Confounding by Conception Seasonality in Studies of Temperature and Preterm Birth: A Simulation Study.
Confounding by Conception Seasonality in Studies of Temperature and Preterm Birth: A Simulation Study.
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温度和早产研究中受孕季节性的混杂：模拟研究。
DOI：
10.1097/ede.0000000000001588
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Darrow,LyndseyA
中科院分区：
文献类型：
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作者：
Huang,Mengjiao;Strickland,MatthewJ;Richards,Megan;Warren,JoshuaL;Chang,HowardH;Darrow,LyndseyA
背景：季节性受孕模式可能会混淆出生结果与季节性暴露之间的急性关联。我们的目的是评估四种流行病学设计（时间分层病例交叉、时间序列、配对病例对照和事件时间），这些设计通常用于研究环境温度和早产之间的急性关联。方法：我们进行了模拟，假设温度对早产没有影响。我们从观察到的美国出生季节模式中生成伪出生数据，并使用设计特定的季节性调整来分析它们与观察到的温度的关系。结果：采用病例交叉方法（按日历月进行时间分层），我们观察到暖季（5 - 9月）平均气温每升高10℃，回归系数的偏差（在1000个重复中）= 0.016（蒙特卡洛标准误差95% CI: 0.015-0.018）。使用时间序列方法获得的无偏估计需要考虑有风险的怀孕及其加权出生概率。值得注意的是，将时间序列模型中的每日出生加权概率添加到病例交叉模型中，纠正了病例交叉方法中的偏差。在配对病例对照设计中，暴露期与妊娠期窗匹配，我们没有观察到偏倚。时间到事件的方法也是无偏的，但比其他方法的计算量更大。结论：大多数设计都可以通过一种方式来实现，产生不受概念季节性影响的估计。时间分层病例交叉设计显示出小的正偏倚，这可能有助于但不能完全解释先前报道的关联。
Background:Seasonal patterns of conception may confound acute associations between birth outcomes and seasonally varying exposures. We aim to evaluate four epidemiologic designs (time-stratified case-crossover, time-series, pair-matched case-control, and time-to-event) commonly used to study acute associations between ambient temperature and preterm births.Methods:We conducted simulations assuming no effect of temperature on preterm birth. We generated pseudo-birth data from the observed seasonal patterns of birth in the United States and analyzed them in relation to observed temperatures using design-specific seasonality adjustments.Results:Using the case-crossover approach (time-stratified by calendar month), we observed a bias (among 1,000 replicates)= 0.016 (Monte-Carlo standard error 95% CI: 0.015–0.018) in the regression coefficient for every 10 C increase in mean temperature in the warm season (May–September). Unbiased estimates obtained using the time-series approach required accounting for both the pregnancies-at-risk and their weighted probability of birth. Notably, adding the daily weighted probability of birth from the time-series models to the case-crossover models corrected the bias in the case-crossover approach. In the pair-matched case-control design, where the exposure period was matched on gestational window, we observed no bias. The time-to-event approach was also unbiased but was more computationally intensive than others.Conclusions:Most designs can be implemented in a way that yields estimates unbiased by conception seasonality. The time-stratified case-crossover design exhibited a small positive bias, which could contribute to, but not fully explain, previously reported associations.