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Effect of early life exposure to air pollution on development of childhood asthma.

https://arctichealth.org/en/permalink/ahliterature145670
Source
Environ Health Perspect. 2010 Feb;118(2):284-90
Publication Type
Article
Date
Feb-2010
Author
Nina Annika Clark
Paul A Demers
Catherine J Karr
Mieke Koehoorn
Cornel Lencar
Lillian Tamburic
Michael Brauer
Author Affiliation
School of Population and Public Health, University of British Columbia, British Columbia, Canada.
Source
Environ Health Perspect. 2010 Feb;118(2):284-90
Date
Feb-2010
Language
English
Publication Type
Article
Keywords
Air Pollution - adverse effects
Asthma - chemically induced
British Columbia
Carbon Monoxide - adverse effects
Case-Control Studies
Child, Preschool
Environmental Exposure - adverse effects
Female
Humans
Logistic Models
Male
Nitrogen Dioxide - adverse effects
Nitrogen Oxides - adverse effects
Particulate Matter - adverse effects
Pregnancy
Prenatal Exposure Delayed Effects - chemically induced
Time Factors
United States
Abstract
There is increasing recognition of the importance of early environmental exposures in the development of childhood asthma. Outdoor air pollution is a recognized asthma trigger, but it is unclear whether exposure influences incident disease. We investigated the effect of exposure to ambient air pollution in utero and during the first year of life on risk of subsequent asthma diagnosis in a population-based nested case-control study.
We assessed all children born in southwestern British Columbia in 1999 and 2000 (n = 37,401) for incidence of asthma diagnosis up to 34 years of age using outpatient and hospitalization records. Asthma cases were age- and sex-matched to five randomly chosen controls from the eligible cohort. We estimated each individual's exposure to ambient air pollution for the gestational period and first year of life using high-resolution pollution surfaces derived from regulatory monitoring data as well as land use regression models adjusted for temporal variation. We used logistic regression analyses to estimate effects of carbon monoxide, nitric oxide, nitrogen dioxide, particulate matter
Notes
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Comment In: Environ Health Perspect. 2010 Feb;118(2):A8020123625
Comment In: Environ Health Perspect. 2010 Jul;118(7):A283-420601332Camatini, Marina [removed]; Bolzacchini, Ezio [removed]
PubMed ID
20123607 View in PubMed
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The impact of daily mobility on exposure to traffic-related air pollution and health effect estimates.

https://arctichealth.org/en/permalink/ahliterature142520
Source
J Expo Sci Environ Epidemiol. 2011 Jan-Feb;21(1):42-8
Publication Type
Article
Author
Eleanor Setton
Julian D Marshall
Michael Brauer
Kathryn R Lundquist
Perry Hystad
Peter Keller
Denise Cloutier-Fisher
Author Affiliation
Geography Department, University of Victoria, Victoria, British Columbia, Canada. elsetton@uvic.ca
Source
J Expo Sci Environ Epidemiol. 2011 Jan-Feb;21(1):42-8
Language
English
Publication Type
Article
Keywords
Air Pollutants - analysis
Air Pollution - analysis - statistics & numerical data
Bias (epidemiology)
British Columbia
California
Environmental Exposure - analysis - statistics & numerical data
Environmental Monitoring - methods
Humans
Nitrogen Dioxide - analysis
Residence Characteristics
Time Factors
Urban health
Vehicle Emissions - analysis
Abstract
Epidemiological studies of traffic-related air pollution typically estimate exposures at residential locations only; however, if study subjects spend time away from home, exposure measurement error, and therefore bias, may be introduced into epidemiological analyses. For two study areas (Vancouver, British Columbia, and Southern California), we use paired residence- and mobility-based estimates of individual exposure to ambient nitrogen dioxide, and apply error theory to calculate bias for scenarios when mobility is not considered. In Vancouver, the mean bias was 0.84 (range: 0.79-0.89; SD: 0.01), indicating potential bias of an effect estimate toward the null by ~16% when using residence-based exposure estimates. Bias was more strongly negative (mean: 0.70, range: 0.63-0.77, SD: 0.02) when the underlying pollution estimates had higher spatial variation (land-use regression versus monitor interpolation). In Southern California, bias was seen to become more strongly negative with increasing time and distance spent away from home (e.g., 0.99 for 0-2?h spent at least 10?km away, 0.66 for = 10?h spent at least 40?km away). Our results suggest that ignoring daily mobility patterns can contribute to bias toward the null hypothesis in epidemiological studies using individual-level exposure estimates.
PubMed ID
20588325 View in PubMed
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Long-term residential exposure to air pollution and lung cancer risk.

https://arctichealth.org/en/permalink/ahliterature113862
Source
Epidemiology. 2013 Sep;24(5):762-72
Publication Type
Article
Date
Sep-2013
Author
Perry Hystad
Paul A Demers
Kenneth C Johnson
Richard M Carpiano
Michael Brauer
Author Affiliation
School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada. phystad@gmail.com
Source
Epidemiology. 2013 Sep;24(5):762-72
Date
Sep-2013
Language
English
Publication Type
Article
Keywords
Aged
Air Pollution - adverse effects
Canada - epidemiology
Case-Control Studies
Environmental Exposure - statistics & numerical data
Female
Humans
Incidence
Lung Neoplasms - epidemiology
Male
Middle Aged
Models, Biological
Nitrogen Dioxide - adverse effects
Ozone - adverse effects
Particulate Matter - adverse effects
Residence Characteristics - statistics & numerical data
Risk assessment
Spatio-Temporal Analysis
Time Factors
Abstract
There is accumulating evidence that air pollution causes lung cancer. Still, questions remain about exposure misclassification, the components of air pollution responsible, and the histological subtypes of lung cancer that might be produced.
We investigated lung cancer incidence in relation to long-term exposure to three ambient air pollutants and proximity to major roads, using a Canadian population-based case-control study. We compared 2,390 incident, histologically confirmed lung cancer cases with 3,507 population controls in eight Canadian provinces from 1994 to 1997. We developed spatiotemporal models for the whole country to estimate annual residential exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) over a 20-year exposure period. We carried out a subanalysis in urban centers, using exposures derived from fixed-site air pollution monitors, and also examined traffic proximity measures. Hierarchical logistic regression models incorporated a comprehensive set of individual and geographic covariates.
The increase in lung cancer incidence (expressed as fully adjusted odds ratios [ORs]) was 1.29 (95% confidence interval = 0.95-1.76) with a ten-unit increase in PM2.5 (µg/m), 1.11 (1.00-1.24) with a ten-unit increase in NO2 (ppb), and 1.09 (0.85-1.39) with a ten-unit increase in O3 (ppb). The urban monitor-based subanalyses generally supported the national results, with larger associations for NO2 (OR = 1.34; 1.07-1.69) per 10 ppb increase. No dose-response trends were observed, and no clear relationships were found for specific histological cancer subtypes. There was the suggestion of increased risk among those living within 100 m of highways, but not among those living near major roads.
Lung cancer incidence in this Canadian study was increased most strongly with NO2 and PM2.5 exposure. Further investigation is needed into possible effects of O3 on development of lung cancer.
Notes
Comment In: Epidemiology. 2014 Jan;25(1):15924296934
Comment In: Epidemiology. 2014 Jan;25(1):159-6024296935
PubMed ID
23676262 View in PubMed
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Neighbourhood socioeconomic status and individual lung cancer risk: evaluating long-term exposure measures and mediating mechanisms.

https://arctichealth.org/en/permalink/ahliterature106487
Source
Soc Sci Med. 2013 Nov;97:95-103
Publication Type
Article
Date
Nov-2013
Author
Perry Hystad
Richard M Carpiano
Paul A Demers
Kenneth C Johnson
Michael Brauer
Author Affiliation
School of Population and Public Health, University of British Columbia, 2206 East Mall, Vancouver, BC, Canada V6T 1Z3. Electronic address: phystad@gmail.com.
Source
Soc Sci Med. 2013 Nov;97:95-103
Date
Nov-2013
Language
English
Publication Type
Article
Keywords
Aged
Canada - epidemiology
Case-Control Studies
Environmental Exposure - statistics & numerical data
Female
Health Status Disparities
Humans
Lung Neoplasms - epidemiology
Male
Middle Aged
Residence Characteristics - statistics & numerical data
Risk assessment
Risk factors
Smoking - psychology
Social Class
Time Factors
Urban Health - statistics & numerical data
Abstract
Neighbourhood socioeconomic status (SES) has been associated with numerous chronic diseases, yet little information exists on its association with lung cancer incidence. This outcome presents two key empirical challenges: a long latency period that requires study participants' residential histories and long-term neighbourhood characteristics; and adequate data on many risk factors to test hypothesized mediating pathways between neighbourhood SES and lung cancer incidence. Analysing data on urban participants of a large Canadian population-based lung cancer case-control study, we investigate three issues pertaining to these challenges. First, we examine whether there is an association between long-term neighbourhood SES, derived from 20 years of residential histories and five national censuses, and lung cancer incidence. Second, we determine how this long-term neighbourhood SES association changes when using neighbourhood SES measures based on different latency periods or at time of study entry. Third, we estimate the extent to which long-term neighbourhood SES is mediated by a range of individual-level smoking behaviours, other health behaviours, and environmental and occupational exposures. Results of hierarchical logistic regression models indicate significantly higher odds of lung cancer cases residing in the most compared to the least deprived quintile of the long-term neighbourhood SES index (OR: 1.46; 95% CI: 1.13-1.89) after adjustment for individual SES. This association remained significant (OR: 1.38; 1.01-1.88) after adjusting for smoking behaviour and other known and suspected lung cancer risk factors. Important differences were observed between long-term and study entry neighbourhood SES measures, with the latter attenuating effect estimates by over 50 percent. Smoking behaviour was the strongest partial mediating pathway of the long-term neighbourhood SES effect. This research is the first to examine the effects of long-term neighbourhood SES on lung cancer risk and more research is needed to further identify specific, modifiable pathways by which neighbourhood context may influence lung cancer risk.
PubMed ID
24161094 View in PubMed
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Spatiotemporal air pollution exposure assessment for a Canadian population-based lung cancer case-control study.

https://arctichealth.org/en/permalink/ahliterature125484
Source
Environ Health. 2012;11:22
Publication Type
Article
Date
2012
Author
Perry Hystad
Paul A Demers
Kenneth C Johnson
Jeff Brook
Aaron van Donkelaar
Lok Lamsal
Randall Martin
Michael Brauer
Author Affiliation
School of Population and Public Health, University of British Columbia, 2206 East Mall, Vancouver, BC V6T 1Z3, Canada. phystad@gmail.com
Source
Environ Health. 2012;11:22
Date
2012
Language
English
Publication Type
Article
Keywords
Air Pollution - adverse effects - analysis
Canada - epidemiology
Case-Control Studies
Demography
Environmental Exposure - adverse effects - analysis
Environmental Monitoring - methods
Epidemiological Monitoring
Humans
Lung Neoplasms - epidemiology - etiology
Models, Theoretical
Nitric Oxide - adverse effects - analysis
Particulate Matter - adverse effects - analysis
Retrospective Studies
Risk assessment
Spacecraft
Time Factors
Abstract
Few epidemiological studies of air pollution have used residential histories to develop long-term retrospective exposure estimates for multiple ambient air pollutants and vehicle and industrial emissions. We present such an exposure assessment for a Canadian population-based lung cancer case-control study of 8353 individuals using self-reported residential histories from 1975 to 1994. We also examine the implications of disregarding and/or improperly accounting for residential mobility in long-term exposure assessments.
National spatial surfaces of ambient air pollution were compiled from recent satellite-based estimates (for PM2.5 and NO2) and a chemical transport model (for O3). The surfaces were adjusted with historical annual air pollution monitoring data, using either spatiotemporal interpolation or linear regression. Model evaluation was conducted using an independent ten percent subset of monitoring data per year. Proximity to major roads, incorporating a temporal weighting factor based on Canadian mobile-source emission estimates, was used to estimate exposure to vehicle emissions. A comprehensive inventory of geocoded industries was used to estimate proximity to major and minor industrial emissions.
Calibration of the national PM2.5 surface using annual spatiotemporal interpolation predicted historical PM2.5 measurement data best (R2 = 0.51), while linear regression incorporating the national surfaces, a time-trend and population density best predicted historical concentrations of NO2 (R2 = 0.38) and O3 (R2 = 0.56). Applying the models to study participants residential histories between 1975 and 1994 resulted in mean PM2.5, NO2 and O3 exposures of 11.3 µg/m3 (SD = 2.6), 17.7 ppb (4.1), and 26.4 ppb (3.4) respectively. On average, individuals lived within 300 m of a highway for 2.9 years (15% of exposure-years) and within 3 km of a major industrial emitter for 6.4 years (32% of exposure-years). Approximately 50% of individuals were classified into a different PM2.5, NO2 and O3 exposure quintile when using study entry postal codes and spatial pollution surfaces, in comparison to exposures derived from residential histories and spatiotemporal air pollution models. Recall bias was also present for self-reported residential histories prior to 1975, with cases recalling older residences more often than controls.
We demonstrate a flexible exposure assessment approach for estimating historical air pollution concentrations over large geographical areas and time-periods. In addition, we highlight the importance of including residential histories in long-term exposure assessments. For submission to: Environmental Health.
Notes
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PubMed ID
22475580 View in PubMed
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