Baxter Lisa K, Crooks James L, Sacks Jason D
National Health and Environmental Effects Research Laboratory, United States Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27711, USA.
Present address: Division of Biostatistics and Bioinformatics and Department of Biomedical Research, National Jewish Health, 1400 Jackson St., Denver, CO, 80206, USA.
Environ Health. 2017 Jan 4;16(1):1. doi: 10.1186/s12940-016-0208-y.
Multi-city population-based epidemiological studies have observed heterogeneity between city-specific fine particulate matter (PM)-mortality effect estimates. These studies typically use ambient monitoring data as a surrogate for exposure leading to potential exposure misclassification. The level of exposure misclassification can differ by city affecting the observed health effect estimate.
The objective of this analysis is to evaluate whether previously developed residential infiltration-based city clusters can explain city-to-city heterogeneity in PM mortality risk estimates. In a prior paper 94 cities were clustered based on residential infiltration factors (e.g. home age/size, prevalence of air conditioning (AC)), resulting in 5 clusters. For this analysis, the association between PM and all-cause mortality was first determined in 77 cities across the United States for 2001-2005. Next, a second stage analysis was conducted evaluating the influence of cluster assignment on heterogeneity in the risk estimates.
Associations between a 2-day (lag 0-1 days) moving average of PM concentrations and non-accidental mortality were determined for each city. Estimated effects ranged from -3.2 to 5.1% with a pooled estimate of 0.33% (95% CI: 0.13, 0.53) increase in mortality per 10 μg/m increase in PM. The second stage analysis determined that cluster assignment was marginally significant in explaining the city-to-city heterogeneity. The health effects estimates in cities with older, smaller homes with less AC (Cluster 1) and cities with newer, smaller homes with a large prevalence of AC (Cluster 3) were significantly lower than the cluster consisting of cities with older, larger homes with a small percentage of AC.
This is the first study that attempted to examine whether multiple exposure factors could explain the heterogeneity in PM-mortality associations. The results of this study were found to explain a small portion (6%) of this heterogeneity.
基于多城市人群的流行病学研究观察到特定城市的细颗粒物（PM）-死亡率效应估计值之间存在异质性。这些研究通常使用环境监测数据作为暴露的替代指标，这可能导致潜在的暴露错误分类。暴露错误分类的程度可能因城市而异，从而影响观察到的健康效应估计值。
本分析的目的是评估先前基于住宅渗透情况划分的城市集群能否解释PM死亡率风险估计值在城市间的异质性。在之前的一篇论文中，根据住宅渗透因素（如房屋年龄/面积、空调（AC）普及率）对94个城市进行了聚类，形成了5个集群。在本分析中，首先确定了2001 - 2005年美国77个城市中PM与全因死亡率之间的关联。接下来，进行了第二阶段分析，评估集群归属对风险估计值异质性的影响。
确定了每个城市PM浓度的2天（滞后0 - 1天）移动平均值与非意外死亡率之间的关联。估计效应范围为 - 3.2%至5.1%，每增加10μg/m的PM，死亡率汇总估计增加0.33%（95%置信区间：0.13，0.53）。第二阶段分析确定，集群归属在解释城市间异质性方面具有边际显著性。房屋老旧、面积较小且空调使用较少的城市（集群1）以及房屋较新、面积较小且空调普及率较高的城市（集群3）的健康效应估计值显著低于由房屋老旧、面积较大且空调使用比例较小的城市组成的集群。
这是第一项试图研究多种暴露因素能否解释PM - 死亡率关联异质性的研究。本研究结果发现只能解释这种异质性的一小部分（6%）。
