Environmental Research

Ambient particulate matter (PM) is a well-established environmental risk factor for non-communicable diseases, yet its influence on mitochondrial function remains poorly defined. Mitochondrial DNA copy number (mtDNA-CN) serves as a biomarker of mitochondrial biogenesis, making it a candidate exposure biomarker. We conducted the study per PRISMA guidelines (PROSPERO-CRD420261320957) and examined the association between ambient PM exposure and mtDNA-CN. Risk of bias was assessed using Joanna Briggs Institute tools, and relative and absolute changes in mtDNA-CN were pooled using random-effects models, with subgroup analyses by pollutant type and descriptive synthesis of mechanistic evidence. Of 1,224 records identified, 24 studies met inclusion criteria for quantitative analysis, with 12 reporting percentage change and 12 reporting absolute values, covering 13,092 participants. PM exposure was significantly associated with decreased percentage mtDNA-CN (ES: -4.90; 95% CI: -7.97 to -1.82; p = 0.002), while absolute mtDNA-CN levels increased significantly (ES = 0.55; 95% CI: 0.05 to 1.04; p = 0.030). Mechanistic pathways contributing included mtDNA hypermethylation, impaired mitochondrial biogenesis and dynamics. Our findings show ambient PM exposure alters mtDNA-CN, though directionality differs by metric, pointing to the need for larger prospective studies to validate mtDNA-CN as a reliable biomarker of airborne PM and nanoparticulate exposure.

Endocrine-disrupting chemicals can target ovaries and interfere with key milestones of reproduction. Previously, we found that mixtures of the chemical exposome measured in follicular fluid (FF) were cumulatively associated with lower oocyte yield. Because ovaries age faster than many other organs, our current aim was to evaluate associations of FF chemical mixtures with epigenetic age acceleration and epigenetic pathways in FF cells. FF was collected during oocyte retrieval from 76 patients undergoing assisted reproduction in Atlanta. The exposome was measured using untargeted high-resolution mass spectrometry with gas (GC) and liquid (LC) chromatography. Weighted quantile sum (WQS-RS) indices were constructed for three mixtures of chemicals in association with oocyte yield, separated by instrument configuration (GC, LC-HILIC, LC-C18). DNA methylation was measured from the cellular component of FF using Illumina MethylationEPIC BeadChip, with age acceleration based on the GrimAge clock. Regression and pathway enrichment analyses elucidated relationships between chemical exposures or mixture indices and epigenetic markers, adjusted for age and technical covariates. All three chemical mixture indices were associated with epigenetic age acceleration in FF (p<0.05). For example, a standard-deviation increase in the GC-detected mixture was associated with 0.23 standard-deviations higher accelerated aging (95% CI: 0.0058-0.45; p=0.048). Twenty-seven frequently detected chemicals, including benzo[a]pyrene, plasticizers, flame retardants, forever chemicals, and pesticides, were associated with epigenetic pathways related to ovarian follicle growth and hormone signaling (p<0.05; six under false discovery rate<5%). In summary, environmental chemicals may accumulate in ovaries, contribute to accelerated epigenetic aging of ovarian somatic cells, and potentially affect follicle development.

Interest in microbiota-host co-metabolism and the effects of its derived co-metabolites on biological processes is increasing rapidly. In addition to their demonstrated associations with mammalian metabolic health and cognition, microbiota-host co-metabolites (MHCMs) represent lifelong contributors to the endogenous exposome. We have previously shown the MHCM trimethylamine N-oxide (TMAO) to exert beneficial effects on murine blood-brain barrier integrity and cognition. Here we investigated whether these positive neural effects of TMAO extended to humans, analysing how TMAO exposure associates with neurodevelopmental outcomes in children and whether an in vitro human neuronal-astrocyte co-culture could contribute to further investigation of the underlying mechanism(s) and neuronal processes related to these associations. In a cohort study of childhood mental health (N=1,203), TMAO was associated with fewer internalising problems, while its precursor microbial metabolite trimethylamine was associated with more behavioural problems in both the cross-sectional and an independent longitudinal study from 1 to 15 years of age (N=630-820). Given prior associations between TMAO exposure and exposure to the environmental pollutants mercury and arsenic, we investigated how the effects of TMAO interacted with these known neurotoxicants. TMAO had a protective effect, modifying the relationship between arsenic exposure and poorer neurodevelopmental outcomes. Furthermore, TMAO activated synaptogenesis-related gene expression and was functionally protective against the negative effects of mercury in our in vitro model. Together, our findings emphasise the importance of interdisciplinary approaches to evaluate associations and potential pathways of MHCMs (endogenous) and environmental (exogenous) metabolites on neurodevelopment in exposome studies.

Background: Urban environmental and lifestyle factors during early life may influence pubertal timing, but the combined effects of multiple environmental exposures within an exposome analytical framework remain poorly understood. Objective: To examine the association between early-life urban environmental exposures and pubertal timing, and to explore whether these exposures interact with early-life nutritional factors, namely breastfeeding duration and childhood diet quality. Methods: Data from two European population-based birth cohorts were analysed: Generation XXI (G21, Portugal; n=5263; 51.5% girls) and INfancia y Medio Ambiente (INMA, Spain; n=1019; 50.1% girls). Urban environmental exposures including indicators of air pollution, traffic, built environment, and natural spaces were estimated at 4 early-life stages at both cohorts: pregnancy (INMA only), birth, 1 year, and 4-5 years of age. Pubertal development timing was assessed using Tanner staging and/or the Pubertal Development Scale (PDS), and age at menarche was self-reported. Exposome-Wide Association Study (ExWAS) models and unsupervised clustering followed by ordinal logistic regression models were used to examine single- and multi-exposure associations, respectively. Regression models were fitted adjusting for relevant child characteristics, maternal factors, and household socioeconomic conditions, and corrected for multiple testing. Results: Individuals living in more unfavourable urban environments characterised by higher building density, air pollution, and lower access to natural spaces showed earlier pubertal timing according to multiple outcomes, across multiple early-life exposure periods, and in both cohorts. In the G21 cohort, these environmental profiles were associated with earlier age at menarche, particularly for exposures at 1-1.5 and 4-5 years (e.g., 1-1.5y: {beta}=-0.172, FDR-adjusted p-value=0.041), while in the INMA cohort, boys exposed to more unfavourable environmental profiles showed more advanced pubertal development, also particularly for exposures at 1-1.5 and 4-5 years of age (e.g., 1-1.5y; {beta}=0.572, FDR-adjusted p-value=0.008). Among environmental domains, air pollution and traffic were the factors most consistently associated with pubertal timing. Regarding early-life nutritional factors, longer duration of exclusive breastfeeding was associated with a lower Tanner stage among girls in G21. No significant interactions between breastfeeding duration and environmental exposure clusters were observed. Conclusion: Early-life urban environmental exposures, particularly air pollution and traffic, may influence pubertal timing. Exclusive breastfeeding may have a protective role against earlier pubertal development. These findings highlight the importance of improving urban environmental conditions and promoting breastfeeding to support healthy developmental trajectories.

Exposure to higher levels of ambient air pollution during pregnancy has been linked to multiple adverse pregnancy outcomes. However, studies on acute exposures and reduced gestation length have reported inconsistent findings. This project aims to examine the acute association between ambient air pollution and preterm (28-36 gestational weeks) or early-term (37-38 gestational weeks) births. Daily concentrations of 12 air pollutants, based on bias-corrected numerical model outputs, were linked to vital records of singleton live preterm and early-term births from 2005-2017 in California, Florida, Georgia, Kansas, Nevada, New Jersey, North Carolina (2005-2015), and Oregon. Under a time-stratified case-crossover design, odds ratios (OR) were estimated via conditional logistic regression with adjustment for risks among ongoing pregnancies, meteorology, time trends and federal holidays. We estimated cumulative associations up to a 6-day lag using distributed lag models. Risk estimates per interquartile range (IQR) increase in exposure were pooled across states using inverse-variance weighting. Our study included 1,085,162 preterm and 3,901,185 early-term births. We observed positive associations between 0-2 day cumulate exposure to several air pollutants and early-term births, including NO2 (OR: 1.0023, 95% CI:1.0010, 1.0037 per 7.1 g/m3 increase), PM2.5 (OR=1.0022, 95% CI: 1.006, 1.0038 per 4.6 g/m3 increase), PM2.5 organic carbon (OR= 1.0026, 95% CI: 1.0013, 1.0039 per 1.7 g/m3 increase) and PM2.5 elemental carbon (OR=1.0025, 95% CI: 1.0014, 1.0035 per 0.26 g/m3 increase). Associations with preterm birth were mostly null. In conclusion, we found positive associations between short-term air pollution exposure, including PM and major PM2.5 components, and risks of early-term birth.

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.

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.

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.

Background: The effect of extreme temperatures on miscarriage is not well understood. Even less understood is the gestational period most vulnerable to extreme temperature exposure, as early miscarriages are often missed in incident datasets. We employ a birth-rate based approach to infer the risk of miscarriage in response to extreme temperature exposure by gestational week. Methods: We conducted a population-based ecological study using birth registry data from the 7,948 municipalities of Italy between 2013 and 2024 (4.5 million births). The analyses were stratified by five climatically coherent macro-regions (Ecoregions). To infer unreported pregnancy losses, we regressed birth rates dated from the last menstrual period against weekly temperatures across gestational weeks 3-21, accounting for temporal seasonality and spatial heterogeneities. Findings: Exposure to heat (mean weekly temperature of 30.4 degree/C) during gestational weeks 3-4 was associated with a reduction of birth rates of 1.62 (0.71 - 2.51)%, and of 1.91 (0.92 - 2.88)% to mean weekly temperature of 1.6 degree/C. Whilst heat was found to be harmful during gestational weeks 3-4 and 18-21, cold spells were found to be consistently harmful from the 3th up to the 12th week, depending on the Ecoregion. Interpretation: Pregnancies are vulnerable to extreme temperatures during the post-conceptual period and the second trimester. The findings underscore the need for a pre-conceptual cohort to clarify the mechanisms of loss, and urge public health action to protect pregnancies from the beginning of gestation.

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.

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.

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.

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.

Background: Exercise training is a cornerstone intervention for cardiovascular disease, yet large cohort studies have reported attenuation of physical activity benefits at elevated air pollution concentrations, creating uncertainty around exercise prescription in polluted settings where cardiovascular disease burden is greatest. Objectives: To determine whether ambient PM2.5 concentration modifies the cardiovascular benefits of structured exercise training, using a global sample of trials spanning a >100-fold pollution gradient. Methods: We conducted a systematic review and multilevel meta-analysis of exercise training interventions reporting pre-post changes in systolic blood pressure (SBP), diastolic blood pressure (DBP), peak oxygen uptake (VO2Max), or resting heart rate (HR) in adults. Annual ambient PM2.5 concentrations (3.5-283 g/m3) were assigned to each study location from CAMS ERA5 reanalysis data. Three-level random-effects models with cluster-robust variance estimation accounted for arms nested within studies. PM2.5 meta-regression was conducted unadjusted and adjusted for world region, exercise mode, trial duration, and health condition, with subgroup analyses by exercise mode and hypertension status. Results: Across 465 studies (27,629 participants), exercise training produced clinically meaningful benefits for all outcomes (SBP - mmHg, DBP - mmHg, VO2Max +3.2 ml/kg/min, HR - bpm; all p < 0.001), with benefits consistently larger in higher-pollution settings. Hypertensive participants showed the greatest improvements, particularly from aerobic exercise (SBP standardised mean difference 0.396 in the Low vs 1.020 in the High PM2.5 stratum). Although aerobic and resistance training participants experience similar chronic ambient PM2.5 exposure, only aerobic exercise showed a stratum gradient (interaction p = 0.074). Discussion: Exercise training delivers clinically meaningful cardiovascular benefits at every pollution level tested. The larger benefits observed in higher-pollution settings reflect the greater cardiovascular risk burden of those populations, and hypertensive patients stand to gain the most, particularly from aerobic exercise.

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: Extreme heat is increasingly linked to adverse mental health outcomes, yet empirical evidence from sub-Saharan Africa is absent. Such data are critical for health system planning and climate adaptation in one of the world's most heat-vulnerable regions. Objectives: We aimed to estimate the immediate and delayed effects of daily maximum temperature on mental disorder-related hospital admissions in a rural South African district over 13 years. Methods: We conducted a time-series analysis of daily mental disorder admissions at Hlabisa Hospital, South Africa, from 2011 to 2023. Daily maximum temperatures were obtained from ECMWF ERA5 reanalysis and validated with local weather station data. Using distributed lag non-linear quasi-Poisson models, we estimated the association between extreme heat (95th, 97.5th, 99th percentiles of the daily maximum temperature distribution) and relative risk of mental disorder admissions over a 0-21-day lag. Analyses were stratified by sex, age (<60 vs. & >=60 years), and diagnosis (schizophrenia vs. other mental disorders). Results: Between 2011 and 2023, 1760 mental disorder admissions were recorded. Extreme heat at the 97.5th percentile (35.74 degrees celsius) was associated with an immediate increase in admissions (lag 0: RR=1.10, 95 % CI: 1.00 to 1.20; lag 1: RR=1.08, 95% CI: 1.00 to 1.17). Subgroup analyses revealed heterogeneous patterns, with early increases among females and individuals with diagnoses other than schizophrenia, delayed increases among males and those aged <60 years, and delayed decreases among females and older adults. No significant association was observed for schizophrenia. Discussion: To our knowledge, this study provides the first empirical evidence from South Africa that extreme heat is associated with increased hospital admissions for mental disorders, with immediate and delayed effects across population subgroups. These findings highlight the need to integrate mental health into climate adaptation and public health strategies through strengthened surveillance, targeted protection of vulnerable groups, and enhanced health system preparedness for extreme heat.

Air pollution has well-documented negative cardiovascular and respiratory consequences. However, the impact of particulate matter pollution (PM2.5) on brain development is unclear. Animal studies suggest that exposure to early-life PM2.5 can cause adverse neurodevelopmental outcomes, but in vivo human work has been hampered by cross-sectional designs and heavily confounded PM2.5 exposure measures. Here we use an innovative natural experimental design to isolate the effects of wildfire pollution on neurocognitive development in a large cohort of children (N>9000, 4 waves, age 9-16). Doing so, we find that greater wildfire PM2.5 exposure is robustly associated with slower brain development and shallower cognitive improvement across early adolescence. Our study underscores the urgent public health concern that wildfire PM2.5 poses for childhood development.

Socioeconomic inequality in exposure to air pollution possess a significant public health challenge, yet little is known about how the disparities vary across the various economic status areas in Nairobi. Globally, studies have shown that exposure to air pollution is unequal across communities hence disparities in harm to human health. This study examined the association between socioeconomic characteristics and perceived air quality among residents of low- and high-socioeconomic status areas in Nairobi, Kenya. Two regions within Nairobi County were selected for this study: Mukuru kwa Njenga (representing the Low Socioeconomic Status) and Langata (representing the High Socioeconomic Status) with a sample size of 384 in HSES areas and 368 in LSES areas. A cross-sectional study was conducted among 752 respondents residing in selected LSES and HSES areas of Nairobi. Data was collected using a structured questionnaire assessing sociodemographic characteristics, income, education, employment, perceived air quality, and self-reported health outcomes associated with air pollution exposure. Descriptive statistics were used to summarize participant characteristics and perceived air quality. Chi-square tests were used to examine associations between residential area and categorical health outcomes, while ordinal logistic regression was used to assess the association between socioeconomic characteristics and perceived air-quality ratings. Perceived air quality differed significantly between residential socioeconomic groups. Respondents in LSES areas were more likely to rate air quality as poor or very poor, with 45.4% rating it as very poor, compared with only 1.6% of respondents in HSES areas. In contrast, 12.2% of HSES respondents rated air quality as good compared with 0.3% in LSES areas. The association between area of residence and perceived air-quality rating was statistically significant, {chi}2(3) = 282.672, p < 0.001. In the ordinal logistic regression model, HSES residence was associated with significantly lower odds of reporting poorer perceived air quality compared with LSES residence (OR = 0.135, 95% CI: 0.095-0.190, p < 0.001). Income was also significantly associated with perceived air quality, while respondents with no formal education had higher odds of reporting poorer perceived air quality compared with those with secondary education (OR = 3.254, 95% CI: 1.388-7.638, p = 0.007). Significant differences were also observed for several self-reported health outcomes. Respiratory problems were more prevalent among respondents in LSES areas than HSES areas (72.7% versus 50.4%; {chi}2(1) = 29.081, p < 0.001; Cramer's V = 0.224). However, allergies, eye irritation, and headaches were reported more frequently in HSES areas than in LSES areas, with significant associations observed for allergies ({chi}2(1) = 106.479, p < 0.001; Cramer's V = 0.429), eye irritation ({chi}2(1) = 136.577, p < 0.001; Cramer's V = 0.486), and headaches ({chi}2(1) = 149.180, p < 0.001; Cramer's V = 0.508). No statistically significant association was observed for cardiovascular problems, likely reflecting the very low number of reported cases. Substantial socioeconomic disparities in perceived air quality and self-reported respiratory health outcomes were observed. Residents of low-socioeconomic status areas consistently perceived poorer air quality and reported a higher burden of respiratory problems, highlighting the need for targeted interventions to reduce environmental health inequalities.

Introduction The interaction between air pollution and airborne pollen is emerging as a major public health concern, as it may enhance allergic responses and exacerbate asthma at the population level. Available evidence suggests that urban residents experience a higher burden of respiratory allergies than rural populations, potentially due to the combined effects of chemical air pollutants and pollen exposure. Air pollutants may modify pollen characteristics, increase allergen release and potency, and promote airway inflammation, thereby amplifying allergic sensitization and respiratory symptoms. Aims For the first time, the relationship between air pollution, pollen, and asthma and allergies is investigated by simultaneously factoring in spatiotemporal land cover data (urban, agricultural, and forest spaces). Methods We utilized descriptive statistics, Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and spatial analysis to understand the relationship of birch, grass and all taxons count, NO2 and PM2.5 concentrations (micro grams/m3) and land cover type (urban/rural, agriculture, forest) in Bordeaux, Clermont, Marseille, Nancy, Paris, Poitiers, Reims and Strasbourg using prescribed and over the count sales data for asthma (R03) and allergies (R06), from a representative sample of pharmacies (n=12,000), in 2013. Results In 2013, the 8 cities saw total sales of 9,684,577 R03 and 12,344,102 R06 medications, with sales peaks coinciding with high pollen and air pollution. A spatiotemporal and land cover analysis revealed that relationships between these variables are highly context-dependent. For instance, higher R06 sales clustered in areas with medium pollen (taxon deciles 3 to 4, grass 4 to 5, birch 6 to 7), high pollution ("NO" _2 deciles 8 to 10, "PM" _2.5 5 and 8 to 10, "PM" _10 3, 7, 9 to10), high agricultural land, and low forest/urban space. Conversely, some associations did not vary by location, suggesting external influencing factors. Conclusions Our data raise evidence that pollen and air pollution can act synergistically according to the land cover characteristics. Other investigations are needed to confirm the relationship.

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.