title: Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis.
abstract: OBJECTIVE
  To determine which simple index of overweight and obesity is the best discriminator of cardiovascular risk factors.
  
  
  METHODS
  This is a meta-analysis of published literature. MEDLINE was searched. Studies that used receiver-operating characteristics (ROC) curve analysis and published area under the ROC curves (AUC) for overweight and obesity indices with hypertension, type-2 diabetes, and/or dyslipidemia were included. The AUC for each of the four indices, with each risk factor, was pooled using a random-effects model; male and female data were analyzed separately.
  
  
  RESULTS
  Ten studies met the inclusion criteria. Body mass index (BMI) was the poorest discriminator for cardiovascular risk factors. Waist-to-height ratio (WHtR) was the best discriminator for hypertension, diabetes, and dyslipidemia in both sexes; its pooled AUC (95% confidence intervals) ranged from 0.67 (0.64, 0.69) to 0.73 (0.70, 0.75) and from 0.68 (0.63, 0.72) to 0.76 (0.70, 0.81) in males and females, respectively.
  
  
  CONCLUSIONS
  Statistical evidence supports the superiority of measures of centralized obesity, especially WHtR, over BMI, for detecting cardiovascular risk factors in both men and women.
authors: Nutrition and Lifestyle Division, The George Institute for International Health, University of Sydney, PO Box M 201, Missenden Road, Sydney NSW 2050, Australia. clee@george.org.au
authors: Crystal Man Ying
authors: CM
authors: Lee
authors: Rachel R
authors: RR
authors: Huxley
authors: Rachel P
authors: RP
authors: Wildman
authors: Mark
authors: M
authors: Woodward
mesh_terms: D050153:Abdominal Fat; D001823:Body Composition; D001827:Body Height; D015992:Body Mass Index; D001835:Body Weight; D002318:Cardiovascular Diseases / Q000209:etiology*; D005260:Female; D006801:Humans; D008297:Male; D009765:Obesity / Q000150:complications* / Q000175:diagnosis; D012372:ROC Curve; D012307:Risk Factors