[The relation between body mass index and percentage body fat among Chinese adolescent living in urban Beijing]

Zhonghua Liu Xing Bing Xue Za Zhi. 2004 Feb;25(2):113-6.
[Article in Chinese]

Abstract

Objective: To study the relation between body mass index (BMI) and percentage body fat (PBF) in Chinese adolescent, and to compare the prevalence of overweight and obesity using BMI or PBF standards.

Methods: BMI from 757 girls with an average aged of 10.1 years in the rural areas, 165 girls average aged 13.5 years in suburbs and 172 boys average aged 13.7 years in suburb of Beijing, were measured. Their body compositions were also measured by dual-energy X-ray absorptiometry (DEXA).

Results: BMI was found closely correlated with PBF in each age group of rural and suburb girls and suburb boys with the correlation coefficient(r) of 0.59 - 0.83. When age, height and pubertal development were controlled, r became 0.54 - 0.88. The prevalence rates of obesity in rural girls, suburb girls and suburb boys were 33.1%, 21.8% and 21.5%, when PBF cutoff values (girls: PBF >or= 35%, boys: PBF >or= 25%) were used. However, the rates became 2.4%, 3.0% and 4.0% when BMI cutoff values of International Obesity Task Force (IOTF) were used. Compared with PBF cutoff values for obesity, the IOTF recommended BMI cutoff values had relatively lower sensitivity (7.3% - 18.9%) and higher specificity (100%).

Conclusion: BMI correlated well with PBF in Beijing adolescent. IOTF-BMI cutoff values showed low sensitivity and high specificity to Chinese adolescent which might be suitable for identifying obesity but not for the purpose of screening.

Publication types

  • Comparative Study
  • English Abstract

MeSH terms

  • Adolescent
  • Adolescent Development / physiology
  • Age Factors
  • Body Composition / physiology*
  • Body Mass Index*
  • Child
  • China / epidemiology
  • Female
  • Humans
  • Logistic Models
  • Male
  • Multivariate Analysis
  • Obesity / diagnosis
  • Obesity / epidemiology
  • Rural Population / statistics & numerical data
  • Sex Factors
  • Suburban Population / statistics & numerical data
  • Urban Population / statistics & numerical data*