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  • 标题:A Comparison of Proximity and Land Use Regression Traffic Exposure Models and Wheezing in Infants
  • 作者:Patrick H. Ryan ; Grace K. LeMasters ; Pratim Biswas
  • 期刊名称:Environmental Health Perspectives
  • 印刷版ISSN:0091-6765
  • 电子版ISSN:1552-9924
  • 出版年度:2007
  • 卷号:115
  • 期号:2
  • 页码:278-284
  • DOI:10.1289/ehp.9480
  • 语种:English
  • 出版社:OCR Subscription Services Inc
  • 摘要:Background We previously reported an association between infant wheezing and residence < 100 m from stop-and-go bus and truck traffic. The use of a proximity model, however, may lead to exposure misclassification. Objective Results obtained from a land use regression (LUR) model of exposure to truck and bus traffic are compared with those obtained with a proximity model. The estimates derived from the LUR model were then related to infant wheezing. Methods We derived a marker of diesel combustion—elemental carbon attributable to traffic sources (ECAT)—from ambient monitoring results of particulate matter with aerodynamic diameter < 2.5 μm. We developed a multiple regression model with ECAT as the outcome variable. Variables included in the model were locations of major roads, bus routes, truck traffic count, and elevation. Model parameter estimates were applied to estimate individual ECAT levels at infants’ homes. Results The levels of estimated ECAT at the monitoring stations ranged from 0.20 to 1.02 μg/m3. A LUR model of exposure with a coefficient of determination ( R 2) of 0.75 was applied to infants’ homes. The mean (± SD) ambient exposure of ECAT for infants previously categorized as unexposed, exposed to stop-and-go traffic, or exposed to moving traffic was 0.32 ± 0.06, 0.42 ± 0.14, and 0.49 ± 0.14 μg/m3, respectively. Levels of ECAT from 0.30 to 0.90 μg/m3 were significantly associated with infant wheezing. Conclusions The LUR model resulted in a range of ECAT individually derived for all infants’ homes that may reduce the exposure misclassification that can arise from a proximity model.
  • 关键词:diesel; land; model; proximity; regression; spatial; traffic; use
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