Terry T-K Huang1, Michael P Watkins, Michael I Goran. 1. Energy Metabolism Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, USA.
Abstract
OBJECTIVE: To develop prediction equations for total body fat specific to Latino children, using demographic and anthropometric measures. RESEARCH METHODS AND PROCEDURES: Ninety-six Latino children (7 to 13 years old) were studied. Two-thirds of the sample was randomized into the equation development group; the remainder served as the cross-validation group. Total body fat was measured by DXA. Measures included weight, height, waist and hip circumferences, and skinfolds (suprailiac, triceps, abdomen, subscapula, thigh, and calf). RESULTS: The previously published equation from Dezenberg et al. did not accurately predict total body fat in Latino children. However, newly developed equations with either body weight alone (intercept +/- SE = 1.78 +/- 1.53 kg, p > 0.05; slope +/- SE = 0.90 +/- 0.07, p > 0.05 against slope = 1.0; R(2) = 0.86), weight plus age and gender (intercept +/- SE = 2.28 +/- 1.20 kg, p > 0.05; slope +/- SE = 0.91 +/- 0.05, p > 0.05; against slope = 1.0; R(2) = 0.92), or weight plus height, gender, Tanner stage, and abdominal skinfold (intercept +/- SE = 1.47 +/- 1.01 kg, p > 0.05; slope +/- SE = 0.93 +/- 0.04, p > 0.05; against slope = 1.0, R(2) = 0.97) predicted total body fat without bias. DISCUSSION: Unique prediction equations of total body fat may be needed for Latino children. Weight, as the single most significant predictor, can be used easily to estimate total body fat in the absence of any additional measures. Including age and gender with weight produces an equally stable prediction equation with increasing precision. Using a combination of demographic and anthropometric measures, we were able to capture 97% of the variance in measured total body fat.
RCT Entities:
OBJECTIVE: To develop prediction equations for total body fat specific to Latino children, using demographic and anthropometric measures. RESEARCH METHODS AND PROCEDURES: Ninety-six Latino children (7 to 13 years old) were studied. Two-thirds of the sample was randomized into the equation development group; the remainder served as the cross-validation group. Total body fat was measured by DXA. Measures included weight, height, waist and hip circumferences, and skinfolds (suprailiac, triceps, abdomen, subscapula, thigh, and calf). RESULTS: The previously published equation from Dezenberg et al. did not accurately predict total body fat in Latino children. However, newly developed equations with either body weight alone (intercept +/- SE = 1.78 +/- 1.53 kg, p > 0.05; slope +/- SE = 0.90 +/- 0.07, p > 0.05 against slope = 1.0; R(2) = 0.86), weight plus age and gender (intercept +/- SE = 2.28 +/- 1.20 kg, p > 0.05; slope +/- SE = 0.91 +/- 0.05, p > 0.05; against slope = 1.0; R(2) = 0.92), or weight plus height, gender, Tanner stage, and abdominal skinfold (intercept +/- SE = 1.47 +/- 1.01 kg, p > 0.05; slope +/- SE = 0.93 +/- 0.04, p > 0.05; against slope = 1.0, R(2) = 0.97) predicted total body fat without bias. DISCUSSION: Unique prediction equations of total body fat may be needed for Latino children. Weight, as the single most significant predictor, can be used easily to estimate total body fat in the absence of any additional measures. Including age and gender with weight produces an equally stable prediction equation with increasing precision. Using a combination of demographic and anthropometric measures, we were able to capture 97% of the variance in measured total body fat.
Authors: C A Aguirre; G D C Salazar; D V Lopez de Romaña; J A Kain; C L Corvalán; R E Uauy Journal: Eur J Clin Nutr Date: 2014-08-06 Impact factor: 4.016
Authors: Matheus S Cerqueira; Paulo R S Amorim; Irismar G A Encarnação; Leonardo M T Rezende; Paulo H R F Almeida; Analiza M Silva; Manuel Sillero-Quintana; Diego A S Silva; Fernanda K Santos; João C B Marins Journal: Eat Weight Disord Date: 2022-06-14 Impact factor: 3.008
Authors: S H Kehoe; G V Krishnaveni; H G Lubree; A K Wills; A M Guntupalli; S R Veena; D S Bhat; R Kishore; C H D Fall; C S Yajnik; A Kurpad Journal: Eur J Clin Nutr Date: 2011-07-06 Impact factor: 4.016
Authors: Sílvia M Almeida; José M Furtado; Paulo Mascarenhas; Maria E Ferraz; Luís R Silva; José C Ferreira; Mariana Monteiro; Manuel Vilanova; Fernando P Ferraz Journal: Obes Sci Pract Date: 2016-07-20