The discrimination of dyslipidaemia using anthropometric measures in ethnically diverse populations of the Asia-Pacific Region: the Obesity in Asia Collaboration

Obes Rev. 2010 Feb;11(2):127-36. doi: 10.1111/j.1467-789X.2009.00605.x. Epub 2009 Jun 2.


Dyslipidaemia is a major risk factor for cardiovascular disease and is only detectable through blood testing, which may not be feasible in resource-poor settings. As dyslipidaemia is commonly associated with excess weight, it may be possible to identify individuals with adverse lipid profiles using simple anthropometric measures. A total of 222 975 individuals from 18 studies were included as part of the Obesity in Asia Collaboration. Linear and logistic regression models were used to assess the association between measures of body size and dyslipidaemia. Body mass index, waist circumference, waist : hip ratio (WHR) and waist : height ratio were continuously associated with the lipid variables studied, but the relationships were consistently stronger for triglycerides and high-density lipoprotein cholesterol. The associations were similar between Asians and non-Asians, and no single anthropometric measure was superior at discriminating those individuals at increased risk of dyslipidaemia. WHR cut-points of 0.8 in women and 0.9 in men were applicable across both Asians and non-Asians for the discrimination of individuals with any form of dyslipidaemia. Measurement of central obesity may help to identify those individuals at increased risk of dyslipidaemia. WHR cut-points of 0.8 for women and 0.9 for men are optimal for discriminating those individuals likely to have adverse lipid profiles and in need of further clinical assessment.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Anthropometry / methods*
  • Asia
  • Body Composition
  • Body Weight
  • Dyslipidemias / diagnosis*
  • Dyslipidemias / epidemiology*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Obesity / diagnosis*
  • Obesity / epidemiology*
  • Oceania
  • Prevalence
  • Regression Analysis
  • Risk Assessment
  • Waist Circumference
  • Waist-Hip Ratio