BACKGROUND AND AIMS: Atherogenic index of plasma (AIP), defined as the logarithm of triglycerides to high-density lipoprotein cholesterol (HDL-C) ratio, is a strong predictor of future cardiovascular disease. Our aim was to examine the association of AIP with haemodynamic variables in normotensive and never-treated hypertensive subjects in a cross-sectional study. METHODS: Supine haemodynamics in 615 subjects without antihypertensive and lipid-lowering medications were examined using whole-body impedance cardiography and radial pulse wave analysis. Linear regression analysis was applied to investigate the association of AIP with haemodynamic variables and age, sex, body mass index (BMI), smoking status, alcohol consumption, plasma C-reactive protein, electrolytes, uric acid, low density lipoprotein cholesterol (LDL-C), estimated glomerular filtration rate, and quantitative insulin sensitivity check index. RESULTS: The demographics and laboratory values of the study population were (mean ± 95% confidence interval): age 44.9 ± 1.0 years, BMI 26.8 ± 0.4 kg/m2, office blood pressure 140.6 ± 1.6/89.4 ± 1.0 mmHg, total cholesterol 5.2 ± 0.08, LDL-C 3.1 ± 0.08, triglycerides 1.2 ± 0.08, HDL-C 1.6 ± 0.04 mmol/l, and AIP -0.15 ± 0.02. Age (standardized coefficient Beta 0.508, p < .001) and aortic systolic blood pressure (Beta 0.239, p < .001) presented with the strongest associations with pulse wave velocity. However, AIP was also associated with pulse wave velocity (Beta 0.145, p < .001). AIP was not related with aortic or radial blood pressure, cardiac output, systemic vascular resistance, or augmentation index. CONCLUSIONS: AIP is directly and independently associated with arterial stiffness, a variable strongly related to cardiovascular risk. This supports more widespread use of AIP in standard clinical cardiovascular disease risk evaluation.
BACKGROUND AND AIMS: Atherogenic index of plasma (AIP), defined as the logarithm of triglycerides to high-density lipoprotein cholesterol (HDL-C) ratio, is a strong predictor of future cardiovascular disease. Our aim was to examine the association of AIP with haemodynamic variables in normotensive and never-treated hypertensive subjects in a cross-sectional study. METHODS: Supine haemodynamics in 615 subjects without antihypertensive and lipid-lowering medications were examined using whole-body impedance cardiography and radial pulse wave analysis. Linear regression analysis was applied to investigate the association of AIP with haemodynamic variables and age, sex, body mass index (BMI), smoking status, alcohol consumption, plasma C-reactive protein, electrolytes, uric acid, low density lipoprotein cholesterol (LDL-C), estimated glomerular filtration rate, and quantitative insulin sensitivity check index. RESULTS: The demographics and laboratory values of the study population were (mean ± 95% confidence interval): age 44.9 ± 1.0 years, BMI 26.8 ± 0.4 kg/m2, office blood pressure 140.6 ± 1.6/89.4 ± 1.0 mmHg, total cholesterol 5.2 ± 0.08, LDL-C 3.1 ± 0.08, triglycerides 1.2 ± 0.08, HDL-C 1.6 ± 0.04 mmol/l, and AIP -0.15 ± 0.02. Age (standardized coefficient Beta 0.508, p < .001) and aortic systolic blood pressure (Beta 0.239, p < .001) presented with the strongest associations with pulse wave velocity. However, AIP was also associated with pulse wave velocity (Beta 0.145, p < .001). AIP was not related with aortic or radial blood pressure, cardiac output, systemic vascular resistance, or augmentation index. CONCLUSIONS: AIP is directly and independently associated with arterial stiffness, a variable strongly related to cardiovascular risk. This supports more widespread use of AIP in standard clinical cardiovascular disease risk evaluation.
Authors: Waleska Reyes-Ferrada; Patricio Solis-Urra; Julio Plaza-Díaz; Kabir P Sadarangani; Gerson Luis de Moraes Ferrari; Fernando Rodríguez-Rodríguez; Carlos Cristi-Montero Journal: Nutrients Date: 2020-04-28 Impact factor: 5.717
Authors: Olesya A Puchenkova; Vladislav O Soldatov; Andrei E Belykh; OlgaYu Bushueva; Gennadii A Piavchenko; Artem A Venediktov; Nikolay K Shakhpazyan; Alexey V Deykin; Mikhail V Korokin; Mikhail V Pokrovskiy Journal: Biomark Insights Date: 2022-04-25
Authors: Monika Starzak; Agata Stanek; Grzegorz K Jakubiak; Armand Cholewka; Grzegorz Cieślar Journal: Int J Environ Res Public Health Date: 2022-08-19 Impact factor: 4.614