Suppr超能文献

生物电阻抗还是人体测量学?

Bioimpedance or anthropometry?

作者信息

Diaz E O, Villar J, Immink M, Gonzales T

机构信息

Dunn Nutrition Unit, Medical Research Council, University of Cambridge, UK.

出版信息

Eur J Clin Nutr. 1989 Feb;43(2):129-37.

PMID:2707216
Abstract

The ability of bioimpedance (BIA) to predict body composition in comparison with anthropometric measurements (weight and height) was assessed on three groups of adult young women (n = 99) and one group of adult young men (n = 49). Body fat (BF) and fat-free mass (FFM) by densitometry were used as the reference data. Resistance and reactance separately or together were poor predictors of BF and FFM, explaining from 0 to a maximum of 21 per cent of the FFM variation in the different groups. BF followed the same pattern, though the percentage of variance explained by both variables was even lower. Height squared divided by resistance (H2/R) explained from 22 to 68 per cent of the FFM variation and from 0 to 40 per cent of BF variation. Height alone was comparable to H2/R explaining from 11 to 53 per cent of the FFM variance in the four groups studied. Body weight was found to be the best single predictor of body composition; it explained from 56 to 78 per cent of FFM and 37 to 82 per cent of BF variability. Using stepwise regression analysis with all women combined, weight accounted for 70 per cent of the total FFM variation, with height and H2/R contributing only another 5 per cent. The same was found in men (68 vs 73 per cent respectively). The reported equation of Segal et al. was applied to our group, yielding almost the same high FFM prediction (r2 greater than 0.7 and SEE less than 2.5 kg).(ABSTRACT TRUNCATED AT 250 WORDS)

摘要

在三组成年年轻女性(n = 99)和一组成年年轻男性(n = 49)中,评估了生物电阻抗分析法(BIA)与人体测量学指标(体重和身高)相比预测身体成分的能力。采用密度测量法得出的体脂(BF)和去脂体重(FFM)作为参考数据。单独或联合使用电阻和电抗对BF和FFM的预测效果较差,在不同组中,它们对FFM变化的解释率为0至最高21%。BF呈现相同模式,不过这两个变量对其方差的解释率更低。身高平方除以电阻(H2/R)对FFM变化的解释率为22%至68%,对BF变化的解释率为0至40%。单独的身高与H2/R相当,在研究的四组中对FFM方差的解释率为11%至53%。发现体重是身体成分的最佳单一预测指标;它对FFM变化的解释率为56%至78%,对BF变化的解释率为37%至82%。对所有女性进行逐步回归分析,体重占FFM总变化的70%,身高和H2/R仅另外贡献5%。在男性中也有同样的发现(分别为68%和73%)。将Segal等人报告的方程应用于我们的研究组,得出的FFM预测值几乎同样高(r2大于0.7且标准误小于2.5千克)。(摘要截断于250字)

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验