使用参数g计算用于时间到事件数据和分布式滞后模型来识别早产的临界暴露窗口:在以东马萨诸塞州 (2011-2016) 为基础的回顾性出生队列中使用的一个说明性示例
Michael Leung1, Marc G Weisskopf1,2, Anna M Modest3,4
1Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Environmental health perspectives
|July 12, 2024
概括
在怀孕期间减少细颗粒物,特别是5-20周,可以降低早产风险. 这种新的g-survival-DLM方法有助于研究空气污染对健康的影响.
科学领域:
- 环境流行病学环境流行病学
- 生殖健康 生殖健康
- 生物统计学 生物统计学
背景情况:
- 参数g计算对于研究空气污染对健康的影响是有用的,但在探索暴露窗口方面存在局限性.
- 现有的方法缺乏将复杂的滞后反应整合到g计算中的生存数据的能力.
研究的目的:
- 引入一个新的框架,g-survival-DLM,将分布式滞后模型 (DLMs) 与生存数据的参数g计算相结合.
- 评估怀孕期间暴露于细颗粒物 (PM) 与早产 (PTB) 风险之间的关联.
- 为g-survival-DLM方法提供一个实用的实施指南,使用R语法.
主要方法:
- 在9,403次分娩的队列中应用了g-生存-DLM方法.
- 估计了假设每周平均PM2.5减少20%对PTB风险的影响.
- 根据社会人口统计,时间趋势,二氧化和温度进行调整.
主要成果:
- 假设的干预措施将PM2.5降低20%,与36周后累积PTB风险降低0.01 (95%CI:0.003,0.017) 相关.
- 这意味着该队列中PTB人数减少了86人.
- 对于PM2.5对PTB风险的影响,在妊娠5-20周之间确定了关键暴露窗口.
结论:
- 在g-生存-DLM方法提供可解释的,与政策相关的空气污染和健康研究的估计.
- 这种方法通过将PTB视为时间到事件结果来防止不朽的时间偏差.
- 在特定的妊娠周 (5-20) 中减少PM2.5暴露显示了降低PTB风险的潜力.
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