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Objectives: To estimate associations between fine particulate matter (PM 2.5 ) and ozone and the onset of systemic autoimmune rheumatic diseases (SARDs)., Methods: An open cohort of over 6 million adults was constructed from provincial physician billing and hospitalization records between 2000 and 2013. We defined incident SARD cases (SLE, Sjogren's syndrome, scleroderma, polymyositis, dermatomyositis, polyarteritis nodosa and related conditions, polymyalgia rheumatic, other necrotizing vasculopathies, and undifferentiated connective tissue disease) based on at least two relevant billing diagnostic codes (within 2 years, with at least 1 billing from a rheumatologist), or at least one relevant hospitalization diagnostic code. Estimated PM 2.5 and ozone concentrations (derived from remote sensing and/or chemical transport models) were assigned to subjects based on residential postal codes, updated throughout follow-up. Cox proportional hazards models with annual exposure levels were used to calculate hazard ratios (HRs) for SARDs incidence, adjusting for sex, age, urban-versus-rural residence, and socioeconomic status., Results: The adjusted HR for SARDS related to one interquartile range increase in PM 2.5 (3.97 µg/m 3 ) was 1.12 (95% confidence interval 1.08-1.15), but there was no clear association with ozone. Indirectly controlling for smoking did not alter the findings., Conclusions: We found associations between SARDs incidence and PM 2.5 , but no relationships with ozone. Additional studies are needed to better understand interplays between the many constituents of air pollution and rheumatic diseases., (© 2022. The Author(s).)

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., (Crown Copyright © 2021. Published by Elsevier Ltd. All rights reserved.)

Field studies have shown that dense tree canopies and regular tree arrangements reduce noise from a point source. In urban areas, noise sources are multiple and tree arrangements are rarely dense. There is a lack of data on the association between the urban tree canopy characteristics and noise in complex urban settings. Our aim was to investigate the spatial variation of urban tree canopy characteristics, indices of vegetation abundance, and environmental noise levels. Using Light Detection and Ranging point cloud data for 2015, we extracted the characteristics of 1,272,069 public and private trees across the island of Montreal, Canada. We distinguished needle-leaf from broadleaf trees, and calculated the percentage of broadleaf trees, the total area of the crown footprint, the mean crown centroid height, and the mean volume of crowns of trees that were located within 100m, 250m, 500m, and 1000m buffers around 87 in situ noise measurement sites. A random forest model incorporating tree characteristics, the normalized difference vegetation index (NDVI) values, and the distances to major urban noise sources (highways, railways and roads) was employed to estimate variation in noise among measurement locations. We found decreasing trends in noise levels with increases in total area of the crown footprint and mean crown centroid height. The percentages of increased mean squared error of the regression models indicated that in 500m buffers the total area of the crown footprint (29.2%) and the mean crown centroid height (12.6%) had a stronger influence than NDVI (3.2%) in modeling noise levels; similar patterns of influence were observed using other buffers. Our findings suggest that municipal initiatives designed to reduce urban noise should account for tree features, and not just the number of trees or the overall amount of vegetation., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The original coronavirus disease 2019 (COVID-19) outbreak in Wuhan, China has become a global pandemic. By tracking the earliest 118 COVID-19 cases in Canada, we produced a Voronoi treemap to show the travel origins of the country's earliest COVID-19 cases. By March 11, 2020, even though the majority (64.1%) of the world's COVID-19 confirmed cases still had their origin in China, only 7.6% of Canada's first 118 COVID-19 cases were related to travelers from China. The most commonly reported travel history among the 118 cases related to the Middle East, the United States, and Europe. Thus, in retrospect, broadening of early screening tools and travel restrictions to countries and regions outside China may have helped control global COVID-19 spread., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Air pollution has many adverse health effects, but the combined or synergistic effects of multiple ambient air pollutants on anti-nuclear antibodies (ANA, a serologic marker of systemic autoimmune rheumatic disease, SARDs) have never been assessed., Objective: To flexibly model ANA and individual and joint associations of long-term exposures to nitrogen dioxide (NO 2 ), ozone (O 3 ), and fine particles matter (PM 2.5 ) using a Bayesian Kernel machine regression (BKMR) approach and to compare the results to those from individual logistic regressions., Methods: Serum ANA positivity was determined for randomly selected CARTaGENE general population subjects in Quebec, Canada. CARTaGENE is a public research platform created for investigating the associations of environmental, genomic, and lifestyle factors on chronic diseases. Ambient NO 2 , O 3 , and PM 2.5 estimates, derived from ground-measurement and chemical-transport-model simulated concentrations, were assigned to subjects based on residential postal codes at the time of blood collection. Our models adjusted for age, sex, French Canadian origin, smoking, and family income., Results: Concentrations of NO 2 , O 3 , and PM 2.5 were closely correlated in space. In the 5485 CARTaGENE subjects studied, we did not see clear associations between NO 2 , PM 2.5 or O 3 and ANA positivity, with either the BKMR or logistic models., Conclusions: BKMR did not uncover associations between ANA positivity and individual levels or combined exposures of NO 2 , O 3 , and PM 2.5 ; neither did simpler logistic models. Additional studies (in younger populations, in distinct race/ethnicity groups, and/or in jurisdictions with high air pollution levels) would be helpful to reinforce current findings., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)