title: Association of visceral and subcutaneous adiposity with kidney function.
abstract: OBJECTIVE
  Obesity is a risk factor for incident chronic kidney disease (CKD). Visceral (VAT) and subcutaneous adipose tissue (SAT) may confer differential metabolic risk profiles. The relations of VAT and SAT were analyzed with CKD as estimated by creatinine- and cystatin-based estimating equations.
  
  
  METHODS
  Participants from the Framingham Offspring Study who underwent abdominal computed tomography for VAT and SAT quantification were included (n = 1299; 53% women; mean age 60 yr). CKD was defined as estimated GFR <60 ml/min per 1.73 m(2), as estimated using creatinine (n = 89) in the Modification of Diet in Renal Disease (MDRD) formula or by cystatin C (n = 136). Regression models evaluated the cross-sectional relations between VAT and SAT with CKD and cystatin C, with age and gender adjustment and cardiovascular risk factor adjustment.
  
  
  RESULTS
  Neither VAT nor SAT was associated with CKD as estimated by the MDRD equation. In contrast, both VAT and SAT were associated with CKD when defined using cystatin-based equations. The estimated decrease in estimated GFR by cystatin C per 1-SD increase of VAT was 1.9 ml/min per 1.73 m(2) and for SAT was 2.6 ml/min per 1.73 m(2) in a multivariable-adjusted model.
  
  
  CONCLUSIONS
  VAT and SAT were associated with CKD when defined using cystatin C estimating equations but not when using a creatinine-based estimating equation. Mechanisms linking adipose tissue to cystatin C warrant further research.
authors.affiliation: Tufts-New England Medical Center, Boston, Massachusetts, USA.
authors.forename: Jill A
authors.initials: JA
authors.lastname: Young
authors.forename: Shih-Jen
authors.initials: SJ
authors.lastname: Hwang
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Sarnak
authors.forename: Udo
authors.initials: U
authors.lastname: Hoffmann
authors.forename: Joseph M
authors.initials: JM
authors.lastname: Massaro
authors.forename: Daniel
authors.initials: D
authors.lastname: Levy
authors.forename: Emelia J
authors.initials: EJ
authors.lastname: Benjamin
authors.forename: Martin G
authors.initials: MG
authors.lastname: Larson
authors.forename: Ramachandran S
authors.initials: RS
authors.lastname: Vasan
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: O'Donnell
authors.forename: Caroline S
authors.initials: CS
authors.lastname: Fox
mesh_terms: D050154:Adiposity; D000368:Aged; D015415:Biomarkers / Q000097:blood; D002908:Chronic Disease; D003404:Creatinine / Q000097:blood; D003430:Cross-Sectional Studies; D055316:Cystatin C / Q000097:blood; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D050152:Intra-Abdominal Fat / Q000000981:diagnostic imaging / Q000503:physiopathology*; D007668:Kidney / Q000503:physiopathology*; D007674:Kidney Diseases / Q000000981:diagnostic imaging / Q000209:etiology* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009765:Obesity / Q000150:complications* / Q000000981:diagnostic imaging / Q000503:physiopathology; D016017:Odds Ratio; D018570:Risk Assessment; D050151:Subcutaneous Fat / Q000000981:diagnostic imaging / Q000503:physiopathology*; D014057:Tomography, X-Ray Computed
chemical_list: D015415:Biomarkers; D055316:Cystatin C; D003404:Creatinine