| Literature DB >> 32882467 |
Grant M Tinsley1, Abbie E Smith-Ryan2, Youngdeok Kim3, Malia N M Blue2, Brett S Nickerson4, Matthew T Stratton5, Patrick S Harty5.
Abstract
Common body composition estimation techniques necessitate assumptions of uniform fat-free mass (FFM) characteristics, although variation due to sex, race, and body characteristics may occur. National Health and Nutrition Examination Survey data from 1999 to 2004, during which paired dual-energy x-ray absorptiometry (DXA) and bioimpedance spectroscopy assessments were performed, were used to estimate FFM characteristics in a sample of 4619 US adults. Calculated FFM characteristics included the density and water, bone mineral, and residual content of FFM. A rapid 4-component model was also produced using DXA and bioimpedance spectroscopy data. Study variables were compared across sex, race/ethnicity, body mass index (BMI), and age categories using multiple pairwise comparisons. A general linear model was used to estimate body composition after controlling for other variables. Statistical analyses accounted for 6-year sampling weights and complex sampling design of the National Health and Nutrition Examination Survey and were based on 5 multiply imputed datasets. Differences in FFM characteristics across sex, race, and BMI were observed, with notable dissimilarities between men and women for all outcome variables. In racial/ethnic comparisons, non-Hispanic blacks most commonly presented distinct FFM characteristics relative to other groups, including greater FFM density and proportion of bone mineral. Body composition errors between DXA and the 4-component model were significantly influenced by sex, age, race, and BMI. In conclusion, FFM characteristics, which are often assumed in body composition estimation methods, vary due to sex, race/ethnicity, and weight status. The variation of FFM characteristics in diverse populations should be considered when body composition is evaluated.Entities:
Keywords: Body composition; Ethnicity; Obesity; Overweight; Race
Mesh:
Year: 2020 PMID: 32882467 DOI: 10.1016/j.nutres.2020.07.002
Source DB: PubMed Journal: Nutr Res ISSN: 0271-5317 Impact factor: 3.315