Atherogenic index of plasma (AIP): a novel predictive indicator for the coronary artery disease in postmenopausal women

• Main Authors: Ting-Ting Wu, Ying Gao, Ying-Ying Zheng, Yi-Tong Ma, Xiang Xie
• Format: Article
• Language: English
• Published: BMC 2018-08-01
• Series: Lipids in Health and Disease
• Subjects: Atherogenic index of plasma; Coronary artery disease; Postmenopausal women; Lipids
• Online Access: http://link.springer.com/article/10.1186/s12944-018-0828-z

Abstract Background Dyslipidemia is one of the most important factors for coronary artery disease (CAD). Atherogenic index of plasma (AIP) is a novel indicator involved in dyslipidemia. However, the relation between AIP and CAD in postmenopausal women remains unclear. We hypotheses that AIP is a strong predictive indicator of CAD in postmenopausal women. Methods A propensity score matching case–control study including 348 postmenopausal CAD cases and 348 controls was conducted in the present study. Results Compared with controls, CAD patients had higher levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (APOB), but lower high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A-1 (APOA-1). The values of nontraditional lipid profiles, including non-HDL-C, TC/HDL-C, LDL-C/HDL-C, non-HDL-C/HDL-C (atherogenic index, AI), TC∗TG∗LDL/HDL-C (lipoprotein combine index, LCI), log(TG/HDL-C) (atherogenic index of plasma, AIP) and APOB/APOA-1 were all significantly higher in the CAD patients. The results of Pearson correlation analyses showed AIP was positively and significantly correlated with TC (r = 0.092, P < 0.001), TG (r = 0.775, P = 0.015), APOB (r = 0.140, P < 0.001), non-HDL-C (r = 0.295, P < 0.001), TC/HDL-C (r = 0.626, P < 0.001), LDL-C/HDL-C (r = 0.469, P < 0.001), AI (r = 0.626, P < 0.001), LCI (r = 0.665, P < 0.001), APOB/APOA-1(r = 0.290, P < 0.001) and was negatively correlated with APOA-1 (r = − 0.278, P < 0.001) and HDL-C (r = − 0.665, P < 0.001). In the multivariate logistic regression analysis, AIP was an independent predictor of CAD. After adjusting for the traditional clinical prognostic factors including diabetes and hypertension, we found AIP could be an independent risk factor for CAD (odds ratio [OR], 3.290; 95% confidence interval [CI], 1.842–5.877, P < 0.001). After adjusting for multiple clinical factors include diabetes, hypertension, smoking, heart ratio, fasting blood glucose, we found AIP also could a powerful risk factor, OR = 3.619, 95%CI (2.003–6.538), P < 0.001. Conclusion The present study indicated that AIP might be a strong marker for predicting the risk of CAD in postmenopausal women.