使用生物电阻分析估计身体组成的高标准预测方程:系统审查
Francesco Campa1, Giuseppe Coratella2, Giuseppe Cerullo3
1Department of Biomedical Sciences, University of Padua, Padua, Italy. francesco.campa@unipd.it.
Journal of translational medicine
|May 29, 2024
概括
本综述对生物电阻分析 (BIA) 的身体组成预测方程进行了分类,以帮助从业者选择合适的方法. 它提供了基于不同学科特征和技术的106个方程的最新列表.
科学领域:
- 身体组成分析分析.
- 生物电阻分析 (BIA) 生物电阻分析
- 预测方程分类预测方程的分类.
背景情况:
- 使用BIA准确估计身体成分依赖于适当的预测方程,受受受试者的人口统计和健康状况的影响.
- 存在许多孤立的BIA预测方程,这使得选择最适合特定人群的方程变得复杂.
- 需要进行系统审查,以根据其独立参数对现有的BIA预测方程进行分类.
研究的目的:
- 系统地审查和分类用于生物电阻分析 (BIA) 的预测方程.
- 根据用于身体组成估计的独立参数组织方程.
- 为选择适当的BIA预测方程提供一个全面的资源.
主要方法:
- 对1988年至2023年间发表的研究进行了国际电子数据库的系统搜索.
- 包括的研究提供了由标准方法 (例如,多分区模型,MRI,CT) 衍生的BIA预测方程.
- 如果基于非标准方法或没有特定回归变量的混合群体,则不包括等式.
主要成果:
- 总共有106个预测方程被确定和分类.
- 86个方程使用了脚对手技术,20个使用了细分技术;没有找到手对手和腿对腿技术.
- 方程式按主题特征分类:19个为未成年人,26个为成年人,19个为运动员,26个为老年人,16个为患有疾病的人.
结论:
- 本综述提供了一个最新的,分类列表的BIA预测方程的身体组成评估.
- 该分类有助于从业人员根据受试者的特点选择最合适的方程.
- 鼓励进行进一步的研究,以开发用于代表性不足的场景的新预测方程.
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