title: Models for estimating the metabolic syndrome biological age as the new index for evaluation and management of metabolic syndrome.
abstract: OBJECTIVE
  This study aims to propose a metabolic syndrome (MS) biological age model, through which overall evaluation and management of the health status and aging state in MS can be done easily. Through this model, we hope to provide a novel evaluation and management health index that can be utilized in various health care fields.
  
  
  METHODS
  MS parameters from American Heart Association/National Heart, Lung, and Blood Institute guidelines in 2005 were used as biomarkers for the estimation of MS biological age. MS biological age model development was done by analyzing data of 263,828 participants and clinical application of the developed MS biological age was assessed by analyzing the data of 188,886 subjects.
  
  
  RESULTS
  The principal component accounted for 36.1% in male and 38.9% in female of the total variance in the battery of five variables. The correlation coefficient between corrected biological age and chronological age in males and females were 0.711 and 0.737, respectively. Significant difference for mean MS biological age and chronological age between the three groups, normal, at risk and MS, was seen (P<0.001).
  
  
  CONCLUSIONS
  For the comprehensive approach in MS management, MS biological age is expected to be additionally utilized as a novel evaluation and management index along with the traditional MS diagnosis.
authors.affiliation: MediAge Research Center, Seongnam-si, Gyeonggi-do.
authors.forename: Young Gon
authors.initials: YG
authors.lastname: Kang
authors.affiliation: Department of Family Medicine, College of Medicine, CHA University, Chaum, Seoul.
authors.forename: Eunkyung
authors.initials: E
authors.lastname: Suh
authors.affiliation: Department of Family Medicine, College of Medicine, CHA University, Bundang CHA Medical Center, Seongnam-si, Gyeonggi-do.
authors.forename: Hyejin
authors.initials: H
authors.lastname: Chun
authors.affiliation: Department of Family Medicine, International St Mary's Hospital, College of Medicine, Catholic Kwandong University, Incheon.
authors.forename: Sun-Hyun
authors.initials: SH
authors.lastname: Kim
authors.affiliation: Pharmicell Clinical Research Center, Seoul, South Korea.
authors.forename: Deog Ki
authors.initials: DK
authors.lastname: Kim
authors.affiliation: MediAge Research Center, Seongnam-si, Gyeonggi-do.
authors.forename: Chul-Young
authors.initials: CY
authors.lastname: Bae
mesh_terms: D000328:Adult; D000375:Aging / Q000502:physiology*; D015415:Biomarkers; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis / Q000503:physiopathology*; D008875:Middle Aged; D008954:Models, Biological
chemical_list: D015415:Biomarkers
keywords: biological age; biomarker; health care; index; metabolic syndrome