Ideal cardiovascular health metrics on the prevalence of asymptomatic intracranial artery stenosis: a cross-sectional study.

Intracranial Artery Stenosis (ICAS) is one of the most common causes of ischemic stroke in Asia. Previous studies have shown the number of ideal cardiovascular health (CVH) metrics was associated with lower risk of stroke. This study aimed to investigate the relationship between ideal CVH metrics and prevalence of ICAS. A random sample of 5,412 participants (selected from Kailuan Study as a reference population) aged 40 years or older (40.10% women), free of stroke, transient ischemic attack, and coronary disease, were enrolled in the Asymptomatic Polyvascular Abnormalities Community study from 2010 to 2011. We collected information on the seven CVH metrics (including smoking, body mass index, dietary intake, physical activity, blood pressure, total cholesterol and fasting blood glucose); and assessed ICAS by transcranial Doppler. The relationship between the ideal CVH metrics and prevalence of ICAS was analyzed using the multivariate logistic regression. After adjusting for age, sex, and other potential confounders, the adjusted odds ratios(95% confidence interval) for ICAS were 0.76(0.58-0.99), 0.55(0.43-0.72), 0.49(0.37-0.65), 0.43(0.31-0.61), and 0.36(0.22-0.62), respectively, for those having 2, 3, 4, 5, and 6-7 ideal CVH metrics compared with those having 0-1 ideal metric(p-trend<0.0001). Similar inverse associations were observed in different age and gender groups (all p-trends<0.05). We found a clear gradient relationship between the number of ideal CVH metrics and lower prevalence of ICAS in a Chinese population, which supports the importance of ideal health behaviors and factors in the prevention of ICAS.

Citation

Qian Zhang, Shufeng Zhang, Chunxue Wang, Xiang Gao, Yong Zhou, Heng Zhou, Anxin Wang, Jianwei Wu, Liheng Bian, Shouling Wu, Xingquan Zhao. Ideal cardiovascular health metrics on the prevalence of asymptomatic intracranial artery stenosis: a cross-sectional study. PloS one. 2013;8(3):e58923

Mesh Tags

PMID: 23554958

search → result