin resistance (IR) and are predictors of metabolic syndrome and diabetes mellitus. However, their genetic determinants have not been previously reported. Pleiotropic associations of LIPC variants have been observed in lipid profiles and atherosclerotic cardiovascular diseases. We aimed to investigate LIPC polymorphisms as the genetic determinants of adiposity status, visceral adiposity indicators and TyG index-related parameters. Methods A total of 592 participants from Taiwan were genotyped for three LIPC single nucleotide polymorphisms (SNPs). Results The LIPC SNPs rs2043085 and rs1532085 were significantly associated with body mass index (BMI), waist circumference (WC), lipid accumulation product, visceral adiposity index, and TyG index-related parameters [including the TyG index, TyG with adiposity status (TyG-BMI), and TyG-WC index], whereas the rs1800588 SNP was only significantly associated with the TyG index. The associations became nonsignificant after further adjustment for serum TG levels. No significant association was observed between any the studied LIPC SNPs and IR status. Conclusion Our data revealed a pleiotropic association between the LIPC variants and visceral adiposity indicators and TyG index-related parameters, which are mediated by serum TG levels.