Investigating the effects of multiple exposure measures to traffic-related air pollution on the risk of breast and prostate cancer

Traffic-related nitrogen dioxide (NO2) has been traditionally estimated using surfaces generated through land-use regression (LUR). Recently, air pollution dispersion has been used to derive NO2 exposures in urban areas. There is evidence that data collection protocols and modelling assumptions can have a large effect on the resulting NO2 spatial distribution. This study investigates the effects of various NO2 surfaces on the risk estimates of postmenopausal breast cancer (BC) and prostate cancer (PC), both of which have already been associated with traffic-related air pollution. We derived exposures for individuals in two case control studies in Montreal, Canada using four different surfaces for NO2. Two of the surfaces were developed using LUR but employed different data collection protocols (LUR-1 and LUR-2), and the other two surfaces were generated using dispersion modelling; one with a regional model (dispersion-1) and another with a street canyon model (dispersion-2). Also, we estimated separate odds ratios (ORs) using concentrations of NO2 as measures of exposure for both cancers. While the range of NO2 concentrations from dispersion (4–26 ppb) was lower than the range from LUR (4–36 ppb), the four surfaces were found to be moderately correlated, with Spearman correlation coefficients ranging from 0.76 to 0.88. The ORs for BC were estimated to be 1.26, 1.10, 1.07, and 1.05 based on LUR-1, LUR-2, dispersion-1, and dispersion-2. In contrast, the ORs for PC were estimated to be 1.39, 1.30, 1.13, and 1.04 based on LUR-1, LUR-2, dispersion-1, and dispersion-2. The four exposure measures indicated positive associations but we observed higher mean ORs based on the LUR surfaces albeit with overlapping CIs. Since LUR models capture all sources of NO2 and dispersion models only capture traffic emissions, it is possible that this difference is due to the fact that non-road sources also contribute to the spatial distribution in NO2 concentrations.

[1]  Bert Brunekreef,et al.  A Comparison of Different Approaches to Estimate Small-Scale Spatial Variation in Outdoor NO2 Concentrations , 2010, Environmental health perspectives.

[2]  F. Saad,et al.  Metabolic syndrome and prostate cancer risk in a population-based case–control study in Montreal, Canada , 2015, BMC Public Health.

[3]  Dan L. Crouse,et al.  A prediction-based approach to modelling temporal and spatial variability of traffic-related air pollution in Montreal, Canada , 2009 .

[4]  C. Baynes,et al.  A Hospital‐Based Case‐Control Study of Stillbirths and Environmental Exposure to Arsenic Using an Atmospheric Dispersion Model Linked to a Geographical Information System , 1998, Epidemiology.

[5]  Marianne Hatzopoulou,et al.  Investigating the Use Of Portable Air Pollution Sensors to Capture the Spatial Variability Of Traffic-Related Air Pollution. , 2016, Environmental science & technology.

[6]  P. Elliott,et al.  A regression-based method for mapping traffic-related air pollution: application and testing in four contrasting urban environments. , 2000, The Science of the total environment.

[7]  Altaf Arain,et al.  A review and evaluation of intraurban air pollution exposure models , 2005, Journal of Exposure Analysis and Environmental Epidemiology.

[8]  M. Brauer,et al.  The impact of daily mobility on exposure to traffic-related air pollution and health effect estimates , 2011, Journal of Exposure Science and Environmental Epidemiology.

[9]  M. Brauer,et al.  Three Measures of Forest Fire Smoke Exposure and Their Associations with Respiratory and Cardiovascular Health Outcomes in a Population-Based Cohort , 2011, Environmental health perspectives.

[10]  Bruce Misstear,et al.  Comparison of particulate matter dose and acute heart rate variability response in cyclists, pedestrians, bus and train passengers. , 2014, The Science of the total environment.

[11]  S. Moebus,et al.  Comparison of Land-Use Regression Modeling with Dispersion and Chemistry Transport Modeling to Assign Air Pollution Concentrations within the Ruhr Area , 2016 .

[12]  Marita Voogt,et al.  Comparison of the performances of land use regression modelling and dispersion modelling in estimating small-scale variations in long-term air pollution concentrations in a Dutch urban area. , 2010 .

[13]  Bert Brunekreef,et al.  GIS-Based Estimation of Exposure to Particulate Matter and NO2 in an Urban Area: Stochastic versus Dispersion Modeling , 2005, Environmental health perspectives.

[14]  I. Tager,et al.  Population intervention models to estimate ambient NO2 health effects in children with asthma , 2014, Journal of Exposure Science and Environmental Epidemiology.

[15]  Joachim Eichhorn,et al.  The numerical flow model MISKAM: State of development and evaluation of the basic version , 2010 .

[16]  B. Oftedal,et al.  Lung cancer and air pollution: a 27 year follow up of 16 209 Norwegian men , 2003, Thorax.

[17]  Luc Int Panis,et al.  Land use regression models as a tool for short, medium and long term exposure to traffic related air pollution. , 2014, The Science of the total environment.

[18]  Naveen Eluru,et al.  Modelling the Spatio-Temporal Distribution of Ambient Nitrogen Dioxide and Investigating the Effects of Public Transit Policies on Population Exposure , 2017, Environ. Model. Softw..

[19]  Simon Kingham,et al.  Using mobile monitoring to visualise diurnal variation of traffic pollutants across two near-highway neighbourhoods , 2014 .

[20]  Michael Brauer,et al.  Within-urban variability in ambient air pollution: Comparison of estimation methods , 2008 .

[21]  Stephen G. Ritchie,et al.  Environmental Impacts of a Major Freight Corridor , 2009 .

[22]  A. Tjønneland,et al.  Chronic obstructive pulmonary disease and long-term exposure to traffic-related air pollution: a cohort study. , 2011, American journal of respiratory and critical care medicine.

[23]  Michael Brauer,et al.  Traffic-related air pollution and incident asthma in a high-risk birth cohort , 2010, Occupational and Environmental Medicine.

[24]  Shunqin Wang,et al.  Association of Traffic-Related Air Pollution with Children’s Neurobehavioral Functions in Quanzhou, China , 2009, Environmental health perspectives.

[25]  A. Tjønneland,et al.  Air Pollution from Traffic and Risk for Lung Cancer in Three Danish Cohorts , 2010, Cancer Epidemiology, Biomarkers & Prevention.

[26]  A. Cimorelli,et al.  AERMOD: A Dispersion Model for Industrial Source Applications. Part I: General Model Formulation and Boundary Layer Characterization. , 2005 .

[27]  Bert Brunekreef,et al.  Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe - The ESCAPE project , 2013 .

[28]  Kai Zhang,et al.  Prediction and analysis of near-road concentrations using a reduced-form emission/dispersion model , 2010, Environmental health : a global access science source.

[29]  M. Brauer,et al.  Traffic-related air pollution and the development of asthma and allergies during the first 8 years of life. , 2010, American journal of respiratory and critical care medicine.

[30]  A. Cohen,et al.  Lung Cancer and Exposure to Nitrogen Dioxide and Traffic: A Systematic Review and Meta-Analysis , 2015, Environmental health perspectives.

[31]  Luc Int Panis,et al.  Disaggregation of nation-wide dynamic population exposure estimates in The Netherlands: Applications of activity-based transport models , 2009 .

[32]  John S. Gulliver,et al.  Comparative assessment of GIS-based methods and metrics for estimating long-term exposures to air pollution , 2011 .

[33]  C. Paciorek,et al.  Evaluating heterogeneity in indoor and outdoor air pollution using land-use regression and constrained factor analysis. , 2010, Research report.

[34]  Simon Kingham,et al.  Mapping Urban Air Pollution Using GIS: A Regression-Based Approach , 1997, Int. J. Geogr. Inf. Sci..

[35]  R. Burnett,et al.  Long-Term Exposure to Traffic-Related Air Pollution and Cardiovascular Mortality , 2013, Epidemiology.

[36]  Marianne Hatzopoulou,et al.  Spatial variations in ambient ultrafine particle concentrations and the risk of incident prostate cancer: A case‐control study , 2017, Environmental research.

[37]  Pietro Salizzoni,et al.  The model SIRANE for atmospheric urban pollutant dispersion; part I, presentation of the model , 2011 .

[38]  Brigitte Roberge,et al.  Cross-sensitivities of electrochemical detectors used to monitor worker exposures to airborne contaminants: false positive responses in the absence of target analytes. , 2006, Journal of environmental monitoring : JEM.

[39]  Zhi Ning,et al.  Experimental and numerical study of the dispersion of motor vehicle pollutants under idle condition , 2005 .

[40]  D. Altman,et al.  STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT , 1986, The Lancet.

[41]  Bert Brunekreef,et al.  Land use regression models for estimating individual NOx and NO₂ exposures in a metropolis with a high density of traffic roads and population. , 2014, The Science of the total environment.

[42]  Mark S Goldberg,et al.  Traffic-related air pollution and prostate cancer risk: a case–control study in Montreal, Canada , 2013, Occupational and Environmental Medicine.

[43]  Naveen Eluru,et al.  Land-use and socio-economics as determinants of traffic emissions and individual exposure to air pollution , 2013 .

[44]  W James Gauderman,et al.  Childhood Asthma and Exposure to Traffic and Nitrogen Dioxide , 2005, Epidemiology.

[45]  G. Pershagen,et al.  Using geographic information systems to assess individual historical exposure to air pollution from traffic and house heating in Stockholm. , 2001, Environmental health perspectives.

[46]  Shamsunnahar Yasmin,et al.  Investigating the role of transportation models in epidemiologic studies of traffic related air pollution and health effects. , 2015, Environmental research.

[47]  Michelle L Bell,et al.  The use of ambient air quality modeling to estimate individual and population exposure for human health research: a case study of ozone in the Northern Georgia Region of the United States. , 2006, Environment international.

[48]  Peter Steer,et al.  Using continuous sampling to examine the distribution of traffic related air pollution in proximity to a major road , 2011 .

[49]  E. Miller,et al.  Linking an activity-based travel demand model with traffic emission and dispersion models: Transport’s contribution to air pollution in Toronto , 2010 .

[50]  Beate Ritz,et al.  Comparing exposure assessment methods for traffic-related air pollution in an adverse pregnancy outcome study. , 2011, Environmental research.

[51]  Jaakko Kukkonen,et al.  Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies. , 2014, Environment international.

[52]  Michael Brauer,et al.  Long-Term Exposure to Traffic-Related Air Pollution and the Risk of Coronary Heart Disease Hospitalization and Mortality , 2011 .

[53]  J. Gulliver,et al.  A review of land-use regression models to assess spatial variation of outdoor air pollution , 2008 .

[54]  M. Brauer,et al.  A land use regression model for ultrafine particles in Vancouver, Canada. , 2013, Environmental science & technology.

[55]  J. McDonald,et al.  Air pollution & the brain: Subchronic diesel exhaust exposure causes neuroinflammation and elevates early markers of neurodegenerative disease , 2011, Journal of Neuroinflammation.

[56]  S. Weichenthal,et al.  Traffic-Related Air Pollution and Acute Changes in Heart Rate Variability and Respiratory Function in Urban Cyclists , 2011, Environmental health perspectives.

[57]  M. Goldberg,et al.  Postmenopausal Breast Cancer Is Associated with Exposure to Traffic-Related Air Pollution in Montreal, Canada: A Case–Control Study , 2010, Environmental health perspectives.

[58]  Marianne Hatzopoulou,et al.  Integrating a street-canyon model with a regional Gaussian dispersion model for improved characterisation of near-road air pollution , 2017 .

[59]  Michael Brauer,et al.  Centre for Health Services and Policy Research, and , 2022 .

[60]  Maya Milliez,et al.  Numerical simulations of pollutant dispersion in an idealized urban area, for different meteorological conditions , 2007 .