Objective: evaluate how much age and blood pressure (BP) explains carotid-femoral pulse wave velocity (cf-PWV), estimated PWV by Mobil-o-Graph, and an equation derived from the Reference Values for Arterial Stiffness Collaboration. Design and method: We included individuals with at least one risk factor, elevated BP (> 139 or 89 mmHg), previous hypertension, dyslipidemia, diabetes, smoking, body obesity (BMI > 29.9 kg/m2), abdominal waist risk (waist circumference male > 102 cm in female > 88 cm). All individuals have taken three accurate BP (OBP) measurements using a Microlife BP A200 AFIB, and three sequential measurements of cf-PWV using a Complior Analyze device. We calculated the average from them. Also, they record 24 hours of brachial pulse wave velocity (ba-PWV) and ambulatory blood pressure monitoring using the Mobil-O-Graph device. Also, we calculated PWV by utilizing age and mean OBP (MBP) from Eq. (1) derived by the Reference Values for Arterial Stiffness Collaboration. We used five multilevel regression models to determine how much cf-PWV, ba-PWV, and e-PWV depend on age and BP. We used the Forkman test to compare the coefficient of determination (R 2 ). Results: Table 1 shows the main clinical characteristics of the sample. Table 2 demonstrates the results of R 2 for cf-PWV, ba-PWV and e-PWV. All PWV is significantly determined by age than BP; p < 0.001. Age determines 88.4% of ba-PWV, 72.8% of e-PWV, and 21.9% of cf-PWV; p < 0.001. There is no difference in R 2 for model 1 between ba-PWV and e-PWV; p = 0.14. Likely, in model 4, there are no differences for cf_PWV and e-PWV comparisons, p = 1.0. Age and BP determined 93.6% of ba-PWV and 94% of e-PWV; p = 0.97 even though they explain only 21.9% of cf-PWV, p < 0.001 for comparisons with e-PWV and ba-PWV. Conclusions: Age and BP explain equally almost the overall variance of e-PWV and ba-PWV. However, cf-PWV is significantly less dependent on age and BP than them.
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Silva et al. (2024) studied this question.
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