Poster Number 176 Other Body Composition Precision with the Lunar iDXA Serge Rezzi, Nestlé Research Center; Fiona Ginty, GE Global Research Center; Maurice Beaumont, Nestle Research Center; Anny Blondel-Lubrano, Nestle Research Center; Sylviane Oguey-Araymon, Nestlé Research Center; Wynn Wacker, GE Healthcare Lunar; Howard Barden, GE Healthcare Lunar; Sunil Kochhar, Nestlé Research Center; Laurent Fay, Nestlé Research Center; David Ergun, GE Healthcare Interest in body composition measurement is increasing as clinicians, nutritionists, <strong>and</strong> researchers recognize the close relation that the distribution of fat <strong>and</strong> lean tissue compartments has on disease risk factors <strong>and</strong> fitness. Baseline measurement of total <strong>and</strong> regional body composition, <strong>and</strong> changes resulting from dietary <strong>and</strong> exercise interventions, drug therapy, disease progression, <strong>and</strong> aging, offer valuable insights for clinical decision-making. Precision error provides a quantitative measure of the ability of densitometry systems to measure change over time. Minimizing precision error reduces least significant change (LSC) <strong>and</strong> time required to detect significant biological change. We measured body composition precision with the Lunar iDXA, a high-resolution dual-energy X-ray absorptiometry (DXA) scanner (GE Healthcare). DXA uses differential attenuation of x-rays at two energy levels to estimate fat, fat-free soft tissue <strong>and</strong> bone mineral content (BMC). We performed 31 paired scans on 24 subjects (8 males <strong>and</strong> 16 females), age 20-49 years, with repositioning between scans. Paired scans from the same subject at different ages were treated as independent for the purpose of this analysis. Region %fat was calculated as fat/(fat + lean + BMC). Precision was calculated using the root-meansquare (RMS) method. The LSC was calculated as SD x 2.77 (95% 2-tailed confidence for the difference between scans). Subjects had mean (SD) age, height, weight, <strong>and</strong> BMI of 35.9 (8.8) years, 167.4 (9.3) cm, 70.0 (12.9) kg, <strong>and</strong> 24.9 (4.1) kg/ht2, respectively. Total body precision error was less than 0.7% for all body composition variables. Regional %fat precision (SD) values were 0.35% for trunk, 0.48% for arms, 0.24% for legs, 0.46% for <strong>and</strong>roid (waist), <strong>and</strong> 0.48% for gynoid (hip) regions. We conclude that the iDXA has excellent precision for total <strong>and</strong> regional body composition. Poster Number 177 Other Body Composition Analysis by Dual-energy X-ray Absortiometry (DXA) in Underweight, Normal, Overweight <strong>and</strong> Obese Mexican Nutrition College Students Raúl Pineda, Pindel Diagnosis; Angélica Delgadillo, Pindel Diagnosis; María Esther Irigoyen, Metropolitan Autonomous University Xochimilco; María del Consuelo Velazquez, Metropolitan Autonomous University Xochimilco Objective: To evaluate body composition (BC) in a group of female nutrition college students <strong>and</strong> to explore the association of Body Mass Index (BMI) related to main BC compartments. Method: Cross- sectional design. Females at a Mexico City University participated. DXA technology was used to evaluate BC (Prodigy Advance, General Electric, USA). Weight <strong>and</strong> height were measured using st<strong>and</strong>ardized protocols. BMI was classified using WHO criteria. Results: 106 females were examined, their mean age was 23.6 years-old (± 2.2), mean BMI , Fat Mass% (FM%), Lean mass (LM), Bone Mineral Density (BMD), Z- Score were: 22.36 Kg/m2, 33.8% (± 6.7) , 18.7Kg (± 6.8), 1.12g/cm2 (±0.07) <strong>and</strong> -0.1 (± 0.89), respectively . Low weight (LW) was detected in 9.4% of the women, 72.7% were normal <strong>and</strong> overweight-obese (OW-O) 17.9%. An association was observed between BMI <strong>and</strong> FM% r= 0.78, (p0.05). BMI <strong>and</strong> BMD showed a positive correlation r=0.43, (p
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