title: Metabolic syndrome, components, and cardiovascular disease prevalence in chronic kidney disease: findings from the Chronic Renal Insufficiency Cohort (CRIC) Study.
abstract: OBJECTIVE
  Metabolic syndrome may increase the risk for incident cardiovascular disease (CVD) and all-cause mortality in the general population. It is unclear whether, and to what degree, metabolic syndrome is associated with CVD in chronic kidney disease (CKD). We determined metabolic syndrome prevalence among individuals with a broad spectrum of kidney dysfunction, examining the role of the individual elements of metabolic syndrome and their relationship to prevalent CVD.
  
  
  METHODS
  We evaluated four models to compare metabolic syndrome or its components to predict prevalent CVD using prevalence ratios in the Chronic Renal Insufficiency Cohort (CRIC) Study.
  
  
  RESULTS
  Among 3,939 CKD participants, the prevalence of metabolic syndrome was 65% and there was a significant association with prevalent CVD. Metabolic syndrome was more common in diabetics (87.5%) compared with non-diabetics (44.3%). Hypertension was the most prevalent component, and increased triglycerides the least prevalent. Using the bayesian information criterion, we found that the factors defining metabolic syndrome, considered as a single interval-scaled variable, was the best of four models of metabolic syndrome, both for CKD participants overall and for diabetics and non-diabetics separately.
  
  
  CONCLUSIONS
  The predictive value of this model for future CVD outcomes will subsequently be validated in longitudinal analyses.
authors.affiliation: Department of Medicine, University of Pennsylvania Medical Center, Philadelphia, 19104, USA. townsend@mail.med.upenn.edu
authors.forename: Raymond R
authors.initials: RR
authors.lastname: Townsend
authors.forename: Amanda H
authors.initials: AH
authors.lastname: Anderson
authors.forename: Jing
authors.initials: J
authors.lastname: Chen
authors.forename: Crystal A
authors.initials: CA
authors.lastname: Gadebegku
authors.forename: Harold I
authors.initials: HI
authors.lastname: Feldman
authors.forename: Jeffrey C
authors.initials: JC
authors.lastname: Fink
authors.forename: Alan S
authors.initials: AS
authors.lastname: Go
authors.forename: Marshall
authors.initials: M
authors.lastname: Joffe
authors.forename: Lisa A
authors.initials: LA
authors.lastname: Nessel
authors.forename: Akinlolu
authors.initials: A
authors.lastname: Ojo
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Rader
authors.forename: Muredach P
authors.initials: MP
authors.lastname: Reilly
authors.forename: Valerie
authors.initials: V
authors.lastname: Teal
authors.forename: Karen
authors.initials: K
authors.lastname: Teff
authors.forename: Jackson T
authors.initials: JT
authors.lastname: Wright
authors.forename: Dawei
authors.initials: D
authors.lastname: Xie
mesh_terms: D000328:Adult; D000368:Aged; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D005260:Female; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000453:epidemiology*; D008875:Middle Aged; D015233:Models, Statistical; D015995:Prevalence; D051436:Renal Insufficiency, Chronic / Q000453:epidemiology*; D014481:United States / Q000453:epidemiology; D055815:Young Adult