Background: It has been suggested that the baseline triglyceride-glucose (TyG) index, a simple surrogate measure for insulin resistance, is significantly associated with the occurrence of stroke. Nevertheless, the impact of longitudinal patterns of TyG on the stroke risk in hypertensive patients is still unknown. Hence, this study aimed to investigate the association between TyG index trajectory and stroke risk among hypertensive patients.Methods: This prospective study included 19,924 hypertensive patients from the Kailuan Study who underwent three waves survey and were free of myocardial infarction, cancer and stroke before or during 2010. The TyG index was calculated as ln [fasting triglyceride (mg/dL) × fasting plasma glucose (mg/dL)/2], and latent mixed modelling was used to identify the trajectory of TyG during the exposure period (2006–2010). Furthermore, the Cox proportional hazard models were applied to estimate the hazard ratio (HR) and 95% confidence interval (CI) for incident stroke of different trajectory groups.Results: Five distinct TyG trajectory were identified during 2006–2010: low-stable (n = 2483; range, 8.03–8.06), moderate low-stable (n = 9666; range, 8.58–8.57), moderate high-stable (n = 5759; range, 9.16–9.09), elevated-stable (n = 1741; range, 9.79–9.75), and elevated-increasing (n = 275; range, 10.38–10.81). During the median follow-up of 9.97 years, 1,519 cases of incident stroke were identified, including 1,351 with ischemic stroke and 215 with hemorrhage stroke. After adjusting for confounding variables, the HR and 95% CI of stroke were 2.21 (1.49,3.28) for the elevated-increasing group, 1.43 (1.13,1.83) for the elevated-stable group, 1.35 (1.10,1.64) for the moderate high-stable group, 1.26 (1.06,1.52) for the moderate low-stable group, respectively, when compare with the low-stable group. Similar results were observed in ischemic stroke, but a significant association was not found between TyG trajectory and risk of hemorrhage stroke.Conclusion: A long-term elevated TyG index in hypertensive patients is associated with an increased risk of stroke, especially ischemic stroke. This finding implies that regular monitoring of TyG index may assist in identifying individuals at a higher risk of stroke among patients with hypertension.

Background: Studies have demonstrated that remnant cholesterol is correlated with the risk of ischemic stroke. However, it is unknown whether visit-to-visit variability in remnant cholesterol concentration affects ischemic stroke. We sought to examine the role of remnant cholesterol variability in the subsequent development of ischemic stroke in the general population. Methods: We performed a post hoc analysis including eligible participants from the Kailuan Study cohort who underwent 3 health examinations and were free of atrial fibrillation, myocardial infarction, stroke, cancer, or known lipid-medication use from 2006 to 2010. Participants were followed up until the end of 2017. Variability was quantified as variability independent of the mean, average real variability, and SD. Multivariate analysis was performed using the Fine and Gray competing risk model to estimate subhazard ratios assuming death as a competing risk. Results: The final study cohort comprised 38 556 participants. After a median follow-up of 7.0 years, 1058 individuals were newly diagnosed with ischemic stroke. After adjusting for age (time scale), sex, smoking status, alcohol consumption, physical activity, hypertension, diabetes, family history of cardiovascular disease, body mass index, estimated glomerular filtration rate, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, and mean remnant cholesterol, the highest quartile (quartile 4) of variability independent of the mean of remnant cholesterol was associated with an increased ischemic stroke risk compared with the lowest quartile (quartile 1), (subhazard ratio, 1.27 [95% CI, 1.06–1.53]). For each 1-SD increase in variability independent of the mean of remnant cholesterol, the risk increased by 9% (subhazard ratio, 1.09 [95% CI, 1.03–1.16]). The association was also significant using average real variability and SD as indices of variability. Conclusions: Greater remnant cholesterol variability was associated with a higher risk of ischemic stroke in the general population.

Background: Atherogenic index of plasma (AIP) has been demonstrated as a surrogate marker for ischemic stroke, but there is limited evidence for the effect of long-term elevation of AIP on ischemic stroke. Therefore, we aimed to characterize the relationship between cumulative exposure to AIP and the risk of ischemic stroke. Methods: A total of 54,123 participants in the Kailuan Study who attended consecutive health examinations in 2006, 2008, and 2010 and had no history of ischemic stroke or cancer were included. The time-weighted cumulative AIP (cumAIP) was calculated as a weighted sum of the mean AIP values for each time interval and then normalized to the total duration of exposure (2006–2010). Participants were divided into four groups according to quartile of cumAIP: the Q1 group, ≤−0.50; Q2 group, − 0.50 to − 0.12; Q3 group, − 0.12 to 0.28; and Q4 group, ≥ 0.28. Cox proportional hazard models were used to evaluate the relationship between cumAIP and ischemic stroke by calculating hazard ratios (HRs) and 95% confidence intervals (95% CIs). Results: After a median follow-up of 11.03 years, a total of 2,742 new ischemic stroke events occurred. The risk of ischemic stroke increased with increasing quartile of cumAIP. After adjustment for potential confounders, Cox regression models showed that participants in the Q2, Q3, and Q4 groups had significantly higher risks of ischemic stroke than those in the Q1 group. The HRs (95% CIs) for ischemic stroke in the Q2, Q3, and Q4 groups were 1.17 (1.03, 1.32), 1.33 (1.18, 1.50), and 1.45 (1.28, 1.64), respectively. The longer duration of high AIP exposure was significantly associated with increased ischemic stroke risk. Conclusions: High cumulative AIP is associated with a higher risk of ischemic stroke, which implies that the long-term monitoring and maintenance of an appropriate AIP may help prevent such events.

Background: A single measurement of the triglyceride-glucose (TyG) index, a simple and reliable surrogate marker of insulin resistance, is associated with ischemic stroke. However, evidence for an effect of a long-term elevation in TyG index on ischemic stroke is limited. Therefore, we evaluated the relationship between cumulative TyG index exposure and the risk of ischemic stroke. Methods: A total of 54,098 participants in the Kailuan study who had not experienced ischemic stroke underwent three measurements of fasting blood glucose and triglycerides during 2006–2007, 2008–2009, and 2010–2011. Cumulative exposure to TyG index was calculated as the weighted sum of the mean TyG index value for each time interval (value × time). Participants were placed into four groups according to the quartile of the weighted mean: Q1 group, < 32.01; Q2 group, 32.01–34.45; Q3 group, 34.45–37.47; and Q4 group, ≥ 37.47. Cox proportional hazard models were used to assess the relationships of the cumulative TyG index with incident ischemic stroke by calculating hazard ratios (HRs) and 95% confidence intervals (95% CIs). Results: There were 2083 incident ischemic stroke events over the 9 years of follow-up. The risk of ischemic stroke increased with the quartile of cumulative TyG index. After adjustment for multiple potential confounders, participants in groups Q4, Q3, and Q2 had significantly higher risks of ischemic stroke, with HRs (95% CIs) of 1.30 (1.12–1.52), 1.26 (1.09–1.45), and 1.09 (0.94–1.27), respectively (P_trend < 0.05), compared with the Q1 group. The longer duration of high TyG index exposure was significantly associated with increased ischemic stroke. Conclusions: High cumulative TyG index is associated with a higher risk of ischemic stroke. This finding implies that monitoring and the maintenance of an appropriate TyG index may be useful for the prevention of ischemic stroke.

Background: Concurrent atherogenic dyslipidemia and elevated inflammation are commonly observed in overt hyperglycemia and have long been proposed to contribute to diabetogenesis. However, the temporal relationship between them and the effect of their cumulative co-exposure on future incident type 2 diabetes (T2D) remains unclear. Methods: Longitudinal analysis of data on 52,224 participants from a real-world, prospective cohort study (Kailuan Study) was performed to address the temporal relationship between high-sensitivity C-reactive protein (hsCRP) and the atherogenic index of plasma (AIP, calculated as triglyceride/high-density lipoprotein) in an approximately 4-year exposure period (2006/2007 to 2010/2011). After excluding 8824 participants with known diabetes, 43,360 nondiabetic participants were included for further analysis of the T2D outcome. Cox regression models were used to examine the adjusted hazard ratios (aHRs) upon the cumulative hsCRP (CumCRP) and AIP (CumAIP) in the exposure period. Results: In temporal analysis, the adjusted standardized correlation coefficient (β1) of hsCRP_2006/2007 and AIP_2010/2011 was 0.0740 (95% CI, 0.0659 to 0.0820; P < 0.001), whereas the standardized correlation coefficient (β2) of AIP_2006/2007 and hsCRP_2010/2011 was − 0.0293 (95% CI, − 0.0385 to − 0.0201; P < 0.001), which was significantly less than β1 (P < 0.001). During a median follow-up of 7.9 years, 5,118 T2D cases occurred. Isolated exposure to CumAIP or CumCRP was dose-dependently associated with T2D risks, independent of traditional risk factors. Significant interactions were observed between the median CumAIP (− 0.0701) and CumCRP thresholds (1, 3 mg/L) (P = 0.0308). Compared to CumAIP < − 0.0701 and CumCRP < 1 mg/L, those in the same CumAIP stratum but with increasing CumCRP levels had an approximately 1.5-fold higher T2D risk; those in higher CumAIP stratum had significantly higher aHRs (95% CIs): 1.64 (1.45–1.86), 1.87 (1.68–2.09), and 2.04 (1.81–2.30), respectively, in the CumCRP < 1, 1 ≤ CumCRP < 3, CumCRP ≥ 3 mg/L strata. Additionally, the T2D risks in the co-exposure were more prominent in nonhypertensive, nondyslipidemic, nonprediabetic, or female participants. Conclusions: These findings suggest a stronger association between elevated hsCRP and future AIP changes than vice versa and highlight the urgent need for combined assessment and management of chronic inflammation and atherogenic dyslipidemia in primary prevention, particularly for those with subclinical risks of T2D.

Although nonalcoholic fatty liver disease (NAFLD) is commonly seen in metabolic abnormalities patients, NAFLD is also occurred in the non-obese individuals. The ratio of triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) is considered as a predictive factor of NAFLD. However, it is still difficult to confirm the correlation of TG/HDL-C ratio with NAFLD among non-obese Chinese people with normal blood lipid levels. In our study, it is aimed to analyze the correlation of TG/HDL-C ratio with NAFLD among non-obese Chinese population without dyslipidemia. In the retrospective cohort study, 9838 non-obese subjects who were free of NAFLD were enrolled. NAFLD was diagnosed by ultrasonography. During the median follow-up period of 2.9 years, cumulative incidence of NAFLD in non-obesity individuals was 8.69% among the overall population; meanwhile, its incidence was gradually enhanced across the quartiles of TG/HDL-C ratio (0.61, 1.28, 2.55 and 4.25% respectively). Then the multivariate factors were adjusted. The multivariate cox regression analysis results showed that the hazard ratio of NAFLD in higher quartiles (Q2-Q4) was 2.10 (1.33–3.32), 3.11 (2.03–4.75) and 3.40 (2.24–5.17), respectively. Besides, the area under receiver operator characteristic curve (AUC) of TG/HDL-C ratio in the male was 0.70 (0.68–0.72) and 0.72 (0.70–0.75) in the female. The final values were dramatically larger than the other lipid index. There is an independent relationship between TG/HDL-C and NAFLD among non-obese Chinese population without dyslipidemia, and TG/HDL-C may be used as a better predictor for NAFLD.