title: Habitual coffee consumption inversely associated with metabolic syndrome-related biomarkers involving adiponectin.
abstract: OBJECTIVE
  The goal of this cross-sectional study was to assess whether habitual coffee consumption shows beneficial association with metabolic syndrome (MetS) in adults.
  
  
  METHODS
  The association of coffee consumption and MetS-related biomarkers including visceral fat area (VFA) and subcutaneous fat area (SFA), total serum adiponectin (T-Ad), low-molecular-weight serum adiponectin (LMW-AD), medium-molecular-weight serum adiponectin (MMW-Ad), and high-molecular-weight serum adiponectin (HMW-Ad) levels were analyzed among 364 Japanese men (36-61 y old) using two models of multivariate regression analyses; model 1 (adjusted for age, alcohol drinking, smoking, and walking status) and model 2 (adjusted for body mass index in addition to model 1 analysis). Participants were categorized into two groups according to their MetS risk score (raised blood pressure and hemoglobin A1c levels, and reduced high-density lipoprotein cholesterol levels).
  
  
  RESULTS
  Both light (1-3 cups/d) and moderate (≥4 cups/d) coffee consumption showed significant inverse associations with VFA and VFA/SFA ratio (P < 0.0001). Moderate coffee consumption showed a favorable tendency toward these associations with T-Ad (P = 0.06) and HMW-Ad (P = 0.07) levels in model 1 analysis. In participants with lower MetS risk score (≤1), moderate coffee consumption showed significant associations with T-Ad and HMW-Ad levels (P < 0.05) in both analyses, whereas no significant associations of coffee consumption with adiponectin levels were seen in the men with higher MetS risk scores (≥2).
  
  
  CONCLUSIONS
  Habitual moderate coffee consumption shows significant inverse associations with MetS-related biomarkers possibly involving adiponectin, which is inversely related to visceral fat accumulation.
authors.affiliation: Department of Public Health, Wakayama Medical University School of Medicine, Wakayama, Japan.
authors.forename: Kanae
authors.initials: K
authors.lastname: Mure
authors.forename: Shinya
authors.initials: S
authors.lastname: Maeda
authors.forename: Chizu
authors.initials: C
authors.lastname: Mukoubayashi
authors.forename: Kouichi
authors.initials: K
authors.lastname: Mugitani
authors.forename: Masataka
authors.initials: M
authors.lastname: Iwane
authors.forename: Fujihisa
authors.initials: F
authors.lastname: Kinoshita
authors.forename: Osamu
authors.initials: O
authors.lastname: Mohara
authors.forename: Tatsuya
authors.initials: T
authors.lastname: Takeshita
mesh_terms: D052242:Adiponectin / Q000097:blood*; D000328:Adult; D015415:Biomarkers / Q000097:blood*; D015992:Body Mass Index; D002784:Cholesterol / Q000097:blood; D003069:Coffee; D003430:Cross-Sectional Studies; D005247:Feeding Behavior; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D050152:Intra-Abdominal Fat / Q000378:metabolism; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood*; D008875:Middle Aged; D008970:Molecular Weight; D015999:Multivariate Analysis; D012044:Regression Analysis; D012307:Risk Factors; D050151:Subcutaneous Fat / Q000378:metabolism
chemical_list: D052242:Adiponectin; D015415:Biomarkers; D002784:Cholesterol; D003069:Coffee; D006442:Glycated Hemoglobin