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There is a growing awareness that the large number of environmental pollutants we are exposed to on a daily basis are causing major health problems. Compared to traditional studies that focus on individual pollutants, there are relatively few studies on how pollutants mixtures interact. Several studies have reported a relationship between environmental pollutants and the development of cancer, even when pollutant levels are below toxicity reference values. The possibility of synergistic interactions between different pollutants could explain how even low concentrations can cause major health problems. These intricate that molecular interactions can occur through a wide variety of mechanisms, and our understanding of the physiological effects of mixtures is still limited. The purpose of this paper is to discuss recent reports that address possible synergistic interactions between different types of environmental pollutants that could promote cancer development. Our literature studies suggest that key biological pathways are frequently implicated in such processes. These include increased production of reactive oxygen species, activation by cytochrome P450, and aryl hydrocarbon receptor signaling, among others. We discuss the need to understand individual pathological vulnerability not only in relation to basic genetics and gene expression, but also in terms of measurable exposure to contaminants. We also mention the need for significant improvements in future studies using a multitude of disciplines, such as the development of high‐throughput study models, better tools for quantifying pollutants in cancer patients, innovative pharmacological and toxicological studies, and high‐efficiency computer analysis, which allow us to analyze the molecular mechanisms of mixtures. Plain Language Summary In general, every day we are exposed to many pollutants at the same time, and each pollutant can interact with others in different ways. Notably, two or more pollutants can interact and enhance their effects through a phenomenon called synergy and this would explain why, even at low concentrations, pollutants can have important health effects. Several studies have reported a link between environmental pollutants and cancer. Thus, our review of the literature suggests that synergy phenomena between pollutants can alter key points in cells and facilitate cancer development. Similarly, we mention the complications and needs to assess these complex interactions in subsequent studies. Key Points There are an increasing number of reports on the synergetic actions of pollutants in cancer Mixtures of pollutants can interact (synergy/antagonism) affecting different biological pathways Key pathways frequently implicated in synergetic action are reactive oxygen species, cytochrome P450, and aryl hydrocarbon receptor

One valuable application for generative artificial intelligence (AI) is summarizing research studies for non‐academic readers. We submitted five articles to Chat Generative Pre‐trained Transformer (ChatGPT) for summarization, and asked the article's author to rate the summaries. Higher ratings were assigned to more insight‐oriented activities, such as the production of eighth‐grade reading level summaries, and summaries highlighting the most important findings and real‐world applications. The general summary request was rated lower. For the field of environmental health science, no‐cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability. Plain Language Summary This study explored the use of generative artificial intelligence (AI), specifically Chat Generative Pre‐trained Transformer (ChatGPT), to summarize environmental health research articles. The field of environmental health sciences exemplifies this opportunity given the specialized language surrounding environmental contamination. Four differerent ChatGPT‐generated summaries were evaluated from each of five articles. The average rating of summaries indicated good content quality, though sometimes removed important details or had minor inaccuracies. This study suggests that no‐cost AI technology such as ChatGPT holds the promise to improve research translation to support environmental justice communities, mainstream media outlets, and community science groups, but within some boundaries. Key Points Generative artificial intelligence (AI), popularized by services like Chat Generative Pre‐trained Transformer (ChatGPT), has been the source of much recent popular attention for publishing health research AI production of high‐quality plain language summaries could improve access to scientific information ChatGPT holds the promise to improve research translation, but it must continue to be improved from its current capability

Since the publication of the first epidemiological study to establish the connection between long-term exposure to atmospheric pollution and effects on human health, major efforts have been dedicated to estimate the attributable mortality burden, especially in the context of the Global Burden of Disease (GBD). In this work, we review the estimates of excess mortality attributable to outdoor air pollution at the global scale, by comparing studies available in the literature. We find large differences between the estimates, which are related to the exposure response functions as well as the number of health outcomes included in the calculations, aspects where further improvements are necessary. Furthermore, we show that despite the considerable advancements in our understanding of health impacts of air pollution and the consequent improvement in the accuracy of the global estimates, their precision has not increased in the last decades. We offer recommendations for future measurements and research directions, which will help to improve our understanding and quantification of air pollution-health relationships.

The associations of polybrominated diphenyl ethers (PBDEs) with biological aging are unclear. This study explores the possible relationship between PBDEs and accelerated aging. Cross‐sectional data from 6,091 subjects of the National Health and Nutrition Examination Survey (NHANES) 2005–2010 and 2015–2016 are analyzed. Serum PBDE concentrations are quantified via automated liquid‐liquid extraction and subsequent sample purification, with seven PBDEs displaying a capture rate higher than 70%, identified as the exposure. Homeostatic dysregulation (HD), Klemera–Doubal method (KDM), phenoAge (PA), and allostatic load (AL) are utilized to assess biological aging. The associations are assessed with weighted multivariate linear regression models, restricted cubic spline (RCS), weighted quantile sum regression, and Quantile G‐computation analysis. Regarding individual exposures, significant positive associations of PBDE47, PBDE99, PBDE100, PBDE154, and PBDE85 with HD, KDM residual, and PA residual, and PBDE100 with AL ( β  > 0, P  < 0.050) are detected. The associations are further validated by RCS. Mixed PBDEs show a positive relationship with HD, KDM residual, PA residual, and AL ( β  > 0, P  < 0.050), with PBDE99, PBDE47, and PBDE85 as the most significant contributing PBDEs. Exposure to the PBDE mixture exhibits a positive association with predicted age metrics, highlighting PBDE99, PBDE47, and PBDE85 as the significant chemicals. Polybrominated diphenyl ethers (PBDEs) raise concerns due to their persistence, accumulation, and detection in wildlife and humans. The associations of PBDEs with biological aging are explored using National Health and Nutrition Examination Survey data from 6,091 subjects. Serum PBDE levels are measured, and various aging metrics are assessed. Positive associations are found between several PBDEs and aging indicators. PBDE99, PBDE47, and PBDE85 are identified as significant contributors to accelerated aging. The study highlights the adverse effects of PBDE exposure on aging processes. Individual and combined polybrominated diphenyl ethers (PBDEs) exposure are associated with accelerated aging PBDE99, PBDE47, and PBDE85 are the most significant contributing PBDEs

Long‐term exposure to particulate matter (PM) pollution may directly increase the risk of developing tuberculosis (TB). Despite the known link, the multi–scale spatiotemporal variations in the burden of TB attributable to long‐term PM exposure remain largely unclear in China. In this study, we conducted a nationwide, multi‐scale risk assessment of the burden of TB attributable to long‐term PM2.5, PM2.5–10, and PM10 exposure from 2013 to 2019, employing the multivariate distributed lag nonlinear model (MVDLNM), Lorenz curve and Gini index. Our health impact assessments indicate that PM exposure has resulted in significant increases in TB burden. Specifically, approximately$1,202 million (95% CI: 801–1,573 million), $ 486 million (95% CI: 398–572 million), and $944 million (95% CI: 767–1,115 million) of health economic costs could be attributed to long‐term exposure to PM2.5, PM2.5–10, and PM10, respectively. Although the overall the burden of TB attributable to PM exposure was significantly reduced from 2013 to 2019, regional inequalities have become more pronounced. The Gini index reveals a clear disparity in the burden of TB related to PM exposure across provincial, city, and county levels. These disparities are most pronounced at the county level (0.4914–0.6801), followed by the city level (0.4135–0.6382), and are least evident at the province level (0.3672–0.6078). Overall, the regional inequalities in the burden of TB are more pronounced at finer spatial scales. Our study highlights the health impacts of long‐term exposure to PM on the incidence of TB across different spatiotemporal scales, and the findings provide strong scientific evidence for pollution mitigation and efforts to reduce regional inequality. Plain Language Summary Ambient particulate matter (PM) pollution is a significant environmental risk factor contributing to the high tuberculosis (TB) burden in China. Although substantial improvements in air quality have been achieved in recent years, the impact of these improvements on TB incidence remains unclear, and regional exposure inequity has seldom been explored. This study systematically evaluates how regional disparities in health economic costs attributable to long‐term exposure to different sizes of PM (PM2.5, PM2.5–10, and PM10) vary over time and across spatial scales, including the macro‐scale (provincial level), meso‐scale (city level), and micro‐scale (county level). It found that long‐term PM exposure caused billions of dollars in TB‐related health costs, with PM2.5 being the largest contributor. While overall PM‐related TB burden decreased nationwide from 2013 to 2019, inequalities between regions grew, especially at finer scales like counties. Disparities in TB burden were highest at the county level, demonstrating that local conditions strongly influence health risks. This study highlights the urgent need for targeted air quality and health policies in high‐risk areas to reduce TB burden and address health inequalities. Key Points Long‐term exposure to PM2.5–10 was associated with an increased risk of tuberculosis incidence Health economic losses attributable to long‐term particulate matter exposure exceeded one billion USD from 2013 to 2019 Regional inequalities in the tuberculosis burden were more pronounced at finer spatial scales

Fine particulate matter (PM2.5) from U.S. anthropogenic sources is decreasing. However, previous studies have predicted that PM2.5 emissions from wildfires will increase in the midcentury to next century, potentially offsetting improvements gained by continued reductions in anthropogenic emissions. Therefore, some regions could experience worse air quality, degraded visibility, and increases in population‐level exposure. We use global climate model simulations to estimate the impacts of changing fire emissions on air quality, visibility, and premature deaths in the middle and late 21st century. We find that PM2.5 concentrations will decrease overall in the contiguous United States (CONUS) due to decreasing anthropogenic emissions (total PM2.5 decreases by 3% in Representative Concentration Pathway [RCP] 8.5 and 34% in RCP4.5 by 2100), but increasing fire‐related PM2.5 (fire‐related PM2.5 increases by 55% in RCP4.5 and 190% in RCP8.5 by 2100) offsets these benefits and causes increases in total PM2.5 in some regions. We predict that the average visibility will improve across the CONUS, but fire‐related PM2.5 will reduce visibility on the worst days in western and southeastern U.S. regions. We estimate that the number of deaths attributable to total PM2.5 will decrease in both the RCP4.5 and RCP8.5 scenarios (from 6% to 4–5%), but the absolute number of premature deaths attributable to fire‐related PM2.5 will double compared to early 21st century. We provide the first estimates of future smoke health and visibility impacts using a prognostic land‐fire model. Our results suggest the importance of using realistic fire emissions in future air quality projections. Key Points We provide the first estimates of future smoke health and visibility impacts in the contiguous United States using a prognostic land‐fire model Average visibility will improve across the contiguous United States, but fire PM will reduce visibility on the worst days in western and southeastern U.S. regions The number of deaths attributable to total PM2.5 will decrease, but the number attributable to fire‐related PM2.5 will double by late 21st century

Coccidioidomycosis (Valley fever) is a fungal disease endemic to the southwestern United States. Across this region, temperature and precipitation influence the extent of the endemic region and number of Valley fever cases. Climate projections for the western United States indicate that temperatures will increase and precipitation patterns will shift, which may alter disease dynamics. We estimated the area potentially endemic to Valley fever using a climate niche model derived from contemporary climate and disease incidence data. We then used our model with projections of climate from Earth system models to assess how endemic areas will change during the 21st century. By 2100 in a high warming scenario, our model predicts that the area of climate‐limited endemicity will more than double, the number of affected states will increase from 12 to 17, and the number of Valley fever cases will increase by 50%. The Valley fever endemic region will expand north into dry western states, including Idaho, Wyoming, Montana, Nebraska, South Dakota, and North Dakota. Precipitation will limit the disease from spreading into states farther east and along the central and northern Pacific coast. This is the first quantitative estimate of how climate change may influence Valley fever in the United States. Our predictive model of Valley fever endemicity may provide guidance to public health officials to establish disease surveillance programs and design mitigation efforts to limit the impacts of this disease. Plain Language Summary Valley fever is a fungal disease most common in the southwestern United States. Generally, the disease is limited to areas that are hot and dry. Climate change will cause the western United States to become hotter and may change the location, timing, and amount of rain. This is likely to change which counties are affected by Valley fever. We used climate observations to estimate which counties in the United States have a higher risk for Valley fever. Then, we used predictions of future climate to map which counties may become affected by Valley fever during the remainder of the 21st century. By 2100, our model predicts that the area affected by Valley fever will more than double and the number of people who become sick will increase by 50%. The area affected by Valley fever will expand north into drier states in the western US, including Idaho, Wyoming, Montana, Nebraska, South Dakota, and North Dakota. Our estimate may help public health officials develop more effective plans so less people suffer from this disease. Key Points We created a niche model to estimate climate limits on the spatial extent of Valley fever endemicity in the United States For a high warming scenario, the area of climate‐limited endemicity will more than double by 2100, expanding northward into dry western states Our predictive model of Valley fever endemic regions may help mitigate disease impacts as the disease spreads into new regions

As anthropogenic emissions continue to decline and emissions from landscape (wild, prescribed, and agricultural) fires increase across the coming century, the relative importance of landscape‐fire smoke on air quality and health in the United States (US) will increase. Landscape fires are a large source of fine particulate matter (PM2.5), which has known negative impacts on human health. The seasonal and spatial distribution, particle composition, and co‐emitted species in landscape‐fire emissions are different from anthropogenic sources of PM2.5. The implications of landscape‐fire emissions on the sub‐national temporal and spatial distribution of health events and the relative health importance of specific pollutants within smoke are not well understood. We use a health impact assessment with observation‐based smoke PM2.5 to determine the sub‐national distribution of mortality and the sub‐national and sub‐annual distribution of asthma morbidity attributable to US smoke PM2.5 from 2006 to 2018. We estimate disability‐adjusted life years (DALYs) for PM2.5 and 18 gas‐phase hazardous air pollutants (HAPs) in smoke. Although the majority of large landscape fires occur in the western US, we find the majority of mortality (74%) and asthma morbidity (on average 75% across 2006–2018) attributable to smoke PM2.5 occurs outside the West, due to higher population density in the East. Across the US, smoke‐attributable asthma morbidity predominantly occurs in spring and summer. The number of DALYs associated with smoke PM2.5 is approximately three orders of magnitude higher than DALYs associated with gas‐phase smoke HAPs. Our results indicate awareness and mitigation of landscape‐fire smoke exposure is important across the US. Plain Language Summary The pollutants from landscape (wild, prescribed, and agricultural) fires are expected to have an increasing impact on air quality and health in the United States (US) across the current century. The implications of landscape‐fire smoke on the regional and seasonal distribution of health events and the relative health importance of specific pollutants within smoke are not well understood. In the present study, we assess the seasonal and regional distribution of the health impacts from US smoke exposure from 2006 to 2018. We also estimate the long‐term health impacts for both fine particles (PM2.5) and gas‐phase hazardous air pollutants (HAPs) in smoke. Although the majority of large landscape fires occur in the western US, we find the majority of deaths (74%) and asthma emergency department visits and hospital admissions (on average 75% across 2006–2018) attributable to smoke occur outside the West. Across the US, smoke‐attributable asthma emergency department visits predominantly occur in spring and summer. The long‐term health impacts associated with smoke PM2.5 are much higher than the estimated long‐term health impacts of gas‐phase smoke HAPs. Our results indicate awareness and mitigation of landscape‐fire smoke exposure is important across the US, not just in regions in proximity to large wildfires. Key Points While the majority of large fires occur in the United States (US) West, a majority of smoke‐attributable US mortality and morbidity occur east of ∼100 degW A higher percent of mortality and morbidity is attributable to smoke in high fire‐impacted northwestern states, relative to other US states Disability‐adjusted life years attributable to fine particles in smoke are much higher than that from gas‐phase hazardous air pollutants

Increases in wildfire activity across the Western US pose a significant public health threat. While there is evidence that wildfire smoke is detrimental for respiratory health, the impacts on cardiovascular health remain unclear. This study evaluates the association between fine particulate matter (PM2.5) from wildfire smoke and unscheduled cardiorespiratory hospital visits in California during the 2004–2009 wildfire seasons. We estimate daily mean wildfire‐specific PM2.5 with Goddard Earth Observing System‐Chem, a global three‐dimensional model of atmospheric chemistry, with wildfire emissions estimates from the Global Fire Emissions Database. We defined a “smoke event day” as cumulative 0‐1‐day lag wildfire‐specific PM2.5 ≥ 98th percentile of cumulative 0–1 lag day wildfire PM2.5. Associations between exposure and outcomes are estimated using negative binomial regression. Results indicate that smoke event days are associated with a 3.3% (95% CI: [0.4%, 6.3%]) increase in visits for all respiratory diseases and a 10.3% (95% CI: [2.3%, 19.0%]) increase for asthma specifically. Stratifying by age, we found the largest effect for asthma among children ages 0–5 years. We observed no significant association between exposure and overall cardiovascular disease, but stratified analyses revealed increases in visits for all cardiovascular, ischemic heart disease, and heart failure among non‐Hispanic white individuals and those older than 65 years. Further, we found a significant interaction between smoke event days and daily average temperature for all cardiovascular disease visits, suggesting that days with high wildfire PM2.5 concentrations and high temperatures may pose greater risk for cardiovascular disease. These results suggest substantial increases in adverse outcomes from wildfire smoke exposure and indicate the need for improved prevention strategies and adaptations to protect vulnerable populations. Plain Language Summary Due to continued climate change, wildfire activity has increased in recent years and poses a significant public health threat. In this study, we investigated the impact of increased wildfire smoke exposure on cardiovascular and respiratory emergency department (ED) visits. We found that smoke events are linked to a > 3% increase of respiratory ED visits with a > 10% increase for asthma specifically, with the largest effect seen in children 0–5 years of age. We did not find an increase in cardiovascular visits for the entire population, but we did observe significant increases in several cardiovascular outcomes for individuals 65 years of age and older as well as for non‐Hispanic white individuals. Key Points Consecutive days of wildfire smoke PM2.5 exposure can significantly impact respiratory and cardiovascular health outcomes Ischemic heart disease and failure highest in adults 65+; heart failure elevated in non‐Hispanic white and non‐Hispanic Black populations When combined with increase in temperature, wildfire smoke exposure is associated with increased risk of cardiovascular disease

GeoHealth as a research paradigm offers the opportunity to re‐evaluate common research engagement models and science training practices. GeoHealth challenges are often wicked problems that require both transdisciplinary approaches and the establishment of intimate and long‐term partnerships with a range of community members. We examine four common modes of community engagement and explore how research projects are launched, who has the power in these relationships, and how projects evolve to become truly transformative for everyone involved. Plain Language Summary GeoHealth research is often partnership focused. We describe four common models for community‐engaged GeoHealth research and highlight the central characteristics of each, while daylighting the lived experiences of LEAD Agency activists. We note a range of outcomes emerge which can foster science‐based environmental health policy making and lead to justice focused actions. Key Points The GeoHealth research community often engages actively with civil society in the research enterprise, but often uses various models The models of engagement, from researcher‐heavy to community‐heavy, have very different outcomes A new model of training and support is required for the GeoHealth community to more productively engage with civil society