Waist circumference, body mass index and waist to hip ratio for prediction of the metabolic syndrome in Chinese

Nutr Metab Cardiovasc Dis. 2009 Oct;19(8):542-7. doi: 10.1016/j.numecd.2008.11.006. Epub 2009 Feb 1.

Abstract

Background and aims: To explore the ability of waist circumference (WC), body mass index (BMI) and waist to hip ratio (WHR) to predict two or more non-adipose components of the metabolic syndrome (MetS) among individuals aged 18-85 in North China.

Methods and results: This study is a cluster sample survey of 101,510 individuals, complete data are 75,788 subjects, 59,874 males and 15,914 females. Their ages were 51.9+/-12.7 years (males) and 48.7+/-11.5 years (females). Receiver operating characteristic (ROC) analysis was used to examine discrimination and find optimal cut off values of WC, BMI and WHR to predict two or more non-adipose components of MetS. The area under the ROC curve (AURC) for WC (0.694) and BMI (0.692) in females showed no difference. In males BMI (0.657) had a better discrimination than WC (0.634). WHR was weaker in both sexes. The optimal cut off value of WC in males (86.5 cm) was higher than in females (82.1cm); and that of BMI was about 24 kg/m(2) in both genders. The optimal cut off values of WC, BMI, and WHR, increased with age in both sexes.

Conclusions: BMI and WC are more useful than WHR for predicting two or more non-adipose components of MetS. Cut off values for WC in males, and those of BMI and WHR in both sexes are lower than that in present MetS criteria; WC in females is slightly higher. Cut off values of WC, BMI and WHR were increased with age in the Chinese.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adolescent
  • Adult
  • Age Distribution
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Asian People*
  • Body Mass Index*
  • China / epidemiology
  • Female
  • Health Surveys
  • Humans
  • Male
  • Metabolic Syndrome / diagnosis*
  • Metabolic Syndrome / ethnology*
  • Middle Aged
  • Predictive Value of Tests
  • Prevalence
  • ROC Curve
  • Reproducibility of Results
  • Sex Distribution
  • Sex Factors
  • Waist Circumference / ethnology*
  • Waist-Hip Ratio*
  • Young Adult