Inverse correlation between serum irisin and cardiovascular risk factors among Chinese overweight/obese population

Autor: Yi Li, Kun Tang, Shujing Xu, Ying Hu, Qiao Zhang, Lixin Shi, Xi He, Nianchun Peng, Zhengyi Chen, Ruoyi Liu, Miao Zhang
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: BMC Cardiovascular Disorders, Vol 21, Iss 1, Pp 1-8 (2021)
BMC Cardiovascular Disorders
ISSN: 1471-2261
Popis: Background Irisin is a novel myokine associated with obesity, which is a traditional cardiovascular risk factor (CVRF). The present study aimed to investigate the association between serum irisin and a single CVRF as well as the clustering of CVRFs among Chinese overweight/obese population. Methods A total of 98 overweight and 93 obese subjects without clinical treatments were enrolled in this study. Subjects were then divided into two groups, based on the serum irisin level: a low irisin group (1.10–13.44 ng/ml) and a high irisin group (13.49–29.9 ng/ml). The clustering of CVRFs, smoking, diabetes mellitus, dyslipidemia and hypertension, was classified as 0, 1, 2 and ≥ 3 CVRFs. The demographic and baseline clinical characteristics of all participants were collected and serum irisin was measured. Results The high serum irisin group had significantly higher high-density lipoprotein cholesterol but lower fasting plasma glucose than the low serum irisin group. Additionally, the high serum irisin group had a significantly lower prevalence of smoking, diabetes mellitus and dyslipidemia than the low serum irisin group. Increased serum irisin was significantly associated with a reduced risk of smoking and dyslipidemia in both the unadjusted and adjusted models. Furthermore, high serum irisin significantly reduced the risk of the prevalence of 1, 2 and ≥ 3 CVRFs. Conclusions among the Chinese overweight/obese populations, high serum irisin is negatively associated with smoking, dyslipidemia and the clustering of CVRFs. Thus, high serum irisin is potentially associated with a low risk of cardiovascular diseases in the Chinese overweight/obese population.
Databáze: OpenAIRE