Modeling the Residential Infiltration of Outdoor PM2.5 in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiologic studies of fine particulate matter [aerodynamic diameter <= 2.5 mu m (PM2.5)] typically use outdoor concentrations as exposure surrogates. Failure to account for variation in residential infiltration efficiencies (F-inf) will affect epidemiologic study results. OBJECTIVE: We aimed to develop models to predict F-inf for > 6,000 homes in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air), a prospective cohort study of PM2.5 exposure, subclinical cardiovascular disease, and clinical outcomes. METHODS: We collected 526 two-week, paired indoor-outdoor PM2.5 filter samples from a subset of study homes. PM2.5 elemental composition was measured by X-ray fluorescence, and F-inf was estimated as the indoor/outdoor sulfur ratio. We regressed F-inf on meteorologic variables and questionnaire-based predictors in season-specific models. Models were evaluated using the R-2 and root mean square error (RMSE) from a 10-fold cross-validation. RESULTS: The mean +/- SD F-inf across all communities and seasons was 0.62 +/- 0.21, and community-specific means ranged from 0.47 +/- 0.15 in Winston-Salem, North Carolina, to 0.82 +/- 0.14 in New York, New York. F-inf was generally greater during the warm (> 18 degrees C) season. Central air conditioning (AC) use, frequency of AC use, and window opening frequency were the most important predictors during the warm season; outdoor temperature and forced-air heat were the best cold-season predictors. The models predicted 60% of the variance in 2-week F-inf, with an RMSE of 0.13. CONCLUSIONS: We developed intuitive models that can predict F-inf using easily obtained variables. Using these models, MESA Air will be the first large epidemiologic study to incorporate variation in residential F-inf into an exposure assessment.