Association of triglyceride-glucose index and its combination with adiposity-related indices with the incidence of myocardial infarction: a cohort study from the UK Biobank.

The triglyceride-glucose (TyG) index performs better at reflecting insulin resistance when combined with waist circumference (WC), body mass index (BMI), and waist-to-height ratio (WHtR) than when used alone. This study aimed to prospectively examine the relationships between TyG, TyG-BMI, TyG-WC, and TyG-WHtR with the incidence of myocardial infarction (MI) and its subtypes. This cohort study included 370,390 participants from the UK Biobank. The Cox proportional hazards model and restricted cubic spline regression model were used to assess the associations of TyG, TyG-BMI, TyG-WC, and TyG-WHtR with MI, ST-elevation MI (STEMI) and non-ST-elevation MI (NSTEMI). The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were employed to examine the predictive value of four indicators. The hazard ratios (HRs) and 95% confidence intervals (CIs) of MI in the highest quartiles for TyG, TyG-BMI, TyG-WC, and TyG-WHtR were 1.36 (1.28-1.44), 1.47 (1.39-1.56), 1.53 (1.43-1.64), and 1.58 (1.48-1.68) in the fully-adjusted model. Comparable findings were observed when the outcomes were reclassified as STEMI or NSTEMI. However, the associations of TyG-BMI, TyG-WC, and TyG-WHtR with the risk of STEMI were weaker than MI and NSTEMI. A linear dose-response association between TyG and the risk of MI and NSTEMI were demonstrated. TyG-BMI, TyG-WC, and TyG-WHtR all showed nonlinear patterns in their associations with the risk of MI, STEMI, and NSTEMI. TyG-WC was most effective in diagnosing MI (AUC: 0.648, 95% CI: 0.644-0.653), STEMI (AUC: 0.631, 95% CI: 0.622-0.639), and NSTEMI (AUC: 0.647, 95% CI: 0.641-0.654). The TyG index was linearly associated with increased risk of MI and NSTEMI, whereas TyG-BMI, TyG-WC, and TyG-WHtR were nonlinearly associated with increased risk of MI and NSTEMI. There were distinct patterns in the relationships between these indicators with STEMI. TyG-WC provided the best diagnostic effectiveness for MI, STEMI, and NSTEMI.

Zhou J ，Huang H ，Huang H ，Peng J ，Chen W ，Chen F ，Tang Y ，Li Q ，Xiong Y ，Zhou L ... -  《-》

Longitudinal analysis of insulin resistance and sarcopenic obesity in Chinese middle-aged and older adults: evidence from CHARLS.

The correlation between surrogate insulin resistance (IR) indices and sarcopenic obesity (SO) remains uncertain. This study aimed to assess the association between six IR surrogates-triglyceride-glucose (TyG), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), triglyceride-to-high-density lipoprotein-cholesterol ratio (TG/HDL), metabolic score for insulin resistance (METS-IR), and Chinese visceral adiposity index (CVAI)-and SO risk in a middle-aged and older population in China. The study employed longitudinal data obtained from the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2015, involving 6,395 participants. We used multivariate logistic regression models to examine the link between six surrogates and SO. Nonlinear relationships were evaluated using restricted cubic spline analysis, and subgroup analyses were conducted for validation. Receiver operating characteristic (ROC) curves were used to assess predictive capabilities. Over the course of a 4-year follow-up period, 319 participants (5.0%) developed SO. In the fully adjusted model, all six surrogates were significantly associated with SO. The adjusted odds ratios (ORs) with a 95% confidence interval (95% CI) per standard deviation increase were 1.21 (1.08-1.36) for TyG, 1.56 (1.39-1.75) for TyG-WC, 2.04 (1.81-2.31) for TyG-WHtR, 1.11 (1.01-1.21) for TG/HDL, 1.67 (1.50-1.87) for METS-IR, and 1.74 (1.55-1.97) for CVAI. Notably, TyG-WC, TyG-WHtR, TG/HDL, METS-IR, and CVAI exhibited nonlinear correlations with SO. Conversely, TG/HDL did not exhibit a significant association during subgroup analysis. Furthermore, TyG-WHtR had a significantly larger area under the receiver operating characteristic curve than other indices. The results indicated that TyG, TyG-WC, TyG-WHtR, METS-IR, and CVAI were significantly and positively associated with SO incidence. Meanwhile, TyG-WC, TyG-WHtR, METS-IR, and CVAI showed nonlinear relationships with SO. Specifically, TyG-WHtR may be the most appropriate indicator for predicting SO among middle-aged and older Chinese adults.

Xu C ，He L ，Tu Y ，Guo C ，Lai H ，Liao C ，Lin C ，Tu H ... -  《Frontiers in Public Health》

The potential of insulin resistance indices to predict non-alcoholic fatty liver disease in patients with type 2 diabetes.

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

Tian J ，Cao Y ，Zhang W ，Wang A ，Yang X ，Dong Y ，Zhou X ... -  《BMC Endocrine Disorders》

Association of triglyceride glucose index combined with obesity indicators with cognitive impairment.

The association of a combination of the TyG index and obesity markers, specifically waist circumference (WC), with cognitive function is unknown. This research investigated the relationship between TyG-WC measurements and cognitive impairment in a low-income population in China; moreover, this study evaluated the role of diabetes mellitus and body mass index (BMI) in modulating this relationship. 1125 eligible individuals aged ≥ 60 years participated in this study. The TyG index and obesity indicators (BMI, WC, and waist-to-height ratio) were calculated for individual participants and categorized into quartiles. Multivariate logistic regression analysis was used to evaluate the correlation between TyG-WC values and cognitive impairment; the possibility of a nonlinear relationship was explored using constrained cubic spline analysis. The participants were divided into different groups according to their diabetes status and BMI category for subgroup analyses. Linear regression was used to investigate the correlation between TyG-WC values and MMSE scores. The prevalence of cognitive impairment in the study participants was 47.3%, with a significant negative association between TyG-WC values and cognitive impairment, (odds ratio [OR] = 0.999; 95% confidence interval [CI], 0.997-1.00, P = 0.009). A U-shaped correlation was observed between the TyG-WC values and cognitive impairment (P = 0.008). Subgroup analyses showed that the inverse association between TyG-WC values and cognitive impairment was stronger in non-diabetic individuals (OR = 0.998; 95% CI, 0.997-0.999; P = 0.002) and in those with a lower BMI (< 24 kg/m2; OR = 0.996; 95% CI, 0.994-0.998; P = 0.001). A positive correlation was found between TyG-WC values and MMSE scores, particularly in men and non-diabetic individuals (β = 0.003; 95% CI, 0.0002-0.005; P = 0.031). This study demonstrates a nonlinear U-shaped relationship between TyG-WC values and cognitive function. The stronger inverse association between TyG-WC values and cognitive decline in the non-diabetic and low-BMI subgroups suggests that these populations may benefit the most from targeted interventions. These findings are important for clinical practice and formulating disease-prevention policies, emphasizing the need for metabolic health management to prevent cognitive decline, particularly in low-income populations.

Hao J ，Lu Y ，Zhang L ，Li X ，Wen H ，Zhao X ，Wang L ，Tu J ，Wang J ，Yang C ，Ning X ，Li Y ... -  《Lipids in Health and Disease》

Utility of Anthropometric Indexes for Detecting Metabolic Syndrome in Resource-Limited Regions of Northwestern China: Cross-Sectional Study.

Anthropometric indexes offer a practical approach to identifying metabolic syndrome (MetS) and its components. However, there is a scarcity of research on anthropometric indexes tailored to predict MetS in populations from resource-limited regions. This study aimed to examine the association between 8 easy-to-collect anthropometric indexes and MetS, and determine the most appropriate indexes to identify the presence of MetS for adults in resource-limited areas. A total of 10,520 participants aged 18-85 years from Ningxia Hui Autonomous Region, China, were included in this cross-sectional study. Participants were recruited through a stratified sampling approach from January 1, 2020, to December 31, 2021. MetS was defined using the International Diabetes Federation (IDF) criteria. Eight anthropometric indexes were examined, including BMI, waist-to-height ratio (WHtR), weight-adjusted waist index (WWI), conicity index, a body shape index (ABSI), lipid accumulation products (LAP), visceral obesity index (VAI), and the triglyceride-glucose (TyG) index. Logistic regression analysis and restricted cubic splines (RCSs) were applied to identify the association between the anthropometric indexes. The receiver operating characteristic curve and the area under the curve (AUC) were analyzed to identify and compare the discriminative power of anthropometric indexes in identifying MetS. The Youden index was used to determine a range of optimal diagnostic thresholds. Logistic regression analysis was applied to identify the association between the anthropometric indexes. A total of 3324 (31.60%) participants were diagnosed with MetS. After adjusting for age, ethnicity, current residence, education level, habitual alcohol consumption, and tobacco use, all the 8 indexes were positively correlated with the risks of MetS (P<.05). LAP presented the highest adjusted odds ratios (adjOR 35.69, 95% CI 34.59-36.80), followed by WHtR (adjOR 29.27, 95% CI 28.00-30.55), conicity index (adjOR 11.58, 95% CI 10.95-12.22), TyG index (adjOR 5.53, 95% CI 5.07-6.04), BMI (adjOR 3.88, 95% CI 3.71-4.05), WWI (adjOR 3.23, 95% CI 3.02-3.46), VAI (adjOR 2.11, 95% CI 2.02-2.20), and ABSI (adjOR 1.71, 95% CI 1.62-1.80). Significantly nonlinear associations between the 8 indexes and the risk of MetS (all Pnonlinear<.001) were observed in the RCSs. WHtR was the strongest predictor of MetS for males (AUC 0.91, 95% CI 0.90-0.92; optimal cutoff 0.53). LAP were the strongest predictor of MetS for females (AUC 0.89, 95% CI 0.89-0.90; optimal cutoff 28.67). Statistical differences were present between WHtR and all other 7 anthropometric indexes among males and overall (all P<.05). In females, the AUC values between LAP and BMI, WWI, ABSI, conicity index, VAI, and TyG index were significantly different (P<.001). No statistical difference was observed between LAP and WHtR among females. According to 8 anthropometric and lipid-related indices, it is suggested that WHtR and LAP are the most appropriate indexes for identifying the presence of MetS in resource-limited areas.

Yang D ，Ma L ，Cheng Y ，Shi H ，Liu Y ，Shi C ... -  《JMIR Public Health and Surveillance》