Prediction of central Augmentation Index in healthy adults

BACKGROUND: Central Augmentation Index (AIx) is a surrogate marker of large artery stiffness that may provide valuable insight to cardiovascular health. The aim of this study was to evaluate the relationship between AIx and components of physical fitness. METHODS: One hundred eighty-five healthy men and women (aged 20-79 years) underwent non-invasive assessment of arterial wave reflection to determine AIx, which was corrected to a heart rate of 75 beats per minute (AI×75). Body composition was evaluated using dual energy X-ray absorptiometry (DXA) and aerobic capacity (VO<inf>2max</inf>) was derived from expired gas analysis during a symptom limited exercise test on a treadmill. RESULTS: A multiple linear regression revealed age and VO<inf>2max</inf> as significant predictors of AI×75 [AI×75=32.055 + (0.252×age) - (0.722×VO<inf>2max</inf>)]. Upon removal of VO<inf>2max</inf> from regression analysis, resting heart rate (RHR) and % body fat (BF%) were revealed to be significant predictors of AI×75: AI×75=-61.316 + (0.481×age) + (0.565×BF%) + (0.56×RHR). CONCLUSIONS: Our findings demonstrate that central Augmentation Index can be reliably predicted in healthy adults who undergo a maximal exercise or body composition assessment. These prediction equations may be applied in non-medical settings to assist in creating comprehensive health and fitness profiles for healthy clientele.