对时间依赖性暴露的错误分析可以解释PM2.5暴露与痴呆风险之间的关联吗?
Annette M Bachand1, Linda D Dell1
1Ramboll Health Sciences, Amherst, MA, USA.
Journal of Alzheimer's disease : JAD
|February 10, 2024
概括
对颗粒物 (PM2.5) 和痴呆症风险的统计分析可能会偏差,如果不适当考虑时间变化的暴露. 这种偏见,特别是当PM2.5水平随着时间的推移而下降时,可以膨胀危险比率,模仿流行病学研究中的发现.
科学领域:
- 环境流行病学环境流行病学
- 生物统计学 生物统计学
- 神经退行性疾病 神经退行性疾病
背景情况:
- 流行病学研究将长期暴露于细颗粒物 (PM2.5) 与阿尔茨海默病和痴呆症风险的增加联系起来.
- 考克斯比例危险 (PH) 回归是常用的,但它的应用与时间变化的暴露,如PM2.5需要仔细考虑.
- 由于更严格的空气质量标准,户外PM2.5水平普遍下降.
研究的目的:
- 在考克斯PH分析中调查PM2.5和痴呆风险的潜在偏差,当不适当地解决时间变化的暴露时.
- 确定这种偏差是否可以产生与现有流行病学文献中报告的危险比率 (HRs) 相比的危险比率.
主要方法:
- 使用模拟分析来建模时间依赖暴露对统计结果的影响.
- 该研究侧重于在随访期间暴露水平,特别是PM2.5在随访期间变化的场景.
主要成果:
- 考克斯PH分析只考虑在事件时间的暴露,可以产生偏差的危险比率.
- 当PM2.5水平随着时间的推移持续下降时,这种偏差尤其明显.
- 模拟偏差的大小和方向 (远离零) 与PM2.5和痴呆症研究中报告的HRs (1.2-2.0) 相一致.
结论:
- 在PM2.5和痴呆风险研究中的偏差可以通过在整个随访期间准确地分配时间依赖的暴露数据来减轻.
- 敦促研究人员在Cox PH分析中提供透明和详细的方法来处理时间依赖的暴露.
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