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.

中文翻译：

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美国成年人的无脂肪质量特征因性别、种族和体重状况而异

常见的身体成分估计技术需要假设均匀的无脂肪质量 (FFM) 特征，尽管可能会因性别、种族和身体特征而发生变化。1999 年至 2004 年的国家健康和营养检查调查数据，在此期间进行了配对双能 X 射线吸收测定法 (DXA) 和生物阻抗谱评估，用于估计 4619 名美国成年人样本的 FFM 特征。计算得出的 FFM 特征包括密度和水、骨矿物质和 FFM 的残留含量。还使用 DXA 和生物阻抗光谱数据生成了一个快速的 4 分量模型。研究变量在性别、种族/民族、体重指数 (BMI) 和年龄类别之间使用多个成对比较进行了比较。在控制其他变量后，使用通用线性模型来估计身体成分。统计分析考虑了国家健康和营养检查调查的 6 年抽样权重和复杂抽样设计，并基于 5 个多重插补数据集。观察到不同性别、种族和 BMI 的 FFM 特征存在差异，男性和女性在所有结果变量上均存在显着差异。在种族/族裔比较中，非西班牙裔黑人最常表现出与其他群体不同的实况调查特征，包括更高的实况调查密度和骨矿物质比例。DXA 和 4 分量模型之间的身体成分误差受性别、年龄、种族和 BMI 显着影响。总之，在身体成分估计方法中经常假设的 FFM 特征，因性别、种族/民族和体重状况而异。在评估身体成分时，应考虑不同人群中 FFM 特征的变化。