title: Metabolic syndrome and the risk of cardiovascular disease in older adults.
abstract: OBJECTIVE
  The purpose of this study was to assess whether metabolic syndrome (MetSyn) predicts a higher risk for cardiovascular events in older adults.
  
  
  BACKGROUND
  The importance of MetSyn as a risk factor has not previously focused on older adults and deserves further study.
  
  
  METHODS
  We studied the impact of MetSyn (38% prevalence) on outcomes in 3,035 participants in the Health, Aging, and Body Composition (Health ABC) study (51% women, 42% black, ages 70 to 79 years).
  
  
  RESULTS
  During a 6-year follow-up, there were 434 deaths overall, 472 coronary events (CE), 213 myocardial infarctions (MI), and 231 heart failure (HF) hospital stays; 59% of the subjects had at least one hospital stay. Coronary events, MI, HF, and overall hospital stays occurred significantly more in subjects with MetSyn (19.9% vs. 12.9% for CE, 9.1% vs. 5.7% for MI, 10.0% vs. 6.1% for HF, and 63.1% vs. 56.1% for overall hospital stay; all p < 0.001). No significant differences in overall mortality was seen; however, there was a trend toward higher cardiovascular mortality (5.1% vs. 3.8%, p = 0.067) and coronary mortality (4.5% vs. 3.2%, p = 0.051) in patients with MetSyn. After adjusting for baseline characteristics, patients with MetSyn were at a significantly higher risk for CE (hazard ratio [HR] 1.56, 95% confidence interval [CI] 1.28 to 1.91), MI (HR 1.51, 95% CI 1.12 to 2.05), and HF hospital stay (HR 1.49, 95% CI 1.10 to 2.00). Women and whites with MetSyn had a higher coronary mortality rate. The CE rate was higher among subjects with diabetes and with MetSyn; those with both had the highest risk.
  
  
  CONCLUSIONS
  Overall, subjects over 70 years are at high risk for cardiovascular events; MetSyn in this group is associated with a significantly greater risk.
authors.affiliation: Division of Cardiovascular Medicine, Vanderbilt University, Nashville, Tennessee, USA. javed.butler@vanderbilt.edu
authors.forename: Javed
authors.initials: J
authors.lastname: Butler
authors.forename: Nicolas
authors.initials: N
authors.lastname: Rodondi
authors.forename: Yuwei
authors.initials: Y
authors.lastname: Zhu
authors.forename: Kathleen
authors.initials: K
authors.lastname: Figaro
authors.forename: Sergio
authors.initials: S
authors.lastname: Fazio
authors.forename: Douglas E
authors.initials: DE
authors.lastname: Vaughan
authors.forename: Suzanne
authors.initials: S
authors.lastname: Satterfield
authors.forename: Anne B
authors.initials: AB
authors.lastname: Newman
authors.forename: Bret
authors.initials: B
authors.lastname: Goodpaster
authors.forename: Douglas C
authors.initials: DC
authors.lastname: Bauer
authors.forename: Paul
authors.initials: P
authors.lastname: Holvoet
authors.forename: Tamara B
authors.initials: TB
authors.lastname: Harris
authors.forename: Nathalie
authors.initials: N
authors.lastname: de Rekeneire
authors.forename: Susan
authors.initials: S
authors.lastname: Rubin
authors.forename: Jingzhong
authors.initials: J
authors.lastname: Ding
authors.forename: Stephen B
authors.initials: SB
authors.lastname: Kritchevsky
mesh_terms: D000368:Aged; D000375:Aging; D002303:Cardiac Output, Low / Q000209:etiology; D002318:Cardiovascular Diseases / Q000209:etiology* / Q000401:mortality; D015331:Cohort Studies; D003327:Coronary Disease / Q000209:etiology; D048909:Diabetes Complications; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000150:complications*; D009203:Myocardial Infarction / Q000209:etiology; D016016:Proportional Hazards Models; D018570:Risk Assessment; D017678:Sex Distribution; D044465:White People / Q000706:statistics & numerical data