Interdisciplinary-driven hypotheses on spatial associations of mixtures of industrial air pollutants with adverse birth outcomes

Background: Adverse birth outcomes (ABO) such as prematurity and small for gestational age confer a high risk of mortality and morbidity. ABO have been linked to air pollution; however, relationships with mixtures of industrial emissions are poorly understood. The exploration of relationships between ABO and mixtures is complex when hundreds of chemicals are analyzed simultaneously, requiring the use of novel approaches. Objective: We aimed to generate robust hypotheses spatially linking mixtures and the occurrence of ABO using a spatial data mining algorithm and subsequent geographical and statistical analysis. The spatial data mining approach aimed to reduce data dimensionality and efficiently identify spatial associations between multiple chemicals and ABO. Methods: We discovered co-location patterns of mixtures and ABO in Alberta, Canada (2006–2012). An ad-hoc spatial data mining algorithm allowed the extraction of primary co-location patterns of 136 chemicals released into the air by 6279 industrial facilities (National Pollutant Release Inventory), wind-patterns from 182 stations, and 333,247 singleton live births at the maternal postal code at delivery (Alberta Perinatal Health Program), from which we identified cases of preterm birth, small for gestational age, and low birth weight at term. We selected secondary patterns using a lift ratio metric from ABO and non-ABO impacted by the same mixture. The relevance of the secondary patterns was estimated using logistic models (adjusted by socioeconomic status and ABO-related maternal factors) and a geographic-based assignment of maternal exposure to the mixtures as calculated by kernel density. Results: From 136 chemicals and three ABO, spatial data mining identified 1700 primary patterns from which five secondary patterns of three-chemical mixtures, including particulate matter, methyl-ethyl-ketone, xylene, carbon monoxide, 2-butoxyethanol, and n-butyl alcohol, were subsequently analyzed. The significance of the associations (odds ratio > 1) between the five mixtures and ABO provided statistical support for a new set of hypotheses. Conclusion: This study demonstrated that, in complex research settings, spatial data mining followed by pattern selection and geographic and statistical analyses can catalyze future research on associations between air pollutant mixtures and adverse birth outcomes

The Canadian Urban Environmental Health Research Consortium - A protocol for building a national environmental exposure data platform for integrated analyses of urban form and health

Background: Multiple external environmental exposures related to residential location and urban form including, air pollutants, noise, greenness, and walkability have been linked to health impacts or benefits. The Canadian Urban Environmental Health Research Consortium (CANUE) was established to facilitate the linkage of extensive geospatial exposure data to existing Canadian cohorts and administrative health data holdings. We hypothesize that this linkage will enable investigators to test a variety of their own hypotheses related to the interdependent associations of built environment features with diverse health outcomes encompassed by the cohorts and administrative data. Methods: We developed a protocol for compiling measures of built environment features that quantify exposure; vary spatially on the urban and suburban scale; and can be modified through changes in policy or individual behaviour to benefit health. These measures fall into six domains: air quality, noise, greenness, weather/climate, and transportation and neighbourhood factors; and will be indexed to six-digit postal codes to facilitate merging with health databases. Initial efforts focus on existing data and include estimates of air pollutants, greenness, temperature extremes, and neighbourhood walkability and socioeconomic characteristics. Key gaps will be addressed for noise exposure, with a new national model being developed, and for transportation-related exposures, with detailed estimates of truck volumes and diesel emissions now underway in selected cities. Improvements to existing exposure estimates are planned, primarily by increasing temporal and/or spatial resolution given new satellite-based sensors and more detailed national air quality modelling. Novel metrics are also planned for walkability and food environments, green space access and function and life-long climate-related exposures based on local climate zones. Critical challenges exist, for example, the quantity and quality of input data to many of the models and metrics has changed over time, making it difficult to develop and validate historical exposures. Discussion: CANUE represents a unique effort to coordinate and leverage substantial research investments and will enable a more focused effort on filling gaps in exposure information, improving the range of exposures quantified, their precision and mechanistic relevance to health. Epidemiological studies may be better able to explore the common theme of urban form and health in an integrated manner, ultimately contributing new knowledge informing policies that enhance healthy urban living

Biomass burning as a source of ambient fine particulate air pollution and acute myocardial infarction

Background: Biomass burning is an important source of ambient fine particulate air pollution (PM2.5) in many regions of the world. Methods: We conducted a time-stratified case-crossover study of ambient PM2.5 and hospital admissions for myocardial infarction (MI) in three regions of British Columbia, Canada. Daily hospital admission data were collected between 2008 and 2015 and PM2.5 data were collected from fixed site monitors. We used conditional logistic regression models to estimate odds ratios (ORs) describing the association between PM2.5 and the risk of hospital admission for MI. We used stratified analyses to evaluate effect modification by biomass burning as a source of ambient PM2.5 using the ratio of levoglucosan/ PM2.5 mass concentrations. Results: Each 5 μg/m3 increase in 3-day mean PM2.5 was associated with an increased risk of MI among elderly subjects (≥65 years; OR = 1.06, 95% CI: 1.03, 1.08); risk was not increased among younger subjects. Among the elderly, the strongest association occurred during colder periods (<6.44°C); when we stratified analyses by tertiles of monthly mean biomass contributions to PM2.5 during cold periods, ORs of 1.19 (95% CI: 1.04, 1.36), 1.08 (95% CI: 1.06, 1.09), and 1.04 (95% CI: 1.03, 1.06) were observed in the upper, middle, and lower tertiles (Ptrend = 0.003), respectively. Conclusion: Short-Term changes in ambient PM2.5 were associated with an increased risk of MI among elderly subjects. During cold periods, increased biomass burning contributions to PM2.5 may modify its association with MI. Copyright © 2017 The Author(s).Published by Wolters Kluwer Health, Inc

Short-term exposure to ambient air pollution and individual emergency department visits for COVID-19:a case-crossover study in Canada

Abstract Background: Ambient air pollution is thought to contribute to increased risk of COVID-19, but the evidence is controversial. Objective: To evaluate the associations between short-term variations in outdoor concentrations of ambient air pollution and COVID-19 emergency department (ED) visits. Methods: We conducted a case-crossover study of 78 255 COVID-19 ED visits in Alberta and Ontario, Canada between 1 March 2020 and 31 March 2021. Daily air pollution data (ie, fine particulate matter with diameter less than 2.5 µm (PM2.5), nitrogen dioxide (NO₂) and ozone were assigned to individual case of COVID-19 in 10 km × 10 km grid resolution. Conditional logistic regression was used to estimate associations between air pollution and ED visits for COVID-19. Results: Cumulative ambient exposure over 0–3 days to PM2.5 (OR 1.010; 95% CI 1.004 to 1.015, per 6.2 µg/m³) and NO₂ (OR 1.021; 95% CI 1.015 to 1.028, per 7.7 ppb) concentrations were associated with ED visits for COVID-19. We found that the association between PM2.5 and COVID-19 ED visits was stronger among those hospitalised following an ED visit, as a measure of disease severity, (OR 1.023; 95% CI 1.015 to 1.031) compared with those not hospitalised (OR 0.992; 95% CI 0.980 to 1.004) (p value for effect modification=0.04). Conclusions: We found associations between short-term exposure to ambient air pollutants and COVID-19 ED visits. Exposure to air pollution may also lead to more severe COVID-19 disease

From good Intentions to proven interventions : effectiveness of actions to reduce the health impacts of air pollution

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. Objectives: 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. Discussion: 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. C onclusion: 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.Education, Faculty ofEnvironmental Health (SOEH), School ofKinesiology, School ofMedicine, Department ofPopulation and Public Health (SPPH), School ofRespiratory Medicine, Division ofNon UBCMedicine, Faculty ofReviewedFacult