Refined ambient PM2.5 exposure surrogates and the risk of myocardial infarction

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 PM2.5 with those calculated using central-site PM2.5 concentrations to estimate exposure to PM2.5 of outdoor origin (exposure to ambient PM2.5). Because variability in human activity and indoor PM2.5 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 PM2.5 is modified by residential air exchange rate (AER), a variable that influences the fraction of ambient PM2.5 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 PM2.5. 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 PM2.5 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 PM2.5 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.

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