Atherogenic index of plasma is a novel and better biomarker associated with obesity: a population-based cross-sectional study in China

被引:125
|
作者
Zhu, Xiaowei [1 ,2 ]
Yu, Lugang [3 ]
Zhou, Hui [3 ]
Ma, Qinhua [4 ]
Zhou, Xiaohua [4 ]
Lei, Ting [3 ]
Hu, Jiarong [4 ]
Xu, Wenxin [4 ]
Yi, Nengjun [5 ]
Lei, Shufeng [1 ,2 ]
机构
[1] Soochow Univ, Sch Publ Hlth, Med Coll, Ctr Genet Epidemiol & Genom, Suzhou 215123, Jiangsu, Peoples R China
[2] Soochow Univ, Sch Publ Hlth, Med Coll, Jiangsu Key Lab Prevent & Translat Med Geriatr Di, Suzhou 215123, Jiangsu, Peoples R China
[3] Ctr Dis Control & Prevent Suzhou Ind Pk, Suzhou 215021, Jiangsu, Peoples R China
[4] 3 Peoples Hosp Xiang Cheng Dist, Suzhou 215134, Jiangsu, Peoples R China
[5] Univ Alabama Birmingham, Dept Biostat, Birmingham, AL 35294 USA
关键词
Obesity; Atherogenic index of plasma; Blood lipid components; ATHEROSCLEROSIS; CHILDREN; RISK;
D O I
10.1186/s12944-018-0686-8
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Background: Atherogenic index of plasma (AIP) has been reported to be associated with cardiovascular diseases. However no study has yet systematically evaluated the association between AIP and obesity and its advantage in obesity prediction compared with conventional lipid components. Methods: A total of 6465 participants aged over 30 years were included in this study. Blood lipid components including triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were measured, and AIP was calculated as log(10)(TG/HDL-C). Pearson correlation analyses, multivariable logistic analyses and predictive analyses were used to evaluate the association and discrimination ability between AIP, four conventional lipid profiles and obesity. Results: Subjects in the higher quartiles of AIP all had a significantly increased risk of obesity compared with those in the lowest quartile (P for trend< 0.01). AIP showed a stronger association with obesity than the conventional lipid components as the pearson coefficient reached up to 0.372 and the adjusted odds ratio was 5.55. Using AIP rather than HDL-C and TG significantly improved risk prediction for obesity (AUC improvement = 0.011, P = 0.011; Continuous net reclassification index = 29.55%, P < 0.01; Category net reclassification index = 6.06%; Integrated discrimination improvement = 0.68%, P < 0.01). Conclusions: Higher AIP level was positively and strongly associated with obesity. AIP is a novel and better biomarker associated with obesity. Controlling the AIP level would be more helpful for the prevention of obesity.
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页数:6
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