Examining the Shape of the Association between Low Levels of Fine Particulate Matter and Mortality across Three Cycles of the Canadian Census Health and Environment Cohort

Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning

Global fine particulate matter (PM2.5) assessment is impeded by a paucity of monitors. We improve estimation of the global distribution of PM2.5 concentrations by developing, optimizing, and applying a convolutional neural network with information from satellite-, simulation-, and monitor-based sources to predict the local bias in monthly geophysical a priori PM2.5 concentrations over 1998-2019. We develop a loss function that incorporates geophysical a priori estimates and apply it in model training to address the unrealistic results produced by mean-square-error loss functions in regions with few monitors. We introduce novel spatial cross-validation for air quality to examine the importance of considering spatial properties. We address the sharp decline in deep learning model performance in regions distant from monitors by incorporating the geophysical a priori PM2.5. The resultant monthly PM2.5 estimates are highly consistent with spatial cross-validation PM2.5 concentrations from monitors globally and regionally. We withheld 10% to 99% of monitors for testing to evaluate the sensitivity and robustness of model performance to the density of ground-based monitors. The model incorporating the geophysical a priori PM2.5 concentrations remains highly consistent with observations globally even under extreme conditions (e.g., 1% for training, R2 = 0.73), while the model without exhibits weaker performance (1% for training, R2 = 0.51).

Monthly average air pollution models using geographically weighted regression in Europe from 2000 to 2019

Detailed spatial models of monthly air pollution levels at a very fine spatial resolution (25 m) can help facilitate studies to explore critical time-windows of exposure at intermediate term. Seasonal changes in air pollution may affect both levels and spatial patterns of air pollution across Europe. We built Europe-wide land-use regression (LUR) models to estimate monthly concentrations of regulated air pollutants (NO2, O3, PM10 and PM2.5) between 2000 and 2019. Monthly average concentrations were collected from routine monitoring stations. Including both monthly-fixed and -varying spatial variables, we used supervised linear regression (SLR) to select predictors and geographically weighted regression (GWR) to estimate spatially-varying regression coefficients for each month. Model performance was assessed with 5-fold cross-validation (CV). We also compared the performance of the monthly LUR models with monthly adjusted concentrations. Results revealed significant monthly variations in both estimates and model structure, particularly for O3, PM10, and PM2.5. The 5-fold CV showed generally good performance of the monthly GWR models across months and years (5-fold CV R2: 0.31-0.66 for NO2, 0.4-0.79 for O3, 0.4-0.78 for PM10, 0.46-0.87 for PM2.5). Monthly GWR models slightly outperformed monthly-adjusted models. Correlations between monthly GWR model were generally moderate to high (Pearson correlation >0.6). In conclusion, we are the first to develop robust monthly LUR models for air pollution in Europe. These monthly LUR models, at a 25 m spatial resolution, enhance epidemiologists to better characterize Europe-wide intermediate-term health effects related to air pollution, facilitating investigations into critical exposure time windows in birth cohort studies.

Differential Participation, a Potential Cause of Spurious Associations in Observational Cohorts in Environmental Epidemiology

Differential participation in observational cohorts may lead to biased or even reversed estimates. In this article, we describe the potential for differential participation in cohorts studying the etiologic effects of long-term environmental exposures. Such cohorts are prone to differential participation because only those who survived until the start of follow-up and were healthy enough before enrollment will participate, and many environmental exposures are prevalent in the target population and connected to participation via factors such as geography or frailty. The relatively modest effect sizes of most environmental exposures also make any bias induced by differential participation particularly important to understand and account for. We discuss key points to consider for evaluating differential participation and use causal graphs to describe two example mechanisms through which differential participation can occur in health studies of long-term environmental exposures. We use a real-life example, the Canadian Community Health Survey cohort, to illustrate the non-negligible bias due to differential participation. We also demonstrate that implementing a simple washout period may reduce the bias and recover more valid results if the effect of interest is constant over time. Furthermore, we implement simulation scenarios to confirm the plausibility of the two mechanisms causing bias and the utility of the washout method. Since the existence of differential participation can be difficult to diagnose with traditional analytical approaches that calculate a summary effect estimate, we encourage researchers to systematically investigate the presence of time-varying effect estimates and potential spurious patterns (especially in initial periods in the setting of differential participation).

Two-sample mendelian randomization analysis investigates ambient fine particulate matter's impact on cardiovascular disease development

PM2.5, a key component of air pollution, significantly threatens public health. Cardiovascular disease is increasingly associated with air pollution, necessitating more research. This study used a meticulous two-sample Mendelian randomization (MR) approach to investigate the potential causal link between elevated PM2.5 levels and 25 types of cardiovascular diseases. Data sourced from the UK Biobank, focusing on individuals of European ancestry, underwent primary analysis using Inverse Variance Weighting. Additional methods such as MR-Egger, weighted median, Simple mode, and Weighted mode provided support. Sensitivity analyses assessed instrument variable heterogeneity, pleiotropy, and potential weak instrument variables. The study revealed a causal link between PM2.5 exposure and higher diagnoses of Atherosclerotic heart disease (primary or secondary, OR [95% CI] 1.0307 [1.0103-1.0516], p-value = 0.003 and OR [95% CI] 1.0179 [1.0028-1.0333], p-value = 0.0202) and Angina pectoris (primary or secondary, OR [95% CI] 1.0303 [1.0160-1.0449], p-value = 3.04e-05 and OR [95% CI] 1.0339 [1.0081-1.0603], p-value = 0.0096). Additionally, PM2.5 exposure increased the likelihood of diagnoses like Other forms of chronic ischaemic heart disease (secondary, OR [95% CI] 1.0193 [1.0042-1.0346], p-value = 0.0121), Essential hypertension (secondary, OR [95% CI] 1.0567 [1.0142-1.1010], p-value = 0.0085), Palpitations (OR [95% CI] 1.0163 [1.0071-1.0257], p-value = 5e-04), and Stroke (OR [95% CI] 1.0208 [1.0020-1.0401], p-value = 0.0301). Rigorous sensitivity analyses confirmed these significant findings' robustness and validity. Our study revealed the causal effect between higher PM2.5 concentrations and increased cardiovascular disease risks. This evidence is vital for policymakers and healthcare providers, urging targeted interventions to reduce PM2.5 levels.

[Health protection and climate change require ambitious limit values for air pollutants in Europe : Opinion on the revision of the Directive on Air Quality and Clean Air for Europe of the Environmental Public Health commission of the Robert Koch Institute and the Federal Environment Agency]

Based on scientific findings, the World Health Organization (WHO) has recommended stricter guideline values for air quality in 2021. Significant reductions in the annual mean values of particulate matter (particle size 2.5 µm or smaller, PM2.5) and long-term exposure to nitrogen dioxide (NO2) and ozone (O3) were put forward. The risk of mortality already increases above the WHO guideline values, as shown in studies investigating low concentrations of air pollutants. In Germany, the 2021 WHO guideline values for PM2.5 and NO2 were clearly exceeded in 2022.In this position paper we give the following recommendations for the European Air Quality Directive: (1) set binding limit values according to WHO 2021, (2) apply the limit values to the whole of Europe, (3) continue and expand the established country-based monitoring networks, (4) expand air quality measurements for ultrafine particles and soot particles, and (5) link air pollution control and climate protection measures.Stricter limits for air pollutants require societal and political changes in areas such as mobility, energy use and generation, and urban and spatial planning. Implementation according to WHO 2021 would lead to a net economic benefit of 38 billion euros per year.Ambitious limit values for air pollutants also have an impact on climate change mitigation and its health impacts. The Environmental Public Health commission concludes that more ambitious limit values are crucial to enable effective health protection in Germany and calls for air pollutant limit values in line with the 2021 WHO recommendations to become binding in Europe.

Inequality in the Distribution of Air Pollution Attributable Mortality Within Canadian Cities

Recent studies have identified inequality in the distribution of air pollution attributable health impacts, but to our knowledge this has not been examined in Canadian cities. We evaluated the extent and sources of inequality in air pollution attributable mortality at the census tract (CT) level in seven of Canada's largest cities. We first regressed fine particulate matter (PM2.5) and nitrogen dioxide (NO2) attributable mortality against the neighborhood (CT) level prevalence of age 65 and older, low income, low educational attainment, and identification as an Indigenous (First Nations, Métis, Inuit) or Black person, accounting for spatial autocorrelation. We next examined the distribution of baseline mortality rates, PM2.5 and NO2 concentrations, and attributable mortality by neighborhood (CT) level prevalence of these characteristics, calculating the concentration index, Atkinson index, and Gini coefficient. Finally, we conducted a counterfactual analysis of the impact of reducing baseline mortality rates and air pollution concentrations on inequality in air pollution attributable mortality. Regression results indicated that CTs with a higher prevalence of low income and Indigenous identity had significantly higher air pollution attributable mortality. Concentration index, Atkinson index, and Gini coefficient values revealed different degrees of inequality among the cities. Counterfactual analysis indicated that inequality in air pollution attributable mortality tended to be driven more by baseline mortality inequalities than exposure inequalities. Reducing inequality in air pollution attributable mortality requires reducing disparities in both baseline mortality and air pollution exposure.

Association between long-term exposure to wildfire-related PM2.5 and mortality: A longitudinal analysis of the UK Biobank

Little is known about the associations between long-term exposure to wildfire-related fine particulate matter (PM_2.5) and mortality. We aimed to explore theses associations using the data from the UK Biobank cohort. Long-term wildfire-related PM_2.5 exposure was defined as the 3-year cumulative concentrations of wildfire-related PM_2.5 within a 10-km buffer surrounding the residential address for each individual. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using the time-varying Cox regression model. We included 492,394 participants aged between 38 and 73 years. We found that after adjusting for potential covariates, a 10 μg/m³ increase of wildfire-related PM_2.5 exposure was associated with a 0.4% higher risk of all-cause mortality (HR = 1.004 [95% CI: 1.001, 1.006]) and nonaccidental mortality (HR = 1.004 [95% CI: 1.002, 1.006]), and a 0.5% higher risk of neoplasm mortality (HR = 1.005 [95% CI: 1.002, 1.008]). However, no significant associations were observed between wildfire-related PM_2.5 exposure and mortality from cardiovascular, respiratory, and mental diseases. Additionally, no significant modification effects of a series of modifiers were observed. Targeted health protection strategies should be adopted in response to wildfire-related PM_2.5 exposure, in order to reduce the risk of premature mortality.

Association between exposure to multiple air pollutants, transportation noise and cause-specific mortality in adults in Switzerland

BACKGROUND

Long-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for a range of air pollutants and transportation noise.

METHODS

Over 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM_2.5, PM_2.5 components (Cu, Fe, S and Zn), NO₂, black carbon (BC) and ozone (O₃) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges.

RESULTS

During follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM_2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m³ PM_2.5, 1.050 (1.041, 1.059) per 10 µg/m³ NO₂, 1.057 (1.048, 1.067) per 0.5 × 10^-5/m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO₂, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM_2.5 was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m³ for PM_2.5 and NO₂, < 1.5 10^-5/m BC and < 53 dB Lden total transportation noise. The O₃ association was inverse for all outcomes. Including noise attenuated all outcome associations, though many remained significant. Across outcomes, noise was robust to adjustment to air pollutants (e.g. natural mortality 1.037 (1.033, 1.042) per 10 dB Lden total transportation noise, after including BC).

CONCLUSION

Long-term exposure to air pollution and transportation noise in Switzerland contribute to premature mortality. Considering co-exposures revealed the importance of local traffic-related pollutants such as NO₂, BC and transportation noise.

Air quality in post-mining towns: tracking potentially toxic elements using tree leaves

In this study, leaves of the evergreen holm oak Quercus ilex were used to assess airborne contamination of potentially toxic elements (PTEs) at five towns located on the slopes of the Mt. Amiata (central Italy), an area with a long history of mining and, more recently, an important district for the industrial exploitation of geothermal energy. PTE composition and covariance of washed and unwashed Q. ilex leaves of three different ages (6, 12 and 24 month-old) were used to identify atmospheric inputs of PTEs at residential areas, evaluate long-term adsorption and retention of PTEs by the leaves, thus providing an indication of potential human exposure. Moreover, the determination of foliar concentrations of major elements (C, N, S and P) allowed an assessment of the nutritional status of the investigated urban tree stands which excluded the existence of stress condition caused by air pollution or other disturbances. Results indicated that overall Pb, Cu, and Cd concentration were low in the investigated urban sites, if compared with similar studies conducted in larger Italian cities, denoting a low contribution of vehicular traffic to the atmospheric pathway. The five urban settlements were characterized by a specific profile of elements (Al, Ba, Hg and Sb) enriched in unwashed leaves, resulting from the distinct geochemical characteristics of the area and from diffuse (i.e., urban activity) and point sources of PTEs emission (i.e., brownfields, geothermal power plants). The latter sources primarily govern the distribution of Hg, whose contamination was found to be very localized close to a major abandoned mining area. Our data provided quantitative evidence of the spectrum of PTEs potentially impacting resident population and may prove useful in support of follow-up instrumental monitoring campaigns of air quality, as well as for human health and ecological risk assessments.

Using Parametric g-Computation to Estimate the Effect of Long-Term Exposure to Air Pollution on Mortality Risk and Simulate the Benefits of Hypothetical Policies: The Canadian Community Health Survey Cohort (2005 to 2015)

BACKGROUND

Numerous epidemiological studies have documented the adverse health impact of long-term exposure to fine particulate matter [particulate matter ≤2.5μm in aerodynamic diameter (PM2.5)] on mortality even at relatively low levels. However, methodological challenges remain to consider potential regulatory intervention's complexity and provide actionable evidence on the predicted benefits of interventions. We propose the parametric g-computation as an alternative analytical approach to such challenges.

METHOD

We applied the parametric g-computation to estimate the cumulative risks of nonaccidental death under different hypothetical intervention strategies targeting long-term exposure to PM2.5 in the Canadian Community Health Survey cohort from 2005 to 2015. On both relative and absolute scales, we explored the benefits of hypothetical intervention strategies compared with the natural course that a) set the simulated exposure value at each follow-up year to a threshold value if exposure was above the threshold (8.8 μg/m3, 7.04 μg/m3, 5 μg/m3, and 4 μg/m3), and b) reduced the simulated exposure value by a percentage (5% and 10%) at each follow-up year. We used the 3-y average PM2.5 concentration with 1-y lag at the postal code of respondents' annual mailing addresses as their long-term exposure to PM2.5. We considered baseline and time-varying confounders, including demographics, behavior characteristics, income level, and neighborhood socioeconomic status. We also included the R syntax for reproducibility and replication.

RESULTS

All hypothetical intervention strategies explored led to lower 11-y cumulative mortality risks than the estimated value under the natural course without intervention, with the smallest reduction of 0.20 per 1,000 participants (95% CI: 0.06, 0.34) under the threshold of 8.8 μg/m3, and the largest reduction of 3.40 per 1,000 participants (95% CI: -0.23, 7.03) under the relative reduction of 10% per interval. The reductions in cumulative risk, or numbers of deaths that would have been prevented if the intervention was employed instead of maintaining the status quo, increased over time but flattened toward the end of the follow-up period. Estimates among those ≥65 years of age were greater with a similar pattern. Our estimates were robust to different model specifications.

DISCUSSION

We found evidence that any intervention further reducing the long-term exposure to PM2.5 would reduce the cumulative mortality risk, with greater benefits in the older population, even in a population already exposed to low levels of ambient PM2.5. The parametric g-computation used in this study provides flexibilities in simulating real-world interventions, accommodates time-varying exposure and confounders, and estimates adjusted survival curves with clearer interpretation and more information than a single hazard ratio, making it a valuable analytical alternative in air pollution epidemiological research. https://doi.org/10.1289/EHP11095.

Inequities in ambient fine particulate matter: A spatiotemporal analysis in Canadian communities

BACKGROUND

Exposure to fine particulate matter (PM_2.5) is associated with adverse health outcomes but communities are not randomly exposed to PM_2.5. Previous cross-sectional environmental injustice analyses in Canada found disproportionately higher exposure to PM_2.5 in low-income populations, visible minorities and immigrants. Beyond static surveillance, it is also important to evaluate how changes in PM_2.5 exposure over time may differentially impact disadvantaged communities. We examine whether communities with different sociodemographic characteristics benefited equitably from the overall decreases in ambient concentrations of PM_2.5 from 2001 to 2016 in Canada.

METHODS

We derived census tract level estimates of average annual PM_2.5 using validated satellite-based estimations of annual average PM_2.5 concentration surfaces. We investigated how the spatial distribution of PM_2.5 has evolved over 15 years (2001-2016) by comparing absolute values and rank percentiles of census tract level annual average PM_2.5 concentrations in 2001 and 2016. Using decennial census data and multivariable linear regression, we determined if sociodemographic characteristics are associated with changes in exposure to PM_2.5, accounting for geographic boundary changes between census periods.

RESULTS

Overall, ambient PM_2.5 concentrations decreased from 2001 (median of 9.1 μg/m³) to 2016 (median of 6.4 μg/m³), with varying provincial patterns. Across communities, ranked census tract specific PM_2.5 in 2001 and in 2016 are highly correlated (Spearman's rho = 0.75). We found that, on average and accounting for provincial differences and baseline PM_2.5, communities with greater density of aboriginal population, lower education, higher shelter-cost-to-income ratio, unemployment or lower income experienced smaller absolute decreases in PM_2.5 from 2001 to 2016.

CONCLUSIONS

Identifying sociodemographic groups that benefit least from decreasing exposure to PM_2.5 highlights the need to consider environmental injustice when designing or revising air pollution policies.

Association between cold weather, influenza infection, and asthma exacerbation in adults in Hong Kong

Despite a conspicuous exacerbation of asthma among patients hospitalized due to influenza infection, no study has attempted previously to elucidate the relationship between environmental factors, influenza activity, and asthma simultaneously in adults. In this study, we examined this relationship using population-based hospitalization records over 22 years. Daily numbers of hospitalizations due to asthma in adults of 41 public hospitals in Hong Kong during 1998-2019 were obtained. The data were matched with meteorological records and air pollutant concentrations. We used type-specific and all-type influenza-like illness plus (ILI+) rates as proxies for seasonal influenza activity. Quasi-Poisson generalized additive models together with distributed-lag non-linear models were used to examine the association. A total of 212,075 hospitalization episodes due to asthma were reported over 22 years. The cumulative adjusted relative risk (ARR) of asthma hospitalizations reached 1.15 (95 % confidence interval [CI], 1.12-1.18) when the ILI+ total rate increased from zero to 20.01 per 1000 consultations. Compared with the median temperature, a significantly increased risk of asthma hospitalization (cumulative ARR = 1.10, 95 % CI, 1.05-1.15) was observed at the 5^th percentile of temperature (i.e., 14.6 °C). Of the air pollutants, oxidant gas was significantly associated with asthma, but only at its extreme level of concentrations. In conclusion, cold conditions and influenza activities are risk factors to asthma exacerbation in adult population. Influenza-related asthma exacerbation that appeared to be more common in the warm and hot season, is likely to be attributable to influenza A/H3N2. The heavy influence of both determinants on asthma activity implies that climate change may complicate the asthma burden.

Mortality Attributable to Ambient Air Pollution: A Review of Global Estimates

Since the publication of the first epidemiological study to establish the connection between long-term exposure to atmospheric pollution and effects on human health, major efforts have been dedicated to estimate the attributable mortality burden, especially in the context of the Global Burden of Disease (GBD). In this work, we review the estimates of excess mortality attributable to outdoor air pollution at the global scale, by comparing studies available in the literature. We find large differences between the estimates, which are related to the exposure response functions as well as the number of health outcomes included in the calculations, aspects where further improvements are necessary. Furthermore, we show that despite the considerable advancements in our understanding of health impacts of air pollution and the consequent improvement in the accuracy of the global estimates, their precision has not increased in the last decades. We offer recommendations for future measurements and research directions, which will help to improve our understanding and quantification of air pollution-health relationships.

Wildfire-related PM2.5 and DNA methylation: An Australian twin and family study

BACKGROUND

Wildfire-related fine particulate matter (PM_2.5) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM_2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM_2.5.

METHODS

We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM_2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant's home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM_2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate.

RESULTS

The 3-year average wildfire-related PM_2.5 (range: 0.3 to 7.6 µg/m³_, mean: 1.6 µg/m³) was negatively, but not significantly (p-values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM_2.5 (Bonferroni adjusted p-value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM_2.5.

CONCLUSIONS

Long-term exposure to wildfire-related PM_2.5 was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM_2.5.

Impact of lowering fine particulate matter from major emission sources on mortality in Canada: A nationwide causal analysis

Emissions of fine particulate matter (PM_2.5) from human activities have been linked to substantial disease burdens, but evidence regarding how reducing PM_2.5 at its sources would improve public health is sparse. We followed a population-based cohort of 2.7 million adults across Canada from 2007 through 2016. For each participant, we estimated annual mean concentrations of PM_2.5 and the fractional contributions to PM_2.5 from the five leading anthropogenic sources at their residential address using satellite observations in combination with a global atmospheric chemistry transport model. For each source, we estimated the causal effects of six hypothetical interventions on 10-y nonaccidental mortality risk using the parametric g-formula, a structural causal model. We conducted stratified analyses by age, sex, and income. This cohort would have experienced tangible health gains had contributions to PM_2.5 from any of the five sources been reduced. Compared with no intervention, a 10% annual reduction in PM_2.5 contributions from transportation and power generation, Canada's largest and fifth-largest anthropogenic sources, would have prevented approximately 175 (95%CI: 123-226) and 90 (95%CI: 63-117) deaths per million by 2016, respectively. A more intensive 50% reduction per year in PM_2.5 contributions from the two sources would have averted 360 and 185 deaths per million, respectively, by 2016. The potential health benefits were greater among men, older adults, and low-income earners. In Canada, where PM_2.5 levels are among the lowest worldwide, reducing PM_2.5 contributions from anthropogenic sources by as little as 10% annually would yield meaningful health gains.

Air Pollution and Pediatric Respiratory Hospitalizations: Effect Modification by Particle Constituents and Oxidative Potential

Rationale: Outdoor particulate and gaseous air pollutants impair respiratory health in children, and these associations may be influenced by particle composition. Objectives: To examine whether associations between short-term variations in fine particulate air pollution, oxidant gases, and respiratory hospitalizations in children are modified by particle constituents (metals and sulfur) or oxidative potential. Methods: We conducted a case-crossover study of 10,500 children (0-17 years of age) across Canada. Daily fine particle mass concentrations and oxidant gases (nitrogen dioxide and ozone) were collected from ground monitors. Monthly estimates of fine particle constituents (metals and sulfur) and oxidative potential were also measured. Conditional logistic regression models were used to estimate associations between air pollutants and respiratory hospitalizations, above and below median values for particle constituents and oxidative potential. Measurements and Main Results: Lag-1 fine particulate matter mass concentrations were not associated with respiratory hospitalizations (odds ratio and 95% confidence interval per 10 μg/m³ increase in fine particulate matter: 1.004 [0.955-1.056]) in analyses ignoring particle constituents and oxidative potential. However, when models were examined above or below median metals, sulfur, and oxidative potential, positive associations were observed above the median. For example, the odds ratio and 95% confidence interval per 10 μg/m³ increase in fine particulate matter were 1.084 (1.007-1.167) when copper was above the median and 0.970 (0.929-1.014) when copper was below the median. Similar trends were observed for oxidant gases. Conclusions: Stronger associations were observed between outdoor fine particles, oxidant gases, and respiratory hospitalizations in children when metals, sulfur, and particle oxidative potential were elevated.

Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE): Phase 2

INTRODUCTION

Mortality is associated with long-term exposure to fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter; PM2.5), although the magnitude and form of these associations remain poorly understood at lower concentrations. Knowledge gaps include the shape of concentration-response curves and the lowest levels of exposure at which increased risks are evident and the occurrence and extent of associations with specific causes of death. Here, we applied improved estimates of exposure to ambient PM2.5 to national population-based cohorts in Canada, including a stacked cohort of 7.1 million people who responded to census year 1991, 1996, or 2001. The characterization of the shape of the concentration-response relationship for nonaccidental mortality and several specific causes of death at low levels of exposure was the focus of the Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE) Phase 1 report. In the Phase 1 report we reported that associations between outdoor PM2.5 concentrations and nonaccidental mortality were attenuated with the addition of ozone (O3) or a measure of gaseous pollutant oxidant capacity (Ox), which was estimated from O3 and nitrogen dioxide (NO2) concentrations. This was motivated by our interests in understanding both the effects air pollutant mixtures may have on mortality and also the role of O3 as a copollutant that shares common sources and precursor emissions with those of PM2.5. In this Phase 2 report, we further explore the sensitivity of these associations with O3 and Ox, evaluate sensitivity to other factors, such as regional variation, and present ambient PM2.5 concentration-response relationships for specific causes of death.

METHODS

PM2.5 concentrations were estimated at 1 km2 spatial resolution across North America using remote sensing of aerosol optical depth (AOD) combined with chemical transport model (GEOS-Chem) simulations of the AOD:surface PM2.5 mass concentration relationship, land use information, and ground monitoring. These estimates were informed and further refined with collocated measurements of PM2.5 and AOD, including targeted measurements in areas of low PM2.5 concentrations collected at five locations across Canada. Ground measurements of PM2.5 and total suspended particulate matter (TSP) mass concentrations from 1981 to 1999 were used to backcast remote-sensing-based estimates over that same time period, resulting in modeled annual surfaces from 1981 to 2016.

Annual exposures to PM2.5 were then estimated for subjects in several national population-based Canadian cohorts using residential histories derived from annual postal code entries in income tax files. These cohorts included three census-based cohorts: the 1991 Canadian Census Health and Environment Cohort (CanCHEC; 2.5 million respondents), the 1996 CanCHEC (3 million respondents), the 2001 CanCHEC (3 million respondents), and a Stacked CanCHEC where duplicate records of respondents were excluded (Stacked CanCHEC; 7.1 million respondents). The Canadian Community Health Survey (CCHS) mortality cohort (mCCHS), derived from several pooled cycles of the CCHS (540,900 respondents), included additional individual information about health behaviors. Follow-up periods were completed to the end of 2016 for all cohorts. Cox proportional hazard ratios (HRs) were estimated for nonaccidental and other major causes of death using a 10-year moving average exposure and 1-year lag. All models were stratified by age, sex, immigrant status, and where appropriate, census year or survey cycle. Models were further adjusted for income adequacy quintile, visible minority status, Indigenous identity, educational attainment, labor-force status, marital status, occupation, and ecological covariates of community size, airshed, urban form, and four dimensions of the Canadian Marginalization Index (Can-Marg; instability, deprivation, dependency, and ethnic concentration). The mCCHS analyses were also adjusted for individual-level measures of smoking, alcohol consumption, fruit and vegetable consumption, body mass index (BMI), and exercise behavior.

In addition to linear models, the shape of the concentration-response function was investigated using restricted cubic splines (RCS). The number of knots were selected by minimizing the Bayesian Information Criterion (BIC). Two additional models were used to examine the association between nonaccidental mortality and PM2.5. The first is the standard threshold model defined by a transformation of concentration equaling zero if the concentration was less than a specific threshold value and concentration minus the threshold value for concentrations above the threshold. The second additional model was an extension of the Shape Constrained Health Impact Function (SCHIF), the eSCHIF, which converts RCS predictions into functions potentially more suitable for use in health impact assessments. Given the RCS parameter estimates and their covariance matrix, 1,000 realizations of the RCS were simulated at concentrations from the minimum to the maximum concentration, by increments of 0.1 μg/m3. An eSCHIF was then fit to each of these RCS realizations. Thus, 1,000 eSCHIF predictions and uncertainty intervals were determined at each concentration within the total range.

Sensitivity analyses were conducted to examine associations between PM2.5 and mortality when in the presence of, or stratified by tertile of, O3 or Ox. Additionally, associations between PM2.5 and mortality were assessed for sensitivity to lower concentration thresholds, where person-years below a threshold value were assigned the mean exposure within that group. We also examined the sensitivity of the shape of the nonaccidental mortality-PM2.5 association to removal of person-years at or above 12 μg/m3 (the current U.S. National Ambient Air Quality Standard) and 10 μg/m3 (the current Canadian and former [2005] World Health Organization [WHO] guideline, and current WHO Interim Target-4). Finally, differences in the shapes of PM2.5-mortality associations were assessed across broad geographic regions (airsheds) within Canada.

RESULTS

The refined PM2.5 exposure estimates demonstrated improved performance relative to estimates applied previously and in the MAPLE Phase 1 report, with slightly reduced errors, including at lower ranges of concentrations (e.g., for PM2.5 <10 μg/m3).

Positive associations between outdoor PM2.5 concentrations and nonaccidental mortality were consistently observed in all cohorts. In the Stacked CanCHEC analyses (1.3 million deaths), each 10-μg/m3 increase in outdoor PM2.5 concentration corresponded to an HR of 1.084 (95% confidence interval [CI]: 1.073 to 1.096) for nonaccidental mortality. For an interquartile range (IQR) increase in PM2.5 mass concentration of 4.16 μg/m3 and for a mean annual nonaccidental death rate of 92.8 per 10,000 persons (over the 1991-2016 period for cohort participants ages 25-90), this HR corresponds to an additional 31.62 deaths per 100,000 people, which is equivalent to an additional 7,848 deaths per year in Canada, based on the 2016 population. In RCS models, mean HR predictions increased from the minimum concentration of 2.5 μg/m3 to 4.5 μg/m3, flattened from 4.5 μg/m3 to 8.0 μg/m3, then increased for concentrations above 8.0 μg/m3. The threshold model results reflected this pattern with -2 log-likelihood values being equal at 2.5 μg/m3 and 8.0 μg/m3. However, mean threshold model predictions monotonically increased over the concentration range with the lower 95% CI equal to one from 2.5 μg/m3 to 8.0 μg/m3. The RCS model was a superior predictor compared with any of the threshold models, including the linear model.

In the mCCHS cohort analyses inclusion of behavioral covariates did not substantially change the results for both linear and nonlinear models. We examined the sensitivity of the shape of the nonaccidental mortality-PM2.5 association to removal of person-years at or above the current U.S. and Canadian standards of 12 μg/m3 and 10 μg/m3, respectively. In the full cohort and in both restricted cohorts, a steep increase was observed from the minimum concentration of 2.5 μg/m3 to 5 μg/m3. For the full cohort and the <12 μg/m3 cohort the relationship flattened over the 5 to 9 μg/m3 range and then increased above 9 μg/m3. A similar increase was observed for the <10 μg/m3 cohort followed by a clear decline in the magnitude of predictions over the 5 to 9 μg/m3 range and an increase above 9 μg/m3. Together these results suggest that a positive association exists for concentrations >9 μg/m3 with indications of adverse effects on mortality at concentrations as low as 2.5 μg/m3.

Among the other causes of death examined, PM2.5 exposures were consistently associated with an increased hazard of mortality due to ischemic heart disease, respiratory disease, cardiovascular disease, and diabetes across all cohorts. Associations were observed in the Stacked CanCHEC but not in all other cohorts for cerebrovascular disease, pneumonia, and chronic obstructive pulmonary disease (COPD) mortality. No significant associations were observed between mortality and exposure to PM2.5 for heart failure, lung cancer, and kidney failure.

In sensitivity analyses, the addition of O3 and Ox attenuated associations between PM2.5 and mortality. When analyses were stratified by tertiles of copollutants, associations between PM2.5 and mortality were only observed in the highest tertile of O3 or Ox. Across broad regions of Canada, linear HR estimates and the shape of the eSCHIF varied substantially, possibly reflecting underlying differences in air pollutant mixtures not characterized by PM2.5 mass concentrations or the included gaseous pollutants. Sensitivity analyses to assess regional variation in population characteristics and access to healthcare indicated that the observed regional differences in concentration-mortality relationships, specifically the flattening of the concentration-mortality relationship over the 5 to 9 μg/m3 range, was not likely related to variation in the makeup of the cohort or its access to healthcare, lending support to the potential role of spatially varying air pollutant mixtures not sufficiently characterized by PM2.5 mass concentrations.

CONCLUSIONS

In several large, national Canadian cohorts, including a cohort of 7.1 million unique census respondents, associations were observed between exposure to PM2.5 with nonaccidental mortality and several specific causes of death. Associations with nonaccidental mortality were observed using the eSCHIF methodology at concentrations as low as 2.5 μg/m3, and there was no clear evidence in the observed data of a lower threshold, below which PM2.5 was not associated with nonaccidental mortality.

An exposure-response meta-analysis of ambient PM2.5 during pregnancy and preeclampsia

Relationships between PM_2.5 exposure and preeclampsia have been the focus of four recent systematic reviews and meta-analyses. We expand on knowledge gaps in these reviews by characterizing the shape of the exposure-outcome relationship, and by assessing the heterogeneity in these associations by study characteristics. Studies of PM_2.5 and preeclampsia were identified from reviews, and confounder-adjusted estimates were extracted. Estimates were derived using a random-effects model. Potential non-linearity was evaluated using a one-stage dose-response meta-analysis. Contrary to previous meta-analyses reporting stronger relationships, the overall adjusted relative risk (RR) for a 10 μg/m³ average increase in PM_2.5 during pregnancy and preeclampsia was modest and not statistically significant (RR: 1.07, 95% CI: 0.99-1.15). This was mainly attributable to inclusion/exclusion decisions for studies made during this review. In addition, there was no evidence of non-linearity, and no important sub-group differences by characteristics such as region, exposure assessment, participant exclusions, and early versus late-onset preeclampsia. Overall, our analysis suggests a modest relationship between ambient PM_2.5 and preeclampsia. We provide details on inclusion and exclusion decisions that were lacking in previous studies, and report novel investigations of non-linearity and heterogeneity.

The global burden of disease attributable to ambient fine particulate matter in 204 countries and territories, 1990-2019: A systematic analysis of the Global Burden of Disease Study 2019

Understanding the spatio-temporal patterns of the disease burden attributable to ambient PM2.5 across the world is essential for the prevention of related diseases, as well as ambient PM2.5 control. Following the framework and methodology of the Global Burden of Disease Study (GBD) in 2019, the global, regional, and national data on ambient PM2.5-attributable death and disability-adjusted life years (DALYs), and the age-standardized rates of mortality (ASMR) and disability-adjusted life years (ASDR) were summarized based on age, gender, year, location and specific diseases. We calculated the average annual percentage change (AAPC) to depict the secular trends of ASMR and ASDR from 1990 to 2019. In 2019, the global ambient PM2.5-related deaths and DALYs were 4,140,970 and 118.2 million, respectively, with 1,702,150 deaths and 47.5 million DALYs for females and 2,438,820 deaths and 70.7 million DALYs for male. In the 13 level-three causes, ischemic heart disease, stroke, chronic obstructive and pulmonary disease (COPD) were the leading three causes of deaths and DALYs attributable to ambient PM2.5. The number of global deaths and DALYs attributable to ambient PM2.5 has increased by 102.3% and 67.7% from 1990 to 2019, respectively. However, ASMR and ASDR showed little change. In the 13 level-three diseases, ischemic heart disease, stroke, COPD, diabetes mellitus, and lung cancer were the top five contributors to the increase of global deaths or DALYs, among which diabetes mellitus had the fastest increase of ASMR and ASDR, with AAPC of 1.5 (95% CI: 1.43, 1.58) and 2.21 (95% CI: 2.15, 2.27), respectively. The population attributable fractions (PAF) of causes in ASMR or ASDR varied significantly across regions, of which PAF of COPD, stroke and lung cancer were the top three. Regarding the GBD region, high PAF mainly occurred in North Africa and Middle East, South Asia, and East Asia. The age-specific PAFs of ischemic heart disease and stroke deaths and DALYs due to ambient PM2.5 were negatively correlated with age. ASMR and ASDR of overall PM2.5 related-burden showed an inverted "V/U" relationship with the socio-demographic index (SDI). The AAPC of ASMR and ASDR of the overall causes showed a strong negative correlation with SDI in 2019, especially at the SDI larger than 0.5. The deaths and DALYs attributable to ambient PM2.5 continued to increase under the context of population growth and aging. Decision-makers should consider controlling the PM2.5 emission when developing the economy.

Low-Concentration Air Pollution and Mortality in American Older Adults: A National Cohort Analysis (2001-2017)

Mounting epidemiological evidence has documented the associations between long-term exposure to multiple air pollutants and increased mortality. There is a pressing need to determine whether risks persist at low concentrations including below current national standards. Air pollution levels have decreased in the United States, and better understanding of the health effects of low-level air pollution is essential for the amendment of National Ambient Air Quality Standards (NAAQS). A nationwide, population-based, open cohort study was conducted to estimate the association between long-term exposure to low-level PM_2.5, NO₂, O₃, and all-cause mortality. The study population included all Medicare enrollees (ages 65 years or older) in the contiguous U.S. from 2001 to 2017. We further defined three low-exposure subcohorts comprised of Medicare enrollees who were always exposed to low-level PM_2.5 (annual mean ≤12-μg/m³), NO₂ (annual mean ≤53-ppb), and O₃ (warm-season mean ≤50-ppb), respectively, over the study period. Of the 68.7-million Medicare enrollees, 33.1% (22.8-million, mean age 75.9 years), 93.8% (64.5-million, mean age 76.2 years), and 65.0% (44.7-million, mean age 75.6 years) were always exposed to low-level annual PM_2.5, annual NO₂, and warm-season O₃ over the study period, respectively. Among the low-exposure cohorts, a 10-μg/m³ increase in PM_2.5, 10-ppb increase in NO₂, and 10-ppb increase in warm-season O₃, were, respectively, associated with an increase in mortality rate ranging between 10 and 13%, 2 and 4%, and 12 and 14% in single-pollutant models, and between 6 and 8%, 1 and 3%, and 9 and 11% in tripollutant models, using three statistical approaches. There was strong evidence of linearity in concentration-response relationships for PM_2.5 and NO₂ at levels below the current NAAQS, suggesting that no safe threshold exists for health-harmful pollution levels. For O₃, the concentration-response relationship shows an increasingly positive association at levels above 40-ppb. In conclusion, exposure to low levels of PM_2.5, NO₂, and warm-season O₃ was associated with an increased risk of all-cause mortality.

Long-term exposure to air pollution and mortality in a Danish nationwide administrative cohort study: Beyond mortality from cardiopulmonary disease and lung cancer

BACKGROUND

The association between long-term exposure to air pollution and mortality from cardiorespiratory diseases is well established, yet the evidence for other diseases remains limited.

OBJECTIVES

To examine the associations of long-term exposure to air pollution with mortality from diabetes, dementia, psychiatric disorders, chronic kidney disease (CKD), asthma, acute lower respiratory infection (ALRI), as well as mortality from all-natural and cardiorespiratory causes in the Danish nationwide administrative cohort.

METHODS

We followed all residents aged ≥ 30 years (3,083,227) in Denmark from 1 January 2000 until 31 December 2017. Annual mean concentrations of fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), black carbon (BC), and ozone (warm season) were estimated using European-wide hybrid land-use regression models (100 m × 100 m) and assigned to baseline residential addresses. We used Cox proportional hazard models to evaluate the association between air pollution and mortality, accounting for demographic and socioeconomic factors. We additionally applied indirect adjustment for smoking and body mass index (BMI).

RESULTS

During 47,023,454 person-years of follow-up, 803,881 people died from natural causes. Long-term exposure to PM_2.5 (mean: 12.4 µg/m³), NO₂ (20.3 µg/m³), and/or BC (1.0 × 10^-5/m) was statistically significantly associated with all studied mortality outcomes except CKD. A 5 µg/m³ increase in PM_2.5 was associated with higher mortality from all-natural causes (hazard ratio 1.11; 95% confidence interval 1.09-1.13), cardiovascular disease (1.09; 1.07-1.12), respiratory disease (1.11; 1.07-1.15), lung cancer (1.19; 1.15-1.24), diabetes (1.10; 1.04-1.16), dementia (1.05; 1.00-1.10), psychiatric disorders (1.38; 1.27-1.50), asthma (1.13; 0.94-1.36), and ALRI (1.14; 1.09-1.20). Associations with long-term exposure to ozone (mean: 80.2 µg/m³) were generally negative but became significantly positive for several endpoints in two-pollutant models. Generally, associations were attenuated but remained significant after indirect adjustment for smoking and BMI.

CONCLUSION

Long-term exposure to PM_2.5, NO₂, and/or BC in Denmark were associated with mortality beyond cardiorespiratory diseases, including diabetes, dementia, psychiatric disorders, asthma, and ALRI.

Long-term exposure to wildfires and cancer incidence in Canada: a population-based observational cohort study

BACKGROUND

Wildfires emit many carcinogenic pollutants that contaminate air, water, terrestrial, and indoor environments. However, little is known about the relationship between exposure to wildfires and cancer risk. We aimed to assess the associations between residential exposure to wildfires and the incidence of several cancer outcomes (lung cancer, brain cancer, non-Hodgkin lymphoma, multiple myeloma, and leukaemia) in Canada.

METHODS

We did a population-based observational cohort study of participants in the 1996 Canadian Census Health and Environment Cohort. The 1996 Canadian Census Health and Environment Cohort is a nationally representative sample of Canadian adults, followed up for cancer incidence and mortality from 1996 to 2015. For this analysis, we excluded participants who lived in major Canadian cities (with a population size greater than 1·5 million people), recent immigrants, and individuals younger than 25 years or 90 years of age or older at baseline. Exposures to wildfires were assigned on the basis of area burned within a 20 km or 50 km radius of residential locations and updated for annual residential mobility. Multivariable Cox proportional hazards models were used to estimate associations between exposure to wildfires and specific cancers associated with carcinogenic compounds released by wildfires, including lung and brain cancer, non-Hodgkin lymphoma, multiple myeloma, and leukaemia, adjusted for many personal and neighbourhood-level covariates.

FINDINGS

Our analyses included more than 2 million people followed up for a median of 20 years, for a total of 34 million person-years. Wildfire exposure was associated with slightly increased incidence of lung cancer and brain tumours. For example, cohort members exposed to a wildfire within 50 km of residential locations in the past 10 years had a 4·9% relatively higher incidence (adjusted hazard ratio [HR] 1·049, 95% CI 1·028-1·071) of lung cancer than unexposed populations, and a 10% relatively higher incidence (adjusted HR 1·100, 1·026-1·179) of brain tumours. Similar associations were observed for the 20 km buffer size. Wildfires were not associated with haematological cancers in this study, and concentration-response trends were not readily apparent when area burned was modelled as a continuous variable.

INTERPRETATION

Long-term exposure to wildfires might increase the risk of lung cancer and brain tumours. Further work is needed to develop long-term estimates of wildfire exposures that capture the complex mixture of environmental pollutants released during these events.

FUNDING

Canadian Institute for Health Research and Fonds de recherche du Quebec.

Ambient air pollution and the risk of acute myocardial infarction and stroke: A national cohort study

We used a large national cohort in Canada to assess the incidence of acute myocardial infarction (AMI) and stroke hospitalizations in association with long-term exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃). The study population comprised 2.7 million respondents from the 2006 Canadian Census Health and Environment Cohort (CanCHEC), followed for incident hospitalizations of AMI or stroke between 2006 and 2016. We estimated 10-year moving average estimates of PM_2.5, NO₂, and O₃, annually. We used Cox proportional hazards models to examine the associations adjusting for various covariates. For AMI, each interquartile range (IQR) increase in exposure was found to be associated with a hazard ratio of 1.026 (95% CI: 1.007-1.046) for PM_2.5, 1.025 (95% CI: 1.001-1.050) for NO₂, and 1.062 (95% CI: 1.041-1.084) for O₃, respectively. Similarly, for stroke, an IQR increase in exposure was associated with a hazard ratio of 1.078 (95% CI: 1.052-1.105) for PM_2.5, 0.995 (95% CI: 0.965-1.030) for NO₂, and 1.055 (95% CI: 1.028-1.082) for O₃, respectively. We found consistent evidence of positive associations between long-term exposures to PM_2.5, and O₃, and to a lesser degree NO₂, with incident AMI and stroke hospitalizations.

Association of weather, air pollutants, and seasonal influenza with chronic obstructive pulmonary disease hospitalization risks

The influences of weather and air pollutants on chronic obstructive pulmonary disease (COPD) have been well-studied. However, the heterogeneous effects of different influenza viral infections, air pollution and weather on COPD admissions and re-admissions have not been thoroughly examined. In this study, we aimed to elucidate the relationships between meteorological variables, air pollutants, seasonal influenza, and hospital admissions and re-admissions due to COPD in Hong Kong, a non-industrial influenza epicenter. A total number of 507703 hospital admissions (i.e., index admissions) and 301728 re-admission episodes (i.e., episodes within 30 days after the previous discharge) for COPD over 14 years (1998-2011) were obtained from all public hospitals. The aggregated weekly numbers were matched with meteorological records and outdoor air pollutant concentrations. Type-specific and all-type influenza-like illness positive (ILI+) rates were used as proxies for influenza activity. Generalized additive models were used in conjunction with distributed-lag non-linear models to estimate the associations of interest. According to the results, high concentrations of fine particulate matter, oxidant gases, and cold weather were strong independent risk factors of COPD outcomes. The cumulative adjusted relative risks exhibited a monotone increasing trend except for ILI+ B, and the numbers were statistically significant over the entire observed range of ILI+ total and ILI+ A/H3N2 when the reference rate was zero. COPD hospitalization risk from influenza infection was higher in the elderly than that in the general population. In conclusion, our results suggest that health administrators should impose clean air policies, such as strengthening emissions control on petrol vehicles, to reduce pollution from oxidant gases and particulates. An extension of the influenza vaccination program for patients with COPD may need to be encouraged: for example, vaccination may be included in hospital discharge planning, particularly before the winter epidemic.

Proximity to coal-fired power plants and neurobehavioral symptoms in children

BACKGROUND

Coal-fired power plants are a major source of air pollution that can impact children's health. Limited research has explored if proximity to coal-fired power plants contributes to children's neurobehavioral disorders.

OBJECTIVE

This community-based study collected primary data to investigate the relationships of residential proximity to power plants and neurobehavioral problems in children.

METHODS

235 participants aged 6-14 years who lived within 10 miles of two power plants were recruited. Exposure to particulate matter ≤10 μm (PM₁₀) was measured in children's homes using personal modular impactors. Neurobehavioral symptoms were assessed using the Child Behavior Checklist (CBCL). Multiple regression models were performed to test the hypothesized associations between proximity/exposure and neurobehavioral symptoms. Geospatial statistical methods were used to map the spatial patterns of exposure and neurobehavioral symptoms.

RESULTS

A small proportion of the variations of neurobehavioral problems (social problems, affective problems, and anxiety problems) were explained by the regression models in which distance to power plants, traffic proximity, and neighborhood poverty was statistically associated with the neurobehavioral health outcomes. Statistically significant hot spots of participants who had elevated levels of attention deficit hyperactivity disorder, anxiety, and social problems were observed in the vicinity of the two power plants.

SIGNIFICANCE

Results of this study suggest an adverse impact of proximity to power plants on children's neurobehavioral health. Although coal-fired power plants are being phased out in the US, health concern about exposure from coal ash storage facilities remains. Furthermore, other countries in the world are increasing coal use and generating millions of tons of pollutants and coal ash. Findings from this study can inform public health policies to reduce children's risk of neurobehavioral symptoms in relation to proximity to power plants.

Long-term exposure to low ambient air pollution concentrations and mortality among 28 million people: results from seven large European cohorts within the ELAPSE project

BACKGROUND

Long-term exposure to ambient air pollution has been associated with premature mortality, but associations at concentrations lower than current annual limit values are uncertain. We analysed associations between low-level air pollution and mortality within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE).

METHODS

In this multicentre longitudinal study, we analysed seven population-based cohorts of adults (age ≥30 years) within ELAPSE, from Belgium, Denmark, England, the Netherlands, Norway, Rome (Italy), and Switzerland (enrolled in 2000-11; follow-up until 2011-17). Mortality registries were used to extract the underlying cause of death for deceased individuals. Annual average concentrations of fine particulate matter (PM_2·5), nitrogen dioxide (NO₂), black carbon, and tropospheric warm-season ozone (O₃) from Europe-wide land use regression models at 100 m spatial resolution were assigned to baseline residential addresses. We applied cohort-specific Cox proportional hazard models with adjustment for area-level and individual-level covariates to evaluate associations with non-accidental mortality, as the main outcome, and with cardiovascular, non-malignant respiratory, and lung cancer mortality. Subset analyses of participants living at low pollutant concentrations (as per predefined values) and natural splines were used to investigate the concentration-response function. Cohort-specific effect estimates were pooled in a random-effects meta-analysis.

FINDINGS

We analysed 28 153 138 participants contributing 257 859 621 person-years of observation, during which 3 593 741 deaths from non-accidental causes occurred. We found significant positive associations between non-accidental mortality and PM_2·5, NO₂, and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021-1·085) per 5 μg/m³ increment in PM_2·5, 1·044 (1·019-1·069) per 10 μg/m³ NO₂, and 1·039 (1·018-1·059) per 0·5 × 10^-5/m black carbon. Associations with PM_2·5, NO₂, and black carbon were slightly weaker for cardiovascular mortality, similar for non-malignant respiratory mortality, and stronger for lung cancer mortality. Warm-season O₃ was negatively associated with both non-accidental and cause-specific mortality. Associations were stronger at low concentrations: HRs for non-accidental mortality at concentrations lower than the WHO 2005 air quality guideline values for PM_2·5 (10 μg/m³) and NO₂ (40 μg/m³) were 1·078 (1·046-1·111) per 5 μg/m³ PM_2·5 and 1·049 (1·024-1·075) per 10 μg/m³ NO₂. Similarly, the association between black carbon and non-accidental mortality was highest at low concentrations, with a HR of 1·061 (1·032-1·092) for exposure lower than 1·5× 10^-5/m, and 1·081 (0·966-1·210) for exposure lower than 1·0× 10^-5/m.

INTERPRETATION

Long-term exposure to concentrations of PM_2·5 and NO₂ lower than current annual limit values was associated with non-accidental, cardiovascular, non-malignant respiratory, and lung cancer mortality in seven large European cohorts. Continuing research on the effects of low concentrations of air pollutants is expected to further inform the process of setting air quality standards in Europe and other global regions.

FUNDING

Health Effects Institute.

Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution: Implementation of Causal Inference Methods

This report provides a final summary of the principal findings and key conclusions of a study supported by an HEI grant aimed at "Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution." It is the second and final report on this topic. The study was designed to advance four critical areas of inquiry and methods development. First, it focused on predicting short- and long-term exposures to ambient fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) at high spatial resolution (1 km × 1 km) for the continental United States over the period 2000-2016 and linking these predictions to health data. Second, it developed new causal inference methods for estimating exposure-response (ER) curves (ERCs) and adjusting for measured confounders. Third, it applied these methods to claims data from Medicare and Medicaid beneficiaries to estimate health effects associated with short- and long-term exposure to low levels of ambient air pollution. Finally, it developed pipelines for reproducible research, including approaches for data sharing, record linkage, and statistical software. Our HEI-funded work has supported an extensive portfolio of analyses and the development of statistical methods that can be used to robustly understand the health effects of short- and long-term exposure to low levels of ambient air pollution. Our Phase 1 report (Dominici et al. 2019) provided a high-level overview of our statistical methods, data analysis, and key findings, grouped into the following five areas: (1) exposure prediction, (2) epidemiological studies of ambient exposures to air pollution at low levels, (3) sensitivity analysis, (4) methodological contributions in causal inference, and (5) an open access research data platform. The current, final report includes a comprehensive overview of the entire research project.

Considering our (1) massive study population, (2) numerous sensitivity analyses, and (3) transparent assessment of covariate balance indicating the quality of causal inference for simulating randomized experiments, we conclude that conditionally on the required assumptions for causal inference, our results collectively indicate that long-term PM2.5 exposure is likely to be causally related to mortality. This conclusion assumes that the causal inference assumptions hold and, more specifically, that we accounted adequately for confounding bias. We explored various modeling approaches, conducted extensive sensitivity analyses, and found that our results were robust across approaches and models. This work relied on publicly available data, and we have provided code that allows for reproducibility of our analyses.

Our work provides comprehensive evidence of associations between exposures to PM2.5, NO2, and O3 and various health outcomes. In the current report, we report more specific results on the causal link between long-term exposure to PM2.5 and mortality, even at PM2.5 levels below or equal to 12 μg/m3, and mortality among Medicare beneficiaries (ages 65 and older). This work relies on newly developed causal inference methods for continuous exposure.

For the period 2000-2016, we found that all statistical approaches led to consistent results: a 10-μg/m3 decrease in PM2.5 led to a statistically significant decrease in mortality rate ranging between 6% and 7% (= 1 - 1/hazard ratio [HR]) (HR estimates 1.06 [95% CI, 1.05 to 1.08] to 1.08 [95% CI, 1.07 to 1.09]). The estimated HRs were larger when studying the cohort of Medicare beneficiaries that were always exposed to PM2.5 levels lower than 12 μg/m3 (1.23 [95% CI, 1.18 to 1.28] to 1.37 [95% CI, 1.34 to 1.40]).

Comparing the results from multiple and single pollutant models, we found that adjusting for the other two pollutants slightly attenuated the causal effects of PM2.5 and slightly elevated the causal effects of NO2 exposure on all-cause mortality. The results for O3 remained almost unchanged.

We found evidence of a harmful causal relationship between mortality and long-term PM2.5 exposures adjusted for NO2 and O3 across the range of annual averages between 2.77 and 17.16 μg/m3 (included >98% of observations) in the entire cohort of Medicare beneficiaries across the continental United States from 2000 to 2016. Our results are consistent with recent epidemiological studies reporting a strong association between long-term exposure to PM2.5 and adverse health outcomes at low exposure levels. Importantly, the curve was almost linear at exposure levels lower than the current national standards, indicating aggravated harmful effects at exposure levels even below these standards.

There is, in general, a harmful causal impact of long-term NO2 exposures to mortality adjusted for PM2.5 and O3 across the range of annual averages between 3.4 and 80 ppb (included >98% of observations). Yet within low levels (annual mean ≤53 ppb) below the current national standards, the causal impacts of NO2 exposures on all-cause mortality are nonlinear with statistical uncertainty.

The ERCs of long-term O3 exposures on all-cause mortality adjusted for PM2.5 and NO2 are almost flat below 45 ppb, which shows no statistically significant effect. Yet we observed an increased hazard when the O3 exposures were higher than 45 ppb, and the HR was approximately 1.10 when comparing Medicare beneficiaries with annual mean O3 exposures of 50 ppb versus those with 30 ppb.

institutions, including those that support the Health Effects Institute; therefore, it may not reflect the views or policies of these parties, and no endorsement by them should be inferred.

A list of abbreviations and other terms appears at the end of this volume.

Fine particles matter components and interstitial lung disease in rheumatoid arthritis

Exposure to ambient fine particulate matter (PM_2.5) is a risk factor for pulmonary and systemic autoimmune diseases, however evidence on which PM_2.5 chemical components are more harmful is still scant. Our goal is to investigate potential associations between PM_2.5 components and interstitial lung disease (ILD) onset in rheumatoid arthritis (RA).New-onset RA subjects identified from a United States health care insurance database (MarketScan) were followed for new onset of RA associated ILD (RA-ILD) from 2011 to 2018. Annual ambient PM_2.5 concentrations of its chemical components (i.e. sulfate, nitrate, ammonium, organic matter, black carbon, mineral dust, and sea salt) were estimated by combining satellite retrievals with chemical transport modelling and refined by geographically weighted regression. Exposures from 2006 up to one year before ILD onset or end of study were assigned to subjects based on their metropolitan division or core-based statistical area codes. A novel time-to-event quantile-based g(generalised)-computation approach was used to estimate potential associations between RA-ILD onset and the exposure mixture of all seven PM_2.5 chemical components adjusting for age, sex, and prior chronic obstructive pulmonary disease (as a proxy for smoking).We followed 280 516 new-onset RA patients and detected 2194 RA-ILD cases across 1 394 385 person-years. The adjusted hazard ratio for RA-ILD onset was 1.54 (95% confidence interval 1.47-1.63) per every decile increase in all seven exposures. Ammonium, mineral dust, and black carbon contributed more to ILD risk than the other PM_2.5 components.In conclusion, exposure to elements of PM_2.5, particularly ammonium, increases ILD risk in RA.

The influence of outdoor PM2.5 concentration at workplace on nonaccidental mortality estimates in a Canadian census-based cohort

Background

Associations between mortality and exposure to ambient air pollution are usually explored using concentrations of residential outdoor fine particulate matter (PM_2.5) to estimate individual exposure. Such studies all have an important limitation in that they do not capture data on individual mobility throughout the day to areas where concentrations may be substantially different, leading to possible exposure misclassification. We examine the possible role of outdoor PM_2.5 concentrations at work for a large population-based mortality cohort.

Methods

Using the 2001 Canadian Census Health and Environment Cohort (CanCHEC), we created a time-weighted average that incorporates employment hours worked in the past week and outdoor PM_2.5 concentration at work and home. We used a Cox proportional hazard model with a 15-year follow-up (2001 to 2016) to explore whether inclusion of workplace estimates had an impact on hazard ratios for mortality for this cohort.

Results

Hazard ratios relying on outdoor PM_2.5 concentration at home were not significantly different from those using a time-weighted estimate, for the full cohort, nor for those who commute to a regular workplace. When exploring cohort subgroups according to neighborhood type and commute distance, there was a notable but insignificant change in risk of nonaccidental death for those living in car-oriented neighborhoods, and with commutes greater than 10 km.

Conclusions

Risk analyses performed with large cohorts in low-pollution environments do not seem to be biased if relying solely on outdoor PM_2.5 concentrations at home to estimate exposure.

Long-term ozone exposure and mortality from neurological diseases in Canada

BACKGROUND

There is increasing interest in the health effects of air pollution. However, the relationships between ozone exposure and mortality attributable to neurological diseases remain unclear.

OBJECTIVES

To assess associations of long-term exposure to ozone with death from Parkinson's disease, dementia, stroke, and multiple sclerosis.

METHODS

Our analyses were based on the 2001 Canadian Census Health and Environment Cohort. Census participants were linked with vital statistics records through 2016, resulting in a cohort of 3.5 million adults/51,045,700 person-years, with 8,500/51,300/43,300/1,300 deaths from Parkinson's/dementia/stroke/multiple sclerosis, respectively. Ten-year average ozone concentrations estimated by chemical transport models and adjusted by ground measurements were assigned to subjects based on postal codes. Cox proportional hazards models were used to calculate hazard ratios (HRs) for deaths from the four neurological diseases, adjusting for eight common demographic and socioeconomic factors, seven environmental indexes, and six contextual covariates.

RESULTS

The fully adjusted HRs for Parkinson's, dementia, stroke, and multiple sclerosis mortalities related to one interquartile range increase in ozone (10.1 ppb), were 1.09 (95% confidence interval 1.04-1.14), 1.08 (1.06-1.10), 1.06 (1.04-1.09), and 1.35 (1.20-1.51), respectively. The covariates did not influence significance of the ozone-mortality associations, except airshed (i.e., broad region of Canada). During the period of 2001-2016, 5.66%/5.01%/ 3.77%/19.11% of deaths from Parkinson's/dementia/stroke/multiple sclerosis, respectively, were attributable to ozone exposure.

CONCLUSIONS

We found positive associations between ozone exposure and mortality due to Parkinson's, dementia, stroke, and multiple sclerosis.

Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty

Annual global satellite-based estimates of fine particulate matter (PM2.5) are widely relied upon for air-quality assessment. Here, we develop and apply a methodology for monthly estimates and uncertainties during the period 1998-2019, which combines satellite retrievals of aerosol optical depth, chemical transport modeling, and ground-based measurements to allow for the characterization of seasonal and episodic exposure, as well as aid air-quality management. Many densely populated regions have their highest PM2.5 concentrations in winter, exceeding summertime concentrations by factors of 1.5-3.0 over Eastern Europe, Western Europe, South Asia, and East Asia. In South Asia, in January, regional population-weighted monthly mean PM2.5 concentrations exceed 90 μg/m3, with local concentrations of approximately 200 μg/m3 for parts of the Indo-Gangetic Plain. In East Asia, monthly mean PM2.5 concentrations have decreased over the period 2010-2019 by 1.6-2.6 μg/m3/year, with decreases beginning 2-3 years earlier in summer than in winter. We find evidence that global-monitored locations tend to be in cleaner regions than global mean PM2.5 exposure, with large measurement gaps in the Global South. Uncertainty estimates exhibit regional consistency with observed differences between ground-based and satellite-derived PM2.5. The evaluation of uncertainty for agglomerated values indicates that hybrid PM2.5 estimates provide precise regional-scale representation, with residual uncertainty inversely proportional to the sample size.

Changes in exposure to ambient fine particulate matter after relocating and long term survival in Canada: quasi-experimental study

OBJECTIVE

To investigate the association between changes in long term residential exposure to ambient fine particulate matter (PM_2.5) and premature mortality in Canada.

DESIGN

Population based quasi-experimental study.

SETTING

Canada.

PARTICIPANTS

663 100 respondents to the 1996, 2001, and 2006 Canadian censuses aged 25-89 years who had consistently lived in areas with either high or low PM_2.5 levels over five years preceding census day and moved during the ensuing five years.

INTERVENTIONS

Changes in long term exposure to PM_2.5 arising from residential mobility.

MAIN OUTCOME MEASURES

The primary outcome was deaths from natural causes. Secondary outcomes were deaths from any cardiometabolic cause, any respiratory cause, and any cancer cause. All outcomes were obtained from the national vital statistics database.

RESULTS

Using a propensity score matching technique with numerous personal, socioeconomic, health, and environment related covariates, each participant who moved to a different PM_2.5 area was matched with up to three participants who moved within the same PM_2.5 area. In the matched groups that moved from high to intermediate or low PM_2.5 areas, residential mobility was associated with a decline in annual PM_2.5 exposure from 10.6 μg/m³ to 7.4 and 5.0 μg/m³, respectively. Conversely, in the matched groups that moved from low to intermediate or high PM_2.5 areas, annual PM_2.5 increased from 4.6 μg/m³ to 6.7 and 9.2 μg/m³. Five years after moving, individuals who experienced a reduction in exposure to PM_2.5 from high to intermediate levels showed a 6.8% (95% confidence interval 1.7% to 11.7%) reduction in mortality (2510 deaths in 56 025 v 4925 deaths in 101 960). A greater decline in mortality occurred among those exposed to a larger reduction in PM_2.5. Increased mortality was found with exposure to PM_2.5 from low to high levels, and to a lesser degree from low to intermediate levels. Furthermore, the decreases in PM_2.5 exposure were most strongly associated with reductions in cardiometabolic deaths, whereas the increases in PM_2.5 exposure were mostly related to respiratory deaths. No strong evidence was found for the changes in PM_2.5 exposure with cancer related deaths.

CONCLUSIONS

In Canada, decreases in PM_2.5 were associated with lower mortality, whereas increases in PM_2.5 were associated with higher mortality. These results were observed at PM_2.5 levels considerably lower than many other countries, providing support for continuously improving air quality.

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.

Characterizing the sources, concentrations and resuspension potential of metals and metalloids in the thoracic fraction of urban road dust

Road dust is a sink and source of metals and metalloids of human health concern. To date, many studies have examined the composition of road dust but there remain critical knowledge gaps on the chemistry of thoracic fractions (< 10 μm) and their patterns of deposition and resuspension. The goal of this study is to characterize the elemental concentrations and sources of thoracic fractions of road dust and their resuspension potential for Toronto, Ontario, Canada. Bulk and thoracic road sweepings were acid digested (HF, HClO₄, HNO₃ and HCl) and the elemental concentrations measured using ICP-MS. Principal component analysis (PCA) was applied to infer source emissions. Annual elemental loadings to roads were estimated using data on total sweepings collected by the City of Toronto. The mass amounts of metals and metalloids (< 10 μm) available for resuspension were calculated assuming a contribution of 10% to total loadings for this fraction. The median trace element concentrations in city sweepings (n = 64) ranged from highest to lowest as follows: Mn > Zn > Ba > Cr > Cu > Pb > V > Ni > Sn > Mo > Co > As > Sb > Cd. Iron, Cr, Ni, Co, Mo and Cu levels were significantly associated with road class, with the highest concentrations measured for the expressway. Most elements, especially Sb and Zn, were enriched in thoracic sweepings. The PCA results demonstrate the importance of non-fossil fuel, traffic-related elemental emissions. Difficulties in identifying sources, given uncertainties regarding overlapping chemical profiles, are also highlighted. Significant elemental loadings to roads were estimated to occur, with the largest amounts identified for Fe, Al, Mn, Zn, Cr and Cu. Road dust resuspension is predicted to be the most important source of emissions for Fe, Al, Mn, Cr, V, Sn, Mo, Co and Sb.

Impact of long-term exposure to PM2.5 and temperature on coronavirus disease mortality: observed trends in France

BACKGROUND

The outbreak of coronavirus disease (COVID-19) began in Wuhan, China in December 2019 and was declared a global pandemic on 11 March 2020. This study aimed to assess the effects of temperature and long-term exposure to air pollution on the COVID-19 mortality rate at the sub-national level in France.

METHODS

This cross-sectional study considered different periods of the COVID-19 pandemic from May to December 2020. It included 96 departments (or NUTS 3) in mainland France. Data on long-term exposure to particulate matter (PM2.5), annual mean temperature, health services, health risk, and socio-spatial factors were used as covariates in negative binomial regression analysis to assess their influence on the COVID-19 mortality rate. All data were obtained from open-access sources.

RESULTS

The cumulative COVID-19 mortality rate by department increased during the study period in metropolitan France-from 19.8/100,000 inhabitants (standard deviation (SD): 20.1) on 1 May 2020, to 65.4/100,000 inhabitants (SD: 39.4) on 31 December 2020. The rate was the highest in the departments where the annual average of long-term exposure to PM2.5 was high. The negative binomial regression models showed that a 1 μg/m3 increase in the annual average PM2.5 concentration was associated with a statistically significant increase in the COVID-19 mortality rate, corresponding to 24.4%, 25.8%, 26.4%, 26.7%, 27.1%, 25.8%, and 15.1% in May, June, July, August, September, October, and November, respectively. This association was no longer significant on 1 and 31 December 2020. The association between temperature and the COVID-19 mortality rate was only significant on 1 November, 1 December, and 31 December 2020. An increase of 1 °C in the average temperature was associated with a decrease in the COVID-19-mortality rate, corresponding to 9.7%, 13.3%, and 14.5% on 1 November, 1 December, and 31 December 2020, respectively.

CONCLUSION

This study found significant associations between the COVID-19 mortality rate and long-term exposure to air pollution and temperature. However, these associations tended to decrease with the persistence of the pandemic and massive spread of the disease across the entire country.

Long term exposure to low level air pollution and mortality in eight European cohorts within the ELAPSE project: pooled analysis

OBJECTIVE

To investigate the associations between air pollution and mortality, focusing on associations below current European Union, United States, and World Health Organization standards and guidelines.

DESIGN

Pooled analysis of eight cohorts.

SETTING

Multicentre project Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) in six European countries.

PARTICIPANTS

325 367 adults from the general population recruited mostly in the 1990s or 2000s with detailed lifestyle data. Stratified Cox proportional hazard models were used to analyse the associations between air pollution and mortality. Western Europe-wide land use regression models were used to characterise residential air pollution concentrations of ambient fine particulate matter (PM_2.5), nitrogen dioxide, ozone, and black carbon.

MAIN OUTCOME MEASURES

Deaths due to natural causes and cause specific mortality.

RESULTS

Of 325 367 adults followed-up for an average of 19.5 years, 47 131 deaths were observed. Higher exposure to PM_2.5, nitrogen dioxide, and black carbon was associated with significantly increased risk of almost all outcomes. An increase of 5 µg/m³ in PM_2.5 was associated with 13% (95% confidence interval 10.6% to 15.5%) increase in natural deaths; the corresponding figure for a 10 µg/m³ increase in nitrogen dioxide was 8.6% (7% to 10.2%). Associations with PM_2.5, nitrogen dioxide, and black carbon remained significant at low concentrations. For participants with exposures below the US standard of 12 µg/m³ an increase of 5 µg/m³ in PM_2.5 was associated with 29.6% (14% to 47.4%) increase in natural deaths.

CONCLUSIONS

Our study contributes to the evidence that outdoor air pollution is associated with mortality even at low pollution levels below the current European and North American standards and WHO guideline values. These findings are therefore an important contribution to the debate about revision of air quality limits, guidelines, and standards, and future assessments by the Global Burden of Disease.

Ambient Air Pollution and Stillbirths Risk in Sydney, Australia

We aimed to determine the associations between ambient air pollution, specifically particulate matter less than or equal to 10 microns and 2.5 microns (PM₁₀ and PM_2.5 respectively) and ozone (O₃), and stillbirths. We analysed all singleton births between 20–42 weeks gestation in metropolitan Sydney, Australia, from 1997 to 2012. We implemented logistic regression to assess the associations between air pollutants and stillbirth for each trimester and for the entire pregnancy. Over the study period, there were 967,694 live births and 4287 stillbirths. Mean levels of PM₁₀, PM_2.5 and O₃ for the entire pregnancy were 17.9 µg/m³, 7.1 µg/m³ and 3.2 ppb, respectively. Adjusted odds ratios were generally greater than unity for associations between PM and stillbirths, but none were statistically significant. There were no significant associations between O₃ and stillbirths. There was potential effect modification of the PM₁₀ and O₃ association by maternal age. We did not find consistent evidence of associations between PM and O₃ and stillbirths in Sydney, Australia. More high quality birth cohort studies are required to clarify associations between air pollution and stillbirths.

Source sector and fuel contributions to ambient PM2.5 and attributable mortality across multiple spatial scales

Ambient fine particulate matter (PM_2.5) is the world's leading environmental health risk factor. Reducing the PM_2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM_2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74-1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM_2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52-0.95] million deaths; 19.2%), industrial (0.45 [0.32-0.58] million deaths; 11.7%), and energy (0.39 [0.28-0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.

Particulate Air Pollution and Risk of Cardiovascular Events Among Adults With a History of Stroke or Acute Myocardial Infarction

Background

Previous studies have found associations between fine particulate matter <2.5 µm in diameter (PM_2.5) and increased risk of cardiovascular disease (CVD) among populations with no CVD history. Less is understood about susceptibility of adults with a history of CVD and subsequent PM_2.5‐related CVD events and whether current regulation levels for PM_2.5 are protective for this population.

Methods and Results

This retrospective cohort study included 96 582 Kaiser Permanente Northern California adults with a history of stroke or acute myocardial infarction. Outcome, covariate, and address data obtained from electronic health records were linked to time‐varying 1‐year mean PM_2.5 exposure estimates based on residential locations. Cox proportional hazard models estimated risks of stroke, acute myocardial infarction, and cardiovascular mortality associated with PM_2.5 exposure, adjusting for multiple covariates. Secondary analyses estimated risks below federal and state regulation levels (12 µg/m³ for 1‐year mean PM_2.5). A 10‐µg/m³ increase in 1‐year mean PM_2.5 exposure was associated with an increase in risk of cardiovascular mortality (hazard ratio [HR], 1.20; 95% CI, 1.11–1.30), but no increase in risk of stroke or acute myocardial infarction. Analyses of <12 µg/m³ showed increased risk for CVD mortality (HR, 2.31; 95% CI, 1.96–2.71), stroke (HR, 1.41; 95% CI, 1.09–1.83]), and acute myocardial infarction (HR, 1.51; 95% CI, 1.21–1.89) per 10‐µg/m³ increase in 1‐year mean PM_2.5.

Conclusions

Adults with a history of CVD are susceptible to the effects of PM_2.5 exposure, particularly on CVD mortality. Increased risks observed at exposure levels <12 µg/m³ highlight that current PM_2.5 regulation levels may not be protective for this susceptible population.

Examining PM2.5 concentrations and exposure using multiple models

Epidemiologic studies have found associations between fine particulate matter (PM_2.5) exposure and adverse health effects using exposure models that incorporate monitoring data and other relevant information. Here, we use nine PM_2.5 concentration models (i.e., exposure models) that span a wide range of methods to investigate i) PM_2.5 concentrations in 2011, ii) potential changes in PM_2.5 concentrations between 2011 and 2028 due to on-the-books regulations, and iii) PM_2.5 exposure for the U.S. population and four racial/ethnic groups. The exposure models included two geophysical chemical transport models (CTMs), two interpolation methods, a satellite-derived aerosol optical depth-based method, a Bayesian statistical regression model, and three data-rich machine learning methods. We focused on annual predictions that were regridded to 12-km resolution over the conterminous U.S., but also considered 1-km predictions in sensitivity analyses. The exposure models predicted broadly consistent PM_2.5 concentrations, with relatively high concentrations on average over the eastern U.S. and greater variability in the western U.S. However, differences in national concentration distributions (median standard deviation: 1.00 μg m^-3) and spatial distributions over urban areas were evident. Further exploration of these differences and their implications for specific applications would be valuable. PM_2.5 concentrations were estimated to decrease by about 1 μg m^-3 on average due to modeled emission changes between 2011 and 2028, with decreases of more than 3 μg m^-3 in areas with relatively high 2011 concentrations that were projected to experience relatively large emission reductions. Agreement among models was closer for population-weighted than uniformly weighted averages across the domain. About 50% of the population was estimated to experience PM_2.5 concentrations less than 10 μg m^-3 in 2011 and PM_2.5 improvements of about 2 μg m^-3 due to modeled emission changes between 2011 and 2028. Two inequality metrics were used to characterize differences in exposure among the four racial/ethnic groups. The metrics generally yielded consistent information and suggest that the modeled emission reductions between 2011 and 2028 would reduce absolute exposure inequality on average.

Taking a stand against air pollution - the impact on cardiovascular disease

Although the attention of the world and the global health community specifically is deservedly focused on the COVID-19 pandemic, other determinants of health continue to have large impacts and may also interact with COVID-19. Air pollution is one crucial example. Established evidence from other respiratory viruses and emerging evidence for COVID-19 specifically indicates that air pollution alters respiratory defense mechanisms leading to worsened infection severity. Air pollution also contributes to co-morbidities that are known to worsen outcomes amongst those infected with COVID-19, and air pollution may also enhance infection transmission due to its impact on more frequent coughing. Yet despite the massive disruption of the COVID-19 pandemic, there are reasons for optimism: broad societal lockdowns have shown us a glimpse of what a future with strong air pollution measures could yield. Thus, the urgency to combat air pollution is not diminished, but instead heightened in the context of the pandemic.

Taking a Stand Against Air Pollution-The Impact on Cardiovascular Disease: A Joint Opinion From the World Heart Federation, American College of Cardiology, American Heart Association, and the European Society of Cardiology

Although the attention of the world and the global health community specifically is deservedly focused on the COVID-19 pandemic, other determinants of health continue to have large impacts and may also interact with COVID-19. Air pollution is one crucial example. Established evidence from other respiratory viruses and emerging evidence for COVID-19 specifically indicates that air pollution alters respiratory defense mechanisms leading to worsened infection severity. Air pollution also contributes to comorbidities that are known to worsen outcomes among those infected with COVID-19, and air pollution may also enhance infection transmission due to its impact on more frequent coughing. Yet despite the massive disruption of the COVID-19 pandemic, there are reasons for optimism: broad societal lockdowns have shown us a glimpse of what a future with strong air pollution measures could yield. Thus, the urgency to combat air pollution is not diminished, but instead heightened in the context of the pandemic.

Taking a Stand Against Air Pollution-The Impact on Cardiovascular Disease: A Joint Opinion from the World Heart Federation, American College of Cardiology, American Heart Association, and the European Society of Cardiology

Although the attention of the world and the global health community specifically is deservedly focused on the COVID-19 pandemic, other determinants of health continue to have large impacts and may also interact with COVID-19. Air pollution is one crucial example. Established evidence from other respiratory viruses and emerging evidence for COVID-19 specifically indicates that air pollution alters respiratory defense mechanisms leading to worsened infection severity. Air pollution also contributes to co-morbidities that are known to worsen outcomes amongst those infected with COVID-19, and air pollution may also enhance infection transmission due to its impact on more frequent coughing. Yet despite the massive disruption of the COVID-19 pandemic, there are reasons for optimism: broad societal lockdowns have shown us a glimpse of what a future with strong air pollution measures could yield. Thus, the urgency to combat air pollution is not diminished, but instead heightened in the context of the pandemic.

Ambient Air Pollution and Mortality among Older Patients Initiating Maintenance Dialysis

BACKGROUND

Fine particulate matter (particulate matter with diameter <2.5 µm [PM2.5]) is associated with CKD progression and may impact the health of patients living with kidney failure. While older (aged ≥65 years) adults are most vulnerable to the impact of PM2.5, it is unclear whether older patients on dialysis are at elevated risk of mortality when exposed to fine particulate matter.

METHODS

Older adults initiating dialysis (2010-2016) were identified from US Renal Data System (USRDS). PM2.5 concentrations were obtained from NASA's Socioeconomic Data and Application Center (SEDAC) Global Annual PM2.5 Grids. We investigated the association between PM2.5 and all-cause mortality using Cox proportional hazard models with linear splines [knot at the current Environmental Protection Agency (EPA) National Ambient Air Quality Standard for PM2.5 of 12 μg/m3] and robust variance.

RESULTS

For older dialysis patients who resided in areas with high PM2.5, a 10 μg/m3 increase in PM2.5 was associated with 1.16-fold (95% CI: 1.08-1.25) increased risk of mortality; furthermore, those who were female (aHR = 1.26, 95% CI: 1.13-1.42), Black (aHR = 1.31, 95% CI: 1.09-1.59), or had diabetes as a primary cause of kidney failure (aHR = 1.25, 95% CI: 1.13-1.38) were most vulnerable to high PM2.5. While the mortality risk associated with PM2.5 was stronger at higher levels (aHR = 1.19, 95% CI: 1.08-1.32), at lower levels (≤12 μg/m3), PM2.5 was significantly associated with mortality risk (aHR = 1.04, 95% CI: 1.00-1.07) among patients aged ≥75 years (Pslope difference = 0.006).

CONCLUSIONS

Older adults initiating dialysis who resided in ZIP codes with PM2.5 levels >12 μg/m3 are at increased risk of mortality. Those aged >75 were at elevated risk even at levels below the EPA Standard for PM2.5.

A leucopoietic-arterial axis underlying the link between ambient air pollution and cardiovascular disease in humans

AIMS

Air pollution [i.e. particulate matter with diameter <2.5 μm (PM2.5)] is a risk factor for major adverse cardiovascular events (MACE). While PM2.5 promotes leucopoiesis and atherosclerotic inflammation in experimental models, it is unknown whether this occurs in humans. We tested in humans (a) whether PM2.5 associates with higher leucopoietic tissue activity and arterial inflammation (ArtI), (ii) whether these associations persist after accounting for the effects of potential confounders including socioeconomics, traffic noise, and risk factors, and (iii) whether these tissue effects mediate the association between air pollution and MACE.

METHODS AND RESULTS

Individuals (N = 503) without cardiovascular disease (CVD) or active malignancy underwent 18 F-fluorodeoxyglucose positron emission tomography/computed tomography. Major adverse cardiovascular event was adjudicated over 5 years of follow-up. Leucopoietic tissue activity (in bone marrow and spleen) as well as ArtI were measured. Annual PM2.5 levels were assessed at each individual's home address. At baseline, higher PM2.5 associated with increased leucopoietic activity [standardized (95% CI): 0.129 (0.042, 0.215), P = 0.004] as well as ArtI [0.088 (0.006, 0.171), P = 0.036] after adjusting for CVD risk factors. Over a median 4.1 years, 40 individuals experienced MACE. PM2.5 exposure associated with MACE [Cox HR (95% CI): 1.404 (1.135, 1.737), P = 0.002], remaining significant after adjustment for CVD risk factors and other potential confounders. Mediation analysis demonstrated that increased leucopoietic activity and ArtI serially mediate the link between PM2.5 exposure and MACE.

CONCLUSIONS

Higher air pollution exposure associates with heightened leucopoietic activity and ArtI and independently predicts MACE through a biological pathway that includes higher leucopoietic activity and ArtI in series.

The Benefits of Intensive Versus Standard Blood Pressure Treatment According to Fine Particulate Matter Air Pollution Exposure: A Post Hoc Analysis of SPRINT

Fine particulate matter <2.5 µm (PM_2.5) air pollution is implicated in global mortality, especially from cardiovascular causes. A large body of evidence suggests a link between PM_2.5 and elevation in blood pressure (BP), with the latter implicated as a potential mediator of cardiovascular events. We sought to determine if the outcomes of intensive BP lowering (systolic BP <120 mm Hg) on cardiovascular events are modified by PM_2.5 exposure in the SPRINT (Systolic BP Intervention Trial). We linked annual PM_2.5 exposure estimates derived from an integrated model to subjects participating in SPRINT. We evaluated the effect of intensive BP lowering by PM_2.5 exposure on the primary outcome in SPRINT using cox-proportional hazard models. A total of 9286 participants were linked to PM_2.5 levels (mean age 68±9 years). Intensive BP-lowering decreased risk of the primary outcome more among patients exposed to higher PM_2.5 (P_interaction=0.047). The estimate for lowering of primary outcome was numerically lower in the highest than in the lower quintiles. The benefits of intensive BP-lowering were larger among patients chronically exposed to PM_2.5 levels above US National Ambient Air Quality Standards of 12 µg/m³ (hazard ratio, 0.47 [95% CI, 0.29-0.74]) compared with those living in cleaner locations (hazard ratio, 0.81 [95% CI, 0.68-0.97]), P_interaction=0.037. This exploratory nonprespecified post hoc analysis of SPRINT suggests that the benefits of intensive BP lowering on the primary outcome was greater in patients exposed to higher PM_2.5, suggesting that the magnitude of benefit may depend upon the magnitude of antecedent PM_2.5 exposure.

Comparison of hospitalization and mortality associated with short-term exposure to ambient ozone and PM2.5 in Canada

BACKGROUND

Hospitalization and mortality (H-M) have been linked to air pollution separately. However, previous studies have not adequately compared whether air pollution is a stronger risk factor for hospitalization or mortality. This study aimed to investigate differences in H-M risk from short-term ozone and PM_2.5 exposures, and determine whether differences are modified by season, age, and sex.

METHODS

Daily ozone, PM_2.5, temperature, and all-cause H-M counts (ICD-10, A00-R99) were collected for 22-24 Canadian cities for up to 29 years. Generalized additive Poisson models were employed to estimate associations between each pollutant and health outcome, which were compared across season (warm, cold, or year-round), age (all ages or seniors > 65), and sex.

RESULTS

Overall, ozone and PM_2.5 showed higher season-specific risk of mortality than hospitalization: warm-season ozone: 0.54% (95% credible interval, 0.20, 0.85) vs. 0.14% (0.02, 0.27) per 10 ppb; and year-round PM_2.5: 0.90% (0.33, 1.41) vs. 0.29% (0.03, 0.56) per 10 μg/m³. While age showed little H-M difference, sex appeared to be a modifier of H-M risk. While females had higher mortality risk, males had higher hospitalization risk: for females, ozone 0.87% (0.36, 1.35) vs. -0.03% (-0.18, 0.11) and PM_2.5 1.19% (0.40, 1.90) vs. 0.19% (-0.10, 0.47); and for males ozone 0.20% (-0.28, 0.65) vs. 0.35% (0.18, 0.51).

CONCLUSION

This study found H-M differences attributable to ozone and PM_2.5, suggesting that both are stronger risk factors for mortality than hospitalization. In addition, there were clear H-M differences by sex: specifically, females showed higher mortality risk and males showed higher hospitalization risk.

Taking a Stand Against Air Pollution - The Impact on Cardiovascular Disease: A Joint Opinion from the World Heart Federation, American College of Cardiology, American Heart Association, and the European Society of Cardiology

Although the attention of the world and the global health community specifically is deservedly focused on the COVID-19 pandemic, other determinants of health continue to have large impacts and may also interact with COVID-19. Air pollution is one crucial example. Established evidence from other respiratory viruses and emerging evidence for COVID-19 specifically indicates that air pollution alters respiratory defense mechanisms leading to worsened infection severity. Air pollution also contributes to co-morbidities that are known to worsen outcomes amongst those infected with COVID-19, and air pollution may also enhance infection transmission due to its impact on more frequent coughing. Yet despite the massive disruption of the COVID-19 pandemic, there are reasons for optimism: broad societal lockdowns have shown us a glimpse of what a future with strong air pollution measures could yield. Thus, the urgency to combat air pollution is not diminished, but instead heightened in the context of the pandemic.

Centralizing environmental datasets to support (inter)national chronic disease research: Values, challenges, and recommendations

Whereas environmental data are increasingly available, it is often not clear how or if datasets are available for health research. Exposure metrics are typically developed for specific research initiatives using disparate exposure assessment methods and no mechanisms are put in place for centralizing, archiving, or distributing environmental datasets. In parallel, potentially vast amounts of environmental data are emerging due to new technologies such as high resolution imagery and machine learning.