Background: The triglyceride-glucose (TyG) index could serve as a convenient substitute of insulin resistance (IR), but epidemiological evidence on its relationship with the long-term risk of mortality is limited.Methods: Participants from the National Health and Nutrition Examination Survey during 1999–2014 were grouped according to TyG index (10). Cox regression was conducted to compute the hazard ratios (HRs) and 95% confidence interval (CI). Restricted cubic spline and piecewise linear regression were performed to detect the shape of the relationship between TyG index and mortality.Results: A total of 19,420 participants (48.9% men) were included. On average, participants were followed-up for 98.2 months, and 2,238 (11.5%) and 445 (2.3%) cases of mortality due to all-cause or cardiovascular disease were observed. After adjusting for confounders, TyG index was independently associated with an elevated risk of all-cause (HR, 1.10; 95% CI, 1.00–1.20) and cardiovascular death (HR, 1.29; 95% CI, 1.05–1.57). Spline analyses showed that the relationship of TyG index with mortality was non-linear (All non-linear P < 0.001), and the threshold value were 9.36 for all-cause and 9.52 for cardiovascular death, respectively. The HRs above the threshold point were 1.50 (95% CI, 1.29–1.75) and 2.35 (95% CI, 1.73–3.19) for all-cause and cardiovascular death. No significant difference was found below the threshold points (All P > 0.05).Conclusion: Elevated TyG index reflected a more severe IR and was associated with mortality due to all-cause and cardiovascular disease in a non-linear manner.

Objective: Individuals with both hypertension and diabetes have been confirmed to significantly increase the risk of cardiovascular disease morbidity and mortality compared with those with only hypertension or diabetes. This study aimed to evaluate the potential of different anthropometric indices for predicting diabetes risk among hypertensive patients.Methods: The study group consisted of 6,990 hypertensive adults without diabetes who were recruited in China. Demographic and clinical assessment, physical examinations, laboratory tests, and anthropometric measurements, including body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and novel indices (ABSI, AVI, BAI, BRI, CI, WWI, and WHHR), were performed at baseline and during the (median) 3-year follow-up. Cox regression analyses were conducted to estimate effects from these indices for the onset of diabetes. Receiver operator characteristic (ROC) analyses were conducted to assess the predictive capacities of the anthropometric indices and determine the optimal cut-points.Results: A total of 816 (11.7%) developed diabetes during our prospective study. Multivariate Cox regression analyses revealed weight, WC, WHR, WHtR, BAI, BRI, and WWI as the independent risk factor for diabetes among hypertensive patients, regardless of whether it was treated as a continuous or categorical variable (P < 0.05). Further Cox analyses combining BMI and different central obesity indices showed that elevated WC, WHR, WHtR, AVI, BRI, CI, regardless of the general obesity status, were found to be each independently associated with increased diabetes risk (P < 0.05). Dynamic increases of BRI < 5.24 to BRI ≥ 5.24 were associated with increased risk (HR = 1.29; 95% CI, 1.02, 1.64), and its reversal was associated with reduced risk (HR = 1.56; 95% CI, 1.23, 1.98) compared with the others (HR = 1.95; 95% CI, 1.63, 2.32). ROC analysis indicated that the areas under the ROC curves (AUC) of the anthropometric indices ranged from 0.531 to 0.63, with BRI (cut-off value = 4.62) and WHtR having the largest area.Conclusions: Based on this novel study, BRI was the most superior predictor and independent determinant for diabetes onset among the hypertensive population. Hypertensive patients with BRI > 4.62, regardless of general obesity status, were at high risk of diabetes. Thus, the prompt screening and diagnosis of diabetes should be carried out among these patients for timely integrated intervention.

Limited evidence exists on the combined and mediating effects of systemic inflammation on the association between insulin resistance and cardiovascular events in patients with diabetes and chronic coronary syndrome (CCS). This secondary analysis of a multicenter prospective cohort included 4419 diabetic CCS patients. Triglyceride–glucose index (TyG) and high-sensitivity C-reactive protein (hsCRP) were applied to evaluate insulin resistance and systemic inflammation, respectively. The primary endpoint was major adverse cardiac event (MACE). Associations of TyG and hsCRP with cardiovascular events were estimated using Cox regression. A mediation analysis was performed to assess whether hsCRP mediates the relationship between TyG and cardiovascular events. Within a median 2.1-year follow-up period, 405 MACEs occurred. Patients with high levels of TyG and hsCRP experienced the highest MACE risk (hazard ratio = 1.82, 95% confidence interval: 1.24–2.70, p = 0.002) compared to individuals with low levels of both markers. HsCRP significantly mediated 14.37% of the relationship between TyG and MACE (p < 0.001). In diabetic CCS patients, insulin resistance and systemic inflammation synergically increased the risk of cardiovascular events, and systemic inflammation partially mediated the association between insulin resistance and clinical outcomes. Combining TyG and hsCRP can help identify high-risk patients. Controlling inflammation in patients with insulin resistance may bring added benefits.

The triglyceride glucose (TyG) index has been proposed to be a surrogate of insulin resistance. In the present study, we aimed to examine the relationship between TyG index and the risk of incident diabetes in middle-age and older adults in China using nationally representative data from the China Health and Retirement Longitudinal Study 2011–2015. Information on socio-demographics, medical background, anthropometric measurement, and laboratory information were collected. The association between TyG index and diabetes was examined by Cox proportional hazards models and restricted cubic spline regression, and the results were presented in hazard ratio (HR) with 95% confidence interval (CI). Subgroup analyses were also conducted to examine potential interactions between demographics and TyG index. Among 7,428 participants, 791 (10.6%) of them developed diabetes over 3.4 years of follow-up. The multivariate HR for every SD increment in TyG index was 1.22 (95% CI, 1.14–1.31). When comparing to the lowest quartile of TyG index, the multivariate HRs for new-onset diabetes were 1.22 (0.96–1.54) for Q2, 1.61 (1.28–2.01) for Q3, and 1.73 (1.38–2.16) for Q4 (P for trend <0.001). The restricted cubic spline regression also showed a linear association. No interaction was found between subgroup variables and the association between TyG index and the risk of diabetes. In conclusion, higher TyG index associated with the elevated risk of new-onset diabetes in middle-aged and older adults.

Cardiovascular-kidney-metabolic (CKM) syndrome is a novel staging framework used to evaluate CKM health. The burden of CKM syndrome in China is relatively unknown, and such data may inform future health priority. The purpose of this study was to assess the prevalence and mortality risk across CKM stages. Nationally representative populations (n = 33,685) were included from the China Hypertension Survey. The weighted prevalence of each CKM stage was calculated. All-cause, cardiovascular (CV), and non-CV death associated with CKM stages were analyzed using Cox regression analysis. Population attributable fraction (PAF) was calculated to estimate the mortality burden related to each CKM stage. Between 2012 and 2015, 18.8% of Chinese adults met criteria for stage 0, 15.5% for stage 1, 42.1% for stage 2, 14.7% for stage 3, and 8.9% for stage 4, with advanced stage (stages 3-4) was 23.6%. After 5-year follow-up, compared with stage 0, adjusted HR for all-cause death in stage 1 was 0.77 (95% CI: 0.51-1.15), stage 2 was 1.36 (95% CI: 1.04-1.77), stage 3 was 2.47 (95% CI: 1.91-3.19), and stage 4 was 4.00 (95% CI: 3.07-5.22). Similarly, adjusted HRs for CV death and non-CV death progressively increased from stage 2 to 4 (both P-trend values < 0.001). For all-cause, CV, and non-CV death, PAFs increased with advancing CKM stages. For instance, for all-cause death, PAFs caused by stages 2, 3, and 4 were 13.4%, 18.6%, and 22.0%. Poor CKM health is widespread in China, underscoring the urgent need for collaborative and comprehensive management strategies to tackle CKM syndrome epidemic.

Background Given the fat redistribution in later stages of life, how the associations between abdominal obesity and the risk of morbidity and mortality have changed with age have not been elucidated, especially for waist to height ratio (WHtR). Objective To compare the strength of association between obesity indices and chronic diseases at baseline, and the subsequent mortality risk among US adults. Methods We included 21 109 participants from National Health and Nutrition Examination Survey 1999–2014. We performed logistic regression and receiver operating curve analysis to examine the discriminatory power of obesity indicators on cardiometabolic diseases and cancer at baseline. Sex-stratified and age-stratified Cox models were constructed to explore the prospective association between obesity indices and all-cause, cardiovascular and cancer mortality. Results Elevated WHtR, elevated waist circumference (WC) and body mass index (BMI)-classified obesity are associated with higher odds of hypertension (OR: 1.37-2.13), dyslipidemia (OR: 1.06 to 1.75, all p<0.05) and diabetes (OR: 1.40-3.16, all p<0.05). WHtR had significantly better discriminatory power to predict cardiometabolic health than BMI, especially for diabetes (area under the curve: 0.709 vs 0.654). After multivariable adjustment, all obesity indicators are associated with lower risk of all-cause mortality among females aged ≥65 years (HR: 0.64 to 0.85), but the association was only significant for BMI when obesity indicators were mutually adjusted (HR: 0.79). Conclusions WHtR and WC appeared to be the better indicators for cardiometabolic health than BMI. However, BMI had a stronger and inverse association with a greater risk of all-cause mortality among older females.