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估计暴露混合物的因果作用:一种通用倾向得分方法

Qian Gao¹, Ting Li¹, Guiming Zhu¹

¹Department of Health Statistics, School of Public Health, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention, Shanxi Medical University, No.56 Xinjian South Road, Taiyuan, 030001, Taiyuan, China.

BMC medical research methodology

|September 30, 2025

概括

一种新的方法,非参数的多变量共变量平衡通用倾向评分 (npmvCBGPS),准确估计多次暴露的因果影响. 这种方法改进了环境流行病学和公共卫生研究的现有方法.

科学领域:

环境流行病学环境流行病学
因果推理的原因推理.
公共卫生公共卫生

背景情况:

估计多次并发暴露的因果影响对于公共卫生干预至关重要.
观测数据分析需要控制混,通常使用通用倾向得分 (GPS) 方法.
对于多次连续暴露的现有GPS方法是有限的.

研究的目的:

提出一种新的因果模型,即非参数的多变量共变量平衡通用倾向得分 (npmvCBGPS),用于估计暴露混合物的影响.
评估npmvCBGPS的性能与现有的多变量GPS (mvGPS) 和线性回归模型相比.

主要方法:

开发了非参数的多变量共变量平衡通用倾向得分 (npmvCBGPS) 模型.
进行模拟研究,将npmvCBGPS与mvGPS和线性回归进行比较.
应用方法来分析对BMI的per-和多甲基物质 (PFAS) 的因果作用.

主要成果:

在所有模拟场景中,npmvCBGPS实现了可接受的共变量平衡.
当暴露或结果模型被正确指定时,npmvCBGPS提供了准确和精确的估计.
在准确性,精度和共变量平衡方面,npmvCBGPS的表现优于mvGPS.
在PFAS混合物和BMI之间观察到显著的反向趋势.

结论:

npmvCBGPS是一种可靠的方法,用于准确估计多次暴露混合物的因果关系.
提出的方法具有广泛的适用性,特别是在环境流行病学中.
这一进步有助于理解复杂的环境暴露及其对健康的影响.

关键词:

因果模型是一种因果模型.暴露-反应暴露-反应概括的倾向得分一般化倾向得分.混合物混合物混合物多重风险多重的风险.

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