BACKGROUND: The prevalence of obesity-associated insulin resistance (IR) is increasing along with the increase in obesity rates. In this study, we compared the predictive utility of four alternative indexes of IR [triglyceride glucose index (TyG index), metabolic score for insulin resistance (METS-IR), the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and homeostatic model assessment of insulin resistance (HOMA-IR)] for all-cause mortality and cardiovascular mortality in the general population based on key variables screened by the Boruta algorithm. The aim was to find the best replacement index of IR.
METHODS: In this study, 14,653 participants were screened from the National Health and Nutrition Examination Survey (2001-2018). And TyG index, METS-IR, TG/HDL-C and HOMA-IR were calculated separately for each participant according to the given formula. The predictive values of IR replacement indexes for all-cause mortality and cardiovascular mortality in the general population were assessed.
RESULTS: Over a median follow-up period of 116 months, a total of 2085 (10.23%) all-cause deaths and 549 (2.61%) cardiovascular disease (CVD) related deaths were recorded. Multivariate Cox regression and restricted cubic splines analysis showed that among the four indexes, only METS-IR was significantly associated with both all-cause and CVD mortality, and both showed non-linear associations with an approximate \"U-shape\". Specifically, baseline METS-IR lower than the inflection point (41.33) was negatively associated with mortality [hazard ratio (HR) 0.972, 95% CI 0.950-0.997 for all-cause mortality]. In contrast, baseline METS-IR higher than the inflection point (41.33) was positively associated with mortality (HR 1.019, 95% CI 1.011-1.026 for all-cause mortality and HR 1.028, 95% CI 1.014-1.043 for CVD mortality). We further stratified the METS-IR and showed that significant associations between METS-IR levels and all-cause and cardiovascular mortality were predominantly present in the nonelderly population aged < 65 years.
CONCLUSIONS: In conjunction with the results of the Boruta algorithm, METS-IR demonstrated a more significant association with all-cause and cardiovascular mortality in the U.S. population compared to the other three alternative IR indexes (TyG index, TG/HDL-C and HOMA-IR), particularly evident in individuals under 65 years old.

BACKGROUND: The birth of large-for-gestational-age (LGA) infants is associated with many short-term adverse pregnancy outcomes. It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus (GDM) is significantly higher than that born to healthy pregnant women. However, traditional methods for the diagnosis of LGA have limitations. Therefore, this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants.
OBJECTIVE: To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM, and provide strategies for the effective prevention and timely intervention of LGA.
METHODS: The multivariable prediction model was developed by carrying out the following steps. First, the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses, for which the P value was < 0.10. Subsequently, Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations, and the optimal combination factors were selected by choosing lambda 1se as the criterion. The final predictors were determined by multiple backward stepwise logistic regression analysis, in which only the independent variables were associated with LGA risk, with a P value < 0.05. Finally, a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve, calibration curve and decision curve analyses.
RESULTS: After using a multistep screening method, we establish a predictive model. Several risk factors for delivering an LGA infant were identified (P < 0.01), including weight gain during pregnancy, parity, triglyceride-glucose index, free tetraiodothyronine level, abdominal circumference, alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks. The nomogram\'s prediction ability was supported by the area under the curve (0.703, 0.709, and 0.699 for the training cohort, validation cohort, and test cohort, respectively). The calibration curves of the three cohorts displayed good agreement. The decision curve showed that the use of the 10%-60% threshold for identifying pregnant women with GDM who are at risk of delivering an LGA infant would result in a positive net benefit.
CONCLUSIONS: Our nomogram incorporated easily accessible risk factors, facilitating individualized prediction of pregnant women with GDM who are likely to deliver an LGA infant.

The triglyceride-glucose (TyG) index is a simple and inexpensive new marker of insulin resistance that is being increasingly used for the clinical prediction of metabolic syndrome (MetS). Nevertheless, there are only a few comparative studies on its predictive capacity for MetS versus those using the traditional homeostasis model assessment (HOMA). We conducted a cross-sectional study using a database from the National Health and Nutrition Examination Survey (1999 March to 2020 pre-pandemic period). Using statistical methods, we compared the predictive abilities of the TyG index and HOMA (including HOMA of insulin resistance [HOMA-IR] and HOMA of beta-cell function [HOMA-β]) for MetS. A total of 34,195 participants were enrolled and divided into the MetS group (23.1%) or no MetS group (76.9%) according to the International Diabetes Federation (IDF) diagnostic criteria. After applying weighted data, the baseline characteristics of the population were described. Following the exclusion of medication influences, the final count was 31,304 participants. Receiver operating characteristic curve analysis revealed that while distinguishing between MetS and no MetS, the TyG index had an area under the curve (AUC) of 0.827 (sensitivity = 71.9%, specificity = 80.5%), and the cutoff was 8.75, slightly outperforming HOMA-IR (AUC = 0.784) and HOMA-β (AUC = 0.614) with a significance of P < 0.01. The prevalence of MetS in the total population calculated using the TyG index cutoff value was 30.9%, which was higher than that reported in the IDF diagnostic criteria. Weighted data analysis using univariate and multivariate logistic regression displayed an independent association between elevated TyG and HOMA-IR with the risk of MetS. Subgroup analysis further revealed differences in the predictive ability of the TyG index among adult populations across various genders and ethnicities, whereas such differences were not observed for children and adolescents. The TyG index is slightly better than HOMA in predicting MetS and may identify more patients with MetS; thus, its applications in a clinical setting can be appropriately increased.

BACKGROUND: The Triglyceride-glucose (TyG) index, a surrogate marker of insulin resistance, has been implicated in the risk of ischemic stroke. However, the interplay between TyG levels, lifestyle factors, and their collective impact on stroke risk in non-diabetic populations remains inadequately explored. This study aims to evaluate the association of ischemic stroke with the joint development of the TyG index and lifestyle in the non-diabetic population.
METHODS: In this prospective cohort study, data was collected across three consecutive biennial surveys of the Kailuan Study from 2006 to 2011. The dual-trajectory model was used to determine the temporal development of TyG levels and lifestyle scores. Statistical analysis involved Cox regression models to evaluate the association between TyG-lifestyle trajectories and ischemic stroke risk, adjusting for potential confounders.
RESULTS: A total of 44,403 participants were included, with five distinct TyG levels and lifestyle scores trajectory subtypes identified. In the multivariable-adjusted analyses, significant differences in ischemic stroke risk among the trajectory subtypes. Group 5, characterized by the highest TyG levels and moderate lifestyle scores, exhibited the greatest ischemic stroke risk (HR = 1.81, 95% CI: 1.51-2.18), while group 4, with moderate TyG levels and higher lifestyle scores, demonstrated the lowest risk (HR = 1.19, 95% CI: 1.04-1.37), compared with group 3. Participants with elevated TyG levels were at an increased risk of ischemic stroke in cases of pronounced insulin resistance, even with a healthy lifestyle.
CONCLUSIONS: This study reveals the significant associations between the identified TyG and lifestyle trajectories and the stratification of ischemic stroke risk among non-diabetics. The TyG index is a valuable indicator for assessing insulin resistance. However, the potential benefits of lifestyle changes for those with significantly high TyG levels need to be clarified by more research to develop more effective stroke prevention strategies.

Background: A correlation between plasma lipids and timing of pubertal development has been hypothesized, though lipid influence remains unclear in central precocious puberty (CPP). Aim: To assess any possible alterations in the lipid profile and triglyceride glucose index (TyG) in children diagnosed with CPP. Patients and Methods: Retrospective single-center study conducted on children (aged 6.3 ± 2.1 years) evaluated for the suspicion of CPP. Results: Based on the results of the gonadotropin releasing hormone (GnRH) test, considering 5 IU/L as cut-off of the luteinizing hormone peak, CPP was confirmed in 43 patients (57.3%). Sixteen (37.2%) had a pathologic body mass index (BMI), with 9 (20.9%) being overweight and 7 (16.27%) obese. High total cholesterol was found in 3 patients with CPP (6.97%), high triglycerides were found in 11 patients with CPP (25.58%), high LDL cholesterol was found in 5 patients with CPP (11.62%), low HDL cholesterol was found in 12/43 patients with CPP (27.9%), a pathologic TyG was found in 13/43 patients with CPP (30.23%). No significant association was observed in the lipid profile for patients with or without CPP, except for HDL cholesterol, which was lower in the CPP group (47.1 ± 10.9; p = 0.033). However, the association between serum HDL cholesterol and CPP was not confirmed at the multivariate logistic regression analysis adjusted for patients\' sex and age (p = 0.1; OR: 1.035; 95% CI: 0.993-1.078). Conclusion: The overall lipid profile of our pediatric patients diagnosed with CPP did not differ from patients having idiopathic precocious thelarche or normal variants of puberty development.

The article by Zhao et al. titled \"Associations of Triglyceride-Glucose (TyG) Index with Chest Pain Incidence and Mortality among the U.S. Population\" provides valuable insights into the positive correlation between the TyG index and chest pain incidence, as well as a nonlinear relationship with mortality. However, the use of the COX proportional hazards model in their analysis presents several limitations. The assumption of constant hazard ratios over time may not hold, potentially leading to biased estimates. The model\'s struggle with time-dependent covariates and the possibility of residual confounding are notable concerns. Additionally, the study\'s subgroup analyses might suffer from reduced statistical power, and potential interactions with other metabolic markers were not explored. Considering these limitations, future research should adopt alternative approaches, such as time-varying covariate models, to provide a more comprehensive understanding of the relationship between the TyG index and cardiovascular outcomes.

OBJECTIVE: To explore the effects of short-term particulate matter (PM) exposure and the melatonin receptor 1B (MTNR1B) gene on triglyceride-glucose (TyG) index utilizing data from Fang-shan Family-based Ischemic Stroke Study in China (FISSIC).
METHODS: Probands and their relatives from 9 rural areas in Fangshan District, Beijing, were included in the study. PM data were obtained from fixed monitoring stations of the National Air Pollution Monitoring System. TyG index was calculated by fasting triglyceride and glucose concentrations. The associations of short-term PM exposure and rs10830963 polymorphism of the MTNR1B gene with the TyG index were assessed using mixed linear models, in which covariates such as age, sex, and lifestyles were adjusted for. Gene-environment inter-action analysis was furtherly performed using the maximum likelihood methods to explore the potential effect modifier role of rs10830963 polymorphism in the association of PM with TyG index.
RESULTS: A total of 4 395 participants from 2 084 families were included in the study, and the mean age of the study participants was (58.98±8.68) years, with 53. 90% females. The results of association analyses showed that for every 10 μg/m3 increase in PM2.5 concentration, TyG index increased by 0.017 (95%CI: 0.007-0.027), while for per 10 μg/m3 increment in PM10, TyG index increased by 0.010 (95%CI: 0.003-0.017). And the associations all had lagged effects. In addition, there was a positive association between the rs10830963 polymorphism and the TyG index. For per increase in risk allele G, TyG index was elevated by 0.040 (95%CI: 0.004-0.076). The TyG index was 0.079 (95%CI: 0.005-0.152) higher in carriers of the GG genotype compared with carriers of the CC genotype. The interaction of rs10830963 polymorphism with PM exposure had not been found to be statistically significant in the present study.
CONCLUSIONS: Short-term exposure to PM2.5 and PM10 were associated with higher TyG index. The G allele of rs10830963 polymorphism in the MTNR1B gene was associated with the elevated TyG index.

UNASSIGNED: The association of the triglyceride-glucose (TyG) index, a promising novel biomarker for insulin resistance, with the risk of endometriosis has not been investigated to date. This nationwide study aimed to explore the association between the TyG index and the endometriosis risk.
UNASSIGNED: Data were obtained from the National Health and Nutrition Examination Survey (1999-2006). Female participants who provided complete data on the TyG index and endometriosis were enrolled in the analysis. Multivariate logistic regression analyses were utilized to assess the association of the TyG index with endometriosis, adjusted by multiple potential confounders. Meanwhile, in-depth subgroup analyses were conducted.
UNASSIGNED: A total of 1,590 eligible participants were included, among whom 135 (8.5%) women were diagnosed with endometriosis. The fully adjusted multivariate logistic model showed TyG index was significantly associated with the endometriosis risk (odds ratio [OR]Q4 versus Q1 2.04, 95% confidence interval [CI]: 1.15-3.62; P for trend=0.013). In subgroup analyses, the significantly positive association between TyG index and the risk of endometriosis was also found in parous women (ORQ4 versus Q1 2.18, 95% CI: 1.20-3.96), women without diabetes (OR Q4 versus Q1 2.12, 95% CI: 1.19-3.79), women who smoke currently (OR Q4 versus Q1 3.93, 95% CI: 1.33-11.58), women who drink currently (OR Q4 versus Q1 2.54, 95% CI: 1.27-5.07), and in women who use oral contraceptives (OR Q4 versus Q1 1.91, 95% CI: 1.04-3.51). Additionally, significantly increasing trends in the odds of endometriosis across the quartiles of the TyG index were observed in the above-mentioned subgroups (all P for trend<0.05).
UNASSIGNED: This population-based study found that a higher TyG index, representing an increased level of insulin resistance, was associated with a higher risk of endometriosis among the US population. Our findings suggested TyG index might be a promising tool for the risk assessment of endometriosis. Prospective studies are warranted to further verify these findings.

UNASSIGNED: The triglyceride-glucose (TyG) index, a simple surrogate marker of insulin resistance, is significantly associated with chronic kidney disease (CKD). However, there is limited research on the longitudinal trajectory of TyG index over time and its relationship with CKD.
UNASSIGNED: To analyse the characteristics of the longitudinal trajectory of the TyG index over time and its association with the development of CKD in a health check-up population.
UNASSIGNED: Participants who underwent at least three annual health check-ups at the Health Management Center of Sichuan Provincial People\'s Hospital from 2015 to 2022 were included in this retrospective cohort study. The TyG index was calculated as ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. The latent class mixed model (LCMM) was used to identify the TyG index trajectory of the study population. A Cox proportional hazard model was used to estimate the CKD incidence risk in different quartile groups and the association of changes in the TyG index trajectory with the development of CKD.
UNASSIGNED: A total of 4,921 participants were included in this study, and they were divided into four groups according to the quartiles of the baseline TyG index: Q1 (5.43-6.66), Q2 (6.67-7.04), Q3 (7.05-7.43), and Q4 (7.43-9.97). There was no difference in the risk of CKD occurrence among the TyG groups. Three different TyG index trajectories were identified in this study: a high-level group, middle-level stable group and low-level stable group, respectively. The incidence rate of CKD in the high-level TyG index trajectory group was 2.399 times greater than that in the low-level stable trajectory group (HR=2.399, 95% CI 1.167-4.935).
UNASSIGNED: Individuals with long-term exposure to high TyG index levels had a significantly greater risk of CKD. Routine monitoring of the TyG index and its longitudinal trend will aid in the risk stratification of CKD in the general population and will be helpful for CKD prevention and targeted management.

[This corrects the article DOI: 10.3389/fendo.2024.1376166.].