Suppr超能文献

运动传感器在估计儿童和成人能量消耗方面的实用性:使用双标水法的研究的叙述性综述

Usefulness of motion sensors to estimate energy expenditure in children and adults: a narrative review of studies using DLW.

作者信息

Sardinha L B, Júdice P B

机构信息

Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Estrada da Costa, Lisboa, Portugal.

出版信息

Eur J Clin Nutr. 2017 Mar;71(3):331-339. doi: 10.1038/ejcn.2017.2. Epub 2017 Feb 1.

Abstract

It is well documented that meeting moderate-to-vigorous physical activity guidelines of 150 min per week is protective against chronic disease, and this is likely explained by higher energy expenditure (EE). In opposition, sedentary behavior (low EE) seems to impair health outcomes. There are gold standard methods to measure EE such as the doubly labeled water (DLW) or calorimetry. These methods are highly expensive and rely on complex techniques. Motion sensors present a good alternative to estimate EE and have been validated against these reference methods. This review summarizes findings from previous reviews and the most recently published studies on the validity of different motion sensors to estimate physical activity energy expenditure (PAEE) and total energy expenditure (TEE) against DLW, and whether adding other indicators may improve these estimations in children and adults. Regardless of the recognized validity of motion sensors to estimate PAEE and TEE at the group level, individual bias is very high even when combining biometric or physiological indicators. In children, accelerometers explained 13% of DLW's PAEE variance and 31% of TEE variance. In adults, DLW's explained variance was higher, 29 and 44% for PAEE and TEE, respectively. There is no ideal device, but identifying postures seems to be relevant for both children and adults' PAEE estimates. The variance associated with the number of methodological choices that these devices require invite investigators to work with the raw data in order to standardize all these procedures and potentiate the accelerometer signal-derived information. Models that consider biometric covariates seem only to improve TEE estimations, but adding heart rate enhances PAEE estimations in both children and adults.

摘要

有充分的文献记载,达到每周150分钟的中等至剧烈身体活动指南可预防慢性病,这可能是由于更高的能量消耗(EE)所致。相反,久坐行为(低EE)似乎会损害健康结果。有测量EE的金标准方法,如双标水(DLW)法或量热法。这些方法成本高昂且依赖复杂技术。运动传感器是估计EE的良好替代方法,并且已针对这些参考方法进行了验证。本综述总结了先前综述以及最近发表的关于不同运动传感器针对DLW估计身体活动能量消耗(PAEE)和总能量消耗(TEE)的有效性的研究结果,以及添加其他指标是否可以改善儿童和成人的这些估计。尽管运动传感器在群体水平上估计PAEE和TEE的有效性已得到认可,但即使结合生物特征或生理指标,个体偏差仍然很高。在儿童中,加速度计解释了DLW的PAEE方差的13%和TEE方差的31%。在成年人中,DLW解释的方差更高,PAEE和TEE分别为29%和44%。没有理想的设备,但识别姿势似乎与儿童和成人的PAEE估计都相关。这些设备所需的方法选择数量相关的方差促使研究人员处理原始数据,以便标准化所有这些程序并增强加速度计信号衍生的信息。考虑生物特征协变量的模型似乎仅能改善TEE估计,但添加心率可增强儿童和成人的PAEE估计。

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