Triglyceride to High-Density Lipoprotein Cholesterol (TG/HDL-C) Ratio, a Simple but Effective Indicator in Predicting Type 2 Diabetes Mellitus in Older Adults

Data-driven cluster analysis of lipids, inflammation, and aging in relation to new-onset type 2 diabetes mellitus

PURPOSE

Early detection and intervention are vital for managing type 2 diabetes mellitus (T2DM) effectively. However, it's still unclear which risk factors for T2DM onset are most significant. This study aimed to use cluster analysis to categorize individuals based on six known risk factors, helping to identify high-risk groups requiring early intervention to prevent T2DM onset.

METHODS

This study comprised 7402 Korean Genome and Epidemiology Study individuals aged 40 to 69 years. The hybrid hierarchical k-means clustering algorithm was employed on six variables normalized by Z-score-age, triglycerides, total cholesterol, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol and C-reactive protein. Multivariable Cox proportional hazard regression analyses were conducted to assess T2DM incidence.

RESULTS

Four distinct clusters with significantly different characteristics and varying risks of new-onset T2DM were identified. Cluster 4 (insulin resistance) had the highest T2DM incidence, followed by Cluster 3 (inflammation and aging). Clusters 3 and 4 exhibited significantly higher T2DM incidence rates compared to Clusters 1 (healthy metabolism) and 2 (young age), even after adjusting for covariates. However, no significant difference was found between Clusters 3 and 4 after covariate adjustment.

CONCLUSION

Clusters 3 and 4 showed notably higher T2DM incidence rates, emphasizing the distinct risks associated with insulin resistance and inflammation-aging clusters.

Quantitative Lipoprotein Subclass Analysis in Pig Plasma by 1H NMR Spectroscopy and Stability Assessment

This study explores, for the first time, the accurate prediction of lipoprotein subclasses in pig plasma by a partial least-squares regression (PLSR) model based on the optimization of the 1H NMR detection method. The 1H NMR-based detection method of plasma metabolites first was optimized and evaluated. The coefficients of variation for intraday and interday detection were less than 5%, and there were no obvious metabolic differences among repeated tests of plasma samples. The variability of plasma metabolite detection based on 1H NMR revealed the consistent and stable performance of NMR methods, and the prediction models for a total of 116 subclasses in four lipoprotein classes including plasma very-low-density lipoprotein, low-density lipoprotein, intermediate-density lipoprotein, and high-density lipoprotein were established combining 1H NMR spectra and PLSR models using the data from the ultracentrifugation method. The cross-validation results showed that the PLSR prediction models for 107 lipoproteins' main and subfractions performed excellently (R2 > 0.5), which met the method requirements. The PLSR models for the remaining nine lipoprotein major components and subcomponents performed well (0.2 < R2 < 0.5), which basically met the method requirements. According to the PLSR models based on 1H NMR, the concentrations of lipoprotein subclasses were predicted, including APO A1 (277.84-731.4 μg/mL), APO B (11.97-431.5 μg/mL), PL (142.36-1100.76 ng/mL), TG (70.21-915.35 μmol/L), CH (1313.56-6761.79 μmol/L), FC (6.37-93.06 μmol/L), and CE (1319.93-6854.85 μmol/L). Therefore, the 1H NMR-based method for the detection of lipoprotein subclasses in pig plasma was successfully established and could provide the methodological basis for the research on molecular mechanism, function, and application of lipoprotein subclasses.

Mediating effects of insulin resistance on lipid metabolism with elevated paraben exposure in the general Taiwan population

Introduction

Parabens are commonly used to prevent bacteria from growing in cosmetics and foodstuffs. Parabens have been reported to influence hormone regulation, potentially leading to metabolic anomalies, including insulin resistance and obesity. However, there is a paucity of knowledge regarding the relationship between urinary paraben levels and lipid metabolism in the general Taiwanese population. Therefore, the objective of this study was to determine whether the mediating role of insulin resistance exists between paraben exposure and lipid metabolism.

Methods

We selected the data of 264 adult participants from a representative survey in five major Taiwan area in 2013. UPLC tandem mass spectrometry was used to examine four urine parabens: methyl- (MeP), ethyl- (EtP), propyl- (PrP) and butyl- (BuP). Blood samples were analyzed for concentrations of glucose and lipid metabolic indices using the DxI 800 immunoassay analyzer and immunoradiometric assay kit. The relationship between urinary paraben levels and metabolism indices were evaluated through a multiple linear regression analysis. Finally, a mediation analysis was employed to understand the underlying mechanism by which paraben exposure influences lipid metabolism through insulin resistance.

Results

The significant positive association between MeP exposure and Castelli risk index I (CRI-I; β = 0.05, p = 0.049) was found, and also exhibited the similar associations between EtP exposure and low-density lipoprotein cholesterol (β = 0.10, p = 0.001), total cholesterol (β = 0.06, p = 0.003), and non-HDL cholesterol (NHC; β = 0.08, p = 0.005). EtP exhibited a significant positive association with triglyceride BMI (TyG-BMI; β = 0.02, p = 0.040). Additionally, TyG-BMI was positively associated with CRI-I (β = 0.98, p < 0.001), CRI-II (β = 1.03, p < 0.001) and NHC (β = 0.63, p < 0.001). Moreover, insulin resistance served as mediators for the effects of EtP exposure on lipid metabolism indices.

Discussion

The results indicate that changes in insulin resistance mediated the relationship between urinary paraben and lipid metabolism. Large-scale epidemiological and animal studies are warranted to identify biological mechanisms underlying validate these relationships.

The first-trimester triglyceride glucose-body mass index is a valuable predictor for adverse pregnancy outcomes

BACKGROUND

Although insulin resistance has been associated with unfavorable pregnancy outcomes, the ability of non-insulin-based insulin resistance indicators to predict adverse pregnancy outcomes has yet to be thoroughly understood. The study aims to investigate the association and predictability of triglyceride glucose-body mass index (TyG-BMI), a biomarker of non-insulin-based insulin resistance, with the risks of adverse pregnancy outcomes.

METHOD

The retrospective study included 1,136 subjects. Group-based trajectory modeling (GBTM) was employed to identify the TyG-BMI index trajectory. Logistic regression, restricted cubic spline (RCS) regression, and subgroup analysis were used to assess the association between the TyG-BMI index trajectory and the first-trimester TyG-BMI index with the risks of adverse pregnancy outcomes. Receiver-operating characteristic (ROC) curve analysis and the DeLong test were utilized to evaluate the prediction ability of the first-trimester TyG-BMI index for adverse pregnancy outcomes.

RESULTS

GBTM revealed three distinct trajectories of the TyG-BMI index. Using the "low-stable" trajectory as a reference, the "high-stable" trajectory was independently associated with an increased risk of gestational diabetes mellitus (GDM) (aOR = 2.01, 95% CI 1.20-3.37), hypertensive disorders of pregnancy (HDP) (aOR = 6.05, 95% CI 3.00-12.18), and large for gestational age (LGA) (aOR = 2.83, 95% CI 1.28-6.25). The highest quartile of the first-trimester TyG-BMI index was independently linked to elevated GDM (aOR = 3.27, 95% CI 1.92-5.59), HDP (aOR = 9.26, 95% CI 3.19-26.88), and LGA (aOR = 2.26, 95% CI 1.00-5.09)risks. Additionally, the third quartile of the first-trimester TyG-BMI index had 2.21-fold increased odds of GDM (aOR = 2.21, 95% CI 1.27-3.82). The first-trimester TyG-BMI index demonstrated a significant linear association with GDM, HDP, SGA, and LGA risks. Compared to the TyG-BMI index trajectory, the highest quartile of the first-trimester TyG-BMI index exhibited a stronger association with the risks of GDM and HDP (aOR = 3.09 and 7.39, respectively). Furthermore, according to the ROC curve, the first-trimester TyG-BMI index outperformed the TyG index and triglyceride/high-density lipoprotein cholesterol (TG/HDL-c) ratio at predicting HDP (0.726 [0.650-0.801] vs. 0.603 [0.527-0.679] vs. 0.615 [0.537-0.693]), LGA (0.619 [0.540-0.699] vs. 0.534 [0.454-0.613] vs. 0.540 [0.458-0.622]), and GDM (0.664 [0.622-0.705] vs. 0.632 [0.588-0.676] vs. 0.604 [0.560-0.649]). According to the DeLong test, the first-trimester TyG-BMI index was a more valuable predictor for LGA and HDP compared to TyG index and TG/HDL-c ratio.

CONCLUSION

Higher levels of first-trimester TyG-BMI and a "high-stable" trajectory were linked to a greater risk of adverse pregnancy outcomes. Furthermore, as compared to TyG and TG/HDL-c, the first-trimester TyG-BMI index is a valuable predictor for HDP, GDM, and LGA.

Predicting Type 2 diabetes onset age using machine learning: A case study in KSA

The rising prevalence of Type 2 Diabetes (T2D) in Saudi Arabia presents significant healthcare challenges. Estimating the age at onset of T2D can aid early interventions, potentially reducing complications due to late diagnoses. This study, conducted at King Abdulaziz Medical University Hospital, aims to predict the age at onset of T2D using Multiple Linear Regression (MLR), Artificial Neural Networks (ANN), Random Forest (RF), Support Vector Regression (SVR), and Decision Tree Regression (DTR). It also seeks to identify key predictors influencing the age at onset of T2D in Saudi Arabia, which ranks 7th globally in prevalence. Medical records from 1,000 diabetic patients from 2018 to 2022 that contain demographic, lifestyle, and lipid profile data are used to develop the models. The average onset age was 65 years, with the most common onset range between 40 and 90 years. The MLR and RF models provided the best fit, achieving R2 values of 0.90 and 0.89, root mean square errors (RMSE) of 0.07 and 0.01, and mean absolute errors (MAE) of 0.05 and 0.13, respectively, using the logarithmic transformation of the onset age. Key factors influencing the age at onset included triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), ferritin, body mass index (BMI), systolic blood pressure (SBP), white blood cell count (WBC), diet, and vitamin D levels. This study is the first in Saudi Arabia to employ MLR, ANN, RF, SVR, and DTR models to predict T2D onset age, providing valuable tools for healthcare practitioners to monitor and design intervention strategies aimed at reducing the impact of T2D in the region.

Association between triglyceride to HDL cholesterol ratio and a risk of diabetes mellitus: a systematic review and meta-analysis

OBJECTIVE

The aim of this study was to investigate the link between the triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C) and the occurrence of type 2 diabetes mellitus (T2DM).

METHODS

PubMed, Embase, and Scopus databases were searched for cohort and case-control studies that reported on the link between TG/HDL-C and a risk of T2DM, with no restrictions on criteria used for the definition and categorization of low and high TG/HDL-C ratios.

RESULTS

A total of 20 studies were included. There was considerable variability in terms of categorization of low or normal and higher TG/HDL-C ratio among the studies. Patients with high TG/HDL-C ratio had markedly higher risk of developing T2DM compared with patients with low or normal TG/HDL-C. Each unit increase in the ratio correlated with the increased risk of diabetes. Subgroup analysis based on sex showed an increased risk of T2DM in males and females with a high ratio compared with the group with a low/normal ratio.

CONCLUSION

Higher TG/HDL-C ratio correlates with increased risk of T2DM. Despite limitations, the study demonstrates a possible value of using TG/HDL-C ratio as a biomarker for diabetes risk.

Associations between non-insulin-based insulin resistance indices and diabetic nephropathy in patients with diabetes mellitus in US adults: a cross-sectional study of NHANES 1999-2018

Objective

This study investigated the associations between non-insulin-based insulin resistance indices (METS-IR, TyG, TG/HDL, and TyG-BMI) and the risk of diabetic nephropathy (DN) in US adults with diabetes mellitus (DM).

Methods

This study was based on the 1999-2018 National Health and Nutrition Examination Survey (NHANES) database and included 6,891 patients with DM for cross-sectional analysis. Multivariate adjusted models and restricted cubic spline (RCS) models were employed to assess the association between the insulin resistance index and the risk of DN. Subgroup analyses were conducted to explore the impact of different population characteristics.

Results

The results indicated that higher quartiles of METS-IR, TyG, TG/HDL, and TyG-BMI were associated with a significantly increased risk of DN. After adjusting for multiple covariates, including gender, age, and race, the associations between these indices and the risk of DN remained significant, with corresponding odds ratios (ORs) of 1.51 (95% confidence interval [CI]: 1.29-1.76), 2.06 (95% CI: 1.77-2.40), 1.61 (95% CI: 1.38-1.88), and 1.57 (95% CI: 1.35-1.84), with all P-values less than 0.001. RCS analysis indicated a nonlinear relationship between these indices and the risk of DN. The TyG index exhibited a highly consistent association with the risk of DN in all models.

Conclusion

Non-insulin-based insulin resistance indices are significantly associated with the risk of DN. The TyG index is a superior tool for assessing the risk of DN. These indices can assist in identifying patients at risk of DN, thereby enabling the implementation of more effective preventive and therapeutic strategies.

The triglyceride-to-high-density lipoprotein cholesterol ratio is associated with an increased risk of peripartum cardiomyopathy

Background

Peripartum cardiomyopathy (PPCM) is a form of heart failure that severely affects women during the late stages of pregnancy and in the postpartum period. Currently, the diagnosis of PPCM is not fully understood and is likely multifactorial. Abnormal lipid metabolism plays an important role in the onset of cardiovascular diseases, especially in patients with heart failure. Moreover, animal experiments have confirmed a possible association between abnormal lipid metabolism and PPCM onset. However, clinical evidence is currently lacking, and reliable and effective indicators for predicting the onset of PPCM are insufficient. The ratio of triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) is a novel metabolic marker that is associated with the risk of coronary heart disease. However, the relationship between the TG/HDL-C ratio and the risk of PPCM in parturients remains unknown. Therefore, this study aimed to explore the role of the TG/HDL-C ratio in predicting the risk of PPCM.

Methods

This study included 600 parturients hospitalized at Qilu Hospital of Shandong University between January 2010 and August 2023 (150 patients with PPCM and 450 healthy parturients). The TG/HDL-C ratio was calculated as triglyceride levels (mmol/L)/high-density lipoprotein cholesterol levels (mmol/L). The relationship between the TG/HDL-C ratio and PPCM was analyzed using logistic regression analysis and receiver operating characteristic curve analysis.

Results

Significant differences were observed in the TG/HDL-C ratio between patients with PPCM and healthy parturients. The TG/HDL-C ratio was higher in patients with PPCM than in healthy parturients (p < 0.001). Logistic regression analysis revealed that the TG/HDL-C ratio increased the risk of PPCM and had predictive accuracy for the onset of PPCM (odds ratio, 1.249; 95% confidence interval, 1.004-1.553; p = 0.046). Moreover, the TG/HDL-C ratio was positively correlated with the NT-proBNP levels at the onset of PPCM (R 2 = 0.081, p = 0.008).

Conclusions

A higher TG/HDL-C ratio was significantly associated with the risk of PPCM.

Elevated Plasma High Sensitive C-Reactive Protein and Triglyceride/High-Density Lipoprotein Cholesterol Ratio are Risks Factors of Diabetes Progression in Prediabetes Patients After Kidney Transplant: A 3-Year Single-Center Study in Vietnam

Purpose

Determination the rate of developing post-transplant diabetes mellitus (PTDM) in prediabetic patients and the relationship with plasma hs-CRP levels and TG/HDL-C ratio in patients after kidney transplantation from living donors followed for 3 years.

Subjects and Methods

A total of 206 post-transplant patients diagnosed with prediabetes by oral glucose tolerance test (OGTT) were included in the study. At the time of diagnosis of prediabetes, all patients were clinically examined, paraclinical tests were performed, plasma hs-CRP was quantified, and the TG/HDL-C ratio was determined. Patients are individualized and given a reasonable diet and exercise regimen. Patients had their fasting blood glucose measured monthly or had an OGTT every 3 months. Patients meeting the criteria for diagnosis of PTDM according to the American Diabetes Association (ADA)-2018 were collected during 3 years of follow-up.

Results

The study group had an average age of 39.46 ± 10.26 years old, including 74.8% males and 25.2% females. The rate of patients who had a development of PTDM from prediabetes was 29.6% (61/206 patients). BMI, plasma TG, HDL-C, hs-CRP, and TG/HDL-C ratio at the time of prediabetes diagnosis were factors related to the progression of PTDM, in which hs-CRP and TG/HDL-C ratio were good predictors (with AUC = 0.85 and 0.874, respectively; p < 0.001).

Conclusion

After 3 years of follow-up, nearly one-third of prediabetic patients developed PTDM post-living donor kidney transplantation. BMI, plasma TG, HDL-C, hs-CRP, and the TG/HDL-C ratio were linked to DM progression, with hs-CRP and TG/HDL-C being the strongest predictors.

Association of lipid levels at different stages of pregnancy with gestational diabetes mellitus and the incidence of neonatal macrosomia: A retrospective study

OBJECTIVE

To investigate the correlation between lipid levels during gestation and the incidence rate of gestational diabetes mellitus (GDM) and macrosomia.

METHOD

Clinical records of 607 pregnant women with GDM (GDM group) who delivered in the Obstetrics Department of Fujian Maternal and Child Health Hospital from May to December 2018 and of 833 women with uncomplicated pregnancies (control group) were retrospectively analyzed. After delivery, the entire cohort was further grouped based on the weight of the neonates: women who delivered newborns with body mass <4 kg comprised the normal group (n = 1367), and pregnancies that resulted in delivery of neonates with body mass >4 kg were classified as the macrosomia group (n = 73). Fasting serum levels of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and TG/HDL-C ratio were compared between the groups at the early (10-12 weeks), middle (24-28 weeks), and late (28 weeks-delivery) stages of pregnancy, and the correlation between the lipid indices and the rates of GDM and macrosomia were analyzed.

RESULTS

There was a gradual increase in TC, TG, LDL-C, and TG/HDL-C levels with increasing gestational weeks in pregnant women. TG and TG/HDL-C levels were markedly higher, while HDL-C was lower in women with GDM compared with women of the same gestational age with uncomplicated pregnancies (p < 0.05).

CONCLUSION

Lipid metabolism disorders exist in pregnant women with GDM at different gestational stages and are closely related to the higher incidence of macrosomia. TG, TG/HDL-C, and HDL-C in early and late pregnancy are independent risk factors for macrosomia in all trimesters, and TG/HDL-C ratio at different gestational stages has a good predictive value for macrosomia.

Biomarkers of insulin sensitivity/resistance

In recent years, remarkable advancements in elucidating the intricate molecular underpinnings of type 2 diabetes mellitus (T2D) have been achieved. Insulin resistance (IR) has been unequivocally acknowledged as the driving pathogenetic mechanism of T2D, preceding disease onset by several years. Nonetheless, diagnostic tools for ascertaining IR are lacking in current clinical practice, representing a critical unmet need; use of the hyperinsulinemic-euglycemic glucose clamp, widely accepted as the gold standard method for evaluating IR at present, is cumbersome in a clinical setting. Thus, the development of well-validated, reliable, and affordable biomarkers of IR has attracted considerable attention from the research community. The biomarkers under investigation can be divided into two major categories: (1) indices or ratios, comprising parameters obtained from a basic or comprehensive metabolic panel and/or derived from anthropometric measurements, and (2) circulating molecules implicated in pathophysiological processes associated with IR. Furthermore, numerous novel biomarkers, including markers of β-cell dysfunction, radiographic quantification of excess visceral adipose tissue, T2D prediction models, certain microRNAs and metabolomic biomarkers, have also provided promising preliminary results. This narrative review aims to present current evidence pertaining to the most notable and exciting biomarkers of IR that are under rigorous evaluation.

Insulin resistance and sarcopenia: a prognostic longitudinal link to stroke risk in middle-aged and elderly Chinese population

BACKGROUND

Stroke is the leading cause of death in middle-aged and elderly people in China. Insulin resistance (IR) and sarcopenia are both closely associated with metabolic diseases. However, the relationship between these two indicators and stroke has not been fully investigated. The aim of this study was to investigate the relationship between IR and sarcopenia and the risk of new-onset stroke.

METHODS

Using longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018, Cox proportional hazards models were used to determine the association between IR surrogate indicators and sarcopenia status with stroke incidence.

RESULTS

In the present study, during a median 7 years of follow-up, we included 7009 middle-aged and elderly residents, of whom 515 presented with stroke incidence. After adjustment for potential confounders, both baseline IR surrogates and sarcopenia independently predicted stroke risk. In addition, co-morbidities had a higher risk of stroke than other groups. The positive association between TyG-WC and sarcopenia on stroke risk was particularly significant [HR (95% CI): 2.03 (1.52, 2.70)]. In subgroups of different ages and sexes, the combination of IR and sarcopenia is associated with the highest risk of stroke.

CONCLUSIONS

We found that IR and sarcopenia synergistically increase the incidence of stroke in older adults. This finding provides new perspectives for stroke detection and intervention and highlights the importance of early detection and management of IR and sarcopenia in older adults.

A longitudinal study on the impact of the TyG Index and TG/HDL-C ratio on the risk of type 2 diabetes in Chinese patients with prediabetes

OBJECTIVE

To elucidate the impact and predictive value of the Triglyceride Glucose Index (TyG) and the ratio of Triglycerides to High-Density Lipoprotein Cholesterol (TG/HDL-C) in identifying the risk of diabetes progression in Chinese individuals with prediabetes.

METHODS

This longitudinal study enrolled 15,012 prediabetic adults from the Rich Healthcare Group between 2010 and 2016. Diabetes was defined as self-reported diabetes or a fasting glucose level ≥ 7.0 mmol/L. The Cox proportional hazards models was utilized to assess the relationship between the two indices and the risk of developing diabetes. The predictive efficacy of the two markers was gauged by the area under the curve (AUC).

RESULTS

Over a median follow-up period of 2.87 years, 1,730 (11.5%) prediabetic participants developed diabetes. The adjusted hazard ratios for the top quartile of the TyG index and the TG/HDL-C ratio were 2.03 (95% confidence interval [CI]: 1.71-2.40) and 2.59 (95% CI: 2.20-3.05), respectively, compared to the lowest quartile. A significant trend of increasing diabetes risk with higher quartiles of both indices was observed. The AUC for the adjusted prediction model for prediabetes-to-diabetes transition was 0.726 for the TyG index and 0.710 for the TG/HDL-C ratio. The difference in AUCs was statistically significant (P = 0.03).

CONCLUSIONS

The baseline TyG index or TG/HDL-C ratio was significantly associated with an increased risk of diabetes in prediabetic individuals. The TyG index demonstrated superior predictive accuracy, underscoring its importance in preventing diabetes in prediabetic individuals.

Short-term HIIT impacts HDL function differently in lean, obese, and diabetic subjects

Introduction

High density lipoproteins (HDL) exert cardiovascular protection in part through their antioxidant capacity and cholesterol efflux function. Effects of exercise training on HDL function are yet to be well established, while impact on triacylglycerol (TG)-lowering has been often reported. We previously showed that a short-term high-intensity interval training (HIIT) program improves insulin sensitivity but does not inhibit inflammatory pathways in immune cells in insulin-resistant subjects. The purpose of this study is to evaluate HDL function along with changes of lipoproteins after the short-term HIIT program in lean, obese nondiabetic, and obese type 2 diabetic (T2DM) subjects.

Methods

All individuals underwent a supervised 15-day program of alternative HIIT for 40 minutes per day. VO2peak was determined before and after this training program. A pre-training fasting blood sample was collected, and the post-training fasting blood sample collection was performed 36 hours after the last exercise session.

Results

Blood lipid profile and HDL function were analyzed before and after the HIIT program. Along with improved blood lipid profiles in obese and T2DM subjects, the HIIT program affected circulating apolipoprotein amounts differently. The HIIT program increased HDL-cholesterol levels and improved the cholesterol efflux capacity only in lean subjects. Furthermore, the HIIT program improved the antioxidant capacity of HDL in all subjects. Data from multiple logistic regression analysis showed that changes in HDL antioxidant capacity were inversely associated with changes in atherogenic lipids and changes in HDL-TG content.

Discussion

We show that a short-term HIIT program improves aspects of HDL function depending on metabolic contexts, which correlates with improvements in blood lipid profile. Our results demonstrate that TG content in HDL particles may play a negative role in the anti-atherogenic function of HDL.

The Association Between the Triglyceride to High-Density Lipoprotein Cholesterol Ratio and the Incidence of Type 2 Diabetes Mellitus in the Japanese Population

Abstract Aims: To explore whether the triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) was independently associated with the risk of incident type 2 diabetes mellitus (T2DM) in a large Japanese cohort. Methods: A secondary analysis was performed using open-access data from a retrospective cohort study. A total of 12,716 eligible participants who had standard medical examinations at the Murakami Memorial Hospital were included in this study. New-onset T2DM was the main outcome during follow-up. The risk of T2DM based on the TG/HDL-C ratio was evaluated using Cox regression analysis and Kaplan-Meier analysis. Subgroup analysis was performed to understand further the significance of the TG/HDL-C ratio in particular populations. To assess the potential of the TG/HDL-C ratio for predicting T2DM, a receiver operating characteristic (ROC) analysis was performed. Results: One hundred fifty new-onset T2DM cases were observed during a median follow-up of 5.39 years. The incidence of T2DM increased with a rise in the TG/HDL-C ratio based on the Kaplan-Meier curves (P < 0.0001). After controlling for potential confounding variables, the TG/HDL-C ratio was positively related to incidence of T2DM (hazard ratio = 1.08, 95% confidence interval: 1.01-1.15, P = 0.0239). In subgroup analysis, those with a body mass index of ≥18.5 and <24 kg/m2 showed a significantly positive relationship. The area under the ROC curve for the TG/HDL-C ratio as a T2DM predictor was 0.684. The optimal TG/HDL-C ratio cutoff value for T2DM was 1.609, with a sensitivity of 54.7% and a specificity of 73.6%. Conclusion: The authors' results showed a significant relationship between the TG/HDL-C ratio and the incidence of T2DM in the Japanese population.

The prognostic significance of insulin resistance in COVID-19: a review

Objectives

Emerging publications indicate that diabetes predisposes patients with COVID-19 to more severe complications, which is partly attributed to inflammatory condition. In the current review, we reviewed recent published literature to provide evidence on the role of insulin resistance (IR) in diabetes, the association between diabetes and COVID-19 severity and mortality, the impact of COVID-19 infection on incident new-onset diabetes, mechanisms responsible for IR in COVID-19 patients, and the predictive value of different surrogates of IR in COVID-19.

Method

The literature search performs to find out studies that have assessed the association between IR surrogates and morbidity and mortality in patients with COVID-19.

Results

We showed that there is a bulk of evidence in support of the fact that diabetes is a potent risk factor for enhanced morbidity and mortality in COVID-19 patients. COVID-19 patients with diabetes are more prone to remarkable dysglycemia compared to those without diabetes, which is associated with an unfavourable prognosis. Furthermore, SARS-COV2 can make patients predispose to IR and diabetes via activating ISR, affecting RAAS signaling pathway, provoking inflammation, and changing the expression of PPARɣ and SREBP-1. Additionally, higher IR is associated with increased morbidity and mortality in COVID-19 patients and different surrogates of IR can be utilized as a prognostic biomarker for COVID-19 patients.

Conclusion

Different surrogates of IR can be utilized as predictors of COVID-19 complications and death.

Correlation between alternative insulin resistance indexes and diabetic kidney disease: a retrospective study

PURPOSE

This retrospective study aimed to investigate the relationship between alternative insulin resistance (IR) indexes not reliant on insulin and diabetic kidney disease (DKD) incidence in a newly diagnosed cohort of individuals with type 2 diabetes mellitus (T2DM).

METHODS

We conducted a retrospective analysis of baseline characteristics in a cohort of 521 individuals with T2DM, then followed up on the outcome of DKD. To assess the predictive ability of IR indexes, we compared the performance of four non-insulin-based IR indexes and the homeostasis model for insulin resistance (HOMA-IR) using logistic regression and consistency-statistics (C-statistics). Furthermore, we computed the net reclassification index (NRI) and integrated discrimination improvement (IDI) to evaluate the additional effects of the indexes.

RESULTS

The four alternative IR indexes of DKD patients were significantly higher than those of non-DKD. After adjustment for other variables, the highest tertile of all indexes was significantly related to DKD incidence, compared with the lowest tertile. Furthermore, the C-statistics for the triglyceride-glucose index (TyG index) and triglyceride to high-density lipoprotein ratio (TG/HDL) were all 0.652, while triglyceride glucose-body mass index (TyG-BMI) and metabolic score for insulin resistance (METS-IR) were 0.639 and 0.651, respectively. The incorporation of the alternative IR indexes into the baseline model revealed positive additional effects, leading to an improved prediction of the risk for DKD.

CONCLUSIONS

It was discovered that the alternative IR indexes served as independent risk factors of DKD. Among the four alternative indexes, TyG index and TG/HDL had the best prediction performance for DKD, followed by METS-IR.

Antioxidant and Anti-Inflammatory Functions of High-Density Lipoprotein in Type 1 and Type 2 Diabetes

(1) Background: high-density lipoproteins (HDLs) exhibit antioxidant and anti-inflammatory properties that play an important role in preventing the development of atherosclerotic lesions and possibly also diabetes. In turn, both type 1 diabetes (T1D) and type 2 diabetes (T2D) are susceptible to having deleterious effects on these HDL functions. The objectives of the present review are to expound upon the antioxidant and anti-inflammatory functions of HDLs in both diabetes in the setting of atherosclerotic cardiovascular diseases and discuss the contributions of these HDL functions to the onset of diabetes. (2) Methods: this narrative review is based on the literature available from the PubMed database. (3) Results: several antioxidant functions of HDLs, such as paraoxonase-1 activity, are compromised in T2D, thereby facilitating the pro-atherogenic effects of oxidized low-density lipoproteins. In addition, HDLs exhibit diminished ability to inhibit pro-inflammatory pathways in the vessels of individuals with T2D. Although the literature is less extensive, recent evidence suggests defective antiatherogenic properties of HDL particles in T1D. Lastly, substantial evidence indicates that HDLs play a role in the onset of diabetes by modulating glucose metabolism. (4) Conclusions and perspectives: impaired HDL antioxidant and anti-inflammatory functions present intriguing targets for mitigating cardiovascular risk in individuals with diabetes. Further investigations are needed to clarify the influence of glycaemic control and nephropathy on HDL functionality in patients with T1D. Furthermore, exploring the effects on HDL functionality of novel antidiabetic drugs used in the management of T2D may provide intriguing insights for future research.

A decreased level of high-density lipoprotein is a possible risk factor for type 2 diabetes mellitus: A review

Introduction

Type 2 diabetes mellitus (T2DM) is characterized primarily by dyslipidemia and hyperglycemia due to insulin resistance. High-density lipoprotein (HDL) play a significant role in preventing the incidence of dyslipidemia and its complications. HDL has different protective functions, such as reducing oxidation, vascular inflammation, and thrombosis; additionally, its anti-diabetic role is one of the most significant recent discoveries about HDL and some of its constituent lipoproteins.

Methods

This research reviews ongoing studies and preliminary investigations into the assessment of relation between decreased level of HDL and T2DM.

Results

The levels of HDL and its functions contribute to glucose hemostasis and the development of T2DM through four possible mechanisms, including insulin secretion by beta cells, peripheral insulin sensitivity, non-insulin-dependent glucose uptake, and adipose tissue metabolic activity. Additionally, the anti-oxidant properties of HDL protect beta cells from apoptosis caused by oxidative stress and inflammation induced by low-density lipoprotein, which facilitate insulin secretion.

Conclusion

Therefore, HDL and its compositions, especially Apo A-I, play an important role in regulating glucose metabolism, and decreased levels of HDL can be considered a risk factor for DM. Different factors, such as hypoalphalipoproteinemia that manifests as a consequence of genetic factors, such as Apo A-I deficiency, as well as secondary causes arising from lifestyle choices and underlying medical conditions that decrease the level of HDL, could be associated with DM. Moreover, intricate connections between HDL and diabetic complications extend beyond glucose metabolism to encompass complications like cardiovascular disease and kidney disease. Therefore, the exact interactions between HDL level and DM should be evaluated in future studies.

Triglyceride to high-density lipoprotein cholesterol ratio is associated with regression to normoglycemia from prediabetes in adults: a 5-year cohort study in China

OBJECTIVE

The current body of evidence on the association between the ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-c) and the reversal of prediabetes to normoglycemia remains limited. The aim of this study is to investigate the association between TG/HDL-c and the reversion to normoglycemia in patients with prediabetes.

METHODS

This retrospective cohort study included 15,107 individuals with prediabetes from 32 Chinese districts and 11 cities who completed health checks from 2010 to 2016. The Cox proportional-hazards regression model examined baseline TG/HDL-c and reversion to normoglycemia from prediabetes. Cox proportional hazards regression with cubic spline functions and smooth curve fitting determined the non-linear connection between TG/HDL-c and reversion to normoglycemia. We also ran sensitivity and subgroup analysis. By characterizing progression to diabetes as a competing risk for the reversal of prediabetes to normoglycemic event, a multivariate Cox proportional hazards regression model with competing risks was created.

RESULTS

Upon adjusting for covariates, the findings indicate a negative association between TG/HDL-c and the likelihood of returning to normoglycemia (HR = 0.869, 95%CI:0.842-0.897). Additionally, a non-linear relationship between TG/HDL-c and the probability of reversion to normoglycemia was observed, with an inflection point of 1.675. The HR on the left side of the inflection point was 0.748 (95%CI:0.699, 0.801). The robustness of our results was confirmed through competing risks multivariate Cox's regression and a series of sensitivity analyses.

CONCLUSION

The present study reveals a negative and non-linear correlation between TG/HDL-c and the reversion to normoglycemia among Chinese individuals with prediabetes. The findings of this study are anticipated to serve as a valuable resource for clinicians in managing dyslipidemia in prediabetic patients. Interventions aimed at reducing the TG/HDL-c ratio through the reduction of TG or elevation of HDL-c levels may substantially enhance the likelihood of achieving normoglycemia in individuals with prediabetes.

Triglycerides/HDL cholesterol ratio and type 2 diabetes incidence: Panasonic Cohort Study 10

BACKGROUND

Previous studies have investigated the association between the ratio of triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C) and the incidence of diabetes in adults and discovered that a high TG/HDL-C ratio was linked to an elevated risk of new-onset diabetes. However, the comparison of predicting diabetes development among lipid profiles including the TG/HDL-C ratio, and the ratio of TG/HDL-C cut-off value has received limited attention. We examined the relationship between diabetes onset and the TG/HDL-C ratio in addition to the applicable cut-off value for predicting diabetes onset.

METHODS

This study included 120,613 participants from the health examination database at Panasonic Corporation from 2008 to 2017. Cox regression analysis employing multivariable models was used to investigate the association between lipid profiles, particularly the ratio of TG/HDL-C and the development of type 2 diabetes (T2D). The multivariable model was adjusted for age, sex, BMI, systolic blood pressure, plasma glucose levels after fasting, smoking status, and exercise habits. Areas under time-dependent receiver operating characteristic (ROC) curves (AUCs) were employed to assess the prediction performance and cut-off values of each indicator. A fasting plasma glucose level of 126 mg/dL, a self-reported history of diabetes, or usage of antidiabetic medicines were used to identify T2D.

RESULTS

During the course of the study, 6,080 people developed T2D. The median follow-up duration was 6.0 (3-10) years. Multivariable analysis revealed that the ratio of TG/HDL-C (per unit, HR; 1.03 [95% CI 1.02-1.03]) was substantially linked to the risk of incident T2D. AUC and cut-off points for the ratio of TG/HDL-C for T2D development after 10 years were 0.679 and 2.1, respectively. Furthermore, the AUC of the ratio of TG/HDL-C was considerably larger compared to that of LDL-C, HDL-C, and TG alone (all P < 0.001). We discovered an interaction effect between sex, BMI, and lipid profiles in subgroup analysis. Females and participants having a BMI of < 25 kg/m2 showed a higher correlation between lipid profile levels and T2D onset.

CONCLUSIONS

The ratio of TG/HDL-C was found to be a stronger predictor of T2D development within 10 years than LDL-C, HDL-C, or TG, indicating that it may be useful in future medical treatment support.

Triglyceride to high-density lipoprotein cholesterol ratio was negatively associated with relative grip strength in older adults: a cross-sectional study of the NHANES database

Aim

This study aims to explore the association between triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio and relative grip strength in older adults in order to provide some references for the prevention and control of sarcopenia.

Methods

For this cross-sectional study, the demographic and clinical data of 1,404 individuals aged ≥60 years old were extracted from the National Health and Nutrition Examination Survey (NHANES) database in 2011-2014. The definition of relative grip strength was the sum of the largest reading from each hand/body mass index (BMI) ratio. We used weighted univariate linear regression and stepwise regression analysis to screen the covariates. Weighted univariate and multivariate linear regression analyses were used to explore the association between the TG/HDL-C ratio and the relative grip strength. We also explored this relationship in subgroups of gender, diabetes mellitus (DM), cardiovascular disease (CVD), and arthritis. The evaluation index was β with 95% confidence intervals (CIs).

Results

A total of 1,306 older adults were eligible. After adjusting for the covariates including age, gender, race, marital status, physical activity, DM, CVD, arthritis, and chronic kidney disease (CKD), we found that the TG/HDL-C ratio was negatively linked to the relative grip strength (all p < 0.05). Furthermore, the increased TG/HDL-C ratio was also related to the decreased relative grip strength in those who were women, not having DM, and having CVD (all p < 0.05).

Conclusion

With the increase in the TG/HDL-C ratio, the relative grip strength of older adults decreased significantly, indicating that the TG/HDL-C ratio could be closely monitored in the older adult population and may be associated with the prevention and control of sarcopenia.

A U-shaped association between the triglyceride to high-density lipoprotein cholesterol ratio and the risk of incident type 2 diabetes mellitus in Japanese men with normal glycemic levels: a population-based longitudinal cohort study

Background

Several studies have verified that a high baseline TG/HDL-C ratio is a risk factor for incident type 2 diabetes mellitus (T2DM). However, for low baseline TG/HDL-C levels, the findings were inconsistent with ours. In addition, the association between baseline TG/HDL-C ratio and the risk of incident T2DM in Japanese men with normal glycemic levels is unclear. As a result, our study further investigated the relationship between baseline TG/HDL-C and the risk of incident T2DM in Japanese men with normal glycemic levels.

Methods

This was a secondary longitudinal cohort study. We selected 7,684 male participants between 2004 and 2015 from the NAGALA database. A standardized Cox regression model and two piecewise Cox regression models were used to explore the relationship between the baseline high-density lipoprotein cholesterol ratio (TG/HDL-C) and incident T2DM.

Results

During a median follow-up of 2,282 days, 162 men developed incident T2DM. In the adjusted model, the baseline TG/HDL-C ratio was strongly associated with the risk of incident T2DM, and no dose-dependent positive association was observed between the baseline TG/HDL-C ratio and incidence of T2DM throughout the baseline TG/HDL-C quartiles. Two-piecewise linear regression analysis showed a U-shaped association between baseline TG/HDL-C ratio and incidence of incident T2DM. A baseline TG/HDL-C ratio below 1.188 was negatively associated with incident T2DM (H.R. = 0.105, 95% CI = 0.025, 0.451; P = 0.002). In contrast, a baseline TG/HDL-C ratio >1.188 was positively associated with incident T2DM (H.R. = 1.248, 95% CI = 1.113, 1.399; P<0.001). The best TG/HDL-C threshold for predicting incident T2DM was 1.8115 (area under the curve, 0.6837).

Conclusion

A U-shaped relationship between baseline TG/HDL-C ratio and incident T2DM in Japanese men with normal glycemic levels was found.

The Association between the Atherogenic Index of Plasma and Cardiometabolic Risk Factors: A Review

Background: Metabolic syndrome (MetS) is a condition caused by a combination of cardiometabolic risk factors (CMR). MetS leads to type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD), both of which place a burden on not only the patients but also the healthcare system. Diagnostic criteria for MetS vary, and there is no universal tool to detect it. Recently, many studies have found positive associations between the atherogenic index of plasma (AIP) and some CMR factors. Therefore, a comprehensive review was needed to recapitulate these studies and qualitatively estimate the likelihood of AIP being associated with CMR. We aimed to review and summarise observational data on AIP and CMR factors and verify their association. Materials and Methods: A review of observational studies was conducted by searching “atherogenic index of plasma” in PubMed, One Search, and the Cochrane library. A total of 2068 articles were screened, and 32 were included after excluding paediatric, non-human and interventional studies, and those carried out on cohorts with conditions unrelated to MetS or on lipid-lowering medication. The Newcastle-Ottawa scale was used to assess their quality. Results: Most studies that reported high waist circumference (WC), triglycerides (TG), insulin resistance (IR) and low high-density lipoprotein cholesterol (HDL-C) concentration, also reported high AIP. Few studies investigated blood pressure (BP) and some discrepancies existed between their results. Conclusion: AIP may be associated with WC, TG, IR, and HDL-C. It is unclear if AIP is associated with BP. The current study’s results should be used to inform futureward a meta-analysis to be seen quantitatively. It is also recommended that more cohort studies stratified by gender and ethnicity be performed to ascertain if AIP can predict MetS before it manifests.

Association between triglyceride to high-density lipoprotein cholesterol ratio and type 2 diabetes risk in Japanese

Abnormal lipid metabolism is known to increases the risk for metabolic diseases, such as type 2 diabetes mellitus(T2DM). The relationship between baseline ratio of triglyceride to HDL cholesterol (TG/HDL-C) and T2DM in Japanese adults was investigated in this study. Our secondary analysis included 8419 male and 7034 female Japanese subjects who were free of diabetes at baseline. The correlation between baseline TG/HDL-C and T2DM was analyzed by a proportional risk regression model, the nonlinear correlation between baseline TG/HDL-C and T2DM was analyzed by a generalized additive model (GAM), and the threshold effect analysis was performed by a segmented regression model. We conducted subgroup analyses in different populations. During the median 5.39 years follow-up, 373 participants, 286 males and 87 females, developed diabetes mellitus. After full adjustment for confounders, the baseline TG/HDL-C ratio positively correlated with the risk of diabetes (hazard ratio 1.19, 95% confidence interval 1.09-1.3), and smoothed curve fitting and two-stage linear regression analysis revealed a J-shaped relationship between baseline TG/HDL-C and T2DM. The inflection point for baseline TG/HDL-C was 0.35. baseline TG/HDL-C > 0.35 was positively associated with the development of T2DM (hazard ratio 1.2, 95% confidence interval 1.10-1.31). Subgroup analysis showed no significant differences in the effect between TG/HDL-C and T2DM in different populations. A J-shaped relationship was observed between baseline TG/HDL-C and T2DM risk in the Japanese population. When TG/HDL-C was higher than 0.35, there was a positive relationship between baseline TG/HDL-C and the incidence of diabetes mellitus.

Association of four lipid-derived indicators with the risk of developing type 2 diabetes: a Chinese population-based cohort study

BACKGROUND

Studies have reported that lipid-derived indicators are associated with type 2 diabetes (T2D) in various populations; however, it is unclear which lipid-derived indicators could effectively predict T2D risk. Therefore, this study aimed to explore the association between four lipid-derived indicators and T2D risk.

METHODS

This was a post-hoc analysis from a large cohort that included data from 114,700 Chinese individuals aged 20 years and older from 11 cities and 32 sites. The association between four lipid-derived indicators and T2D risk was determined using Kaplan-Meier (KM) survival curves, Cox regression, and restricted cubic spline analyses. This study used receiver operating characteristic (ROC) curves for assessing the ability of four lipid-derived indicators to accurately predict the development of T2D during follow-up.

RESULTS

This study included a total of 114,700 participants, with a mean age of 44.15. These individuals were followed up for 3.1 years, of which 2668 participants developed T2D. ROC curve analysis showed that TyG was the most robust predictor of 3-year [aera under the ROC (AUC) = 0.77, 95% CI: 0.768, 0.772] and 5-year T2D risk (AUC = 0.763, 95% CI: 0.760, 0.765). In addition, sensitivity analysis showed an association between TyG and an increased incidence of T2D.

CONCLUSIONS

The results suggest that TyG was a superior for predicting the risk of developing T2D in the general Chinese population.

Comparison of longitudinal changes in four surrogate insulin resistance indexes for incident T2DM in middle-aged and elderly Chinese

Aims

Previous studies suggested a significant relationship between four surrogate indexes of insulin resistance and subsequent type 2 diabetes mellitus (T2DM). But the association of longitudinal changes (denoted as -D) in CVAI (Chinese visceral adiposity index), LAP (lipid accumulation product), TyG (triglyceride-glucose), and TG/HDL-C (triglyceride/ high-density lipoprotein cholesterol) indexes with the risk of T2DM remained uncertain. We aimed to compare the changes in those four surrogate indexes for predicting T2DM in middle-aged and elderly Chinese.

Methods

We extracted data from the China Health and Retirement Longitudinal Study (CHARLS). Multivariate logistic regression models were used to estimate odds ratio (OR) with 95% confidence interval (CI) of incident T2DM with four surrogate indexes. The restricted cubic spline analysis was used to examine potential non-linear correlation and visualize the dose-response relationship between four indexes and T2DM. The receiver operator characteristic curve was used to compare the performance of the four indexes to predict T2DM.

Results

We enrolled 4,596 participants in total, including 504 (10.97%) with T2DM. Analysis results showed that four surrogate indexes were associated with T2DM, and the multivariate-adjusted ORs (95% CIs) of T2DM were 1.08 (1.00-1.16), 1.47 (1.32-1.63), 1.12 (1.00-1.25), and 2.45 (2.12-2.83) for each IQR (interquartile range) increment in CVAI-D, LAP-D, TG/HDLC-D, and TyG-D, respectively. Restricted cubic spline regression showed a non-linear correlation between four surrogate indexes and the risk of T2DM (p for non-linear < 0.001). From the ROC (receiver operating characteristic) curve, TyG-D had the highest AUC (area under curve), and its AUC values were significantly different from other three indexes both in male and female (all P < 0.001).

Conclusion

Compared with other indexes, TyG-D was a better predictor in the clinical setting for identifying middle-aged and elderly Chinese with T2DM. Monitoring long-term changes in TyG might help in the early identification of individuals at high risk of T2DM.

Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional Study

Background

Visceral adiposity plays a key role in the development of insulin resistance (IR), so surrogate index that can indicate visceral obesity may have higher predictive value for IR. This study aimed to establish and validate a new predictive model including indicator of visceral obesity for IR.

Methods

The study population consisted of two cohorts. The derivation cohort was a group of 667 patients with newly diagnosed type 2 diabetes and the population undergoing a routine health checkup was the validation cohort. The predictive model was established by the logistic regression analysis. Its value for predicting IR was compared with other surrogate indices by the receiver operating characteristic curve.

Results

The odds ratio (OR) of age, visceral fat area (VFA), triglyceride (TG), fasting plasma glucose (FPG), and alanine aminotransferase (ALT) for IR was 1.028 (95% CI, 1.008-1.048) (P < 0.01), 1.016 (95% CI, 1.009-1.023) (P < 0.001), 1.184 (95% CI, 1.005-1.396) (P < 0.05), 1.334 (95% CI, 1.225-1.451) (P < 0.001), and 1.021 (95% CI, 1.001-1.040) (P < 0.05). The formula of the predictive model was (0.0293 × age + 1.4892 × Ln VFA + 0.4966 × Ln TG + 2.784 × Ln FPG + 0.6906 × Ln ALT)/2. The area under the curve was the largest among all the previously reported predictors.

Conclusions

This study established and validated a predicting model for IR and confirmed its predictive value in comparison with other surrogate indicators, which will offer a simple and effective tool to measure IR in future large population studies.

Remnant cholesterol for the detection of glucose metabolic states in patients with coronary heart disease angina pectoris

BACKGROUND

This study aimed to evaluate the relationship between remnant cholesterol (RC) and glucose metabolic states in coronary heart disease (CHD) patients with angina pectoris.

METHODS

This study collected data from 11,557 CHD patients with angina pectoris aged 35-75 years in Tianjin, China. Participants were divided into normal glucose regulation (NGR), prediabetes (Pre-DM) and diabetes mellitus (DM) groups according to glucose metabolic states. Linear regression analysis was used to explore the relationship between glucose metabolism [fasting blood glucose (FBG) and glycated hemoglobin (HbA1c)] and RC levels. Logistic regression was performed to analyze the relationship between RC levels and glucose metabolic states.

RESULTS

Among all participants, 5883 (50.9%) had a DM state and 4034 (34.9%) had a Pre-DM state. FBG levels and HbA1c levels were positively related with RC in all patients (P < 0.001). NGR was used as a reference, multi-adjusted model showing that RC level was significantly associated with Pre-DM [Odds ratio (OR): 1.37; 95% confidence interval (CI) 1.19-1.56; P < 0.001] and DM state (OR:1.47; 95% CI 1.29-1.67; P < 0.001). When considering RC as categorical variables (tertiles), using T1 as a reference, T3 had the strongest relationship between RC levels and Pre-DM and DM state in univariate model and multivariate model. In the stratified analyses, the association between RC levels and pre-DM and DM in women was higher than that in men, and the elderly patients was higher than in the middle-aged patients.

CONCLUSION

The study demonstrated a significant association between RC levels and pre-DM and DM state among CHD patients with angina pectoris, and the relationship was stronger in women and elderly patients.

Older Women Who Practiced Physical Exercises before the COVID-19 Pandemic Present Metabolic Alterations and Worsened Functional Physical Capacity after One Year of Social Isolation

Background: Because the consequences of the lifestyle changes in older adults associated with the social isolation imposed in response to the COVID-19 pandemic are not fully understood, here, we investigated the effects of one year of social isolation imposed by COVID-19 on the metabolic parameters and functional physical capacity of older women who regularly practiced physical exercises before the pandemic. Methods: Systemic lipid and protein profiles, estimated creatinine clearance (ECC), and functional physical capacity (FPC) were assessed before (January-February 2020) and 12 months after social isolation in 30 older women (mean age 73.77 ± 6.22) who were engaged in a combined-exercise training program for at least 3 years before the COVID-19 pandemic. Results: In this group, we observed increased plasma levels of triglycerides and creatinine, an increase in the time necessary to perform gait speed and time-up-and-go tests, and reduced muscle strength assessed by the handgrip test and ECC post-COVID-19 pandemic relative to values recorded pre-pandemic. In addition, we observed significant correlations (both negative and positive) between anthropometric, some metabolic parameters, and physical tests. Conclusion: One year of interruption of physical exercise practice imposed in response to the COVID-19 pandemic significantly altered some systemic metabolic parameters and worsened ECC and FPC in older women.

Association of the cumulative triglyceride-glucose index with major adverse cardiovascular events in patients with type 2 diabetes

BACKGROUND

The triglyceride-glucose (TyG) index is a reliable surrogate marker of insulin resistance and is associated with major adverse cardiovascular events (MACEs) in patients with type 2 diabetes mellitus (T2DM). However, the long-term effect of the TyG index on the incidence of MACEs remains unclear. We aimed to investigate the association between the cumulative TyG index and the risk of MACEs in patients with T2DM.

METHODS

This post-hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial assessed patients' (T2DM > 3 months) cumulative TyG index and MACE data from the study database. Five fasting blood glucose and triglyceride measurements, at baseline and the first four visits, were taken from 5695 participants who had not experienced MACEs. Cumulative exposure to the TyG index was calculated as the weighted sum of the mean TyG index value for each time interval (value × time). Multivariable-adjusted Cox proportional hazard models and restricted cubic spline analysis were used to determine the association between the cumulative TyG index and MACEs. The incremental predictive value of the cumulative TyG index was further assessed.

RESULTS

Over a median follow-up of 5.09 years, 673 (11.82%) MACEs occurred, including 256 (4.50%) cardiovascular disease (CVD) deaths, 288 (5.06%) non-fatal myocardial infarctions (MIs), and 197 (3.46%) strokes. The risk of developing MACEs increased with the cumulative TyG index quartile. After adjusting for multiple potential confounders, the hazard ratios for the very high cumulative TyG index group versus the low group were 1.59 (95% confidence interval [CI], 1.17-2.16), 1.97 (95% CI 1.19-3.26), and 1.66 (95% CI 1.02-2.70) for overall MACEs, CVD death, and non-fatal MI, respectively. Restricted cubic spline analysis also showed a cumulative increase in the risk of MACEs with an increase in the magnitude of the cumulative TyG index. The addition of the cumulative TyG index to a conventional risk model for MACEs improved the C-statistics, net reclassification improvement value, and integrated discrimination improvement value.

CONCLUSIONS

In patients with T2DM, the cumulative TyG index independently predicts the incidence of MACEs, and monitoring the long-term TyG index may assist with optimized-for-risk stratification and outcome prediction for MACEs. Trial registration URL: http://www.

CLINICALTRIALS

gov . Unique identifier: NCT00000620.

Association of Non-Insulin-Based Insulin Resistance Indices with Risk of Incident Prediabetes and Diabetes in a Chinese Rural Population: A 12-Year Prospective Study

OBJECTIVE

Three non-insulin-based insulin resistance (IR) indices, ie, triglyceride-glucose (TyG) index, triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio, and metabolic score for IR (METS-IR), were considered powerful and simplified alternatives for IR. However, evidence for the association between the three IR indices and incident type 2 diabetes mellitus (T2DM), especially impaired fasting glucose (IFG), remains limited. Therefore, this study aimed to explore the association among IR indices, incident IFG, and T2DM in a rural population cohort.

METHODS

We analyzed data from 2209 adults (aged 24-75 years) at baseline and from 1205 normoglycemic participants who were followed up. Cox proportional hazards models were used to evaluate the associations between the three indices and IFG or T2DM. Restricted cubic spline curves based on the Cox regression model were used to examine the association between baseline indices and incident T2DM.

RESULTS

For the baseline data, logistic analyses demonstrated that the TyG index, TG/HDL-C ratio, and METS-IR had a significantly positive correlation with IFG or T2DM after multivariable adjustment. During a median follow-up of 12.17 years, 157 incident cases of IFG and 97 incident cases of T2DM were noted. The risk of T2DM, but not IFG, was strongly associated with the baseline TyG index in the adjusted model, and participants with the TyG index in the third tertile had a higher risk of developing T2DM (adjusted hazards ratio, 2.84; 95% confidence intervals, 1.26-6.37; p for trend <0.001) than those in the lowest tertile (reference). Moreover, a linear relationship was observed between the TyG index and T2DM incidence. The TG/HDL-C ratio and METS-IR had no significant relationship with the risk of IFG or T2DM.

CONCLUSION

The TyG index is more useful than the TG/HDL-C ratio and METS-IR in predicting T2DM in the normoglycemic population.