title: Metabolic syndrome across Europe: different clusters of risk factors.
abstract: BACKGROUND
  Metabolic syndrome (MetS) remains a controversial entity. Specific clusters of MetS components - rather than MetS per se - are associated with accelerated arterial ageing and with cardiovascular (CV) events. To investigate whether the distribution of clusters of MetS components differed cross-culturally, we studied 34,821 subjects from 12 cohorts from 10 European countries and one cohort from the USA in the MARE (Metabolic syndrome and Arteries REsearch) Consortium.
  
  
  METHODS
  In accordance with the ATP III criteria, MetS was defined as an alteration three or more of the following five components: elevated glucose (G), fasting glucose ≥110 mg/dl; low HDL cholesterol, < 40mg/dl for men or <50 mg/dl for women; high triglycerides (T), ≥150 mg/dl; elevated blood pressure (B), ≥130/≥85 mmHg; abdominal obesity (W), waist circumference >102 cm for men or >88 cm for women.
  
  
  RESULTS
  MetS had a 24.3% prevalence (8468 subjects: 23.9% in men vs. 24.6% in women, p < 0.001) with an age-associated increase in its prevalence in all the cohorts. The age-adjusted prevalence of the clusters of MetS components previously associated with greater arterial and CV burden differed across countries (p < 0.0001) and in men and women (p < 0.0001). In details, the cluster TBW was observed in 12% of the subjects with MetS, but was far more common in the cohorts from the UK (32.3%), Sardinia in Italy (19.6%), and Germany (18.5%) and less prevalent in the cohorts from Sweden (1.2%), Spain (2.6%), and the USA (2.5%). The cluster GBW accounted for 12.7% of subjects with MetS with higher occurrence in Southern Europe (Italy, Spain, and Portugal: 31.4, 18.4, and 17.1% respectively) and in Belgium (20.4%), than in Northern Europe (Germany, Sweden, and Lithuania: 7.6, 9.4, and 9.6% respectively).
  
  
  CONCLUSIONS
  The analysis of the distribution of MetS suggested that what follows under the common definition of MetS is not a unique entity rather a constellation of cluster of MetS components, likely selectively risky for CV disease, whose occurrence differs across countries.
authors.affiliation: San Raffaele Pisana IRCCS, Rome, Italy angeloelefante@interfree.it.
authors.forename: Angelo
authors.initials: A
authors.lastname: Scuteri
authors.affiliation: INSERM U970, Paris, France University Paris Descartes, Paris, France.
authors.forename: Stephane
authors.initials: S
authors.lastname: Laurent
authors.affiliation: Consiglio Nazionale delle Ricerche, Monserrato, Cagliari, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Cucca
authors.affiliation: Cardiff University, Cardiff, UK.
authors.forename: John
authors.initials: J
authors.lastname: Cockcroft
authors.affiliation: Centro Hospitalar do Alto Ave/Minho University. Guimaraes Braga, Portugal.
authors.forename: Pedro Guimaraes
authors.initials: PG
authors.lastname: Cunha
authors.affiliation: Hospital Universitario de Getafe, Madrid, Spain.
authors.forename: Leocadio Rodriguez
authors.initials: LR
authors.lastname: Mañas
authors.affiliation: Erasmus University Medical Center, Rotterdam, The Netherlands.
authors.forename: Francesco U
authors.initials: FU
authors.lastname: Mattace Raso
authors.affiliation: Università di Brescia, Brescia, Italy 2° Medicina Generale Spedali Civili, Brescia, Italy.
authors.forename: Maria Lorenza
authors.initials: ML
authors.lastname: Muiesan
authors.affiliation: Vilnius University Hospital Santariškių Klinikos, Vilnius, Lithuania.
authors.forename: Ligita
authors.initials: L
authors.lastname: Ryliškytė
authors.affiliation: Ghent University Hospital and Ghent University, Ghent, Belgium.
authors.forename: Ernst
authors.initials: E
authors.lastname: Rietzschel
authors.affiliation: National Institutes of Health, Baltimore, USA.
authors.forename: James
authors.initials: J
authors.lastname: Strait
authors.affiliation: Athens Medical School, Athens, Greece.
authors.forename: Charalambos
authors.initials: C
authors.lastname: Vlachopoulos
authors.affiliation: University Medicine Greifswald, Germany.
authors.forename: Henry
authors.initials: H
authors.lastname: Völzke
authors.affiliation: National Institutes of Health, Baltimore, USA.
authors.forename: Edward G
authors.initials: EG
authors.lastname: Lakatta
authors.affiliation: Lund University, Malmö, Sweden.
authors.forename: Peter M
authors.initials: PM
authors.lastname: Nilsson
mesh_terms: D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D002318:Cardiovascular Diseases / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D002784:Cholesterol / Q000097:blood; D016000:Cluster Analysis; D003431:Cross-Cultural Comparison; D003920:Diabetes Mellitus / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology; D050171:Dyslipidemias / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology; D005060:Europe / Q000453:epidemiology; D005260:Female; D006801:Humans; D006973:Hypertension / Q000175:diagnosis / Q000453:epidemiology / Q000503:physiopathology; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D008875:Middle Aged; D056128:Obesity, Abdominal / Q000175:diagnosis / Q000453:epidemiology; D015995:Prevalence; D012307:Risk Factors; D017678:Sex Distribution; D012737:Sex Factors; D014280:Triglycerides / Q000097:blood; D014481:United States / Q000453:epidemiology; D055105:Waist Circumference; D055815:Young Adult
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D014280:Triglycerides; D002784:Cholesterol
keywords: Blood pressure; Europe; HDL cholesterol; epidemiology; glucose; metabolic syndrome; triglycerides; waist circumference