title: The identification of children with adverse risk factor levels by body mass index cutoffs from 2 classification systems: the Bogalusa Heart Study.
abstract: BACKGROUND
  The cutoffs from the Centers for Disease Control and Prevention (CDC) growth charts and from the Cooper Institute (FitnessGram) are widely used to identify children who have a high body mass index (BMI).
  
  
  OBJECTIVE
  We compared the abilities of these 2 systems to identify children who have adverse lipid concentrations and blood pressure measurements and the reliability (consistency) of each classification system over time (mean follow-up: 7 y).
  
  
  METHODS
  A cross-sectional analysis based on data from 22,896 examinations of 5- to 17-y-olds was conducted. Principal components analyses were used to summarize levels of the 5 risk factors, and likelihood ratios and the κ statistic were used to compare the screening abilities of the 2 systems. Of these children, 3972 were included in longitudinal analyses.
  
  
  RESULTS
  There were marked differences in the prevalence of a high FitnessGram BMI by age, with the prevalence among boys increasing from 2.5% to 21% between the ages of 5 and 11 y. The identification of adverse risk factors by the 2 systems was only fair (κ = 0.25), but there was little difference in the abilities of the CDC and FitnessGram cutoffs to identify high-risk children. Longitudinal analyses, however, indicated that the agreement between initial and follow-up FitnessGram classifications was substantially lower than that based on CDC cutoffs (κ = 0.28 compared with 0.49).
  
  
  CONCLUSIONS
  The FitnessGram and CDC cutoffs have similar abilities to identify high-risk children. However, a high FitnessGram BMI is difficult to interpret because the reliability over time is low, and the prevalence increases markedly with age.
authors.affiliation: Division of Nutrition, Physical Activity and Obesity, Centers for Disease Control and Prevention, Atlanta, GA, USA. dxf1@cdc.gov
authors.forename: David S
authors.initials: DS
authors.lastname: Freedman
authors.forename: Janet E
authors.initials: JE
authors.lastname: Fulton
authors.forename: William H
authors.initials: WH
authors.lastname: Dietz
authors.forename: Liping
authors.initials: L
authors.lastname: Pan
authors.forename: Allison J
authors.initials: AJ
authors.lastname: Nihiser
authors.forename: Sathanur R
authors.initials: SR
authors.lastname: Srinivasan
authors.forename: Gerald S
authors.initials: GS
authors.lastname: Berenson
mesh_terms: D000293:Adolescent; D000367:Age Factors; D001794:Blood Pressure; D001823:Body Composition; D015992:Body Mass Index; D002487:Centers for Disease Control and Prevention, U.S.; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D057238:Growth Charts; D006801:Humans; D008055:Lipids / Q000097:blood; D008137:Longitudinal Studies; D008297:Male; D008403:Mass Screening / Q000379:methods*; D009765:Obesity / Q000175:diagnosis* / Q000453:epidemiology; D015995:Prevalence; D012016:Reference Values; D012307:Risk Factors; D014481:United States / Q000453:epidemiology
chemical_list: D008055:Lipids