Abstract：
Among various aspects of environmental epidemiology, one is to assess the relationships between ambient air pollution and health outcomes. The goal of this work is to estimate the associations in the form of the parametric concentration-response functions (C-RF). Various forms of the C-RFs are proposed in this short-term health effect study. Emergency department (ED) visits for all respiratory health problems are analyzed as an illustrative example. A case-crossover (CC) technique is applied as a study design. Daily cases are organized as daily counts by the same day of the week in one common month. A conditional Poisson regression is used in the constructed statistical models. Temperature and relative humidity are included in the statistical models in the form of natural splines. Ground-level ozone concentration is considered an exposure. Ozone concentration values are transformed and submitted to the statistical models. The parameters of the transformation are determined by using the goodness of fit criterion. Counts of ED visits are analyzed in relation to a sequence of lagged exposure to ozone. The C-RF shapes are constructed for each individual lag. In a final step, the set of the estimated C-RF shapes is used to create a pooled C-RF shape. The results are positive and statistically significant for nine lagged exposures, from 0 to 8 days. The following relative risks (RR) were estimated from the constructed C-RFs at 30 ppb concentration of ozone: RR = 1.0531 (95% confidence interval: 1.0231, 1.0718), 1.0462 (1.0253, 1.0677), and 1.0387, (1.0240, 1.0531), realizing the CC method, CC method + transformation, and CC method + flexible transformation, respectively. The pooled C-RF shape gives a summary of the associations between ED visits for respiratory conditions and ambient ozone. The estimated shapes indicate lower air health effects than the standard CC methods. Among three considered statistical models, the CC method + flexible transformation is the most appropriate to use according to the goodness of fit criterion.
摘要：
在环境流行病学的各个方面，一是评估环境空气污染与健康结果之间的关系。这项工作的目的是以参数浓度响应函数（C-RF）的形式估计关联。在这项短期健康效应研究中提出了各种形式的C-RF。作为说明性示例，对所有呼吸健康问题的急诊科（ED）访问进行了分析。案例交叉(CC)技术被用作研究设计。在一个普通月份的一周的同一天，每日病例被组织为每日计数。在构建的统计模型中使用条件泊松回归。温度和相对湿度以自然样条的形式包含在统计模型中。地面臭氧浓度被认为是暴露。转换臭氧浓度值并提交给统计模型。通过使用拟合优度准则来确定变换的参数。分析ED访问次数与一系列滞后的臭氧暴露有关。为每个单独的滞后构造C-RF形状。在最后一步，估计的C-RF形状的集合用于创建汇集的C-RF形状。对于9个滞后暴露，结果是积极的，具有统计学意义，从0到8天。以下相对风险（RR）从构建的C-RFs在30ppb浓度的臭氧：RR=1.0531（95％置信区间：1.0231，1.0718），1.0462（1.0253，1.0677），和1.0387，（1.0240，1.0531），实现CC方法，CC方法+转换，和CC方法+灵活转换，分别。汇集的C-RF形状总结了ED对呼吸状况和环境臭氧的访问之间的关联。估计的形状表明比标准CC方法更低的空气健康影响。在三个考虑的统计模型中，根据拟合优度准则，CC方法+柔性变换是最合适的。
