Environmental Health Perspectives

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 ([≥] 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.

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.

While exposure to volatile organic compounds such as ethylene dichloride and vinyl chloride monomer is a well-established cause of liver disease, particularly hepatic hemangiosarcoma, characterizing real-world exposure profiles in communities surrounding industrial centers remains challenging. Calvert City, Kentucky (population ~2,500), provides a unique setting characterized by both active industrial emissions and legacy sources of air toxics. To address these complexities, this method paper describes the framework for the Biomonitoring and Environmental Assessment for Community Outreach and Neighborhood Safety (BEACON) study. By utilizing a novel, multi-dimensional exposure assessment strategy, BEACON aims to characterize air toxic exposures and provide actionable data for community health and safety. For the BEACON study, we will leverage Kentucky Department of Air Quality measures of air toxics, analyze urine samples in a small cohort of community volunteers, analyze community urine via wastewater in an adjacent community, geocode citizen odor reporting, assess blood markers in wildlife, survey small and large animal veterinarians in the area for anomalies in morbidity and mortality, and work with the regional health system to enhance vigilance for health issues associated with toxicants present in the area. In addition, blood samples will be collected at three time points and biobanked for future analyses. Efforts will be made to link this study to additional large-scale long-term cohorts where possible. Throughout the project, community engagement will play a critical role by raising awareness, fostering collaboration, and ensuring that the voices of affected residents are heard.

Background: Lead exposure is estimated to cause approximately 3.5 million premature deaths a year, yet the key ongoing sources of lead exposure are unclear. Methods: We estimated the contribution of dietary lead intake to global blood lead levels (BLLs) for 7-year-old children and 22-year-old adults by applying the All-Ages Lead Model (AALM) to calculate blood lead levels (BLLs) based on 25 total diet studies (TDS) that quantify dietary lead intake across 46 countries. Results: For children, the population-weighted average dietary lead intake in low- and middle-income countries (LMICs) (32.0 g/day) was found to be more than three times higher than in high-income countries (HICs) (9.3 g/day), and more than 10 times higher than the FDA reference level for children (2.2 g/day). The average impact on BLLs for children is estimated to be near 29 g/L in LMICs and near 12 g/L in HICs. Averaged across the TDS data, vegetables (27%) and cereals (24%) were found to contribute the most to dietary lead. Conclusions: While there are limitations associated with biokinetic modelling and the TDS data from LMICs, these results suggest that the contribution of dietary lead intake to global lead exposure is in the region of 40 to 50%, suggesting, in turn, that dietary lead intake is likely a major global driver of lead poisoning. Lead absorbed from the environment into food crops is expected to be the key driver of dietary lead. Current regulatory levels for maximum lead concentrations in foods (0.05-0.3 mg/kg) are out-of-date and may imply a dietary lead intake of 200 g/day, far higher than the FDA reference level (2.2 g/day). Collecting representative TDS data in high lead burden countries should be a priority. Further research is also recommended on upstream lead sources and pathways of lead uptake in plants, driving global food contamination.

Background: Environmental noise and air pollution are both shaped by road traffic and the built environment, and exposure assessment increasingly folds them into composite indices or proxies both by traffic exposure. Whether the two share a social distribution has rarely been tested against direct measurement of several exposures in the same communities, and community noise is almost always characterized by A-weighted levels alone, which discount low-frequency energy. Methods: At 176 sites across Rhode Island, spanning the contiguous urban area of Providence, Central Falls, and Pawtucket together with four rural municipalities, we measured the acoustic environment under A- and C-weighting (LAeq, LCeq), fine particulate matter (PM2.5), night-time illuminance, and relative humidity across four session types over roughly one year (704 site-sessions). Exposures were linked to census-tract composition (American Community Survey), and mixed-effects models were fitted for each of eight area-level markers of disadvantage, adjusting for campaign and session. Relative humidity was carried through the identical model as a negative control. Results: A-weighted noise was consistently higher in more disadvantaged tracts, rising with non-White, poverty, renter, and no-vehicle shares and falling with income and older-resident share (six of eight markers significant; 1.3 to 1.8 dBA per standard deviation; 6.6 dBA between the least and most racially diverse neighborhoods). C-weighted levels followed the same gradient on every marker and exceeded their A-weighted counterparts at block-group scale for renter occupancy and vehicle absence. Night-time illuminance was also socially patterned, whereas short-term PM2.5 was roughly an order of magnitude weaker and relative humidity showed no gradient. The acoustic gradient persisted within the urban core alone. Conclusions: Measured burden was carried by the acoustic environment, including its low-frequency component, and by night-time light, not by short-term particulates. The exposure metric and the averaging time determine which disparities are visible at all.

BackgroundThe cardiovascular system is significantly affected by exogenous factors, but understanding the risks posed by pharmaceuticals and environmental chemicals is restricted due to limited data availability. New approach methodologies (NAMs) apply in vitro, in chemico, and in silico methods to characterize hazard and risk, thus offering rapid, multiscale human biology-based strategies to overcome regulatory challenges and the potential to complement or replace animal testing for understanding chemical cardiovascular effects. MethodsIn the present study, we applied a systems-based workflow using physiologically based pharmacokinetic (PBPK) models to convert bioactive concentrations from >300 high-throughput screening (HTS) assays with cardiovascular-relevant molecular and cellular targets to human equivalent administered doses (EADs) for >800 substances with widespread human exposure potential. To derive human-relevant risk predictions, the in vitro activity-derived EADs were compared with human exposure estimates and in vivo points of departure (PODs) from toxicological animal studies. For a subset of chemicals, we applied a geospatial analysis to assess the combined risks for populations across regions of the US. ResultsThe combined HTS assay data, human exposure predictions, animal study-based PODs, geospatial exposure data, and PBPK modeling identified compounds with potential cardiovascular toxicity at relevant exposure levels. Personal care product ingredients, flame retardants, herbicides, pesticides, pharmaceuticals, and byproducts of various industrial processes were noted as agents of concern preferentially targeting endothelial cell signaling, nuclear hormone receptors, and other critical cardiovascular targets. Of the 859 chemicals assessed, in vitro CV-relevant assays were more risk protective than animal studies for 96.4% of the chemicals. A set of 17 chemicals had a log10 bioactivity exposure ratio (BER) below -2, indicating estimated human exposure more than 100-fold above the in vitro-derived bioactive dose. ConclusionsThis study establishes an integrative, multiscale framework linking molecular perturbations to population-level cardiovascular risk, enabling systematic identification of potentially cardiotoxic chemicals and the communities most vulnerable to their effects. By bridging mechanistic toxicology with pharmacokinetic modeling and epidemiologic context, this approach enhances the biological relevance and translational impact of human health risk assessment. This scalable, adaptable framework supports timely, evidence-based decision-making and aligns with the growing adoption of NAMs to advance cardiovascular research and disease prevention. Novelty and SignificanceO_ST_ABSWhat is known?C_ST_ABSHigh-throughput screening (HTS) assays can identify chemicals with activity at cardiovascular (CV) relevant molecular targets, but translating in vitro bioactivity concentrations into biologically meaningful human equivalent doses requires physiologically based pharmacokinetic (PBPK) modelling. The bioactivity exposure ratio (BER) provides a data-driven metric for comparing in vitro-derived equivalent administered doses against population exposure estimates, but its application to CV endpoints across a large and chemically diverse environmental chemical landscape has not been demonstrated. Geospatial mapping of CV chemical exposure risk has been demonstrated for a limited set of air pollutants but has not been extended to a broad environmental chemical landscape using human-relevant in vitro bioactivity data. What new information does this article contribute?Integrated in vitro to in vivo extrapolation (IVIVE) across 859 environmental chemicals demonstrates that cardiovascular-relevant in vitro endpoints are sensitive indicators of broader systemic toxicity, 96.4% of chemicals showed positive POD ratios, meaning in vitro CV assays flagged hazard at lower doses than non-specific animal toxicity studies despite the absence of endpoint matching. Seventeen chemicals including PFAS, brominated flame retardants, endocrine disruptors, and agricultural herbicides, had a BER below -2, indicating estimated human exposure more than 100-fold above the in vitro-derived cardiovascular bioactive dose, with convergent evidence from both in vitro and in vivo data supporting regulatory priority. County-level geospatial mapping reveals that cardiovascular chemical exposure risk is geographically heterogeneous across the United States, concentrated in industrially active regions already associated with elevated cardiovascular disease mortality, identifying specific populations for targeted environmental monitoring. SummaryThis study presents a scalable, systems-based IVIVE framework that integrates cardiovascular-relevant in vitro HTS bioactivity data with reverse dosimetry, population exposure predictions, and in vivo animal toxicity data to prioritize environmental chemicals for cardiovascular risk assessment. Applied to 859 chemicals spanning personal care products, flame retardants, pesticides, pharmaceuticals, and industrial compounds, the framework demonstrates that CV-relevant in vitro endpoints are sensitive indicators of systemic toxicity even in the absence of direct endpoint matching with in vivo studies. The BER emerges as a flexible and resource-adaptable prioritization metric, identifying 92 chemicals where estimated human exposure falls within the CV bioactive range, of which 17 represent the highest regulatory priority based on convergent evidence from both data streams. Geospatial mapping further reveals regional heterogeneity in cardiovascular chemical exposure risk concentrated in industrial areas of the central and southeastern United States. This work advances the application of new approach methodologies for cardiovascular chemical risk assessment at a time of accelerating regulatory transition toward human-relevant in vitro-based safety evaluation, providing a reproducible computational workflow directly applicable to chemical prioritization under evolving EPA and FDA regulatory frameworks.

Abstract Background. Chronic low-level exposure to lead, cadmium, mercury, and arsenic remains a determinant of premature mortality in the U.S. general population, but previous hazard-ratio analyses do not characterize how exposure shifts the lower tail of the survival distribution, where premature mortality is concentrated. Objectives. We estimated the association of whole-blood lead, whole-blood total mercury, urinary cadmium, and the sum of urinary inorganic and methylated arsenic species with the 10th, 25th, and 50th conditional quantiles of follow-up time to all-cause mortality among U.S. adults aged 40 years and older. Methods. NHANES Continuous 1999 to 2018 was linked to the National Death Index through December 31, 2019 (n = 29,652). Censored quantile regression was fit per metal on the log2 scale at quantiles {tau}{0.10, 0.25, 0.50}. A restricted-cubic-spline (RCS) censored-quantile-regression was fit for blood lead and urinary cadmium to investigate the threshold effect. Results. Over a median follow-up of 9.1 years, 7,215 deaths were ascertained. A doubling of urinary cadmium was associated with -1.57 years of follow-up (95% CI: -2.08, -1.07) at the 10th conditional quantile, -1.50 (-2.04, -0.96) at the 25th, and -1.49 (-1.93, -1.04) at the median (Benjamini Hochberg q < 0.001 throughout). A doubling of whole-blood lead was associated with -0.70 years (95% CI: -0.99, -0.40) at the 10th conditional quantile, -0.62 (-0.92,-0.31) at the 25th, and -0.61 years (-0.89, -0.34) at the median; the absolute loss was largest at {tau} = 0.10 for both metals. Urinary arsenic-metabolite sum was not associated with conditional follow-up at the estimable quantiles. Despite adjustment for dark and fatty-fish intake or DHA/EPA, whole-blood total mercury was associated with longer follow-up (i.e., negatively associated with mortality risk), possibly due to residual confounding by broader dietary or socioeconomic factors, rather than a true protective effect. The cadmium association was additionally robust to the mutual adjustment of lead. Discussion. Low-to-moderate urinary cadmium and whole-blood lead were associated with fewer years of follow-up survival at the lower-tail and median conditional quantiles of survival, with the largest absolute losses at the lower tail of the conditional survival distribution, where premature mortality is concentrated. These findings support continued reductions in U.S. cadmium exposure and lead with particular benefit for adults most vulnerable to premature death.

Hydroclimate whiplash, defined as the rapid transition between unusually wet and dry conditions, is expected to intensify under climate change, yet its population health impacts remain largely unknown. Here we quantified the association between hydroclimate whiplash and mortality across the contiguous United States from 2003 to 2023 using monthly county-level mortality records, standardized precipitation evapotranspiration index data, and two-stage time-series models. We identified overall and direction-specific dry-to-wet and wet-to-dry whiplash events at seasonal and sub-annual timescales and across 5-, 10-, and 20-year recurrence intervals. More severe whiplash events were associated with higher all-cause mortality risk; 5-, 10-, and 20-year sub-annual overall whiplash events increased mortality risk over five months by 3.4%, 4.5%, and 5.7%, respectively. Elevated risks were observed across cause-specific mortality outcomes, with the strongest association for infectious diseases. We estimated that 103,471 deaths were attributable to overall whiplash during the study period. These findings identify hydroclimate whiplash as an emerging climate-related public health threat and suggest that adaptation strategies focused on single hazards may underestimate the health burden of rapid, sequential hydroclimatic extremes.

Background: Endocrine-disrupting chemicals (EDCs) in consumer products are ubiquitously detected in human biospecimens, yet most epidemiological studies examine single chemicals rather than real-world co-exposures. We evaluated associations between a mixture of seven urinary chemical biomarkers and systemic inflammation. Methods: Survey-weighted log-log regression models adjusted for age, sex, race/ethnicity, poverty-income ratio, and survey cycle were conducted with Benjamini-Hochberg FDR correction (primary analysis, N=4,864). A sensitivity analysis additionally adjusted for body mass index and smoking status (N=4,494). Results: In the primary analysis, 5 of 7 chemicals showed significant associations after FDR correction: ethylparaben ({beta} = -0.056, FDR P < .001), propylparaben ({beta} = -0.026, FDR P = .007), bisphenol A ({beta} = +0.052, FDR P = .005), monoethyl phthalate ({beta} = +0.043, FDR P = .002), and monocyclohexyl phthalate ({beta} = +0.215, FDR P = .007). The WQS mixture index was significantly associated with CRP ({beta} = +0.056, 95% CI [0.031, 0.081], P < .001), with monocyclohexyl phthalate carrying the largest mixture weight (0.342). In the BMI- and smoking-adjusted sensitivity analysis, associations attenuated to null for all chemicals, though MCP preserved direction ({beta} = +0.129) and the WQS mixture direction was maintained ({beta} = +0.018). Two multiple imputation sensitivity analyses confirmed that monocyclohexyl phthalate was the only chemical to maintain a positive direction across all four analytical specifications (primary complete-case, BMI-adjusted complete-case, primary-aligned imputation, and BMI-adjusted imputation), reaching statistical significance in three of four specifications and providing convergent evidence of a robust MCP-inflammation association. Conclusions: The chemical mixture showed a significant collective association with systemic inflammation, consistent with a cumulative pro-inflammatory burden from co-exposure to multiple consumer product chemicals. These findings suggest that regulatory approaches should shift from single-chemical to mixture-based risk assessment frameworks for consumer product safety.

Background Wildfire activity and smoke exposure are increasing worldwide because of climate and land-use change. Although fine particulate matter (PM2.5) may impair pulmonary immune defences against tuberculosis (TB), population-level evidence remains limited. We estimated the effect of wildfire-related PM2.5 exposure on TB notification rates in Brazil. Methods We conducted a nationwide panel study linking municipality-level monthly TB notifications from Brazil's SINAN system with wildfire-related PM2.5 estimates from GEOS-Chem simulations across 5,545 municipalities (2003-2023). We estimated the impact of high-exposure days (PM2.5 > 25 g/m3) on monthly TB notifications using Poisson regression with fixed effects for municipalities, state-by-year, and state-by-month, controlling for time-invariant differences, secular trends, and seasonality. Distributed lag effects were estimated over 1-24 months before notification. Models accounted for meteorological conditions, GeneXpert diagnostic coverage, and spatial correlation using Conley standard errors. We computed attributable fractions among exposed municipality-months (AFE). Sensitivity analyses evaluated alternative PM2.5 thresholds (15 and 35 g/m3), co-pollutants, and agricultural expansion. Findings From Jan 1, 2003 to Dec 1, 2023, 1,758,982 TB cases were reported. Of these, 353,319 (20.1%) had at least one high-exposure day (PM2.5 > 25 g/m3) 1-24 months before notification. An additional 14 high-exposure days over the 24-month lag period was associated with an average monthly increase of 2.9% [95% CI: 0.9-4.9%] in TB notification rates. Effects peaked at 13 months (IQR: 11-14) prior to notification. Results showed a dose-response relationship across PM2.5 thresholds and were robust to controlling for NO2, O3, and agricultural expansion. Overall, wildfire-related PM2.5 exposure accounted for 2.1% [0.7-3.5%] of TB notifications in exposed municipality-months, corresponding to 7,802 [2,612-12,544] attributable cases. The AFE reached 10.7% [7.1-14.0%] in Pantanal and 7.3% [6.1-8.5%] in Amazonia, areas most impacted by wildfires. Interpretation Wildfire-related PM2.5 exposure may represent an increasingly important and modifiable risk factor for TB. As wildfire activity increases across many regions of the world, these findings highlight the need for integrating air quality into climate adaptation and TB control strategies.

Short-term environmental exposures have been linked to cognitive and attention-related outcomes, but the robustness of these associations remains uncertain. We linked daily weather and air-pollution exposures to repeated measures of subjective cognitive difficulties and attention-related outcomes among participants in the All of Us Research Program from 2018 to 2024. Associations were evaluated using complementary longitudinal and causal-inference approaches, including fixed-effects, lagged-exposure, and event-study analyses. Machine-learning methods were used to characterize heterogeneity and latent psychosocial structure, and findings were independently evaluated using 2024 Behavioral Risk Factor Surveillance System data. Several environmental exposure measures were associated with cognitive outcomes in pooled analyses; however, most associations attenuated substantially after accounting for within-location temporal variation. In contrast, mental-health burden, loneliness, and impaired social functioning remained consistently associated with subjective cognitive difficulty across analytical approaches. Similar patterns were observed in the validation dataset. These findings suggest that some observed environmental associations may reflect broader geographic and contextual differences rather than short-term environmental effects. Overall, psychosocial factors demonstrated more consistent associations with subjective cognitive difficulties than short-term environmental exposures across multiple analytical frameworks and independent datasets.

Short-term environmental exposures have been linked to cognitive and behavioral outcomes, although many reported associations may reflect broader geographic and contextual differences. Using longitudinal data from the All of Us Research Program (2018--2024), we linked daily weather and air-pollution exposures to repeated attention-related and subjective cognitive outcomes. Associations were evaluated using pooled, fixed-effects, lagged, and event-study analyses. Additional machine-learning analyses were conducted to explore potential heterogeneity and latent psychosocial structure. Replication analyses were performed using the 2024 Behavioral Risk Factor Surveillance System (BRFSS). Several environmental exposure measures showed small associations with cognitive outcomes in pooled analyses, but most attenuated substantially after accounting for within-location temporal variation. Mediation, sensitivity, and machine-learning analyses yielded similar conclusions. In contrast, mental-health burden, loneliness, and social functioning were consistently associated with subjective cognitive difficulty and exhibited substantially larger effect sizes than environmental exposures. Similar patterns were observed in BRFSS. Exploratory AI-assisted analyses yielded findings broadly consistent with the primary longitudinal analyses. These findings suggest that short-term environmental perturbations may have limited associations with cognitive outcomes after accounting for within-location variation, whereas psychosocial factors appear to be more consistently associated with subjective cognitive burden.

Many urban health outcomes are shaped by environmental stressors that occur together rather than in isolation, yet methods for measuring such co-occurrence at the neighbourhood scale remain underdeveloped. We developed a multi-metric framework for joint co-exposure assessment and applied it to characterise the joint spatial distribution of summer surface heat and fine particulate matter (PM2.5) across 42,304 census tracts in 48 large US metropolitan areas during summers 2015 to 2020, covering approximately 174.6 million residents. The framework combines a composite co-exposure index, a joint exceedance indicator, a conditional exceedance ratio that compares observed joint occurrence to within-group statistical independence, and an upper tail dependence parameter estimated using both the non-parametric Caperaa-Fougeres-Genest estimator and a Gumbel copula, with bias-corrected and accelerated (BCa) confidence intervals obtained from a 5,000-replicate metropolitan-area block bootstrap. Among residents of predominantly Black tracts, 13.21% lived in neighbourhoods that simultaneously exceeded the within-metropolitan-area 80th percentile for both heat and PM2.5, compared with 3.33% of residents of predominantly White tracts; the corresponding heat-only and PM2.5-only ratios were 2.88 and 2.48. Residents of Home Owners Loan Corporation grade D tracts had 3.97 times the odds (95% confidence interval 2.79 to 5.66) of joint hotspot residence compared with grade A residents after adjustment for contemporary tract racial composition, poverty, renter-occupancy, and pre-1960 housing. The within-group conditional exceedance ratio at the 80th percentile was 2.29 in predominantly White tracts (95% BCa CI 1.81 to 2.78), 1.27 in predominantly Black tracts (0.71 to 1.56), and 1.13 in predominantly Hispanic tracts (0.70 to 1.41); the White interval excluded one while the Black and Hispanic intervals included one, which we interpret as power-limited given fewer contributing CBSAs. Magnitudes attenuated under near-surface air temperature surfaces but the direction and statistical significance of the primary findings were preserved. The framework is portable to other compound-exposure questions and supports cumulative-impact assessment.

Fine particulate matter (PM2.5) was found to be associated with elevated blood lipids, but fewer studies have examined the associations with specific constituents of PM2.5. We studied the associations between exposure to annual PM2.5 and its 14 constituents, and repeated blood lipid measurements among general responders enrolled in the World Trade Center Health Program between 2003 and 2019 (n = 44,876). We used generalized additive mixed effect models to investigate the single-pollutant associations with repeated measures of blood total cholesterol (TC), high and low-density lipoprotein (HDL-C and LDL-C) levels. We then used linear generalized weighted quantile sum regression with a random intercept for participant ID to account for the clustering of repeated measures and evaluate the combined associations with the component mixture. A decile increase in the mixture of 14 PM2.5 chemical components was associated with 0.375 mg/dL increase in TC levels (95% confidence Interval (CI): 0.174-0.577) and 0.302 mg/dL increase in LDL-C (95% CI: 0.063, 0.540). Lead, organic carbon, and iron were major drivers of both associations. Component-specific models also show higher TC and LDL levels associated with interquartile range increases in organic carbon (0.472, 95% CI [0.027, 0.918] and 0.648 95% CI [0.136, 1.160]) and iron exposure (1.081, 95% CI [0.630, 1.532] and 0.748, 95% CI [0.318, 1.178]). In conclusion, we found PM2.5 exposure to be associated with elevated lipid levels. The associations differed by PM2.5 composition, highlighting organic carbon, lead, and iron and major drivers. These findings are highly significant for a population exposed to extreme air pollution event and susceptible to lipid alterations that might trigger cardiovascular events.

Fine particulate air pollution (PM2.5) in the United States has fallen by roughly half since 2000, yet linked health outcomes such as diabetes and childhood ADHD have not improved in parallel. One reconciling possibility is that pollution exposure in early life produces health effects that emerge only years or decades later, after pollution itself has declined. Using two decades of U.S. county-level data, we relate annual PM2.5 estimates to birth outcomes, diabetes prevalence, and small-area estimates of childhood attention-deficit/hyperactivity disorder (ADHD) across short and long time scales. Within counties, changes in low birth weight rates are associated with changes in PM2.5 during the same year and the year prior to birth. At longer time scales, cross-county comparisons show that PM2.5 exposure is associated with higher prevalence of adult diabetes and ADHD after approximately a decade. Together, these patterns suggest that population-level health risks from air pollution may persist over decades, even as pollution itself declines.

Plastic products have greatly improved convenience in daily life. However, diverse pollutants released from these materials pose substantial risks to human health. Lactiplantibacillus plantarum PD01 has previously been demonstrated to reduce microplastic (MP) bioaccumulation and toxicity in murine model. In this study, we conducted a randomized, double-blind, placebo-controlled trial to further evaluate the efficacy of L. plantarum PD01 in reducing MPs and MP-associated chemicals in humans. A total of 106 participants were recruited in November 2025. Eligible participants were randomly assigned to either the placebo or intervention group, and orally received placebo or 1.0x1010 colony-forming units (CFU) L. plantarum PD01 after meals three times a day, respectively. Fecal, urinary, and blood samples were collected to determine the MPs contents, plasticizer levels, gut microbiota composition, blood metabolic profiles and biochemical indicators. Among these measurements, the analysis of urinary phthalate metabolites was completed first and revealed a significant reduction after the probiotic intervention. Compared with the placebo group, 6-week L. plantarum PD01 supplementation resulted in significant relative reductions in urinary levels of MCMHP by 60.2% (P = 0.0343), MMP by 51.2% (P < 0.001), MEHP by 49.6% (P = 0.0058), MiBP by 45.7% (P = 0.0085), MnBP by 35.8% (P = 0.0478), and {Sigma}DEHP by 46.2% (P = 0.0461). The interim results presented here provide the first clinical evidence that the probiotic strain PD01 can significantly reduce residual MP-associated chemicals in human body. To the best of our knowledge, this is the first randomized controlled trial (RCT) to evaluate probiotic intervention targeting MPs and MP-associated chemicals in humans.

The introduction of salt iodization is associated with improved health and socioeconomic outcomes, but is not yet universally adopted and not always sustained. Using a quasi-experimental event study with difference-in-differences over space and time, we quantify the impacts of iodine deficiency in utero and infancy on childhood mortality and later academic achievement in Ethiopia, comparing cohorts born just before and after the May 1998 border closure that interrupted access to iodized salt. Rural children with fewer months of early-life exposure to iodized salt scored lower on standardized secondary-school exams, especially in districts with low environmental iodine, with excess deaths emerging in infancy and persisting through early childhood. These findings reveal the long-term benefits of salt iodization for health and education, especially for people with low intake of iodine from environmental sources.

Typical environmental exposures to the toxic class of chemicals known as polycyclic aromatic hydrocarbons (PAHs) involve complex mixtures; however, relatively few mechanistic toxicity studies have evaluated them as environmental mixtures, instead focusing on individual compounds or simple mixtures. In this study, we first derived Republic Sediment Extract (REPSE), a complex PAH mixture extracted from sediment at the Republic Creosoting site of the Elizabeth River in Norfolk, Virginia. After characterizing the PAH contents of REPSE, we evaluated its mechanisms of developmental neurotoxicity in three evolutionarily distinct taxa, leveraging the unique strengths of Atlantic killifish, zebrafish, and Caenorhabditis elegans as model species, with a focus on the Aryl hydrocarbon Receptor (AhR) pathway. Embryonic REPSE exposure caused induction of CYP1A in both fish species at sub-teratogenic concentrations, consistent with activation of the canonical AhR pathway. These sub-teratogenic exposures nevertheless induced neurotoxicity across both fish species, altering neurobehavioral phenotypes in fish, and induced dopaminergic neuronal damage in worms, again at non-teratogenic concentrations. To determine whether these effects were linked to canonical AhR response pathways, we examined killifish offspring from the pollution-adapted Republic Creosoting population, which exhibited characteristic recalcitrance to CYP1A induction, but remained susceptible to the neurobehavioral effects of REPSE. The induction of neuronal damage in worms provides orthogonal evidence for a non-AhR mechanism, because C. elegans AhR is not transcriptionally activated by PAHs as in vertebrates. Further probing of potential mechanisms underlying REPSE-induced neurotoxicity in worms revealed altered neuronal redox status (roGFP) and energy availability (ATP:ADP ratio). Collectively, our multispecies approach reveals conserved mechanisms of PAH mixture neurotoxicity, including effects that extend beyond canonical AhR signaling.

Environmental factors including chemical exposures are important contributors to Parkinsons disease (PD). Nearly all well-validated chemicals involved in PD affect mitochondria, and the great majority of those identified inhibit mitochondrial complex I, causing ATP depletion and oxidative stress. We hypothesized that inhibition of mitochondrial complex III would also cause dopaminergic neurotoxicity. Using Caenorhabditis elegans to evaluate the in vivo effects of complex III-inhibiting pesticides antimycin A and pyraclostrobin, we found that both caused selective dopaminergic neurotoxicity. We evaluated exacerbation of dopaminergic neurotoxicity by the presence of -synuclein, and pdr-1/PRKN and pink-1/PINK1 mutant backgrounds and found increased neurotoxicity for pdr-1. Complex III inhibition caused a more-oxidized cellular environment in those neurons and pharmacological and genetic antioxidant interventions rescued neurotoxicity, but energetic rescue attempts did not. Finally, optogenetic production of superoxide anion specifically at complex III caused dopaminergic neuronal damage. Thus, redox stress at complex III following chemical exposure causes dopaminergic neurotoxicity in vivo in C. elegans.

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with poorly understood sublethal effects on insects. Perfluorooctanoic acid (PFOA), one of the most widely distributed legacy PFAS is increasingly recognized for altering organismal physiology beyond traditional toxicity endpoints. Here, we use the fruit fly Drosophila melanogaster as a model to examine how PFOA exposure during larval (juvenile) development reshapes insect life-history progression and metabolic homeostasis. Our studies reveal that at environmentally relevant concentrations (nM to low {micro}M), PFOA induces precocious expression of developmentally-regulated genes and leads to metabolic changes that persist into adulthood. At higher concentrations used to probe mechanism, PFOA accelerates larval development, disrupts mitochondrial membrane potential, and increases whole-organism metabolic heat production - results that suggest altered mitochondrial energetic efficiency. Consistent with this tradeoff, PFOA-exposed larvae that develop faster under permissive conditions exhibit heightened sensitivity to environmental stressors, including elevated temperature and reduced food hydration. Together, these findings demonstrate that PFOA disrupts metabolic and developmental processes in a dose- and context-dependent manner, highlighting sublethal effects that may influence insect resilience under environmental stress. SYNOPSIS STATEMENTHere we describe how PFOA alters the growth, development, and metabolism of the fruit fly Drosophila melanogaster. Specifically, we find that PFOA accelerates Drosophila juvenile growth while also rendering exposed larvae sensitive to environmental stress. These observations suggest that widespread PFOA contamination may impair the developmental fitness of insect populations.