Research report (Health Effects Institute)最新文献

{"title":"Chemical and Cellular Formation of Reactive Oxygen Species from Secondary Organic Aerosols in Epithelial Lining Fluid.","authors":"M Shiraiwa, T Fang, J Wei, Psj Lakey, Bch Hwang, K C Edwards, S Kapur, Jem Mena, Y-K Huang, M A Digman, S A Weichenthal, S Nizkorodov, M T Kleinman","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Oxidative stress mediated by reactive oxygen species (ROS) is a key process for adverse aerosol health effects. Secondary organic aerosols (SOA) account for a major fraction of particulate matter with aerodynamic diameter ≤2.5 µm (PM<sub>2.5</sub>). PM<sub>2.5</sub> inhalation and deposition into the respiratory tract causes the formation of ROS by chemical reactions and phagocytosis of macrophages in the epithelial lining fluid (ELF), but their relative contributions are not well quantified and their link to oxidative stress remains uncertain. The specific aims of this project were (1) elucidating the chemical mechanism and quantifying the formation kinetics of ROS in the ELF by SOA; (2) quantifying the relative importance of ROS formation by chemical reactions and macrophages in the ELF.</p><p><strong>Methods: </strong>SOA particles were generated using reaction chambers from oxidation of various precursors including isoprene, terpenes, and aromatic compounds with or without nitrogen oxides (NO<sub>x</sub>). We collected size-segregated PM at two highway sites in Anaheim, CA, and Long Beach, CA, and at an urban site in Irvine, CA, during two wildfire events. The collected particles were extracted into water or surrogate ELF that contained lung antioxidants. ROS generation was quantified using electron paramagnetic resonance (EPR) spectroscopy with a spin-trapping technique. PM oxidative potential (OP) was also quantified using the dithiothreitol assay. In addition, kinetic modeling was applied for analysis and interpretation of experimental data. Finally, we quantified cellular superoxide release by RAW264.7 macrophage cells upon exposure to quinones and isoprene SOA using a chemiluminescence assay as calibrated with an EPR spin-probing technique. We also applied cellular imaging techniques to study the cellular mechanism of superoxide release and oxidative damage on cell membranes.</p><p><strong>Results: </strong>Superoxide radicals (·O<sub>2</sub><sup>-</sup>) were formed from aqueous reactions of biogenic SOA generated by hydroxy radical (·OH) photooxidation of isoprene, β-pinene, α-terpineol, and d-limonene. The temporal evolution of ·OH and ·O<sub>2</sub><sup>-</sup> formation was elucidated by kinetic modeling with a cascade of aqueous reactions, including the decomposition of organic hydroperoxides (ROOH), ·OH oxidation of primary or secondary alcohols, and unimolecular decomposition of α-hydroxyperoxyl radicals. Relative yields of various types of ROS reflected the relative abundance of ROOH and alcohols contained in SOA, which generated under high NO<sub>x</sub> conditions, exhibited lower ROS yields. ROS formation by SOA was also affected by pH. Isoprene SOA had higher ·OH and organic radical yields at neutral than at acidic pH. At low pH ·O<sub>2</sub><sup>-</sup> was the dominant species generated by all types of SOA. At neutral pH, α-terpineol SOA exhibited a substantial yield of carbon-centered or","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 215","pages":"1-56"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10957138/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139991999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Term Exposure to AIR Pollution and COVID-19 Mortality and Morbidity in DENmark: Who Is Most Susceptible? (AIRCODEN).","authors":"Z J Andersen, J Zhang, Y-H Lim, R So, J T Jørgensen, L H Mortensen, G M Napolitano, T Cole-Hunter, S Loft, S Bhatt, G Hoek, B Brunekreef, Rgj Westendorp, M Ketzel, J Brandt, T Lange, T Kølsen-Fisher","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Early ecological studies have suggested a link between air pollution and Coronavirus Diseases 2019 (COVID-19); however, the evidence from individual-level prospective cohort studies is still sparse. Here, we have examined, in a general population, whether long-term exposure to air pollution is associated with the risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and developing severe COVID-19, resulting in hospitalization or death and who is most susceptible. We also examined whether long-term exposure to air pollution is associated with hospitalization or death due to COVID-19 in those who have tested positive for SARS-CoV-2.</p><p><strong>Methods: </strong>We included all Danish residents 30 years or older who resided in Denmark on March 1, 2020. and followed them in the National COVID-19 Surveillance System until first positive test (incidence), COVID-19 hospitalization, or death until April 26, 2021. We estimated mean levels of nitrogen dioxide (NO<sub>2</sub>), particulate matter with an aerodynamic diameter <2.5 μm (PM<sub>2.5</sub>), black carbon (BC), and ozone (O<sub>3</sub>) at cohort participants' residence in 2019 by the Danish Eulerian Hemispheric Model/Urban Background Model. We used Cox proportional hazard models to estimate the associations of air pollutants with COVID-19 incidence, hospitalization, and mortality adjusting for age, sex, and socioeconomic status (SES) at the individual and area levels. We examined effect modification by age, sex, SES (education, income, wealth, employment), and comorbidities with cardiovascular disease, respiratory disease, acute lower respiratory infections, diabetes, lung cancer, and dementia. We used logistic regression to examine association of air pollutants with COVID-19-related hospitalization or death among SARS-CoV-2 positive patients, adjusting for age, sex, individual- and area-level SES.</p><p><strong>Results: </strong>Of 3,721,810 people, 138,742 were infected, 11,270 hospitalized, and 2,557 died from COVID-19 during 14 months of follow-up. We detected strong positive associations with COVID-19 incidence, with hazard ratio (HR) and 95% confidence interval (CI) of 1.10 (CI: 1.05-1.14) per 0.5-μg/m<sup>3</sup> increase in PM<sub>2.5</sub> and 1.18 (CI: 1.14-1.23) per 3.6-μg/m<sup>3</sup> increase in NO<sub>2</sub>. For COVID-19 hospitalizations and for COVID-19 deaths, corresponding HRs and 95% CIs were 1.09 (CI: 1.01-1.17) and 1.19 (CI: 1.12-1.27), respectively for PM<sub>2.5</sub>, and 1.23 (CI: 1.04-1.44) and 1.18 (CI: 1.03-1.34), respectively for NO<sub>2</sub>. We also found strong positive and statistically significant associations with BC and negative associations with O<sub>3</sub>. Associations were strongest in those aged 65 years old or older, participants with the lowest SES, and patients with chronic cardiovascular, respiratory, metabolic, lung cancer, and neurodegenerative disease. Among 138,742 individuals wh","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 214","pages":"1-41"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10983616/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139577313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ambient Air Pollution and All-Cause and Cause-Specific Mortality in an Analysis of Asian Cohorts.","authors":"G S Downward, R Vermeulen","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Much of what is currently known about the adverse effects of ambient air pollution comes from studies conducted in high-income regions, with relatively low air pollution levels. The aim of the current project is to examine the relationship between exposure to ambient air pollution (as predicted from satellite-based models) and all-cause and cause-specific mortality in several Asian cohorts.</p><p><strong>Methods: </strong>Cohorts were recruited from the Asia Cohort Consortium (ACC). The geocoded residences of participants were assigned levels of ambient particulate material with aerodynamic diameter of 2.5 μm or less (PM_2.5) and nitrogen dioxide (NO₂) utilizing global satellite-derived models and assigned for the year of enrollment (or closest available year). The association between ambient exposure and mortality was established with Cox proportional hazard models, after adjustment for common confounders. Both single- and two-pollutant models were generated. Model robustness was evaluated, and hazard ratios were calculated for each cohort separately and combined via random effect meta-analysis for pooled risk estimates.</p><p><strong>Results: </strong>Six cohort studies from the ACC participated: the Community-based Cancer Screening Program (CBCSCP, Taiwan), the Golestan Cohort Study (Iran), the Health Effects for Arsenic Longitudinal Study (HEALS, Bangladesh), the Japan Public Health Center-based Prospective Study (JPHC), the Korean Multi-center Cancer Cohort Study (KMCC), and the Mumbai Cohort Study (MCS, India). The cohorts represented over 340,000 participants.</p><p><p>Mean exposures to PM_2.5 ranged from 8 to 58 μg/m³. Mean exposures to NO₂ ranged from 7 to 23 ppb. For PM_2.5, a positive, borderline nonsignificant relationship was observed between PM_2.5 and cardiovascular mortality. Other relationships with PM_2.5 tended toward the null in meta-analysis. For NO₂, an overall positive relationship was observed between exposure to NO₂ and all cancers and lung cancer. A borderline association between NO₂ and nonmalignant lung disease was also observed. The findings within individual cohorts remained consistent across a variety of subgroups and alternative analyses, including two-pollutant models.</p><p><strong>Conclusions: </strong>In a pooled examination of cohort studies across Asia, ambient PM_2.5 exposure appears to be associated with an increased risk of cardiovascular mortality and ambient NO₂ exposure is associated with an increased cancer (and lung cancer) mortality. This project has shown that satellite-derived models of pollution can be used in examinations of mortality risk in areas with either incomplete or missing air pollution monitoring.</p>","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 213","pages":"1-53"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266370/pdf/hei-2016-189.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10044499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing Determinants of Near-Road Ambient Air Quality for an Urban Intersection and a Freeway Site.","authors":"H C Frey, A P Grieshop, A Khlystov, J J Bang, N Rouphail, J Guinness, D Rodriguez, M Fuentes, P Saha, H Brantley, M Snyder, S Tanvir, K Ko, T Noussi, M Delavarrafiee, S Singh","doi":"","DOIUrl":"","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Introduction: &lt;/strong&gt;Near-road ambient air pollution concentrations that are affected by vehicle emissions are typically characterized by substantial spatial variability with respect to distance from the roadway and temporal variability based on the time of day, day of week, and season. The goal of this work is to identify variables that explain either temporal or spatial variability based on case studies for a freeway site and an urban intersection site. The key hypothesis is that dispersion modeling of near-road pollutant concentrations could be improved by adding estimates or indices for site-specific explanatory variables, particularly related to traffic. Based on case studies for a freeway site and an urban intersection site, the specific aims of this project are to (1) develop and test regression models that explain variability in traffic-related air pollutant (TRAP) ambient concentration at two near-roadway locations; (2) develop and test refined proxies for land use, traffic, emissions and dispersion; and (3) prioritize inputs according to their ability to explain variability in ambient concentrations to help focus efforts for future data collection and model development.&lt;/p&gt;&lt;p&gt;&lt;p&gt;The key pollutants that are the key focus of this work include nitrogen oxides (NO&lt;sub&gt;x&lt;/sub&gt;), carbon monoxide (CO), black carbon (BC), fine particulate matter (PM&lt;sub&gt;2.5&lt;/sub&gt;; PM ≤ 2.5 μm in aerodynamic diameter), ultrafine particles (UFPs; PM ≤ 0.1 μm in aerodynamic diameter), and ozone (O&lt;sub&gt;3&lt;/sub&gt;). NO&lt;sub&gt;x&lt;/sub&gt;, CO, and BC are tracers of vehicle emissions and dispersion. PM&lt;sub&gt;2.5&lt;/sub&gt; is influenced by vehicle table emissions and regional sources. UFPs are sensitive to primary vehicle emissions. Secondary particles can form near roadways and on regional scales, influencing both PM&lt;sub&gt;2.5&lt;/sub&gt; and UFP concentrations. O&lt;sub&gt;3&lt;/sub&gt; concentrations are influenced by interaction with NO&lt;sub&gt;x&lt;/sub&gt; near the roadway. Nitrogen dioxide (NO&lt;sub&gt;2&lt;/sub&gt;), CO, PM&lt;sub&gt;2.5&lt;/sub&gt;, and O&lt;sub&gt;3&lt;/sub&gt; are regulated under the National Ambient Air Quality Standards (NAAQS) because of demonstrated health effects. BC and UFPs are of concern for their potential health effects. Therefore, these pollutants are the focus of this work.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The methodological approach includes case studies for which variables are identified and assesses their ability to explain either temporal or spatial variability in pollutant ambient concentrations. The case studies include one freeway location and one urban intersection. The case studies address (1) temporal variability at a fixed monitor 10 meters from a freeway; (2) downwind concentrations perpendicular to the same location; (3) variability in 24-hour average pollutant concentrations at five sites near an urban intersection; and (4) spatiotemporal variability along a walking path near that same intersection.&lt;/p&gt;&lt;p&gt;&lt;p&gt;The study boundary encompasses key factors in the continuum from vehicle emi","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 207","pages":"1-73"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620485/pdf/hei-2022-207.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10006151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE): Phase 2.","authors":"M Brauer,&nbsp;J R Brook,&nbsp;T Christidis,&nbsp;Y Chu,&nbsp;D L Crouse,&nbsp;A Erickson,&nbsp;P Hystad,&nbsp;C Li,&nbsp;R V Martin,&nbsp;J Meng,&nbsp;A J Pappin,&nbsp;L L Pinault,&nbsp;M Tjepkema,&nbsp;A van Donkelaar,&nbsp;C Weagle,&nbsp;S Weichenthal,&nbsp;R T Burnett","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Mortality is associated with long-term exposure to fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter; PM_2.5), although the magnitude and form of these associations remain poorly understood at lower concentrations. Knowledge gaps include the shape of concentration-response curves and the lowest levels of exposure at which increased risks are evident and the occurrence and extent of associations with specific causes of death. Here, we applied improved estimates of exposure to ambient PM_2.5 to national population-based cohorts in Canada, including a stacked cohort of 7.1 million people who responded to census year 1991, 1996, or 2001. The characterization of the shape of the concentration-response relationship for nonaccidental mortality and several specific causes of death at low levels of exposure was the focus of the Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE) Phase 1 report. In the Phase 1 report we reported that associations between outdoor PM_2.5 concentrations and nonaccidental mortality were attenuated with the addition of ozone (O₃) or a measure of gaseous pollutant oxidant capacity (O_x), which was estimated from O₃ and nitrogen dioxide (NO₂) concentrations. This was motivated by our interests in understanding both the effects air pollutant mixtures may have on mortality and also the role of O₃ as a copollutant that shares common sources and precursor emissions with those of PM_2.5. In this Phase 2 report, we further explore the sensitivity of these associations with O₃ and O_x, evaluate sensitivity to other factors, such as regional variation, and present ambient PM_2.5 concentration-response relationships for specific causes of death.</p><p><strong>Methods: </strong>PM_2.5 concentrations were estimated at 1 km² spatial resolution across North America using remote sensing of aerosol optical depth (AOD) combined with chemical transport model (GEOS-Chem) simulations of the AOD:surface PM_2.5 mass concentration relationship, land use information, and ground monitoring. These estimates were informed and further refined with collocated measurements of PM_2.5 and AOD, including targeted measurements in areas of low PM_2.5 concentrations collected at five locations across Canada. Ground measurements of PM_2.5 and total suspended particulate matter (TSP) mass concentrations from 1981 to 1999 were used to backcast remote-sensing-based estimates over that same time period, resulting in modeled annual surfaces from 1981 to 2016.</p><p><p>Annual exposures to PM_2.5 were then estimated for subjects in several national population-based Canadian cohorts using residential histories derived from annual postal code entries in income tax files. These cohorts included three c","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 212","pages":"1-91"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556709/pdf/hei-2022-212.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10383370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations of Air Pollution on the Brain in Children: A Brain Imaging Study.","authors":"Guxens Mònica,&nbsp;J Lubczyńska Małgorzata,&nbsp;Pérez-Crespo Laura,&nbsp;L Muetzel Ryan,&nbsp;El Marroun Hanan,&nbsp;Basagaña Xavier,&nbsp;Hoek Gerard,&nbsp;Tiemeier Henning","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Epidemiological studies are highlighting the negative effects of the exposure to air pollution on children's neurodevelopment. However, most studies assessed children's neurodevelopment using neuropsychological tests or questionnaires. Using magnetic resonance imaging (MRI) to precisely measure global and region-specific brain development would provide details of brain morphology and connectivity. This would help us understand the observed cognitive and behavioral changes related to air pollution exposure. Moreover, most studies assessed only a few air pollutants. This project investigates whether air pollution exposure to many pollutants during pregnancy and childhood is associated with the morphology and connectivity of the brain in school-age children and pre-adolescents.</p><p><strong>Methods: </strong>We used data from the Generation R Study, a population-based birth cohort set up in Rotterdam, the Netherlands in 2002-2006 (n = 9,610). We used land-use regression (LUR) models to estimate the levels of 14 air pollutants at participant's homes during pregnancy and childhood: nitrogen oxides (NO_x), nitrogen dioxide (NO₂), particulate matter with aerodynamic diameter ≤10 μm (PM₁₀) or ≤2.5 μm (PM_2.5), PM between 10 μm and 2.5 μm (PM_COARSE), absorbance of the PM_2.5 fraction - a measure of soot (PM_2.5absorbance), the composition of PM_2.5 such as polycyclic aromatic hydrocarbons (PAHs), organic carbon (OC), copper (Cu), iron (Fe), silicon (Si), zinc (Zn), and the oxidative potential of PM_2.5 evaluated using two acellular methods: dithiothreitol (OP^DTT) and electron spin resonance (OP^ESR). We performed MRI measurements of structural morphology (i.e., brain volumes, cortical thickness, and cortical surface area) using T₁-weighted images in 6- to 10-year-old school-age children and 9- to 12-year-old pre-adolescents, structural connectivity (i.e., white matter microstructure) using diffusion tensor imaging (DTI) in pre-adolescents, and functional connectivity (i.e., connectivity score between brain areas) using resting-state functional MRI (rs-fMRI) in pre-adolescents. We assessed cognitive function using the Developmental Neuropsychological Assessment test (NEPSY-II) in school-age children. For each outcome, we ran regression analysis adjusted for several socioeconomic and lifestyle characteristics. We performed single-pollutant analyses followed by multipollutant analyses using the deletion/substitution/addition (DSA) approach.</p><p><strong>Results: </strong>The project has air pollution and brain MRI data for 783 school-age children and 3,857 pre-adolescents. First, exposure to air pollution during pregnancy or childhood was not associated with global brain volumes (e.g., total brain, cortical gray matter, and cortical white matter) in school-age children or pre-adolescents. However, hi","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 209","pages":"1-61"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476146/pdf/hei-2022-209.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10009298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution: Implementation of Causal Inference Methods.","authors":"F Dominici, A Zanobetti, J Schwartz, D Braun, B Sabath, X Wu","doi":"","DOIUrl":"","url":null,"abstract":"&lt;p&gt;&lt;p&gt;This report provides a final summary of the principal findings and key conclusions of a study supported by an HEI grant aimed at \"Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution.\" It is the second and final report on this topic. The study was designed to advance four critical areas of inquiry and methods development. First, it focused on predicting short- and long-term exposures to ambient fine particulate matter (PM&lt;sub&gt;2.5&lt;/sub&gt;), nitrogen dioxide (NO&lt;sub&gt;2&lt;/sub&gt;), and ozone (O&lt;sub&gt;3&lt;/sub&gt;) at high spatial resolution (1 km × 1 km) for the continental United States over the period 2000-2016 and linking these predictions to health data. Second, it developed new causal inference methods for estimating exposure-response (ER) curves (ERCs) and adjusting for measured confounders. Third, it applied these methods to claims data from Medicare and Medicaid beneficiaries to estimate health effects associated with short- and long-term exposure to low levels of ambient air pollution. Finally, it developed pipelines for reproducible research, including approaches for data sharing, record linkage, and statistical software. Our HEI-funded work has supported an extensive portfolio of analyses and the development of statistical methods that can be used to robustly understand the health effects of short- and long-term exposure to low levels of ambient air pollution. Our Phase 1 report (Dominici et al. 2019) provided a high-level overview of our statistical methods, data analysis, and key findings, grouped into the following five areas: (1) exposure prediction, (2) epidemiological studies of ambient exposures to air pollution at low levels, (3) sensitivity analysis, (4) methodological contributions in causal inference, and (5) an open access research data platform. The current, final report includes a comprehensive overview of the entire research project.&lt;/p&gt;&lt;p&gt;&lt;p&gt;Considering our (1) massive study population, (2) numerous sensitivity analyses, and (3) transparent assessment of covariate balance indicating the quality of causal inference for simulating randomized experiments, we conclude that conditionally on the required assumptions for causal inference, our results collectively indicate that long-term PM&lt;sub&gt;2.5&lt;/sub&gt; exposure is likely to be causally related to mortality. This conclusion assumes that the causal inference assumptions hold and, more specifically, that we accounted adequately for confounding bias. We explored various modeling approaches, conducted extensive sensitivity analyses, and found that our results were robust across approaches and models. This work relied on publicly available data, and we have provided code that allows for reproducibility of our analyses.&lt;/p&gt;&lt;p&gt;&lt;p&gt;Our work provides comprehensive evidence of associations between exposures to PM&lt;sub&gt;2.5,&lt;/sub&gt; NO&lt;sub&gt;2&lt;/sub&gt;, and O&lt;sub&gt;3&lt;/sub&gt; and various health outcomes. In the current report, we report more specific results on the causal ","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 211","pages":"1-56"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530797/pdf/hei-2022-211.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9999839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global Burden of Disease from Major Air Pollution Sources (GBD MAPS): A Global Approach.","authors":"E McDuffie,&nbsp;R Martin,&nbsp;H Yin,&nbsp;M Brauer","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Ambient fine particulate matter (particles <2.5 μm in aerodynamic diameter [PM_2.5]) is the world's leading environmental health risk factor. Reducing the PM_2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. The Global Burden of Disease from Major Air Pollution Sources (GBD MAPS) project provides a contemporary and comprehensive evaluation of contributions to the ambient PM_2.5 disease burden from source sectors and fuels across 21 regions, 204 countries, and 200 subnational areas. We first derived quantitative contributions from 24 emission sensitivity simulations using an updated global atmospheric chemistry-transport model, input with a newly developed detailed anthropogenic emissions dataset that includes emissions specific to source sector and fuels. These simulation results were integrated with newly available high-resolution satellite-derived PM_2.5 exposure estimates and disease-specific concentration-response relationships consistent with the GBD project to quantify contributions of specific source sector and fuel to the ambient PM_2.5 disease burden across all regions, countries, and subnational areas. To improve the transparency and reproducibility of this and future work, we publicly provided the global atmospheric chemistry-transport model source code, emissions dataset and emissions model source code, analysis scripts, and source sensitivity results, and further described the emissions dataset and source contribution results in two publications.</p><p><p>We found that nearly 1.05 million (95% uncertainty interval [UI]: 0.74-1.36 million) deaths worldwide (27.3% of the total mortality attributable to PM_2.5) would be avoidable by eliminating fossil fuel combustion, with coal contributing over half of that burden. Residential (19.2%; 736,000 deaths [95% UI: 521,000-955,000]), industrial (11.7%; 448,000 deaths [95% UI: 318,000-582,000]), and energy (10.2%; 391,000 deaths [95% UI: 277,000-507,000]) sector emissions are among the dominant global sources Uncertainty in these estimates reflects those of the input datasets. Regions with the largest anthropogenic contributions generally have the highest numbers of attributable deaths, which clearly demonstrates the importance of reducing these emissions to realize reductions in global air pollution and its disease burden.</p>","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 210","pages":"1-45"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9501767/pdf/hei-2021-210.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10011334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mortality and Morbidity Effects of Long-Term Exposure to Low-Level PM_2.5, BC, NO₂, and O₃: An Analysis of European Cohorts in the ELAPSE Project.","authors":"Brunekreef Bert,&nbsp;Strak Maciej,&nbsp;Chen Jie,&nbsp;J Andersen Zorana,&nbsp;Atkinson Richard,&nbsp;Bauwelinck Mariska,&nbsp;Bellander Tom,&nbsp;Boutron Marie-Christine,&nbsp;Brandt Jørgen,&nbsp;Carey Iain,&nbsp;Cesaroni Giulia,&nbsp;Forastiere Francesco,&nbsp;Fecht Daniela,&nbsp;Gulliver John,&nbsp;Hertel Ole,&nbsp;Hoffmann Barbara,&nbsp;de Hoogh Kees,&nbsp;Houthuijs Danny,&nbsp;Hvidtfeldt Ulla,&nbsp;Janssen Nicole,&nbsp;Jørgensen Jeanette,&nbsp;Katsouyanni Klea,&nbsp;Ketzel Matthias,&nbsp;Klompmaker Jochem,&nbsp;Hjertager Krog Norun,&nbsp;Liu Shuo,&nbsp;Ljungman Petter,&nbsp;Mehta Amar,&nbsp;Nagel Gabriele,&nbsp;Oftedal Bente,&nbsp;Pershagen Göran,&nbsp;Peters Annette,&nbsp;Raaschou-Nielsen Ole,&nbsp;Renzi Matteo,&nbsp;Rodopoulou Sophia,&nbsp;Samoli Evi,&nbsp;Schwarze Per,&nbsp;Sigsgaard Torben,&nbsp;Stafoggia Massimo,&nbsp;Vienneau Danielle,&nbsp;Weinmayr Gudrun,&nbsp;Wolf Kathrin,&nbsp;Hoek Gerard","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Epidemiological cohort studies have consistently found associations between long-term exposure to outdoor air pollution and a range of morbidity and mortality endpoints. Recent evaluations by the World Health Organization and the Global Burden of Disease study have suggested that these associations may be nonlinear and may persist at very low concentrations. Studies conducted in North America in particular have suggested that associations with mortality persisted at concentrations of particulate matter with an aerodynamic diameter of less than 2.5 μm (PM_2.5) well below current air quality standards and guidelines. The uncertainty about the shape of the concentration-response function at the low end of the concentration distribution, related to the scarcity of observations in the lowest range, was the basis of the current project. Previous studies have focused on PM_2.5, but increasingly associations with nitrogen dioxide (NO₂) are being reported, particularly in studies that accounted for the fine spatial scale variation of NO₂. Very few studies have evaluated the effects of long-term exposure to low concentrations of ozone (O₃). Health effects of black carbon (BC), representing primary combustion particles, have not been studied in most large cohort studies of PM_2.5. Cohort studies assessing health effects of particle composition, including elements from nontailpipe traffic emissions (iron, copper, and zinc) and secondary aerosol (sulfur) have been few in number and reported inconsistent results. The overall objective of our study was to investigate the shape of the relationship between long-term exposure to four pollutants (PM_2.5, NO₂, BC, and O₃) and four broad health effect categories using a number of different methods to characterize the concentration-response function (i.e., linear, nonlinear, or threshold). The four health effect categories were (1) natural- and cause-specific mortality including cardiovascular and nonmalignant as well as malignant respiratory and diabetes mortality; and morbidity measured as (2) coronary and cerebrovascular events; (3) lung cancer incidence; and (4) asthma and chronic obstructive pulmonary disease (COPD) incidence. We additionally assessed health effects of PM_2.5 composition, specifically the copper, iron, zinc, and sulfur content of PM_2,5.</p><p><strong>Methods: </strong>We focused on analyses of health effects of air pollutants at low concentrations, defined as less than current European Union (EU) Limit Values, U.S. Environmental Protection Agency (U.S. EPA), National Ambient Air Quality Standards (NAAQS), and/or World Health Organization (WHO) Air Quality Guideline values for PM_2.5, NO₂, and O₃. We address the health effects at low air pollution levels by performing new analyses within selected cohorts of the ESCAPE ","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 208","pages":"1-127"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476567/pdf/hei-2021-208.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10063820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social Susceptibility to Multiple Air Pollutants in Cardiovascular Disease.","authors":"J E Clougherty,&nbsp;J L Humphrey,&nbsp;E J Kinnee,&nbsp;L F Robinson,&nbsp;L A McClure,&nbsp;L D Kubzansky,&nbsp;C E Reid","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Cardiovascular disease (CVD) is the leading cause of death in the United States, and substantial research has linked ambient air pollution to elevated rates of CVD etiology and events. Much of this research identified increased effects of air pollution in lower socioeconomic position (SEP) communities, where pollution exposures are also often higher. The complex spatial confounding between air pollution and SEP makes it very challenging, however, to disentangle the impacts of these very different exposure types and to accurately assess their interactions. The specific causal components (i.e., specific social stressors) underlying this SEP-related susceptibility remain unknown, because there are myriad pathways through which poverty and/or lower-SEP conditions may influence pollution susceptibility - including diet, smoking, coexposures in the home and occupational environments, health behaviors, and healthcare access. Growing evidence suggests that a substantial portion of SEP-related susceptibility may be due to chronic psychosocial stress - given the known wide-ranging impacts of chronic stress on immune, endocrine, and metabolic function - and to a higher prevalence of unpredictable chronic stressors in many lower-SEP communities, including violence, job insecurity, and housing instability. As such, elucidating susceptibility to pollution in the etiology of CVD, and in the risk of CVD events, has been identified as a research priority. This interplay among social and environmental conditions may be particularly relevant for CVD, because pollution and chronic stress both impact inflammation, metabolic function, oxidative stress, hypertension, atherosclerosis, and other processes relevant to CVD etiology. Because pollution exposures are often spatially patterned by SEP, disentangling their effects - and quantifying any interplay - is especially challenging. Doing so, however, would help to improve our ability to identify and characterize susceptible populations and to improve our understanding of how community stressors may alter responses to multiple air pollutants. More clearly characterizing susceptible populations will improve our ability to design and target interventions more effectively (and cost-effectively) and may reveal greater benefits of pollution reduction in susceptible communities, strengthening cost-benefit and accountability analyses, ultimately reducing the disproportionate burden of CVD and reducing health disparities.</p><p><strong>Methods: </strong>In the current study, we aimed to quantify combined effects of multiple pollutants and stressor exposures on CVD events, using a number of unique datasets we have compiled and verified, including the following. 1. Poverty metrics, violent crime rates, a composite socioeconomic deprivation index (SDI), an index of racial and economic segregation, noise disturbance metrics, and three composite spatial factors produced from a factor analysis of 27 c","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 206","pages":"1-71"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403800/pdf/hei-2021-206.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9999831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}