Department of Environmental Sciences, Rutgers University, New Brunswick, New Jersey, USA.
J Expo Sci Environ Epidemiol. 2013 Nov-Dec;23(6):573-80. doi: 10.1038/jes.2013.24. Epub 2013 May 29.
Using a case-crossover study design and conditional logistic regression, we compared the relative odds of transmural (full-wall) myocardial infarction (MI) calculated using exposure surrogates that account for human activity patterns and the indoor transport of ambient PM(2.5) with those calculated using central-site PM(2.5) concentrations to estimate exposure to PM(2.5) of outdoor origin (exposure to ambient PM(2.5)). Because variability in human activity and indoor PM(2.5) transport contributes exposure error in epidemiologic analyses when central-site concentrations are used as exposure surrogates, we refer to surrogates that account for this variability as "refined" surrogates. As an alternative analysis, we evaluated whether the relative odds of transmural MI associated with increases in ambient PM(2.5) is modified by residential air exchange rate (AER), a variable that influences the fraction of ambient PM(2.5) that penetrates and persists indoors. Use of refined exposure surrogates did not result in larger health effect estimates (ORs=1.10-1.11 with each interquartile range (IQR) increase), narrower confidence intervals, or better model fits compared with the analysis that used central-site PM(2.5). We did observe evidence for heterogeneity in the relative odds of transmural MI with residential AER (effect-modification), with residents of homes with higher AERs having larger ORs than homes in lower AER tertiles. For the level of exposure-estimate refinement considered here, our findings add support to the use of central-site PM(2.5) concentrations for epidemiological studies that use similar case-crossover study designs. In such designs, each subject serves as his or her own matched control. Thus, exposure error related to factors that vary spatially or across subjects should only minimally impact effect estimates. These findings also illustrate that variability in factors that influence the fraction of ambient PM(2.5) in indoor air (e.g., AER) could possibly bias health effect estimates in study designs for which a spatiotemporal comparison of exposure effects across subjects is conducted.
采用病例交叉研究设计和条件逻辑回归方法，我们比较了考虑人类活动模式和环境 PM（2.5）室内传输的暴露替代物计算的透壁性（全壁）心肌梗死（MI）的相对几率，以及使用中心位置 PM（2.5）浓度计算的相对几率，以估算源自室外的 PM（2.5）的暴露（环境 PM（2.5）暴露）。由于当使用中心位置浓度作为暴露替代物时，人类活动和室内 PM（2.5）传输的变异性会导致流行病学分析中的暴露误差，因此我们将考虑到这种变异性的替代物称为“精细化”替代物。作为替代分析，我们评估了与环境 PM（2.5）增加相关的透壁性 MI 的相对几率是否受住宅空气交换率（AER）的影响，AER 是一个影响穿透并在室内持续存在的环境 PM（2.5）的分数的变量。与使用中心位置 PM（2.5）的分析相比，使用精细化暴露替代物并没有导致更大的健康效应估计值（OR 为每增加一个四分位距（IQR）的 1.10-1.11）、更窄的置信区间或更好的模型拟合度。我们确实观察到住宅 AER 与透壁性 MI 的相对几率之间存在异质性（效应修饰）的证据，住宅 AER 较高的居民的 OR 大于 AER 较低的 tertile 住宅的 OR。对于这里考虑的暴露估计细化程度，我们的研究结果为使用类似病例交叉研究设计的流行病学研究中使用中心位置 PM（2.5）浓度提供了支持。在这种设计中，每个研究对象都作为自己的匹配对照。因此，与空间上或研究对象之间变化的因素有关的暴露误差应最小程度地影响效应估计值。这些发现还表明，影响室内空气中环境 PM（2.5）分数的因素（例如 AER）的变异性可能会在进行跨研究对象暴露效应时空比较的研究设计中导致健康效应估计值的偏差。
