Suppr超能文献

基于人体测量学的婴儿从出生到 6 个月期间体脂预测:Baby-bod 研究。

Anthropometry-based prediction of body fat in infants from birth to 6 months: the Baby-bod study.

机构信息

School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, TAS, 7250, Australia.

出版信息

Eur J Clin Nutr. 2021 Apr;75(4):715-723. doi: 10.1038/s41430-020-00768-3. Epub 2020 Oct 14.

Abstract

BACKGROUND/OBJECTIVES: Prediction equations generated from anthropometric measures are frequently used to quantify paediatric body composition. We tested the agreeability and predictive power of select (Lingwood and Aris) fat mass prediction equations against body fat measured via ADP; and generated and evaluated new anthropometry-based models for use in the first 6 months of life.

SUBJECTS/METHODS: Data were obtained from 278 white European Australian infants at birth, 3 and 6 months. Prediction models (i.e. Baby-bod models) were generated for each time point via stepwise linear regression and compared for agreeability with ADP via limits of agreement, mean difference and total bias in Bland-Altman analyses. Predictive power of all equations in comparison to ADP were assessed using linear regression analysis.

RESULTS

Overall, there was poor agreeability between percent body fat predicted via published equations and ADP. Proportional bias was detected for both methods (i.e. published equations and Baby-bod models) of body fat prediction. At birth, both Lingwood and BB0 equations overestimated percent body fat at the lower end of the FM spectrum. This trend was repeated at 3 months with all equations displaying a propensity to overestimate body fat at lower FM levels and underestimate at higher FM levels.

CONCLUSIONS

The results indicate that anthropometry, although less costly and relatively easier to implement, does not always produce comparable results with objective measures such as ADP. Given the importance of the accurate assessment of physical growth, including body composition in early life, it is timely to recommend the increased utilisation of techniques such as ADP.

摘要

背景/目的:基于人体测量学指标生成的预测方程常用于量化儿童的身体成分。我们检验了特定(Lingwood 和 Aris)脂肪质量预测方程与通过 ADP 测量的体脂之间的一致性和预测能力;并生成和评估了新的基于人体测量学的模型,用于生命的前 6 个月。

对象/方法:数据来自于 278 名欧洲白种澳大利亚出生婴儿、3 个月和 6 个月时的数据。通过逐步线性回归为每个时间点生成预测模型(即 Baby-bod 模型),并通过一致性界限、平均差异和 Bland-Altman 分析中的总偏差来评估与 ADP 的一致性。使用线性回归分析评估所有方程与 ADP 的预测能力。

结果

总体而言,通过已发表的方程和 ADP 预测的体脂百分比之间一致性较差。两种体脂预测方法(即已发表的方程和 Baby-bod 模型)都存在比例偏差。在出生时,Lingwood 和 BB0 方程都高估了 FM 谱低端的体脂百分比。这种趋势在 3 个月时再次出现,所有方程都显示出在较低的 FM 水平高估体脂和在较高的 FM 水平低估体脂的倾向。

结论

结果表明,尽管人体测量学成本较低且相对更容易实施,但并不总是能与 ADP 等客观测量方法产生可比的结果。鉴于准确评估身体生长,包括生命早期的身体成分的重要性,及时建议增加 ADP 等技术的使用是适时的。

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