title: Receiver-operating characteristics of adiposity for metabolic syndrome: the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study.
abstract: OBJECTIVE
  To assess the predictive values of various adiposity indices for metabolic syndrome (MetS) among adults using baseline data from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) cohort.
  
  
  METHODS
  In a cross-sectional study, BMI, waist circumference (WC), body composition by dual-energy X-ray absorptiometry (DEXA) and metabolic risk factors such as TAG, HDL cholesterol, blood pressure, fasting glucose and insulin, uric acid and C-reactive protein were measured. Receiver-operating characteristic (ROC) curves and logistic regression analyses were conducted.
  
  
  METHODS
  Baltimore, Maryland.
  
  
  METHODS
  White and African-American US adults (n 1981), aged 30-64 years.
  
  
  RESULTS
  In predicting risk of MetS using obesity-independent National Cholesterol Education Program Adult Treatment Panel III criteria, percentage total body fat mass (TtFM) assessed using DEXA measuring overall adiposity had no added value over WC. This was true among both men (area under the ROC curve (AUC) = 0.680 v. 0.733 for TtFM and WC, respectively; P < 0.05) and women (AUC = 0.581 v. 0.686). Percentage rib fat mass (RbFM) was superior to TtFM only in women for MetS (AUC = 0.701 and 0.581 for RbFM and TtFM, respectively; P < 0.05), particularly among African-American women. Elevated percentage leg fat mass (LgFM) was protective against MetS among African-American men. Among white men, BMI was inferior to WC in predicting MetS. Optimal WC cut-off points varied across ethnic-sex groups and differed from those recommended by the National Institutes of Health/North American Association for the Study of Obesity.
  
  
  CONCLUSIONS
  The study provides evidence that WC is among the most powerful tools to predict MetS, and that optimal cut-off points for various indices including WC may differ by sex and race.
authors.affiliation: National Institute on Aging, NIA/NIH-IRP, NIH Biomedical Research Center, Baltimore, MD 21224, USA. baydounm@mail.nih.gov
authors.forename: May A
authors.initials: MA
authors.lastname: Beydoun
authors.forename: Marie T Fanelli
authors.initials: MT
authors.lastname: Kuczmarski
authors.forename: Youfa
authors.initials: Y
authors.lastname: Wang
authors.forename: Marc A
authors.initials: MA
authors.lastname: Mason
authors.forename: Michele K
authors.initials: MK
authors.lastname: Evans
authors.forename: Alan B
authors.initials: AB
authors.lastname: Zonderman
mesh_terms: D050154:Adiposity / Q000502:physiology*; D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data; D000375:Aging / Q000502:physiology*; D019540:Area Under Curve; D015142:Baltimore / Q000453:epidemiology; D001794:Blood Pressure / Q000502:physiology; D001823:Body Composition / Q000502:physiology; D015992:Body Mass Index; D002097:C-Reactive Protein / Q000378:metabolism; D002784:Cholesterol / Q000097:blood; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology*; D008875:Middle Aged; D011237:Predictive Value of Tests; D012372:ROC Curve; D012307:Risk Factors; D012737:Sex Factors; D055105:Waist Circumference; D044465:White People / Q000706:statistics & numerical data
chemical_list: D002097:C-Reactive Protein; D002784:Cholesterol