Background: Exposure to wildfire smoke has been associated with cardiopulmonary health impacts. Climate change will increase the severity and frequency of smoke events, suggesting a need for enhanced public health protection. Forecasts of smoke exposure can facilitate public health responses.
Objectives: We evaluated the utility of a wildfire smoke forecasting system (BlueSky) for public health protection by comparing its forecasts with observations and assessing their associations with population-level indicators of respiratory health in British Columbia, Canada.
Methods: We compared BlueSky PM2.5 forecasts with PM2.5 measurements from air quality monitors, and BlueSky smoke plume forecasts with plume tracings from National Oceanic and Atmospheric Administration Hazard Mapping System remote sensing data. Daily counts of the asthma drug salbutamol sulfate dispensations and asthma-related physician visits were aggregated for each geographic local health area (LHA). Daily continuous measures of PM2.5 and binary measures of smoke plume presence, either forecasted or observed, were assigned to each LHA. Poisson regression was used to estimate the association between exposure measures and health indicators.
Results: We found modest agreement between forecasts and observations, which was improved during intense fire periods. A 30-μg/m3 increase in BlueSky PM2.5 was associated with an 8% increase in salbutamol dispensations and a 5% increase in asthma-related physician visits. BlueSky plume coverage was associated with 5% and 6% increases in the two health indicators, respectively. The effects were similar for observed smoke, and generally stronger in very smoky areas.
Conclusions: BlueSky forecasts showed modest agreement with retrospective measures of smoke and were predictive of respiratory health indicators, suggesting they can provide useful information for public health protection.
Citation: Yao J, Brauer M, Henderson SB. 2013. Evaluation of a wildfire smoke forecasting system as a tool for public health protection. Environ Health Perspect 121:1142–1147; http://dx.doi.org/10.1289/ehp.1306768
Exposure to traffic-related air pollution (TRAP) can adversely impact health but epidemiologic studies are limited in their abilities to assess long-term exposures and incorporate variability in indoor pollutant infiltration.
In order to examine settled house dust levels of hopanes, engine lubricating oil byproducts found in vehicle exhaust, as a novel TRAP exposure measure, dust samples were collected from 171 homes in five Canadian cities and analyzed by gas chromatography–mass spectrometry. To evaluate source contributions, the relative abundance of the highest concentration hopane monomer in house dust was compared to that in outdoor air. Geographic variables related to TRAP emissions and outdoor NO2 concentrations from city-specific TRAP land use regression (LUR) models were calculated at each georeferenced residence location and assessed as predictors of variability in dust hopanes.
Hopanes relative abundance in house dust and ambient air were significantly correlated (Pearson’s r=0.48, p<0.05), suggesting that dust hopanes likely result from traffic emissions. The proportion of variance in dust hopanes concentrations explained by LUR NO2 was less than 10% in Vancouver, Winnipeg and Toronto while the correlations in Edmonton and Windsor explained 20 to 40% of the variance. Modeling with household factors such as air conditioning and shoe removal along with geographic predictors related to TRAP generally increased the proportion of explained variability (10-80%) in measured indoor hopanes dust levels.
Hopanes can consistently be detected in house dust and may be a useful tracer of TRAP exposure if determinants of their spatiotemporal variability are well-characterized, and when home-specific factors are considered.
Air pollution; Dust; Exposure assessment; Hopanes; Land use regression; Traffic
Background: A growing body of evidence has associated maternal exposure to air pollution with adverse effects on fetal growth; however, the existing literature is inconsistent.
Objectives: We aimed to quantify the association between maternal exposure to particulate air pollution and term birth weight and low birth weight (LBW) across 14 centers from 9 countries, and to explore the influence of site characteristics and exposure assessment methods on between-center heterogeneity in this association.
Methods: Using a common analytical protocol, International Collaboration on Air Pollution and Pregnancy Outcomes (ICAPPO) centers generated effect estimates for term LBW and continuous birth weight associated with PM10 and PM2.5 (particulate matter ≤ 10 and 2.5 µm). We used meta-analysis to combine the estimates of effect across centers (~ 3 million births) and used meta-regression to evaluate the influence of center characteristics and exposure assessment methods on between-center heterogeneity in reported effect estimates.
Results: In random-effects meta-analyses, term LBW was positively associated with a 10-μg/m3 increase in PM10 [odds ratio (OR) = 1.03; 95% CI: 1.01, 1.05] and PM2.5 (OR = 1.10; 95% CI: 1.03, 1.18) exposure during the entire pregnancy, adjusted for maternal socioeconomic status. A 10-μg/m3 increase in PM10 exposure was also negatively associated with term birth weight as a continuous outcome in the fully adjusted random-effects meta-analyses (–8.9 g; 95% CI: –13.2, –4.6 g). Meta-regressions revealed that centers with higher median PM2.5 levels and PM2.5:PM10 ratios, and centers that used a temporal exposure assessment (compared with spatiotemporal), tended to report stronger associations.
Conclusion: Maternal exposure to particulate pollution was associated with LBW at term across study populations. We detected three site characteristics and aspects of exposure assessment methodology that appeared to contribute to the variation in associations reported by centers.
air pollution; fetal growth; heterogeneity; ICAPPO; low birth weight; meta-analysis; meta-regression; multi-center study; particulate matter; pregnancy
Background: The effect of ambient air pollution on global variations and trends in asthma prevalence is unclear.
Objectives: Our goal was to investigate community-level associations between asthma prevalence data from the International Study of Asthma and Allergies in Childhood (ISAAC) and satellite-based estimates of particulate matter with aerodynamic diameter < 2.5 µm (PM2.5) and nitrogen dioxide (NO2), and modelled estimates of ozone.
Methods: We assigned satellite-based estimates of PM2.5 and NO2 at a spatial resolution of 0.1° × 0.1° and modeled estimates of ozone at a resolution of 1° × 1° to 183 ISAAC centers. We used center-level prevalence of severe asthma as the outcome and multilevel models to adjust for gross national income (GNI) and center- and country-level sex, climate, and population density. We examined associations (adjusting for GNI) between air pollution and asthma prevalence over time in centers with data from ISAAC Phase One (mid-1900s) and Phase Three (2001–2003).
Results: For the 13- to 14-year age group (128 centers in 28 countries), the estimated average within-country change in center-level asthma prevalence per 100 children per 10% increase in center-level PM2.5 and NO2 was –0.043 [95% confidence interval (CI): –0.139, 0.053] and 0.017 (95% CI: –0.030, 0.064) respectively. For ozone the estimated change in prevalence per parts per billion by volume was –0.116 (95% CI: –0.234, 0.001). Equivalent results for the 6- to 7-year age group (83 centers in 20 countries), though slightly different, were not significantly positive. For the 13- to 14-year age group, change in center-level asthma prevalence over time per 100 children per 10% increase in PM2.5 from Phase One to Phase Three was –0.139 (95% CI: –0.347, 0.068). The corresponding association with ozone (per ppbV) was –0.171 (95% CI: –0.275, –0.067).
Conclusion: In contrast to reports from within-community studies of individuals exposed to traffic pollution, we did not find evidence of a positive association between ambient air pollution and asthma prevalence as measured at the community level.
air pollution; asthma prevalence; children; epidemiology; global; nitrogen dioxide; ozone; particulate matter; satellite observations
Background: Few cohort studies have evaluated the risk of mortality associated with long-term exposure to fine particulate matter [≤ 2.5 μm in aerodynamic diameter (PM2.5)]. This is the first national-level cohort study to investigate these risks in Canada.
Objective: We investigated the association between long-term exposure to ambient PM2.5 and cardiovascular mortality in nonimmigrant Canadian adults.
Methods: We assigned estimates of exposure to ambient PM2.5 derived from satellite observations to a cohort of 2.1 million Canadian adults who in 1991 were among the 20% of the population mandated to provide detailed census data. We identified deaths occurring between 1991 and 2001 through record linkage. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) adjusted for available individual-level and contextual covariates using both standard Cox proportional survival models and nested, spatial random-effects survival models.
Results: Using standard Cox models, we calculated HRs of 1.15 (95% CI: 1.13, 1.16) from nonaccidental causes and 1.31 (95% CI: 1.27, 1.35) from ischemic heart disease for each 10-μg/m3 increase in concentrations of PM2.5. Using spatial random-effects models controlling for the same variables, we calculated HRs of 1.10 (95% CI: 1.05, 1.15) and 1.30 (95% CI: 1.18, 1.43), respectively. We found similar associations between nonaccidental mortality and PM2.5 based on satellite-derived estimates and ground-based measurements in a subanalysis of subjects in 11 cities.
Conclusions: In this large national cohort of nonimmigrant Canadians, mortality was associated with long-term exposure to PM2.5. Associations were observed with exposures to PM2.5 at concentrations that were predominantly lower (mean, 8.7 μg/m3; interquartile range, 6.2 μg/m3) than those reported previously.
Canada; cardiovascular mortality; cohort study; fine particulate matter
Background: Forest, grass, and peat fires release approximately 2 petagrams of carbon into the atmosphere each year, influencing weather, climate, and air quality.
Objective: We estimated the annual global mortality attributable to landscape fire smoke (LFS).
Methods: Daily and annual exposure to particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5) from fire emissions was estimated globally for 1997 through 2006 by combining outputs from a chemical transport model with satellite-based observations of aerosol optical depth. In World Health Organization (WHO) subregions classified as sporadically affected, the daily burden of mortality was estimated using previously published concentration–response coefficients for the association between short-term elevations in PM2.5 from LFS (contrasted with 0 μg/m3 from LFS) and all-cause mortality. In subregions classified as chronically affected, the annual burden of mortality was estimated using the American Cancer Society study coefficient for the association between long-term PM2.5 exposure and all-cause mortality. The annual average PM2.5 estimates were contrasted with theoretical minimum (counterfactual) concentrations in each chronically affected subregion. Sensitivity of mortality estimates to different exposure assessments, counterfactual estimates, and concentration–response functions was evaluated. Strong La Niña and El Niño years were compared to assess the influence of interannual climatic variability.
Results: Our principal estimate for the average mortality attributable to LFS exposure was 339,000 deaths annually. In sensitivity analyses the interquartile range of all tested estimates was 260,000–600,000. The regions most affected were sub-Saharan Africa (157,000) and Southeast Asia (110,000). Estimated annual mortality during La Niña was 262,000, compared with 532,000 during El Niño.
Conclusions: Fire emissions are an important contributor to global mortality. Adverse health outcomes associated with LFS could be substantially reduced by curtailing burning of tropical rainforests, which rarely burn naturally. The large estimated influence of El Niño suggests a relationship between climate and the burden of mortality attributable to LFS.
air pollution; biomass burning; carbon cycle; deforestation; global burden of disease; landscape fire smoke; mortality
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
Air pollution; Canada; Exposure assessment; Lung cancer; Residential mobility; Spatiotemporal
Background: Physical inactivity and exposure to air pollution are important risk factors for death and disease globally. The built environment may influence exposures to these risk factors in different ways and thus differentially affect the health of urban populations.
Objective: We investigated the built environment’s association with air pollution and physical inactivity, and estimated attributable health risks.
Methods: We used a regional travel survey to estimate within-urban variability in physical inactivity and home-based air pollution exposure [particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), nitrogen oxides (NOx), and ozone (O3)] for 30,007 individuals in southern California. We then estimated the resulting risk for ischemic heart disease (IHD) using literature-derived dose–response values. Using a cross-sectional approach, we compared estimated IHD mortality risks among neighborhoods based on “walkability” scores.
Results: The proportion of physically active individuals was higher in high- versus low-walkability neighborhoods (24.9% vs. 12.5%); however, only a small proportion of the population was physically active, and between-neighborhood variability in estimated IHD mortality attributable to physical inactivity was modest (7 fewer IHD deaths/100,000/year in high- vs. low-walkability neighborhoods). Between-neighborhood differences in estimated IHD mortality from air pollution were comparable in magnitude (9 more IHD deaths/100,000/year for PM2.5 and 3 fewer IHD deaths for O3 in high- vs. low-walkability neighborhoods), suggesting that population health benefits from increased physical activity in high-walkability neighborhoods may be offset by adverse effects of air pollution exposure.
Policy implications: Currently, planning efforts mainly focus on increasing physical activity through neighborhood design. Our results suggest that differences in population health impacts among neighborhoods are similar in magnitude for air pollution and physical activity. Thus, physical activity and exposure to air pollution are critical aspects of planning for cleaner, health-promoting cities.
active travel; air quality; environmental planning; infill; risk assessment; urban form
Epidemiologic studies have linked exposure to traffic-generated air and noise pollution with a wide range of adverse health effects in children. Children spend a large portion of time at school, and both air pollution and noise are elevated in close proximity to roads, so school location may be an important determinant of exposure. No studies have yet examined the proximity of schools to major roads in Canadian cities.
Data on public elementary schools in Canada's 10 most populous cities were obtained from online databases. School addresses were geocoded and proximity to the nearest major road, defined using a standardized national road classification scheme, was calculated for each school. Based on measurements of nitrogen oxide concentrations, ultrafine particle counts, and noise levels in three Canadian cities we conservatively defined distances < 75 m from major roads as the zone of primary interest. Census data at the city and neighborhood levels were used to evaluate relationships between school proximity to major roads, urban density, and indicators of socioeconomic status.
Addresses were obtained for 1,556 public elementary schools, 95% of which were successfully geocoded. Across all 10 cities, 16.3% of schools were located within 75 m of a major road, with wide variability between cities. Schools in neighborhoods with higher median income were less likely to be near major roads (OR per $20,000 increase: 0.81; 95% CI: 0.65, 1.00), while schools in densely populated neighborhoods were more frequently close to major roads (OR per 1,000 dwellings/km2: 1.07; 95% CI: 1.00, 1.16). Over 22% of schools in the lowest neighborhood income quintile were close to major roads, compared to 13% of schools in the highest income quintile.
A substantial fraction of students at public elementary schools in Canada, particularly students attending schools in low income neighborhoods, may be exposed to elevated levels of air pollution and noise while at school. As a result, the locations of schools may negatively impact the healthy development and academic performance of a large number of Canadian children.
A growing body of evidence links the built environment to physical activity levels, health outcomes, and transportation behaviors. However, little of this research has focused on cycling, a sustainable transportation option with great potential for growth in North America. This study examines associations between decisions to bicycle (versus drive) and the built environment, with explicit consideration of three different spatial zones that may be relevant in travel behavior: trip origins, trip destinations, and along the route between. We analyzed 3,280 utilitarian bicycle and car trips in Metro Vancouver, Canada made by 1,902 adults, including both current and potential cyclists. Objective measures were developed for built environment characteristics related to the physical environment, land use patterns, the road network, and bicycle-specific facilities. Multilevel logistic regression was used to model the likelihood that a trip was made by bicycle, adjusting for trip distance and personal demographics. Separate models were constructed for each spatial zone, and a global model examined the relative influence of the three zones. In total, 31% (1,023 out of 3,280) of trips were made by bicycle. Increased odds of bicycling were associated with less hilliness; higher intersection density; less highways and arterials; presence of bicycle signage, traffic calming, and cyclist-activated traffic lights; more neighborhood commercial, educational, and industrial land uses; greater land use mix; and higher population density. Different factors were important within each spatial zone. Overall, the characteristics of routes were more influential than origin or destination characteristics. These findings indicate that the built environment has a significant influence on healthy travel decisions, and spatial context is important. Future research should explicitly consider relevant spatial zones when investigating the relationship between physical activity and urban form.
Bicycle; Built environment; Physical activity; Urban form; Non-motorized transportation
Otitis media is the main reason young children receive antibiotics and is the leading reason for physician visits.
To characterize the incidence, recurrence and risk factors for otitis media in a population-based birth cohort.
All children born in southwestern British Columbia during 1999 to 2000 were followed until the age of three years. Otitis media was defined using The International Classification of Diseases, Ninth Revision coding of physician visits, and linked with antibiotic prescription data. Information on sex, birth weight, gestational age, Aboriginal status, maternal age, older siblings, maternal smoking during pregnancy, breastfeeding initiation, neighbourhood income, female education and rural residence were obtained from vital statistics, birth hospitalizations, perinatal registry and census data.
Complete risk factor information was available for 50,474 children (86% of all births). Nearly one-half of the children (48.6%) had one or more physician visits for otitis media during follow-up, and 3952 children (7.8%) met the definition for recurrent otitis media. Of the children with at least three visits during follow-up (n=7571), 73% had their initial visit during the first year of life. Aboriginal status, maternal age younger than 20 years, male sex and older siblings were the strongest risk factors identified in the adjusted conditional logistic regression models.
The present study established a population-based birth cohort by linking multiple administrative databases to characterize the incidence of and risk factors for otitis media. Although the incidence of otitis media is generally low in southwestern British Columbia, important risk factors continue to be young maternal age, mothers who smoke during pregnancy and children with Aboriginal ancestry.
Birth cohort; Incidence; Otitis media; Risk factors
Background: During the summer of 2003 numerous fires burned in British Columbia, Canada.
Objectives: We examined the associations between respiratory and cardiovascular physician visits and hospital admissions, and three measures of smoke exposure over a 92-day study period (1 July to 30 September 2003).
Methods: A population-based cohort of 281,711 residents was identified from administrative data. Spatially specific daily exposure estimates were assigned to each subject based on total measurements of particulate matter (PM) ≤ 10 μm in aerodynamic diameter (PM10) from six regulatory tapered element oscillating microbalance (TEOM) air quality monitors, smoke-related PM10 from a CALPUFF dispersion model run for the study, and a SMOKE exposure metric for plumes visible in satellite images. Logistic regression with repeated measures was used to estimate associations with each outcome.
Results: The mean (± SD) exposure based on TEOM-measured PM10 was 29 ± 31 μg/m3, with an interquartile range of 14–31 μg/m3. Correlations between the TEOM, smoke, and CALPUFF metrics were moderate (0.37–0.76). Odds ratios (ORs) for a 30-μg/m3 increase in TEOM-based PM10 were 1.05 [95% confidence interval (CI), 1.03–1.06] for all respiratory physician visits, 1.16 (95% CI, 1.09–1.23) for asthma-specific visits, and 1.15 (95% CI, 1.00–1.29) for respiratory hospital admissions. Associations with cardiovascular outcomes were largely null.
Conclusions: Overall we found that increases in TEOM-measured PM10 were associated with increased odds of respiratory physician visits and hospital admissions, but not with cardiovascular health outcomes. Results indicating effects of fire smoke on respiratory outcomes are consistent with previous studies, as are the null results for cardiovascular outcomes. Some agreement between TEOM and the other metrics suggests that exposure assessment tools that are independent of air quality monitoring may be useful with further refinement.
biomass smoke; cohort study; exposure assessment; particulate matter; population-based
Background: Population exposure assessment methods that capture local-scale pollutant variability are needed for large-scale epidemiological studies and surveillance, policy, and regulatory purposes. Currently, such exposure methods are limited.
Methods: We created 2006 national pollutant models for fine particulate matter [PM with aerodynamic diameter ≤ 2.5 μm (PM2.5)], nitrogen dioxide (NO2), benzene, ethylbenzene, and 1,3-butadiene from routinely collected fixed-site monitoring data in Canada. In multiple regression models, we incorporated satellite estimates and geographic predictor variables to capture background and regional pollutant variation and used deterministic gradients to capture local-scale variation. The national NO2 and benzene models are evaluated with independent measurements from previous land use regression models that were conducted in seven Canadian cities. National models are applied to census block-face points, each of which represents the location of approximately 89 individuals, to produce estimates of population exposure.
Results: The national NO2 model explained 73% of the variability in fixed-site monitor concentrations, PM2.5 46%, benzene 62%, ethylbenzene 67%, and 1,3-butadiene 68%. The NO2 model predicted, on average, 43% of the within-city variability in the independent NO2 data compared with 18% when using inverse distance weighting of fixed-site monitoring data. Benzene models performed poorly in predicting within-city benzene variability. Based on our national models, we estimated Canadian ambient annual average population-weighted exposures (in micrograms per cubic meter) of 8.39 for PM2.5, 23.37 for NO2, 1.04 for benzene, 0.63 for ethylbenzene, and 0.09 for 1,3-butadiene.
Conclusions: The national pollutant models created here improve exposure assessment compared with traditional monitor-based approaches by capturing both regional and local-scale pollution variation. Applying national models to routinely collected population location data can extend land use modeling techniques to population exposure assessment and to informing surveillance, policy, and regulation.
air pollution; Canada; fixed-site monitors; gradients; land use regression; population exposure assessment; satellite data
Background: The findings of prior studies of air pollution effects on adverse birth outcomes are difficult to synthesize because of differences in study design.
Objectives: The International Collaboration on Air Pollution and Pregnancy Outcomes was formed to understand how differences in research methods contribute to variations in findings. We initiated a feasibility study to a) assess the ability of geographically diverse research groups to analyze their data sets using a common protocol and b) perform location-specific analyses of air pollution effects on birth weight using a standardized statistical approach.
Methods: Fourteen research groups from nine countries participated. We developed a protocol to estimate odds ratios (ORs) for the association between particulate matter ≤ 10 μm in aerodynamic diameter (PM10) and low birth weight (LBW) among term births, adjusted first for socioeconomic status (SES) and second for additional location-specific variables.
Results: Among locations with data for the PM10 analysis, ORs estimating the relative risk of term LBW associated with a 10-μg/m3 increase in average PM10 concentration during pregnancy, adjusted for SES, ranged from 0.63 [95% confidence interval (CI), 0.30–1.35] for the Netherlands to 1.15 (95% CI, 0.61–2.18) for Vancouver, with six research groups reporting statistically significant adverse associations. We found evidence of statistically significant heterogeneity in estimated effects among locations.
Conclusions: Variability in PM10–LBW relationships among study locations remained despite use of a common statistical approach. A more detailed meta-analysis and use of more complex protocols for future analysis may uncover reasons for heterogeneity across locations. However, our findings confirm the potential for a diverse group of researchers to analyze their data in a standardized way to improve understanding of air pollution effects on birth outcomes.
air pollution; birth weight; ICAPPO; low birth weight; particulate matter; pregnancy
The environment is suspected to play an important role in the development of childhood asthma. Cohort studies are a powerful observational design for studying exposure–response relationships, but their power depends in part upon the accuracy of the exposure assessment.
The purpose of this paper is to summarize and discuss issues that make accurate exposure assessment a challenge and to suggest strategies for improving exposure assessment in longitudinal cohort studies of childhood asthma and allergies.
Exposures of interest need to be prioritized, because a single study cannot measure all potentially relevant exposures. Hypotheses need to be based on proposed mechanisms, critical time windows for effects, prior knowledge of physical, physiologic, and immunologic development, as well as genetic pathways potentially influenced by the exposures. Modifiable exposures are most important from the public health perspective. Given the interest in evaluating gene–environment interactions, large cohort sizes are required, and planning for data pooling across independent studies is critical. Collection of additional samples, possibly through subject participation, will permit secondary analyses. Models combining air quality, environmental, and dose data provide exposure estimates across large cohorts but can still be improved.
Exposure is best characterized through a combination of information sources. Improving exposure assessment is critical for reducing measurement error and increasing power, which increase confidence in characterization of children at risk, leading to improved health outcomes.
childhood asthma; cohort studies; exposure assessment
Epidemiologic studies have demonstrated that exposure to road traffic is associated with adverse cardiovascular outcomes.
We aimed to identify specific traffic-related air pollutants that are associated with the risk of coronary heart disease (CHD) morbidity and mortality to support evidence-based environmental policy making.
This population-based cohort study included a 5-year exposure period and a 4-year follow-up period. All residents 45–85 years of age who resided in Metropolitan Vancouver during the exposure period and without known CHD at baseline were included in this study (n = 452,735). Individual exposures to traffic-related air pollutants including black carbon, fine particles [aerodynamic diameter ≤ 2.5 μm (PM2.5)], nitrogen dioxide (NO2), and nitric oxide were estimated at residences of the subjects using land-use regression models and integrating changes in residences during the exposure period. CHD hospitalizations and deaths during the follow-up period were identified from provincial hospitalization and death registration records.
An interquartile range elevation in the average concentration of black carbon (0.94 × 10−5/m filter absorbance, equivalent to approximately 0.8 μg/m3 elemental carbon) was associated with a 3% increase in CHD hospitalization (95% confidence interval, 1–5%) and a 6% increase in CHD mortality (3–9%) after adjusting for age, sex, preexisting comorbidity, neighborhood socioeconomic status, and copollutants (PM2.5 and NO2). There were clear linear exposure–response relationships between black carbon and coronary events.
Long-term exposure to traffic-related fine particulate air pollution, indicated by black carbon, may partly explain the observed associations between exposure to road traffic and adverse cardiovascular outcomes.
air pollution; cohort studies; coronary heart disease; particulate matter; vehicle emissions
Associations between air pollution and a multitude of health effects are now well established. Given ubiquitous exposure to some level of air pollution, the attributable health burden can be high, particularly for susceptible populations.
An international multidisciplinary workshop was convened to discuss evidence of the effectiveness of actions to reduce health impacts of air pollution at both the community and individual level. The overall aim was to summarize current knowledge regarding air pollution exposure and health impacts leading to public health recommendations.
During the workshop, experts reviewed the biological mechanisms of action of air pollution in the initiation and progression of disease, as well as the state of the science regarding community and individual-level interventions. The workshop highlighted strategies to reduce individual baseline risk of conditions associated with increased susceptibility to the effects of air pollution and the need to better understand the role of exposure duration in disease progression, reversal, and adaptation.
We have identified two promising and largely unexplored strategies to address and mitigate air pollution–related health impacts: reducing individual baseline risk of cardiovascular disease and incorporating air pollution–related health impacts into land-use decisions.
air pollution; antioxidant; cardiovascular; exposure; intervention; public health; respiratory; urban planning
Epidemiologic and health impact studies of fine particulate matter with diameter < 2.5 μm (PM2.5) are limited by the lack of monitoring data, especially in developing countries. Satellite observations offer valuable global information about PM2.5 concentrations.
In this study, we developed a technique for estimating surface PM2.5 concentrations from satellite observations.
We mapped global ground-level PM2.5 concentrations using total column aerosol optical depth (AOD) from the MODIS (Moderate Resolution Imaging Spectroradiometer) and MISR (Multiangle Imaging Spectroradiometer) satellite instruments and coincident aerosol vertical profiles from the GEOS-Chem global chemical transport model.
We determined that global estimates of long-term average (1 January 2001 to 31 December 2006) PM2.5 concentrations at approximately 10 km × 10 km resolution indicate a global population-weighted geometric mean PM2.5 concentration of 20 μg/m3. The World Health Organization Air Quality PM2.5 Interim Target-1 (35 μg/m3 annual average) is exceeded over central and eastern Asia for 38% and for 50% of the population, respectively. Annual mean PM2.5 concentrations exceed 80 μg/m3 over eastern China. Our evaluation of the satellite-derived estimate with ground-based in situ measurements indicates significant spatial agreement with North American measurements (r = 0.77; slope = 1.07; n = 1057) and with noncoincident measurements elsewhere (r = 0.83; slope = 0.86; n = 244). The 1 SD of uncertainty in the satellite-derived PM2.5 is 25%, which is inferred from the AOD retrieval and from aerosol vertical profile errors and sampling. The global population-weighted mean uncertainty is 6.7 μg/m3.
Satellite-derived total-column AOD, when combined with a chemical transport model, provides estimates of global long-term average PM2.5 concentrations.
aerosol; aerosol optical depth; AOD; particulate matter; PM2.5
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 3–4 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 ≤ 10 μm and ≤ 2.5 μm in aerodynamic diameter (PM10 and PM2.5), ozone, sulfur dioxide, black carbon, woodsmoke, and proximity to roads and point sources on asthma diagnosis.
A total of 3,482 children (9%) were classified as asthma cases. We observed a statistically significantly increased risk of asthma diagnosis with increased early life exposure to CO, NO, NO2, PM10, SO2, and black carbon and proximity to point sources. Traffic-related pollutants were associated with the highest risks: adjusted odds ratio = 1.08 (95% confidence interval, 1.04–1.12) for a 10-μg/m3 increase of NO, 1.12 (1.07–1.17) for a 10-μg/m3 increase in NO2, and 1.10 (1.06–1.13) for a 100-μg/m3 increase in CO. These data support the hypothesis that early childhood exposure to air pollutants plays a role in development of asthma.
administrative data; air pollution; asthma; children’s health; in utero; respiratory; traffic
The built environment may influence health in part through the promotion of physical activity and exposure to pollution. To date, no studies have explored interactions between neighborhood walkability and air pollution exposure.
We estimated concentrations of nitric oxide (NO), a marker for direct vehicle emissions), and ozone (O3) and a neighborhood walkability score, for 49,702 (89% of total) postal codes in Vancouver, British Columbia, Canada. NO concentrations were estimated from a land-use regression model, O3 was estimated from ambient monitoring data; walkability was calculated based on geographic attributes such as land-use mix, street connectivity, and residential density.
All three attributes exhibit an urban–rural gradient, with high walkability and NO concentrations, and low O3 concentrations, near the city center. Lower-income areas tend to have higher NO concentrations and walkability and lower O3 concentrations. Higher-income areas tend to have lower pollution (NO and O3). “Sweet-spot” neighborhoods (low pollution, high walkability) are generally located near but not at the city center and are almost exclusively higher income.
Increased concentration of activities in urban settings yields both health costs and benefits. Our research identifies neighborhoods that do especially well (and especially poorly) for walkability and air pollution exposure. Work is needed to ensure that the poor do not bear an undue burden of urban air pollution and that neighborhoods designed for walking, bicycling, or mass transit do not adversely affect resident’s exposure to air pollution. Analyses presented here could be replicated in other cities and tracked over time to better understand interactions among neighborhood walkability, air pollution exposure, and income level.
air quality; built environment; exercise; infill; pedestrian friendliness; physical activity; sprawl; traffic; urban design; urban environmental health; vehicle emissions
Previous research has documented effects of both physical and social environmental exposures on childhood asthma. However, few studies have considered how these two environments might interact to affect asthma.
This study aimed to test interactions between chronic exposure to traffic-related air pollution and chronic family stress in predicting biologic and clinical outcomes in children with asthma.
Children with asthma (n = 73, 9–18 years of age) were interviewed about life stress, and asthma-relevant inflammatory markers [cytokine production, immunoglobulin E (IgE), eosinophil counts] were measured. Parents reported on children’s symptoms. Children completed daily diaries of symptoms and peak expiratory flow rate (PEFR) measures at baseline and 6 months later. Exposure to traffic-related air pollution was assessed using a land use regression model for nitrogen dioxide concentrations.
NO2 by stress interactions were found for interleukin-5 (β for interaction term = −0.31, p = 0.02), IgE (interaction β = −0.29, p = 0.02), and eosinophil counts (interaction β = −0.24, p = 0.04). These interactions showed that higher chronic stress was associated with heightened inflammatory profiles as pollution levels decreased. Longitudinally, NO2 by stress interactions emerged for daily diary symptoms (interaction β = −0.28, p = 0.02), parent-reported symptoms (interaction β = −0.25, p = 0.07), and PEFR (interaction β = 0.30, p = 0.03). These interactions indicated that higher chronic stress was associated with increases over time in symptoms and decreases over time in PEFR as pollution levels decreased.
The physical and social environments interacted in predicting both biologic and clinical outcomes in children with asthma, suggesting that when pollution exposure is more modest, vulnerability to asthma exacerbations may be heightened in children with higher chronic stress.
air pollution; asthma; immune; psychosocial; stress; traffic
There is a growing body of epidemiologic literature reporting associations between atmospheric pollutants and reproductive outcomes, particularly birth weight and gestational duration.
The objectives of our international workshop were to discuss the current evidence, to identify the strengths and weaknesses of published epidemiologic studies, and to suggest future directions for research.
Participants identified promising exposure assessment tools, including exposure models with fine spatial and temporal resolution that take into account time–activity patterns. More knowledge on factors correlated with exposure to air pollution, such as other environmental pollutants with similar temporal variations, and assessment of nutritional factors possibly influencing birth outcomes would help evaluate importance of residual confounding. Participants proposed a list of points to report in future publications on this topic to facilitate research syntheses. Nested case–control studies analyzed using two-phase statistical techniques and development of cohorts with extensive information on pregnancy behaviors and biological samples are promising study designs. Issues related to the identification of critical exposure windows and potential biological mechanisms through which air pollutants may lead to intrauterine growth restriction and premature birth were reviewed.
To make progress, this research field needs input from toxicology, exposure assessment, and clinical research, especially to aid in the identification and exposure assessment of feto-toxic agents in ambient air, in the development of early markers of adverse reproductive outcomes, and of relevant biological pathways. In particular, additional research using animal models would help better delineate the biological mechanisms underpinning the associations reported in human studies.
atmospheric pollution; bias; birth weight; environment; exposure assessment; fecundity; geographic information system; intrauterine growth restriction; particulate matter; pregnancy; reproduction; small for gestational age
Evidence suggests that air pollution exposure adversely affects pregnancy outcomes. Few studies have examined individual-level intraurban exposure contrasts.
We evaluated the impacts of air pollution on small for gestational age (SGA) birth weight, low full-term birth weight (LBW), and preterm birth using spatiotemporal exposure metrics.
With linked administrative data, we identified 70,249 singleton births (1999–2002) with complete covariate data (sex, ethnicity, parity, birth month and year, income, education) and maternal residential history in Vancouver, British Columbia, Canada. We estimated residential exposures by month of pregnancy using nearest and inverse-distance weighting (IDW) of study area monitors [carbon monoxide, nitrogen dioxide, nitric oxide, ozone, sulfur dioxide, and particulate matter < 2.5 (PM2.5) or < 10 (PM10) μm in aerodynamic diameter], temporally adjusted land use regression (LUR) models (NO, NO2, PM2.5, black carbon), and proximity to major roads. Using logistic regression, we estimated the risk of mean (entire pregnancy, first and last month of pregnancy, first and last 3 months) air pollution concentrations on SGA (< 10th percentile), term LBW (< 2,500 g), and preterm birth.
Residence within 50 m of highways was associated with a 26% increase in SGA [95% confidence interval (CI), 1.07–1.49] and an 11% (95% CI, 1.01–1.23) increase in LBW. Exposure to all air pollutants except O3 was associated with SGA, with similar odds ratios (ORs) for LUR and monitoring estimates (e.g., LUR: OR = 1.02; 95% CI, 1.00–1.04; IDW: OR = 1.05; 95% CI, 1.03–1.08 per 10-μg/m3 increase in NO). For preterm births, associations were observed with PM2.5 for births < 37 weeks gestation (and for other pollutants at < 30 weeks). No consistent patterns suggested exposure windows of greater relevance.
Associations between traffic-related air pollution and birth outcomes were observed in a population-based cohort with relatively low ambient air pollution exposure.
air pollution; birth weight; carbon black; carbon monoxide; nitrogen dioxide; nitric oxide; particulate matter; pregnancy; pregnancy outcome; preterm birth; soot; sulfur dioxide; vehicle emissions
Otitis media is one of the most common infections in young children. Although exposure to environmental tobacco smoke is a known risk factor associated with otitis media, little information is available regarding the potential association with air pollution.
We set out to study the relationship between exposure to traffic-related air pollution and otitis media in two birth cohorts.
Individual estimates of outdoor concentrations of traffic-related air pollutants—nitrogen dioxide, fine particles [particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5)], and elemental carbon—were calculated for home addresses of approximately 3,700 and 650 infants from birth cohort studies in the Netherlands and Germany, respectively. Air pollution exposure was analyzed in relation to physician diagnosis of otitis media in the first 2 years of life.
Odds ratios (adjusted for known major risk factors) for otitis media indicated positive associations with traffic-related air pollutants. An increase in 3 μg/m3 PM2.5, 0.5 μg/m3 elemental carbon, and 10 μg/m3 NO2 was associated with odds ratios of 1.13 (95% confidence interval, 1.00–1.27), 1.10 (1.00–1.22), and 1.14 (1.03–1.27) in the Netherlands and 1.24 (0.84–1.83), 1.10 (0.86–1.41), and 1.14 (0.87–1.49) in Germany, respectively.
These findings indicate an association between exposure to traffic-related air pollutants and the incidence of otitis media. Given the ubiquitous nature of air pollution exposure and the importance of otitis media to children’s health, these findings have significant public health implications.
air pollution; cohort studies; infant; otitis media; vehicle emissions