Persistent DNA Methylation Changes across the First Year of Life and Prenatal NO2 Exposure in a Canadian Prospective Birth Study.

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 (NO2) 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 NO2 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 NO2 (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 NO2 in the first year of life was examined. Causal mediation investigated whether DNAm differences mediated associations between NO2 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 NO2, 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 NO2 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 NO2 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.

HealthyPlan.City: A Web Tool to Support Urban Environmental Equity and Public Health in Canadian Communities.

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.

Maternal smoking during pregnancy increases the risk of gut microbiome-associated childhood overweight and obesity.

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 in house dust and mental health outcomes among Canadian mothers: A nested prospective cohort study in CHILD.

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 (ß: 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.

Evidence Synthesis of Observational Studies in Environmental Health: Lessons Learned from a Systematic Review on Traffic-Related Air Pollution.

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.

Long-term spatiotemporal variations in surface NO2 for Beijing reconstructed from surface data and satellite retrievals.

Remote sensing data from the Ozone Monitoring Instrument (OMI) and the TROPOspheric Monitoring Instrument (TROPOMI) play important roles in estimating surface nitrogen dioxide (NO2), but few studies have compared their differences for application in surface NO2 reconstruction. This study aims to explore the effectiveness of incorporating the tropospheric NO2 vertical column density (VCD) from OMI and TROPOMI (hereafter referred to as OMI and TROPOMI, respectively, for conciseness) for deriving surface NO2 and to apply the resulting data to revisit the spatiotemporal variations in surface NO2 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 R2 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 NO2 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 NO2 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 R2 of 0.46 (RMSE = 7.0 ppb). Regarding the long-term trend of surface NO2, 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 NO2 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 NO2 dataset was developed for Beijing to support future environmental management questions and epidemiological research.

Natural Green Spaces, Sensitization to Allergens, and the Role of Gut Microbiota during Infancy.

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.

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries.

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.

GlobeCorr: interactive globe-based visualization for correlation datasets.

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.

A database of modeled gridded dry deposition velocities for 45 gaseous species and three particle size ranges across North America.

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 (Vd). Field measurement based Vd 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 Vd 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 Vd 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 Vd showed values higher than 1-3 cm/sec for those soluble and reactive species over certain land types. Soluble species have the highest Vd over water surfaces, while insoluble but reactive species have the highest Vd over forests. Hourly Vd of PM2.5 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 Vd for PM2.5-10 is twice that of PM2.5. Uncertainties in the modeled Vd 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.

Predicting walking-to-work using street-level imagery and deep learning in seven Canadian cities.

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.

How low can you go? Air pollution affects mortality at very low levels.

The World Health Organization (WHO) recently released new guidelines for outdoor fine particulate air pollution (PM2.5) recommending an annual average concentration of 5 µg/m3. Yet, our understanding of the concentration-response relationship between outdoor PM2.5 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 PM2.5 and mortality at very low (<5 µg/m3) concentrations. Our updated global concentration-response function incorporating this new information suggests an additional 1.5 million deaths globally attributable to outdoor PM2.5 annually compared to previous estimates. The global health benefits of meeting the new WHO guideline for outdoor PM2.5 are greater than previously assumed and indicate a need for continued reductions in outdoor air pollution around the world.

Health burden and economic loss attributable to ambient PM2.5 in Iran based on the ground and satellite data.

We estimated mortality and economic loss attributable to PM2·5 air pollution exposure in 429 counties of Iran in 2018. Ambient PM2.5-related deaths were estimated using the Global Exposure Mortality Model (GEMM). According to the ground-monitored and satellite-based PM2.5 data, the annual mean population-weighted PM2·5 concentrations for Iran were 30.1 and 38.6 µg m-3, respectively. We estimated that long-term exposure to ambient PM2.5 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 PM2.5. The crude death rate and the age-standardized death rate per 100,000 population for age group ≥ 25 year due to ground-monitored PM2.5 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 PM2.5 data, the economic loss attributable to ambient PM2.5-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.

An Investigation into Which Methods Best Explain Children's Exposure to Traffic-Related Air Pollution.

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.

Ambient Air Pollution and Dysanapsis: Associations with Lung Function and Chronic Obstructive Pulmonary Disease in the Canadian Cohort Obstructive Lung Disease Study.

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 (PM2.5) and nitrogen dioxide (NO2) 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 FEV1 were demonstrated per increase of 2.4 ug/m3 PM2.5 and 9.2 ppb NO2, 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 FEV1 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/m3 increment of PM2.5. 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.

Assessment of Alkylated and Unsubstituted Polycyclic Aromatic Hydrocarbons in Air in Urban and Semi-Urban Areas in Toronto, Canada.

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.

Global fine-scale changes in ambient NO2 during COVID-19 lockdowns.

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health1-9. A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-1910-20. Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 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 NO2 concentrations from NO2 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 NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 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 NO2 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.

Urinary Eicosanoid Levels Reflect Allergen and Diesel Exhaust Coexposure and Are Linked to Impaired Lung Function.

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-PGF1α (PGF1α, prostaglandin F1α) 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 E4 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.

Assessing secondhand and thirdhand tobacco smoke exposure in Canadian infants using questionnaires, biomarkers, and machine learning.

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.