title: Serum fetuin-A is correlated with metabolic syndrome in middle-aged and elderly Chinese.
abstract: OBJECTIVE
  Fetuin-A is an important player in the enhancement of insulin resistance. We aimed to investigate the association of serum fetuin-A and metabolic syndrome (MetS) in a community based Chinese population.
  
  
  METHODS
  A total of 5469 subjects aged 40 years or above were recruited from two urban communities in Shanghai. Demographic, anthropometric and biochemical features were collected according to a standard protocol. Serum fetuin-A levels were measured using ELISA and the modified NCEP-ATP III criteria were adopted to diagnose MetS.
  
  
  RESULTS
  A higher level of serum fetuin-A was well associated with a variety of metabolic disorders and an increased prevalence of MetS. The relative risks for MetS were markedly elevated in a dose-dependent manner both before and after extended adjustment in total participants (adjusted odds ratios were 1.00, 1.11, 1.20 and 1.40 for fetuin-A quartiles 1, 2, 3 and 4, respectively; P value for trend = 0.0002). MetS risks were also significantly associated with serum fetuin-A in various subgroups of sex, age, body mass index and glycaemic status. Moreover, an elevated serum fetuin-A was also independently associated with MetS components including central obesity, high blood pressure, high blood glucose and high triglycerides. Stepwise regression analyses revealed fetuin-A as an independent determinant of insulin resistance measured by the index of homeostasis model (HOMA-IR) (β = 0.064; P = 0.009).
  
  
  CONCLUSIONS
  Serum fetuin-A levels were strongly and independently associated with MetS and its components in community-dwelling Chinese adults.
authors.affiliation: State Key Laboratory of Medical Genomics, E-Institute of Shanghai Universities, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200025, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Xu
authors.forename: Min
authors.initials: M
authors.lastname: Xu
authors.forename: Yufang
authors.initials: Y
authors.lastname: Bi
authors.forename: Aiyun
authors.initials: A
authors.lastname: Song
authors.forename: Yun
authors.initials: Y
authors.lastname: Huang
authors.forename: Yu
authors.initials: Y
authors.lastname: Liu
authors.forename: Yaohua
authors.initials: Y
authors.lastname: Wu
authors.forename: Yuhong
authors.initials: Y
authors.lastname: Chen
authors.forename: Weiqing
authors.initials: W
authors.lastname: Wang
authors.forename: Xiaoying
authors.initials: X
authors.lastname: Li
authors.forename: Guang
authors.initials: G
authors.lastname: Ning
mesh_terms: D000367:Age Factors; D000368:Aged; D000375:Aging; D044466:Asian People / Q000706:statistics & numerical data*; D015415:Biomarkers / Q000097:blood; D001798:Blood Proteins / Q000032:analysis*; D002681:China / Q000453:epidemiology; D003430:Cross-Sectional Studies; D004797:Enzyme-Linked Immunosorbent Assay; D005260:Female; D006801:Humans; D007333:Insulin Resistance / Q000208:ethnology; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood* / Q000175:diagnosis / Q000208:ethnology* / Q000503:physiopathology; D008875:Middle Aged; D016017:Odds Ratio; D015995:Prevalence; D018570:Risk Assessment; D012307:Risk Factors; D015854:Up-Regulation; D014505:Urban Population / Q000706:statistics & numerical data; D060749:alpha-2-HS-Glycoprotein
chemical_list: C556354:AHSG protein, human; D015415:Biomarkers; D001798:Blood Proteins; D060749:alpha-2-HS-Glycoprotein