Multiple non-invasive peripheral vascular function parameters with obesity and cardiometabolic risk indicators in school-aged children

Abstract

Background The Peripheral Arterial Tonometry (PAT) technique measured by Endo-PAT™, is recently introduced for peripheral vascular assessment in youth, primarily benefits from its easy and non-invasive operation. However, the value of Endo-PAT as early indicator of obesity-related cardiometabolic risk factors remains unclear, with few studies focusing solely on Reactive Hyperemia Index (RHI). A wider coverage of Endo-PAT algorithms is recommended to be applied simultaneously in youth. We evaluated the value of multiple Endo-PAT parameters on obesity and cardiometabolic risk indication in school-aged children, in comparison with another non-invasive Brachial-ankle Pulse Wave Velocity (BaPWV) method. Methods This cross-sectional sample included 545 youth (80 with overweight and 73 with obesity) aged 7–17 years. RHI, Framingham-Reactive Hyperemia Index (F-RHI), peak response and Augmentation Index normalized to Heart Rate 75 bpm (AIx75) were measured by Endo-PAT™ 2000 device. Spearman correlations of abovementioned Endo-PAT parameters and BaPWV, with adiposity (weight, waist circumference, BMI, body fat mass) and cardiometabolic indicators (glycemic response, blood pressure, lipid profiles) were calculated with non-linear adjustment on age, height, gender and baseline pulse-wave amplitude (PWA) using fractional polynomials. Analysis was repeated in students with obesity only [median BMI z score: 3.0 (2.5,3.5)] for sensitivity analysis. Results The correlations of Endo-PAT parameters with adiposity measures and cardiometabolic indicators were overall mixed and weak (DBP: r ranged from − 0.20 to − 0.13, others: |r| < 0.1) after adjustment. Except that body fat mass (AIx75: r = 0.52 p < 0.01) and triglyceride level (RHI: r = − 0.32 p < 0.01, F-RHI: r = − 0.21 p > 0.05) was moderately reversed in students with obesity. In contrast, BaPWV showed consistently moderate correlations (|r| ranged from 0.123 to 0.322, p < 0.05) with almost all adiposity measures and cardiometabolic indicators regardless of obesity status. Conclusion Contrary to previous suggestion, various Endo-PAT parameters performed similarly weak for early cardiometabolic risk indication in school-aged children, and less preferable than that by another non-invasive BaPWV method. Despite further investigation is needed to improve certainty of relevant research evidence, innovative technology and algorithms taking into account specifics of young population are worthy of consideration.

Body Mass Index and Non-invasive Cardiovascular Parameters

“…Our findings indicate that maintaining a healthy body weight, especially reducing BMI to be in the normal range, would be beneficial to reduce cardiovascular risk. Our findings were consistent with prior limited studies 10,11 . Several potential mechanisms might be involved in the role of obesity in the above cardiovascular problems.…”

“…AIx75 was positively correlated with body fat mass ( r = 0.154, p < 0.05), but negatively correlated with BMI ( r = -0.209, p < 0.05) in school-aged children, with stronger correlations in students with obesity ( r = 0.573 and r = -0.410, respectively) 10 . Higher arterial stiffness augments systolic pressure and consequently AIx which represents the afterload inflicting the ventricles.…”

“…AIx75 was positively correlated with body fat mass (r = 0.154, p < 0.05), but negatively correlated with BMI (r = -0.209, p < 0.05) in school-aged children, with stronger correlations in students with obesity (r = 0.573 and r = -0.410, respectively) 10 .…”

“…Increase of the arterial stiffness is associated with increase of the propagation speed of the pulse wave in the arteries [7][8][9] . PWV was positively correlated with BMI in school-aged children (r = 0.237, p < 0.05) 10 and adults (r = 0.206, p < 0.05) 11 . Carotid-femoral PWV (cfPWV), calculated as the distance traveled by the pulse wave from carotid to femoral artery divided by the transient time, it is a strong independent predictor of CVD risk in both general and patient populations [7][8][9] .…”