Environmental Health Perspectives

Climate change has led to more frequent individual and concurrent drought and wildfire smoke events in the U.S., yet whether their concurrence adds to health burden remains understudied. We assessed the frequency of these events, developed a Two-Step Individual and Added Effect Estimation (TIAE) Model to evaluate their effects, and estimated the attributable mortality across 3,103 U.S. counties from 2007 to 2023. We identified annual averages of 3,630 county-months ([~]110,342 county-days) of drought, 14,049 county-days of wildfire smoke, and 980 county-days of concurrent exposure. Both individual events were significantly associated with increased all-cause mortality, with a significant added effect observed during concurrent days. We estimated 6,576 (95% CI: 3,990, 9,155), 10,465 (95% CI: 6,642, 14,261), and 469 (95% CI: 256, 682) annual deaths attributable to drought, wildfire smoke, and their added effect, respectively, with a higher burden in counties with higher overall social vulnerability index. These findings call for targeted measures to address the burden from drought, wildfire smoke, and their concurrence.

Transcriptomic responses to wildfire smoke are difficult to study given the unpredictability of wildfires and the challenges of collecting blood during active disasters. To overcome these challenges, we developed a flexible study design leveraging homeRNA, our at-home blood collection and RNA stabilization kit. Between June 2021 and April 2022, 58 participants across 10 U.S. states collected 635 blood samples before, during, and after wildfire events. This responsive approach captured three exposure groups: high exposure in Okanogan County, Washington, medium exposure from transported smoke, and low exposure. During the 10-month study, 93% of participants (n=54/58) returned at least 6 samples. In a preliminary exploratory analysis, we analyzed 770 genes with a Nanostring panel from nine participants (6 high, 3 low-medium exposure) using the BloodGen3 framework. In the high exposure participants, we observed trends toward overexpression of inflammation (inflammation aggregates A33 and A35, and modules M13.1 and M13.12), with concurrent underexpression of adaptive immune responses (lymphocytic aggregates A1 and A6, B cell module M13.18, T cell modules M16.24 and M15.38). This study establishes that homeRNA enables flexible, responsive sampling during disasters, overcoming traditional logistical barriers to capture time-sensitive biological data across dispersed populations.

There are large differences in premature mortality in the USA by racial/ethnic, education, rurality, and social vulnerability index groups. Using existing concentration-response functions, particulate matter (PM2.5) air pollution, population estimates at the tract level, and county-level mortality data, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in mortality attributable to PM2.5 were consistently more pronounced between racial/ethnic groups than by education, rurality, or social vulnerability index, with the Black American population having by far the highest proportion of deaths attributable to PM2.5 in all years from 1990 to 2016. Over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic White population was attributable to PM2.5 in the years 2000 to 2011.

BackgroundEnvironment-wide association studies (ExWAS) offer a systematic approach to identifying chemical biomarker-health outcome associations, yet few have applied rigorous multi-stage validation. MethodsWe screened 92 chemical biomarkers against 48 health outcomes in NHANES 2017-2018 (2,796 tests across four screening rounds; not all chemicals were crossed with all outcomes). Associations passing an initial FDR screen were subjected to cross-cycle validation in NHANES 2015-2016--the primary inferential safeguard given the adaptive screening design--followed by dose-response analysis and multiple sensitivity specifications. Survey-weighted regression models adjusted for age, sex, race/ethnicity, poverty-income ratio, BMI, and smoking. ResultsOf 26 associations passing FDR correction, 21 were testable in cross-cycle validation; of these, 15 (71%) replicated with concordant direction and p < 0.05 in a temporally independent NHANES 2015-2016 sample. Of these 15, 14 remained robust after analyte-specific sensitivity checks; urinary creatinine adjustment identified one association (iodine-BMI) as a dilution artifact. Two novel findings emerged: dimethylarsonic acid with uric acid ({beta} = 0.20 mg/dL per log-unit DMA, 95% CI: 0.15-0.26) and urinary perchlorate with BUN ({beta} = 1.21 mg/dL per log-unit perchlorate, 95% CI: 0.97-1.45); a third high-novelty association (methylmercury-waist circumference) is likely explained by fish consumption patterns. ConclusionsMulti-stage ExWAS with cross-cycle validation identified 14 robust chemical-health associations. Two novel findings--DMA-uric acid and perchlorate-BUN--survived all sensitivity checks and warrant prospective investigation.

We report small-sample evidence from a randomized experiment among a set of urban Ecuadorian households who owned both electric induction and gas stoves. We randomly assigned households to cook only with one stove during a prescribed two-day monitoring period, and then cook only with the other stove in a subsequent two-day period. The order of stove use was randomized, and air pollution was measured during each period. We found that mean 48-hour personal NO2 exposure was 9.9 ppb higher (95% CI, 4.5-15.3) -- a 50% increase over the 48-hour induction mean -- when households were randomized to gas as compared to induction. Mean kitchen area NO2 concentrations were 1 ppb higher (95% CI, 0.4-2.1) (a 6% increase) and mean personal PM2.5 exposure was 11 gm-3 higher (95% CI, -0.1-22.8) (a 44% increase) during study periods when randomized to gas. We use time-resolved cooking and pollution data to illustrate that these differences are driven by LPG cooking, which was associated with a 5.0 ppb increase in 5-minute average NO2 kitchen area concentrations (95% CI, 3.4-6.7) and a 20.8 gm-3 increase in 5-minute average personal PM2.5 exposure (95% CI 8.9-32.6). In contrast, cooking with induction was not associated with changes to short-term NO2 kitchen area concentrations, though it was associated with short-term increased personal PM2.5 exposure (10.8, 95% CI, 5.7-15.9).

We review current knowledge on the trends and drivers of global wildfire activity, advances in the measurement of wildfire smoke exposure, and evidence on the health effects of this exposure. We discuss methodological issues in estimating the causal effects of wildfire smoke exposures on health. We conduct a systematic review and meta-analysis of the effects of wildfire smoke exposure on all-cause mortality and respiratory and cardiovascular morbidity. We conclude by highlighting high priority areas for future research, including leveraging recently-developed spatially and temporally resolved wildfire specific ambient air pollution data to improve estimates of the health effects of wildfire smoke exposure.

Mobile monitoring campaigns to estimate long-term air pollution levels are becoming increasingly common. Still, many campaigns have not conducted temporally-balanced sampling, and few have looked at the implications of such study designs for epidemiologic exposure assessment. We carried out a simulation study of fixed-site air quality monitors to better understand how different mobile monitoring designs involving short-term stationary measurements at fixed locations impact the resulting exposure surfaces. We used Monte Carlo resampling to simulate three archetypal monitoring designs using oxides of nitrogen (NOx) monitoring data from 69 regulatory sites in California: a year-around Balanced Design that sampled during all seasons of the year, days of the week, and all or various hours of the day; a temporally reduced Rush Hours Design; and a temporally reduced Business Hours Design. We evaluated the performance of each designs land use regression prediction model. The Balanced Design consistently yielded the most accurate annual averages; while the reduced Rush Hours and Business Hours Designs generally produced more biased results. A temporally-balanced sampling design is crucial for mobile monitoring campaigns aiming to assess accurate long-term exposure in epidemiologic cohorts. SynopsisAir pollution mobile monitoring campaigns rarely conduct temporally balanced sampling. We show that this results in biased annual average exposure estimates. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/21255641v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@126c8ddorg.highwire.dtl.DTLVardef@14d52e5org.highwire.dtl.DTLVardef@17d390dorg.highwire.dtl.DTLVardef@2cc3d1_HPS_FORMAT_FIGEXP M_FIG C_FIG

Environmental exposures are increasingly examined in relation to mental health, yet large-scale epidemiological analyses remain constrained by fragmented geospatial data, heterogeneous spatial and temporal resolutions, and privacy-preserving linkage requirements, limiting systematic investigation of multiple environmental domains at the population level. We present environMAP, a harmonised set of analysis-ready environmental exposure layers derived from open, global sources. environMAP spans the built environment, green and blue spaces, light exposure (solar radiation and night-time light), terrain, weather and extremes, and air pollution. We document data provenance, spatial buffers, preprocessing, projection alignment, and metadata, and provide a reproducible workflow for privacy-preserving linkage to cohort residential locations. To demonstrate utility, we linked environMAP to >200,000 adults in the German National Cohort (NAKO) and summarised self-reported lifetime doctor-diagnosed depression across exposure gradients using sex-stratified descriptive analyses. Gradients were interpretable and broadly consistent with prior evidence, supporting feasibility, scalability, and hypothesis generation. The framework is adaptable to other outcomes, cohorts, and regions.

BackgroundIn 2019, an explosion at the Philadelphia Energy Solutions Refinery, one of the largest urban oil refineries in the U.S., led to its shuttering and transition into redevelopment. Local fenceline communities, previously impacted by refinery operations, expressed concern about air toxics, particularly benzene, released during the decommissioning process. To monitor volatile organic compounds (VOCs), including benzene, in fenceline communities, we created THRIVEair, a partnership between environmental justice organization Philly Thrive and Drexel University scientists. Key goals of the project included community-responsive air monitoring, data democratization, and timely report-back of results. MethodsThrough an action-reflection-action approach, we co-designed a one-year VOC monitoring campaign from June 2023-June 2024, and data dissemination products, including fact sheets, Teach-Ins, and a public website. We monitored 37 VOCs using one-week integrated samples collected using passive thermal desorption tubes. Nine stationary sites were monitored weekly, and 11 additional sites were monitored on a rotating basis for two one-week sessions in summer and winter. ResultsOn average, we found that benzene concentrations were relatively low over the one-year monitoring period (mean for stationary sites: 1.32 {micro}g/m3, range = 0.30 - 9.04 {micro}g/m3), though spatial and temporal variability were evident. ConclusionThrough the air monitoring campaign design and implementation process, THRIVEair supported Philly Thrives goal of establishing an air monitoring network in neighborhoods impacted by the former refinery. By providing publicly available air quality data, THRIVEair results can be leveraged in Philly Thrives advocacy efforts.

Long-term exposure to air pollution has been associated with changes in levels of several metabolites measured in the peripheral blood. However, most work has been conducted in ethnically homogenous populations. We studied the relationship between the plasma metabolome and long-term exposure to three air pollutants: particulate matter (PM) less than 2.5 {micro}m in aero diameter (PM2.5), PM less than 10 {micro}m in aero diameter (PM10) and nitrogen dioxide (NO2) among 107 participants of the Washington Heights and Inwood Community Aging Project (WHICAP) in New York City. Plasma metabolomic profiles were generated using untargeted liquid chromatography coupled with high-resolution mass spectrometry. We estimated the association between each metabolic feature and predicted annual mean exposure to the air pollutants using three approaches: 1. A metabolome wide association study (MWAS) framework; 2. Feature selection using elastic net regression; and 3. A multivariate approach using partial least squares discriminant analysis. Additionally, we identified the pathways enriched by metabolic features associated with exposure through pathway analysis. The samples were collected from 1995 - 2015 and included non-Hispanic white, Caribbean Hispanic, and non-Hispanic Black older adults. Through the MWAS, we found 79 features associated with exposure to PM2.5 (false discovery rate at 5%) but none associated with PM10 or NO2. Pathway analysis revealed that PM2.5 exposure was associated with altered amino acid metabolism, energy production, and oxidative stress response. Six features were found to be associated with PM2.5 exposure through all three approaches, annotated as: cysteinylglycine disulfide, a diglyceride, and a dicarboxylic acid. Additionally, we found that the relationship between several features and PM2.5 exposure was modified by diet and metabolic diseases. These signals, identified in a neighborhood-representative older population, could help understand the mechanisms through which PM2.5 exposure can lead to altered metabolic outcomes in an older population. HIGHLIGHTSO_LILong-term exposure to PM2.5 is associated with altered plasma metabolic features in an aging population C_LIO_LIThese associations are modified by a dementia diagnosis, history of diabetes, APOE-{varepsilon}4 allele, and diet C_LIO_LIPathways related to energy production, amino acid metabolism, and redox homeostasis are associated with exposure to PM2.5 C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/22284045v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@1c77e99org.highwire.dtl.DTLVardef@4872ccorg.highwire.dtl.DTLVardef@68ccf8org.highwire.dtl.DTLVardef@68e45c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Millions of outdoor workers cannot avoid wildfire smoke, likely leading to inequalities in exposure and health risk. We characterized work-related exposure to wildfire PM2.5 for 3,108 contiguous US counties during 2006-2019. Despite experiencing less ambient exposure to wildfire PM2.5, counties with higher portions of non-Hispanic Black and Hispanic Americans experienced higher work-related exposure. We also find suggestive evidence that the effect of ambient smoke fine particulate matter (PM2.5) concentrations on all-cause mortality may differ by workplace exposure. These findings suggest that workplace exposures should be considered in wildfire smoke adaptation measures.

This protocol is reported in accordance with the SPIRIT 2025 guidelines for clinical trial protocols. IntroductionYoung children, from birth to age 5 y are particularly vulnerable to indoor air pollutants and respiratory pathogens. Portable air purifiers (or filtration) and upper-room ultraviolet germicidal irradiation (UVGI) are two widely used interventions with the potential to improve indoor air quality (IAQ) and reduce sick-related absences. However, a review of the literature revealed no real-world randomised studies evaluating their effectiveness in reducing young childrens sick-related absences in early care and education (ECE) classrooms. Methods and AnalysisThe OK-AIR study is a longitudinal, cluster-randomised 2x2 factorial trial conducted in Head Start centers using two implementation cohorts: Cohort 1 (five Head Start centers and 20 classrooms from 2023 to 2024) and Cohort 2 (11 centers and 59 classrooms from 2025 to 2026), with expanded inclusion of rural areas. Cohort 1 enrolled 204 children, 48 teachers and 5 site directors, and Cohort 2 enrolled 462 children, 97 teachers and 11 site directors. Within each center, four classrooms are randomised to: (1) control; (2) portable filtration; (3) upper-room ultraviolet germicidal irradiation (UVGI); or (4) both interventions. Cohort 2 was initially planned as a second factorial trial but was amended to a purifier-only design due to funding changes; details are provided in the protocol amendments section. We collect continuous IAQ data, including particulate matter (PM) with aerodynamic diameters [&le;]1 {micro}m (PM1), [&le;]2.5 {micro}m (PM2.5), [&le;]4 {micro}m (PM4), and [&le;]10 {micro}m (PM10); total volatile organic compounds (TVOCs) index; nitrogen oxides (NOx) index; carbon monoxide (CO), noise; temperature; and relative humidity, alongside daily child absences. Seasonal environmental surface swabs (dining tables and toilet flooring) are tested by Reverse-Transcriptase quantitative Polymerase Chain Reaction (RT-qPCR) for Influenza A/B, Respiratory Syncytial Virus (RSV), Human Parainfluenza Virus Type 3 (HPIV3), Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and Norovirus. IAQ monitoring is structured across Winter, Spring, Summer, and Fall, including designated baseline/off-period weeks to characterize temporal and seasonal variability in environmental measures across classrooms and centers. Multi-informant surveys (Director, Teacher, Parent) capture contextual factors, and childrens social-emotional development is assessed using teacher ratings on the Devereux Early Childhood Assessment (DECA). The primary outcome is the sick-related absence rate, analyzed as cumulative absences over the attendance year while accounting for clustering by school and classroom using generalized mixed-effects models. Secondary outcomes include childrens social-emotional ratings, IAQ metrics and pathogen detection rates; analyses of IAQ incorporate time/seasonal structure, and season-stratified absenteeism analyses will be treated as secondary/exploratory refinements. An economic evaluation will estimate incremental intervention costs and cost-effectiveness/cost-benefit (such as cost per sick-related absence day averted). Ethics and DisseminationThis study was approved by the Institutional Review Board (IRB) at the University of Oklahoma. Findings will be shared through peer-reviewed publications; presentations at local, state, and national conferences; research briefs developed for lay and policy audiences; and community briefings prioritizing the participating early childhood programs and communities. DisclaimerThe views expressed are those of the authors and do not reflect the official views of the Uniformed Services University or the United States Department of War. Strengths and Limitations of This StudyO_LIReal-world longitudinal cluster RCT: The study uses a rigorous longitudinal cluster-randomised 2x2 factorial design in real-world ECE settings. C_LIO_LICombined interventions: Interventions target both air filtration and disinfection, allowing for combined and comparative evaluation. C_LIO_LIObjective air-quality monitoring: Continuous monitoring of IAQ metrics provides objective and reliable data on environmental change. C_LIO_LIEnvironmental pathogen surveillance: qPCR on surface swabs yields an objective biological outcome to triangulate with IAQ and absences. C_LIO_LIComprehensive context and child measures: Multi-method and multi-reporter data collection includes Head Start attendance records, continuous air monitoring, pathogen detection, contextual surveys completed by center directors, teachers, and parents, and standardized social-emotional assessments (DECA) completed by classroom teachers. Head Start program records providing childrens longer-term health data available through Health Insurance Portability and Accountability Act (HIPAA) authorization. C_LIO_LIClustered/temporal complexity: Seasonal design accounts for variation over time but may introduce complexity in modeling temporal effects. C_LIO_LIPractical Implications: Study findings will have practical implications for Head Start and other ECE programs striving to maximize child attendance with cost effective strategies. C_LI

Background: Current chemical mixture approaches are largely data-driven without considering shared biological mechanisms among mixture components, highlighting the need for biology-informed approaches. Objectives: We constructed an integrated measure of a chemical mixture's oxidative stress potential and assessed its association with mortality in the US population. Methods: The sample comprised 4,574 adults ([&ge;] 20 years) from National Health and Nutrition Examination Survey (NHANES) 2005-2010. To obtain robust estimates, we performed 1,000 repeated random 50:50 splits into training and testing sets. In each training set, we used survey-weighted quantile g-computation to model serum gamma-glutamyl transferase (GGT), an oxidative stress biomarker, as a function of a 30-chemical mixture (blood metals, urinary polycyclic aromatic hydrocarbons (PAHs), pesticides, phenols/parabens, and phthalates), adjusting for sociodemographic, behavioral, and dietary factors. We then applied the fitted model from each training set to the corresponding testing set to derive the environmental risk score for oxidative stress (ERSOS), defined by predicted GGT values. Associations of ERSOS with all-cause, cardiovascular, and cancer mortality over 11 years of follow-up were estimated in the testing sets using survey-weighted Cox proportional hazards models and summarized across the 1,000 repeated splits. Results: Chemicals with the largest positive weights in quantile g-computation included mono-(2-ethyl-5-hydroxyhexyl) phthalate, mono-2-ethyl-5-carboxypentyl phthalate, 2-hydroxyfluorene, methyl paraben, and benzophenone-3; chemicals with the largest negative weights included mono-(2-ethyl-5-oxohexyl) phthalate and PAH metabolites (1-hydroxynaphthalene, 3-hydroxyphenanthrene, and 3-hydroxyfluorene). The median correlation between observed and predicted GGT in the testing sets was 0.43 (2.5th, 97.5th percentiles: 0.40-0.48). A one standard deviation increase in ERSOS was associated with a median hazard ratio of 1.60 (2.5th, 97.5th percentiles: 1.01-2.57) for cardiovascular mortality. No associations were found for all-cause mortality or cancer mortality. Discussion: The proposed survey-weighted quantile g-computation approach may help estimate biology-informed chemical mixture effects in complex survey data, supporting the potential utility for population-generalizable environmental mixture research.

Despite the substantial evidence on the health effects of short-term exposure to ambient fine particles (PM2.5), including increasing studies focusing on those from wildland fire smoke, the impacts of long-term wildland fire smoke PM2.5 exposure remain unclear. We investigated the association between long-term exposure to wildland fire smoke PM2.5 and non-accidental mortality and mortality from a wide range of specific causes in all 3,108 counties in the contiguous U.S., 2007-2020. Controlling for non-smoke PM2.5, air temperature, and unmeasured spatial and temporal confounders, we found a non-linear association between 12-month moving average concentration of smoke PM2.5 and monthly non-accidental mortality rate. Relative to a month with the long-term smoke PM2.5 exposure below 0.1 g/m3, non-accidental mortality increased by 0.16-0.63 and 2.11 deaths per 100,000 people per month when the 12-month moving average of PM2.5 concentration was of 0.1-5 and 5+ g/m3, respectively. Cardiovascular, ischemic heart disease, digestive, endocrine, diabetes, mental, and chronic kidney disease mortality were all found to be associated with long-term wildland fire smoke PM2.5 exposure. Smoke PM2.5 contributed to approximately 11,415 non-accidental deaths/year (95% CI: 6,754, 16,075) in the contiguous U.S. Higher smoke PM2.5-related increases in mortality rates were found for people aged 65 above. Positive interaction effects with extreme heat (monthly number of days with daily mean air temperature higher than the countys 90th percentile warm season air temperature) were also observed. Our study identified the detrimental effects of long-term exposure to wildland fire smoke PM2.5 on a wide range of mortality outcomes, underscoring the need for public health actions and communications that span the health risks of both short- and long-term exposure. Significance StatementThe area burned by wildland fire has greatly increased in the U.S. in recent decades. Short-term exposure to smoke pollutants emitted by wildland fires, particularly PM2.5, is associated with numerous adverse health effects. However, the impacts of long-term exposure to wildland fire smoke PM2.5 on health and specifically mortality remain unclear. Utilizing wildland fire smoke PM2.5 and mortality data in the contiguous U.S. during 2007-2020, we found positive associations between long-term smoke PM2.5 exposure and increased non-accidental, cardiovascular, ischemic heart disease, digestive, endocrine, diabetes, mental, and chronic kidney disease mortality rates. Each year, in addition to the well-recognized mortality burden from non-smoke PM2.5, smoke PM2.5 contributed to an estimated over 10 thousand non-accidental deaths in the U.S. This study demonstrates the detrimental effects of wildland fire smoke PM2.5 on a wide range of health outcomes, and calls for more effective public health actions and communications that span the health risks of both short- and long-term exposure.

BackgroundWaste incineration in Baltimore, USA, involves two major facilities: a municipal solid waste incinerator (WIN Waste) and the nations largest medical waste incinerator (Curtis Bay Medical Waste Incinerator). Both operate in socio-economically disadvantaged communities, raising concerns about cumulative environmental exposures and health disparities from hazardous air pollutants. MethodsWe estimated health impacts from available criteria incinerator emissions data (PM, NOx, SO2, CO). We used AERMOD to model ground-level pollutant concentrations, linked these to U.S. Census tracts, and monetized health damages using established relative risk and cost of illness data. Health disparities were evaluated by modeling incinerator-attributable mortality against the Social Vulnerability Index (SVI). FindingsIn 2024, the WIN Waste incinerator caused an estimated $53.8 million in health damages in Maryland and Washington DC. On average, the Curtis Bay Medical Waste Incinerator releases black smoke emissions for 52.5 minutes/day, a regulatory violation. The facility causes $36.9 million/year in health damages and is permitted to burn enough waste to cause up to $107.1 million/year; enforcing pollution controls at this site could prevent $13.8 million in annual harm in Baltimore. Combined, the two incinerators cause $97.0 million in damages annually. All-cause mortality from incinerator pollution was more common in communities with higher socioeconomic vulnerability. InterpretationDespite being required to install new pollution control equipment following community and regulatory pressure, the WIN Waste incinerator still causes significant health damages to Maryland and Washington DC. Meanwhile, repeated black smoke emissions from the Curtis Bay incinerator indicate that ongoing, uncontrolled pollution is also a major threat to public health in the region. Health damages from these incinerators disproportionately affect communities least able to bear the economic burden. Our conservative estimates highlight the need for urgent policy reforms, including stricter emissions monitoring, phasing out non-essential incineration, and ongoing cumulative impact assessments. FundingKJT and SD were funded by the University of Maryland Baltimore Provosts Climate Health & Resilience internship program. KJT was supported by a Point Foundation Internship & Professional Development Award and the Alpha Omega Alpha Carolyn L. Kuckein Student Research Fellowship. BS, MAA, and CDH were supported by the National Institute of Environmental Health Sciences (NIEHS) P30 Center for Community Health: Addressing Regional Maryland Environmental Determinants of Disease (CHARMED) [grant no. P30ES032756]. BS, MAA, and CDH were supported by the Johns Hopkins Community Science and Innovation for Environmental Justice (CSI EJ) Initiative. CDH was supported by the National Institute for Occupational Safety and Health (NIOSH) Education and Research Center [grant no. T42OH0008428]. GS and CS are affiliated with the Curtis Bay Community Association and South Baltimore Community Land Trust. The authors have no other conflicts of interest to report.

Background Prenatal exposure to pesticides and psychosocial factors often co-occurs, particularly in low- and middle-income settings, yet their joint effects on epigenetic age acceleration (EAA) in early life remain unknown. We investigated the joint associations of prenatal pesticides metabolites and psychosocial factors on EAA in the first five years of life in the South African Drakenstein Child Health Study. Methods In 643 mothers, we measured 11 urinary pesticide metabolites and seven psychosocial factors during the second trimester of pregnancy. Child DNA methylation was measured in whole blood at ages 1, 3, and 5 years. EAA was estimated using the Horvath, Skin & Blood Horvath (skinHorvath), and Wu epigenetic clocks. Longitudinal associations were estimated using generalized estimating equations, adjusted for confounders. Joint mixture associations were evaluated using weighted quantile sum regression (WQS) and quantile g-computation (QGCOMP). Results The joint prenatal exposure mixture was positively associated with Wu ({beta} per one quintile increase in the mixture [95% CI]: 0.41 years [0.15, 0.80]), skinHorvath (0.11 years [0.06, 0.16]), and Horvath EAA (0.31 years [0.20, 0.46]) over time using WQS. Psychosocial factors, particularly food insecurity, physical interpersonal violence, and stress biomarkers, contributed most to the total mixture effect for all clocks. Pyrethroid metabolites PBA and TDCCA were top pesticide contributors to Wu EAA. Pathway enrichment analyses of clock-specific CpGs revealed distinct biological architectures, with the Wu clock enriched for neurodevelopmental and immune pathways, and metabolic pathways for the Horvath clock. Discussion Joint prenatal exposure to pesticides and psychosocial factors was associated with increased EAA across early childhood, with psychosocial factors contributing the most to the total effect. These findings highlight the importance of assessing chemical and non-chemical stressors jointly and clock-specific biological interpretation in epigenetic aging research.

BackgroundOutdoor workers are particularly vulnerable to the adverse impacts of heat, but many studies focus on heat exposure in residential settings only. This leads to a limited understanding of the full mortality burden due to occupational heat exposures. Here, we aimed to improve estimates of the total, short-term mortality burden attributable to outdoor occupational heat exposure in the United States (US). MethodsWe developed a panel data set for 3,108 US counties during 2010-2019 by linking all-cause mortality among the working age population, derived from CDC WONDER, with the prevalence of workers exposed to outdoor occupational heat, which integrates data on wet bulb globe temperature, workplace activities, and employment counts. We developed a quasi-Poisson regression model adjusted for ambient temperature, total precipitation, and county and state-year fixed effects to estimate short-term excess deaths attributable to outdoor occupational heat exposure. FindingsNationwide, approximately 3.8% (95% CI: 2.5-5.8%) of all workers were annually exposed to dangerous wet-bulb globe temperatures. This outdoor occupational heat exposure resulted in approximately 9,800 (3,100-17,000) annual excess deaths in the working age population. An estimated 62% of excess deaths occurred in the most socially vulnerable counties despite accounting for 25% of workers. InterpretationThe mortality burden of occupational heat exposure is likely far larger than 39 officially reported annual deaths that the Bureau of Labor Statistics reports for this time period. The workplace should be an explicit focus of heat policies, advocacy, and adaptation measures. FundingUS Centers for Disease Control and Prevention/National Institute for Occupational Safety and Health.

AbstractO_ST_ABSImportanceC_ST_ABSGeneral responders of the World Trade Center (WTC) Health Program (WTCHP), who were uniquely exposed to chemical toxicants and extreme psychological stress during the 2001 terrorist attack, now experience a wide range of unusually prevalent health outcomes for a mid-aged population, including frailty, Post Traumatic Stress Disorder (PTSD), and depression. ObjectiveWe investigated whether these outcomes are associated with urban environmental exposures experienced in the two decades post 9/11. DesignProspective cohort study. SettingWTCHP general responders cohort. ParticipantsWe included 18,861 WTCHP general responders between the years 2003 to 2023 who took part in rescue, recovery, and clean-up tasks following the 9/11/2001 attack on the WTC. ExposuresWe evaluated the distinct and combined associations with annual fine particulate matter (PM2.5), temperature, and Green View Index (GVI) and assessed interactions with WTC-exposures. OutcomesWe assessed frailty using a validated index developed specifically for the WTCHP. We determined PTSD and depression status based on repeated test scores from validated tools administered during the monitoring visits. ResultsWe included 18,861 responders, 81.89% were males, and the mean age at entry was 47. Interquartile range increases in PM2.5 and temperature were significantly associated with increased frailty, PTSD, and depression scores, while greenness (GVI) was protective. A decile increase in the overall exposure mixture was associated with a 0.50% (95% confidence interval 0.08; 0.94) increase in frailty and a 0.10 unit (0.02; 0.18) increase in PTSD scores, primarily driven by temperature. Importantly, the exposure-mixture was associated with an increased risk of reaching a clinical threshold for PTSD (odds ratio: 1.013[1.001,1.024]). Finally, the associations between the exposure-mixture and mental health were significantly amplified among responders with high WTC-exposures, though no such modification was observed for frailty. Conclusion and relevanceExposures to heat and PM2.5 were associated with increased frailty, PTSD, and depression, while greenness exposure was protective. Responders who experienced more intense WTC exposures were more vulnerable to later-life environmental exposure-mixture effects on mental health. These findings may help explain the elevated burden of these conditions among WTCHP responders and suggest avenues for public health interventions including education on risk mitigation strategies.

BackgroundThe state of New York expects to receive $115 million in 2022 alone from the US Infrastructure Investment and Jobs Act to support the replacement of lead water service lines. ObjectivesTo determine the number and proportion of Potential Lead water service lines across New York City (NYC), and the association between racial/ethnic composition, housing vulnerability, and child lead exposure vulnerability with service line type (Potential Lead, Unknown) at the census tract level for N= 2,083 NYC tracts. MethodsWe used conditional autoregressive Bayesian Poisson models to assess the relative risk (median posterior estimates, and 95% credible interval, CrI) of service line type per 20% higher proportion of residents in a given racial/ethnic group, and per higher housing vulnerability and child lead exposure vulnerability index scores corresponding to the interquartile range. We also evaluated the associations in flexible natural cubic spline models. ResultsOut of 854,672 residential service line records, 136,891 (16.0%) were Potential Lead and 227,443 (26.6%) were Unknown. In fully adjusted models, higher proportions of Hispanic/Latino residents and higher child lead exposure vulnerability were associated with Potential Lead service lines in flexible spline models and linear models (RR 1.15, 95% CrI 1.11, 1.21, and RR 1.11, 95% CrI 1.02, 1.20, respectively). Associations were modified by borough; Potential Lead service lines were associated with higher proportions of non-Hispanic White and non-Hispanic Asian residents in the Bronx and Manhattan, and with higher proportions of non-Hispanic Black residents in Queens. DiscussionNYC has a high number of Potential Lead and Unknown service lines. Communities with a high proportion of Hispanic/Latino residents and those with children who are already highly vulnerable to lead exposures from numerous sources are disproportionately impacted by Potential Lead service lines. These findings can inform equitable service line replacement across NY state and NYC.

Copper (Cu) is an essential metal involved in neurobiological processes including energy metabolism and neurotransmission, yet dysregulated Cu levels may adversely affect brain health and olfactory performance. Although olfactory dysfunction has primarily been studied in older adults and neurodegenerative disease, adolescence is a critical period of brain maturation during which the olfactory system may be particularly vulnerable. This cross-sectional study examined associations between Cu exposure, olfactory bulb (OB) volume, and olfactory performance in 200 adolescents and young adults (64% female; ages 13 - 25) from the Public Health Impact of Metals Exposure cohort. Cu concentrations in blood, urine, hair, and saliva were measured using inductively coupled plasma mass spectrometry. T2-weighted magnetic resonance imaging scans estimated left, right, and total OB volumes using a three-stage deep learning pipeline. Olfactory performance was assessed using the Sniffin Sticks test. Weighted quantile sum regression evaluated associations between a Cu mixture index and OB outcomes, while standard linear regression models assessed individual Cu biomarkers. Models were adjusted for age and sex. A higher Cu index was associated with reduced left (Beta= -0.72, 95% CI [-1.42, -0.02]), right (Beta = -0.79, 95% CI [-1.43, -0.15]), and total OB volume (Beta= -1.55, 95% CI [-2.85, -0.25]), as well as lower odor threshold scores (Beta = -0.23, 95% CI [-0.42, -0.03]). Individual biomarkers were not independently associated with outcomes. These findings suggest that Cu exposure may adversely affect olfactory neurodevelopment during adolescence and highlight the importance of studying environmental exposures relevant to long-term neurological health.