多重回归模型通过人类测量和简单的测量来预测6-12岁儿童的电气生物阻抗变量
Paulo Roberto Santos Lopes1, Gisele Bailich1, Vinicius Layter Xavier2
1Laboratory of Development and Postural Control (LADESCOP), Universidade do Estado de Santa Catarina, Centro de Ciências da Saúde e do Esporte (UDESC/CEFID), Florianópolis, SC, Brazil; Graduation Program in Human Movement Sciences, Universidade do Estado de Santa Catarina, Centro de Ciências da Saúde e do Esporte (UDESC/CEFID), Florianópolis, SC, Brazil.
Clinical nutrition ESPEN
|December 4, 2025
概括
简单的临床测量可以预测儿童的生物电阻分析 (BIA) 变量. 这项研究开发了回归模型来估计儿科患者的身体组成,有助于评估肥胖症.
科学领域:
- 儿童营养学 儿童营养学
- 代谢障碍 代谢障碍 代谢障碍
- 身体组成分析 身体成分分析
背景情况:
- 肥胖是一种普遍存在的全球营养和代谢障碍,影响所有年龄段.
- 生物电阻分析 (BIA) 是评估身体成分的关键工具.
- 准确的BIA预测模型对于理解新陈代谢健康至关重要,特别是在儿童中.
研究的目的:
- 开发和内部验证多重回归模型.
- 用简单的临床和人体测量测量来预测BIA变量.
- 专注于6-12岁的儿童,以准确估计身体组成.
主要方法:
- 观察性横截面研究设计.
- 评估身体质量,身高,BIA,人体周长和皮.
- 多重回归模型是使用逐步方法与Akaike信息标准开发的.
主要成果:
- 评估了128名儿童,包括肥胖,超重和肥胖的儿童.
- 在BIA变量和人类测量测量之间发现了显著的相关性.
- 身体脂肪百分比,骨肌肉质量,总体水分和无脂肪质量显示出最高的相关性.
结论:
- 简单的临床和人体测量测量有效地估计了儿童的BIA变量.
- 开发的回归模型为儿科身体成分分析提供了经过验证的方法.
- 这种方法支持改善儿科人口的肥胖评估和管理.
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