评估金属混合物对神经心理发展的影响:复杂性和可解释性之间的权衡
Susana Diaz-Coto1, Leyre Notario-Barandiaran2, Pablo Martinez-Camblor3
1Department of Orthopaedics, Dartmouth Health. Geisel School of Medicine at Dartmouth, NH, USA.
International journal of hygiene and environmental health
|October 22, 2025
概括
线性回归模型有效评估金属混合物对儿童神经发育的影响,类似于复杂的贝叶斯核机器回归 (BKMR). 这简化了对环境暴露和发展结果的理解.
科学领域:
- 环境健康 环境健康
- 神经科学是一个神经科学.
- 生物统计学 生物统计学
背景情况:
- 评估金属混合物的健康影响是复杂的.
- 像贝叶斯内核机器回归 (BKMR) 这样的复杂的统计方法被使用,但难以解释.
- 了解金属混合物对幼儿神经发育的影响至关重要.
研究的目的:
- 评估先进的统计技术的可行性和可解释性,以评估金属混合物暴露对神经心理发展的影响.
- 将BKMR的结果与传统的线性回归模型 (LRM) 进行比较.
主要方法:
- 横截面研究设计. 截面研究设计.
- 主要组件分析 (PCA) 用于识别神经发育领域.
- 贝叶斯核心机器回归 (BKMR) 和线性回归模型 (LRM) 被采用并进行了比较.
- 分析的重点是,和混合物的暴露.
主要成果:
- 在执行,运动和视觉/语言功能的BKMR和LRM估计之间发现了高相关性 (0.92-0.95).
- 模型之间的差异很小,主要是低和不同度的.
- 结果表明金属之间存在线性关联,而不是金属之间的高阶相互作用.
结论:
- 线性回归模型提供了与BKMR等复杂方法可比的结果,用于评估金属混合物对神经发育的影响.
- 像LRM这样的简单模型可以更好地了解金属暴露的个体和相互作用效应.
- 这支持在环境健康研究中使用可访问的统计方法.
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