首页> 外文期刊>The British Journal of Nutrition >Development and validation of anthropometric prediction equations for lean body mass, fat mass and percent fat in adults using the National Health and Nutrition Examination Survey (NHANES) 1999–2006
【24h】

Development and validation of anthropometric prediction equations for lean body mass, fat mass and percent fat in adults using the National Health and Nutrition Examination Survey (NHANES) 1999–2006

机译:瘦体重的发展与验证瘦体重,脂肪质量和成人脂肪脂肪脂肪百分比使用国家健康营养考试调查(NHANES)1999-2006

获取原文
获取原文并翻译 | 示例
           

摘要

Quantification of lean body mass and fat mass can provide important insight into epidemiological research. However, there is no consensus on generalisable anthropometric prediction equations to validly estimate body composition. We aimed to develop and validate practical anthropometric prediction equations for lean body mass, fat mass and percent fat in adults (men, n 7531; women, n 6534) from the National Health and Nutrition Examination Survey 1999–2006. Using a prediction sample, we predicted each of dual-energy X-ray absorptiometry (DXA)-measured lean body mass, fat mass and percent fat based on different combinations of anthropometric measures. The proposed equations were validated using a validation sample and obesity-related biomarkers. The practical equation including age, race, height, weight and waist circumference had high predictive ability for lean body mass (men: R 2=0·91, standard error of estimate (SEE)=2·6 kg; women: R 2=0·85, SEE=2·4 kg) and fat mass (men: R 2=0·90, SEE=2·6 kg; women: R 2=0·93, SEE=2·4 kg). Waist circumference was a strong predictor in men only. Addition of other circumference and skinfold measures slightly improved the prediction model. For percent fat, R 2 were generally lower but the trend in variation explained was similar. Our validation tests showed robust and consistent results with no evidence of substantial bias. Additional validation using biomarkers demonstrated comparable abilities to predict obesity-related biomarkers between direct DXA measurements and predicted scores. Moreover, predicted fat mass and percent fat had significantly stronger associations with obesity-related biomarkers than BMI did. Our findings suggest the potential application of the proposed equations in various epidemiological settings.
机译:瘦体重和脂肪质量的定量可以提供对流行病学研究的重要洞察。然而,在最常见的人体测量预测方程上没有共识,以有效地估计身体组成。我们的旨在从1999 - 2006年国家卫生和营养考试调查中发育和验证成人瘦体重,脂肪质量和脂肪百分比的实际人类群体,脂肪质量和脂肪百分比的预测方程。使用预测样品,我们预测了基于各方位措施的不同组合的双能X射线吸收体(DXA) - 浆化体质量,脂肪质量和脂肪百分比。使用验证样本和肥胖相关的生物标志物进行验证所提出的方程。包括年龄,种族,高度,体重和腰围的实用方程具有高预测瘦体重的能力(男性:R 2 = 0·91,估计的标准误差(见)= 2·6公斤;女性:R 2 = 0·85,见= 2·4千克)和脂肪质量(男性:R 2 = 0·90,见= 2·6公斤;女性:R 2 = 0·93,见= 2·4千克)。腰围只是男性的强烈预测因素。添加其他圆周和肤色措施略微改善预测模型。对于脂肪百分比,R 2通常较低,但解释的变异趋势是相似的。我们的验证测试显示了稳健和一致的结果,没有大幅偏见的证据。使用生物标志物的额外验证表明了预测直接DXA测量和预测分数之间的肥胖相关生物标志物的可比能力。此外,预测的脂肪质量和脂肪百分比与肥胖相关的生物标志物具有明显更强的关联,而不是BMI。我们的研究结果表明,在各种流行病学环境中提出了所提出的方程的潜在应用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号