Most of the models developed to study the effects of pollutants on the health of people are single input and single outcome while adjusting for other variables. However, the real environment is a mixture of pollutants, which affect people synergistically and varies in time and space. The aim of this work is to introduce a multiple exposures-outcomes tree regression method. An oblique tree with Weighted Oblique Decision Trees (WODT) algorithm was designed to find the share effects of pollutant(s) on health outcomes and investigate the temporal and spatial differences. Using this method, a case study was conducted on the association between O 3 , NO 2 , PM 2.5 and asthma, COPD, pneumonia, and bronchitis in CA, USA. The results indicated that NO 2 and O 3 are responsible for asthma emergency department (ED) visits in South Coast and San Diego Air Basins during January–April and October–December for the years 2005–2015. For PM 2.5 , the results indicated that an increase in concentration was associated with an increase in the number of ED visits for COPD and pneumonia during January–December in the whole study area. The method introduced in this study is useful in handling multi-pollutant exposure conditions. Using this method, public health agencies and policy makers can better understand the relative effects of multiple pollutants on the health of people in temporal and spatial scales.

中文翻译：

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多污染物模型：适用于研究环境流行病学中复杂关系的方法

大多数用于研究污染物对人类健康影响的模型都是单一输入和单一结果，同时针对其他变量进行调整。然而，真实的环境是污染物的混合物，它们协同作用于人，并在时间和空间上变化。这项工作的目的是介绍一种多重曝光-结果树回归方法。带有加权倾斜决策树 (WODT) 算法的倾斜树旨在发现污染物对健康结果的份额影响并调查时空差异。使用这种方法，在美国加利福尼亚州对 O 3 、NO 2 、PM 2.5 与哮喘、COPD、肺炎和支气管炎之间的关联进行了案例研究。结果表明，在 2005-2015 年的 1-4 月和 10-12 月期间，NO 2 和 O 3 负责南海岸和圣地亚哥空气盆地的哮喘急诊科 (ED) 就诊。对于 PM 2.5 ，结果表明浓度的增加与整个研究区域 1 月至 12 月期间因 COPD 和肺炎就诊的急诊次数增加有关。本研究中介绍的方法可用于处理多污染物暴露条件。使用这种方法，公共卫生机构和政策制定者可以更好地了解多种污染物在时空尺度上对人们健康的相对影响。结果表明，浓度的增加与整个研究区域 1 月至 12 月期间因 COPD 和肺炎就诊的急诊次数增加有关。本研究中介绍的方法可用于处理多污染物暴露条件。使用这种方法，公共卫生机构和政策制定者可以更好地了解多种污染物在时空尺度上对人们健康的相对影响。结果表明，浓度的增加与整个研究区域 1 月至 12 月期间因 COPD 和肺炎就诊的急诊次数增加有关。本研究中介绍的方法可用于处理多污染物暴露条件。使用这种方法，公共卫生机构和政策制定者可以更好地了解多种污染物在时空尺度上对人们健康的相对影响。