title: The metabolic syndrome identifies a heterogeneous group of metabolic component combinations in the Asia-Pacific region.
abstract: OBJECTIVE
  To compare the prevalence of metabolic syndrome (MetS) by combinations of MetS components derived from the National Cholesterol Education Program Adult Treatment Panel III (ATPIII) and International Diabetes Federation (IDF) definitions.
  
  
  METHODS
  Four studies with ethnically distinct populations from the Asia-Pacific region were selected from the DETECT-2 study database. The prevalences of combinations of MetS components using the modified ATPIII (modATPIII) and IDF MetS definitions were compared between sexes and across populations.
  
  
  RESULTS
  A total of 22,952 participants from Australia, Japan, Korea and Samoa were included. The age-adjusted prevalence of modATPIII MetS varied from 9.4 to 35.8% in men and 10.3 to 57.2% in women; results for IDF were generally higher. Prevalences of the 16 possible MetS component combinations from the modATPIII definition that result in a diagnosis of MetS ranged from 0 to 12.7%. Of those with IDF-defined abdominal obesity, the prevalences of the 11 IDF-defined MetS component combinations ranged from 0.2 to 18.3%.
  
  
  CONCLUSIONS
  The large variation in the prevalence of possible MetS component combinations to diagnose MetS may explain the different risk of cardiovascular outcomes associated with MetS in different populations, especially since particular combinations of MetS components are associated with different risk of cardiovascular disease.
authors.affiliation: The George Institute for International Health, University of Sydney, Sydney, NSW 2050, Australia. clee@george.org.au
authors.forename: Crystal Man Ying
authors.initials: CM
authors.lastname: Lee
authors.forename: Rachel R
authors.initials: RR
authors.lastname: Huxley
authors.forename: Mark
authors.initials: M
authors.lastname: Woodward
authors.forename: Paul
authors.initials: P
authors.lastname: Zimmet
authors.forename: Jonathan
authors.initials: J
authors.lastname: Shaw
authors.forename: Nam H
authors.initials: NH
authors.lastname: Cho
authors.forename: Hyung Rae
authors.initials: HR
authors.lastname: Kim
authors.forename: Satu
authors.initials: S
authors.lastname: Viali
authors.forename: Makoto
authors.initials: M
authors.lastname: Tominaga
authors.forename: Dorte
authors.initials: D
authors.lastname: Vistisen
authors.forename: Knut
authors.initials: K
authors.lastname: Borch-Johnsen
authors.forename: Stephen
authors.initials: S
authors.lastname: Colagiuri
mesh_terms: D001315:Australia / Q000453:epidemiology; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D049628:Body Size; D005260:Female; D006801:Humans; D007564:Japan / Q000453:epidemiology; D007723:Korea / Q000453:epidemiology; D008055:Lipids / Q000097:blood; D008297:Male; D024821:Metabolic Syndrome / Q000145:classification* / Q000453:epidemiology* / Q000503:physiopathology; D015995:Prevalence; D012307:Risk Factors; D018947:Samoa / Q000453:epidemiology
chemical_list: D001786:Blood Glucose; D008055:Lipids