A non-linear relationship between triglyceride glucose waist circumference and nonalcoholic fatty liver disease in a Japanese population: a secondary analysis

Metabolic outcomes in non-alcoholic and alcoholic steatotic liver disease among Korean and American adults

BACKGROUND

This study investigated the prevalence and causal relationships of chronic metabolic diseases (diabetes, hypertension, and dyslipidemia) with steatotic liver disease (SLD), specifically metabolically associated alcoholic liver disease (MetALD).

METHODS

We conducted a comprehensive analysis using cross-sectional data from the KNHANES from 2011 to 2021 and the NHANES from 1999 to 2020. Longitudinal data from 2001 to 2014 from the KoGES were used. Participants were categorized into the metabolic dysfunction-associated SLD(MASLD), MetALD, and ALD groups based on their hepatic steatosis index (HSI), including liver profiles, body composition, and diabetes, and alcohol consumption. Multivariable, including age and smoking status, logistic and Cox regression analyses were performed to assess the prevalence and incidence of chronic diseases.

RESULTS

In both the KNHANES and NHANES cohorts, an increased HSI was significantly associated with a higher prevalence of chronic metabolic diseases. Longitudinal data from the KoGES cohort showed that MASLD and MetALD were significant predictors of chronic metabolic disease in both men and women. MetALD showed a higher hazard ratio for the development of chronic metabolic diseases than MASLD in Cox regression analysis.

CONCLUSIONS

This study highlighted the intertwined nature of SLD and metabolic health, with an emphasis on the role of MetALD. The significant association between MetALD and chronic metabolic diseases underscores the need for integrated management strategies that address both liver health and metabolic risk factors.

Changes in the triglyceride-glucose-body mass index estimate the risk of hypertension among the middle-aged and older population: a prospective nationwide cohort study in China in the framework of predictive, preventive, and personalized medicine

Background

Hypertension is a major modifiable cause of cardiovascular diseases and premature death worldwide. The triglyceride-glucose-body mass index (TyG-BMI), as a novel indicator, has been proposed for assessing hypertension risk. Nevertheless, a paucity of studies has explored the predictive potential of dynamic TyG-BMI for hypertension. The purpose of this study was to investigate whether cumulative TyG-BMI could better predict hypertension incidence and explore the interplay between TyG and BMI in hypertension development. From the perspective of predictive, preventive, and personalized medicine (PPPM/3PM), we assumed that dynamic monitoring of TyG-BMI level and joint assessment of TyG and BMI provide novel insights for individual risk assessment, targeted prevention, and personalized intervention of cardiovascular diseases.

Methods

Using data from the China Health and Retirement Longitudinal Study (CHARLS), a nationwide cohort conducted between 2011 and 2018, the changes in TyG-BMI between 2012 and 2015 were categorized into four groups by K-means clustering analysis. Cumulative TyG-BMI was also divided into four levels based on quartile cutoffs. Logistic regression and restricted cubic spline analyses were performed to examine the associations of different TyG-BMI classes with hypertension. Mediating and interactive analyses were utilized to discern the mutual effects between TyG and BMI in hypertension development.

Results

A total of 2891 participants were enrolled, among whom 386 (13.4%) developed hypertension during a median 36.5-month follow-up period. Logistic regression analysis revealed that, compared to participants with persistently low TyG‑BMI, an increased risk of hypertension was observed among those with a moderate (odds ratio (OR) = 1.60, 95% confidence interval (CI) 1.15 to 2.22), a higher (OR = 1.93, 95% CI 1.28 to 2.89), and the highest TyG‑BMI (OR = 2.33, 95% CI 1.35 to 4.03). A positive linear association of cumulative TyG-BMI with hypertension was discovered (P for non-linear = 0.343). Furthermore, TyG partially mediated the relationship between BMI and hypertension, accounting for 13.18% of the total effect. The joint effect of BMI and TyG was positively affiliated to hypertension development.

Conclusions

This study demonstrated a significant positive association between dynamic TyG-BMI and hypertension among the Chinese middle-aged and older population. In the context of PPPM/3PM, long-term monitoring of TyG-BMI could assist in identifying individuals at high risk of hypertension, strengthening primary prevention efforts and facilitating prompt intervention strategies. In addition, this study revealed the mutual effect of TyG and BMI on hypertension development, which provides a novel approach for mitigating the risk of cardiovascular diseases via addressing metabolic disorders, thereby enhancing effective prevention and targeted intervention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00380-6.

Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005-2018

BACKGROUND

The intake of dietary antioxidants and glycolipid metabolism are closely related to chronic kidney disease (CKD), particularly among individuals with abdominal obesity. Nevertheless, the cumulative effect of multiple comorbid risk factors on the progression and complications of CKD remains inadequately characterized.

METHODS

This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) dat abase (2005-2018), to examine potential factors related to CKD, including glycolipid metabolism, dietary antioxidant intake, and pertinent medical history. To explore the associations between these variables and CKD, the present study used a multivariable-adjusted least absolute shrinkage and selection operator (LASSO) regression model, along with a restricted cubic spline (RCS) model. Furthermore, an optimal predictive model was developed for CKD using ten machine learning algorithms and enhanced model interpretability with the Shapley Additive Explanations (SHAP) method.

RESULTS

A cohort comprising 8,764 eligible individuals (52% male, including 1,839 CKD patients) with abdominal obesity aged 20-85 years were included. The findings revealed significant positive correlations in patients with abdominal obesity between the presence of CKD and age, a history of heart failure, hypertension, diabetes, elevated lipid accumulation product (LAP) and triglyceride glucose-waist circumference (TyG-WC) levels. Conversely, negative correlations were identified between CKD and variables such as sex, high-density lipoprotein cholesterol (HDL-C) levels, and the composite dietary antioxidant index (CDAI). In parallel, RCS regression analysis revealed significant nonlinear associations between the CDAI, HDL-C, TyG-WC, and CKD among patients with abdominal obesity aged 60-80 years. The development of predictive models demonstrated that the CatBoost model surpassed other models, achieving an accuracy of 86.74% on the validation set. The model's area under the receiver operator curve (AUC) and F1 score were 0.938 and 0.889, respectively. The SHAP values revealed that age was the most significant predictor, followed by diabetes history, hypertension, HDL-C levels, CDAI index, TyG-WC, and LAP.

CONCLUSION

CatBoost models, along with glycolipid metabolism indexes and dietary antioxidant intake, are effective for early CKD detection in patients with abdominal obesity.

The nonlinear relationship between triglyceride glucose-waist circumference and stroke risk in middle-aged and elderly people: a nationwide prospective cohort study of the CHARLS

BACKGROUND AND AIMS

Numerous research have focused on the relationship of metabolic markers and stroke risk, yet limited research has focused on the triglyceride glucose-waist circumference (TyG-WC) index. This study explored the possible association of TyG-WC and stroke among moderately aged and old Chinese adults over 45 years of age.

METHODS

This observational cohort analysis involved 9054 participants from the Chinese Longitudinal Study of Health and Retirement and employed a standardized questionnaire administered via in-person interviews. Cox proportional hazard model, smoothed curve fitting, and threshold effect analysis were conducted for examining the potential nonlinear relationships among TyG-WC and stroke risk.

RESULTS

Within an average follow-up period of six years, 463 new strokes occurred, representing 5.11% of the total number of patients. After adjusting for possible confounding factors, a nonlinear association between TyG-WC and stroke risk was identified, with a significant dose-response relationship (P = 0.023 for the log-likelihood ratio test). A turning point was identified at the TyG-WC level of 554.48, beyond that the likelihood of stroke increased markedly (HR = 1.323, 95% CI = 1.098-1.594, P = 0.003).

CONCLUSION

This study revealed a specific curvilinear association with the TyG-WC score and stroke risk, identifying a key threshold value. This study focused on Chinese middle-aged and senior adults over the age of 45, emphasizing that increased stroke risk is linked to higher TyG-WC levels.

Prognostic effect of triglyceride glucose-related parameters on all-cause and cardiovascular mortality in the United States adults with metabolic dysfunction-associated steatotic liver disease

BACKGROUNDS

Insulin resistance (IR) plays a vital role in the pathogenesis of the metabolic dysfunction-associated steatotic liver disease (MASLD). However, it remains unclear whether triglyceride-glucose (TyG) related parameters, which serve as useful biomarkers to assess IR, have prognostic effects on mortality outcomes of MASLD.

METHODS

Participants in the National Health and Nutrition Examination Survey (NHANES) database from 1999 to 2018 years were included. TyG and its related parameters [TyG-waist circumference (TyG-WC) and TyG-waist to height ratio (TyG-WHtR)] were calculated. Kaplan-Meier curves, Cox regression analysis, and restricted cubic splines (RCS) were conducted to evaluate the association between TyG-related indices with the all-cause and cardiovascular mortality of adults with MASLD. The concordance index (C-index) was used to evaluate the prediction accuracy of TyG-related indices.

RESULTS

A total of 8208 adults (4209 men and 3999 women, median age 49.00 years) with MASLD were included in this study. Multivariate-adjusted Cox regression analysis revealed that high quartile levels of TyG-related indices were significantly associated with the all-cause mortality of participants with MASLD [TyGadjusted hazard ratio (aHR) = 1.25, 95% confidence interval (CI) 1.05-1.50, P = 0.014; TyG-WCaHR for all-cause mortality = 1.28, 95% CI 1.07-1.52, P = 0.006; TyG-WHtRaHR for all-cause mortality = 1.50, 95% CI 1.25-1.80, P < 0.001; TyG-WCaHR for cardiovascular mortality = 1.81, 95% CI 1.28-2.55, P = 0.001; TyG-WHtRaHR for cardiovascular mortality = 2.22, 95% CI 1.55-3.17, P < 0.001]. The C-index of TyG-related indices for predicting all-cause mortality was 0.563 for the TyG index, 0.579 for the TyG-WC index, and 0.585 for the TyG-WHtR index, respectively. Regarding cardiovascular mortality, the C-index was 0.561 for the TyG index, 0.607 for the TyG-WC index, and 0.615 for the TyG-WHtR index, respectively. Nonlinear trends were observed between TyG and TyG-WC indices with all-cause mortality of MASLD (P < 0.001 and = 0.012, respectively). A non-linear relationship was observed between the TyG index and cardiovascular mortality of MASLD (P = 0.025). Subgroup analysis suggested that adults aged < 65 years old and those without comorbidities were more sensitive to the mortality prediction of TyG-related indices.

CONCLUSION

Findings of this study highlight the predictive value of TyG-related indices, especially the TyG-WHtR index, in the mortality outcomes of adults with MASLD. TyG-related indices would be surrogate biomarkers for the clinical management of MASLD.

Diagnostic Accuracy of the Triglyceride-Glucose Index (TyG), TyG Body Mass Index, and TyG Waist Circumference Index for Liver Steatosis Detection

BACKGROUND

The triglyceride-glucose index (TyG) and a combination of body mass index (BMI) and waist circumference (WC) have been proposed as predictive scores for liver steatosis (LS). The aim of this study was to determine the diagnostic accuracy of these indices compared with controlled attenuation parameters (CAPs) and other predictive scores of LS.

METHODS

A retrospective analysis of patients who attended a check-up unit in 2021 was performed. LS was determined by CAP. Anthropometric and biochemical parameters for calculating TyG, TyG-BMI, TyG-WC, fatty liver index, and hepatic steatosis index were obtained. ROC curve was used to establish the best cut-off point of each TyG index for LS detection. The accuracy was determined for all patients, as well as for overweight and diabetic patients.

RESULTS

Medical records of 855 patients with a median age of 48 [IQR, 44-54] years and a BMI of 25.7 [IQR 23.4-28.1] kg/m2 were included. According to CAP, LS prevalence was 31.8% (n = 272). TyG-BMI and TyG-WC show better AUCs compared with CAP (0.82, 0.81), FLI (0.96, both), and HSI (0.93, 0.85). For diabetic patients, TyG-WC shows an AUC of 0.70. Meanwhile, TyG-BMI shows better accuracy (0.75) compared with CAP.

CONCLUSIONS

TyG-BMI and TyG-WC showed a superior predictive accuracy for detecting LS compared with the TyG index.

Associations of the triglyceride-glucose index and atherogenic index of plasma with the severity of new-onset coronary artery disease in different glucose metabolic states

BACKGROUND

The triglyceride-glucose (TyG) index is considered a dependable biomarker for gauging insulin resistance. The atherogenic index of plasma (AIP) represents a marker reflecting atherosclerosis. However, there is currently no study specifically exploring the associations of these two biomarkers with the severity of new-onset coronary artery disease (CAD) under different glucose metabolic states. Therefore, this study aims to evaluate the correlations of these two biomarkers with CAD severity in patients newly diagnosed with CAD under various glucose metabolism conditions.

METHOD

Totally 570 subjects first administered coronary angiography were enrolled, including 431 first diagnosed CAD patients and 139 non-CAD patients. CAD severity  was gauged by the quantity of narrowed arteries (single-vessel and multi-vessel CAD). According to WHO diabetes guidelines, glucose metabolic states were divided into normal glucose regulation (NGR), pre-diabetes mellitus (Pre-DM), and diabetes mellitus (DM). The relationships of the TyG index and AIP with CAD severity were validated by logistic regression analysis, including adjustment for traditional cardiovascular risk elements and medical treatments. Their predictive efficacy for CAD was evaluated by receiver operating characteristic (ROC) curves.

RESULT

The TyG index and AIP were independently correlated with CAD in accordance with logistic regression analysis (both P < 0.05). Regardless of the glucose metabolic states, there was no statistical correlation between the TyG index and CAD severity. However, AIP in NGR patients was significantly related to CAD severity (P < 0.05). The areas under the curve of the TyG index and AIP for predicting CAD were 0.682 and 0.642 (both P < 0.001), respectively, and their optimal cut-off values were 3.210 (Youden index: 0.305) and 0.095 (Youden index:0.246), respectively.

CONCLUSION

The TyG index and AIP have significant associations with CAD. The TyG index had no association with CAD severity, regardless of glucose metabolic states. AIP exhibited a discernible link with CAD severity in NGR patients, but not in the pre-DM or DM populations. The TyG index and AIP have similar predictive values for new-onset CAD.