A spatiotemporal case-crossover model of asthma exacerbation in the City of Houston.

A spatiotemporal case-crossover model of asthma exacerbation in the City of Houston.
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DOI:
10.1002/sta4.357
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发表时间:
2021-12
期刊:
影响因子:
1.7
通讯作者:
Ensor, Katherine B.
Ensor, Katherine B.
中科院分区:
数学4区
文献类型:
--
作者:
Schedler, Julia C.;Ensor, Katherine B.

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病例交叉设计是一种流行的结构,用于分析瞬时效应(如环境污染水平)对急性结果(如哮喘急性发作)的影响。病例交叉设计通过将病例作为其自身的“对照”,避免了对病例的个体、时变风险因素建模的需要,选择的时间段可以假设个体风险因素为常数,无需建模。许多研究已经检查了控制期结构对模型性能的复杂影响,但是当研究参与者之间的暴露量被认为是恒定的时,当病例交叉设计被证明等同于泊松回归的各种规格时,这些讨论被简化了。虽然对于某些应用是合理的,但在某些情况下,由于暴露的空间变异性,这种假设不适用,这可能会影响参数估计。本文提出了一种时空模型,该模型具有时间上的案例交叉和基于Hausdorff距离的几何感知空间随机效应。模型的建设采用了残留的空间结构的情况下,当恒定的假设曝光是不合理的,当空间区域是不规则的。
Case‐crossover design is a popular construction for analyzing the impact of a transient effect, such as ambient pollution levels, on an acute outcome, such as an asthma exacerbation. Case‐crossover design avoids the need to model individual, time‐varying risk factors for cases by using cases as their own ‘controls’, chosen to be time periods for which individual risk factors can be assumed constant and need not be modelled. Many studies have examined the complex effects of the control period structure on model performance, but these discussions were simplified when case‐crossover design was shown to be equivalent to various specifications of Poisson regression when exposure is considered constant across study participants. While reasonable for some applications, there are cases where such an assumption does not apply due to spatial variability in exposure, which may affect parameter estimation. This work presents a spatiotemporal model, which has temporal case‐crossover and a geometrically aware spatial random effect based on the Hausdorff distance. The model construction incorporates a residual spatial structure in cases when the constant assumption exposure is not reasonable and when spatial regions are irregular.
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