在与热相关的健康结果回归模型中,核心体温总结测量的性能
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Updated: Jun 13, 2025

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M Dally1,2, A Dye-Robinson3,4, Y Li3,5
1Centers for Health, Work & Environment, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. miranda.dally@cuanschutz.edu.
农业工人的实时核心体温监测有助于评估热应变. "三角形"测量最好预测肌肉分解,功能和脱水,而AUC表明急性损伤.
科学领域:
- 职业健康 职业健康 职业健康
- 环境健康 环境健康
- 生理监测 生理监测
背景情况:
- 与气候有关的危险对劳动人口构成重大风险.
- 技术进步使实时核心体温 (CBT) 监测在职业环境中成为可能.
- 对纵向CBT数据的有效总结对于理解热应变至关重要.
研究的目的:
- 为了评估核心体温数据的14种不同总结测量的性能.
- 确定运用CBT数据的最佳方法,以预测特定与热有关的健康影响.
- 引导研究人员和从业人员分析职业热应变数据.
主要方法:
- 收集了来自危地马拉128名农业工人的纵向核心体温数据.
- 测量了与热有关的并发健康影响:肌肉衰竭,功能下降和脱水.
- 利用线性混合效应回归模型,并比较使用AIC和BIC的模型性能.
主要成果:
- 没有单一的统计总结统计统一地最好地预测了所有与热有关的健康结果.
- "三角形"测量 (观察到的CBT与初始60分钟平均值之间的差异) 最好预测肌肉分解 (肌酸激酶),功能 (血清肌素) 和脱水 (血清度).
- 曲线下的面积 (AUC) 在识别急性损伤方面表现最好.
结论:
- 总结纵向核心体温数据的最佳方法取决于具体的研究问题和感兴趣的健康结果.
- "三角洲"和AUC的测量结果显示,对于分析职业热应变有前途.
- 这项研究提供了基于证据的建议,用于在职业健康研究中运行可摄入的核心体温药片数据.
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