Aim: This study aims to investigate the relationship between two novel inflammatory markers, namely, the Systemic Inflammatory Response Index (SIRI) and the Systemic Immune Inflammatory Index (SII), as well as the all-cause and cardiovascular disease (CVD) mortality in the obese population. Materials and methods: We conducted a prospective cohort study based on the data of 13,026 obese adults (age ≥ 18 years) from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014 and followed until December 2019. SIRI was calculated by the formula: (neutrophil count × monocyte count) / lymphocyte count, while that of SII was: (platelet count × neutrophil count)/lymphocyte count. The association of SIRI and SII with all-cause and CVD mortality was evaluated using Cox regression. In addition, the nomogram was performed to predict 10-year survival probability. Results: During a median follow-up of 137 months, 1959 and 553 all-cause and CVD deaths were recorded, respectively. Spearman correlation analysis indicated that SIRI and SII were unrelated to almost all baseline characteristics (r < 0.15). Multivariate Cox regression models displayed that each standard deviation (SD) increase in SIRI was associated with a 16% (HR 1.16; 95% CI 1.09–1.24) and 22% (HR 1.22; 95% CI 1.10–1.36) increase in the risk of all-cause and CVD mortality, respectively. Likewise, every SD increase in SII was correlated with a 9% (HR 1.09; 95% CI 1.02–1.16) and 14% (HR 1.14; 95% CI 1.04–1.26) increase in the risk of all-cause and CVD mortality, respectively. The predictive value of SIRI for all-cause and CVD mortality (AUC = 0.601 and 0.624) exceeded that of SII (AUC = 0.528 and 0.539). Moreover, the nomogram displayed a substantial predictive value for 10-year survival (AUC = 0.847) with sensitivity and specificity exceeding 75%. Conclusions: In the obese population, SIRI and SII are independent risk factors for all-cause and CVD mortality. Notably, the predictive ability of SIRI for both all-cause and CVD mortality significantly outperforms that of SII, suggesting that SIRI is a more valuable marker of inflammation.

Evidence regarding the role of chronic low-grade inflammation in the progression of cardiometabolic diseases (CMDs) and cardiometabolic multimorbidity (CMM) is currently limited. This prospective cohort study, utilising data from the UK Biobank, included 273,804 adults aged 40–69 years initially free of CMD at baseline. CMM was defined as the coexistence of two or more CMDs, such as coronary artery disease, type 2 diabetes mellitus, hypertension and stroke. The aggregated inflammation score (INFLA-score), incorporating C-reactive protein, white blood cell count, platelet count and granulocyte-to-lymphocyte ratio, quantified chronic low-grade inflammation. Absolute risks (ARs), hazard ratios (HRs) and 95% confidence intervals (CIs) assessed the association of increased INFLA-score with the risk of CMMs and CMDs. The accelerated failure time model explored the effect of INFLA-score on the time to CMM onset, and a restricted cubic spline characterised the dose-dependent relationship between INFLA-score and CMM risk. After a median follow-up of 166.37 months, 13,755 cases of CMM were identified. In quartiles with increasing INFLA-score levels, CMM ARs were 4.41%, 4.49%, 5.04% and 6.01%, respectively; HR increased by 2%, 15% and 36%, respectively, compared to the lowest quartile. The INFLA-score and CMM risk relationship was nonlinear (P for nonlinear < 0.001), exhibiting a significant risk trend change at a score of 9. For INFLA-score < 9, CMM risk increased by 1.9% for each 1-point increase; for INFLA-score ≥ 9, the risk increased by 5.9% for each 1-point increase. Additionally, a higher INFLA-score was associated with an earlier onset of CMM (P < 0.001). Compared to the first INFLA-score quartile, the AFT model revealed adjusted median times to CMM occurrence were 2.92, 6.10 and 13.19 months earlier in the second, third and fourth quartile groups, respectively. Chronic low-grade inflammation is associated with a higher risk of cardiometabolic multimorbidity and earlier onset among middle-aged and older adults. Monitoring and screening the INFLA-score in adults without CMDs may improve early prevention of CMM.

Background: Patterns of dyslipidemia and incidence of hypertension have been rarely reported in Asian populations with inconsistent findings. To accumulate further evidence in Asian populations, the study aimed to investigate the relationship between lipid profiles and hypertension in Chinese adult males.Methods: We conducted a cross-sectional study based on the data from the DATADRYAD database. The overall population was divided into hypertensive and non-hypertensive groups based on baseline blood pressure levels. For continuous variables, Mann-Whitney test was performed between two groups, while Kruskal-Wallis and Dunn tests were used among multiple groups. The chi-square test was carried out for dichotomous variables. Spearman's correlation coefficient was employed to assess the association between systolic blood pressure (SBP), diastolic blood pressure (DBP) and lipid profiles, whereas the relationship between lipid profiles and the incidence of hypertension was evaluated using multivariate logistic regression. The Bayesian network (BN) model was adopted to investigate the relationship between clinical characteristics and hypertension, and the importance of related predictor to the incidence of hypertension was obtained to make conditional probability analysis.Results: Finally, totally 62,957 participants were included in this study. In the lipid profiles, total cholesterol (TC), low-density cholesterol (LDL-c), and non- high-density lipoprotein cholesterol (non-HDL-c) were higher in the hypertensive population (p <0.001). In the fully multivariate model, for every 1 mg/dl increase in TC, LDL-c and non-HDL, the risk of hypertension increased by 0.2% [1.002 (1.001–1.003)], 0.1% [1.001 (1.000–1.002)], and 0.1% [1.001 (1.000–1.002)]. Meanwhile, HDL-c became positively associated with the incidence of hypertension (p for trend < 0.001) after adjusting for the body mass index (BMI), and 1 mg/dl increment in HDL-c increased the risk of hypertension by 0.2% [1.002 (1.000–1.002)] after fully adjusting for multiple variables. Furthermore, the BN showed that the importance of age, BMI, fasting plasma glucose (FPG), and TC to the effect of hypertension is 43.3, 27.2, 11.8, and 5.1%, respectively.Conclusion: Elevated TC, LDL-c, and non-HDL-c were related to incidence of hypertension in Chinese adult males, whereas triglycerides (TG) was not significantly associated. The relationship between HDL-c and hypertension incidence shifted from no association to a positive correlation after adjusting for the BMI. Moreover, the BN model displayed that age, the BMI, FPG, and TC were strongly associated with hypertension incidence.

Background: Insulin resistance (IR) significantly contributes to cardiovascular disease (CVD) development. Triglyceride glucose (TyG) index and triglyceride glucose-body mass index (TyG-BMI) are recognised as convenient proxies for IR. However, their relationship with sudden cardiac arrest (SCA) remains unclear. Methods: This prospective cohort analysis included 355,242 UK Biobank participants with available TyG index and TyG-BMI data and no history of CVD. Cox proportional risk models assessed the association between the TyG index, TyG-BMI and SCA risk. Additionally, Accelerated Failure Time (AFT) models were employed to investigate the timing of SCA onset. The impact of dynamic increases in TyG index and TyG-BMI levels on SCA risk was examined using restricted cubic spline. Results: Over a median follow-up period of 165.4 months (interquartile range 156.5–174 months), 1,622 cases of SCA were recorded. Multivariate Cox regression analysis revealed a 9% increase in SCA risk per standard deviation increase in TyG index (adjusted hazard ratio (aHR) = 1.09, 95% confidence interval (CI) 1.04–1.15) and an 14% increase per standard deviation increase in TyG-BMI (aHR 1.14, 95% CI 1.09–1.2). AFT models indicated earlier median times to SCA occurrence with increasing quintiles of TyG index and TyG-BMI compared to the lowest quintile (P for trend < 0.05). SCA risk was linearly (P = 0.54) and non-linearly (P = 0.007) correlated with gradual increases in TyG index and TyG-BMI levels, respectively. Sex-stratified analyses showed stronger associations in women. Conclusions: Higher TyG index and TyG-BMI levels are associated with an increased SCA risk and earlier onset, particularly in women.

Background: The association between the triglyceride-glucose (TyG) index and its combination with obesity indictors in aortic aneurysm and dissection (AAD) remains unclear. We aimed to investigate the association between TyG and TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), TyG-waist height ratio (TyG-WHtR) and AAD risk.Methods: This study included 387,483 baseline participants from the UK Biobank with complete data on TyG, TyG-BMI, TyG-WC and TyG-WHtR. Cox proportional hazard models evaluated the relationship between these four indicators and the risk of AAD occurrence. Restricted cubic spline (RCS) examined the non-linear relationship between these indicators and AAD risk, while receiver operating characteristic (ROC) curves assessed the predictive value of these four indicators for AAD risk.Results: Over a median follow-up of 13.7 years, 3,041 AAD events were recorded. Multivariate Cox regression analysis indicated that for each standard deviation increase, the risk of AAD occurrence increased by 33% (HR: 1.33, 95%CI: 1.29–1.38), 25% (HR: 1.25, 95%CI: 1.21–1.29), 61% (HR: 1.61, 95%CI: 1.56–1.66) and 44% (HR: 1.44, 95%CI: 1.39–1.49) for TyG, TyG-BMI, TyG-WC and TyG-WHtR, respectively. RCS demonstrated a linear relationship between these indicators and AAD risk, with TyG-WC demonstrating the best performance in predicting AAD occurrence based on ROC curves.Conclusion: The present study, based on a large prospective cohort design, showed that higher TyG index and its combination with obesity indices were significantly associated with the risk of AAD. Moreover, AFT models further showed that elevation of these indicators significantly advanced the onset of AAD. In addition, RCS analyses demonstrated a linear association between these indicators and the risk of AAD, and the TyG-WC showed higher predictive ability for AAD. These findings emphasize the potential application of the TyG index and its combination with obesity indicators in the early identification of AAD.