title: A multivariate model for predicting segmental body composition.
abstract: The aims of the present study were to propose a multivariate model for predicting simultaneously body, trunk and appendicular fat and lean masses from easily measured variables and to compare its predictive capacity with that of the available univariate models that predict body fat percentage (BF%). The dual-energy X-ray absorptiometry (DXA) dataset (52% men and 48% women) with White, Black and Hispanic ethnicities (1999-2004, National Health and Nutrition Examination Survey) was randomly divided into three sub-datasets: a training dataset (TRD), a test dataset (TED); a validation dataset (VAD), comprising 3835, 1917 and 1917 subjects. For each sex, several multivariate prediction models were fitted from the TRD using age, weight, height and possibly waist circumference. The most accurate model was selected from the TED and then applied to the VAD and a French DXA dataset (French DB) (526 men and 529 women) to assess the prediction accuracy in comparison with that of five published univariate models, for which adjusted formulas were re-estimated using the TRD. Waist circumference was found to improve the prediction accuracy, especially in men. For BF%, the standard error of prediction (SEP) values were 3.26 (3.75) % for men and 3.47 (3.95)% for women in the VAD (French DB), as good as those of the adjusted univariate models. Moreover, the SEP values for the prediction of body and appendicular lean masses ranged from 1.39 to 2.75 kg for both the sexes. The prediction accuracy was best for age < 65 years, BMI < 30 kg/m2 and the Hispanic ethnicity. The application of our multivariate model to large populations could be useful to address various public health issues.
authors.affiliation: INRA, Unité de Recherche MIA, F-78352 Jouy-en-Josas, France.
authors.forename: Simiao
authors.initials: S
authors.lastname: Tian
authors.forename: Laurence
authors.initials: L
authors.lastname: Mioche
authors.forename: Jean-Baptiste
authors.initials: JB
authors.lastname: Denis
authors.forename: Béatrice
authors.initials: B
authors.lastname: Morio
mesh_terms: D015502:Absorptiometry, Photon; D000273:Adipose Tissue; D000328:Adult; D001741:Black or African American; D000367:Age Factors; D000368:Aged; D001823:Body Composition; D001825:Body Fluid Compartments; D015992:Body Mass Index; D005260:Female; D006630:Hispanic or Latino; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015203:Reproducibility of Results; D012737:Sex Factors; D055105:Waist Circumference; D044465:White People