Research report (Health Effects Institute)最新文献

{"title":"Ambient Air Pollution and COVID-19 in California.","authors":"M Kleeman, C Nau, J Su, D R Young, R Butler, L-S Yang, C Batteate, S Eng, R T Burnett, M Jerrett","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>As of December 2023, more than 6.9 million people globally had died from COVID-19, including more than 1.165 million deaths in the United States. It is estimated that approximately 18.8 million people in the United States have experienced post-acute COVID-19 conditions, also known as post-acute sequelae of SARS-CoV-2 (PASC) or long COVID, in the first 3 years after the pandemic. Although some initial cases of long COVID have resolved, with the ongoing incidence of COVID-19, roughly 17.8 million persons in the United States continue to suffer from long COVID at the time of this writing.<sup>1-3</sup> Preliminary evidence early in the COVID-19 pandemic suggested that exposure to air pollution increased the likelihood of contracting COVID-19 and worsened outcomes for those who became ill. The validity of these findings was uncertain, however, as few studies used highly accurate exposure models incorporating individual-level data on patient characteristics and risk factors. Although the COVID-19 public health emergency has ended, the disease continues to pose substantial risks to individual and population health. At the time of this writing, nearly 35,000 individuals per week are hospitalized with COVID-19 in the United States, and the weekly number of COVID-19-related deaths ranges from 900 to 1,400.<sup>4</sup>.</p><p><strong>Methods: </strong>In this study, we investigated relationships between ambient air pollution and COVID-19-related outcomes, including incidence, severity, mortality, and long COVID conditions. We used advanced models to estimate exposures, incorporating numerous air pollutants, particle species, and wildfire emissions. We used administrative COVID-19 data and several cohorts of patients from a large health system, and each was formed to evaluate different hypotheses.</p><p><p>Daily air pollution exposures for Southern California were estimated with high spatial and chemical resolution, using a combination of land use regression and chemical transport models for the years 2016, 2019, and 2020. Exposure variables included ozone (O<sub>3</sub>), nitrogen dioxide (NO<sub>2</sub>), fine particulate matter (PM) ≤2.5 μm in aerodynamic diameter (PM<sub>2.5</sub>mass), ultrafine PM ≤0.1 μm in aerodynamic diameter (PM<sub>0.1</sub>), and major sources or chemical components of PM in each size fraction. Exposures for multiple study populations were investigated using statistical analysis methods to test for associations with COVID-19-related outcomes, including the following.</p><p><p>• COVID-19 cases (N = 773,374) and deaths (N = 14,311), by age, race, and sex, for 308 ZIP codes in Los Angeles County between June 19 and January 3, 2021. A negative binomial regression was performed for both individual and multiple ambient air pollutants to evaluate their associations with COVID-19 incidence and mortality.</p><p><p>• Patients with COVID-19 who were admitted to Kaiser Permanente Southern California (KPSC) ","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 238","pages":"1-97"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13077763/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147679385","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":"Early-Life Air Pollution Exposure Is Associated with the Infant Gut Microbiome and Fecal Metabolome in the First Two Years of Life.","authors":"T L Alderete, E A Holzhausen, D Liang, R B Jones, F Lurmann, M I Goran, H H Chang, J A Sarnat","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Obesity is a major public health concern because it increases the risk of numerous diseases, including cardiovascular disease and type 2 diabetes. Ambient and near-roadway air pollution has been associated with childhood obesity risk, independent of diet and physical activity. However, the biological mechanisms underlying these relationships remain unclear. Based on our previous work and existing literature, we hypothesized that exposure to air pollutants alters the developing infant gut microbiome and fecal metabolome, with implications for childhood obesity risk. In this study, we aimed to determine whether prenatal or early-life exposure to ambient air pollution and near-roadway air pollution is associated with the gut microbiome and fecal metabolome during the first 2 years of life.</p><p><strong>Methods: </strong>Our analysis had two components, both of which examined participants from the Southern California Mother's Milk Study, a Latino cohort in which we collected detailed information regarding maternal and child health during the first 24 months of life. Residential-based estimates of exposure to ambient particulate matter (particulate matter ≤2.5 µm and ≤10 µm in aerodynamic diameter: PM<sub>2.5</sub> and PM<sub>10</sub>, respectively), nitrogen dioxide (NO<sub>2</sub>), and ozone (O<sub>3</sub>), as well as near-roadway air pollution (NO<sub>x</sub>), were modeled using residential address histories. High-throughput metagenomics and metabolomics were performed on stool samples collected at 1, 6, 12, 18, and 24 months of age. Overall, our sample included 207 unique individuals with gut microbiome data and 127 unique individuals with fecal metabolomics data. In the first analysis component, we examined the cross-sectional associations of pre- and postnatal exposure to ambient and near-roadway pollutants with the infant gut microbiome and fecal metabolome at 1, 6, 12, 18, and 24 months of age. In the second analysis component, we examined the longitudinal associations of pre- and postnatal exposure to air pollutants with the trajectory of the developing infant gut microbiome and fecal metabolome.</p><p><strong>Results: </strong>Our findings indicate that exposure to air pollutants during prenatal and postnatal periods is associated with significant changes in the developing gut microbiome and its metabolic output, as evidenced by perturbations in the fecal metabolome. These molecular alterations were evident in both cross-sectional and longitudinal analyses. The results suggest that early-life exposure to air pollution can disrupt the developmental trajectory of the gut microbiome, potentially leading to changes with substantial health implications. These findings underscore the importance of mitigating air pollution exposure during critical developmental periods to protect and promote gut health and overall well-being in infants.</p><p><strong>Conclusions: </strong>We identified gut microbes and fecal me","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 237","pages":"1-58"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13077761/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147679438","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":"Traffic-Related Air Pollution and Birth Weight: The Roles of Noise, Placental Function, Green Space, Physical Activity, and Socioeconomic Status (FRONTIER).","authors":"P Dadvand, J Sunyer, I Rivas, M D Gómez-Roig, E Llurba, M Foraster, G Arévalo, L Barril, M Bustamante, X Basagaña, M Cirach, A Domínguez, T Galmés, M Gascon, J Lao, E M Gallego, T Moreno, M J Nieuwenhuijsen, C Persavento, B Raimbault, X Querol, C Tonne","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>FRONTIER aimed to provide a robust and comprehensive evaluation of the impact of maternal exposure to traffic-related air pollution (TRAP) on fetal growth. Toward this aim it (1) disentangled the effects of noise as a co-exposure; (2) identified the relevant window(s) of vulnerability for this impact; (3) evaluated its modification by household and neighborhood level socioeconomic status (SES), stress, physical activity, and the timing of conception and delivery in relation to the COVID-19 pandemic lockdown; (4) elucidated the role of placental function as an underlying mechanism; and (5) explored the potential of urban tree canopies and green spaces to mitigate it.</p><p><strong>Methods: </strong>FRONTIER established a new pregnancy cohort of 1,080 pregnant women in Barcelona, Spain - Barcelona Life Study Cohort (BiSC). Fetal growth was characterized by anthropometric measures at birth, together with ultrasound-based trajectories of fetal development. We developed an innovative exposure assessment framework integrating objective data on time-activity patterns with dispersion, land use regression, and hybrid models, with campaigns of personal and home-outdoor air pollution monitoring to estimate maternal exposure levels as well as inhaled dose of black carbon (BC), nitrogen dioxide (NO<sub>2</sub>), fine particulate matter (PM<sub>2.5</sub>), and PM<sub>2.5</sub> copper, iron, and zinc in the main microenvironments for pregnant women (home, workplace, and commuting routes). We also assessed maternal exposure to noise by integrating measurements at participants' homes and outdoors using noise monitors with modeled microenvironmental noise levels, data on noise sensitivity, annoyance, and protections against noise. We developed single- and multipollutant models to evaluate the impact of TRAP exposure and inhaled dose on fetal growth while also correcting for the exposure measurement error. We further evaluated the modification of associations by SES, stress (cortisol levels and perceived stress), physical activity (objective and subjective measures), their mitigation by urban greenness and canopy volume, and their mediation by Doppler ultrasound measures of placental function.</p><p><strong>Results: </strong>We found that higher pregnancy exposure to NO<sub>2</sub>, BC, PM<sub>2.5</sub>, and PM<sub>2.5</sub> copper and iron contents, particularly at home and all microenvironments combined, were generally associated with lower birth weight, higher risk of small for gestational age (SGA), and a decelerated trajectory of fetal growth, although some of these associations were not statistically significant. These associations appeared to be stronger for mothers with higher SES and those with higher objective measures of psychological stress. For the COVID-19 pandemic and physical activity, as effect modifiers, and urban greenness and canopy cover, as effect mitigators, we observed mixed patterns. In multipollutant model","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 236","pages":"1-97"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13057358/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147635107","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":"Using Geoscientific Analysis and Community Engagement to Analyze Exposures to Potential Groundwater Contamination Related to Hydrocarbon Extraction in Southwestern Pennsylvania.","authors":"J Baka, S L Brantley, T Wen, L Xue, S Shaheen, O Harrington","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Community concerns about the potential health effects of energy development have grown in recent years. This project evaluated the links between unconventional oil and gas development (UOGD) and potential water contamination in Beaver, Greene, and Washington counties of southwestern Pennsylvania (SW PA). This region, with its long history of hydrocarbon development, including coal mining and conventional oil and gas development, has many overlapping sources of potential contamination. Additionally, it is one of the most active UOGD regions globally. As the study progressed, we extended many of our statistical investigations of groundwater in SW PA to the entire state.</p><p><strong>Methods: </strong>We used statistical analysis to isolate the influences of geogenic and anthropogenic processes on groundwater chemistry and to identify potential linkages between UOGD and water contamination using a groundwater chemistry dataset of over 7,000 samples in SW PA, each with approximately 40 reported chemical analytes. We primarily targeted contamination by salt species found in brines. We conducted six community focus groups in the tri-county region during the summers of 2022 and 2023, which helped identify areas of community concern and interpret our preliminary findings. The focus groups highlighted wastewater mismanagement as a key area of community concern, which we examined in our geoscience analysis. Where possible, we also extended our statistical analysis to the entire state (28,609 groundwater quality analyses) so we could assess the effect of different land uses and geology on water quality.</p><p><strong>Results: </strong>Across the SW PA region, we observe small but statistically significant increases in barium (Ba) and strontium (Sr) in groundwater within 1 km of UOGD, with higher concentrations associated with greater proximity to and density of unconventional oil and gas (UOG) wells. Statistical inferences from the groundwater data point to spills of briny wastewaters on UOG well pads as the likeliest explanation for these increases. For example, Ba and Sr have an even stronger relationship with the locations of spill-related violations at UOG well pads. We found a statistically significant increase in salt concentrations near wastewater impoundments that are no longer in operation because of reprimands by the state regulator and environmental violations. These relationships persist even after better controlling for other geogenic and anthropogenic salt sources using a fixed-effects model. The information gathered from the focus groups suggests that communities are most concerned about potential radiation exposure from UOGD wastewater management, which may increase cancer risks. The geoscientific analysis does not reveal evidence across the region of increased concentrations of species associated with radiation risks in groundwater related to UOGD. This lack of evidence is partly because few groundwater an","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 233","pages":"1-50"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13036856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147583202","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":"Measuring and Modeling Air Pollution and Noise Exposure Near Unconventional Oil and Gas Development in Colorado.","authors":"J L Collett, D Pan, L McKenzie, D Zimmerle, W Zhang, Y Zhou, Seongjun Kim, I-T Ku, A Sullivan, J Pierce, W Allshouse, S Levine, G P Duggan, E Rimelman","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Rapid growth in unconventional oil and gas development (UOGD), driven by improvements in directional drilling and hydraulic fracturing technologies, has made the United States the world's largest producer of oil and natural gas. Rapid UOGD expansion in Colorado's Denver-Julesburg (DJ) Basin, often intersecting with a growing population, has elevated local concerns about noise and air quality impacts. Independent near-pad observations of hazardous air pollutants (HAPs) exposure and noise are uncommon, particularly during well drilling and completions, where evolving technologies and practices continue to alter emissions. The chief goals of this study were to identify potential impacts of UOGD HAPs emissions on nearby communities, characterize A- and C-weighted noise impacts from UOGD operations, and contextualize air and noise pollution measurement and modeling results at health-relevant temporal and spatial scales. Our focus was on the DJ Basin, where a changing regulatory environment has driven innovation to better protect human health and the environment, and past observations facilitate examining whether new operational practices have reduced impacts.</p><p><strong>Methods: </strong>Air quality and noise impacts of UOGD operations conducted by three major DJ Basin operators were studied at four large well pads at three locations across the basin. Studied operations included well drilling, hydraulic fracturing, coiled tubing/millout operations, flowback, and early production. Methane and speciated volatile organic compound (VOC) measurements were made at near-pad and background locations to characterize increases in concentrations associated with specific UOGD activities. Air dispersion modeling was conducted to assess impacts as a function of distance from well pad operations. A- and C-weighted noise levels were monitored at multiple locations.</p><p><strong>Results: </strong>Near-pad concentration increases of UOGD-related VOCs were most prominent on short timescales, with the most concentrated plumes often one to two orders of magnitude more concentrated than regional background concentrations but typically persisting for less than an hour at a given location. Benzene and, during drilling operations, n-nonane levels came closest to their respective chronic noncancer inhalation health guideline values (HGVs) but remained well below these levels. One-hour benzene levels exceeded 9 parts per billion by volume (ppbv), the acute HGV, on several occasions during different operational phases. Analyses of VOC emissions from specific operational practices provide the first estimate of speciated VOC emission rates from coiled tubing/millout operations, revealed increased emission of C<sub>8</sub>-C<sub>10</sub> n-alkanes from use of low-odor synthetic drilling muds, and indicated that implementation of closed-loop, tankless fluid-handling systems can reduce flowback emissions of benzene by more than 98% relative to ot","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 232","pages":"1-62"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13036433/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147583188","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":"Robust Statistical Approaches to Understanding the Causal Effect of Air Pollution Mixtures.","authors":"J Antonelli, H Shin, S Kang, A Franks, M Audirac, D Braun","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Most existing epidemiological evidence on the health effects of air pollution has focused on single-pollutant analyses, although recent research has increasingly emphasized estimating the effects of multiple exposures simultaneously. In this report, we used causal inference methodology to highlight four impediments to analyses with multiple exposures: (1) there is little information in the data to estimate effects typically of interest, (2) the effects of air pollution mixtures can be heterogeneous, (3) exposure assessment using an individual's home location can be problematic when daily mobility takes them to areas of different exposure levels, and (4) bias due to unmeasured confounding. The objectives of this report were to address these four concerns through the development of rigorous statistical methodology and to provide a corresponding case study that examines the health effects of air pollution in the Medicare cohort in the United States.</p><p><strong>Methods: </strong>The statistical methodology developed in this report improves the analysis of environmental mixtures in two distinct ways. First, our results highlight inherent difficulties, which require careful consideration in any study of the health effects of multiple exposures. Second, we developed a statistical methodology that broadens the scope of questions that can be answered in analyses of air pollution mixtures and can increase the policy relevance of evidence obtained from epidemiological studies using multiple exposures. Additionally, we illustrated the aforementioned approaches in a nationwide study of the health effects of air pollution in the US Medicare population, extending the existing evidence on the health effects of air pollution within this cohort.</p><p><strong>Results: </strong>In specific aim 1, we found that quantities typically targeted in studies with multiple exposures are difficult to estimate from the observed data alone, as they frequently rely on model-based extrapolation, which can provide unreliable findings. We presented alternative strategies that provide policy-relevant evidence of health effects, while avoiding issues caused by extrapolation. In specific aim 2, we found that the adverse effects of particulate matter ≤2.5 μm in aerodynamic diameter (PM<sub>2.5</sub>) components are heterogeneous and that these effects are more pronounced in areas with lower socioeconomic status. Specific aim 3 studied the mobility of individuals and found that ignoring mobility can bias health effects, although typically toward the null of no exposure effect. Incorporating mobility in the Medicare cohort did not lead to substantially different findings; however, accounting for mobility tended to increase the magnitude of estimated health effects. In specific aim 4, we developed a methodology for assessing robustness of health effects to unmeasured confounding bias and found that there is robust evidence overall of a harmful effect ","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 234","pages":"1-63"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13047131/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147610739","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 Source Contributions to Air Quality and Noise in Unconventional Oil Shale Plays.","authors":"Meredith Franklin, Gunnar Schade, Detlev Helmig, Lara Cushing, Jill Johnston","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Unconventional oil and gas development (UOGD<sup>3</sup>) has enabled the exploration of previously inaccessible or uneconomic oil and gas resources in shale rock, resulting in thousands of extraction sites across the landscape, many near people's homes. Human exposure to air pollution and noise related to these activities poses a health risk. This study focused on characterizing air pollutants, greenhouse gas emissions, airborne radioactivity, and noise associated with UOGD in two shale production basins.</p><p><strong>Methods: </strong>During one year of stationary air monitoring in Loving, New Mexico, in the western part of the Permian Basin (PB), we characterized the magnitude, frequency, and duration of UOGD-related emissions at temporal scales from 1 minute to seasonal. Continuous monitoring was performed for meteorological variables, near-surface ozone, nitrogen oxides (NO<sub>x</sub>), sulfur dioxide, hydrogen sulfide, 20 speciated volatile organic compounds (VOCs) in the ethane to octane volatility range, and noise. Airborne radioactivity was measured in the gas and particle phases. Source apportionment was performed using nonnegative matrix factorization (NMF). To disentangle sound frequencies, we developed spectrograms and conducted machine learning regression to analyze sound sources and relationships to air pollutants. A network of passive hydrocarbon samplers that collected weekly measurements of 15 hydrocarbons was established throughout populated regions of both the PB and Eagle Ford Shale (EFS) areas to measure regional pollutant concentrations and their spatial gradients around UOGD. Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire (VNF) data were acquired to quantify gas flaring activity throughout the region during our field measurement period. VNF flares and estimated flare gas volume were linked to the stationary air quality measurements to examine associations.</p><p><strong>Results: </strong>Most of the monitored primary air pollutants showed high variability, with frequent concentration spikes that exceeded background mole fractions by up to three orders of magnitude. The frequency of concentration spikes, their maximum mole fractions, and averaged metrics (hourly, 8-hour, 24-hour, and annual) were higher than those reported from mostly urban comparison sites. Near-surface ozone measurements confirmed that this area of the PB is in nonattainment of the ozone national ambient air quality standard (NAAQS), exceeding the 70 ppb threshold more than 30 days of the year, and that this nonattainment is driven by UOGD-related emissions of VOCs and NO<sub>x</sub>. The highest ozone values occurred during conditions of high temperatures, dry air, and slow advection of air masses across the PB from the south-southeast. VOC monitoring showed dominant impacts from saturated hydrocarbons, and associated NMF analysis identified five emission sources: a UOGD-related hydrocarbon source, two gas","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 231","pages":"1-71"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13006887/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147500915","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":"How Do Household Energy Transitions Work?","authors":"J Baumgartner, S Harper, C Barrington-Leigh, C Brehmer, E M Carter, X Li, B E Robinson, G Shen, T J Sternbach, S Tao, K Xue, W Yuan, X Zhang, Y Zhang","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Since 2015, thousands of rural and peri-urban villages across Beijing and northern China have been treated by a household Clean Heating Policy (CHP) that banned household coal burning and subsidized the costs of electric heaters and electricity. Whether this large-scale policy was successful in improving air quality and health remains an important and unresolved question. We estimated the effects of the CHP policy on air quality and cardiopulmonary health in Beijing villages and quantified how much of the policy's effects on health were mediated by changes in air pollution and indoor temperature.</p><p><strong>Methods: </strong>In winter 2018-2019, we enrolled 1,003 participants in 50 Beijing villages that were eligible for, but not currently treated by, the CHP and followed them over four consecutive winter data collection waves. In waves 1, 2, and 4, we administered questionnaires and measured participants' anthropometrics, blood pressure (BP), airway inflammation (fractional concentration of exhaled nitric oxide [FeNO]), and 24-hour personal exposure to fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter [PM<sub>2.5</sub>]). Fasting whole blood samples were obtained at clinic visits in waves 1 and 2 for analysis of glucose, lipid profile, and markers of inflammation and oxidative stress. We attempted to contact all prior participants in each follow-up wave. If a previously enrolled participant was not at home or refused subsequent participation, staff first tried to randomly recruit an eligible participant from the same household. If this was not possible, village guides helped field staff to enroll a new participant from a new household using the same sampling procedures as the baseline. Wintertime outdoor PM<sub>2.5</sub> was measured in all four waves, and wintertime indoor PM<sub>2.5</sub> was measured in waves 2, 3, and 4. Indoor temperature was measured in all waves. The PM<sub>2.5</sub> filters were analyzed for their mass, black carbon (BC), and chemical composition, which were used for source apportionment. To estimate the impacts of the policy, we used a difference-in-differences design that accommodated the staggered rollout of the CHP. We used \"extended\" two-way fixed effects models and marginal effects to quantify the effect of the policy on air pollution and health outcomes. We further evaluated whether villages treated by the policy in different years responded differently to the policy and whether the observed health impacts of the policy were mediated through changes in air pollution or home (indoor) temperature.</p><p><strong>Results: </strong>We enrolled a total of 1,438 participants from 1,236 households during our four study waves. At baseline (wave 1), the mean participant age was 60 years old (standard deviation [SD] = 9.2), 60% of participants were female, and most participants (63%) worked in agriculture. Geometric mean personal exposures to PM<sub>2.5</sub> wer","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 235","pages":"1-65"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051260/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625018","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":"REACH-OUT: Race, Ethnicity, and Air Pollution in COVID-19 Hospitalization OUTcomes.","authors":"J A Stingone, S Lovinsky-Desir, S Kannoth, M Shafiq, C Zhang, S Albrecht, A Azan, E C Chambers, M Qian, P Sheffield, A B Thompson, J W Baidal","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Determining whether chronic exposure to air pollution contributes to observed disparities in COVID-19 outcomes requires integrating multiple determinants of patient vulnerability to COVID-19, given the complex interactions that contribute to health disparities. Exposure to adverse social and structural factors heightens vulnerability to environmental exposures, potentially resulting in increased risk of unfavorable COVID-19 outcomes. Additionally, as populations are often exposed to various co-occurring adverse factors in the setting of disinvested neighborhoods and communities, examining such factors individually may not be sufficient to fully understand how they may modify the effects of air pollutant exposures. In an effort to explain COVID-19-related disparities observed in New York City (NYC<sup>3</sup>), this study aimed to estimate the effect of chronic air pollutant exposures on the risk of COVID-19 morbidity and mortality and to determine whether these effects vary by neighborhood-level vulnerability as defined by social and structural factors.</p><p><strong>Methods: </strong>We used harmonized electronic health record (EHR) data from five healthcare systems in NYC to derive a study population of hospitalized or emergency department (ED) patients diagnosed with COVID-19 from March 1, 2020, through February 28, 2021, who had a NYC zip code of residence. To reduce potential selection bias, we also constructed a subset of the study population restricted to patients with residential zip codes in the typical catchment area of the hospitals affiliated with the EHR data repository. We estimated air pollutant concentrations for fine particulate matter (PM<sub>2.5</sub>), nitrogen dioxide (NO<sub>2</sub>), black carbon (BC), and ozone (O<sub>3</sub>) by using zip code-level 11-year averages based on data from the 2009-2019 New York City Community Air Survey. For each pollutant, we constructed Cox proportional hazards models to estimate the hazards of fatality (i.e., dying from COVID among individuals with COVID) and hospital length of stay. Additionally, for each pollutant, we constructed Poisson regression models to estimate RRs (RRs) for acute respiratory distress syndrome (ARDS), pneumonia, mechanical ventilation, and dialysis during hospitalization and risk of hospitalization among ED patients. Models were adjusted for age, sex, body mass index, smoking status, history of chronic disease, and a neighborhood environmental vulnerability index (NEVI). Interaction terms were used to evaluate effect modification between pollutant exposures and the NEVI metric. Additionally, we conducted supplementary analyses to determine the joint effects of air pollution and pre-existing chronic diseases and whether those relationships varied by NEVI tertile. To supplement the fatality analysis, we conducted an excess mortality analysis among the full urban population using all-cause mortality data from public health records for","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 230","pages":"1-55"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12663533/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145643693","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":"Accounting for Mobility in Air Pollution Exposure Estimates in Studies on Long-Term Health Effects.","authors":"K de Hoogh, B Flückiger, N Probst-Hensch, D Vienneau, A Jeong, M Imboden, A Karsies, S Baruth, D de Ferrars, O Schmitz, M Lu, R Vermeulen, K Kyriakou, A Ndiaye, Y Shen, D Karssenberg, G Hoek","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Large-scale epidemiological studies investigating long-term health effects of air pollution can typically only consider the residential locations of the participants, thereby ignoring the space-time-activity patterns that likely influence total exposure. People are mobile and can be exposed to considerably different levels of air pollution or air pollution mixtures when inside versus outside, commuting, recreating, or working. Neglecting these mechanisms in exposure assessment may lead to incorrect distributions of exposure over the population, which may, subsequently, lead to incorrect exposure-health relations in epidemiological studies. In this study, we investigated whether a more sophisticated mobility-enhanced exposure assessment would lead to different exposure predictions and health effect estimates compared with using a residential-based exposure.</p><p><strong>Methods: </strong>Agent-based modeling (ABM<sup>3</sup>) was used to model mobility patterns in Switzerland and the Netherlands based on travel survey information. Hourly air pollution surfaces of nitrogen dioxide (NO<sub>2</sub>) and fine particulate matter (PM<sub>2.5</sub>) developed separately for the Netherlands and Switzerland, for weekdays and weekends, were overlaid with the ABM data to extract exposures. These air pollution exposures were assigned to two adult cohorts in Switzerland - the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) and the Swiss National Cohort (SNC) - and the European Prospective Investigation into Cancer study adult cohort in the Netherlands (EPIC-NL). Exposures were assigned based on (1) residential address location only (residential-based) and (2) residential and work address locations plus mobility (mobility-enhanced). In the case of SAPALDIA, known work address locations were available and additionally used. Associations with health outcomes (natural and cardiovascular mortality, coronary and stroke events, blood pressure, and lung function) in the three cohorts were investigated. To evaluate the performance of the ABM, we collected GPS readings from 489 participants in Switzerland and 189 participants in the Netherlands in tracking campaigns. The participants recorded GPS readings, using both a wearable GPS recording device and a mobile phone app while also recording their time-activity in the app diary.</p><p><strong>Results: </strong>We successfully developed mobility-enhanced exposures for over 3 million participants, including an assessment of uncertainty. We found a good agreement between exposures estimated with the app and the GPS tracker, supporting the scalability of the approach. We evaluated the ABMs with GPS and time-activity data collected independently in tracking campaigns that included almost 700 participants from selected areas in the two countries. For these participants, the exposures based on GPS measurements versus those derived from ABM showed a moderat","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 229","pages":"1-60"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12661506/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145643742","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}