title: A prediction equation for estimating body fat percentage using readily accessible measures: a multivariate study of 200 adult women.
abstract: OBJECTIVE
  This study was conducted to develop a regression equation that accurately estimates body fat percentage using relatively easy and inexpensive methods that do not require women to remove clothing.
  
  
  METHODS
  A cross-sectional design was employed.
  
  
  METHODS
  All data were collected at the University.
  
  
  METHODS
  Subjects were 200 white women ages 20 to 65 years. The sample was equally distributed across four age groups, 20-29, 30-39, 40-49, and 50-65, and within each age group, one-third of the women were lean, one-third were of average weight, and one-third were obese.
  
  
  METHODS
  Subjects were hydrostatically weighed and participated in a variety of anthropometric and lifestyle assessments, including skinfolds, circumferences, and questionnaire responses.
  
  
  RESULTS
  The full regression model included six measures: hip circumference, triceps skinfold (observed and quadratic), age (quadratic), self-reported physical activity, and calf skinfold (quadratic). This equation accounted for 81% of the variance in body weight measured by hydrostatic weighing (SEE = 3.5%). A simpler, five-variable equation was also formed that did not include the calf skinfold assessment (R2 = .800, SEE = 3.6%).
  
  
  CONCLUSIONS
  The prediction equations in this study afford accurate and relatively easy and inexpensive means of estimating body fat percentage in a wide range of white women without having them remove their clothing.
authors.affiliation: Brigham Young University, Provo, Utah, USA.
authors.forename: L A
authors.initials: LA
authors.lastname: Tucker
authors.forename: D S
authors.initials: DS
authors.lastname: Demers
authors.forename: K P
authors.initials: KP
authors.lastname: Kelly
mesh_terms: D000273:Adipose Tissue / Q000502:physiology*; D000328:Adult; D000886:Anthropometry / Q000379:methods*; D016022:Case-Control Studies; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D008875:Middle Aged; D008954:Models, Biological; D015999:Multivariate Analysis; D012044:Regression Analysis; D015203:Reproducibility of Results