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Background Gut damage allows translocation of bacterial lipopolysaccharide (LPS) and fungal β-D-glucan (BDG) into the blood. This microbial translocation contributes to systemic inflammation and risk of non-AIDS comorbidities in people living with HIV, including those receiving antiretroviral therapy (ART). We assessed whether markers of gut damage and microbial translocation were associated with cognition in ART-treated PLWH. Methods Eighty ART-treated men living with HIV from the Positive Brain Health Now Canadian cohort were included. Brief cognitive ability measure (B-CAM) and 20-item patient deficit questionnaire (PDQ) were administered to all participants. Three groups were selected based on their B-CAM levels. We excluded participants who received proton pump inhibitors or antiacids in the past 3 months. Cannabis users were also excluded. Plasma levels of intestinal fatty acid binding protein (I-FABP), regenerating islet-derived protein 3 α (REG3α), and lipopolysaccharides (LPS = were quantified by ELISA, while 1–3-β-D-glucan BDG) levels were assessed using the Fungitell assay. Univariable, multivariable, and splines analyses were performed. Results Plasma levels of I-FABP, REG3α, LPS and BDG were not different between groups of low, intermediate and high B-CAM levels. However, LPS and REG3α levels were higher in participants with PDQ higher than the median. Multivariable analyses showed that LPS association with PDQ, but not B-CAM, was independent of age and level of education. I-FABP, REG3α, and BDG levels were not associated with B-CAM nor PDQ levels in multivariable analyses. Conclusion In this well characterized cohort of ART-treated men living with HIV, bacterial but not fungal translocation was associated with presence of cognitive difficulties. These results need replication in larger samples.

Supplementary Table 1. Sample Size of each participated study, by case-control status and genotype platform. Supplementary Table 2. Association between fourteen environmental factors and the risk of breast cancer. Supplementary Table 3. Interactions between genes and fourteen environmental factors.

Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this.We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test.After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6).In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk.Our study suggests a limited role of gene–environment interactions in breast cancer risk.

Funding and acknowledgements.

Quantile-Quantile plot (Q-Q plot) of the aMiSTi p-values for each set of the GxE interactions.

BackgroundLyme disease is the most common vector-borne illness in the United States. Incidence is related to specific environmental conditions such as temperature, metrics of land cover, and species diversity.ObjectiveTo determine whether greenness, as measured by the Normalized Difference Vegetation Index (NDVI), and other selected indices of land cover were associated with the incidence of Lyme disease in the northeastern USA, 2000-2018.Materials and MethodsWe conducted an ecological analysis of incidence rates in counties of 15 “high” incidence states and the District of Columbia for 2000-2018. Annual counts of Lyme disease by county were obtained from the US Centers for Disease Control and values of NDVI were acquired from the Moderate Resolution Imaging Spectroradiometer instrument aboard Terra and Aqua Satellites. County-specific values of population density, area of land and water were obtained from the US Census. Using quasi-Poisson regression, multivariable associations were estimated between the incidence of Lyme disease NDVI, land cover variables, human population density, and calendar year.ResultsWe found that incidence increased by 7.1% per year (95% confidence interval: 6.8-8.2%). Land cover variables showed complex non-linear associations with incidence: average county-specific NDVI showed a ‘u-shaped” association, the standard deviation of NDVI showed a monotonic upward relationship, population density showed a decreasing trend, areas of land and water showed “n”-shaped relationships. We found an interaction between average and standard deviation of NDVI, with the highest average NDVI category, increased standard deviation of NDVI showed the greatest increase in rates.DiscussionThese associations cannot be interpreted as causal but indicate that certain patterns of land cover may have the potential to increase exposure to infected ticks and thereby may contribute indirectly to increased rates. Public health interventions could make use of these results in informing people where risks may be high.

Little is known about environmental factors that may increase the risk of prostate cancer. We estimated associations between incident prostate cancer and environmental concentrations of five ambient volatile organic compounds (VOCs): benzene; n-decane; ethylbenzene; hexane; and 1,2,4-trimethylbenzene.This study is based on a population-based case-control study of incident prostate cancer (PROtEuS) in men ≤ 75 years of age living in Montreal, Canada, in 2005 to 2012. We included 1172 cases and 1177 population controls. We had personal information, lifetime residential addresses, occupational exposures, and a variety of area-wide covariables. We inferred concentrations of the five VOCs using Bayesian geostatistical models using data from a dense environmental survey conducted in Montreal in 2005 to 2006. We used different sets of adjustments to estimate odds ratios (OR) and confidence intervals.We found nonlinear associations such that the ORs increased monotonically and then either flattened or fell off with increased exposures. The model that contained other environmental variables and contextual variables led to lower ORs and results were similar when we restricted analyses to controls recently screened or tested for prostate cancer or cases with low- or high-grade tumors. A change from the 5th to 25th percentile in mean environmental benzene levels led to an adjusted OR of 2.00 (95% confidence interval = 1.47, 2.71).We found positive associations between prostate cancer and concentrations of benzene and ethylbenzene, independently of previous testing for prostate cancer or tumor grade, suggesting that exposure to certain ambient VOCs may increase incidence.

Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk.

Results from ecological studies have suggested that air pollution increases the risk of developing and dying from COVID-19. Drawing causal inferences from the measures of association reported in ecological studies is fraught with challenges given biases arising from an outcome whose ascertainment is incomplete, varies by region, time, and across sociodemographic characteristics, and cannot account for clustering or within-area heterogeneity. Through a series of analyses, we illustrate the dangers of using ecological studies to assess whether ambient air pollution increases the risk of dying from, or transmitting, COVID-19.We performed an ecological analysis in the continental United States using county-level ambient concentrations of fine particulate matter (PMOur analyses revealed that the shape of the exposure-response curve between PMOur analyses indicated that ecological analyses are prone to showing spurious relationships between ambient air pollution and mortality from COVID-19 as well as the prevalence of HIV. We discuss the many potential biases inherent in any ecological-based analysis of air pollution and COVID-19.

Exposure to biocontaminants, such as dust mites, animal dander, bacteria, and mold, is associated with a range of health effects. This study identified household characteristics associated with indoor biocontaminant loadings in four Canadian cities. Floor dust was collected in 290 Canadian homes in Edmonton, Halifax, Montreal, and Windsor. The dust samples were analyzed for house dust mite allergens (Der f 1 and Der p 1), cat allergen (Fel d 1), cockroach allergen (Bla g 1), beta-(1,3)-D-glucan, and endotoxin. Household information was obtained through questionnaires and home inspections. We performed univariate and multivariate analyses to identify household determinants of biocontaminant loadings and mold odor presence. We observed large regional variations for all biocontaminants, except for cockroach allergen. The ranges of the contaminants measured in loadings and concentrations were similar to that of previous Canadian studies. Household characteristics including presence of carpeting, low floor cleaning frequency, older home age, presence of pets, and indoor relative humidity above 45% were positively associated with the presence of multiple indoor biocontaminants. High floor cleaning frequency and use of dehumidifiers were negatively associated with the presence of multiple indoor biocontaminants. Mold odor was positively associated with older home age, past water damage, and visible mold growth.

The objective of this paper was to estimate the inter-rater reliability of expert assessments of occupational exposures. An inter-rater reliability sub-study was conducted within a population-based case-control study of postmenopausal breast cancer. Detailed information on lifetime occupational histories was obtained from participants and two industrial hygienists assigned exposures to 185 jobs using a checklist of 293 agents. Experts rated exposure for each job-agent combination according to exposure status (unexposed/exposed), confidence that the exposure occurred (possible/probable/definite), intensity (low/medium/high), and frequency (% time per week). The statistical unit of observation was each job-agent assessment (185 jobs × 293 agents = 54,205 assessments per expert). Crude agreement, Gwet AC1/2 statistics, and Cohen's Kappa were used to estimate inter-rater agreement for confidence and intensity; for frequency, the intra-class correlation coefficient (ICC) was used. The majority of job-agent combinations were evaluated by the two experts to be not exposed (crude agreement98% of decisions). The degree of agreement between the experts for the confidence of exposure status was Gwet AC1/2 = 0.99 (95% CI: 0.99-0.99), and for intensity, a Gwet AC2 = 0.99 (95% CI: 0.99-0.99). For frequency, an ICC of 0.31 (95% CI: 0.26-0.35) was found. A sub-analysis restricted to job-agent combinations for which the two experts agreed on exposure status revealed a moderate agreement for confidence of exposure (Gwet AC2 = 0.66) and high agreement for intensity (Gwet AC2 = 0.96). For frequency, the ICC was 0.52 (95% CI: 0.47-0.57). A high level of inter-rater agreement was found for identifying exposures and for coding intensity, but agreement was lower for the coding of frequency of exposure.

Genome-wide analysis identifies 32 loci associated with breast cancer susceptibility, accounting for estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype(1-3). To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 x 10(-8)), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

Lung and female breast cancers are highly prevalent worldwide. Although the association between exposure to ambient fine particulate matter (PM2.5 ) and lung cancer has been recognized, there is less evidence for associations with other common air pollutants such as nitrogen dioxide (NO2 ) and ozone (O3 ). Even less is known about potential associations between these pollutants and breast cancer. We conducted a population-based cohort study to investigate the associations of chronic exposure to PM2.5 , NO2 , O3 and redox-weighted average of NO2 and O3 (Ox ) with incident lung and breast cancer, using the Ontario Population Health and Environment Cohort (ONPHEC), which includes all long-term residents aged 35-85 years who lived in Ontario, Canada, 2001-2015. Incident lung and breast cancers were ascertained using the Ontario Cancer Registry. Annual estimates of exposures were assigned to the residential postal codes of subjects for each year during follow-up. We used Cox proportional-hazards models adjusting for personal- and neighborhood-level covariates. Our cohorts for lung and breast cancer analyses included ~4.9 million individuals and ~2.5 million women, respectively. During follow-up, 100,146 incident cases of lung cancer and 91,146 incident cases of breast cancer were diagnosed. The fully adjusted analyses showed positive associations of lung cancer incidence with PM2.5 (hazard ratio [HR] = 1.02 [95% CI: 1.01-1.05] per 5.3 μg/m3 ) and NO2 (HR = 1.05 [95% CI: 1.03-1.07] per 14 ppb). No associations with lung cancer were observed for O3 or Ox . Relationships between PM2.5 and NO2 with lung cancer exhibited a sublinear shape. We did not find compelling evidence linking air pollution to breast cancer.

Volatile organic compounds (VOCs) are components of the complex mixture of air pollutants within cities and can cause various adverse health effects. Therefore, it is necessary to understand their spatial distribution for exposure assessment in epidemiological studies.The objective was to model measured concentrations of five VOCs within the city of Montreal, Canada, developing spatial prediction models that can be used in health studies.We measured concentrations using 3M 3500 Organic Vapor Monitors, over 2-week periods, for three monitoring campaigns between 2005 and 2006 in over 130 locations in the city. Using GC/MSD (Gas Chromatography/Mass Selective Detector), we measured concentrations of benzene, n-decane, ethylbenzene, hexane, and trimethylbenzene. We fitted four different models that combine land-use regression and geostatistical methods to account for the potential spatial structure that remains after accounting for the land-use variables. The fitted models also accounted for possible variations in the concentration of air pollutants across campaigns.The highest concentrations for all VOCs were found in December with hexane being the most abundant followed by ethylbenzene. We obtained predicted surfaces for the VOCs for the three campaigns and mean surfaces across campaigns. We found higher concentrations of some VOCs along highways and in the Eastern part of Montreal, which is a highly industrialized area.Each of the fitted models captured the spatial and across-campaigns variability for each VOC, and we found that different VOCs required different model structures.

There is little data as to whether exposure to residential greenness is associated with the incidence of breast cancer. Lack of physical activity and obesity are two of the accepted risk factors for postmenopausal breast cancer and living near green areas may contribute to an active lifestyle and maintaining a normal body mass index and, consequently, residential greenness may be associated with lower incidence rates.The objective of this study was to determine whether there was an association between past exposure to residential greenness and the incidence of invasive postmenopausal breast cancer among Canadian women living in Montreal, Quebec, in the mid-2000s.We conducted a population-based, case-control study of incident postmenopausal breast cancer in Montreal, Canada, and herein we show analyses by level of greenness surrounding participants' homes. Incident cases were identified between 2008 and 2011 from all but one hospital that treated breast cancer in the Montreal area. Population controls were identified from provincial electoral lists of Montreal residents and frequency-matched to cases on age. Residential greenness was estimated using the maximum daily normalized difference vegetation index averaged over the growing season ("maximum NDVI"). Maximum NDVI was assigned at the home address of recruitment for the years 1992-1998 (about 15 years before diagnosis), and we measured subjects' personal information, exposure to NOWe found that the response functions between incident postmenopausal breast cancer and maximum NDVI were consistent with linearity. The age-adjusted and fully-adjusted ORs, per increase in the interquartile range (IQR=0.13) of maximum NDVI measured with a 250 m buffer around residences, were 0.95 (95%CI: 0.86-1.04) and 1.00 (95%CI: 0.84-1.11), respectively. For maximum NDVI measured using a 1000 m buffer (IQR=0.05), these were 0.98 (95%CI: 0.94-1.02) and 0.99 (95%CI: 0.95-1.03), respectively.Our findings suggest that exposure to NDVI evaluated where participants were interviewed is not associated with the risk of incident postmenopausal breast cancer.

Background: Epidemiologic studies indicate that early life arsenic exposures are linked to an increased risk of cardiovascular diseases. Different oxidation and methylation states of arsenic exist in the environment and are formed in vivo via the action of arsenic (+3 oxidation state) methyltransferase (As3MT). Methylated arsenicals are pro-atherogenic postnatally, but pre- and perinatal effects are unclear. This is particularly important because methylated arsenicals are known to cross the placenta. Objectives: We tested the effects of early life exposure to inorganic and methylated arsenicals on atherosclerotic plaque formation and its composition in apolipoprotein E knock-out (apoE−/−) mice and evaluated whether apoE−/− mice lacking As3MT expression were susceptible to this effect. Methods: We exposed apoE−/− or apoE−/−/As3MT−/− mice to 200 ppb inorganic or methylated arsenic in the drinking water from conception to weaning and assessed atherosclerotic plaques in the offspring at 18 wk of age. Mixed regression models were used to estimate the mean difference in each outcome relative to controls, adjusting for sex and including a random effects term to account for within-litter clustering. Results: Early life exposure to inorganic arsenic, and more profoundly methylated arsenicals, resulted in significantly larger plaques in the aortic arch and sinus in both sexes. Lipid levels in these plaques were higher without a substantial difference in macrophage numbers. Smooth muscle cell content was not altered, but collagen content was lower. Importantly, there were sex-specific differences in these observations, where males had higher lipids and lower collagen in the plaque, but females did not. In mice lacking As3MT, arsenic did not alter the plaque size, although the size was highly variable. In addition, control apoE−/−/As3MT−/− mice had significantly larger plaque size compared with control apoE−/−. Conclusion: This study shows that early life exposure to inorganic and methylated arsenicals is pro-atherogenic with sex-specific differences in plaque composition and a potential role for As3MT in mice. https://doi.org/10.1289/EHP8171

Objectives To estimate associations between fine particulate matter (PM2.5) 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 PM2.5 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 PM2.5 (3.97 µg/m3) 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 PM2.5, but no relationships with ozone. Additional studies are needed to better understand interplays between the many constituents of air pollution and rheumatic diseases.

Author(s): Coignard, Juliette; Lush, Michael; Beesley, Jonathan; O'Mara, Tracy A; Dennis, Joe; Tyrer, Jonathan P; Barnes, Daniel R; McGuffog, Lesley; Leslie, Goska; Bolla, Manjeet K; Adank, Muriel A; Agata, Simona; Ahearn, Thomas; Aittomaki, Kristiina; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Arnold, Norbert; Aronson, Kristan J; Arun, Banu K; Augustinsson, Annelie; Azzollini, Jacopo; Barrowdale, Daniel; Baynes, Caroline; Becher, Heko; Bermisheva, Marina; Bernstein, Leslie; Bialkowska, Katarzyna; Blomqvist, Carl; Bojesen, Stig E; Bonanni, Bernardo; Borg, Ake; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Buys, Saundra S; Caldes, Trinidad; Caligo, Maria A; Campa, Daniele; Carter, Brian D; Castelao, Jose E; Chang-Claude, Jenny; Chanock, Stephen J; Chung, Wendy K; Claes, Kathleen BM; Clarke, Christine L; GEMO Study Collaborators; EMBRACE Collaborators; Collee, J Margriet; Conroy, Don M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Diez, Orland; Ding, Yuan Chun; Domchek, Susan M; Dork, Thilo; Dos-Santos-Silva, Isabel; Dunning, Alison M; Dwek, Miriam; Eccles, Diana M; Eliassen, A Heather; Engel, Christoph; Eriksson, Mikael; Evans, D Gareth; Fasching, Peter A; Flyger, Henrik; Fostira, Florentia; Friedman, Eitan; Fritschi, Lin; Frost, Debra; Gago-Dominguez, Manuela; Gapstur, Susan M; Garber, Judy; Garcia-Barberan, Vanesa; Garcia-Closas, Montserrat; Garcia-Saenz, Jose A; Gaudet, Mia M; Gayther, Simon A; Gehrig, Andrea; Georgoulias, Vassilios; Giles, Graham G; Godwin, Andrew K; Goldberg, Mark S; Goldgar, David E | Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-23162-4.

Background: Studies have reported that ambient air pollution is associated with an increased risk of developing or dying from coronavirus-2 (COVID-19). Methodological approaches to investigate the health impacts of air pollution on epidemics should differ from those used for chronic diseases, but the methods used in these studies have not been appraised critically. Objectives: Our study aimed to identify and critique the methodological approaches of studies of air pollution on infections and mortality due to COVID-19 and to identify and critique the methodological approaches of similar studies concerning severe acute respiratory syndrome (SARS). Methods: Published and unpublished papers of associations between air pollution and developing or dying from COVID-19 or SARS that were reported as of 10 May 2020 were identified through electronic databases, internet searches, and other sources. Results: All six COVID-19 studies and two of three SARS studies reported positive associations. Two were time series studies that estimated associations between daily changes in air pollution, one was a cohort that assessed associations between air pollution and the secondary spread of SARS, and six were ecological studies that used area-wide exposures and outcomes. Common shortcomings included possible cross-level bias in ecological studies, underreporting of health outcomes, using grouped data, the lack of highly spatially resolved air pollution measures, inadequate control for confounding and evaluation of effect modification, not accounting for regional variations in the timing of outbreaks’ temporal changes in at-risk populations, and not accounting for nonindependence of outcomes. Discussion: Studies of air pollution and novel coronaviruses have relied mainly on ecological measures of exposures and outcomes and are susceptible to important sources of bias. Although longitudinal studies with individual-level data may be imperfect, they are needed to adequately address this topic. The complexities involved in these types of studies underscore the need for careful design and for peer review. https://doi.org/10.1289/EHP7411

BackgroundLiving in greener areas of cities was linked to increased physical activity levels, improved mental well-being, and lowered harmful environmental exposures, all of which may affect human health. However, whether living in greener areas may be associated with lower risk of cardiovascular disease incidence, progression, and premature mortality is unclear.ObjectivesWe conducted a cohort study to examine the associations between residential green spaces and the incidence of acute myocardial infarction (AMI) and heart failure (HF), post-AMI and HF hospital readmissions, and mortality.MethodsWe simultaneously followed four large population-based cohorts in Ontario, Canada, including the entire adult population, adults free of AMI and HF, and survivors of AMI or HF from 2000 to 2014. We estimated residential exposure to green spaces using satellite-derived observations and ascertained health outcomes using validated disease registries. We estimated the associations using spatial random-effects Cox proportional hazards models. We conducted various sensitivity analyses, including further adjusting for property values and performing exploratory mediation analysis.ResultsEach interquartile range increase in residential greenness was associated with a 7% [95% confidence interval (CI): 4%, 9%] decrease in incident AMI and a 6% (95% CI: 4%, 7%) decrease in incident HF. Residential greenness was linked to a ∼10% decrease in cardiovascular mortality in both adults free of AMI and HF and the entire adult population. These associations remained consistent in sensitivity analyses and were accentuated among younger adults. Additionally, we estimated that the decreases in AMI and HF incidence associated with residential greenness explained ∼53% of the protective association between residential greenness and cardiovascular mortality. Conversely, residential greenness was not associated with any delay in readmission or mortality among AMI and HF patients.ConclusionsLiving in urban areas with more green spaces was associated with improved cardiovascular health in people free of AMI and HF but not among individuals who have already developed these conditions. https://doi.org/10.1289/EHP6161.

Background: Living in greener areas of cities was linked to increased physical activity levels, improved mental well-being, and lowered harmful environmental exposures, all of which may affect human health. However, whether living in greener areas may be associated with lower risk of cardiovascular disease incidence, progression, and premature mortality is unclear. Objectives: We conducted a cohort study to examine the associations between residential green spaces and the incidence of acute myocardial infarction (AMI) and heart failure (HF), post-AMI and HF hospital readmissions, and mortality. Methods: We simultaneously followed four large population-based cohorts in Ontario, Canada, including the entire adult population, adults free of AMI and HF, and survivors of AMI or HF from 2000 to 2014. We estimated residential exposure to green spaces using satellite-derived observations and ascertained health outcomes using validated disease registries. We estimated the associations using spatial random-effects Cox proportional hazards models. We conducted various sensitivity analyses, including further adjusting for property values and performing exploratory mediation analysis. Results: Each interquartile range increase in residential greenness was associated with a 7% [95% confidence interval (CI): 4%, 9%] decrease in incident AMI and a 6% (95% CI: 4%, 7%) decrease in incident HF. Residential greenness was linked to a ∼10% decrease in cardiovascular mortality in both adults free of AMI and HF and the entire adult population. These associations remained consistent in sensitivity analyses and were accentuated among younger adults. Additionally, we estimated that the decreases in AMI and HF incidence associated with residential greenness explained ∼53% of the protective association between residential greenness and cardiovascular mortality. Conversely, residential greenness was not associated with any delay in readmission or mortality among AMI and HF patients. Conclusions: Living in urban areas with more green spaces was associated with improved cardiovascular health in people free of AMI and HF but not among individuals who have already developed these conditions. https://doi.org/10.1289/EHP6161

Background Exposure to road traffic noise has been linked to cardiometabolic complications, such as elevated blood pressure and glucose dysregulation. However, epidemiologic evidence linking road traffic noise to diabetes mellitus and hypertension remains scarce. We examined associations between road traffic noise and the incidence of diabetes mellitus and hypertension in Toronto, Canada. Methods and Results Using the Ontario Population Health and Environment Cohort, we conducted a retrospective, population‐based cohort study of long‐term residents of Toronto, aged 35 to 100 years, who were registered for provincial publicly funded health insurance, and were without a history of hypertension (n=701 174) or diabetes mellitus (n=914 607). Road traffic noise exposure levels were assessed by the equivalent continuous A‐weighted sound pressure level (dBA) for the 24‐hour day and the equivalent continuous A‐weighted sound pressure level for the night (11 pm –7 am) . Noise exposures were assigned to subjects according to their annual residential postal codes during the 15‐year follow‐up. We used random‐effect Cox proportional hazards models adjusting for personal and area‐level characteristics. From 2001 to 2015, each interquartile range increase in the equivalent continuous A‐weighted sound pressure level (dBA) for the 24‐hour day (10.0 dBA) was associated with an 8% increase in incident diabetes mellitus (95% CI, 1.07–1.09) and a 2% increase in hypertension (95% CI, 1.01–1.03). We obtained similar estimates with the equivalent continuous A‐weighted sound pressure level for the night (11 pm –7 am) . These results were robust to all sensitivity analyses conducted, including further adjusting for traffic‐related air pollutants (ultrafine particles and nitrogen dioxide). For both hypertension and diabetes mellitus, we observed stronger associations with the equivalent continuous A‐weighted sound pressure level (dBA) for the 24‐hour day among women and younger adults (aged Conclusions Long‐term exposure to road traffic noise was associated with an increased incidence of diabetes mellitus and hypertension in Toronto.

ObjectiveTo assess the associations between ambient temperatures and hospitalisations for coronary heart disease (CHD) and stroke.MethodsOur study comprised all residents living in Ontario, Canada, 1996–2013. For each of 14 health regions, we fitted a distributed lag non-linear model to estimate the cold and heat effects on hospitalisations from CHD, acute myocardial infarction (AMI), stroke and ischaemic stroke, respectively. These effects were pooled using a multivariate meta-analysis. We computed attributable hospitalisations for cold and heat, defined as temperatures above and below the optimum temperature (corresponding to the temperature of minimum morbidity) and for moderate and extreme temperatures, defined using cut-offs at the 2.5th and 97.5th temperature percentiles.ResultsBetween 1996 and 2013, we identified 1.4 million hospitalisations from CHD and 355 837 from stroke across Ontario. On cold days with temperature corresponding to the 1st percentile of temperature distribution, we found a 9% increase in daily hospitalisations for CHD (95% CI 1% to 16%), 29% increase for AMI (95% CI 15% to 45%) and 11% increase for stroke (95% CI 1% to 22%) relative to days with an optimal temperature. High temperatures (the 99th percentile) also increased CHD hospitalisations by 6% (95% CI 1% to 11%) relative to the optimal temperature. These estimates translate into 2.49% of CHD hospitalisations attributable to cold and 1.20% from heat. Additionally, 1.71% of stroke hospitalisations were attributable to cold. Importantly, moderate temperatures, rather than extreme temperatures, yielded the most of the cardiovascular burdens from temperatures.ConclusionsAmbient temperatures, especially in moderate ranges, may be an important risk factor for cardiovascular-related hospitalisations.

Introduction: Emerging studies have implicated air pollution in the neurodegenerative processes. Less is known about the influence of air pollution, especially at the relatively low levels, on developing dementia. We conducted a population-based cohort study in Ontario, Canada, where the concentrations of pollutants are among the lowest in the world, to assess whether air pollution exposure is associated with incident dementia. Methods: The study population comprised all Ontario residents who, on 1 April 2001, were 55–85years old, Canadian-born, and free of physician-diagnosed dementia (~2.1 million individuals). Follow-up extended until 2013. We used population-based health administrative databases with a validated algorithm to ascertain incident diagnosis of dementia as well as prevalent cases. Using satellite observations, land-use regression model, and an optimal interpolation method, we derived long-term average exposure to fine particulate matter (≤2.5μm in diameter) (PM2.5), nitrogen dioxide (NO2), and ozone (O3), respectively at the subjects' historical residences based on a population-based registry. We used multilevel spatial random-effects Cox proportional hazards models, adjusting for individual and contextual factors, such as diabetes, brain injury, and neighborhood income. We conducted various sensitivity analyses, such as lagging exposure up to 10years and considering a negative control outcome for which no (or weaker) association with air pollution is expected. Results: We identified 257,816 incident cases of dementia in 2001–2013. We found a positive association between PM2.5 and dementia incidence, with a hazard ratio (HR) of 1.04 (95% confidence interval (CI): 1.03–1.05) for every interquartile-range increase in exposure to PM2.5. Similarly, NO2 was associated with increased incidence of dementia (HR=1.10; 95% CI: 1.08–1.12). No association was found for O3. These associations were robust to all sensitivity analyses examined. These estimates translate to 6.1% of dementia cases (or 15,813 cases) attributable to PM2.5 and NO2, based on the observed distribution of exposure relative to the lowest quartile in concentrations in this cohort. Discussion: In this large cohort, exposure to air pollution, even at the relative low levels, was associated with higher dementia incidence. Keywords: Fine particulate matter, Nitrogen dioxides, Ozone, Dementia, Cohort

Background In previous studies investigating the short-term health effects of ambient air pollution the exposure metric that is often used is the daily average across monitors, thus assuming that all individuals have the same daily exposure. Studies that incorporate space-time exposures of individuals are essential to further our understanding of the short-term health effects of ambient air pollution. Objectives As part of a longitudinal cohort study of the acute effects of air pollution that incorporated subject-specific information and medical histories of subjects throughout the follow-up, the purpose of this study was to develop and compare different prediction models using data from fixed-site monitors and other monitoring campaigns to estimate daily, spatially-resolved concentrations of ozone (O 3 ) and nitrogen dioxide (NO 2 ) of participants’ residences in Montreal, 1991–2002. Methods We used the following methods to predict spatially-resolved daily concentrations of O 3 and NO 2 for each geographic region in Montreal (defined by three-character postal code areas): (1) assigning concentrations from the nearest monitor; (2) spatial interpolation using inverse-distance weighting; (3) back-extrapolation from a land-use regression model from a dense monitoring survey, and; (4) a combination of a land-use and Bayesian maximum entropy model. We used a variety of indices of agreement to compare estimates of exposure assigned from the different methods, notably scatterplots of pairwise predictions, distribution of differences and computation of the absolute agreement intraclass correlation (ICC). For each pairwise prediction, we also produced maps of the ICCs by these regions indicating the spatial variability in the degree of agreement. Results We found some substantial differences in agreement across pairs of methods in daily mean predicted concentrations of O 3 and NO 2 . On a given day and postal code area the difference in the concentration assigned could be as high as 131 ppb for O 3 and 108 ppb for NO 2 . For both pollutants, better agreement was found between predictions from the nearest monitor and the inverse-distance weighting interpolation methods, with ICCs of 0.89 (95% confidence interval (CI): 0.89, 0.89) for O 3 and 0.81 (95%CI: 0.80, 0.81) for NO 2 , respectively. For this pair of methods the maximum difference on a given day and postal code area was 36 ppb for O 3 and 74 ppb for NO 2 . The back-extrapolation method showed a higher degree of disagreement with the nearest monitor approach, inverse-distance weighting interpolation, and the Bayesian maximum entropy model, which were strongly constrained by the sparse monitoring network. The maps showed that the patterns of agreement differed across the postal code areas and the variability depended on the pair of methods compared and the pollutants. For O 3 , but not NO 2 , postal areas showing greater disagreement were mostly located near the city centre and along highways, especially in maps involving the back-extrapolation method. Conclusions In view of the substantial differences in daily concentrations of O 3 and NO 2 predicted by the different methods, we suggest that analyses of the health effects from air pollution should make use of multiple exposure assessment methods. Although we cannot make any recommendations as to which is the most valid method, models that make use of higher spatially resolved data, such as from dense exposure surveys or from high spatial resolution satellite data, likely provide the most valid estimates.

Background: Air pollution has been classified as a human carcinogen based largely on epidemiological studies of lung cancer. Recent research suggests that exposure to ambient air pollution increases the risk of female breast cancer especially in premenopausal women. Methods: Our objective was to determine the association between residential exposure to ambient nitrogen dioxide (NO2) and newly diagnosed cases of invasive breast cancer in a cohort of 89,247 women enrolled in the Canadian National Breast Screening Study between 1980 and 1985. Vital status and incident breast cancers through 2005 were determined through record linkage to the Canadian national mortality and cancer registries. Estimates of exposures to NO2 using participants’ addresses at time of entry into the study were derived from a national land use regression model. We classified women as reaching menopause according to information obtained at baseline. In addition, as we had no information from women on their menopausal status during the observation period, we conducted analyses using different cut-points for defining postmenopausal status (i.e., at 50 or at 52 years of age), and hence we had four non-independent cohorts. We computed rate ratios for the incidence of breast cancer and their 95% confidence intervals (CI) separately for premenopausal and postmenopausal women. Our Cox models used attained age as the time axis and the rate ratios were adjusted for several individual-level risk factors, including reproductive history, as well as census-based neighborhood-level characteristics. Results: The median concentration of NO2 was about 15 parts per billion (ppb). After adjusting for personal risk factors and contextual variables, we found no evidence of associations for the incidence of breast cancer in the postmenopausal cohorts. In premenopausal women, the rate ratio for an increase of 9.7 ppb (about the interquartile range) was 1.13 (95%CI: 0.94–1.37) for the 50 years of age cut-off for menopausal status and it was 1.17 (95%CI: 1.00–1.38) for the 52 years of age cut-off. Conclusions: Our findings suggest that exposure to low concentrations of NO2, a marker for traffic-related air pollution, increases the risk of premenopausal breast cancer, but not postmenopausal breast cancer. Keywords: Breast cancer, Air pollution, Nitrogen dioxide, Epidemiology, Cohort study

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate PIn-silico analyses showed these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 37.6% for triple-negative and 54.2% for luminal A-like disease. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1–3. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10−8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate (FDR)

Background: Telomere shortening is associated with early mortality and chronic disease. Recent studies indicate that environmental exposures, including urban and traffic-related air pollution, may shorten telomeres. Associations between exposure to household air pollution from solid fuel stoves and telomere length have not been evaluated. Methods: Among 137 rural Chinese women using biomass stoves (mean=55y of age), we measured 48-h personal exposures to fine particulate matter [PM ≤ 2.5μm in aerodynamic diameter (PM2.5)] and black carbon and collected oral DNA on up to three occasions over a period of 2.5 y. Relative telomere length (RTL) was quantified using a modified real-time polymerase chain reaction protocol. Mixed effects regression models were used to investigate the exposure–response associations between household air pollution and RTL, adjusting for key sociodemographic, behavioral, and environmental covariates. Results: Women’s daily exposures to air pollution ranged from 13–1,136 μg/m3 for PM2.5 (mean=154) and 0.1–34 μg/m3 for black carbon (mean=3.6). Natural cubic spline models indicated a mostly linear association between increased exposure to air pollution and shorter RTL, except at very high concentrations where there were few observations. We thus modeled the linear associations with all observations, excluding the highest 3% and 5% of exposures. In covariate-adjusted models, an interquartile range (IQR) increase in exposure to black carbon (3.1 μg/m3) was associated with shorter RTL [all observations: −0.27 (95% CI: −0.48, −0.06); excluding highest 5% exposures: −1.10 (95% CI: −1.63, −0.57)]. Further adjustment for outdoor temperature brought the estimates closer to zero [all observations: −0.15 (95% CI: −0.36, 0.06); excluding highest 5% exposures: −0.68 (95% CI: −1.26, −0.10)]. Models with PM2.5 as the exposure metric followed a similar pattern. Conclusion: Telomere shortening, which is a biomarker of biological aging and chronic disease, may be associated with exposure to air pollution in settings where household biomass stoves are commonly used. https://doi.org/10.1289/EHP4041

Although growing evidence links air pollution to stroke incidence, less is known about the effect of air pollution on atrial fibrillation (AF), an important risk factor for stroke.We assessed the associations between air pollution and incidence of AF and stroke. We also sought to characterize the shape of pollutant-disease relationships.The population-based cohort comprised 5,071,956 Ontario residents, age 35–85 y and without the diagnoses of both outcomes on 1 April 2001 and was followed up until 31 March 2015. AF and stroke cases were ascertained using health administrative databases with validated algorithms. Based on annual residential postal codes, we assigned 5-y running average concentrations of fine particulate matter ([Formula: see text]), nitrogen dioxide ([Formula: see text]), and ozone ([Formula: see text]) from satellite-derived data, a land-use regression model, and a fusion-based method, respectively, as well as redox-weighted averages of [Formula: see text] and [Formula: see text] ([Formula: see text]) for each year. Using Cox proportional hazards models, we estimated the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of AF and stroke with each of these pollutants, adjusting for individual- and neighborhood-level variables. We used newly developed nonlinear risk models to characterize the shape of pollutant–disease relationships.Between 2001 and 2015, we identified 313,157 incident cases of AF and 122,545 cases of stroke. Interquartile range increments of [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] were associated with increases in the incidence of AF [HRs (95% CIs): 1.03 (1.01, 1.04), 1.02 (1.01, 1.03), 1.01 (1.00, 1.02), and 1.01 (1.01, 1.02), respectively] and the incidence of stroke [HRs (95% CIs): 1.05 (1.03, 1.07), 1.04 (1.01, 1.06), 1.05 (1.03, 1.06), and 1.05 (1.04, 1.06), respectively]. Associations of similar magnitude were found in various sensitivity analyses. Furthermore, we found a near-linear association for stroke with [Formula: see text], whereas [Formula: see text], [Formula: see text]-, and [Formula: see text] relationships exhibited sublinear shapes.Air pollution was associated with stroke and AF onset, even at very low concentrations. https://doi.org/10.1289/EHP4883.

Purpose: Growing evidence implicates ambient air pollutants in the development of major chronic diseases and premature mortality. However, epidemiologic evidence linking air pollution to diabetes remains inconclusive. This study sought to determine the relationships between selected air pollutants (nitrogen dioxide [NO2], fine particulate matter [PM2.5], ozone [O3], and oxidant capacity [Ox; the redox-weighted average of O3 and NO2]) and the incidence of diabetes, as well as the risk of cardiovascular or diabetes mortality among individuals with prevalent diabetes. Research Design and Methods: We followed two cohorts, which included 4.8 million Ontario adults free of diabetes and 452,590 Ontario adults with prevalent diabetes, from 2001 to 2015. Area-level air pollution exposures were assigned to subjects’ residential areas, and outcomes were ascertained using health administrative data with validated algorithms. We estimated hazard ratios for the association between each air pollutant and outcome using Cox proportional hazards models, and modelled the shape of the concentration-response relationships. Results: Over the study period, 790,461 individuals were diagnosed with diabetes. Among those with prevalent diabetes, 26,653 died from diabetes and 64,773 died from cardiovascular diseases. For incident diabetes, each IQR increase in NO2 had a hazard ratio of 1.04 (95% CI: 1.03–1.05). This relationship was relatively robust to all sensitivity analyses considered, and exhibited a near-linear shape. There were also positive associations between incident diabetes and PM2.5, O3, and Ox, but these estimates were somewhat sensitive to different models considered. Among those with prevalent diabetes, almost all pollutants were associated with increased diabetes and cardiovascular mortality risk. The strongest association was observed between diabetes mortality and exposure to NO2 (HR = 1.08, 95% CI: 1.02–1.13). Conclusions: Selected air pollutants, especially NO2, were linked to an increased risk of incident diabetes, as well as risk of cardiovascular or diabetes mortality among persons with prevalent diabetes. As NO2 is frequently used as a proxy for road traffic exposures, this result may indicate that traffic-related air pollution has the strongest effect on diabetes etiology and survival after diabetes development. Keywords: Air pollution, Diabetes, Cardiovascular, Mortality, Incidence, Epidemiology

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P −6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

In this study, we estimated the transportation-related emissions of nitrogen oxides (NO x ) at an individual level for a sample of the Montreal population. Using linear regression, we quantified the associations between NO x emissions and selected individual attributes. We then investigated the relationship between individual emissions of NO x and exposure to nitrogen dioxide (NO 2 ) concentrations derived from a land-use regression model. Factor analysis and clustering of land-uses were used to test the relationships between emissions and exposures in different Montreal areas. We observed that the emissions generated per individual are positively associated with vehicle ownership, gender, and employment status. We also noted that individuals who live in the suburbs or in peripheral areas generate higher emissions of NO x but are exposed to lower NO 2 concentrations at home and throughout their daily activities. Finally, we observed that for most individuals, NO 2 exposures based on daily activity locations were often slightly more elevated than NO 2 concentrations at the home location. We estimated that between 20% and 45% of individuals experience a daily exposure that is largely different from the concentration at their home location. Our findings are relevant to the evaluation of equity in the generation of transport emissions and exposure to traffic-related air pollution. We also shed light on the effect of accounting for daily activities when estimating air pollution exposure.

Introduction Dysfunction of the autonomic nervous system is one of the postulated pathways linking short-term exposure to air pollution to adverse cardiovascular outcomes. A hypothesis is that exposure to air pollution decreases heart rate variability, a recognized independent predictor of poorer cardiovascular prognosis. Methods We conducted a structured review of panel studies published between 1946 and July 2015 of the association between ambient air pollution and parameters of heart rate variability reflecting autonomic nervous function. We focused on exposure to mass concentrations of fine particles (PM 2.5 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) , and four commonly used indices of heart rate variability (HRV): standard deviation of all normal-to-normal intervals (SDNN); root mean square of successive differences in adjacent normal-to-normal intervals (RMSSD); high frequency power (HF); and low frequency power (LF). We searched bibliographic databases and references of identified articles and abstracted characteristics of their design and conduct, and synthesized the quantitative findings in graphic form according to health condition of the study population and the functional form of the HRV indices used in the regression analyses. Results A total of 33 panel studies were included: 31, 12, and 13 studies were used to investigate ambient exposure to PM 2.5 , NO 2 and O 3 , respectively. We found substantial variation across studies in terms of design characteristics and statistical methodologies, and we identified some studies that may have had methodological and statistical issues. Because many panel studies were not comparable to each other, meta-analyses were not generally possible, although we were able to pool the results obtained amongst older adults who had cardiovascular disease for the 24-h average concentrations of PM 2.5 prior to the heart rate variability measurements. In studies of PM 2.5 among older adults with cardiovascular disease, logarithmic transformations of the HRV indices were used in ten studies. Negative associations across all HRV indices were found in 60–86% of these studies for periods of exposures ranging from 5-min to 5-days. The pooled percent changes for an increase of 10 μg/m 3 in the 24-h prior to the measurements of HRV were: −2.11% for SDNN (95% confidence interval (95%CI): −4.00, −0.23%), −3.29% for RMSSD (95%CI: −6.32, −0.25%), −4.76% for LF (95%CI: −12.10, 2.58%), and −1.74% for HF (95%CI: −7.79, 4.31%). No transformations were used in seven studies of PM 2.5 among older adults with cardiovascular disease, and we found for absolute differences pooled changes in the HRV indices, for an increase of 10 μg/m 3 , of −0.31 ms for SDNN (95%CI: −1.02, 0.41 ms) and −1.22 ms for RMSSD (95%CI: −2.37; −0.07 ms). For gaseous pollutants, negative associations over periods of exposure ranging from 5-min or to 5-days prior to the heart rate variability measurements were reported in 71–83% of studies of NO 2 and 57–100% of studies of O 3 , depending of the indices of heart rate variability. However, many of these studies had statistical or methodological issues, and in the few studies without these issues the confidence intervals were relatively wide and mostly included the null. Conclusions and discussion We were not persuaded by the results that there was an association between PM 2.5 and any of the four indices of heart rate variability. For NO 2 and O 3 the number of high-quality studies was insufficient to draw any definite conclusions. Further panel studies with improved design and methodologies are needed to help establish or refute an association between ambient exposure to air pollution and heart rate variability.

This study investigates the variability in near-road concentrations of ultra-fine particles (UFP). Our results are based on a mobile data collection campaign conducted in 2012 in Montreal, Canada using instrumented bicycles and covering approximately 475 km of unique roadways. The spatial extent of the data collected included a diverse array of roads and land use patterns. Average concentrations of UFP per roadway segment varied greatly across the study area (1411–192,340 particles/cm 3 ) as well as across the different visits to the same segment. Mixed effects linear regression models were estimated for UFP (R 2 = 43.80%), incorporating a wide range of predictors including land-use, built environment, road characteristics, and meteorology. Temperature and wind speed had a large negative effect on near-road concentrations of UFP. Both the day of the week and time of day had a significant effect with Tuesdays and afternoon periods positively associated with UFP. Since UFP are largely associated with traffic emissions and considering the wide spatial extent of our data collection campaign, it was impossible to collect traffic volume data. For this purpose, we used simulated data for traffic volumes and speeds across the region and observed a positive effect for volumes and negative effect for speed. Finally, proximity to truck routes was also associated with higher UFP concentrations.

Background: Epidemiological studies have provided strong evidence that fine particulate matter (PM2.5; aerodynamic diameter ≤ 2.5 μm) can exacerbate asthmatic symptoms in children. Pro-oxidant components of PM2.5 are capable of directly generating reactive oxygen species. Oxidative burden is used to describe the capacity of PM2.5 to generate reactive oxygen species in the lung. Objective: In this study we investigated the association between airway inflammation in asthmatic children and oxidative burden of PM2.5 personal exposure. Methods: Daily PM2.5 personal exposure samples (n = 249) of 62 asthmatic school-aged children in Montreal were collected over 10 consecutive days. The oxidative burden of PM2.5 samples was determined in vitro as the depletion of low-molecular-weight antioxidants (ascorbate and glutathione) from a synthetic model of the fluid lining the respiratory tract. Airway inflammation was measured daily as fractional exhaled nitric oxide (FeNO). Results: A positive association was identified between FeNO and glutathione-related oxidative burden exposure in the previous 24 hr (6.0% increase per interquartile range change in glutathione). Glutathione-related oxidative burden was further found to be positively associated with FeNO over 1-day lag and 2-day lag periods. Results further demonstrate that corticosteroid use may reduce the FeNO response to elevated glutathione-related oxidative burden exposure (no use, 15.8%; irregular use, 3.8%), whereas mold (22.1%), dust (10.6%), or fur (13.1%) allergies may increase FeNO in children with versus children without these allergies (11.5%). No association was found between PM2.5 mass or ascorbate-related oxidative burden and FeNO levels. Conclusions: Exposure to PM2.5 with elevated glutathione-related oxidative burden was associated with increased FeNO. Citation: Maikawa CL, Weichenthal S, Wheeler AJ, Dobbin NA, Smargiassi A, Evans G, Liu L, Goldberg MS, Godri Pollitt KJ. 2016. Particulate oxidative burden as a predictor of exhaled nitric oxide in children with asthma. Environ Health Perspect 124:1616–1622; http://dx.doi.org/10.1289/EHP175

Background: Survivors of acute myocardial infarction (AMI) are at increased risk of dying within several hours to days following exposure to elevated levels of ambient air pollution. Little is known, however, about the influence of long-term (months to years) air pollution exposure on survival after AMI. Objective: We conducted a population-based cohort study to determine the impact of long-term exposure to fine particulate matter ≤ 2.5 μm in diameter (PM2.5) on post-AMI survival. Methods: We assembled a cohort of 8,873 AMI patients who were admitted to 1 of 86 hospital corporations across Ontario, Canada in 1999–2001. Mortality follow-up for this cohort extended through 2011. Cumulative time-weighted exposures to PM2.5 were derived from satellite observations based on participants’ annual residences during follow-up. We used standard and multilevel spatial random-effects Cox proportional hazards models and adjusted for potential confounders. Results: Between 1999 and 2011, we identified 4,016 nonaccidental deaths, of which 2,147 were from any cardiovascular disease, 1,650 from ischemic heart disease, and 675 from AMI. For each 10-μg/m3 increase in PM2.5, the adjusted hazard ratio (HR10) of nonaccidental mortality was 1.22 [95% confidence interval (CI): 1.03, 1.45]. The association with PM2.5 was robust to sensitivity analyses and appeared stronger for cardiovascular-related mortality: ischemic heart (HR10 = 1.43; 95% CI: 1.12, 1.83) and AMI (HR10 = 1.64; 95% CI: 1.13, 2.40). We estimated that 12.4% of nonaccidental deaths (or 497 deaths) could have been averted if the lowest measured concentration in an urban area (4 μg/m3) had been achieved at all locations over the course of the study. Conclusions: Long-term air pollution exposure adversely affects the survival of AMI patients. Citation: Chen H, Burnett RT, Copes R, Kwong JC, Villeneuve PJ, Goldberg MS, Brook RD, van Donkelaar A, Jerrett M, Martin RV, Brook JR, Kopp A, Tu JV. 2016. Ambient fine particulate matter and mortality among survivors of myocardial infarction: population-based cohort study. Environ Health Perspect 124:1421–1428; http://dx.doi.org/10.1289/EHP185