title: Fitness Is Independently Associated with Central Hemodynamics in Metabolic Syndrome.
abstract: Fit individuals with metabolic syndrome (MetS) have lower mortality risk compared with less fit counterparts, despite the presence of obesity as a component of the syndrome. To understand the importance of fitness in treating this condition, we examined the association of fitness and fatness with central hemodynamic indices that are known independent predictors of cardiovascular events.
  
  
  
  Sixty-eight individuals with MetS participated in this cross-sectional study. Central hemodynamics is calculated from radial applanation tonometry and comprised aortic reservoir pressure, backward pressure wave (Pb), reflection magnitude (RM), and augmentation index at 75 bpm (AIx75). Cardiorespiratory fitness (CRF) and body fat percentage (BF%) were determined via indirect calorimetry during maximal exercise testing and dual-energy x-ray absorptiometry, respectively.
  
  
  
  CRF was inversely associated with aortic reservoir pressure (r = -0.29, P = 0.02), Pb (r = -0.42, P < 0.001), RM (r = -0.48, P < 0.001), and AIx75 (r = -0.65, P < 0.001). BF% was also correlated with AIx75 (r = 0.37, P < 0.05) and RM (r = 0.36, P < 0.005) but at a weaker association compared with CRF. Multiple regression analysis revealed CRF as a predictor of aortic reservoir pressure (β = -0.52, P = <0.01), Pb (β = -0.41, P < 0.03), and AIx75 (β = -0.45, P = 0.01), independent of BF% and other confounding factors.
  
  
  
  CRF predicts central hemodynamics independent of BF% and other confounding factors. This suggests that CRF improvement may be a higher priority when compared with fat loss for lowering the risk of cardiovascular mortality in MetS individuals.
authors.affiliation: 1Centre for Research on Exercise, Physical Activity and Health, School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, AUSTRALIA; 2Institute of Biomedical Technologies, School of Engineering, Auckland University of Technology, Auckland, NEW ZEALAND; 3Recreation, Exercise, and Sport Science Department, Western State Colorado University, Gunnison, CO; 4The Institute of Sport Sciences University of Lausanne, University of Lausanne, Lausanne, SWITZERLAND; 5Department of Physiology, Faculty of Biology and Medicine, Lausanne University, Lausanne, SWITZERLAND; and 6Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, AUSTRALIA.
authors.forename: Joyce S
authors.initials: JS
authors.lastname: Ramos
authors.forename: Maximiano V
authors.initials: MV
authors.lastname: Ramos
authors.forename: Lance C
authors.initials: LC
authors.lastname: Dalleck
authors.forename: Fabio
authors.initials: F
authors.lastname: Borrani
authors.forename: Kaitlyn B
authors.initials: KB
authors.lastname: Walker
authors.forename: Robert G
authors.initials: RG
authors.lastname: Fassett
authors.forename: James E
authors.initials: JE
authors.lastname: Sharman
authors.forename: Jeff S
authors.initials: JS
authors.lastname: Coombes
mesh_terms: D015502:Absorptiometry, Photon; D050154:Adiposity; D000328:Adult; D000368:Aged; D000072599:Cardiorespiratory Fitness; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000503:physiopathology; D005080:Exercise Test; D005260:Female; D006439:Hemodynamics; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000503:physiopathology*; D008875:Middle Aged; D016032:Randomized Controlled Trials as Topic