Long-Term Exposure to Traffic-Related Air Pollution and Diabetes: A Systematic Review and Meta-Analysis.

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population. Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022. Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO2 was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10 µg/m3), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10 µg/m3). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies. Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes.

Mapping Inequalities in the Physical, Built and Social Environment in Population-Based Studies of Brain Health.

This mini-tutorial describes how combining aggregate-level data about the physical, built and social environment can facilitate our understanding of factors shaping the human brain and, in turn, brain health. It provides entry-level information about methods and approaches one can use to uncover how inequalities in the local environment lead to health inequalities in general, and those in brain health in particular. This background knowledge should be helpful to those who are interested in using neuroimaging to investigate how environmental factors shape inter-individual variations in the human brain.

Association of Sulfur, Transition Metals, and the Oxidative Potential of Outdoor PM2.5 with Acute Cardiovascular Events: A Case-Crossover Study of Canadian Adults.

BACKGROUND: We do not currently understand how spatiotemporal variations in the composition of fine particulate air pollution [fine particulate matter with aerodynamic diameter ≤2.5µm (PM2.5)] affects population health risks. However, recent evidence suggests that joint concentrations of transition metals and sulfate may influence the oxidative potential (OP) of PM2.5 and associated health impacts. OBJECTIVES: The purpose of the study was to evaluate how combinations of transition metals/OP and sulfur content in outdoor PM2.5 influence associations with acute cardiovascular events. METHODS: We conducted a national case-crossover study of outdoor PM2.5 and acute cardiovascular events in Canada between 2016 and 2017 (93,344 adult cases). Monthly mean transition metal and sulfur (S) concentrations in PM2.5 were determined prospectively along with estimates of OP using acellular assays for glutathione (OPGSH), ascorbate (OPAA), and dithiothreitol depletion (OPDTT). Conditional logistic regression models were used to estimate odds ratios (OR) [95% confidence intervals (CI)] for PM2.5 across strata of transition metals/OP and sulfur. RESULTS: Among men, the magnitudes of observed associations were strongest when both transition metal and sulfur content were elevated. For example, an OR of 1.078 (95% CI: 1.049, 1.108) (per 10µg/m3) was observed for cardiovascular events in men when both copper and S were above the median, whereas a weaker association was observed when both elements were below median values (OR=1.019, 95% CI: 1.007, 1.031). A similar pattern was observed for OP metrics. PM2.5 was not associated with acute cardiovascular events in women. DISCUSSION: The combined transition metal and sulfur content of outdoor PM2.5 influences the strength of association with acute cardiovascular events in men. Regions with elevated concentrations of both sulfur and transition metals in PM2.5 should be examined as priority areas for regulatory interventions. https://doi.org/10.1289/EHP9449.

Ambient Air Pollution and Mortality After Cardiac Transplantation.

BACKGROUND: Heart transplant recipients are at high risk for mortality, with traditional risk scores performing modestly in predicting post-transplant survival, underscoring the importance of as yet unidentified factors in determining prognosis. In this analysis, the association between PM2.5 exposure levels and survival after heart transplantation were investigated. OBJECTIVES: This study sought to study the association between PM2.5 exposure and mortality following heart transplantation. METHODS: On the basis of the zip code of residence, mortality data in patients who underwent heart transplantation (2004 to 2015) in the United Network for Organ Sharing (UNOS) database were linked with validated estimates of fine particulate matter concentrations (particles with diameter <2.5 µm [PM2.5]; 1 × 1-km grids) for each calendar year during which a UNOS cardiac transplant recipient was at risk for death. Cox proportional hazard models were used to estimate the relationship between exposure and overall mortality adjusting for recipient, donor, and neighborhood variables. RESULTS: A total of 21,800 patients with 86,713 patient-years of follow-up was included. Mean age at transplantation was 52.6 ± 12.6 years, 75% were male, 69% were white, and 39% had ischemic etiology of heart failure. Mean annual exposure to PM2.5 was 10.6 ± 2.3 µg/m3. At a median follow-up of 4.8 (95% confidence interval: 2.0 to 7.8) years, 5,208 patients (23.9%) had died. The estimated mortality hazard ratio, per 10 µg/m3 increment increase in annual PM2.5 exposure was 1.43 (95% confidence interval: 1.21 to 1.49). After adjusting for 30 recipient, donor, and neighborhood variables, the estimated mortality hazard ratio per 10 µg/m3 increment in annual exposure to PM2.5 was 1.26 (95% confidence interval: 1.11 to 1.43) relative increase in hazard of mortality. This association was consistent across subgroups. CONCLUSIONS: This study provides evidence linking air pollution with mortality after heart transplantation. These results suggest an important influence of a key environmental factor in outcomes following heart transplantation, and supports the need for further studies in this population.

Aeroallergens in Canada: Distribution, Public Health Impacts, and Opportunities for Prevention.

Aeroallergens occur naturally in the environment and are widely dispersed across Canada, yet their public health implications are not well-understood. This review intends to provide a scientific and public health-oriented perspective on aeroallergens in Canada: their distribution, health impacts, and new developments including the effects of climate change and the potential role of aeroallergens in the development of allergies and asthma. The review also describes anthropogenic effects on plant distribution and diversity, and how aeroallergens interact with other environmental elements, such as air pollution and weather events. Increased understanding of the relationships between aeroallergens and health will enhance our ability to provide accurate information, improve preventive measures and provide timely treatments for affected populations.

Canadian Alliance for Healthy Hearts and Minds: First Nations Cohort Study Rationale and Design.

BACKGROUND: This is the first national indigenous cohort study in which a common, in-depth protocol with a common set of objectives has been adopted by several indigenous communities across Canada. OBJECTIVES: The overarching objective of the Canadian Alliance for Healthy Hearts and Minds (CAHHM) cohort is to investigate how the community-level environment is associated with individual health behaviors and the presence and progression of chronic disease risk factors and chronic diseases such as cardiovascular disease (CVD) and cancer. METHODS: CAHHM aims to recruit approximately 2,000 First Nations indigenous individuals from up to nine communities across Canada and have participants complete questionnaires, blood collection, physical measurements, cognitive assessments, and magnetic resonance imaging (MRI). RESULTS: Through individual- and community-level data collection, we will develop an understanding of the specific role of the socioenvironmental, biological, and contextual factors have on the development of chronic disease risk factors and chronic diseases. CONCLUSIONS: Information collected in the indigenous cohort will be used to assist communities to develop local management strategies for chronic disease, and can be used collectively to understand the contextual, environmental, socioeconomic, and biological determinants of differences in health status in harmony with First Nations beliefs and reality.

Spatiotemporal air pollution exposure assessment for a Canadian population-based lung cancer case-control study.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Validation of continuous particle monitors for personal, indoor, and outdoor exposures.

Continuous monitors can be used to supplement traditional filter-based methods of determining personal exposure to air pollutants. They have the advantages of being able to identify nearby sources and detect temporal changes on a time scale of a few minutes. The Windsor Ontario Exposure Assessment Study (WOEAS) adopted an approach of using multiple continuous monitors to measure indoor, outdoor (near-residential) and personal exposures to PM2.5, ultrafine particles and black carbon. About 48 adults and households were sampled for five consecutive 24-h periods in summer and winter 2005, and another 48 asthmatic children for five consecutive 24-h periods in summer and winter 2006. This article addresses the laboratory and field validation of these continuous monitors. A companion article (Wheeler et al., 2010) provides similar analyses for the 24-h integrated methods, as well as providing an overview of the objectives and study design. The four continuous monitors were the DustTrak (Model 8520, TSI, St. Paul, MN, USA) and personal DataRAM (pDR) (ThermoScientific, Waltham, MA, USA) for PM2.5; the P-Trak (Model 8525, TSI) for ultrafine particles; and the Aethalometer (AE-42, Magee Scientific, Berkeley, CA, USA) for black carbon (BC). All monitors were tested in multiple co-location studies involving as many as 16 monitors of a given type to determine their limits of detection as well as bias and precision. The effect of concentration and electronic drift on bias and precision were determined from both the collocated studies and the full field study. The effect of rapid changes in environmental conditions on switching an instrument from indoor to outdoor sampling was also studied. The use of multiple instruments for outdoor sampling was valuable in identifying occasional poor performance by one instrument and in better determining local contributions to the spatial variation of particulate pollution. Both the DustTrak and pDR were shown to be in reasonable agreement (R² of 90 and 70%, respectively) with the gravimetric PM2.5 method. Both instruments had limits of detection of about 5 µg/m³. The DustTrak and pDR had multiplicative biases of about 2.5 and 1.6, respectively, compared with the gravimetric samplers. However, their average bias-corrected precisions were <10%, indicating that a proper correction for bias would bring them into very good agreement with standard methods. Although no standard methods exist to establish the bias of the Aethalometer and P-Trak, the precision was within 20% for the Aethalometer and within 10% for the P-Trak. These findings suggest that all four instruments can supply useful information in environmental studies.

A temporal, multicity model to estimate the effects of short-term exposure to ambient air pollution on health.

BACKGROUND: Countries worldwide are expending significant resources to improve air quality partly to improve the health of their citizens. Are these societal expenditures improving public health? OBJECTIVES: We consider these issues by tracking the risk of death associated with outdoor air pollution over both space and time in Canadian cities. MATERIALS AND METHODS: We propose two multi-year estimators that use current plus several previous years of data to estimate current year risk. The estimators are derived from sequential time series analyses using moving time windows. To evaluate the statistical properties of the proposed methods, a simulation study with three scenarios of changing risk was conducted based on 12 Canadian cities from 1981 to 2000. Then an optimal estimator was applied to 24 of Canada's largest cities over the 17-year period from 1984 to 2000. RESULTS: The annual average daily concentrations of ozone appeared to be increasing over the time period, whereas those of nitrogen dioxide were decreasing. However, the proposed method returns different time trends in public health risks. Evidence for some monotonic increasing trends in the annual risks is weak for O(3) (p = 0.3870) but somewhat stronger for NO(2) (p = 0.1082). In particular, an increasing time trend becomes apparent when excluding year 1998, which reveals lower risk than proximal years, even though concentrations of NO(2) were decreasing. The simulation results validate our two proposed methods, producing estimates close to the preassigned values. CONCLUSIONS: Despite decreasing ambient concentrations, public health risks related to NO(2) appear to be increasing. Further investigations are necessary to understand why the concentrations and adverse effects of NO(2) show opposite time trends.

Panel discussion review: session 1--exposure assessment and related errors in air pollution epidemiologic studies.

Examining the validity of exposure metrics used in air pollution epidemiologic models has been a key focus of recent exposure assessment studies. The objective of this work has been, largely, to determine what a given exposure metric represents and to quantify and reduce any potential errors resulting from using these metrics in lieu of true exposure measurements. The current manuscript summarizes the presentations of the co-authors from a recent EPA workshop, held in December 2006, dealing with the role and contributions of exposure assessment in addressing these issues. Results are presented from US and Canadian exposure and pollutant measurement studies as well as theoretical simulations to investigate what both particulate and gaseous pollutant concentrations represent and the potential errors resulting from their use in air pollution epidemiologic studies. Quantifying the association between ambient pollutant concentrations and corresponding personal exposures has led to the concept of defining attenuation factors, or alpha. Specifically, characterizing pollutant-specific estimates for alpha was shown to be useful in developing regression calibration methods involving PM epidemiologic risk estimates. For some gaseous pollutants such as NO2 and SO2, the associations between ambient concentrations and personal exposures were shown to be complex and still poorly understood. Results from recent panel studies suggest that ambient NO2 measurements may, in some locations, be serving as surrogates to traffic pollutants, including traffic-related PM2.5, hopanes, steranes, and oxidized nitrogen compounds (rather than NO2).

A time-series study of air pollution, socioeconomic status, and mortality in Vancouver, Canada.

We evaluated the relationship between daily levels of particulate and gaseous phase pollutants and mortality within a dynamic cohort of approximately 550,000 individuals whose vital status was ascertained between 1986 and 1999. Time-series methods were applied to evaluate whether there were differential pollutant effects on daily aggregated numbers of deaths in the cohort that was stratified into quintiles of income as defined by the 1991 and 1996 Canadian censuses. The percent change in all-cause, cardiovascular, respiratory, and cancer daily mortality was calculated in relation to short-term changes in levels of a number of particulate (PM(2.5), PM(10-2.5), total suspended particle co-efficient of haze PM(10), SO(4)) and gaseous (O(3), CO, SO(2), NO(2)) pollutants. The estimated effects of air pollution on mortality were adjusted for day of week effects, and several meteorologic variables including temperature, change in barometric pressure, and relative humidity. Several gaseous pollutants were associated with an increased risk of mortality. Specifically for an increase equivalent to the difference between the 90th and 10th percentiles, the estimated percent change in daily mortality based on the 3-day average of NO(2), and SO(2) was 4.0% and 1.3%, respectively. The corresponding changes in mortality associated with SO(2) were much higher when analyses were restricted to death from respiratory disease. Specifically, a difference between the 90th and 10th percentiles was associated with a 5.6% (95% CI= -0.7% to 12.3%). The daily mean coarse fraction (PM(10-2.5)) was associated with increased cardiovascular mortality (estimated change=5.9%, 95% CI=1.1-10.8%). PM(2.5) was not found to be an important predictor of mortality. For NO(2), CO, and SO(2), there was some suggestion of increased risk of all-cause and cardiovascular mortality at lower levels of socioeconomic status. However, these results should be interpreted cautiously due to the small number of deaths observed within each stratum of socioeconomic status.