Using meta-smoothing to estimate dose-response trends across multiple studies, with application to air pollution and daily death
Using meta-smoothing to estimate dose-response trends across multiple studies, with application to air pollution and daily death
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DOI：
10.1097/00001648-200011000-00009
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发表时间：
2000-11-01
期刊：
影响因子：
5.4
通讯作者：
Zanobetti, A
中科院分区：
文献类型：
--
作者：
Schwartz, J;Zanobetti, A
在过去的十年中，许多研究中的空气污染与乳制品死亡率有关。尽管非常关注这些关联中潜在混淆的问题，但几乎没有采取任何措施来解决剂量反应关系的形状的问题。关于这些关系和许多其他流行病学问题，这些关系是否存在阈值的问题特别关注。非参数平滑被广泛用于控制协变量和乳制品死亡之间的潜在非线性关系，但很少被用来建模空气污染关联。由于采样变异性（除其他因素）可以在线性剂量响应曲线的估计值中引入相当大的噪声，因此已广泛使用定量摘要来进行。搭配最佳线性拟合。元分析技术平均噪声的能力适用于各个城市中的非参数平滑估计。我们已经开发了一种将这些技术应用于非参数平滑剂的方法。使用仿真研究，我们表明该方法可以检测流行病学研究中的阈值和其他非线性关系，然后我们将其应用于分析PM10之间的关联，以及在美国十个城市的每日死亡。我们发现该关联似乎是线性的，直至研究中观察到的最低启示。该方法通常适用于可以组合多个研究数据的设置。
Air pollution has been associated with dairy mortality in numerous studies over the last decade. Although considerable attention has focused on issues of potential confounding in these associations, little has been done to address the question of what the shape of the dose-response relation looks Like. The question of whether a threshold exists for these relations is of particular concern, with regard to both this application and many other epidemiologic questions. Nonparametric smoothing is widely used to control for the potentially nonlinear relations between covariates and dairy deaths but has been little used to model the air pollution associations. Because sampling variability, among other factors, can introduce considerable noise into the estimates of linear dose-response curves, quantitative summaries have been widely used to come. up with best linear fits. The same ability of mete-analytic techniques to average out noise applies to nonparametric smooth estimates in individual cities. We have developed a method of applying these techniques to combining nonparametric smooths. Using simulation studies, we show that this method can detect threshold and other nonlinear relations in epidemiologic studies, and we then apply it to analyze the association between PM10, and daily deaths in ten U.S. cities. We find that the association appears linear down to the lowest revels observed in the study. This method is generally applicable in settings where data from multiple studies can be combined.