Vinson R Lee1, Rob M Blew1, Josh N Farr1, Rita Tomas1, Timothy G Lohman1, Scott B Going2. 1. University of Arizona, College of Medicine, Department of Physiology, Tucson, AZ. 2. University of Arizona, College of Agriculture and Life Sciences, Department of Nutritional Sciences, Tucson, AZ.
Abstract
OBJECTIVE: Assess the utility of peripheral quantitative computed tomography (pQCT) for estimating whole body fat in adolescent girls. RESEARCH METHODS AND PROCEDURES: Our sample included 458 girls (aged 10.7 ± 1.1y, mean BMI = 18.5 ± 3.3 kg/m2) who had DXA scans for whole body percent fat (DXA %Fat). Soft tissue analysis of pQCT scans provided thigh and calf subcutaneous percent fat and thigh and calf muscle density (muscle fat content surrogates). Anthropometric variables included weight, height and BMI. Indices of maturity included age and maturity offset. The total sample was split into validation (VS; n = 304) and cross-validation (CS; n = 154) samples. Linear regression was used to develop prediction equations for estimating DXA %Fat from anthropometric variables and pQCT-derived soft tissue components in VS and the best prediction equation was applied to CS. RESULTS: Thigh and calf SFA %Fat were positively correlated with DXA %Fat (r = 0.84 to 0.85; p <0.001) and thigh and calf muscle densities were inversely related to DXA %Fat (r = -0.30 to -0.44; p < 0.001). The best equation for estimating %Fat included thigh and calf SFA %Fat and thigh and calf muscle density (adj. R2 = 0.90; SEE = 2.7%). Bland-Altman analysis in CS showed accurate estimates of percent fat (adj. R2 = 0.89; SEE = 2.7%) with no bias. DISCUSSION: Peripheral QCT derived indices of adiposity can be used to accurately estimate whole body percent fat in adolescent girls.
OBJECTIVE: Assess the utility of peripheral quantitative computed tomography (pQCT) for estimating whole body fat in adolescent girls. RESEARCH METHODS AND PROCEDURES: Our sample included 458 girls (aged 10.7 ± 1.1y, mean BMI = 18.5 ± 3.3 kg/m2) who had DXA scans for whole body percent fat (DXA %Fat). Soft tissue analysis of pQCT scans provided thigh and calf subcutaneous percent fat and thigh and calf muscle density (muscle fat content surrogates). Anthropometric variables included weight, height and BMI. Indices of maturity included age and maturity offset. The total sample was split into validation (VS; n = 304) and cross-validation (CS; n = 154) samples. Linear regression was used to develop prediction equations for estimating DXA %Fat from anthropometric variables and pQCT-derived soft tissue components in VS and the best prediction equation was applied to CS. RESULTS: Thigh and calfSFA %Fat were positively correlated with DXA %Fat (r = 0.84 to 0.85; p <0.001) and thigh and calf muscle densities were inversely related to DXA %Fat (r = -0.30 to -0.44; p < 0.001). The best equation for estimating %Fat included thigh and calfSFA %Fat and thigh and calf muscle density (adj. R2 = 0.90; SEE = 2.7%). Bland-Altman analysis in CS showed accurate estimates of percent fat (adj. R2 = 0.89; SEE = 2.7%) with no bias. DISCUSSION: Peripheral QCT derived indices of adiposity can be used to accurately estimate whole body percent fat in adolescent girls.
Entities:
Keywords:
adolescent girls; body composition; dual energy x-ray absorptiometry (DXA); percent fat
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