title: Comparison of the effect of the metabolic syndrome and multiple traditional cardiovascular risk factors on vascular function.
abstract: OBJECTIVE
  To assess the effect of the metabolic syndrome (MetS) on endothelial function and compare these findings to those in individuals with a similar burden of traditional cardiovascular (CV) risk factors (≥ 3) without MetS.
  
  
  METHODS
  Both MetS and multiple CV risk factors were identified from 1103 individuals who underwent the evaluation of endothelial function at the Mayo Clinic, in Rochester, Minnesota, from July 1, 2000, through July 31, 2011. Endothelial function was measured using digital arterial tonometry by assessing reactive hyperemia-induced vasodilation in one arm and adjusting for changes in the contralateral arm (reactive hyperemia index [RHI]).
  
  
  RESULTS
  A total of 316 individuals with MetS and 210 with multiple risk factors were assessed. Endothelial dysfunction was more pronounced in the MetS group compared with the multiple risk factor group (mean ± SD natural logarithmic RHI, 0.61 ± 0.25 and 0.68 ± 0.28, respectively; P=.006). Leukocyte count (7.00 ± 1.89 × 10(9)/L vs 6.41 ± 1.76 × 10(9)/L, respectively; P=.001) and high-sensitivity C-reactive protein level (1.78 ± 1.53 mg/L vs 1.48 ± 1.42 mg/L, respectively; P=.01) were higher in the MetS group compared with the multiple risk factor group. After adjustment for covariates and 6 traditional CV risk factors in a multivariate regression model, MetS had a significant and independent influence on natural logarithmic RHI (β=-.11; P=.01).
  
  
  CONCLUSIONS
  The current study found that individuals with MetS have a higher degree of endothelial dysfunction and inflammation compared with individuals with multiple CV risk factors and may therefore have an increased CV risk beyond the contributions of multiple traditional risk factors.
authors.affiliation: Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN 55905, USA.
authors.forename: Jing
authors.initials: J
authors.lastname: Li
authors.forename: Andreas J
authors.initials: AJ
authors.lastname: Flammer
authors.forename: Ryan J
authors.initials: RJ
authors.lastname: Lennon
authors.forename: Rebecca E
authors.initials: RE
authors.lastname: Nelson
authors.forename: Rajiv
authors.initials: R
authors.lastname: Gulati
authors.forename: Paul A
authors.initials: PA
authors.lastname: Friedman
authors.forename: Randal J
authors.initials: RJ
authors.lastname: Thomas
authors.forename: Nicole P
authors.initials: NP
authors.lastname: Sandhu
authors.forename: Qi
authors.initials: Q
authors.lastname: Hua
authors.forename: Lilach O
authors.initials: LO
authors.lastname: Lerman
authors.forename: Amir
authors.initials: A
authors.lastname: Lerman
mesh_terms: D000328:Adult; D000368:Aged; D002318:Cardiovascular Diseases / Q000097:blood / Q000453:epidemiology*; D015897:Comorbidity; D004730:Endothelium, Vascular / Q000503:physiopathology*; D005260:Female; D006801:Humans; D007249:Inflammation / Q000097:blood / Q000453:epidemiology*; D018836:Inflammation Mediators / Q000097:blood; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000453:epidemiology*; D008875:Middle Aged; D015999:Multivariate Analysis; D012044:Regression Analysis; D012189:Retrospective Studies; D012307:Risk Factors; D012720:Severity of Illness Index; D012737:Sex Factors; D014664:Vasodilation
chemical_list: D018836:Inflammation Mediators