title: The metabolic syndrome adds utility to the prediction of mortality over its components: The Vietnam Experience Study.
abstract: BACKGROUND
  The metabolic syndrome increases mortality risk. However, as "non-affected" individuals may still have up to two risk factors, the utility of using three or more components to identify the syndrome, and its predictive advantage over individual components have yet to be determined.
  
  
  METHODS
  Participants, male Vietnam-era veterans (n=4265) from the USA, were followed-up from 1985/1986 for 14.7 years (61,498 person-years), and all-cause and cardiovascular disease deaths collated. Cox's proportional-hazards regression was used to assess the effect of the metabolic syndrome and its components on mortality adjusting for a wide range of potential confounders.
  
  
  RESULTS
  At baseline, 752 participants (17.9%) were identified as having metabolic syndrome. There were 231 (5.5%) deaths from all-causes, with 60 from cardiovascular disease. After adjustment for a range of covariates, the metabolic syndrome increased the risk of all-cause, HR 2.03, 95%CI 1.52, 2.71, and cardiovascular disease mortality, HR 1.92, 95%CI 1.10, 3.36. Risk increased dose-dependently with increasing numbers of components. The increased risk from possessing only one or two components was not statistically significant. The adjusted risk for four or more components was greater than for only three components for both all-cause, HR 2.30, 95%CI 1.45, 3.66 vs. HR 1.70, 95%CI 1.11, 2.61, and cardiovascular disease mortality, HR 3.34, 95%CI 1.19, 9.37 vs. HR 2.81, 95%CI 1.07, 7.35. The syndrome was more informative than the individual components for all-cause mortality, but could not be assessed for cardiovascular disease mortality due to multicollinearity. Hyperglycaemia was the individual strongest parameter associated with mortality.
  
  
  CONCLUSIONS
  The metabolic syndrome is informative in predicting mortality, with risk increasing as the number of components increase above the threshold required for diagnosis.
authors.affiliation: Epidemiology, Public Health and Biostatistics, College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK. gneilthomas@yahoo.co.uk
authors.forename: G Neil
authors.initials: GN
authors.lastname: Thomas
authors.forename: Anna C
authors.initials: AC
authors.lastname: Phillips
authors.forename: Douglas
authors.initials: D
authors.lastname: Carroll
authors.forename: Catharine R
authors.initials: CR
authors.lastname: Gale
authors.forename: G David
authors.initials: GD
authors.lastname: Batty
mesh_terms: D000328:Adult; D002318:Cardiovascular Diseases / Q000401:mortality; D006801:Humans; D006943:Hyperglycemia / Q000401:mortality; D024821:Metabolic Syndrome / Q000401:mortality*; D011379:Prognosis; D016016:Proportional Hazards Models; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D014728:Veterans