Search

Prenatal exposures to ambient particulate matter (PM2.5) from traffic may generate oxidative stress and thus contribute to adverse birth outcomes. We investigated whether PM2.5 constituents from brake and tire wear affect levels of oxidative stress biomarkers (malondialdehyde [MDA], 8-hydroxy-2'-deoxyguanosine [8-OHdG]) using urine samples collected up to 3 times during pregnancy in 156 women recruited from antenatal clinics at the University of California Los Angeles. Land use regression models with co-kriging were employed to estimate average residential outdoor concentrations of black carbon (BC), PM2.5 mass, PM2.5 metal components, and 3 PM2.5 oxidative potential metrics during the 4 weeks prior to urine sample collection. The 8-OHdG concentrations in mid-pregnancy increased by 24.8% (95% confidence interval [CI], 9.0-42.8) and 14.3% (95% CI, 0.4%-30.0%) per interquartile range (IQR) increase in PM2.5 mass and BC, respectively. The brake wear marker (barium) and the oxidative potential metrics were associated with increased MDA concentration in the first sample collected (10-17 gestational week), but 95% CIs included the null. Traffic-related air pollution contributed in early to mid-pregnancy to oxidative stress generation previously linked to adverse birth outcomes. This article is part of a Special Collection on Environmental Epidemiology., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Air pollution is the leading environmental risk factor for health. Assessing outdoor air pollution exposure with detailed spatial and temporal variability in urban areas is crucial for evaluating its health effects., Aim: We developed and compared Land Use Regression (LUR), dispersion (DM), and hybrid (HM) models to estimate outdoor concentrations for NO 2 , PM 2.5 , black carbon (BC), and PM 2.5-constituents (Fe, Cu, Zn) in Barcelona., Methods: Two monitoring campaigns were conducted. In the first, NO 2 concentrations were measured twice at 984 home addresses and in the second, NO 2 , PM 2.5 , and BC were measured four times at 34 points across Barcelona. LUR and DM were constructed using conventional techniques, while HM was developed using Random Forest (RF). Model performance was evaluated using leave-one-out cross-validation (LOOCV) and 10-fold cross-validation (10-CV) for LUR and HM, and by comparing DM and LUR estimates with routine monitoring stations. NO 2 levels estimated by all models were externally validated using the home monitoring campaign. Agreement between models was assessed using Spearman correlation (rs) and Bland-Altman (BA) plots., Results: Models showed moderate to good performance. LUR exhibited R 2 LOOCV of 0.62 (NO 2 ), 0.45 (PM 2.5 ), 0.83 (BC), and 0.85 to 0.89 (PM 2.5-constituents ). DM model comparison showed R 2 values of 0.39 (NO 2 ), 0.26 (PM 2.5 ), and 0.65 (BC). HM models had higher R 2 10-CV 0.64 (NO 2 ), 0.66 (PM 2.5 ), 0.86 (BC), and 0.44 to 0.70 (PM 2.5-constituents ). Validation for NO 2 showed R 2 values of 0.56 (LUR), 0.44 (DM), and 0.64 (HM). Correlations between models varied from -0.38 to 0.92 for long-term exposure, and - 0.23 to 0.94 for short-term exposure. BA plots showed good agreement between models, especially for NO 2 and BC., Conclusions: Our models varied substantially, with some models performing better in validation samples (NO 2 and BC). Future health studies should use the most accurate methods to minimize bias from exposure measurement error., 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 © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Racially minoritized populations experience higher rates of adverse birth outcomes than White populations in the U.S. We estimated the mediating effect of neighborhood social and physical environments on disparities in adverse birth outcomes in California., Method: We used birthing parent's residential address for California live birth records from 2019 to estimate census block group Area Deprivation Index and census tract level measures of ambient fine particulate matter (PM2.5), drinking water contamination, tree canopy coverage, as a measure of greenspace, potential heat vulnerability, and noise. We performed mediation analysis to assess whether neighborhood factors explain racial/ethnic disparities in preterm birth (PTB) and term-birth low birth weight (TLBW) comparing Black, Latinx, and Asian with White births after controlling for individual-level factors., Results: Black, Latinx, and Asian parents had PTB rates that were 67%, 36%, and 11% higher, and TLBW rates that were 150%, 38%, and 81% higher than Whites. Neighborhood deprivation contributed 7% (95% CI: 3%, 11%) to the Black-White and 9% (95% CI: 6%, 12%) to the Latinx-White disparity in PTB, and 8% (95% CI: 3%, 12%) of the Black-White and 9% (95% CI: 5%, 15%) of the Latinx-White disparity in TLBW. Drinking water contamination contributed 2% (95% CI: 1%, 4%) to the Latinx-White disparity in PTB. Lack of greenspace accounted for 7% (95% CI: 2%, 10%) of the Latinx-White PTB disparity and 7% (95% CI: 3%, 12%) of the Asian-White PTB disparity. PM2.5 contributed 11% (95% CI: 5%, 18%), drinking water contamination contributed 3% (95% CI: 1%, 7%), and potential heat vulnerability contributed 2% (95% CI: 1%, 3%) to the Latinx-White TLBW disparity. Lack of green space contributed 3% (95% CI: 1%, 6%) to the Asian-White TLBW disparity., Conclusions: Our study suggests social environments explain portions of Black/Latinx-White disparities while physical environments explain Latinx/Asian-White disparities in PTB and TLBW., 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 © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Post-9/11 veterans were exposed to environmental and occupational pollutants during deployment., Objective: Our aim was to determine associations between deployment-related exposures and sinusitis and rhinitis., Methods: Between April 2018 and March 2020, veterans with land-based deployment after 9/11 who were living within 25 miles of 6 Department of Veteran Affairs medical centers were randomly chosen by using a Defense Manpower Data Center roster. Participants completed interviewer-administered questionnaires, which included a 32-item deployment exposure battery and self-report of rhinitis and health professional-diagnosed sinusitis. Exposure categories included burn pit smoke, combustion engine exhaust/ground dust, other open combustion sources, toxicants, and military job-related VGDF. Each item was scored on the basis of frequency and duration of exposure; ordinal scores were summed and scaled to 100 within each category. Odds ratios (ORs) were estimated using logistic regression for sinusitis and rhinitis separately. ORs were scaled per 20-point exposure score., Results: Among the 1960 participants, the incidences of sinusitis and rhinitis with onset during deployment were 2.1% and 3.6%, respectively; the incidences of postdeployment onset were 5.1% and 5.6%, respectively. Toxicant exposure consisted mainly of "applying pesticide, insecticide, or repellent to your own skin or to your own clothing" and was associated with rhinitis with onset during deployment (OR = 1.50 [95% CI = 1.31-1.84]) and onset after deployment (OR = 1.21 [95% CI = 0.93-1.50]). There were no associations with burn pit smoke or other exposure categories., Conclusion: Veterans with deployment exposures to toxicants were at increased risk of rhinitis, particularly during deployment. The clinical evaluation of postdeployment veterans should address rhinitis as a deployment-related condition., Competing Interests: Supported by the VA Cooperative Studies Program 595: Pulmonary Health and Deployment to Southwest Asia and Afghanistan, also known as SHADE (Service and Health Among Deployed Veterans) from the US Department of Veterans Affairs, 10.13039/100006379Office of Research and Development, 10.13039/100015728Clinical Science Research and Development, Cooperative Studies Program. The contents do not represent the views of the US Department of Veterans Affairs or the US Government. Disclosure of potential conflict of interest: E. S. Wan has served on a scientific advisory board for Verona Pharma, outside the current work. The rest of the authors declare that they have no relevant conflicts of interest., (© 2024 The Authors.)

Introduction: The effects of smoking on lung function among post-9/11 Veterans deployed to environments with high levels of ambient particulate matter are incompletely understood., Materials and Methods: We analyzed interim data (04/2018-03/2020) from the Veterans Affairs (VA) Cooperative Studies Program #595, "Service and Health Among Deployed Veterans". Veterans with ≥1 land-based deployments enrolled at 1 of 6 regional Veterans Affairs sites completed questionnaires and spirometry. Multivariable linear regression models assessed associations between cigarette smoking (cumulative, deployment-related and non-deployment-related) with pulmonary function., Results: Among 1,836 participants (mean age 40.7 ± 9.6, 88.6% male), 44.8% (n = 822) were ever-smokers (mean age 39.5 ± 9.5; 91.2% male). Among ever-smokers, 86% (n = 710) initiated smoking before deployment, while 11% (n = 90) initiated smoking during deployment(s). Smoking intensity was 50% greater during deployment than other periods (0.75 versus 0.50 packs-per-day; P < .05), and those with multiple deployments (40.4%) were more likely to smoke during deployment relative to those with single deployments (82% versus 74%). Total cumulative pack-years (median [IQR] = 3.8 [1, 10]) was inversely associated with post-bronchodilator FEV1%-predicted (-0.82; [95% CI] = [-1.25, -0.50] %-predicted per 4 pack-years) and FEV1/FVC%-predicted (-0.54; [95% CI] = [-0.78, -0.43] %-predicted per 4 pack-years). Deployment-related pack-years demonstrated similar point estimates of associations with FEV1%-predicted (-0.61; [95% CI] = [-2.28, 1.09]) and FEV1/FVC%-predicted (-1.09; [95% CI] = [-2.52, 0.50]) as non-deployment-related pack-years (-0.83; [95% CI] = [-1.26, -0.50] for FEV1%-predicted; -0.52; [95% CI] = [-0.73, -0.36] for FEV1/FVC%-predicted)., Conclusions: Although cumulative pack-years smoking was modest in this cohort, an inverse association with pulmonary function was detectable. Deployment-related pack-years had a similar association with pulmonary function compared to non-deployment-related pack-years., (Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2024. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Background: Polycyclic aromatic hydrocarbons (PAHs) have been linked to adverse birth outcomes that have been reported to be induced by oxidative stress, but few epidemiological studies to date have evaluated associations between urinary PAH metabolites and oxidative stress biomarkers in pregnancy and identified critical periods for these outcomes and PAH exposures in pregnancy., Methods: A cohort of pregnant women was recruited early in pregnancy from antenatal clinics at the University of California Los Angeles during 2016-2019. We collected urine samples up to three times during pregnancy in a total of 159 women enrolled in the cohort. A total of 7 PAH metabolites and 2 oxidative stress biomarkers [malondialdehyde (MDA), 8-hydroxy-2'-deoxyguanosine (8-OHdG)] were measured in all available urine samples. Using multiple linear regression models, we estimated the percentage change (%) and 95% confidence interval (CI) in 8-OHdG and MDA measured at each sample collection time per doubling of PAH metabolite concentrations. Furthermore, we used linear mixed models with a random intercept for participant to estimate the associations between PAH metabolite and oxidative stress biomarker concentrations across multiple time points in pregnancy., Results: Most PAH metabolites were positively associated with both urinary oxidative stress biomarkers, MDA and 8-OHdG, with stronger associations in early and late pregnancy. A doubling of each urinary PAH metabolite concentration increased MDA concentrations by 5.8-41.1% and 8-OHdG concentrations by 13.8-49.7%. Linear mixed model results were consistent with those from linear regression models for each gestational sampling period., Conclusion: Urinary PAH metabolites are associated with increases in oxidative stress biomarkers during pregnancy, especially in early and late pregnancy., (© 2024. The Author(s).)

This study bridges gaps in air pollution research by examining exposure dynamics in disadvantaged communities. Using cutting-edge machine learning and massive data processing, we produced high-resolution (100 meters) daily air pollution maps for nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), and ozone (O 3 ) across California for 2012-2019. Our findings revealed opposite spatial patterns of NO 2 and PM 2.5 to that of O 3 . We also identified consistent, higher pollutant exposure for disadvantaged communities from 2012 to 2019, although the most disadvantaged communities saw the largest NO 2 and PM 2.5 reductions and the advantaged neighborhoods experienced greatest rising O 3 concentrations. Further, day-to-day exposure variations decreased for NO 2 and O 3 . The disparity in NO 2 exposure decreased, while it persisted for O 3 . In addition, PM 2.5 showed increased day-to-day variations across all communities due to the increase in wildfire frequency and intensity, particularly affecting advantaged suburban and rural communities.

California faces several serious direct and indirect climate exposures that can adversely affect public health, some of which are already occurring. The public health burden now and in the future will depend on atmospheric greenhouse gas concentrations, underlying population vulnerabilities, and adaptation efforts. Here, we present a structured review of recent literature to examine the leading climate risks to public health in California, including extreme heat, extreme precipitation, wildfires, air pollution, and infectious diseases. Comparisons among different climate-health pathways are difficult due to inconsistencies in study design regarding spatial and temporal scales and health outcomes examined. We find, however, that the current public health burden likely affects thousands of Californians each year, depending on the exposure pathway and health outcome. Further, while more evidence exists for direct and indirect proximal health effects that are the focus of this review, distal pathways (e.g., impacts of drought on nutrition) are more uncertain but could add to this burden. We find that climate adaptation measures can provide significant health benefits, particularly in disadvantaged communities. We conclude with priority recommendations for future analyses and solution-driven policy actions., Competing Interests: Competing interests statement:The authors declare no competing interest.

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM 2.5 ), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM 2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM 2.5 estimates. We used a concentration-response function for PM 2.5 , applying ZIP code-level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM 2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $432 to $456 billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

Objective: The aim of Placental Assessment in Response to Environmental Pollution Study (PARENTs) was to determine whether imaging of the placenta by novel multiparametric magnetic resonance imaging (MRI) techniques in early pregnancy could help predict adverse pregnancy outcomes (APOs) due to ischemic placental disease (IPD). Additionally, we sought to determine maternal characteristics and environmental risk factors that contribute to IPD and secondary APOs., Study Design: Potential patients in their first trimester of pregnancy, who agreed to MRI of the placenta and measures of assessment of environmental pollution, were recruited into PARENTs, a prospective population-based cohort study. Participants were seen at three study visits during pregnancy and again at their delivery from 2015 to 2019. We collected data from interviews, chart abstractions, and imaging. Maternal biospecimens (serum, plasma, and urine) at antepartum study visits and delivery specimens (placenta, cord, and maternal blood) were collected, processed, and stored. The primary outcome was a composite of IPD, which included any of the following: placental abruption, hypertensive disease of pregnancy, fetal growth restriction, or a newborn of small for gestational age., Results: In this pilot cohort, of the 190 patients who completed pregnancy to viable delivery, 50 (26%) developed IPD. Among demographic characteristics, having a history of prior IPD in multiparous women was associated with the development of IPD. In the multiple novel perfusion measurements taken of the in vivo placenta using MRI, decreased high placental blood flow (mL/100 g/min) in early pregnancy (between 14 and 16 weeks) was found to be significantly associated with the later development of IPD., Conclusion: Successful recruitment of the PARENTs prospective cohort demonstrated the feasibility and acceptability of the use of MRI in human pregnancy to study the placenta in vivo and at the same time collect environmental exposure data. Analysis is ongoing and we hope these methods will assist researchers in the design of prospective imaging studies of pregnancy., Key Points: · MRI was acceptable and feasible for the study of the human placenta in vivo.. · Functional imaging of the placenta by MRI showed a significant decrease in high placental blood flow.. · Measures of environmental exposures are further being analyzed to predict IPD.., Competing Interests: None declared., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background: Air pollution is a global health concern, with fine particulate matter (PM 2.5 ) constituents posing potential risks to human health, including children's neurodevelopment. Here we investigated associations between exposure during pregnancy and infancy to specific traffic-related PM 2.5 components with Autism Spectrum Disorder (ASD) diagnosis., Methods: For exposure assessment, we estimated PM 2.5 components related to traffic exposure (Barium [Ba] as a marker of brake dust and Zinc [Zn] as a tire wear marker, Black Carbon [BC]) and oxidative stress potential (OSP) markers (Hydroxyl Radical [OP OH ] formation, Dithiothreitol activity [OP DTT ], reactive oxygen species [ROS]) modeled with land use regression with co-kriging based on an intensive air monitoring campaign. We assigned exposures to a cohort of 444,651 children born in Southern California between 2016 and 2019, among whom 11,466 ASD cases were diagnosed between 2018 and 2022, Odds ratios (ORs) and 95% confidence intervals (CIs) were obtained with logistic regression for single pollutant and PM 2.5 mass co-adjusted models, also adjusting for sociodemographic characteristics., Results: Among PM 2.5 components, we found the strongest positive association with ASD for our brake wear marker Ba (OR per IQR  = 1.29, 95 % CI: 1.24, 1.34). This was followed by an increased risk for all PM 2.5 oxidative stress potential markers; the strongest association was with ROS formation (OR per IQR  = 1.22, 95 % CI: 1.18, 1.25). PM 2.5 mass was linked to ASD in Hispanic and Black children, but not White children, while traffic-related PM 2.5 and OSP markers increased ASD risk across all groups. In neighborhoods with the lowest socioeconomic status (SES), associations with ASD were stronger for all examined pollutants compared to higher SES areas., Conclusions: Our findings suggest that brake wear-related PM 2.5 and PM 2.5 OSP are associated with ASD diagnosis in Southern California. These results suggest that strategies aimed at reducing the public health impacts of PM 2.5 need to consider specific sources., 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 © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Urban green spaces have been consistently shown to have important human health benefits across a range of outcomes. These benefits are thought to be achieved, in part, because urban greenness provides opportunities for participation in recreational activity. However, the findings from studies that have assessed links between exposure to greenness and physical activity have been mixed. To date, few studies have examined association between greenness and specific types of recreational physical activities., Objective: We evaluated associations between measures of greenness and specific types of recreational physical activities. Moreover, we explored the extent to which these associations were modified by socioeconomic conditions, and regionally., Methods: We analyzed cross-sectional data from 49,649 women in the Sister Study and assigned three residentially-based measures of greenness based on national land cover data at buffer distances of 250 m and 500 m. Data on participation in up to ten specific recreational physical activities, including time spent in each activity were collected. Logistic regression was used to estimate odds ratios (OR) and their 95% confidence intervals (CI) controlling for confounders., Results: Compared to those in the lowest tertile of greenness, participants in the upper tertile of greenness within a 500 m buffer, were more likely to garden (OR = 1.46, 95% CI = 1.25,1.69), participate in sports (OR = 1.28, 95% CI = 1.19,1.38), run (OR = 1.15, 95% CI = 1.04,1.27), walk (OR = 1.11, 95% CI = 1.06,1.16), and engage in conditioning exercises (OR = 1.10, 95% CI = 1.05,1.16) at least once a week for at least one month over the past year. These associations were modified by household income and US region., Discussion: Our findings suggest a beneficial effect of greenness on physical activity and provide additional information to inform planning of green environments that contribute to better health and wellbeing., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dale P. Sandler reports financial support was provided by Intramural Program of the NIH, National Institute of Environmental Health Sciences., (Copyright © 2023. Published by Elsevier Inc.)

Objectives: Characterise inhalational exposures during deployment to Afghanistan and Southwest Asia and associations with postdeployment respiratory symptoms., Methods: Participants (n=1960) in this cross-sectional study of US Veterans (Veterans Affairs Cooperative Study 'Service and Health Among Deployed Veterans') completed an interviewer-administered questionnaire regarding 32 deployment exposures, grouped a priori into six categories: burn pit smoke; other combustion sources; engine exhaust; mechanical and desert dusts; toxicants; and military job-related vapours gas, dusts or fumes (VGDF). Responses were scored ordinally (0, 1, 2) according to exposure frequency. Factor analysis supported item reduction and category consolidation yielding 28 exposure items in 5 categories. Generalised linear models with a logit link tested associations with symptoms (by respiratory health questionnaire) adjusting for other covariates. OR were scaled per 20-point score increment (normalised maximum=100)., Results: The cohort mean age was 40.7 years with a median deployment duration of 11.7 months. Heavy exposures to multiple inhalational exposures were commonly reported, including burn pit smoke (72.7%) and VGDF (72.0%). The prevalence of dyspnoea, chronic bronchitis and wheeze in the past 12 months was 7.3%, 8.2% and 15.6%, respectively. Burn pit smoke exposure was associated with dyspnoea (OR 1.22; 95% CI 1.06 to 1.47) and chronic bronchitis (OR 1.22; 95% CI 1.13 to 1.44). Exposure to VGDF was associated with dyspnoea (OR 1.29; 95% CI 1.14 to 1.58) and wheeze (OR 1.18; 95% CI 1.02 to 1.35)., Conclusion: Exposures to burn pit smoke and military occupational VGDF during deployment were associated with an increased odds of chronic respiratory symptoms among US Veterans., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

The majority of Americans fail to achieve recommended levels of physical activity, which leads to numerous preventable health problems such as diabetes, hypertension, and heart diseases. This has generated substantial interest in monitoring human activity to gear interventions toward environmental features that may relate to higher physical activity. Wearable devices, such as wrist-worn sensors that monitor gross motor activity (actigraph units) continuously record the activity levels of a subject, producing massive amounts of high-resolution measurements. Analyzing actigraph data needs to account for spatial and temporal information on trajectories or paths traversed by subjects wearing such devices. Inferential objectives include estimating a subject's physical activity levels along a given trajectory; identifying trajectories that are more likely to produce higher levels of physical activity for a given subject; and predicting expected levels of physical activity in any proposed new trajectory for a given set of health attributes. Here, we devise a Bayesian hierarchical modeling framework for spatial-temporal actigraphy data to deliver fully model-based inference on trajectories while accounting for subject-level health attributes and spatial-temporal dependencies. We undertake a comprehensive analysis of an original dataset from the Physical Activity through Sustainable Transport Approaches in Los Angeles (PASTA-LA) study to ascertain spatial zones and trajectories exhibiting significantly higher levels of physical activity while accounting for various sources of heterogeneity.

Importance: Recent evidence links air pollution to the severity COVID-19 symptoms and to death from the disease. To date, however, few studies have assessed whether air pollution affects the sequelae to more severe states or recovery from COVID-19 in a cohort with individual data., Objective: To assess how air pollution affects the transition to more severe COVID-19 states or to recovery from COVID-19 infection in a cohort with detailed patient information., Design and Outcomes: We used a cohort design that followed patients admitted to hospital in the Kaiser Permanente Southern California (KPSC) Health System, which has 4.7 million members with characteristics similar to the general population. Enrollment began on 06/01/2020 and ran until 01/30/2021 for all patients admitted to hospital while ill with COVID-19. All possible states of sequelae were considered, including deterioration to intensive care, to death, discharge to recovery, or discharge to death. Transition risks were estimated with a multistate model. We assessed exposure using chemical transport model that predicted ambient concentrations of nitrogen dioxide, ozone, and fine particulate matter (PM 2.5 ) at a 1 km scale., Results: Each increase in PM 2.5 concentration equivalent to the interquartile range was associated with increased risk of deterioration to intensive care (HR of 1.16; 95% CI: 1.12-1.20) and deterioration to death (HR of 1.11; 95% CI: 1.04-1.17). Results for ozone were consistent with PM 2.5 effects, but ozone also affected the transition from recovery to death: HR of 1.24 (95% CI: 1.01-1.51). NO 2 had weaker effects but displayed some elevated risks., Conclusions: PM 2.5 and ozone were significantly associated with transitions to more severe states while in hospital and to death after discharge from hospital. Reducing air pollution could therefore lead to improved prognosis for COVID-19 patients and a sustainable means of reducing the health impacts of coronaviruses now and in the future., 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. Published by Elsevier Inc.)

Background: Although many studies have linked prenatal exposure to PM 2.5 to adverse birth outcomes, little is known about the effects of exposure to specific constituents of PM 2.5 or mechanisms that contribute to these outcomes., Objectives: Our objective was to investigate effects of oxidative potential and PM 2.5 metal components from non-exhaust traffic emissions, such as brake and tire wear, on the risk of preterm birth (PTB) and term low birth weight (TLBW)., Methods: For a birth cohort of 285,614 singletons born in Los Angeles County, California, in the period 2017-2019, we estimated speciated PM 2.5 exposures modeled from land use regression with cokriging, including brake and tire wear related metals (barium and zinc), black carbon, and three markers of oxidative potential (OP), including modeled reactive oxygen species based on measured iron and copper (ROS), OH formation ( OP OH ), and dithiothreitol (DTT) loss ( OP DTT ). Using logistic regression, we estimated odds ratios (OR) and 95% confidence intervals (CI) for PTB and TLBW with speciated PM 2.5 exposures and PM 2.5 mass as continuous variables scaled by their interquartile range (IQR)., Results: For both metals and oxidative potential metrics, we estimated increased risks for PTB (ORs ranging from 1.01 to 1.03) and TLBW (ORs ranging from 1.02 to 1.05) per IQR exposure increment that were robust to adjustment for PM 2.5 mass. Associations for PM 2.5 mass, black carbon, metal components, and oxidative potential (especially ROS and OP OH ) with adverse birth outcomes were stronger in Hispanic, Black, and mixed-race or Native American women., Discussion: Our results indicate that exposure to PM 2.5 metals from brake and tire wear and particle components that contribute to oxidative potential were associated with an increased risk of PTB and TLBW in Los Angeles County, particularly among Hispanic, Black, and mixed-race or Native American women. Thus, reduction of PM 2.5 mass only may not be sufficient to protect the most vulnerable pregnant women and children from adverse effects due to traffic source exposures. https://doi.org/10.1289/EHP12196.

Background: Few studies investigated the impact of particulate matter (PM 2.5 ) on some symptom exacerbations that are not perceived as severe enough to search for medical assistance. We aimed to study the association of short-term daily total PM 2.5 exposure with work loss due to sickness among adults living in California., Methods: We included 44,544 adult respondents in the workforce from 2015 to 2018 California Health Interview Survey data. Daily total PM 2.5 concentrations were linked to respondents' home addresses from continuous spatial surfaces of PM 2.5 generated by a geostatistical surfacing algorithm. We estimated the effect of a 2-week average of daily total PM 2.5 exposure on work loss using logistic regression models., Results: About 1.69% (weighted percentage) of adult respondents reported work loss in the week before the survey interview. The odds ratio of work loss was 1.45 (odds ratio [OR] = 1.45, 95% confidence interval [CI]: 1.03, 2.03) when a 2-week average of daily total PM 2.5 exposure was higher than 12 µg/m 3 . The OR for work loss was 1.05 (95% CI: 0.98, 1.13) for each 2.56ug/m 3 increase in the 2-week average of daily total PM 2.5 exposure, and became stronger among those who were highly exposed to wildfire smoke (OR = 1.06, 95% CI: 1.00, 1.13), compared to those with lower wildfire smoke exposure (OR = 1.04, 95% CI: 0.79, 1.39)., Conclusions: Our findings suggest that short-term ambient PM 2.5 exposure is positively associated with work loss due to sickness and the association was stronger among those with higher wildfire smoke exposure. It also indicated that the current federal and state PM 2.5 standards (annual average of 12 µg/m 3 ) could be further strengthened to protect the health of the citizens of California., 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.)

Background: To improve physical activity in Latin American cities, several interventions have been promoted, such as Open Streets programmes. Our study aims to quantify the health and economic effects of Open Streets-related physical activity in 15 Latin American cities., Methods: We used a quantitative health impact assessment approach to estimate annual premature deaths and disease incidence (ischaemic heart disease, ischaemic stroke, type 2 diabetes, colon cancer, breast cancer, and dementia) avoided, the disability-adjusted life-years (DALYs) gained, and the cost saving (from reduced premature mortality) related to increased physical activity from Open Streets programmes in 15 Latin American cities. Input data were obtained from scientific publications, reports, and open street city surveys spanning 2017 to 2019. Physical activity data were converted to metabolic equivalent of the task. Exposure-response relationship functions were applied to estimate relative risk and population-attributable fraction, enabling the assessment of premature deaths and disease incidence., Findings: The percentage of male users of the Open Streets programmes ranged from 55% (27 500 of 50 000 in Guatemala) to 75% (2250 of 3000 in El Alto, Bolivia), and female users ranged from 25% (750; El Alto) to 45% (22 500; Guatemala). We estimated that the current Open Streets programmes in the 15 Latin American cities studied could prevent 363 (95% CI 271-494) annual premature deaths due to increased physical activity, with an annual economic impact of US$194·1 million (144·9 million-263·9 million) saved and an annual reduction of 1036·7 DALYs (346·7-1778·3). If one Open Streets event is added per week in each of those cities, the potential benefit could increase to 496 (370 to 677) premature deaths prevented each year., Interpretation: Open Streets programmes in Latin America can provide health and economic benefits related to increased physical activity and can be used as a health promotion and disease prevention tool., Funding: EU's Horizon 2020 research and innovation programme., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Fine particulate air pollution (PM 2.5 ) is decreasing in most areas of the United States, except for areas most affected by wildfires, where increasing trends in PM 2.5 can be attributed to wildfire smoke. The frequency and duration of large wildfires and the length of the wildfire season have all increased in recent decades, partially due to climate change, and wildfire risk is projected to increase further in many regions including the western United States. Increasingly, empirical evidence suggests differential health effects from air pollution by class and race; however, few studies have investigated such differential health impacts from air pollution during a wildfire event. We investigated differential risk of respiratory health impacts during the 2008 northern California wildfires by a comprehensive list of socio-economic status (SES), race/ethnicity, and smoking prevalence variables. Regardless of SES level across nine measures of SES, we found significant associations between PM 2.5 and asthma hospitalizations and emergency department (ED) visits during these wildfires. Differential respiratory health risk was found by SES for ED visits for chronic obstructive pulmonary disease where the highest risks were in ZIP codes with the lowest SES levels. Findings for differential effects by race/ethnicity were less consistent across health outcomes. We found that ZIP codes with higher prevalence of smokers had greater risk of ED visits for asthma and pneumonia. Our study suggests that public health efforts to decrease exposures to high levels of air pollution during wildfires should focus on lower SES communities., Competing Interests: Conflict of interest The authors have no competing interests to declare.

Substantial evidence suggests that access to urban green spaces and parks is associated with positive health outcomes, including decreased mortality. Few existing studies have investigated the association between green spaces and life expectancy (LE), and none have used small-area data in the U.S. Here we used the recently released U.S. Small-Area Life Expectancy Estimates Project data to quantify the relationship between LE and green space in Los Angeles County, a large diverse region with inequities in park access. We developed a model to quantify the association between green space and LE at the census tract level. We evaluated three green space metrics: normalized difference vegetation index (NDVI, 0.6-meter scale), percent tree canopy cover, and accessible park acres. We statistically adjusted for 15 other determinants of LE. We also developed conditional autoregressive models to account for spatial dependence. Tree canopy and NDVI were both significantly associated with higher LE. For an interquartile range (IQR) increase in each metric respectively, the spatial models demonstrated a 0.24 to 0.33-year increase in LE. Tree canopy and NDVI also modified the effect of park acreage on LE. ln areas with tree canopy levels below the county median, an IQR increase in park acreage was associated with an increase of 0.12 years. Although on an individual level these effects were modest, we predicted 155,300 years of LE gains across the population in LA County if all areas below median tree canopy were brought to the county median of park acres. If tree canopy or NDVI were brought to median levels, between 570,300 and 908,800 years of LE could be gained. The majority of potential gains are in areas with predominantly Hispanic/Latinx and Black populations. These findings suggest that equitable access to green spaces could result in substantial population health benefits., 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 Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Both air pollution and noise exposures have separately been shown to affect cognitive impairment. Here, we examine how air pollution and noise exposures interact to influence the development of incident dementia or cognitive impairment without dementia (CIND)., Methods: We used 1,612 Mexican American participants from the Sacramento Area Latino Study on Aging conducted from 1998 to 2007. Air pollution (nitrogen dioxides, particulate matter, ozone) and noise exposure levels were modeled with a land-use regression and via the SoundPLAN software package implemented with the Traffic Noise Model applied to the greater Sacramento area, respectively. Using Cox proportional hazard models, we estimated the hazard of incident dementia or CIND from air pollution exposure at the residence up to 5-years prior to diagnosis for the members of each risk set at event time. Further, we investigated whether noise exposure modified the association between air pollution exposure and dementia or CIND., Results: In total, 104 incident dementia and 159 incident dementia/CIND cases were identified during the 10 years of follow-up. For each ∼2 µg/m 3 increase in time-varying 1- and 5-year average PM 2.5 exposure, the hazard of dementia increased 33% (HR = 1.33, 95%CI: 1.00, 1.76). The hazard ratios for NO 2 -related dementia/CIND and PM 2.5 -related dementia were stronger in high-noise (≥65 dB) exposed than low-noise (<65 dB) exposed participants., Conclusion: Our study indicates that PM 2.5 and NO 2 air pollution adversely affect cognition in elderly Mexican Americans. Our findings also suggest that air pollutants may interact with traffic-related noise exposure to affect cognitive function in vulnerable populations., 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 Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Recent evidence links ambient air pollution to COVID-19 incidence, severity, and death, but few studies have analyzed individual-level mortality data with high quality exposure models., Methods: We sought to assess whether higher air pollution exposures led to greater risk of death during or after hospitalization in confirmed COVID-19 cases among patients who were members of the Kaiser Permanente Southern California (KPSC) healthcare system (N=21,415 between 06-01-2020 and 01-31-2022 of whom 99.85 % were unvaccinated during the study period). We used 1 km resolution chemical transport models to estimate ambient concentrations of several common air pollutants, including ozone, nitrogen dioxide, and fine particle matter (PM 2.5 ). We also derived estimates of pollutant exposures from ultra-fine particulate matter (PM 0.1 ), PM chemical species, and PM sources. We employed Cox proportional hazards models to assess associations between air pollution exposures and death from COVID-19 among hospitalized patients., Findings: We found significant associations between COVID-19 death and several air pollution exposures, including: PM 2.5 mass, PM 0.1 mass, PM 2.5 nitrates, PM 2.5 elemental carbon, PM 2.5 on-road diesel, and PM 2.5 on-road gasoline. Based on the interquartile (IQR) exposure increment, effect sizes ranged from hazard ratios (HR) = 1.12 for PM 2.5 mass and PM 2.5 nitrate to HR ∼ 1.06-1.07 for other species or source markers. Humidity and temperature in the month of diagnosis were also significant negative predictors of COVID-19 death and negative modifiers of the air pollution effects., Interpretation: Air pollution exposures and meteorology were associated the risk of COVID-19 death in a cohort of patients from Southern California. These findings have implications for prevention of death from COVID-19 and for future pandemics., 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 © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 μm in diameter (PM 2.5 ) to evaluate adverse health outcomes associated with particulate air pollution exposure. Here, we investigate how OP depends on sources and chemical composition and how OP varies by land use type and neighborhood socioeconomic position in the Los Angeles area. We measured OH formation (OP OH ), dithiothreitol loss (OP DTT ), black carbon, and 52 metals and elements for 54 total PM 2.5 samples collected in September 2019 and February 2020. The Positive Matrix Factorization source apportionment model identified four sources contributing to volume-normalized OP OH : vehicular exhaust, brake and tire wear, soil and road dust, and mixed secondary and marine. Exhaust emissions contributed 42% of OP OH , followed by 21% from brake and tire wear. Similar results were observed for the OP DTT source apportionment. Furthermore, by linking measured PM 2.5 and OP with census tract level socioeconomic and health outcome data provided by CalEnviroScreen, we found that the most disadvantaged neighborhoods were exposed to both the most toxic particles and the highest particle concentrations. OP OH exhibited the largest inverse social gradients, followed by OP DTT and PM 2.5 mass. Finally, OP OH was the metric most strongly correlated with adverse health outcome indicators.

Introduction: This study examines whether the "Emission Reduction Plan for Ports and Goods Movement" in California reduced air pollution exposures and emergency room visits among California Medicaid enrollees with asthma and/or chronic obstructive pulmonary disease., Method: We created a retrospective cohort of 5608 Medicaid enrollees from ten counties in California with data from 2004 to 2010. We grouped the patients into two groups: those living within 500 m of goods movement corridors (ports and truck-permitted freeways), and control areas (away from the busy truck or car permitted highways). We created annual air pollution surfaces for nitrogen dioxide and assigned them to enrollees' home addresses. We used a quasi-experimental design with a difference-in-differences method to examine changes before and after the policy for cohort beneficiaries in the two groups., Results: The reductions in nitrogen dioxide exposures and emergency room visits were greater for enrollees in goods movement corridors than those in control areas in post-policy years. We found that the goods movement actions were associated with 14.8% (95% CI, -24.0% to -4.4%; P = 0.006) and 11.8% (95% CI, -21.2% to -1.2%; P = 0.030) greater reduction in emergency room visits for the beneficiaries with asthma and chronic obstructive pulmonary disease, respectively, in the third year after California's emission reduction plan., Conclusion: These findings indicate remarkable health benefits via reduced emergency room visits from the significantly improved air quality due to public policy interventions for disadvantaged and susceptible populations., (Copyright © 2022 Elsevier Inc. All rights reserved.)

In this short communication, we estimate that California's wildfire carbon dioxide equivalent (CO 2 e) emissions from 2020 are approximately two times higher than California's total greenhouse gas (GHG) emission reductions since 2003. Without considering future vegetation regrowth, CO 2 e emissions from the 2020 wildfires could be the second most important source in the state above either industry or electrical power generation. Regrowth may partly of fully occur over a long period, but due to exigencies of the climate crisis most of the regrowth will not occur quickly enough to avert greater than 1.5 degrees of warming. Global monetized damages caused by CO 2 e from in 2020 wildfire emissions amount to some $7.1 billion USD. Our analysis suggests that significant societal benefits could accrue from larger investments in improved forest management and stricter controls on new development in fire-prone areas at the wildland-urban interface., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Due to regulations and technological advancements reducing tailpipe emissions, an increasing proportion of emissions arise from brake and tire wear particulate matter (PM). PM from these non-tailpipe sources contains heavy metals capable of generating oxidative stress in the lung. Although important, these particles remain understudied because the high cost of actively collecting filter samples. Improvements in electrical engineering, internet connectivity, and an increased public concern over air pollution have led to a proliferation of dense low-cost air sensor networks such as the PurpleAir monitors, which primarily measure unspeciated fine particulate matter (PM 2.5 ). In this study, we model the concentrations of Ba, Zn, black carbon, reactive oxygen species concentration in the epithelial lining fluid, dithiothreitol (DTT) loss, and OH formation. We use a co-kriging approach, incorporating data from the PurpleAir network as a secondary predictor variable and a land-use regression (LUR) as an external drift. For most pollutant species, co-kriging models produced more accurate predictions than an LUR model, which did not incorporate data from the PurpleAir monitors. This finding suggests that low-cost sensors can enhance predictions of pollutants that are costly to measure extensively in the field., 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 © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Risk management decisions in public health require consideration of a number of complex, often conflicting factors. The aim of this review was to propose a set of 10 fundamental principles to guide risk decision-making. Although each of these principles is sound in its own right, the guidance provided by different principles might lead the decision-maker in different directions. For example, where the precautionary principle advocates for preemptive risk management action under situations of scientific uncertainty and potentially catastrophic consequences, the principle of risk-based decision-making encourages decision-makers to focus on established and modifiable risks, where a return on the investment in risk management is all but guaranteed in the near term. To evaluate the applicability of the 10 principles in practice, one needs to consider 10 diverse risk issues of broad concern and explore which of these principles are most appropriate in different contexts. The 10 principles presented here afford substantive insight into the process of risk management decision-making, although decision-makers will ultimately need to exercise judgment in reaching appropriate risk decisions, accounting for all of the scientific and extra-scientific factors relevant to the risk decision at hand.

Background: Growing evidence suggests that exposure to green space is associated with improved childhood health and development, but the influence of different green space types remains relatively unexplored. In the present study, we investigated the association between early-life residential exposure to vegetation and early childhood development and evaluated whether associations differed according to land cover types, including paved land., Methods: Early childhood development was assessed via kindergarten teacher-ratings on the Early Development Instrument (EDI) in a large population-based birth cohort (n = 27,539) in Metro Vancouver, Canada. The residential surrounding environment was characterized using a high spatial resolution land cover map that was linked to children by six-digit residential postal codes. Early-life residential exposure (from birth to time of EDI assessment, mean age = 5.6 years) was calculated as the mean of annual percentage values of different land cover classes (i.e., total vegetation, tree cover, grass cover, paved surfaces) within a 250 m buffer zone of postal code centroids. Multilevel models were used to analyze associations between respective land cover classes and early childhood development., Results: In adjusted models, one interquartile range increase in total vegetation percentage was associated with a 0.33 increase in total EDI score (95% CI: 0.21, 0.45). Similar positive associations were observed for tree cover (β-coefficient: 0.26, 95% CI: 0.15, 0.37) and grass cover (β-coefficient: 0.12, 95% CI: 0.02, 0.22), while negative associations were observed for paved surfaces (β-coefficient: -0.35, 95% CI: -0.47, -0.23)., Conclusions: Our findings indicate that increased early-life residential exposure to vegetation is positively associated with early childhood developmental outcomes, and that associations may be stronger for residential exposure to tree cover relative to grass cover. Our results further indicate that childhood development may be negatively associated with residential exposure to paved surfaces. These findings can inform urban planning to support early childhood developmental health., (Copyright © 2022. Published by Elsevier Ltd.)

Background: Emerging studies have associated low greenspace and high air pollution exposure with risk of child attention deficit/hyperactivity disorder (ADHD). Population-based studies are limited, however, and joint effects are rarely evaluated. We investigated associations of ADHD incidence with greenspace, air pollution, and noise in a population-based birth cohort., Methods: We assembled a cohort from administrative data of births from 2000 to 2001 (N ∼ 37,000) in Metro Vancouver, Canada. ADHD was identified by hospital records, physician visits, and prescriptions. Cox proportional hazards models were applied to assess associations between environmental exposures and ADHD incidence adjusting for available covariates. Greenspace was estimated using vegetation percentage derived from linear spectral unmixing of Landsat imagery. Fine particulate matter (PM 2.5 ) and nitrogen dioxide (NO 2 ) were estimated using land use regression models; noise was estimated using a deterministic model. Exposure period was from birth until the age of three. Joint effects of greenspace and PM 2.5 were analysed in two-exposure models and by categorizing values into quintiles., Results: During seven-year follow-up, 1217 ADHD cases were diagnosed. Greenspace was associated with lower incidence of ADHD (hazard ratio, HR: 0.90 [0.81-0.99] per interquartile range increment), while PM 2.5 was associated with increased incidence (HR: 1.11 [1.06-1.17] per interquartile range increment). NO 2 (HR: 1.01 [0.96, 1.07]) and noise (HR: 1.00 [0.95, 1.05]) were not associated with ADHD. There was a 50% decrease in the HR for ADHD in locations with the lowest PM 2.5 and highest greenspace exposure, compared to a 62% increase in HR in locations with the highest PM 2.5 and lowest greenspace exposure. Effects of PM 2.5 were attenuated by greenspace in two-exposure models., Conclusions: We found evidence suggesting environmental inequalities where children living in greener neighborhoods with low air pollution had substantially lower risk of ADHD compared to those with higher air pollution and lower greenspace exposure., (Copyright © 2022. Published by Elsevier Ltd.)

Background: Over the last decade, several studies have reported that residential proximity to vegetation, or 'greenness', is associated with improved birth outcomes, including for term birth weight (TBW), preterm birth (PTB), and small for gestational age (SGA). However, there remain several uncertainties about these possible benefits including the role of air pollution, and the extent to they are influenced socioeconomic status., Methods: We addressed these gaps using a national population-based study of 2.2 million singleton live births in Canadian metropolitan areas between 1999 and 2008. Exposures to greenness, fine particulate matter (PM 2.5 ), and nitrogen dioxide (NO 2 ) were assigned to infants using the postal code of their mother's residence at the time of birth. The Normalized Difference Vegetation Index (NDVI) was used to characterize greenness, while estimates of ambient PM 2.5 and NO 2 were estimated using remote sensing, and a national land-use regression surface, respectively. Multivariable regression analysis was performed to describe associations between residential greenness and the birth outcomes. Stratified analyses explored whether these associations were modified by neighbourhood measures of socioeconomic status., Results: Mothers who lived in greener areas had a lower risk of low TBW, PTB, and SGA babies. These associations persisted after adjustment for ambient NO 2 and PM 2.5. Specifically, in fully adjusted models, an interquartile range (IQR = 0.16) increase in the NDVI within a residential buffer of 250 m yielded odds ratios of 0.93 (95% confidence interval (CI): 0.92, 0.94), 0.94 (95% CI: 0.92, 0.95), and 0.94 (95% CI: 0.93, 0.95) for the outcomes of PTB, low TBW, and SGA, respectively. Similarly, an IQR increase in greenness was associated with a 16.3 g (95% CI: 15.3, 17.4) increase in TBW. We found inverse associations between greenness and the occurrence of adverse birth outcomes regardless of the socioeconomic status of the neighbourhood., Interpretation: Our findings support the hypothesis that residential greenness contributes to healthier pregnancies, that these associations are independent from exposure to air pollution. , and that proximity to greenness benefits all mothers regardless of socioeconomic status., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Objective tracking of asthma medication use and exposure in real-time and space has not been feasible previously. Exposure assessments have typically been tied to residential locations, which ignore exposure within patterns of daily activities., Methods: We investigated the associations of exposure to multiple air pollutants, derived from nearest air quality monitors, with space-time asthma rescue inhaler use captured by digital sensors, in Jefferson County, Kentucky. A generalized linear mixed model, capable of accounting for repeated measures, over-dispersion and excessive zeros, was used in our analysis. A secondary analysis was done through the random forest machine learning technique., Results: The 1039 participants enrolled were 63.4% female, 77.3% adult (>18) and 46.8% White. Digital sensors monitored the time and location of over 286 980 asthma rescue medication uses and associated air pollution exposures over 193 697 patient-days, creating a rich spatiotemporal dataset of over 10 905 240 data elements. In the generalized linear mixed model, an interquartile range (IQR) increase in pollutant exposure was associated with a mean rescue medication use increase per person per day of 0.201 [95% confidence interval (CI): 0.189-0.214], 0.153 (95% CI: 0.136-0.171), 0.131 (95% CI: 0.115-0.147) and 0.113 (95% CI: 0.097-0.129), for sulphur dioxide (SO2), nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3), respectively. Similar effect sizes were identified with the random forest model. Time-lagged exposure effects of 0-3 days were observed., Conclusions: Daily exposure to multiple pollutants was associated with increases in daily asthma rescue medication use for same day and lagged exposures up to 3 days. Associations were consistent when evaluated with the random forest modelling approach., (© The Author(s) 2021; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

The inorganic components of particulate matter (PM), especially transition metals, have been shown to contribute to PM toxicity. In this study, the spatial distribution of PM elements and their potential sources in the Greater Los Angeles area were studied. The mass concentration and detailed elemental composition of fine (PM 2.5 ) and coarse (PM 2.5-10 ) particles were assessed at 46 locations, including urban traffic, urban community, urban background, and desert locations. Crustal enrichment factors (EFs), roadside enrichments (REs), and bivariate correlation analysis revealed that Ba, Cr, Cu, Mo, Pd, Sb, Zn, and Zr were associated with traffic emissions in both PM 2.5 and PM 2.5-10 , while Fe, Li, Mn, and Ti were affected by traffic emissions mostly in PM 2.5 . The concentrations of Ba, Cu, Mo, Sb, Zr (brake wear tracers), Pd (tailpipe tracer), and Zn (associated with tire wear) were higher at urban traffic sites than urban background locations by factors of 2.6-4.6. Both PM 2.5 and PM 2.5-10 elements showed large spatial variations, indicating the presence of diverse emission sources across sampling locations. Principal component analysis extracted four source factors that explained 88% of the variance in the PM 2.5 elemental concentrations, and three sources that explained 86% of the variance in the PM 2.5-10 elemental concentrations. Based on multiple linear regression analysis, the contribution of traffic emissions (27%) to PM 2.5 was found to be higher than mineral dust (23%), marine aerosol (18%), and industrial emissions (8%). On the other hand, mineral dust was the dominant source of PM 2.5-10 with 45% contribution, followed by marine aerosol (22%), and traffic emissions (19%). This study provides novel insight into the spatial variation of traffic-related elements in a large metropolitan area., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Exposure to greenspace is associated with improved childhood development, but the pathways behind this relationship are insufficiently understood. Therefore, we aimed to investigate the association between lifetime residential exposure to greenspace and early childhood development and evaluate the extent to which this association is mediated by reductions in traffic-related air pollution and noise., Methods: This population-based birth cohort study comprised singleton births in Metro Vancouver, BC, Canada, between April 1, 2000, and Dec 31, 2005. Children and mothers had to be registered with the mandatory provincial health insurance programme, Medical Services Plan, and have lived within the study area from the child's birth to the time of outcome assessment. Early childhood development was assessed via teacher ratings on the Early Development Instrument (EDI), and we used the total EDI score as the primary outcome variable. We estimated greenspace using percentage vegetation derived from spectral unmixing of annual Landsat satellite image composites. Lifetime residential exposure to greenspace was estimated as the mean of annual percentage vegetation values within 250 m of participants' residential postal codes. Multilevel modelling, adjusted for eight covariates, was used to investigate associations between greenspace exposure and EDI scores. We estimated the mediation effects of nitrogen dioxide (NO 2 ), fine particulate matter (PM 2·5 ), and noise levels using causal mediation analyses., Findings: Of the 37 745 children born in Metro Vancouver between April 1, 2000, and Dec 31, 2005, 27 372 were included in our final study sample. In the adjusted model, 1 IQR increase in percentage vegetation was associated with a 0·16 (95% CI 0·04-0·28; p=0·0073) increase in total EDI score, indicating small improvements in early childhood development. We estimated that 97·1% (95% CI 43·0-396·0), 29·5% (12·0-117·0), and 35·2% (17·9-139·0) of the association was mediated through reductions in NO 2 , PM 2·5 , and noise, respectively., Interpretation: Increased exposure to residential greenspace might improve childhood development by reducing the adverse developmental effects of traffic-related exposures, especially NO 2 air pollution. Our study supports the implementation of healthy urban planning and green infrastructure interventions., Funding: Canadian Institutes of Health Research., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Type 2 diabetes is a leading contributor to the global burden of morbidity and mortality. Ozone ( O 3 ) exposure has previously been linked to diabetes., Objective: We studied the impact of O 3 exposure on incident diabetes risk in elderly Mexican Americans and investigated whether outdoor physical activity modifies the association., Methods: We selected 1,090 Mexican American participants from the Sacramento Area Latino Study on Aging conducted from 1998 to 2007. Ambient O 3 exposure levels were modeled with a land-use regression built with saturation monitoring data collected at 49 sites across the Sacramento metropolitan area. Using Cox proportional hazard models, we estimated the risk of developing incident diabetes based on average O 3 exposure modeled for 5-y prior to incident diabetes diagnosis or last follow-up. Further, we estimated outdoor leisure-time physical activity at baseline and investigated whether higher vs. lower levels modified the association between O 3 exposure and diabetes., Results: In total, 186 incident diabetes cases were identified during 10-y follow-up. Higher levels of physical activity were negatively associated with incident diabetes [ hazard ratio  ( HR ) = 0.64 (95% CI: 0.43, 0.95)]. The estimated HRs for incident diabetes was 1.13 (95% CI: 1.00, 1.28) per 10-ppb increment of 5-y average O 3 exposure; also, this association was stronger among those physically active outdoors [ HR = 1.52 (95% CI: 1.21, 1.90)], and close to null for those reporting lower levels of outdoor activity [ HR = 1.04 (95% CI: 0.90, 1.20), p interaction = 0.01 ]., Conclusions: Our findings suggest that ambient O 3 exposure contributes to the development of type 2 diabetes, particularly among those with higher levels of leisure-time outdoor physical activity. Policies and strategies are needed to reduce O 3 exposure to guarantee that the health benefits of physical activity are not diminished by higher levels of O 3 pollution in susceptible populations such as older Hispanics. https://doi.org/10.1289/EHP8620.

Poor air quality affects the health and wellbeing of large populations around the globe. Although source controls are the most effective approaches for improving air quality and reducing health risks, individuals can also take actions to reduce their personal exposure by staying indoors, reducing physical activity, altering modes of transportation, filtering indoor air, and using respirators and other types of face masks. A synthesis of available evidence on the efficacy, effectiveness, and potential adverse effects or unintended consequences of personal interventions for air pollution is needed by clinicians to assist patients and the public in making informed decisions about use of these interventions. To address this need, the American Thoracic Society convened a workshop in May of 2018 to bring together a multidisciplinary group of international experts to review the current state of knowledge about personal interventions for air pollution and important considerations when helping patients and the general public to make decisions about how best to protect themselves. From these discussions, recommendations were made regarding when, where, how, and for whom to consider personal interventions. In addition to the efficacy and safety of the various interventions, the committee considered evidence regarding the identification of patients at greatest risk, the reliability of air quality indices, the communication challenges, and the ethical and equity considerations that arise when discussing personal interventions to reduce exposure and risk from outdoor air pollution.

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.)

Study Question: To what extent are ambient concentrations of particulate matter <2.5 microns (PM2.5), nitrogen dioxide (NO2) and ozone (O3) associated with risk of self-reported physician-diagnosed uterine leiomyomata (UL)?, Summary Answer: In this large prospective cohort study of Black women, ambient concentrations of O3, but not PM2.5 or NO2, were associated with increased risk of UL., What Is Known Already: UL are benign tumors of the myometrium that are the leading cause of gynecologic inpatient care among reproductive-aged women. Black women are clinically diagnosed at two to three times the rate of white women and tend to exhibit earlier onset and more severe disease. Two epidemiologic studies have found positive associations between air pollution exposure and UL risk, but neither included large numbers of Black women., Study Design, Size, Duration: We conducted a prospective cohort study of 21 998 premenopausal Black women residing in 56 US metropolitan areas from 1997 to 2011., Participants/material, Setting, Methods: Women reported incident UL diagnosis and method of confirmation (i.e. ultrasound, surgery) on biennial follow-up questionnaires. We modeled annual residential concentrations of PM2.5, NO2 and O3 throughout the study period. We used Cox proportional hazards regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for a one-interquartile range (IQR) increase in air pollutant concentrations, adjusting for confounders and co-pollutants., Main Results and the Role of Chance: During 196 685 person-years of follow-up, 6238 participants (28.4%) reported physician-diagnosed UL confirmed by ultrasound or surgery. Although concentrations of PM2.5 and NO2 were not appreciably associated with UL (HRs for a one-IQR increase: 1.01 (95% CI: 0.93, 1.10) and 1.05 (95% CI: 0.95, 1.16), respectively), O3 concentrations were associated with increased UL risk (HR for a one-IQR increase: 1.19, 95% CI: 1.07, 1.32). The association was stronger among women age <35 years (HR: 1.26, 95% CI: 0.98, 1.62) and parous women (HR: 1.28, 95% CI: 1.11, 1.48)., Limitations, Reasons for Caution: Our measurement of air pollution is subject to misclassification, as monitoring data are not equally spatially distributed and we did not account for time-activity patterns. Our outcome measure was based on self-report of a physician diagnosis, likely resulting in under-ascertainment of UL. Although we controlled for several individual- and neighborhood-level confounding variables, residual confounding remains a possibility., Wider Implications of the Findings: Inequitable burden of air pollution exposure has important implications for racial health disparities, and may be related to disparities in UL. Our results emphasize the need for additional research focused on environmental causes of UL., Study Funding/competing Interest(s): This research was funded by the National Cancer Institute (U01-CAA164974) and the National Institute of Environmental Health Sciences (R01-ES019573). L.A.W. is a fibroid consultant for AbbVie, Inc. and accepts in-kind donations from Swiss Precision Diagnostics, Sandstone Diagnostics, FertilityFriend.com and Kindara.com for primary data collection in Pregnancy Study Online (PRESTO). M.J. declares consultancy fees from the Health Effects Institute (as a member of the review committee). The remaining authors declare they have no actual or potential competing financial interests., Trial Registration Number: N/A., (© The Author(s) 2021. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Physical activity can be affected by both meteorological conditions and surrounding greenness, but few studies have evaluated the effects of these environmental factors on physical activity simultaneously. This multi-city comparative study aimed to assess the synergetic effects of apparent temperature and surrounding greenness on physical activity in four European cities. Specifically, we aimed to identify an interaction between surrounding greenness and apparent temperature in the effects on physical activity., Methods: Data were collected from 352 adult residents of Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands), and Kaunas (Lithuania) as part of the PHENOTYPE study. Participants wore a smartphone for seven consecutive days between May-December 2013 and provided additional sociodemographic survey data. Hourly average physical activity (Metabolic Equivalent of Task (MET)) and surrounding greenness (NDVI) were derived from the Calfit mobile application collecting accelerometer and location data. Hourly apparent temperature was calculated from temperature and relative humidity, which were obtained from local meteorological stations along with other meteorological covariates (rainfall, windspeed, and sky darkness). We assessed the interaction effects of apparent temperature and surrounding greenness on hourly physical activity for each city using linear mixed models, while adjusting for meteorological, demographic, and time-related variables., Results: We found significant interactions between apparent temperature and surrounding greenness on hourly physical activity in three of four cities, aside from the coastal city of Barcelona. Significant quadratic effects of apparent temperature were found in the highest level of surrounding greenness for Stoke-on-Trent and Doetinchem, with 4% decrease in median MET observed for a 10°C departure from optimal temperature (15.2°C and 14.6°C, respectively). Significant linear effects were found for higher levels of surrounding greenness in Kaunas, whereby an increase of 10°C was associated with ∼4% increase in median MET., Conclusion: Apparent temperature and surrounding greenness interacted in the effect on hourly physical activity across three of four European cities, with varying effect between cities. While quadratic effects of temperature suggest diminishing levels of physical activity in the highest greenness levels in cities of temperate climates, the variation in surrounding greenness between cities could be further explored, particularly by looking at indoor-outdoor locations. The study findings support the need for evidence-based physical activity promotion and urban design., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Several studies have assessed the relationship between exposure to natural environments (NEs) and childhood mental health and development. In most cases, a positive association has been found, but results are inconsistent, and the strength of association is unclear. This inconsistency may reflect the heterogeneity in measurements used to assess NE., Objectives: This systematic review aims to identify the most common NE metrics used in childhood mental health and development research. Our second aim is to identify the metrics that are most consistently associated with health and assess the relative strength of association depending on type of NE exposure measurement, in terms of metric used (i.e., measurement technique, such as remote sensing), but also rate (i.e., spatial and temporal exposure)., Methods: We used the PRISMA protocol to identify eligible studies, following a set of pre-defined inclusion criteria based on the PECOS strategy. A number of keywords were used for retrieving relevant articles from Medline, Embase, PsychINFO, and Web of Science databases between January 2000-November 2020. From these, we extracted data on type of NE measurement and relative association to a number of indicators of childhood mental health and development. We conducted a systematic assessment of quality and risk of bias in the included articles to evaluate the level of evidence. Case studies and qualitative studies were excluded., Results: After screening of title (283 studies included), abstract, and full article, 45 studies were included in our review. A majority of which were conducted in North America and Europe (n = 36; 80%). The majority of studies used land use or land covers (LULC, n = 24; 35%) to determine exposures to NEs. Other metrics included the normalized difference vegetation index (NDVI), expert measures (e.g., surveys of data collection done by experts), surveys (e.g., self-reported assessments), and use of NE (e.g., measures of a participant's use of NE such as through GPS tracts or parent reports). Rate was most commonly determined by buffer zones around residential addresses or postal codes. The most consistent association to health outcomes was found for buffers of 100 m, 250 m, 500 m, and within polygons boundaries (e.g., census tracts). Six health categories, academic achievement, prevalence of doctor diagnosed disorders, emotional and behavioral functioning, well-being, social functioning, and cognitive skills, were created post hoc. We found sufficient evidence between NDVI (Landsat) and emotional and behavioral well-being. Additionally, we found limited evidence between LULC datasets and academic achievement; use of NE, parent/guardian reported greenness, and expert measures of greenness and emotional and behavioral functioning; and use of NE and social functioning., Discussion: This review demonstrates that several NE measurements must be evaluated further before sufficient evidence for a potential association between distinct NE exposure metrics and childhood mental health and development can be established. Further, we suggest increased coordination between research efforts, for example, by replication of studies and comparing different NE measurements systematically, so that effect sizes can be confirmed for various health outcomes. Finally, we recommend implementing research designs that assess underlying pathways of nature-health relations and utilize measurement techniques that adequately assess exposure, access, use, and perception of NEs in order to contribute to a better understanding of health impacts of surrounding natural environments., (Copyright © 2021 Elsevier GmbH. All rights reserved.)

Background: Exposure to fine particulate (PM2.5) air pollution is associated with increased cardiovascular disease (CVD), but less is known about its specific components, such as metals originating from non-tailpipe emissions. We investigated the associations of long-term exposure to metal components [iron (Fe) and copper (Cu)] in PM2.5 with CVD incidence., Methods: We conducted a population-based cohort study in Toronto, Canada. Exposures to Fe and Cu in PM2.5 and their combined impact on the concentration of reactive oxygen species (ROS) in lung fluid were estimated using land use regression models. Incidence of acute myocardial infarction (AMI), congestive heart failure (CHF) and CVD death was ascertained using health administrative datasets. We used mixed-effects Cox regression models to examine the associations between the exposures and health outcomes. A series of sensitivity analyses were conducted, including indirect adjustment for individual-level cardiovascular risk factors (e.g. smoking), and adjustment for PM2.5 and nitrogen dioxide (NO2)., Results: In single-pollutant models, we found positive associations between the three exposures and all three outcomes, with the strongest associations detected for the estimated ROS. The associations of AMI and CHF were sensitive to indirect adjustment, but remained robust for CVD death in all sensitivity analyses. In multi-pollutant models, the associations of the three exposures generally remained unaltered. Interestingly, adjustment for ROS did not substantially change the associations between PM2.5 and CVD, but attenuated the associations of NO2., Conclusions: Long-term exposure to Fe and Cu in PM2.5 and their combined impact on ROS were consistently associated with increased CVD death., (© The Author(s) 2020; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Introduction: In 2006, the California Air Resources Board (CARB) and local air quality management districts implemented an Emission Reduction Plan for Ports and Goods Movement program (referred to hereinafter as GM policy actions) (CARB 2006). The GM policy actions comprise approximately 200 actions with an estimated investment value of $6 to $10 billion. These actions targeted the major sources and polluters related to goods movements, such as highways; ports and railyard trucks; ship fuel and shore power; cargo equipment; and locomotives. These actions aimed to reduce total statewide domestic GM emissions to 2001 levels or lower by the year 2010; to reduce the statewide diesel particulate matter (DPM) health risk from GM by 85% by the year 2020; and to reduce the nitrogen oxides (NO x ) emissions from international GM in the South Coast Air Basin by 30% from projected 2015 levels and 50% from projected 2020 levels. The years 2006 and 2007 marked an important milestone in starting to regulate GM polluters and adopting stricter standards for traffic-related air pollution., This project aimed to examine the impact of the GM policy actions on reductions in ambient air pollution and subsequent improvements in health outcomes of Medi-Cal fee-for-service (FFS) beneficiaries with chronic conditions in 10 counties in California. Specifically, we examined whether the GM policy actions reduced air pollution near GMC corridors more than in control areas. We subsequently assessed whether there were greater decreases in emergency room (ER) visits and hospitalizations for enrollees with chronic conditions who lived in the GM corridors (GMCs) than for those who lived in other areas., Methods: The study used a quasi-experimental design. We defined areas within 500 m of truck-permitted freeways and ports as GMCs. We further defined non-goods movement corridors (NGMCs) as locations within 500 m of truck-prohibited freeways or 300 m of a connecting roadway, and areas out of GMCs and NGMCs as controls (CTRLs). We defined years 2004-2007 as the pre-policy period and years 2008-2010 as the post-policy period. We developed linear mixed-effects land use regression models and created annual air pollution surfaces for nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), and ozone (O 3 ) across California for years 2004-2010 at a spatial resolution of 30 m, then assigned them to enrollees' home addresses., We used a retrospective cohort of 23,000 California Medicaid (Medi-Cal) FFS adult beneficiaries living in 10 California counties with six years of data (September 1, 2004, to August 31, 2010). Cohort beneficiaries had at least one of four chronic conditions, including asthma, chronic obstructive pulmonary disease (COPD), diabetes, and heart disease., We used a difference-in-differences (DiD) model to assess whether air pollutant concentration and health care utilization (ER visits and hospitalizations) for cohort beneficiaries declined more for those living in intervention corridors (GMCs, NGMCs) than those living in CTRLs. All the models controlled for age, sex, language spoken, race/ethnicity, number of comorbidities in baseline years, county, time-varying health indicator variables, and several neighborhood variables., To facilitate interpretation, we calculated the DiD estimates in each of the three years after the policy intervention. The DiD was used to assess the causal impact of regulatory policy on reductions of air pollution, as well as for the improvements in health outcomes., We explored whether improvements in health outcomes were due to the air pollution reduction by using a multi- level mediation model, in which the effect of GM actions on health outcomes was mediated through the effect of actual air pollution reductions in the post-policy years. We used the Generalized Structural Equation Models for the estimation and combined the effects of NO 2 and PM 2.5 in the model. To further verify the causal inferences of the GM actions on reductions of exposures and improvements in health outcomes, we performed sensitivity analyses with propensity score weighting., Results: We observed statistically significant reductions in pollutant NO 2 and PM 2.5 concentrations for enrollees in all 10 counties. The enrollees in GMCs experienced greater reductions in NO 2 and PM 2.5 from the pre- to the post-policy periods than those in CTRLs. Greater reductions were also observed among beneficiaries living in NGMCs versus those in CTRLs, but those reductions were smaller than among beneficiaries living in GMCs. For O 3 concentrations, an opposite trend was observed., Furthermore, we observed significantly greater reductions in ER visits for patients with asthma and COPD living in GMCs than those in CTRLS in the post-policy years. For example, we saw in the DiD modeling results there were 170 fewer ER visits for 1,000 beneficiaries with asthma per year in GMCs if the regionwide trend in the CTRL group was considered not related to the GM policy. Similarly, among the beneficiaries with COPD, there were 180 fewer ER visits per 1,000 patients estimated in the GMCs for the third year after the implementation of the policy., We also observed greater reductions in ER visits among those with asthma, when comparing NGMCs with CTRLs, but reductions were smaller than comparisons between GMCs and CTRLs. The ER visits for those with COPD, diabetes, and the total sample in NGMCs also had downward trends in the post-policy year in comparison with those in CTRLs but the differences were not statistically significant; similar phenomena were also observed for the ER visits among those with diabetes and heart diseases and in the total sample when GMCs versus CTRLs and GMCs versus NGMCs were compared. Although hospitalizations also decreased more in GMCs than in NGMCs and more in NGMCs than in CTRLs in the post-policy period, results were not statistically significant., Using the mediation models, we observed 0.129 more reductions in the expected number of ER visits among individuals with asthma for a composite reduction in one unit NO 2 and one unit PM 2.5 (DiD = -0.129, P < 0.05) from the pre-policy years to the post-policy years. The reductions in NO 2 and PM 2.5 due to policy change estimated by the mediation model are essentially the same as shown in the respective DiD models. Mediation analyses suggested that the effects of GM policy interventions on health improvements were largely due to exposure reductions. Finally, sensitivity analyses with propensity scores produced similar DiD results., Conclusions: This project has produced empirical evidence that air pollution control actions reduced pollution exposures among disadvantaged and susceptible populations. More importantly, our findings suggest that the reductions in air pollution led to health outcome improvements among low-income people with chronic conditions. Our investigation also contributed to scientific methods for assessing the health effects of long-term, large-scale, and complex regulatory actions with routinely collected pollutants and medical claims data. Therefore, the results strongly support both short-term and long-term efforts to improve air quality for all members of society and future studies on the impact of air pollution control policies., (© 2021 Health Effects Institute. All rights reserved.)

This review highlights the importance of air quality in the African urban development process. We address connections between air pollution and ( a ) rapid urbanization, ( b ) social problems, ( c ) health impacts, ( d ) climate change, ( e ) policies, and ( f ) new innovations. We acknowledge that air pollution levels in Africa can be extremely high and a serious health threat. The toxic content of the pollution could relate to region-specific sources such as low standards for vehicles and fuels, cooking with solid fuels, and burning household waste. We implore the pursuit of interdisciplinary research to create new approaches with relevant stakeholders. Moreover, successful air pollution research must regard conflicts, tensions, and synergies inherent to development processes in African municipalities, regions, and countries. This includes global relationships regarding climate change, trade, urban planning, and transportation. Incorporating aspects of local political situations (e.g., democracy) can also enhance greater political accountability and awareness about air pollution.

Metal components in fine particulate matter (PM 2.5 ) from nontailpipe emissions may play an important role in underlying the adverse respiratory effects of PM 2.5 . We investigated the associations between long-term exposure to iron (Fe) and copper (Cu) in PM 2.5 and their combined impact on reactive oxygen species (ROS) generation in human lungs, and the incidence of asthma, chronic obstructive pulmonary disease (COPD), COPD mortality, pneumonia mortality, and respiratory mortality. We conducted a population-based cohort study of ∼0.8 million adults in Toronto, Canada. Land-use regression models were used to estimate the concentrations of Fe, Cu, and ROS. Outcomes were ascertained using validated health administrative databases. We found positive associations between long-term exposure to Fe, Cu, and ROS and the risks of all five respiratory outcomes. The associations were more robust for COPD, pneumonia mortality, and respiratory mortality than for asthma incidence and COPD mortality. Stronger associations were observed for ROS than for either Fe or Cu. In two-pollutant models, adjustment for nitrogen dioxide somewhat attenuated the associations while adjustment for PM 2.5 had little influence. Long-term exposure to Fe and Cu in PM 2.5 and estimated ROS concentration in lung fluid was associated with increased incidence of respiratory diseases, suggesting the adverse respiratory effects of nontailpipe emissions.

Fine particulate air pollution <2.5 μm in diameter (PM 2.5 ) is a major environmental threat to global public health. Multiple national and international medical and governmental organizations have recognized PM 2.5 as a risk factor for cardiopulmonary diseases. A growing body of evidence indicates that several personal-level approaches that reduce exposures to PM 2.5 can lead to improvements in health endpoints. Novel and forward-thinking strategies including randomized clinical trials are important to validate key aspects (e.g., feasibility, efficacy, health benefits, risks, burden, costs) of the various protective interventions, in particular among real-world susceptible and vulnerable populations. This paper summarizes the discussions and conclusions from an expert workshop, Reducing the Cardiopulmonary Impact of Particulate Matter Air Pollution in High Risk Populations, held on May 29 to 30, 2019, and convened by the National Institutes of Health, the U.S. Environmental Protection Agency, and the U.S. Centers for Disease Control and Prevention., Competing Interests: Author Disclosures The views expressed in this paper are those of the authors and do not necessarily represent the views of the National Institutes of Health (NIH), National Heart, Lung, and Blood Institute (NHLBI), National Institute of Environmental Health Sciences, Environmental Protection Agency, Centers for Disease Control and Prevention, or the United States Department of Health and Human Services. Drs. Bhatt and Brooks served as co-chairs of this NIH/NHLBI/EPA/CDC Expert Workshop on air pollution. Dr. Newman has received grant support from the NIH (K23HL125991). Dr. Bhatt has served on the advisory board of Cardax, CellProthera, Cereno Scientific, Elsevier Practice Update Cardiology, Level Ex, Medscape Cardiology, PhaseBio, PLx Pharma, and Regado Biosciences; has served on the Board of Directors for Boston VA Research Institute, Society of Cardiovascular Patient Care, and TobeSoft; has served as chair of the American Heart Association Quality Oversight Committee, NCDR-ACTION Registry Steering Committee, and VA CART Research and Publications Committee; has served on the data monitoring committees of Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute, for the PORTICO trial, funded by St. Jude Medical, now Abbott), Cleveland Clinic (including for the ExCEED trial, funded by Edwards), Contego Medical (Chair, PERFORMANCE 2), Duke Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine (for the ENVISAGE trial, funded by Daiichi-Sankyo), and the Population Health Research Institute; has received honoraria from the American College of Cardiology (Senior Associate Editor, Clinical Trials and News, ACC.org; Vice-Chair, ACC Accreditation Committee), Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute; RE-DUAL PCI clinical trial steering committee funded by Boehringer Ingelheim; AEGIS-II executive committee funded by CSL Behring), Belvoir Publications (Editor-in-Chief, Harvard Heart Letter), Duke Clinical Research Institute (clinical trial steering committees, including for the PRONOUNCE trial, funded by Ferring Pharmaceuticals), HMP Global (Editor-in-Chief, Journal of Invasive Cardiology), Journal of the American College of Cardiology (Guest Editor; Associate Editor), K2P (Co-Chair, interdisciplinary curriculum), Level Ex, Medtelligence/ReachMD (CME steering committees), MJH Life Sciences, Population Health Research Institute (for the COMPASS operations committee, publications committee, steering committee, and USA national co-leader, funded by Bayer), Slack Publications (Chief Medical Editor, Cardiology Today’s Intervention), Society of Cardiovascular Patient Care (Secretary/Treasurer), and WebMD (CME steering committees); has served as Deputy Editor of Clinical Cardiology; has received research funding from Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardax, Chiesi, CSL Behring, Eisai, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, Idorsia, Ironwood, Ischemix, Lexicon, Lilly, Medtronic, Pfizer, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic, and The Medicines Company; has received royalties from Elsevier (Editor, Cardiovascular Intervention: A Companion to Braunwald’s Heart Disease); has served as site co-investigator for Biotronik, Boston Scientific, CSI, St. Jude Medical (now Abbott), and Svelte; served as a trustee of the American College of Cardiology; and has received unfunded research from FlowCo, Merck, Novo Nordisk, and Takeda. Dr. Balmes is the Physician Member of the California Air Resources Board. Dr. Brook has received an investigator-initiated grant from RB, Inc.; and has received support from NIH awards 2R01-ES019616 and 2R01-NR014484. Dr. Brauer has received grant support from the Health Effects Institute, the Canadian Institutes of Health Research, The Terry Fox Research Institute, and the Wellcome Trust. Dr. Hansel has received grant support from the NIH, EPA, NHLBI, National Institute of Environmental Health Sciences, COPD Foundation, and Boehringer Ingelheim; and has participated in advisory boards for GlaxoSmithKline, AstraZeneca, and Mylan. Dr. Hernandez has received research funding from American Regent, AstraZeneca, Boehringer Ingelheim, Merck, Novartis, and Verily; and has served as a consultant for Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Merck, Novartis, and Relypsa. Dr. Hochman has received grant support from the NHLBI for the ISCHEMIA Trial, for which there were in-kind donations for participating sites from Abbott Vascular, Medtronic, Inc., St. Jude Medical, Inc., Volcano Corporation, Arbor Pharmaceuticals, AstraZeneca Pharmaceuticals, Merck Sharp & Dohme Corp., Omron Healthcare, Inc., and Amgen Inc; has received financial donations from Arbor Pharmaceuticals and AstraZeneca Pharmaceuticals; and has served as PI for the ZEDS (Long-term Suppressive Valacyclovir Treatment for Herpes Zoster Ophthalmicus) Study, supported by NIH/National Eye Institute. Dr. Kaufman has received grant support from the National Institutes of Health and the Environmental Protection Agency. Dr. Malik is supported by the NHLBI of the NIH under Award Number T32HL110837. Dr. Peel has received research funding from the NIH (1UM1HL134590 and R01ES023688). Dr. Rajagopalan has received research funding from the NIH; and has served as a consultant to Novo Nordisk, Takeda, GlaxoSmithKline, and AstraZeneca. Dr. Zhang’s research has been partly funded by the NIH, Underwriter’s Laboratory, and Natural Science Foundation of China (via Duke Kunshan University in China). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2020 American College of Cardiology Foundation. All rights reserved.)

Cognitive impairment has been linked to traffic-related air pollution and noise exposure as well as to metabolic syndrome or some of its individual components. Here, we investigate whether the presence of metabolic dysfunction modifies associations between air pollution or noise exposures and incident dementia or cognitive impairment without dementia (CIND)., Methods: For 1,612 elderly Mexican-American participants of the Sacramento Area Latino Study on Aging (SALSA) followed for up to 10 years, we estimated residential-based local traffic-related exposures relying on the California Line Source Dispersion Model version 4 (CALINE4) for nitrogen oxides (NOx) and the SoundPLAN software package (Version 8.0; NAVCON, Fullerton, CA) that implements the Federal Highway Administration Traffic Noise Model (TNM) for noise, respectively. We used Cox proportional hazard models to estimate the joint effects of NOx or noise exposures and obesity, hyperglycemia, or low high-density lipoprotein (HDL) cholesterol., Results: The risk of developing dementia/CIND among participants with hyperglycemia who also were exposed to high levels of NOx (≥3.44 parts per billion [ppb] [75th percentile]) or noise (≥65 dB) was 2.4 (1.4, 4.0) and 2.2 (1.7, 3.9), respectively. For participants with low HDL-cholesterol, the estimated hazard ratios for dementia/CIND were 2.5 (1.4, 4.3) and 1.8 (1.0, 3.0) for those also exposed to high levels of NOx (≥3.44 ppb) or noise (≥65 dB), respectively, compared with those without metabolic dysfunction exposed to low traffic-related air pollution or noise levels., Conclusions: Exposure to traffic-related air pollution or noise most strongly increases the risk of dementia/CIND among older Mexican-Americans living in California who also exhibit hyperglycemia or low HDL-cholesterol., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report. This work was supported by grants R01ES023451 from National Institute of Environmental Health Sciences, AG012975, AG033751 and AG053410 from National Institute on Aging, and DK060753 from National Institute of Diabetes and Digestive and Kidney Diseases. The data for these cohorts are available on the server of Inter-university Consortium for Political and Social Research (ICPSR) at University of Michigan and the exposure data will be available upon request to the authors. The analytical code used was standard SAS code (e.g., data steps, proc phreg).Sponsorships or competing interests that may be relevant to content are disclosed at the end of the article., (Copyright © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Background: Recently, it has been suggested that environmental exposures from traffic sources including noise may play a role in cognitive impairment in the elderly. The objective of the study was to investigate the association between local traffic-related noise pollution and incident dementia or cognitive impairment without dementia (CIND) during a 10-year follow-up period., Methods: 1612 Mexican-American participants from the Sacramento Area Latino Study on Aging (SALSA) were followed every 12-15 months via home visits from 1998 to 2007. We used the SoundPLAN software package to estimate noise originating from local traffic with the input of Annual Average Daily Traffic (AADT) data from Metropolitan Planning Organizations (MPO) based on geocoded residential addresses at baseline (1998-1999). We estimated the risks of incident dementia or CIND from 24-hour and nighttime noise exposure using Cox proportional hazard models., Results: During the follow-up, we identified 159 incident dementia or CIND cases in total. Per 11.6 dB (interquartile range width) increase in 24-hour noise, the hazard of developing dementia or CIND increased (hazard ratio = 1.3 [1.0, 1.6]) during follow-up; estimates were slightly lower (hazard ratio = 1.2 [0.97, 1.6]) when adjusting for modeled local air pollution exposure from traffic sources. Overall, the risk of dementia/CIND was elevated when 24-hour and nighttime noise were higher than 75 and 65 dB respectively. See video Abstract: http://links.lww.com/EDE/B728., Conclusions: In our study, traffic-related noise exposure was associated with increased risk of dementia or CIND in elderly Mexican-Americans. Future studies taking into account other noise sources and occupational noise exposure before retirement are needed., Competing Interests: The authors report no conflicts of interest., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Over the past decade, researchers and policy-makers have become increasingly interested in regulatory and policy interventions to reduce air pollution concentrations and improve human health. Studies have typically relied on relatively sparse environmental monitoring data that lack the spatial resolution to assess small-area improvements in air quality and health. Few studies have integrated multiple types of measures of an air pollutant into one single modeling framework that combines spatially- and temporally-rich monitoring data. In this paper, we investigated the differential effects of California emissions reduction plan on reducing air pollution between those living in the goods movement corridors (GMC) that are within 500 m of major highways that serve as truck routes to those farther away or adjacent to routes that prohibit trucks. A mixed effects Deletion/Substitution/Addition (D/S/A) machine learning algorithm was developed to model annual pollutant concentrations of nitrogen dioxide (NO 2 ) by taking repeated measures into consideration and by integrating multiple types of NO 2 measurements, including those through government regulatory and research-oriented saturation monitoring into a single modeling framework. Difference-in-difference analysis was conducted to identify whether those living in GMC demonstrated statistically larger reductions in air pollution exposure. The mixed effects D/S/A machine learning modeling result indicated that GMC had 2 ppb greater reductions in NO 2 concentrations from pre- to post-policy period than far away areas. The difference-in-difference analysis demonstrated that the subjects living in GMC experienced statistically significant greater reductions in NO 2 exposure than those living in the far away areas. This study contributes to scientific knowledge by providing empirical evidence that improvements in air quality via the emissions reductions plan policies impacted traffic-related air pollutant concentrations and associated exposures most among low-income Californians with chronic conditions living in GMC. The identified differences in pollutant reductions across different location domains may be applicable to other states or other countries if similar policies are enacted., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Epidemiological evidence for the association between traffic-related noise and the incidence of major cardiovascular events such as acute myocardial infarction (AMI) and congestive heart failure (CHF) is inconclusive, especially in North America., Objectives: We evaluated the associations between long-term exposure to road traffic noise and the incidence of AMI and CHF., Methods: Our study population comprised ∼ 1  million people 30-100 years of age who lived in Toronto, Canada, from 2001 to 2015 and were free of AMI (referred to as the AMI cohort) or CHF (the CHF cohort) at baseline. Outcomes were ascertained from health administrative databases using validated algorithms. Annual average noise levels were estimated as the A-weighted equivalent sound pressure level over the 24-h period (LAeq24) and during nighttime (LAeqNight), respectively, using propagation modeling, and assigned to participants' annual six-digit postal code addresses during follow-up. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for incident AMI and CHF in relation to LAeq24 and LAeqNight using random-effects Cox proportional hazards models adjusting for individual- and census tract-level covariates, including traffic-related air pollutants [e.g., ultrafine particles (UFPs) and nitrogen dioxide]., Results: During follow-up, there were 37,441 AMI incident cases and 95,138 CHF incident cases. Each interquartile range change in LAeq24 was associated with an increased risk of incident AMI ( HR = 1.07 ; 95% CI: 1.06, 1.08) and CHF ( HR = 1.07 ; 95% CI: 1.06, 1.09). Similarly, LAeqNight was associated with incident AMI ( HR = 1.07 ; 95% CI: 1.05, 1.08) and CHF ( HR = 1.06 ; 95% CI: 1.05, 1.07). These results were robust to various sensitivity analyses and remained elevated after controlling for long-term exposure to UFPs and nitrogen dioxide. We found near-linear relationships between noise and the incidence of AMI and CHF with no evidence of threshold values., Conclusion: In this large cohort study in Toronto, Canada, chronic exposure to road traffic noise was associated with elevated risks for AMI and CHF incidence. https://doi.org/10.1289/EHP5809.