Background: The triglyceride-glucose index (TyG index) has emerged as a reliable surrogate marker of insulin resistance associated with arterial stiffness. However, most studies were based on a cross-sectional design, and few studies have evaluated the longitudinal impact of the TyG index on arterial stiffness. This study aimed to investigate the associations of single time point measurement and the long-term trajectory of the TyG index with arterial stiffness in a Chinese cohort. Methods: Data are derived from the Hanzhong Adolescent Hypertension Cohort study. A total of 2480 individuals who participated in the 2017 survey was included in the cross-sectional analysis. A sample of 180 individuals from the sub-cohort with follow-up data in 2005, 2013, and 2017 was enrolled in the longitudinal analysis. The TyG index was calculated as ln (fasting triglyceride [mg/dL] × fasting glucose [mg/dL]/2), and arterial stiffness was determined using brachial-ankle pulse wave velocity (baPWV). The latent class growth mixture modeling method was used to identify the TyG index trajectories from 2005 to 2017. Results: In the cross-sectional analysis, the median age of the study population was 42.8 (39.8, 44.9) years, and 1351 (54.5%) were males. Each one-unit increment in TyG index was associated with a 37.1 cm/s increase (95% confidence interval [CI] 23.7–50.6 cm/s; P < 0.001) in baPWV, and similar results were observed when the TyG index was in the form of quartiles. In the longitudinal analysis, we identified three distinct TyG index trajectories and found that the highest TyG index trajectory carried the greatest odds of increased arterial stiffness, with a fully adjusted odds ratio (OR) of 2.76 (95% CI 1.40, 7.54). Conclusions: Elevated levels of baseline TyG index and higher long-term trajectory of TyG index were independently associated with increased arterial stiffness. Monitoring immediate levels and longitudinal trends of the TyG index may help with the prevention of arterial stiffness in the long run.

Background: Although high BP is one of the most important factors affecting renal function, whether longitudinal BP trajectories in early life course are associated with renal function damage in later life is unclear. Methods: To investigate the correlation between BP trajectories from childhood to adulthood and renal function in middle age, we used group-based trajectory models to identify BP trajectories in 2430 individuals (aged 6–15 years old at baseline) participating in the ongoing Hanzhong Adolescent Hypertension Cohort. We tested the association between these trajectories and subclinical renal damage in middle age, adjusting for several covariates. Results: We identified four distinct systolic BP trajectories among 2430 subjects: low stable, moderate stable, high stable, and moderate increasing on the basis of systolic BP levels at baseline and during the 30-year follow-up period. The urinary albumin-to-creatinine ratio (uACR) was higher in moderate stable, high stable, and moderate increasing groups compared with the low stable group. A total of 228 individuals had subclinical renal disease by 2017. Compared with the low stable trajectory group, the other groups had increasingly greater odds of experiencing subclinical renal disease in middle age. These associations were not altered after adjustment for other covariates, except for in the moderate stable group. Analyzed results were similar for the mean arterial pressure and diastolic BP trajectory groups. Conclusions: Higher BP trajectories were correlated with higher of uACR levels and risk of subclinical renal disease in middle age. Identifying long-term BP trajectories from early age may assist in predicting individuals’ renal function in later life.

Sodium intake shows a positive correlation with blood pressure, resulting in an increased risk for cardiovascular diseases (CVD). Salt reduction is a key step toward the WHO's goal of 25% reduction in mortality from non‐communicable diseases (NCDs) by 2025. This study aims to assess the current condition and temporal changes of the global CVD burden due to high sodium intake (HSI). We extracted data from the Global Burden of Disease (GBD) study 2019. The numbers and age‐standardized rates of mortality and disability‐adjusted life‐years (DALYs), stratified by location, sex, and socio‐demographic Index (SDI), were used to assess the high sodium intake attributable CVD burden from 1990 to 2019. The relationship between the DALYs rates and related factors was evaluated by stepwise multiple linear regression analysis. Globally, in 2019, the deaths and DALYs of HSI‐related CVD were 1.72 million and 40.54 million, respectively, increasing by 41.08% and 33.06% from 1990. Meanwhile, the corresponding mortality and DALYs rates dropped by 35.1% and 35.2%, respectively. The high‐middle and middle SDI quintiles bore almost two‐thirds of CVD burden caused by HSI. And the leading cause of HSI attributable CVD burden was ischemic heart disease. Universal health coverage (UHC) was associated with the DALYs rates after adjustment. From 1990 to 2019, the global CVD burden attributable to HSI has declined with spatiotemporal and sexual heterogeneity. However, it remains a major public health challenge because of the increasing absolute numbers. Improving UHC serves as an effective strategy to reduce the HSI‐related CVD burden.

Limited data exists on how early-life weight changes relate to metabolic syndrome (MetS) risk in midlife. This study examines the association between long-term trajectories of body mass index (BMI), its variability, and MetS risk in Chinese individuals. In the Hanzhong Adolescent Hypertension study (March 10, 1987-June 3, 2017), 1824 participants with at least five BMI measurements from 1987 to 2017 were included. Using group-based trajectory modeling, different BMI trajectories were identified. BMI variability was assessed through standard deviation (SD), variability independent of the mean (VIM), and average real variability (ARV). Logistic regression analyzed the relationship between BMI trajectory, BMI variability, and MetS occurrence in midlife (URL: https://www.clinicaltrials.gov; Unique identifier: NCT02734472). BMI trajectories were categorized as low-increasing (34.4%), moderate-increasing (51.8%), and high-increasing (13.8%). Compared to the low-increasing group, the odds ratios (ORs) [95% CIs] for MetS were significantly higher in moderate (4.27 [2.63-6.91]) and high-increasing groups (13.11 [6.30-27.31]) in fully adjusted models. Additionally, higher BMI variabilities were associated with increased MetS odds (ORs for SD_BMI, VIM_BMI, and ARV_BMI: 2.30 [2.02-2.62], 1.22 [1.19-1.26], and 4.29 [3.38-5.45]). Furthermore, BMI trajectories from childhood to adolescence were predictive of midlife MetS, with ORs in moderate (1.49 [1.00-2.23]) and high-increasing groups (2.45 [1.22-4.91]). Lastly, elevated BMI variability in this period was also linked to higher MetS odds (ORs for SD_BMI, VIM_BMI, and ARV_BMI: 1.24 [1.08-1.42], 1.00 [1.00-1.01], and 1.21 [1.05-1.38]). Our study suggests that both early-life BMI trajectories and BMI variability could be predictive of incident MetS in midlife. This work was supported by the National Natural Science Foundation of China No. 82070437 (J.-J.M.), the Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University of China (No. XJTU1AF-CRF-2022-002, XJTU1AF2021CRF-021, and XJTU1AF-CRF-2023-004), the Key R&D Projects in Shaanxi Province (Grant No. 2023-ZDLSF-50), the Chinese Academy of Medical Sciences & Peking Union Medical College (2017-CXGC03-2), and the International Joint Research Centre for Cardiovascular Precision Medicine of Shaanxi Province (2020GHJD-14).

Background. Chronological age (CA) is not a perfect proxy for the true biological aging status of the body. A new biological aging measure, phenotypic age (PhenoAge), has been shown to capture morbidity and mortality risk in the general US population and diverse subpopulations. This study was aimed at evaluating the association between PhenoAge and long-term outcome of patients with multivessel coronary artery disease (CAD). Methods. A total of 609 multivessel CAD patients who received PCI attempt and with follow-up were enrolled. The clinical outcome was all-cause mortality on follow-up. PhenoAge was calculated using an equation constructed from CA and 9 clinical biomarkers. Cox proportional hazards regression models and receiver operating characteristic (ROC) curves were performed to evaluate the association between PhenoAge and mortality. Results. Overall, patients with more diseases had older PhenoAge and phenotypic age acceleration (PhenoAgeAccel). After a median follow-up of 33.5 months, those with positive PhenoAgeAccel had a significantly higher incidence of all-cause mortality ( ). After adjusting for CA, Cox proportional hazards models showed that both PhenoAge and PhenoAgeAccel were significantly associated with all-cause mortality. Even after further adjusting for confounding factors, each 10-year increase in PhenoAge was also associated with a 51% increased mortality risk. ROC curves revealed that PhenoAge, with an area under the curve of 0.705, significantly outperformed CA, the individual clinical chemistry measure, and other risk factors. When reexamining the ROC curves using various combinations of variables, we found that PhenoAge provides additional predictive power to all models. Conclusions. In conclusion, PhenoAge was strongly associated with all-cause mortality even after adjusting for CA. Our findings suggest that PhenoAge measure may be complementary in predicting mortality risk for patients with multivessel CAD.