Environmental Epidemiology最新文献

{"title":"Combined and synergistic effects of heat and fine particulate matter on hospitalization among patients with Alzheimer's disease and related dementias.","authors":"Federica Spoto, Antonella Zanobetti, Scott W Delaney, Thomas M Gill, Michelle L Bell, Francesca Dominici, Danielle Braun, Daniel Mork","doi":"10.1097/EE9.0000000000000440","DOIUrl":"10.1097/EE9.0000000000000440","url":null,"abstract":"<p><strong>Background: </strong>Patients with Alzheimer's disease and related dementias (ADRD) are vulnerable to environmental stressors such as extreme heat and air pollution, yet their combined health effects remain poorly understood.</p><p><strong>Methods: </strong>We assessed the joint impact of extreme heat and fine particulate matter exposure (PM_2.5) on the risk of all-cause hospitalization among an ADRD cohort of Medicare beneficiaries aged ≥65 years. Using a time-stratified case-crossover design, we analyzed data from beneficiaries with prior ADRD-related hospitalizations across the contiguous US in 2000-2016. Daily heat index and PM_2.5 concentrations were linked to residential ZIP codes, and conditional logistic regression models were applied to estimate same-day associations during the warm season (May-September), including interaction terms to explore potential synergistic effects.</p><p><strong>Results: </strong>We found a linear association between heat and hospitalization, with an odds ratio (OR) of 1.017 (95% confidence interval [CI] = 1.004, 1.031) on extreme heat days (99th percentile) versus median. The PM_2.5-hospitalization relationship was nonlinear, with stronger effects at lower concentrations (10 vs. 5 µg/m³ OR = 1.010; 95% CI = 1.005, 1.015). When accounting for changes in PM_2.5, the OR on extreme heat days versus the median was 1.016 (95% CI = 1.001, 1.032).</p><p><strong>Conclusion: </strong>These findings underscore the need to consider both environmental stressors when assessing health risks in ADRD populations.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 6","pages":"e440"},"PeriodicalIF":4.2,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12643645/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145602752","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 environmental health aspects of environmental justice in communities living in industrially contaminated areas: An international network to share approaches and experiences.","authors":"Ivano Iavarone, Sandra Cortés, Carmen Ildes Rodrigues Fróes-Asmus, Daniela Marsili, Juan Pablo Ramos-Bonilla, Marcela Tamayo-Ortiz, Roberto Pasetto","doi":"10.1097/EE9.0000000000000435","DOIUrl":"10.1097/EE9.0000000000000435","url":null,"abstract":"<p><strong>Background: </strong>Industrially contaminated areas (ICA) are areas hosting or that have hosted industrial human activities (including industrial agriculture and mining) that have produced or might produce, directly or indirectly, chemical contamination of soil, surface or groundwater, air, or food chains, resulting in ecosystem and/or human health impacts.Pollution in ICA can derive from multiple sources and be closely interrelated with social and economic deprivation of affected communities. Furthermore, these populations may experience health criticalities, limited access to health care and ecosystem resources, and can be considered overburdened or environmental justice (EJ) communities.</p><p><strong>Objectives: </strong>This commentary stems from the discussion at the symposium \"Assessing Environmental Justice for Communities Living in Industrially Contaminated Areas: Sharing Approaches and Experiences\" (36th Conference of the International Society for Environmental Epidemiology-Santiago de Chile, 2024). The objective being to propose an international network to share research experiences on EJ in ICA in Europe and in the Latin American regions to enable more consistent knowledge and better policy responses to address the objectives of the 2030 United Nations Sustainable and Development Goals Agenda, specifically reducing inequality within and among countries.</p><p><strong>Discussion and policy implication: </strong>EJ associated with ICA has been observed in different countries, as investigated through single-site or nationwide assessments. Procedural aspects of EJ include misrecognition of the rights of affected communities to be informed through inclusive communication. This implies the marginalization of the communities in the decision-making process addressing the health impacts of ICA. We propose an international effort based on collaborative work to identify experiences in diversified contexts, research needs, and intervention priorities.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 6","pages":"e435"},"PeriodicalIF":3.8,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12643637/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145602251","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":"Impact of oil and gas boom and busts on working-age mortality in the U.S.","authors":"Ryan P Thombs, Mary D Willis","doi":"10.1097/EE9.0000000000000438","DOIUrl":"10.1097/EE9.0000000000000438","url":null,"abstract":"<p><strong>Background: </strong>The oil and gas sector is prone to boom-and-bust cycles that create precarious employment conditions, social disruptions, and environmental stressors, which could impact working-age mortality (i.e., premature death between 25 and 64 years old).</p><p><strong>Methods: </strong>We evaluated the association between booms and busts from oil and gas development with respect to working-age mortality. Using integrated county-level oil and gas production data with mortality records (2000-2011), we implemented a two-way fixed effects spatial lag of X (i.e., SLX) Poisson regression model, accounting for county-specific trends. We also estimated a distributed lag model to test for long-run effects after the initial shock.</p><p><strong>Results: </strong>We find stronger evidence that busts, rather than booms, in oil and gas production are associated with increases in all-cause working-age mortality. The average production bust yielded 0.4 additional deaths per county (95% confidence interval [CI]: 0.1, 0.6). While rarer, extreme production busts were associated with as many as 19.5 additional deaths per county (95% CI: 6.7, 32.3). These findings suggest that an average, country-wide oil and gas bust event would result in 439 additional working age deaths across the U.S. (95% CI: 165, 714). In the cause-specific analyses, more complex associations emerge regarding the influence of the boom and the bust exposures on working-age mortality, including substantial variation in effect magnitude and directionality by specific causes.</p><p><strong>Conclusions: </strong>This study demonstrates the complexity in the association between boom-and-bust cycles with respect to working-age mortality in the U.S., providing many avenues for future work.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 6","pages":"e438"},"PeriodicalIF":4.2,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12637344/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145586016","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":"Street-view greenspace distribution across racial/ethnic, neighborhood income, and individual education subgroups.","authors":"Tara E Jenson, Pi-I Debby Lin, Peter James, Perry Hystad, Ana V Diez-Roux, Brent Coull, Lilah Besser, Esra Suel, Jennifer Weuve, Marcia Pescador Jimenez","doi":"10.1097/EE9.0000000000000441","DOIUrl":"10.1097/EE9.0000000000000441","url":null,"abstract":"<p><strong>Background: </strong>The maldistribution of greenspaces across Black, Hispanic, and low-income communities can contribute to health disparities. It is unclear whether the interaction of race/ethnicity and socioeconomic status may explain the maldistribution of greenspace, or whether the maldistribution varies by type of greenspace.</p><p><strong>Methods: </strong>Applying deep learning algorithms to street-view images, we calculated percentages of specific types of residential greenspace (i.e., %Trees, %Grass) for each Multi-Ethnic Study of Atherosclerosis participant (N = 5,858; 2000-2002). We used multilevel analysis of individual heterogeneity and discriminatory accuracy to quantify inequities in greenspace type by intersecting stratum of race/ethnicity (Black, Chinese American, Hispanic, and White), education (high school, some college, and bachelor's degree), and neighborhood socioeconomic status (NSES; low, moderate, and high). Models adjusted for age, sex, individual income, and study site.</p><p><strong>Results: </strong>The mean %Trees was 19.0 (SD 8.8) and the mean %Grass was 5.1 (4.6). Distribution of %Trees varied across strata, for example, 13.1% (95% confidence interval [CI] = 9.1, 23.8) for Hispanic participants in the lowest education and NSES group versus 20.5% (14.0, 30.4) for Hispanic participants in the highest education and NSES group. Patterns were similar among corresponding strata of Black and Chinese American participants. However, the lowest %Trees among White participants was in the highest NSES and education stratum (20.6, 95% CI = 14.8, 31.5). About 16% of the variability of %Trees and 11% of the variability of %Grass was explained by intersecting stratum of race/ethnicity, education, and NSES.</p><p><strong>Conclusion: </strong>Maldistribution of greenspace types may be explained by combinations of race/ethnicity, education, and NSES subgroups, as opposed to each factor alone.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 6","pages":"e441"},"PeriodicalIF":4.2,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12626759/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145563103","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":"Transforming air pollution and health research into action in low- and middle-income countries.","authors":"Jonathan Samet, Kerolyn Shairsingh, Wenlu Ye, Sophie Gumy, Pierpaolo Mudu, Zorana Andersen, Wei Huang, Michal Krzyzanowski, Sumi Mehta, Helen Petach, Annette Peters, Ajay Pillarisetti, Jason West, Caradee Y Wright, Thomas Clasen","doi":"10.1097/EE9.0000000000000434","DOIUrl":"10.1097/EE9.0000000000000434","url":null,"abstract":"<p><p>This commentary highlights the need for actionable and context-appropriate research on air pollution and health that will continue to drive policies to reduce exposures and disease burden. Research on air pollution and health has been substantial in high-income countries (HIC), leading to causal conclusions on the adverse effects of air pollution. Despite bearing the greatest disease burden from air pollution, low- and middle-income countries (LMICs) have had scant research funding, a trend that may well be aggravated due to changing political priorities in some HICs. High-quality data from LMICs is urgently needed to help motivate local, subnational, and national policies to raise awareness and identify priority actions to improve health. The new evidence will also provide a more complete understanding of air pollution and health globally. We highlight a framework for moving from research to action and address how this framework differs in HIC and LMIC contexts. We propose a hierarchy of research needs that begins with having the necessary air pollution monitoring and health data, and the capacity to use the data for informative analytics, risk assessment, valuation, and policy formulation. Building technical capacity may be needed for this purpose, as will development of a functioning regulatory system in parallel. We call for greater emphasis on surveillance studies to demonstrate the benefits of action and address barriers to action. The global community would benefit from a broad research agenda with priorities and adequate funding dedicated to building evidence that leads to positive policy change. We urge priority for advancing actionable research and improving research capacity in LMICs, including investments in routine collection of relevant data, emphasizing the foundation of risk monitoring and health data systems, and building a cadre of researchers and informed policy-makers.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 6","pages":"e434"},"PeriodicalIF":3.8,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12599730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145494965","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":"The role of cardiovascular disease as a mediator in mitigating the impact of ambient PM_2.5 on dementia risk.","authors":"Chengyi Lin, Yechi Zhang, Andrew T DeWan, Laura Forastiere, Kai Chen","doi":"10.1097/EE9.0000000000000436","DOIUrl":"10.1097/EE9.0000000000000436","url":null,"abstract":"<p><strong>Background: </strong>Previous research suggested that stricter ambient particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5) standards would reduce the risk of dementia, but immediate reductions in PM_2.5 levels are not always feasible. Limited studies have quantified the extent to which cardiovascular disease (CVD) interventions could mitigate the effect of not achieving stricter PM_2.5 standards on dementia risk.</p><p><strong>Methods: </strong>This study included 283,813 participants in the UK Biobank cohort aged ≥60 years without dementia diagnosis or CVD hospitalization at baseline (2015). We applied the longitudinal targeted maximum likelihood estimation to estimate the total effect of no PM_2.5 intervention compared with hypothetical PM_2.5 interventions on the 5-year risk of dementia. We also estimated the controlled direct effect by setting all participants free from CVD hospitalization in both scenarios.</p><p><strong>Results: </strong>Compared with the hypothetical intervention of reducing PM_2.5 exposure by 10% if it is above the standard of 10 µg/m³, the total effect of no PM_2.5 intervention increased the 5-year dementia risk by 3.77 (95% confidence interval [CI] = 1.47, 4.39) cases per 1000 participants. By setting all participants free from CVD hospitalization, the controlled direct effect was an increase of 2.82 (95% CI = 0.74, 3.30) cases per 1000 participants. The proportion of the total effect that could be mitigated by preventing CVD hospitalization was 25.27% (95% CI = 17.49%, 49.42%) among all eligible participants.</p><p><strong>Conclusion: </strong>Part of the effect of not achieving stricter ambient PM_2.5 standards on dementia risk could be mitigated by preventing CVD hospitalization in the UK Biobank cohort. This finding indicates the potential of promoting cardiovascular health to reduce dementia burden.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 6","pages":"e436"},"PeriodicalIF":4.2,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12588692/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145458078","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":"Neighborhood disadvantage and fecundability in a cohort of US Black women.","authors":"Amelia K Wesselink, Mary D Willis, Sharonda M Lovett, Chen Sheng, Wendy Kuohung, Jacqueline Hicks, Junenette L Peters, Shanshan Sheehy, Julie R Palmer, Lauren A Wise, Yvette Cozier","doi":"10.1097/EE9.0000000000000428","DOIUrl":"10.1097/EE9.0000000000000428","url":null,"abstract":"<p><strong>Background: </strong>Neighborhood context is a root cause of health disparities, but few epidemiologic studies have measured the effect of neighborhoods on fertility, a reproductive outcome with known racial disparities.</p><p><strong>Methods: </strong>The Black Women's Health Study is a prospective cohort study of US Black women who enrolled in 1995. Participants completed questionnaires at baseline and every 2 years afterwards. We linked participant addresses to US Census block group data on six variables representing neighborhood disadvantage and used factor analysis to derive a composite neighborhood disadvantage score. In 2011, participants reported how many months it took to conceive each of their planned pregnancies and whether they had ever tried to conceive for 12 or more months without success. We included 2,085 participants who contributed 2,712 pregnancy attempts during 1995-2011. We fit proportional probabilities regression models with generalized estimating equations to estimate fecundability ratios and 95% confidence intervals (CI). We stratified models by individual-level educational attainment.</p><p><strong>Results: </strong>Relative to the lowest quintile of neighborhood disadvantage, fecundability ratios for participants in quintiles 2, 3, 4, and 5 were 0.89 (95% CI = 0.79, 1.01), 0.94 (95% CI = 0.83, 1.06), 0.84 (95% CI = 0.74, 0.96), and 0.89 (95% CI = 0.79, 1.02), respectively. The association persisted only among participants with a college degree or higher.</p><p><strong>Conclusion: </strong>Higher neighborhood disadvantage was associated with reduced fecundability in this cohort of Black women, particularly among those with high educational attainment. These results support the relevance of studying place-based risk factors for subfertility and have important implications for advancing reproductive justice.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 6","pages":"e428"},"PeriodicalIF":3.8,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12551729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145376567","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":"Cross-sectional associations of self-reported firearm use with blood lead concentrations in a nationally representative cohort of US adults.","authors":"Madeline Day, Joseph M Braun, Christian Hoover","doi":"10.1097/EE9.0000000000000427","DOIUrl":"10.1097/EE9.0000000000000427","url":null,"abstract":"<p><strong>Background: </strong>Firearm-related lead exposure could occur when firearms discharge lead ammunition particles. Prior studies were primarily among military or police participants, but this relation has not been examined in civilian populations. Thus, among noninstitutionalized United States (US) adult civilians, we examined the association of self-reported firearm noise exposure (proxy for firearm-related lead exposure) and firearm use with blood lead concentrations.</p><p><strong>Methods: </strong>We used 5 cycles of the National Health and Nutrition Examination Survey. Using lead biomarkers and questionnaires related to firearm noise exposure (1999-2004, n = 9,606) and firearm use (2011-2012 and 2015-2016, n = 5,972), we calculated survey-weighted and covariate-adjusted percent differences in blood lead concentrations. We adjusted for gender, age, race/ethnicity, and education. Sensitivity analyses separately examined whether former military status, pre-1978 housing, or occupation confounded these associations.</p><p><strong>Results: </strong>Self-reported firearm noise exposure was associated with blood lead concentrations (percent difference 15%; 95% CI = 7%, 23%), but firearm use was not (percent difference 1%; 95% CI = -5%, 9%). However, blood lead concentrations were 9% (95% CI = -5%, 25%) and 21% (95% CI = -5%, 54%) higher among those who reported shooting 1,000-10,000 and 10,000+ rounds, respectively (<i>P</i> value for trend = 0.07), compared with those who reported shooting 0 rounds. Results were similar after separate adjustment for former military status, pre-1978 housing, and occupation.</p><p><strong>Conclusion: </strong>In this representative sample of US civilians, individuals who used firearms more frequently (10,000+ rounds) had increased blood lead concentrations.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 6","pages":"e427"},"PeriodicalIF":4.2,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12551738/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145372188","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 survival among Black women with epithelial ovarian cancer across diverse geographical regions of the United States.","authors":"Ekaterina Chirikova, Courtney E Johnson, Anke Huels, Pushkar P Inamdar, Elisa V Bandera, Lawrence H Kushi, Jennifer A Doherty, Joellen M Schildkraut, Hari S Iyer, Melissa Bondy, Edward S Peters, Kendra Ratnapradipa, Jeffrey Marks, Christopher Pierson, Theresa Hastert, Kristin Haller, Grace Christensen, Salma Shariff-Marco, Scarlett L Gomez, Andrew Lawson","doi":"10.1097/EE9.0000000000000426","DOIUrl":"10.1097/EE9.0000000000000426","url":null,"abstract":"<p><strong>Background: </strong>Ovarian cancer is a leading cause of gynecologic cancer mortality, with Black women experiencing 5-year survival rates of only 41%. Disproportionate air pollution exposure may impact survival. We evaluated associations of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) exposure with survival among Black women with epithelial ovarian cancer using data from the California Cancer Registry (CCR, n = 540) and the multi-state African American Cancer Epidemiology Study (AACES, n = 766).</p><p><strong>Methods: </strong>Annual PM_2.5 and NO₂ levels were estimated at a 1 km resolution using well-validated ensemble-based prediction models derived from the Socioeconomic Data and Application Center and assigned to the participants' residential addresses per their year of diagnosis (2004-2016). Weibull accelerated failure time models with participant-level frailty were used to assess air pollutant exposure associations with overall survival.</p><p><strong>Results: </strong>Average PM_2.5 and NO₂ exposures were 11.3 μg/m³ and 25.8 ppb in CCR and 9.7 μg/m³ and 17.5 ppb in AACES. There was little evidence of an association between air pollution exposures and survival, with event time ratios (> 1 indicate longer survival) in CCR of 1.08 (95% CI = 0.97, 1.20) per 1 μg/m³ PM_2.5 and 1.07 (95% CI = 0.99, 1.15) per 10 ppb NO₂, and in AACES of 1.00 (95% CI = 0.93, 1.07) per 1 μg/m³ PM_2.5 and 1.04 (95% CI = 0.91, 1.19) per 10 ppb NO₂.</p><p><strong>Conclusions: </strong>Findings were modest and consistent across both cohorts and sensitivity analyses, supported by the use of advanced exposure modeling. Future research should use time-varying, long-term exposure data and examine interactions with occupation, physical activity, and neighborhood stressors.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 6","pages":"e426"},"PeriodicalIF":3.8,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12537266/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145344321","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":"Increased mortality from a two-year delay in Mercury and Air Toxics Standards (MATS) emission-reductions of filterable PM_2.5 at specific coal-fired power plants in the United States.","authors":"Bujin Bekbulat, Kevin R Cromar, Julian D Marshall","doi":"10.1097/EE9.0000000000000422","DOIUrl":"10.1097/EE9.0000000000000422","url":null,"abstract":"<p><strong>Background: </strong>In 2024, the US Environmental Protection Agency tightened the Mercury and Air Toxics Standards (MATS) for emissions of filterable particulate matter (fPM) from coal-fired power plants to 0.010 lb/MMBtu. In April 2025, a presidential proclamation stated that 47 specific power plant companies received a 2-year exemption from the new requirements. The proclamation provided no estimates of the resulting health impacts.</p><p><strong>Methods: </strong>Our approach applies conventional risk-assessment calculations for mortality from inhalation of filterable PM_2.5 (fPM_2.5) emissions, for \"with\" versus \"without\" the exemption, across four steps: (1) calculate fPM_2.5 emissions, based on government databases; (2) calculate the change in ambient PM_2.5 concentrations, using the Intervention Model for Air Pollution (InMAP) source-receptor matrix (ISRM); (3) calculate mortality impacts from inhalation of PM_2.5, using the Orellano et al., 2024 concentration-response function (CRF; relative risk (RR) per 10 μg/m³: 1.095, 95% confidence interval (CI) = 1.064, 1.127; in sensitivity analyses, we employ other CRFs); (4) aggregate results (e.g., by US state).</p><p><strong>Results: </strong>Most (83%) of the exempted power plant facilities already have sufficient control technology installed that they operate below the new MATS limit, indicating that much of that fleet already adopted cleaner technologies. For the remaining 17% of facilities, the proclamation will increase total fPM_2.5 emissions to ~6,900 tons, from ~4,400 tons. We estimate that the additional ~2,500 tons emitted will lead to 32 (95% CI = 22, 43) deaths. The highest mortality is in St. Louis, Missouri, (population: 2.2 million) with an estimated 14 (95% CI = 10,19) deaths. The increased mortality is, for some states (e.g., Missouri, and Pennsylvania), caused by mostly in-state emissions; for other states (e.g., Illinois, Maryland, New Jersey, and Virginia), the cause is out-of-state emissions.</p><p><strong>Discussion: </strong>Results here quantify a portion of the health impacts but leave unquantified nonmortality impacts, impacts from hazardous air pollutant (HAP) exposures, and noninhalation pathways. The reduced computational demands of the air pollution model employed here allows for more timely investigation of government actions than would traditional air dispersion modeling. Sensitivity analyses yielded mortality results that ranged from 47% lower to 169% higher than the core findings.</p><p><strong>Conclusions: </strong>We estimate that a 2-year delay in MATS emission reductions of fPM_2.5 at the exempted coal-fired power plants will lead to 32 (95% CI = 22, 43) additional deaths.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"9 5","pages":"e422"},"PeriodicalIF":3.8,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12506990/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145257702","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}