带指数修正的分布滞后交互模型
Distributed Lag Interaction Model with Index Modification
AI总结：
本文提出带指数修正的分布滞后交互模型，在贝叶斯框架下同时估计修饰因子权重与暴露-时间-响应函数，并通过模拟和两个出生队列数据验证其优于现有方法。
摘要：
流行病学证据支持孕期及出生时暴露于空气污染与儿童健康结局之间存在关联。通常，此类关联通过使用分布滞后模型将结局对孕期每日或每周的暴露测量值进行回归来估计。然而，这些关联可能受到多种因素的效应修饰。我们提出了一种带指数修正的分布滞后交互模型，该模型允许通过多个修饰因子的加权平均对函数型预测变量的效应修饰进行建模。我们的模型能够在贝叶斯分层框架中通过样条交叉基同时估计修饰因子指数权重和暴露-时间-响应函数。通过模拟研究，我们表明当存在多个重要性未知的修饰因子时，我们的模型优于竞争方法。我们将所提出的方法应用于科罗拉多州出生队列，以估计出生体重与空气污染之间的关联，该关联受到邻里脆弱性指数的修饰；并应用于墨西哥出生队列，以估计分娩父母心脏代谢终点与空气污染之间的关联，该关联受到分娩父母终生压力指数的修饰。
英文摘要：
Epidemiological evidence supports an association between exposure to air pollution during pregnancy and birth and child health outcomes. Typically, such associations are estimated by regressing an outcome on daily or weekly measures of exposure during pregnancy using a distributed lag model. However, these associations may be modified by multiple factors. We propose a distributed lag interaction model with index modification that allows for effect modification of a functional predictor by a weighted average of multiple modifiers. Our model allows for simultaneous estimation of modifier index weights and the exposure-time-response function via a spline cross-basis in a Bayesian hierarchical framework. Through simulations, we showed that our model out-performs competing methods when there are multiple modifiers of unknown importance. We applied our proposed method to a Colorado birth cohort to estimate the association between birth weight and air pollution modified by a neighborhood-vulnerability index and to a Mexican birth cohort to estimate the association between birthing-parent cardio-metabolic endpoints and air pollution modified by a birthing-parent lifetime stress index.
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