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Background: Persisting atopic dermatitis (AD) is known to be associated with more serious allergic diseases at later ages; however, making an accurate diagnosis during infancy is challenging. We assessed the diagnostic performance of questionnaire-based AD measures with criteria-based in-person clinical assessments at age 1 year and evaluated the ability of these diagnostic methods to predict asthma, allergic rhinitis and food allergies at age 5 years.Methods: Data relate to 3014 children participating in the Canadian Healthy Infant Longitudinal Development (CHILD) Study who were directly observed in a clinical assessment by an experienced healthcare professional using the UK Working Party criteria. The majority (2221; 73.7%) of these children also provided multiple other methods of AD ascertainment: a parent reporting a characteristic rash on a questionnaire, a parent reporting the diagnosis provided by an external physician and a combination of these two reports.Results: Relative to the direct clinical assessment, the area under the Receiver Operating Characteristic curve for a parental report of a characteristic rash, reported physician diagnosis and a combination of both were, respectively, 0.60, 0.69 and 0.70. The strongest predictor of asthma at 5 years was AD determined by criteria-based in-person clinical assessment followed by the combination of parental and physician report.Conclusions: These findings suggest that questionnaire data cannot accurately substitute for assessment by experienced healthcare professionals using validated criteria for diagnosis of atopic dermatitis. Combining the parental report with diagnosis by a family physician might sometimes be appropriate (eg to avoid costs of a clinical assessment). [ABSTRACT FROM AUTHOR]

Background The effect of infant feeding practices on the development of food allergy remains controversial. We examined the relationship between timing and patterns of food introduction and sensitization to foods at age 1 year in the Canadian Healthy Infant Longitudinal Development ( CHILD) birth cohort study. Methods Nutrition questionnaire data prospectively collected at age 3, 6, 12, 18, and 24 months were used to determine timing of introduction of cow's milk products, egg, and peanut. At age 1 year, infants underwent skin prick testing to cow's milk, egg white, and peanut. Logistic regression models were fitted to assess the impact of timing of food exposures on sensitization outcomes, and latent class analysis was used to study patterns of food introduction within the cohort. Results Among 2124 children with sufficient data, delaying introduction of cow's milk products, egg, and peanut beyond the first year of life significantly increased the odds of sensitization to that food (cow's milk adj OR 3.69, 95% CI 1.37-9.08; egg adj OR 1.89, 95% CI 1.25-2.80; peanut adj OR 1.76, 95% CI 1.07-3.01). Latent class analysis produced a three-class model: early, usual, and delayed introduction. A pattern of delayed introduction, characterized by avoidance of egg and peanut during the first year of life, increased the odds of sensitization to any of the three tested foods (adj OR 1.78, 95% CI 1.26-2.49). Conclusions Avoidance of potentially allergenic foods during the first year of life significantly increased the odds of sensitization to the corresponding foods. [ABSTRACT FROM AUTHOR]

Objective: Dysbiosis of the infant gut microbiota may have long-term health consequences. This study aimed to determine the impact of maternal intrapartum antibiotic prophylaxis (IAP) on infant gut microbiota, and to explore whether breastfeeding modifies these effects.Design: Prospective pregnancy cohort of Canadian infants born in 2010-2012: the Canadian Healthy Infant Longitudinal Development (CHILD) Study.Setting: General community.Sample: Representative sub-sample of 198 healthy term infants from the CHILD Study.Methods: Maternal IAP exposures and birth method were documented from hospital records and breastfeeding was reported by mothers. Infant gut microbiota was characterised by Illumina 16S rRNA sequencing of faecal samples at 3 and 12 months.Main Outcome Measures: Infant gut microbiota profiles.Results: In this cohort, 21% of mothers received IAP for Group B Streptococcus prophylaxis or pre-labour rupture of membranes; another 23% received IAP for elective or emergency caesarean section (CS). Infant gut microbiota community structures at 3 months differed significantly with all IAP exposures, and differences persisted to 12 months for infants delivered by emergency CS. Taxon-specific composition also differed, with the genera Bacteroides and Parabacteroides under-represented, and Enterococcus and Clostridium over-represented at 3 months following maternal IAP. Microbiota differences were especially evident following IAP with emergency CS, with some changes (increased Clostridiales and decreased Bacteroidaceae) persisting to 12 months, particularly among non-breastfed infants.Conclusions: Intrapartum antibiotics in caesarean and vaginal delivery are associated with infant gut microbiota dysbiosis, and breastfeeding modifies some of these effects. Further research is warranted to explore the health consequences of these associations.Tweetable Abstract: Maternal #antibiotics during childbirth alter the infant gut #microbiome. [ABSTRACT FROM AUTHOR]

Tissues are exposed to diverse inflammatory challenges that shape future inflammatory responses. While cellular metabolism regulates immune function, how metabolism programs and stabilizes immune states within tissues and tunes susceptibility to inflammation is poorly understood. Here, we describe an innate immune metabolic switch that programs long-term intestinal tolerance. Intestinal interleukin-18 (IL-18) stimulation elicited tolerogenic macrophages by preventing their proinflammatory glycolytic polarization via metabolic reprogramming to fatty acid oxidation (FAO). FAO reprogramming was triggered by IL-18 activation of SLC12A3 (NCC), leading to sodium influx, release of mitochondrial DNA, and activation of stimulator of interferon genes (STING). FAO was maintained in macrophages by a bistable switch that encoded memory of IL-18 stimulation and by intercellular positive feedback that sustained the production of macrophage-derived 2'3'-cyclic GMP-AMP (cGAMP) and epithelial-derived IL-18. Thus, a tissue-reinforced metabolic switch encodes durable immune tolerance in the gut and may enable reconstructing compromised immune tolerance in chronic inflammation., Competing Interests: Declaration of interests The authors declare no competing financial interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The embryonic cerebrospinal fluid (eCSF) plays an essential role in the development of the central nervous system (CNS), influencing processes from neurogenesis to lifelong cognitive functions. An important process affecting eCSF composition is inflammation. Inflammation during development can be studied using the maternal immune activation (MIA) mouse model, which displays altered cytokine eCSF composition and mimics neurodevelopmental disorders including autism spectrum disorder (ASD). The limited nature of eCSF as a biosample restricts its research and has hindered our understanding of the eCSF's role in brain pathologies. Specifically, investigation of the small molecule composition of the eCSF is lacking, leaving this aspect of the eCSF composition under-studied. We report here the eCSF metabolome as a resource for investigating developmental neuropathologies from a metabolic perspective. Our reference metabolome includes comprehensive MS 1 and MS 2 datasets and evaluates two mouse strains (CD-1 and C57Bl/6) and two developmental time points (E12.5 and E14.5). We illustrate the reference metabolome's utility by using untargeted metabolomics to identify eCSF-specific compositional changes following MIA. We uncover MIA-relevant metabolic pathways as differentially abundant in eCSF and validate changes in glucocorticoid and kynurenine pathways through targeted metabolomics approaches. Our resource will guide future studies into the causes of MIA neuropathology and the impact of eCSF composition on brain development., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Air pollution has been classified as a human carcinogen based largely on findings for respiratory cancers. Emerging, but limited, evidence suggests that it increases the risk of breast cancer, particularly among younger women. We characterized associations between residential exposure to ambient fine particulate matter (PM 2.5 ) and nitrogen dioxide (NO 2 ) and breast cancer. Analyses were performed using data collected in the Ontario Environmental Health Study (OEHS)., Methods: The OEHS, a population-based case-control study, identified incident cases of breast cancer in Ontario, Canada among women aged 18-45 between 2013 and 2015. A total of 465 pathologically confirmed primary breast cancer cases were identified from the Ontario Cancer Registry, while 242 population-based controls were recruited using random-digit dialing. Self-reported questionnaires were used to collect risk factor data and residential histories. Land-use regression and remote-sensing estimates of NO 2 and PM 2.5, respectively, were assigned to the residential addresses at interview, five years earlier, and at menarche. Logistic regression was used to estimate odds ratios (OR) and their 95 % confidence intervals (CI) in relation to an interquartile range (IQR) increase in air pollution, adjusting for possible confounders., Results: PM 2.5 and NO 2 were positively correlated with each other (r = 0.57). An IQR increase of PM 2.5 (1.9 µg/m 3 ) and NO 2 (6.6 ppb) at interview residence were associated with higher odds of breast cancer and the adjusted ORs and 95 % CIs were 1.37 (95 % CI = 0.98-1.91) and 2.33 (95 % CI = 1.53-3.53), respectively. An increased odds of breast cancer was observed with an IQR increase in NO 2 at residence five years earlier (OR = 2.16, 95 % CI: 1.41-3.31), while no association was observed with PM 2.5 (OR = 0.96, 95 % CI 0.64-1.42)., Conclusions: Our findings support the hypothesis that exposure to ambient air pollution, especially those from traffic sources (i.e., NO 2 ), increases the risk of breast cancer in young women., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Paul J. Villeneuve reports financial support was provided by The Canadian Institutes of Health Research. If there are other authors, they 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 © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Urban environmental factors such as air quality, heat islands, and access to greenspaces and community amenities impact public health. Some vulnerable populations such as low-income groups, children, older adults, new immigrants, and visible minorities live in areas with fewer beneficial conditions, and therefore, face greater health risks. Planning and advocating for equitable healthy urban environments requires systematic analysis of reliable spatial data to identify where vulnerable populations intersect with positive or negative urban/environmental characteristics. To facilitate this effort in Canada, we developed HealthyPlan.City ( https://healthyplan.city/ ), a freely available web mapping platform for users to visualize the spatial patterns of built environment indicators, vulnerable populations, and environmental inequity within over 125 Canadian cities. This tool helps users identify areas within Canadian cities where relatively higher proportions of vulnerable populations experience lower than average levels of beneficial environmental conditions, which we refer to as Equity priority areas. Using nationally standardized environmental data from satellite imagery and other large geospatial databases and demographic data from the Canadian Census, HealthyPlan.City provides a block-by-block snapshot of environmental inequities in Canadian cities. The tool aims to support urban planners, public health professionals, policy makers, and community organizers to identify neighborhoods where targeted investments and improvements to the local environment would simultaneously help communities address environmental inequities, promote public health, and adapt to climate change. In this paper, we report on the key considerations that informed our approach to developing this tool and describe the current web-based application., (© 2024. The Author(s).)

Background: Evidence suggests that prenatal air pollution exposure alters DNA methylation (DNAm), which could go on to affect long-term health. It remains unclear whether DNAm alterations present at birth persist through early life. Identifying persistent DNAm changes would provide greater insight into the molecular mechanisms contributing to the association of prenatal air pollution exposure with atopic diseases., Objectives: This study investigated DNAm differences associated with prenatal nitrogen dioxide ( NO 2 ) exposure (a surrogate measure of traffic-related air pollution) at birth and 1 y of age and examined their role in atopic disease. We focused on regions showing persistent DNAm differences from birth to 1 y of age and regions uniquely associated with postnatal NO 2 exposure., Methods: Microarrays measured DNAm at birth and at 1 y of age for an atopy-enriched subset of Canadian Health Infant Longitudinal Development (CHILD) study participants. Individual and regional DNAm differences associated with prenatal NO 2 ( n = 128 ) were identified, and their persistence at age 1 y were investigated using linear mixed effects models ( n = 124 ). Postnatal-specific DNAm differences ( n = 125 ) were isolated, and their association with NO 2 in the first year of life was examined. Causal mediation investigated whether DNAm differences mediated associations between NO 2 and age 1 y atopy or wheeze. Analyses were repeated using biological sex-stratified data., Results: At birth ( n = 128 ), 18 regions of DNAm were associated with NO 2 , with several annotated to HOX genes. Some of these regions were specifically identified in males ( n = 73 ), but not females ( n = 55 ). The effect of prenatal NO 2 across CpGs within altered regions persisted at 1 y of age. No significant mediation effects were identified. Sex-stratified analyses identified postnatal-specific DNAm alterations., Discussion: Regional cord blood DNAm differences associated with prenatal NO 2 persisted through at least the first year of life in CHILD participants. Some differences may represent sex-specific alterations, but replication in larger cohorts is needed. The early postnatal period remained a sensitive window to DNAm perturbations. https://doi.org/10.1289/EHP13034.

Folate, an essential vitamin, is a one-carbon acceptor and donor in key metabolic reactions. Erythroid cells harbor a unique sensitivity to folate deprivation, as revealed by the primary pathological manifestation of nutritional folate deprivation: megaloblastic anemia. To study this metabolic sensitivity, we applied mild folate depletion to human and mouse erythroid cell lines and primary murine erythroid progenitors. We show that folate depletion induces early blockade of purine synthesis and accumulation of the purine synthesis intermediate and signaling molecule, 5'-phosphoribosyl-5-aminoimidazole-4-carboxamide (AICAR), followed by enhanced heme metabolism, hemoglobin synthesis, and erythroid differentiation. This is phenocopied by inhibition of folate metabolism using the inhibitor SHIN1, and by AICAR supplementation. Mechanistically, the metabolically driven differentiation is independent of mechanistic target of rapamycin complex 1 (mTORC1) and adenosine 5'-monophosphate-activated protein kinase (AMPK) and is instead mediated by protein kinase C. Our findings suggest that folate deprivation-induced premature differentiation of erythroid progenitor cells is a molecular etiology to folate deficiency-induced anemia.

Childhood obesity is linked to maternal smoking during pregnancy. Gut microbiota may partially mediate this association and could be potential targets for intervention; however, its role is understudied. We included 1,592 infants from the Canadian Healthy Infants Longitudinal Development Cohort. Data on environmental exposure and lifestyle factors were collected prenatally and throughout the first three years. Weight outcomes were measured at one and three years of age. Stool samples collected at 3 and 12 months were analyzed by sequencing the V4 region of 16S rRNA to profile microbial compositions and magnetic resonance spectroscopy to quantify the metabolites. We showed that quitting smoking during pregnancy did not lower the risk of offspring being overweight. However, exclusive breastfeeding until the third month of age may alleviate these risks. We also reported that maternal smoking during pregnancy significantly increased Firmicutes abundance and diversity. We further revealed that Firmicutes diversity mediates the elevated risk of childhood overweight and obesity linked to maternal prenatal smoking. This effect possibly occurs through excessive microbial butyrate production. These findings add to the evidence that women should quit smoking before their pregnancies to prevent microbiome-mediated childhood overweight and obesity risk, and indicate the potential obesogenic role of excessive butyrate production in early life.

Organophosphate ester flame retardants and plasticizers (OPEs) are common exposures in modern built environments. Toxicological models report that some OPEs reduce dopamine and serotonin in the brain. Deficiencies in these neurotransmitters are associated with anxiety and depression. We hypothesized that exposure to higher concentrations of OPEs in house dust would be associated with a greater risk of depression and stress in mothers across the prenatal and postpartum periods. We conducted a nested prospective cohort study using data collected on mothers (n = 718) in the CHILD Cohort Study, a longitudinal multi-city Canadian birth cohort (2008-2012). OPEs were measured in house dust sampled at 3-4 months postpartum. Maternal depression and stress were measured at 18 and 36 weeks gestation and 6 months and 1 year postpartum using the Centre for Epidemiologic Studies for Depression Scale (CES-D) and Perceived Stress Scale (PSS). We used linear mixed models to examine the association between a summed Z-Score OPE index and continuous depression and stress scores. In adjusted models, one standard deviation increase in the OPE Z-score index was associated with a 0.07-point (95% CI: 0.01, 0.13) increase in PSS score. OPEs were not associated with log-transformed CES-D (β: 0.63%, 95% CI: -0.18%, 1.46%). The effect of OPEs on PSS score was strongest at 36 weeks gestation and weakest at 1 year postpartum. We observed small increases in maternal perceived stress levels, but not depression, with increasing OPEs measured in house dust during the prenatal and early postpartum period in this cohort of Canadian women. Given the prevalence of prenatal and postpartum anxiety and the ubiquity of OPE exposures, additional research is warranted to understand if these chemicals affect maternal mental health., 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 © 2023 Elsevier Inc. All rights reserved.)

Remote sensing data from the Ozone Monitoring Instrument (OMI) and the TROPOspheric Monitoring Instrument (TROPOMI) play important roles in estimating surface nitrogen dioxide (NO 2 ), but few studies have compared their differences for application in surface NO 2 reconstruction. This study aims to explore the effectiveness of incorporating the tropospheric NO 2 vertical column density (VCD) from OMI and TROPOMI (hereafter referred to as OMI and TROPOMI, respectively, for conciseness) for deriving surface NO 2 and to apply the resulting data to revisit the spatiotemporal variations in surface NO 2 for Beijing over the 2005-2020 period during which there were significant reductions in nitrogen oxide emissions. In the OMI versus TROPOMI performance comparison, the cross-validation R 2 values were 0.73 and 0.72, respectively, at 1 km resolution and 0.69 for both at 100 m resolution. The comparisons between satellite data sources indicate that even though TROPOMI has a finer resolution it does not improve upon OMI for deriving surface NO 2 at 1 km resolution, especially for analyzing long-term trends. In light of the comparison results, we used a hybrid approach based on machine learning to derive the spatiotemporal distribution of surface NO 2 during 2005-2020 based on OMI. We had novel, independent passive sampling data collected weekly from July to September of 2008 for hindcasting validation and found a spatiotemporal R 2 of 0.46 (RMSE = 7.0 ppb). Regarding the long-term trend of surface NO 2 , the level in 2008 was obviously lower than that in 2007 and 2009, as expected, which was attributed to pollution restrictions during the Olympic Games. The NO 2 level started to steadily decline from 2015 and fell below 2008's level after 2017. Based on OMI, a long-term and fine-resolution surface NO 2 dataset was developed for Beijing to support future environmental management questions and epidemiological research., 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 © 2023 Elsevier B.V. All rights reserved.)

Background: There is a long tradition in environmental health of using frameworks for evidence synthesis, such as those of the U.S. Environmental Protection Agency for its Integrated Science Assessments and the International Agency for Research on Cancer Monographs. The framework, Grading of Recommendations Assessment, Development, and Evaluation (GRADE), was developed for evidence synthesis in clinical medicine. The U.S. Office of Health Assessment and Translation (OHAT) elaborated an approach for evidence synthesis in environmental health building on GRADE., Methods: We applied a modified OHAT approach and a broader "narrative" assessment to assess the level of confidence in a large systematic review on traffic-related air pollution and health outcomes., Discussion: We discuss several challenges with the OHAT approach and its implementation and suggest improvements for synthesizing evidence from observational studies in environmental health. We consider the determination of confidence using a formal rating scheme of up- and downgrading of certain factors, the treatment of every factor as equally important, and the lower initial confidence rating of observational studies to be fundamental issues in the OHAT approach. We argue that some observational studies can offer high-confidence evidence in environmental health. We note that heterogeneity in magnitude of effect estimates should generally not weaken the confidence in the evidence, and consistency of associations across study designs, populations, and exposure assessment methods may strengthen confidence in the evidence. We mention that publication bias should be explored beyond statistical methods and is likely limited when large and collaborative studies comprise most of the evidence and when accrued over several decades. We propose to identify possible key biases, their most likely direction, and their potential impacts on the results. We think that the OHAT approach and other GRADE-type frameworks require substantial modification to align better with features of environmental health questions and the studies that address them. We emphasize that a broader, "narrative" evidence assessment based on the systematic review may complement a formal GRADE-type evaluation. https://doi.org/10.1289/EHP11532.

Background: The health effects of traffic-related air pollution (TRAP) continue to be of important public health interest across the globe. Following its 2010 review, the Health Effects Institute appointed a new expert Panel to systematically evaluate the epidemiological evidence regarding the associations between long-term exposure to TRAP and selected health outcomes. This paper describes the main findings of the systematic review on non-accidental mortality., Methods: The Panel used a systematic approach to conduct the review. An extensive search was conducted of literature published between 1980 and 2019. A new exposure framework was developed to determine whether a study was sufficiently specific to TRAP, which included studies beyond the near-roadway environment. We performed random-effects meta-analysis when at least three estimates were available of an association between a specific exposure and outcome. We evaluated confidence in the evidence using a modified Office of Health Assessment and Translation (OHAT) approach, supplemented with a broader narrative synthesis., Results: Thirty-six cohort studies were included. Virtually all studies adjusted for a large number of individual and area-level covariates-including smoking, body mass index, and individual and area-level socioeconomic status-and were judged at a low or moderate risk for bias. Most studies were conducted in North America and Europe, and a few were based in Asia and Australia. The meta-analytic summary estimates for nitrogen dioxide, elemental carbon and fine particulate matter-pollutants with more than 10 studies-were 1.04 (95% CI 1.01, 1.06), 1.02 (1.00, 1.04) and 1.03 (1.01, 1.05) per 10, 1 and 5 µg/m 3 , respectively. Effect estimates are interpreted as the relative risk of mortality when the exposure differs with the selected increment. The confidence in the evidence for these pollutants was judged as high, because of upgrades for monotonic exposure-response and consistency across populations. The consistent findings across geographical regions, exposure assessment methods and confounder adjustment resulted in a high confidence rating using a narrative approach as well., Conclusions: The overall confidence in the evidence for a positive association between long-term exposure to TRAP and non-accidental mortality was high., 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 © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The dry deposition process refers to the flux loss of an atmospheric pollutant due to uptake of the pollutant by the earth's surfaces. Dry deposition flux of a chemical species is typically calculated as the product of its surface-layer concentration and its dry deposition velocity (V d ). Field measurement based V d data are very scarce or do not exist for many chemical species considered in chemistry transport models. In the present study, gaseous and particulate dry deposition schemes were applied to generate a database of hourly V d for 45 gaseous species and three particle size ranges for two years (2016-2017) at a 15 km by 15 km horizontal resolution across North America. Hourly V d of the 45 gaseous species ranged from < 0.001 to 4.6 cm/sec across the whole domain, with chemical species-dependent median (mean) values being in the range of 0.018-1.37 cm/sec (0.05-1.43 cm/sec). The spatial distributions of the two-year average V d showed values higher than 1-3 cm/sec for those soluble and reactive species over certain land types. Soluble species have the highest V d over water surfaces, while insoluble but reactive species have the highest V d over forests. Hourly V d of PM 2.5 across the whole domain ranged from 0.039 to 0.75 cm/sec with median (mean) value of 0.18 (0.20) cm s -1 , while the mean V d for PM 2.5-10 is twice that of PM 2.5 . Uncertainties in the modeled V d are typically on the order of a factor of 2.0 or larger, which needs to be considered when applying the dataset in other studies., (Copyright © 2022. Published by Elsevier B.V.)

The environment plays an instrumental role in the developmental origins of health and disease. Protective features of the environment in the development of asthma and atopy have been insufficiently studied. We used data from the CHILD (Canadian Healthy Infant Longitudinal Development) Cohort Study to examine relationships between living near natural green spaces in early infancy in Edmonton, AB, Canada and the development of atopic sensitization at 1 year and 3 years of age in a cohort of 699 infants, and whether these associations were mediated by infant gut microbiota (measured using 16s V4 amplicon sequencing) at 4 months. The Urban Planning Land Vegetation Index (uPLVI) map of the City of Edmonton was used to assess infants' exposure to natural spaces based on their home postal codes, and atopic sensitization was assessed using skin prink testing (SPTs) for common food and inhalant allergens. Our findings suggest there is a protective effect of natural green space proximity on the development of multiple inhalant atopic sensitizations at 3 years (odds ratio = 0.28 [95% CI 0.09, 0.90]). This relationship was mediated by changes to Actinobacteria diversity in infant fecal samples taken at 4 months. We also found a positive association between nature proximity and sensitization to at least one food or inhaled allergen; this association was not mediated by gut microbiota. Together, these findings underscore the importance of promoting natural urban greenspace preservation to improve child health by reducing atopic disease susceptibility. IMPORTANCE Our findings highlight the importance of preserving natural green space in urban settings to prevent sensitization to environmental allergens and promote early-life gut microbiota pathways to this health benefit. These findings support a mediating role of gut microbiome compositions in health and disease susceptibility. This study used unique, accurate, and comprehensive methodology to classify natural space exposure via a high-resolution topographical map of foliage subtypes within the City of Edmonton limits. These methods are improvements from other methods previously used to classify natural space exposure, such as the normalized density vegetation index from satellite imagery, which is not able to distinguish anthropogenic from green space. The use of these methods and the associations found between natural green space exposure and atopic sensitization outcomes support their use in future studies. Our findings also provide many avenues for future research including longer term follow up of this cohort and investigation of a causal role of reduced Actinobacteria diversity on atopic sensitization development.

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways., (© 2023. The Author(s).)

Motivation: Increasingly complex omics datasets are being generated, along with associated diverse categories of metadata (environmental, clinical, etc.). Looking at the correlation between these variables can be critical to identify potential confounding factors and novel relationships. To date, some correlation globe software has been developed to aid investigations; however, they lack secure, dynamic visualization capability., Results: GlobeCorr.ca is a web-based application designed to provide user-friendly, interactive visualization and analysis of correlation datasets. Users load tabular data listing pairwise variables and their correlation values, and GlobeCorr creates a dynamic visualization using ribbons to represent positive and negative correlations, optionally grouped by domain/category (such as microbiome taxa against other metadata). GlobeCorr runs securely (locally on a user's computer) and provides a simple method for users to visualize and summarize complex datasets. This tool is applicable to a wide range of disciplines and domains of interest, including the bioinformatics/microbiome and metadata examples provided within., Availability and Implementation: See https://GlobeCorr.ca; Code provided under an open source MIT license: https://github.com/brinkmanlab/globecorr., (© The Author(s) 2023. Published by Oxford University Press.)

New 'big data' streams such as street-level imagery are offering unprecedented possibilities for developing health-relevant data on the urban environment. Urban environmental features derived from street-level imagery have been used to assess pedestrian-friendly neighbourhood design and to predict active commuting, but few such studies have been conducted in Canada. Using 1.15 million Google Street View (GSV) images in seven Canadian cities, we applied image segmentation and object detection computer vision methods to extract data on persons, bicycles, buildings, sidewalks, open sky (without trees or buildings), and vegetation at postal codes. The associations between urban features and walk-to-work rates obtained from the Canadian Census were assessed. We also assessed how GSV-derived urban features perform in predicting walk-to-work rates relative to more widely used walkability measures. Results showed that features derived from street-level images are better able to predict the percent of people walking to work as their primary mode of transportation compared to data derived from traditional walkability metrics. Given the increasing coverage of street-level imagery around the world, there is considerable potential for machine learning and computer vision to help researchers study patterns of active transportation and other health-related behaviours and exposures., (© 2022. The Author(s).)

The World Health Organization (WHO) recently released new guidelines for outdoor fine particulate air pollution (PM 2.5 ) recommending an annual average concentration of 5 μg/m 3 . Yet, our understanding of the concentration-response relationship between outdoor PM 2.5 and mortality in this range of near-background concentrations remains incomplete. To address this uncertainty, we conducted a population-based cohort study of 7.1 million adults in one of the world's lowest exposure environments. Our findings reveal a supralinear concentration-response relationship between outdoor PM 2.5 and mortality at very low (<5 μg/m 3 ) concentrations. Our updated global concentration-response function incorporating this new information suggests an additional 1.5 million deaths globally attributable to outdoor PM 2.5 annually compared to previous estimates. The global health benefits of meeting the new WHO guideline for outdoor PM 2.5 are greater than previously assumed and indicate a need for continued reductions in outdoor air pollution around the world.

We estimated mortality and economic loss attributable to PM 2·5 air pollution exposure in 429 counties of Iran in 2018. Ambient PM 2.5 -related deaths were estimated using the Global Exposure Mortality Model (GEMM). According to the ground-monitored and satellite-based PM 2.5 data, the annual mean population-weighted PM 2·5 concentrations for Iran were 30.1 and 38.6 μg m -3 , respectively. We estimated that long-term exposure to ambient PM 2.5 contributed to 49,303 (95% confidence interval (CI) 40,914-57,379) deaths in adults ≥ 25 yr. from all-natural causes based on ground monitored data and 58,873 (95% CI 49,024-68,287) deaths using satellite-based models for PM 2.5 . The crude death rate and the age-standardized death rate per 100,000 population for age group ≥ 25 year due to ground-monitored PM 2.5 data versus satellite-based exposure estimates was 97 (95% CI 81-113) versus 116 (95% CI 97-135) and 125 (95% CI 104-145) versus 149 (95% CI 124-173), respectively. For ground-monitored and satellite-based PM 2.5 data, the economic loss attributable to ambient PM 2.5 -total mortality was approximately 10,713 (95% CI 8890-12,467) and 12,792.1 (95% CI 10,652.0-14,837.6) million USD, equivalent to nearly 3.7% (95% CI 3.06-4.29) and 4.3% (95% CI 3.6-4.5.0) of the total gross domestic product in Iran in 2018., (© 2022. The Author(s).)

Rationale: Outdoor air pollution is a potential risk factor for lower lung function and chronic obstructive pulmonary disease (COPD). Little is known about how airway abnormalities and lung growth might modify this relationship. Objectives: To evaluate the associations of ambient air pollution exposure with lung function and COPD and examine possible interactions with dysanapsis. Methods: We made use of cross-sectional postbronchodilator spirometry data from 1,452 individuals enrolled in the CanCOLD (Canadian Cohort Obstructive Lung Disease) study with linked ambient fine particulate matter (PM 2.5 ) and nitrogen dioxide (NO 2 ) air pollution estimates. Dysanapsis, or the ratio of the airway-to-lung volume calculated from thoracic computed tomography images, was used to examine possible interactions. Measurements and Main Results: In adjusted models, 101.7 ml (95% confidence interval [CI], -166.2 to -37.2) and 115.0 ml (95% CI, -196.5 to -33.4) lower FEV 1 were demonstrated per increase of 2.4 ug/m 3 PM 2.5 and 9.2 ppb NO 2 , respectively. Interaction between air pollution and dysanapsis was not statistically significant when modeling the airway-to-lung ratio as a continuous variable. However, a 109.8 ml (95% CI, -209.0 to -10.5] lower FEV 1 and an 87% (95% CI, 12% to 213%) higher odds of COPD were observed among individuals in the lowest, relative to highest, airway-to-lung ratio, per 2.4 μg/m 3 increment of PM 2.5 . Conclusions: Ambient air pollution exposure was associated with lower lung function, even at relatively low concentrations. Individuals with dysanaptic lung growth might be particularly susceptible to inhaled ambient air pollutants, especially those at the extremes of dysanapsis.

Introduction: Mortality is associated with long-term exposure to fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter; PM 2.5 ), 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 PM 2.5 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 PM 2.5 concentrations and nonaccidental mortality were attenuated with the addition of ozone (O 3 ) or a measure of gaseous pollutant oxidant capacity (O x ), which was estimated from O 3 and nitrogen dioxide (NO 2 ) concentrations. This was motivated by our interests in understanding both the effects air pollutant mixtures may have on mortality and also the role of O 3 as a copollutant that shares common sources and precursor emissions with those of PM 2.5 . In this Phase 2 report, we further explore the sensitivity of these associations with O 3 and O x , evaluate sensitivity to other factors, such as regional variation, and present ambient PM 2.5 concentration-response relationships for specific causes of death., Methods: PM 2.5 concentrations were estimated at 1 km 2 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 PM 2.5 mass concentration relationship, land use information, and ground monitoring. These estimates were informed and further refined with collocated measurements of PM 2.5 and AOD, including targeted measurements in areas of low PM 2.5 concentrations collected at five locations across Canada. Ground measurements of PM 2.5 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 PM 2.5 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 PM 2.5 . 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/m 3 . 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 PM 2.5 and mortality when in the presence of, or stratified by tertile of, O 3 or O x . Additionally, associations between PM 2.5 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-PM 2.5 association to removal of person-years at or above 12 μg/m 3 (the current U.S. National Ambient Air Quality Standard) and 10 μg/m 3 (the current Canadian and former [2005] World Health Organization [WHO] guideline, and current WHO Interim Target-4). Finally, differences in the shapes of PM 2.5 -mortality associations were assessed across broad geographic regions (airsheds) within Canada., Results: The refined PM 2.5 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 PM 2.5 <10 μg/m 3 )., Positive associations between outdoor PM 2.5 concentrations and nonaccidental mortality were consistently observed in all cohorts. In the Stacked CanCHEC analyses (1.3 million deaths), each 10-μg/m 3 increase in outdoor PM 2.5 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 PM 2.5 mass concentration of 4.16 μg/m 3 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/m 3 to 4.5 μg/m 3 , flattened from 4.5 μg/m 3 to 8.0 μg/m 3 , then increased for concentrations above 8.0 μg/m 3 . The threshold model results reflected this pattern with -2 log-likelihood values being equal at 2.5 μg/m 3 and 8.0 μg/m 3 . However, mean threshold model predictions monotonically increased over the concentration range with the lower 95% CI equal to one from 2.5 μg/m 3 to 8.0 μg/m 3 . 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-PM 2.5 association to removal of person-years at or above the current U.S. and Canadian standards of 12 μg/m 3 and 10 μg/m 3 , respectively. In the full cohort and in both restricted cohorts, a steep increase was observed from the minimum concentration of 2.5 μg/m 3 to 5 μg/m 3 . For the full cohort and the <12 μg/m 3 cohort the relationship flattened over the 5 to 9 μg/m 3 range and then increased above 9 μg/m 3 . A similar increase was observed for the <10 μg/m 3 cohort followed by a clear decline in the magnitude of predictions over the 5 to 9 μg/m 3 range and an increase above 9 μg/m 3 . Together these results suggest that a positive association exists for concentrations >9 μg/m 3 with indications of adverse effects on mortality at concentrations as low as 2.5 μg/m 3 ., Among the other causes of death examined, PM 2.5 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 PM 2.5 for heart failure, lung cancer, and kidney failure., In sensitivity analyses, the addition of O 3 and O x attenuated associations between PM 2.5 and mortality. When analyses were stratified by tertiles of copollutants, associations between PM 2.5 and mortality were only observed in the highest tertile of O 3 or O x . 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 PM 2.5 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/m 3 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 PM 2.5 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 PM 2.5 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/m 3 , and there was no clear evidence in the observed data of a lower threshold, below which PM 2.5 was not associated with nonaccidental mortality., (© 2022 Health Effects Institute. All rights reserved.)

Eicosanoids are potent regulators of homeostasis and inflammation. Co-exposure to allergen and diesel exhaust (DE) have been shown to lead to eosinophilic inflammation, impaired airflow, and increased airway responsiveness. It is not clear whether eicosanoids mediate the mechanism by which these exposures impair lung function. We conducted a randomized, double-blinded, and four-arm crossover study. Fourteen allergen-sensitized participants were exposed to four conditions: negative control; allergen-alone exposure; DE and allergen coexposure; coexposure with particle-reducing technology applied. Quantitative metabolic profiling of urinary eicosanoids was performed using LC-MS/MS. As expected, allergen inhalation increased eicosanoids. The prostacyclin metabolite 2,3-dinor-6-keto-PGF 1α (PGF 1α , prostaglandin F 1α ) increased with coexposure, but particle depletion suppressed this pathway. Individuals with a high genetic risk score demonstrated a greater increase in isoprostane metabolites following coexposure. Causal mediation analyses showed that allergen induced airflow impairment was mediated via leukotriene E 4 and tetranor-prostaglandin D metabolite. Overall, DE exposure did not augment the allergen's effect on urinary eicosanoids, except insofar as variant genotypes conferred susceptibility to the addition of DE in terms of isoprostane metabolites. These findings will add to the body of previous controlled human exposure studies and provide greater insight into how complex environmental exposures in urban air may influence individuals with sensitivity to aeroallergens.

The health effects of traffic-related air pollution (TRAP) continue to be of important public health interest. Following its well-cited 2010 critical review, the Health Effects Institute (HEI) appointed a new expert Panel to systematically evaluate the epidemiological evidence regarding the associations between long-term exposure to TRAP and selected adverse health outcomes. Health outcomes were selected based on evidence of causality for general air pollution (broader than TRAP) cited in authoritative reviews, relevance for public health and policy, and resources available. The Panel used a systematic approach to search the literature, select studies for inclusion in the review, assess study quality, summarize results, and reach conclusions about the confidence in the evidence. An extensive search was conducted of literature published between January 1980 and July 2019 on selected health outcomes. A new exposure framework was developed to determine whether a study was sufficiently specific to TRAP. In total, 353 studies were included in the review. Respiratory effects in children (118 studies) and birth outcomes (86 studies) were the most commonly studied outcomes. Fewer studies investigated cardiometabolic effects (57 studies), respiratory effects in adults (50 studies), and mortality (48 studies). The findings from the systematic review, meta-analyses, and evaluation of the quality of the studies and potential biases provided an overall high or moderate-to-high level of confidence in an association between long-term exposure to TRAP and the adverse health outcomes all-cause, circulatory, ischemic heart disease and lung cancer mortality, asthma onsetin chilldren and adults, and acute lower respiratory infections in children. The evidence was considered moderate, low or very low for the other selected outcomes. In light of the large number of people exposed to TRAP - both in and beyond the near-road environment - the Panel concluded that the overall high or moderate-to-high confidence in the evidence for an association between long-term exposure to TRAP and several adverse health outcomes indicates that exposures to TRAP remain an important public health concern and deserve greater attention from the public and from policymakers., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

There have been several methods employed to quantify individual-level exposure to ambient traffic-related air pollutants (TRAP). These include an individual's residential proximity to roads, measurement of individual pollutants as surrogates or markers, as well as dispersion and land use regression (LUR) models. Hopanes are organic compounds still commonly found on ambient particulate matter and are specific markers of combustion engine primary emissions, but they have not been previously used in personal exposure studies. In this paper, children's personal exposures to TRAP were evaluated using hopanes determined from weekly integrated filters collected as part of a personal exposure study in Windsor, Canada. These hopane measurements were used to evaluate how well other commonly used proxies of exposure to TRAP performed. Several of the LUR exposure estimates for a range of air pollutants were associated with the children's summer personal hopane exposures (r = 0.41-0.74). However, all personal hopane exposures in summer were more strongly associated with the length of major roadways within 500 m of their homes. In contrast, metrics of major roadways and LUR estimates were poorly correlated with any winter personal hopanes. Our findings suggest that available TRAP exposure indicators have the potential for exposure misclassification in winter vs. summer and more so for LUR than for metrics of major road density. As such, limitations are evident when using traditional proxy methods for assigning traffic exposures and these may be especially important when attempting to assign exposures for children's key growth and developmental windows. If long-term chronic exposures are being estimated, our data suggest that measures of major road lengths in proximity to homes are a more-specific approach for assigning personal TRAP exposures.

22 alkylated polycyclic aromatic hydrocarbons (alk-PAHs) were characterized in ambient air individually for the first time in urban and semi-urban locations in Toronto, Canada. Five unsubstituted PAHs were included for comparison. Results from the measurements were used to estimate benzo[ a ]pyrene equivalent toxicity (BaPeq) of individual compounds in order to investigate the significance of a single compound in contributing to the overall toxic equivalency (TEQ) of air mixtures. To determine which compounds merit further investigation, BaPeq values of individual compounds were compared to the measured BaP toxicity. Our results showed that both unsubstituted and alkylated PAHs were more abundant in the urban area (38 and 30%, respectively). Benzo[ a ]pyrene levels at the urban location exceeded Ontario's 24 h guideline (40% of the events), and on average, it was 5 times higher than that at the semi-urban area. Gas-phase two- and three-ring compounds contributed up to 39% (urban) and 76% (semi-urban) of the TEQ of all compounds analyzed. Some alk-PAHs such as 7,12-dimethylbenzo[ a ]anthracene had a huge impact on the toxicity of urban air, and its BaPeq was on average 8 times higher than that of BaP. We emphasize that the toxic impact of alkylated and gaseous PAHs, which is not routinely included in many air monitoring programs, is significant and should not be neglected.

Background: As smoking prevalence has decreased in Canada, particularly during pregnancy and around children, and technological improvements have lowered detection limits, the use of traditional tobacco smoke biomarkers in infant populations requires re-evaluation., Objective: We evaluated concentrations of urinary nicotine biomarkers, cotinine and trans-3'-hydroxycotinine (3HC), and questionnaire responses. We used machine learning and prediction modeling to understand sources of tobacco smoke exposure for infants from the CHILD Cohort Study., Methods: Multivariable linear regression models, chosen through a combination of conceptual and data-driven strategies including random forest regression, assessed the ability of questionnaires to predict variation in urinary cotinine and 3HC concentrations of 2017 3-month-old infants., Results: Although only 2% of mothers reported smoking prior to and throughout their pregnancy, cotinine and 3HC were detected in 76 and 89% of the infants' urine (n = 2017). Questionnaire-based models explained 31 and 41% of the variance in cotinine and 3HC levels, respectively. Observed concentrations suggest 0.25 and 0.50 ng/mL as cut-points in cotinine and 3HC to characterize SHS exposure. This cut-point suggests that 23.5% of infants had moderate or regular smoke exposure., Significance: Though most people make efforts to reduce exposure to their infants, parents do not appear to consider the pervasiveness and persistence of secondhand and thirdhand smoke. More than half of the variation in urinary cotinine and 3HC in infants could not be predicted with modeling. The pervasiveness of thirdhand smoke, the potential for dermal and oral routes of nicotine exposure, along with changes in public perceptions of smoking exposure and risk warrant further exploration., (© 2021. The Author(s).)

Nitrogen dioxide (NO 2 ) is an important contributor to air pollution and can adversely affect human health 1-9 . A decrease in NO 2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-19 10-20 . Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO 2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO 2 concentrations from NO 2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO 2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO 2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO 2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO 2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates., (© 2022. The Author(s).)

Annual global satellite-based estimates of fine particulate matter (PM 2.5 ) 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 PM 2.5 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 PM 2.5 concentrations exceed 90 μg/m 3 , with local concentrations of approximately 200 μg/m 3 for parts of the Indo-Gangetic Plain. In East Asia, monthly mean PM 2.5 concentrations have decreased over the period 2010-2019 by 1.6-2.6 μg/m 3 /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 PM 2.5 exposure, with large measurement gaps in the Global South. Uncertainty estimates exhibit regional consistency with observed differences between ground-based and satellite-derived PM 2.5 . The evaluation of uncertainty for agglomerated values indicates that hybrid PM 2.5 estimates provide precise regional-scale representation, with residual uncertainty inversely proportional to the sample size.

Tailings ponds in the oil sands (OS) region in Alberta, Canada, have been associated with fugitive emissions of volatile organic compounds (VOCs) and other pollutants to the atmosphere. However, the contribution of tailings ponds to the total fugitive emissions of VOCs from OS operations remains uncertain. To address this knowledge gap, a field study was conducted in the summer of 2017 at Suncor's Pond 2/3 to estimate emissions of a suite of pollutants including 68 VOCs using a combination of micrometeorological methods and measurements from a flux tower. The results indicate that in 2017, Pond 2/3 was an emission source of 3322 ± 727 tons of VOCs including alkanes, aromatics, and oxygenated and sulfur-containing organics. While the total VOC emissions were approximately a factor of 2 higher than those reported by Suncor, the individual VOC species emissions varied by up to a factor of 12. A chemical mass balance (CMB) receptor model was used to estimate the contribution of the tailings pond to VOC pollution events in a nearby First Nations and Metis community in Fort McKay. CMB results indicate that Suncor Pond 2/3 contributed up to 57% to the total mass of VOCs measured at Fort McKay, reinforcing the importance of accurate VOC emission estimation methods for tailings ponds.

Background: We do not currently understand how spatiotemporal variations in the composition of fine particulate air pollution [fine particulate matter with aerodynamic diameter ≤ 2.5 μ m ( PM 2.5 )] affects population health risks. However, recent evidence suggests that joint concentrations of transition metals and sulfate may influence the oxidative potential (OP) of PM 2.5 and associated health impacts., Objectives: The purpose of the study was to evaluate how combinations of transition metals/OP and sulfur content in outdoor PM 2.5 influence associations with acute cardiovascular events., Methods: We conducted a national case-crossover study of outdoor PM 2.5 and acute cardiovascular events in Canada between 2016 and 2017 (93,344 adult cases). Monthly mean transition metal and sulfur (S) concentrations in PM 2.5 were determined prospectively along with estimates of OP using acellular assays for glutathione ( OP GSH ), ascorbate ( OP AA ), and dithiothreitol depletion ( OP DTT ). Conditional logistic regression models were used to estimate odds ratios (OR) [95% confidence intervals (CI)] for PM 2.5 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 10 μ g / m 3 ) 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. PM 2.5 was not associated with acute cardiovascular events in women., Discussion: The combined transition metal and sulfur content of outdoor PM 2.5 influences the strength of association with acute cardiovascular events in men. Regions with elevated concentrations of both sulfur and transition metals in PM 2.5 should be examined as priority areas for regulatory interventions. https://doi.org/10.1289/EHP9449.

Owing to their greater outdoor activity and ongoing lung development, children are particularly vulnerable to the harmful effects of exposure to fine particulate matter (PM 2.5 ) . However, the effects of PM 2.5 components are poorly understood. This study aimed to use a longitudinal birth cohort of children with physician-diagnosed incident asthma to investigate the effect of PM 2.5 components at birth on morbidity measured by health services utilization. Of 1277 Toronto Child Health Evaluation Questionnaire (T-CHEQ) participants, the study population included 362 children diagnosed with asthma who were followed for a mean of 13 years from birth until March 31, 2016, or loss-to-follow-up. Concentrations of PM 2.5 and its components were assigned based on participants' postal codes at birth. Study outcomes included counts of asthma, asthma-related, and all-cause health services use. Poisson regression in single-, two-, and multi-pollutant models was used to estimate rate ratios (RR) per interquartile range (IQR) increase of exposures. Covariates were included in all models to further adjust for potential confounding. The adjusted RR for sulfate (SO 4 ) and all-cause hospitalizations was statistically significant with RR = 2.23 (95% confidence interval [CI]: 1.25-3.96) in a multi-pollutant model with nitrogen dioxide (NO 2 ) and ozone (O 3 ). In multi-pollutant models with oxidants, the adjusted RRs for SO 4 of all-cause hospitalizations and emergency department (ED) visits were also statistically significant with RR = 2.31 (95% CI: 1.32-4.03) and RR = 1.39 (95% CI: 1.02-1.90), respectively. While unadjusted single-pollutant RRs for asthma-specific and asthma-related health services use with the SO 4 component of PM 2.5 were above one, none were statistically significant. This study found significant associations with exposure to SO 4 in PM 2.5 and all-cause acute care, chiefly for hospitalizations, in children with asthma., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Rationale: Evidence linking outdoor air pollution with coronavirus disease (COVID-19) incidence and mortality is largely based on ecological comparisons between regions that may differ in factors such as access to testing and control measures that may not be independent of air pollution concentrations. Moreover, studies have yet to focus on key mechanisms of air pollution toxicity such as oxidative stress. Objectives: To conduct a within-city analysis of spatial variations in COVID-19 incidence and the estimated generation of reactive oxygen species (ROS) in lung lining fluid attributable to fine particulate matter (particulate matter with an aerodynamic diameter ⩽2.5 μm [PM 2.5 ]). Methods: Sporadic and outbreak-related COVID-19 case counts, testing data, population data, and sociodemographic data for 140 neighborhoods were obtained from the City of Toronto. ROS estimates were based on a mathematical model of ROS generation in lung lining fluid in response to iron and copper in PM 2.5 . Spatial variations in long-term average ROS were predicted using a land-use regression model derived from measurements of iron and copper in PM 2.5 . Data were analyzed using negative binomial regression models adjusting for covariates identified using a directed acyclic graph and accounting for spatial autocorrelation. Measurements and Main Results: A significant positive association was observed between neighborhood-level ROS and COVID-19 incidence (incidence rate ratio = 1.07; 95% confidence interval, 1.01-1.15 per interquartile range ROS). Effect modification by neighborhood-level measures of racialized group membership and socioeconomic status was also identified. Conclusions: Examination of neighborhood characteristics associated with COVID-19 incidence can identify inequalities and generate hypotheses for future studies.

Background: Studies have demonstrated an association between phthalate exposure and childhood asthma, although results have been inconsistent. No epidemiological studies have examined exposure during the first year of life., Objective: To investigate the association between phthalate exposures in the home environment during the first year of life, and subsequent development of childhood asthma and related symptoms., Methods: This study used a case-cohort design including 436 randomly selected children and all additional cases of asthma at 5 years (n total  = 129) and recurrent wheeze between 2 and 5 years (n total  = 332) within the CHILD Cohort Study, a general population Canadian birth cohort of 3455 children. Phthalate exposure was assessed using house dust samples collected during a standardized home visit when children were 3-4 months of age. All children were assessed by specialist clinicians for asthma and allergy at 1, 3 and 5 years. Logistic regression was used to assess the association between exposure to five phthalates and asthma diagnosis at 5 years, and recurrent wheeze between 2 and 5 years, with further stratification by wheeze subtypes (late onset, persistent, transient) based on the timing of onset and persistence of wheeze symptoms., Results: Di(2-ethylhexyl) phthalate (DEHP) had the highest concentration in dust (median subcohort  = 217 μg/g), followed by benzyl butyl phthalate (BzBP) (20 μg/g). A nearly four-fold increase in risk of developing asthma was associated with the highest concentration quartile of DEHP (OR = 3.92, 95% CI: 1.87-8.24) including a positive dose-response relationship. A two-fold increase in risk of recurrent wheeze was observed across all quartiles compared to the lowest quartile of DEHP concentrations. Compared to other wheeze subtypes, stronger associations for DEHP were observed with the late onset wheezing subtype, while stronger associations for di-iso-butyl phthalate (DiBP) and BzBP were observed with the transient subtype., Discussion: DEHP exposure at 3-4 months, at concentrations lower than other studies that reported an association, were associated with increased risks of asthma and recurrent wheeze among children at 5 years. These findings suggest the need to assess whether more stringent regulations are required to protect children's health, which can be informed by future work exploring the main sources of DEHP exposure., (Copyright © 2021. Published by Elsevier Inc.)

Many countries have dedicated to the mitigation of air pollution in the past several decades. However, evidence of beneficial effects of air quality improvement on chronic kidney disease (CKD) remains limited. We thus investigated the effects of dynamic changes (including deterioration and improvement) in air quality on the incidence of CKD in a longitudinal study in Taiwan. During 2001-2016, this study recruited a total of 163,197 Taiwanese residents who received at least two standard physical examinations. The level of fine particle matter (PM 2.5 ) was estimated using a high-resolution (1 km 2 ) satellite-based spatio-temporal model. We defined changes of PM 2.5 concentrations (ΔPM 2.5 ) as the difference between the two-year average measurements during follow-up and during the immediately preceding visit. The time-dependent Cox regression model was adopted to evaluate the relationships between ΔPM 2.5 and the incidence of CKD after adjusting for a series of covariates. The concentrations of PM 2.5 in Taiwan peaked around 2004 and began to decrease since 2005. We observed an approximate linear concentration-response relationship of ΔPM 2.5 with CKD incidence. Every 5 μg/m 3 decrease in the ambient concentration of PM 2.5 was associated with a 25% reduced risk of CKD development [hazard ratio (HR): 0.75; 95% CI: 0.73, 0.78]. In conclusion, this study demonstrated that the improvement of PM 2.5 air quality might be associated with a lower risk of CKD development. Our findings indicate that reducing air pollution may effectively prevent the development of CKD.

A spatiotemporal land use regression (LUR) model optimized to predict nitrogen dioxide (NO 2 ) concentrations obtained from on-road, mobile measurements collected in 2015-16 was independently evaluated using concentrations observed at multiple sites across Toronto, Canada, obtained more than ten years earlier. This spatiotemporal LUR modelling approach improves upon estimates of historical NO 2 concentrations derived from the previously used method of back-extrapolation. The optimal spatiotemporal LUR model (R 2  = 0.71 for prediction of NO 2 data in 2002 and 2004) uses daily average NO 2 concentrations observed at multiple long-term monitoring sites and hourly average wind speed recorded at a single site, along with spatial predictors based on geographical information system data, to estimate NO 2 levels for time periods outside of those used for model development. While the model tended to underestimate samplers located close to the roadway, it showed great accuracy when estimating samplers located beyond 100 m which are probably more relevant for exposure at residences. This study shows that spatiotemporal LUR models developed from strategic, multi-day (30 days in 3 different months) mobile measurements can enhance LUR model's ability to estimate long-term, intra-urban NO 2 patterns. Furthermore, the mobile sampling strategy enabled this new LUR model to cover a larger domain of Toronto and outlying suburban communities, thereby increasing the potential population for future epidemiological studies., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Movement behaviors (physical activity, sedentary time, and sleep) established in early childhood track into adulthood and interact to influence health outcomes. This study examined the associations between neighborhood characteristics and weather with movement behaviors in preschoolers., Methods: A subset of Canadian Healthy Infant Longitudinal Development birth cohort (n = 385, 50.6% boys) with valid movement behaviors data were enrolled at age 3 years and followed through to age 5 years. Objective measures of neighborhood characteristics were derived by ArcGIS software, and weather variables were derived from the Government of Canada weather website. Random forest and linear mixed models were used to examine predictors of movement behaviors. Cross-sectional analyses were stratified by age and season (winter and nonwinter)., Results: Neighborhood safety, temperature, green space, and roads were important neighborhood characteristics for movement behaviors in 3- and 5-year-olds. An increase in temperature was associated with greater light physical activity longitudinally from age 3 to 5 years and also in the winter at age 5 years in stratified analysis. A higher percentage of expressways was associated with less nonwinter moderate to vigorous physical activity at age 3 years., Conclusions: Future initiatives to promote healthy movement behaviors in the early years should consider age differences, neighborhood characteristics, and season.

The adverse effects of long-term exposure to environmental noise on human health are of increasing concern. Noise mapping methods such as spatial interpolation and land use regression cannot capture complex relationships between environmental conditions and noise propagation or attenuation in a three-dimension (3D) built environment. In this study, we developed a hybrid approach by combining a traffic propagation model and random forests (RF) machine learning algorithm to map the total environment noise levels for daily average, daytime, nighttime, and day-evening-nighttime at 30 m × 30 m resolution for the island of Montreal, Canada. The propagation model was used to predict traffic noise surfaces using road traffic flow, 3D building information, and a digital elevation model. The traffic noise estimates were compared with ground-based sound-level measurements at 87 points to extract residuals between total environmental noise and traffic noise. Residuals at these points were fit to RF models with multiple environmental and geographic predictor variables (e.g., vegetation index, population density, brightness of nighttime lights, land use types, and distances to noise contour around the airport, bus stops, and road intersections). Using the sound-level measurements as baseline data, the prediction errors, i.e., mean error, mean absolute error, and root mean squared error of daily average noise levels estimated by our hybrid approach was -0.03 dB(A), 2.67 dB(A), and 3.36 dB(A). Combining deterministic and stochastic models can provide accurate total environmental noise estimates for large geographic areas where sound-level measurements are available., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Ambient fine particulate matter (PM 2.5 ) data of similar continuously monitored species at two air monitoring sites with different characteristics within the City of Toronto were used to gauge the intra-city variations in the PM composition over a largely concurrent period spanning two years. One location was <8 m from the side of a major highway while the other was an urban background location. For the first time, multi-time resolution factor analysis was applied to dispersion-normalized concentrations to identify and quantify source contributions while reducing the influence of local meteorology. These factors were particulate sulphate (pSO4), particulate nitrate (pNO3), secondary organic aerosols (SOA), crustal matter (CrM) that were common to both sites, a hydrocarbon-like organic matter (HOM) exclusive to the urban background site, three black carbon related factors (BC, BC-HOM at the highway site, and a brown carbon rich factor (BC-BrC) at the urban background site), biomass burning organic matter (BBOM) and brake dust (BD) factors exclusive to the highway site. The PM 2.5 composition was different between these two locations, over only a 10 km distance. The sum of SOA, pSO4 and pNO3 at the urban background site averaged 57% of the PM 2.5 mass while the same species represented 43% of the average PM 2.5 mass at the highway site. Local or site-specific factors may be of greater interest for control policy design. Thus, regression analyses with potential explanatory, site-specific variables were performed for results from the highway site. Three model approaches were explored: multiple linear regression (MLR), regression with a generalized reduced gradient (GRG) algorithm, and a generalized additive model (GAM). GAM gave the largest fraction of variance for the locally-found factors at the highway site. Heavy-duty vehicles were most important for explaining the black carbon (BC and BC-HOM) factors. Light-duty vehicles were dominant for the brake dust (BD) factor. The auxiliary modelling for the local factors showed that the traffic-related factors likely originated along the main roadways at their respective sites while the more regional factors, - pSO4, pNO3, SOA, - had sources that were both regional and local in origin and with contributions that varied seasonally. These results will be useful in understanding ambient particulate matter sources on a city scale that will support air quality management planning., 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., (Crown Copyright © 2020. Published by Elsevier B.V. All rights reserved.)