Cheng Lin1, Kevin J Lane2, Jeffrey K Griffiths1, Doug Brugge3. 1. Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, USA. 2. Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA. 3. Department of Public Health Sciences, University of Connecticut Health Center, Farmington, CT, USA. brugge@uchc.edu.
Abstract
INTRODUCTION: The adverse health outcomes of traffic-related ultrafine particles (UFPs) disproportionally impact near-highway neighborhoods. Current studies focus on either short-term health outcomes associated with short-term UFP exposures averaged over days or weeks, or long-term outcomes associated with long-term (yearly or longer) average UFP exposures. We hypothesized that frequent and repeated exposure to short-term UFP peaks that last for just hours could overwhelm or alter physiological defensive responses, resulting in long-term health issues. Herein, we propose a new exposure metric for measuring the cumulative effect of these peak exposures. METHOD: We used UFP exposure data estimated by the Community Assessment of Freeway Exposure and Health (CAFEH) project, which recruited 704 participants from three pairs of near-highway/urban background neighborhoods in the Greater Boston Area between 2009 and 2012. CAFEH developed land use regression (LUR) models to estimate hourly averages of ambient UFP levels within the study areas based on mobile-monitored UFP data, and applied time-activity adjustment (TAA) to calculate adjusted final hourly estimates. Our alternative metric assigns cumulative peak exposure, which is determined as either the intensity (a high percentile of an individual's adjusted hourly UFP estimates) or the frequency (the number of hours with adjusted UFP estimates greater than a high percentile of all adjusted hourly UFP estimates of all participants in the study area) of UFP peaks. RESULTS: After TAA was applied, for most of the time, our cumulative peak exposure metrics were not strongly correlated with the annual average. However, the level of correlation varied greatly from neighborhood to neighborhood (Spearman's R ranges from 0.39 to 0.97). CONCLUSION: There was variation in UFP peak exposure that was not explained by the annual average, suggesting that our proposed peak metric distinct from annual average exposure metric.
INTRODUCTION: The adverse health outcomes of traffic-related ultrafine particles (UFPs) disproportionally impact near-highway neighborhoods. Current studies focus on either short-term health outcomes associated with short-term UFP exposures averaged over days or weeks, or long-term outcomes associated with long-term (yearly or longer) average UFP exposures. We hypothesized that frequent and repeated exposure to short-term UFP peaks that last for just hours could overwhelm or alter physiological defensive responses, resulting in long-term health issues. Herein, we propose a new exposure metric for measuring the cumulative effect of these peak exposures. METHOD: We used UFP exposure data estimated by the Community Assessment of Freeway Exposure and Health (CAFEH) project, which recruited 704 participants from three pairs of near-highway/urban background neighborhoods in the Greater Boston Area between 2009 and 2012. CAFEH developed land use regression (LUR) models to estimate hourly averages of ambient UFP levels within the study areas based on mobile-monitored UFP data, and applied time-activity adjustment (TAA) to calculate adjusted final hourly estimates. Our alternative metric assigns cumulative peak exposure, which is determined as either the intensity (a high percentile of an individual's adjusted hourly UFP estimates) or the frequency (the number of hours with adjusted UFP estimates greater than a high percentile of all adjusted hourly UFP estimates of all participants in the study area) of UFP peaks. RESULTS: After TAA was applied, for most of the time, our cumulative peak exposure metrics were not strongly correlated with the annual average. However, the level of correlation varied greatly from neighborhood to neighborhood (Spearman's R ranges from 0.39 to 0.97). CONCLUSION: There was variation in UFP peak exposure that was not explained by the annual average, suggesting that our proposed peak metric distinct from annual average exposure metric.
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