Diesel Exposure Model Reduces Allergy Risk Assessment Errors
Many prior air pollution studies rely heavily on what are known as proximity (distance) exposure models, which assume all subjects in a given distance from an exposure sourcefor example, a major interstate highwayare equally exposed.
Pat Ryan, lead author of the UC study, says that isnt necessarily true in urban environments, where infants are exposed to a large number of pollutants, and he advocates using the so-called land-use regression model.
Unlike proximity models, says Ryan, land use regression lets us consider more complex exposure factorslike elevation and the type or number of passing vehiclesin our initial assessment. This allows us to create buffers around specific sample sites and control for factors influencing that locations overall diesel exposure levels.
Specific models are needed for evaluating exposure levels in large cities to accurately determine exposure levels and identify populations at risk for high exposure to air pollutants, Ryan says.
He will present the UC teams findings at the annual meeting of the
Ryan and his coauthors analyzed data from 622 infants enrolled in the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) who were identified as being at greater risk for developing allergies because at least one of their parents had allergies.
The CCAAPS, funded by the National Institute of Environmental Health Sciences, is a five-year study examining the effects of environmental particulates and certain types of traffic on childhood respiratory health and allergy development. All infants in the study had at least one parent with known allergies.
Researchers found that infants who were exposed to the highest levels of elemental carbona marker of diesel exposurewere more than twice as likely to wheeze compared with the infants exposed to lower levels, which was reported in the February 2007 issue of Environmental Health Perspectives.
Research has shown that diesel exhaust particles (DEP), breathable particles able to absorb and transport proteins, aggravate rhinitis (hayfever) and asthma symptoms.
Accurate exposure classifications are imperative in studies of air pollution, and the land use regression model allows us to use our sampled measurements to predict a specific locations exposure level whereas proximity studies do not take sampled levels into account nor do they examine other important factors, like wind direction or elevation.
Collaborators in the study are UCs Grace LeMasters, PhD, principal investigator of the CCAAPS, Linda Levin, Mark Lindsey, David Bernstein, MD, James Lockey, MD, Manuel Villareal, MD and Sergey Grinshpun, PhD, as well as Pratim Biswas, PhD, and Shaohua Hu of
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