Cardiorespiratory fitness but not physical activity are associated with pulse wave velocity and arterial stiffness in the general population

Abstract

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): BMBF Background Higher cardiorespiratory fitness (CRF) and physical activity (PA) are associated with lower cardiovascular morbidity and all-cause mortality. Pulse wave velocity (PWV) and augmentation index (AIx) are vascular parameters associated with aging and end-organ damage and provide reliable information about arterial stiffness. Therefore, PWV and AIx could represent attractive parameters for cardiovascular risk stratification. Purpose To improve our understanding of the relationship between CRF/PA and PWV and arterial stiffness, we associated CRF and PA with central and peripheral PWVs and AIx as outcomes using multivariable regression analysis using data from the population-based Study of Health in Pomerania (SHIP Trend 1). Methods CRF was assessed using cardiopulmonary exercise testing (CPET) on a bicycle ergometer. CRF was defined as peak oxygen uptake (VO2peak), VO2peak per kg fat free mass (VO2peak_ffm) and metabolic equivalent tasks (METs). PA was measured using the Baecke questionnaire. Aortic PWV (aoPWV), carotid-femoral PWV (cfPWV) and brachial-ankle PWV (baPWV) in m/s were determined non-invasively using the Vascular Explorer. Aortic AIx (aoAIx), aortic AIx at a heart rate of 75 bpm (aoAIx@75) and brachial-ankle AIx (brAIx) were measured using the same device. We used linear regression models adjusted for age, sex, smoking status, mean arterial pressure, antihypertensive medication, diabetic medication, HbA1c, fat mass, fat-free-mass and height. Fat-free mass was not included when VO2peak_ffm was the exposure. Fat-free mass and fat mass were not used in models with METs. Results We analysed data of 1,677 individuals which included 840 men (median age 56 years; inter-quartile range [IQR] 47 to 65) and 837 women (median age 54 years; IQR 46 to 65). A one l/min greater VO2peak was related to lower aoPWV (β - 0.22; 95% confidence interval (CI) -0.37 to -0.06, p < 0.01), cfPWV (β - 0.32; 95%CI -0.55 to -0.09; p < 0.01), baPWV (β -0.02; 95%CI -0.03 to 0.00, p < 0.05) and brAIx (β -3.49; 95%CI -6.95 to -0.03, p < 0.01). VO2peak was not related to aoAIx and aoAIx@75. VO2peak_ffm was associated with lower aoPWV (β -0.01; 95%CI -0.02 to -0.00, p < 0.05) and cfPWV (β -0.02; 95%CI -0.03 to -0.00, p < 0.05). VO2peak_ffm was not associated with baPWV, aoAIx, aoAIx@75 or brAIx. METs were positively associated with aoAIx@75 (β 0.30; 95%CI 0.02 to 0.59, p < 0.01). Sport and work related PA were not related to PWV or AIx. Sensitivity analysis with further adjustment for heart rate did not significantly change the results. Conclusions We found an association between CRF and central as well as peripheral PWV and AIx values in the adult general population. Interestingly, body composition had an impact on the relationship between CRF and peripheral but not central parameters. Further, PA was not related to these vascular markers which highlights the important difference between CRF and PA.