title: Risk factors clustering within the metabolic syndrome: a pattern or by chance?
abstract: BACKGROUND
  An accumulation of various cardiovascular risk factors has been noted to occur within the clinical diagnosis of metabolic syndrome. However, it remains unclear whether specific risk factors aggregate following a predefined pattern or whether this happens by chance.
  
  
  METHODS
  This cross-sectional study involved 1715 adults, 37% males and 63% females, aged 34-80 years, who were consecutively recruited from cardiology and endocrinology outpatient clinics, and from internal medicine specialists in the primary healthcare physician office setting in Serbia, on a one-third basis. According to the AHA/NHLBI criteria, the actual prevalence of a combination of 3 or more of the following risk factors was determined: abnormal waist circumference, hypertension, high triglycerides, low high-density lipoprotein cholesterol, and abnormal fasting glucose. In addition, the prevalence of a corresponding combination of 3 factors was predicted from the prevalence of each factor in a given population, assuming that their combination occurred as the result of chance.
  
  
  RESULTS
  The most frequent risk factor was hypertension (87%), followed by waist circumference (60%), dyslipidemia (55%), and abnormal fasting glucose level (50%). Metabolic syndrome was identified in 1135 participants (66.2%). The actual prevalence of the combination of increased waist circumference, elevated blood sugar and hypertension was found to be 5 times more frequent than would be expected to occur by chance (10% actual vs. 2% predicted; p<0.0001).
  
  
  CONCLUSIONS
  A predefined aggregation pattern of risk factors within the metabolic syndrome was found for abdominal obesity, abnormal fasting glucose and hypertension. These risk factors do cluster more frequently than coincidental phenomena in the subjects of the given population, implying common underlying pathophysiological mechanisms.
authors.affiliation: Faculty of Medicine, University of Belgrade, Belgrade, Serbia.
authors.forename: Biljana
authors.initials: B
authors.lastname: Parapid
authors.forename: Miodrag C
authors.initials: MC
authors.lastname: Ostojic
authors.forename: Nebojsa M
authors.initials: NM
authors.lastname: Lalic
authors.forename: Dragan
authors.initials: D
authors.lastname: Micic
authors.forename: Svetozar
authors.initials: S
authors.lastname: Damjanovic
authors.forename: Dragana
authors.initials: D
authors.lastname: Bubanja
authors.forename: Dragan
authors.initials: D
authors.lastname: Simic
authors.forename: Katarina
authors.initials: K
authors.lastname: Lalic
authors.forename: Snezana
authors.initials: S
authors.lastname: Polovina
authors.forename: Jelena
authors.initials: J
authors.lastname: Marinkovic
authors.forename: Natasa M
authors.initials: NM
authors.lastname: Milic
mesh_terms: D000328:Adult; D000367:Age Factors; D015992:Body Mass Index; D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis / Q000453:epidemiology; D008875:Middle Aged; D015995:Prevalence; D018570:Risk Assessment / Q000379:methods / Q000706:statistics & numerical data; D012307:Risk Factors; D055771:Serbia / Q000453:epidemiology; D012737:Sex Factors