High body mass index percentile accurately reflects excess adiposity in white girls

J Am Diet Assoc. 2011 Mar;111(3):437-41. doi: 10.1016/j.jada.2010.11.015.

Abstract

Registered dietitians routinely screen children for overweight and obesity using an age-specific body mass index (BMI) percentile. However, BMI percentile may not be an accurate tool for detecting elevated relative fat mass. The purpose of this study was to assess the validity of BMI percentile for identifying "overfatness" in a cohort of 197 white, 9-year-old girls followed for 6 years during 2000-2007. Height, weight, and relative fat mass data from dual x-ray absorptiometry were collected every 2 years, comprising 695 observations of BMI to relative fat mass relationships. Using receiver operating characteristic analysis and age- and sex-specific cutoff values for relative fat mass from the literature, BMI percentile cutoff values could be identified to screen for girls who were considered "overfat" and "obese" with a high sensitivity (69% to 96%) and specificity (83% to 96%). The Centers for Disease Control and Prevention's BMI cutoff values decreased sensitivity (0 to 76%), but improved specificity (96% to 100%), which may be preferable. Increases in BMI percentile tended to be indicative of increasing adiposity only in girls with a BMI >30th to 40th percentile for age. This study suggests that white girls aged 9 to 15 years with a BMI ≥85th percentile and/or girls with a BMI ≥50th percentile experiencing upward crossing of percentile bands are likely to have excess body fat levels and are good candidates for healthy lifestyle interventions.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adiposity / physiology*
  • Adolescent
  • Anthropometry
  • Body Composition / physiology*
  • Body Mass Index*
  • Child
  • Cohort Studies
  • Female
  • Follow-Up Studies
  • Humans
  • Ideal Body Weight
  • Overweight / diagnosis
  • Overweight / epidemiology
  • ROC Curve
  • Sensitivity and Specificity
  • White People / statistics & numerical data*