The association of blood lipid parameters variability with ischemic stroke in hypertensive patients

Association between PM2.5 and hypertension among the floating population in China: a cross-sectional study

Few studies have investigated the association between PM2.5 and hypertension among floating populations. We therefore examined the relationship using binary logistic regression. Each grade of increment in the annual average PM2.5 (grade one: ≤15 µg/m3; grade two: 15-25 µg/m3; grade three: 25-35 µg/m3 [Excluding 25]; grade four: ≥35 µg/m3) was associated with an increased risk of hypertension (odds ratio [OR] = 1.081, 95% confidence interval (CI): 1.034-1.129). Among the female floating population (OR = 1.114, 95% CI: 1.030-1.204), those with education level of primary school and below (OR = 1.140, 95% CI: 1.058-1.229), construction workers (OR = 1.228, 95% CI: 1.058-1.426), and those living in the eastern region of China (OR = 1.241, 95% CI: 1.145-1.346) were more vulnerable to PM2.5. These results indicate that PM2.5 is positively associated with hypertension in floating populations. Floating populations who are female, less educated, construction workers, and living in the eastern region of China are more vulnerable to the adverse impacts of PM2.5.

The Triglyceride/High-Density Lipoprotein Cholesterol (TG/HDL-C) Ratio as a Risk Marker for Metabolic Syndrome and Cardiovascular Disease

Atherosclerosis is an immunoinflammatory pathological procedure in which lipid plaques are formed in the vessel walls, partially or completely occluding the lumen, and is accountable for atherosclerotic cardiovascular disease (ASCVD). ACSVD consists of three components: coronary artery disease (CAD), peripheral vascular disease (PAD) and cerebrovascular disease (CCVD). A disturbed lipid metabolism and the subsequent dyslipidemia significantly contribute to the formation of plaques, with low-density lipoprotein cholesterol (LDL-C) being the main responsible factor. Nonetheless, even when LDL-C is well regulated, mainly with statin therapy, a residual risk for CVD still occurs, and it is attributable to the disturbances of other lipid components, namely triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C). Increased plasma TG and decreased HDL-C levels have been associated with metabolic syndrome (MetS) and CVD, and their ratio, TG/HDL-C, has been proposed as a novel biomarker for predicting the risk of both clinical entities. Under these terms, this review will present and discuss the current scientific and clinical data linking the TG/HDL-C ratio with the presence of MetS and CVD, including CAD, PAD and CCVD, in an effort to prove the value of the TG/HDL-C ratio as a valuable predictor for each aspect of CVD.

Mean versus variability of lipid measurements over 6 years and incident cardiovascular events: More than a decade follow-up

Background

Lipid variability (LV) has emerged as a contributor to the incidence of cardiovascular diseases (CVD), even after considering the effect of mean lipid levels. However, these associations have not been examined among people in the Middle East and North Africa (MENA) region. We aimed to investigate the association of 6-year mean lipid levels versus lipid variability with the risk of CVD among an Iranian population.

Methods

A total of 3,700 Iranian adults aged ≥ 30 years, with 3 lipid profile measurements, were followed up for incident CVD until March 2018. Lipid variability was measured as standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of mean (VIM). The effects of mean lipid levels and LV on CVD risk were assessed using multivariate Cox proportional hazard models.

Results

During a median 14.5-year follow-up, 349 cases of CVD were recorded. Each 1-SD increase in the mean levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), TC/high-density lipoprotein cholesterol (HDL-C), and non-HDL-C increased the risk of CVD by about 26-29%; for HDL-C, the risk was significantly lower by 12% (all p-values < 0.05); these associations resisted after adjustment for their different LV indices. Considering LV, each 1-SD increment in SD and ARV variability indices for TC and TC/HDL-C increased the risk of CVD by about 10%; however, these associations reached null after further adjustment for their mean values. The effect of TC/HDL-C variability (measured as SD) and mean lipid levels, except for LDL-C, on CVD risk was generally more pronounced in the non-elderly population.

Conclusion

Six-year mean lipid levels were associated with an increased future risk of incident CVD, whereas LV were not. Our findings highlight the importance of achieving normal lipid levels over time, but not necessarily consistent, for averting adverse clinical outcomes.

Lipid Variability and Risk of Cardiovascular Diseases and All-Cause Mortality: A Systematic Review and Meta-Analysis of Cohort Studies

No consensus has yet been reached on the associations of lipid variability (LV) with cardiovascular diseases (CVDs) and all-cause mortality. We aimed to quantify the associations of different types and metrics of LV with CVDs and all-cause mortality. PubMed, Medline, and Embase databases were searched for eligible cohort studies published until 14 December 2021. Lipids included total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). Metrics of variability included standard deviation (SD), coefficient of variation (CV), and variation independent of the mean (VIM). The primary outcomes were CVDs and all-cause mortality. Random-effects meta-analysis was used to generate a summary of the relative risks (SRRs). Sources of heterogeneity were explored by subgroup analysis and meta-regression. A total of 11 articles based on seven cohorts were included. Participants in the top quartile of TC variability had an increased risk of CVDs (vs. bottom quartile: TC-CV: SRR 1.29, 95% CI 1.15-1.45; TC-SD: 1.28, 1.15-1.43; TC-VIM: 1.26, 1.13-1.41, respectively) and all-cause mortality (vs. bottom quartile: TC-CV: 1.28, 1.15-1.42; TC-SD: 1.32, 1.22-1.44; TC-VIM: 1.32, 1.25-1.40, respectively). Participants in the top quartile of HDL-C variability had an increased risk of CVDs (vs. bottom quartile: HDL-C-CV: 1.11, 1.07-1.15; HDL-C-SD: 1.18, 1.02-1.38; HDL-C-VIM: 1.18, 1.09-1.27, respectively) and all-cause mortality (vs. bottom quartile: HDL-C-CV: 1.29, 1.27-1.31; HDL-C-SD: 1.24, 1.09-1.41; HDL-C-VIM: 1.25, 1.22-1.27, respectively). LDL-C variability was also associated with an increased risk of CVDs (for top vs. bottom quartile; LDL-C-SD: 1.09, 1.02-1.17; LDL-C-VIM: 1.16, 1.02-1.32, respectively) and all-cause mortality (for top vs. bottom quartile; LDL-C-CV: 1.19, 1.04-1.36; LDL-C-SD: 1.17, 1.09-1.26, respectively). The relationships of TG variability with the risk of CVDs and all-cause mortality were inconclusive across different metrics. The effects of SRR became stronger when analyses were restricted to studies that adjusted for lipid-lowering medication and unadjusted for mean lipid levels. These findings indicate that the measurement and surveillance of lipid variability might have important clinical implications for risk assessment of CVDs and all-cause mortality.

Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China

Fine particulate matter (PM_2.5) and respirable particulate matter (PM₁₀) are two major air pollutants with toxic effects on the cardiovascular system. Hypertension, as a chronic noncommunicable cardiovascular disease, is also a risk factor for several diseases. We applied generalized linear models with a quasi-Poisson link to assess the effect of air pollution exposure on the number of daily admissions for patients with hypertension. In addition, we established a two-pollutant model to evaluate PM_2.5 and PM₁₀ hazard effect stability by adjusting the other gaseous pollutants. Results showed that during the study period, 24 h mean concentrations of ambient PM_2.5 and PM₁₀ at 38.17 and 59.84 μg/m³, respectively, and a total of 2,611 hypertension hospital admissions were recorded. Air pollution concentrations significantly affected the number of hospitalizations for hypertension approximately 2 months after exposure. For each 10 μg/m³ increase in PM_2.5 and PM₁₀ in single-pollutant models, the number of hospitalizations for hypertension increased by 7.92% (95% CI: 5.48% to 10.42%) and 4.46% (95% CI: 2.86% to 5.65%), respectively, at the lag day with the strongest effect. NO₂, O₃, CO, and SO₂ had different significant effects on the number of hospitalizations over the same time period, and PM_2.5 and PM₁₀ still showed robust significant effects after adjustment of gas pollutants through a two-pollutant model. These findings may contribute to a better understanding of the health effects of ambient particulate matter.