A Novel Approach to Assessing the Joint Effects of Mercury and Fish Consumption on Neurodevelopment in the New Bedford Cohort.

Understanding health risks from methylmercury (MeHg) exposure is complicated by its link to fish consumption which may confound or modify toxicities. One solution is to include fish intake and a biomarker of MeHg exposure in the same model, but resulting estimates do not reflect the independent impact of accumulated MeHg or fish exposures. In fish-eating populations, this can be addressed by separating MeHg exposure into fish intake and average Hg content of the consumed fish. We assessed the joint association of prenatal MeHg exposure (maternal hair Hg) and fish intake (among fish-eating mothers) with neurodevelopment in 361 eight-year-olds from the New Bedford Cohort (born 1993-1998). Neurodevelopmental assessments used standardized tests of IQ, language, memory, and attention. Covariate-adjusted regression assessed the association of maternal fish consumption, stratified by tertiles of estimated average fish Hg, with neurodevelopment. Associations between maternal fish intake and child outcomes were generally beneficial for those in the lowest average fish Hg tertile, but detrimental in the highest average fish Hg tertile where, for example, each serving of fish was associated with 1.3 fewer correct responses (95% CI: -2.2, -0.4) on the Boston Naming test. Standard analyses showed no outcome associations with hair Hg or fish intake.

Regression calibration of self-reported mobile phone use to optimize quantitative risk estimation in the COSMOS study.

The Cohort Study of Mobile Phone Use and Health (COSMOS) has repeatedly collected self-reported and operator-recorded data on mobile phone use. Assessing health effects using self-reported information is prone to measurement error, but operator data were available prospectively for only part of the study population and did not cover past mobile phone use. To optimize the available data and reduce bias, we evaluated different statistical approaches for constructing mobile phone exposure histories within COSMOS. We evaluated and compared the performance of four regression calibration (RC) methods (simple, direct, inverse, and generalized additive model for location, shape, and scale), complete-case (CC) analysis and multiple imputation (MI) in a simulation study with a binary health outcome. We used self-reported and operator-recorded mobile phone call data collected at baseline (2007-2012) from participants in Denmark, Finland, the Netherlands, Sweden, and the UK. Parameter estimates obtained using simple, direct, and inverse RC methods were associated with less bias and lower mean squared error than those obtained with CC analysis or MI. We showed that RC methods resulted in more accurate estimation of the relation between mobile phone use and health outcomes, by combining self-reported data with objective operator-recorded data available for a subset of participants.

Improving spatial exposure data for everyone - lifecourse social context and ascertaining residential history.

Measuring age-specific, contextual exposures is crucial for lifecourse epidemiology research. Longitudinal residential data offers a "golden ticket" to cumulative exposure metrics and can enhance our understanding of health disparities. Residential history can be linked to myriad spatiotemporal databases to characterize environmental, socioeconomic, and policy contexts that a person experienced throughout life. However, obtaining accurate residential history is challenging in the United States due to the limitations of administrative registries and self-reports. Xu et al. (Am J Epidemiol. 2024; 193(2):348-359) detail an approach to linking residential history sourced from LexisNexis ® Accurint ® to a Wisconsin-based research cohort, offering insights into challenges with residential history collection. Researchers must analyze the magnitude of selection and misclassification biases inherent to ascertaining residential history from cohort data. A lifecourse framework can provide insights into why the frequency and distance of moves is patterned by age, birth cohort, racial/ethnic identity, socioeconomic status, and urbanicity. Historic and contemporary migration patterns of marginalized people seeking economic and political opportunities must guide interpretations of residential history data. We outline methodologic priorities for use of residential history in health disparities research, including contextualizing residential history data with determinants of residential moves, triangulating spatial exposure assessment methods, and transparently quantifying measurement error.

Exposure of wetlands important for nonbreeding waterbirds to sea-level rise in the Mediterranean.

Sea-level rise (SLR) is expected to cause major changes to coastal wetlands, which are among the world's most vulnerable ecosystems and are critical for nonbreeding waterbirds. Because strategies for adaptation to SLR, such as nature-based solutions and designation of protected areas, can locally reduce the negative effects of coastal flooding under SLR on coastal wetlands, it is crucial to prioritize adaptation efforts, especially for wetlands of international importance for biodiversity. We assessed the exposure of coastal wetlands important for nonbreeding waterbirds to projected SLR along the Mediterranean coasts of 8 countries by modeling future coastal flooding under 7 scenarios of SLR by 2100 (from 44- to 161-cm rise) with a static inundation approach. Exposure to coastal flooding under future SLR was assessed for 938 Mediterranean coastal sites (≤30 km from the coastline) where 145 species of nonbreeding birds were monitored as part of the International Waterbird Census and for which the monitoring area was delineated by a polygon (64.3% of the coastal sites monitored in the Mediterranean region). Thirty-four percent of sites were threatened by future SLR, even under the most optimistic scenarios. Protected study sites and study sites of international importance for waterbirds were, respectively, 1.5 and 2 times more exposed to SLR than the other sites under the most optimistic scenario. Accordingly, we advocate for the development of a prioritization scheme to be applied to these wetlands for the implementation of strategies for adaptation to SLR to anticipate the effects of coastal flooding. Our study provides major guidance for conservation planning under global change in several countries of the Mediterranean region.

Exposición de los humedales de importancia para las aves acuáticas no reproductoras al incremento del nivel del mar en el Mediterráneo Resumen Se espera que el incremento en el nivel del mar (INM) cause cambios importantes en los humedales costeros, los cuales se encuentran entre los ecosistemas más vulnerables y son críticos para las aves acuáticas no reproductoras. Es crucial la priorización de los esfuerzos de adaptación, especialmente en los humedales con importancia internacional para la biodiversidad, ya que las estrategias de adaptación ante el INM, como las soluciones basadas en la naturaleza y la designación de áreas protegidas, pueden reducir localmente los efectos negativos de las inundaciones costeras por INM en los humedales costeros. Evaluamos la exposición de los humedales costeros con importancia para las aves acuáticas no reproductoras ante el INM proyectado en las costas del Mediterráneo en ocho países con un modelo de inundaciones costeras en el futuro bajo siete escenarios de INM para el año 2100 (de 44 a 161 cm) con un enfoque de inundación estática. Evaluamos la exposición a las inundaciones costeras bajo el INM futuro en 938 sitios costeros del Mediterráneo (≤ 30 km a partir de la costa), en donde monitoreamos a 145 especies de aves no reproductoras como parte del Censo Internacional de Aves Acuáticas y para los cuales el área de monitoreo estuvo delineada con un polígono (64.3% de los sitios costeros monitoreados en la región Mediterránea). El 34% de los sitios se vio amenazado por el INM en el futuro, incluso con los escenarios más optimistas. Los sitios de estudio protegidos y los sitios de estudio de importancia internacional para las aves acuáticas estuvieron expuestos 1.5 y 2 veces más al INM que otros sitios con el escenario más optimista. De acuerdo con esto, abogamos por el desarrollo de un esquema de priorización para aplicarse en estos humedales para la implementación de estrategias de adaptación al INM para anticipar los efectos de las inundaciones costeras. Nuestro estudio proporciona información importante para la planeación de la conservación bajo el cambio global en varios de los países del Mediterráneo.

Urinary and Fecal Excretion of 121 Environmental Chemicals in Pet Dogs and Cats: Significance of Feces in Biomonitoring of Exposures.

Laboratory animal studies have reported the biliary excretion of chemicals following exposure. Nevertheless, feces are rarely used as a matrix in biomonitoring of chemical exposures. In this study, feces and urine from pet dogs and cats were analyzed for the presence of 45 plasticizers, 45 environmental phenols, and 31 pesticides. Thirty-two analytes were detected in ≥70% pet feces, while up to 29 analytes were frequently (≥70%) found in urine. The sum concentrations of all analytes (∑All) in pet feces were significantly higher than those measured in urine (median: 393-666 ng/g wet weight in feces vs 216-464 ng/mL in urine). Plasticizers were the dominant class of chemicals, accounting for 81-97% and 69-77% of ∑All in urine and feces, respectively. Analyte concentrations measured in paired urine and feces exhibited weak correlations. The excretion rates of the chemicals via urine and feces were calculated through a reverse dosimetry approach. Low-molecular-weight phthalates excreted predominantly in urine, whereas high-molecular-weight phthalates and several organophosphate triesters were excreted predominantly in feces. The fecal excretion rates of parabens, benzophenones, bisphenols, naphthalene, 2,4-dichloronicotinic acid, and 4-nitrophenol were similar to or higher than those of urinary excretion. Our results suggest that feces are an important matrix in biomonitoring of exposure to environmental chemicals.

Heat Exposure among Adult Women in Rural Tamil Nadu, India.

Exposure to heat is associated with a substantial burden of disease and is an emerging issue in the context of climate change. Heat is of particular concern in India, which is one of the world's hottest countries and also most populous, where relatively little is known about personal heat exposure, particularly in rural areas. Here, we leverage data collected as part of a randomized controlled trial to describe personal temperature exposures of adult women (40-79 years of age) in rural Tamil Nadu. We also characterize measurement error in heat exposure assessment by comparing personal exposure measurements to the nearest ambient monitoring stations and to commonly used modeled temperature data products. We find that temperatures differ across individuals in the same area on the same day, sometimes by more than 5 °C within the same hour, and that some individuals experience sharp increases in heat exposure in the early morning or evening, potentially a result of cooking with solid fuels. We find somewhat stronger correlations between the personal exposure measurements and the modeled products than with ambient monitors. We did not find evidence of systematic biases, which indicates that adjusting for discrepancies between different exposure measurement methods is not straightforward.

High-Precision Microscale Particulate Matter Prediction in Diverse Environments Using a Long Short-Term Memory Neural Network and Street View Imagery.

In this study, we propose a novel long short-term memory (LSTM) neural network model that leverages color features (HSV: hue, saturation, value) extracted from street images to estimate air quality with particulate matter (PM) in four typical European environments: urban, suburban, villages, and the harbor. To evaluate its performance, we utilize concentration data for eight parameters of ambient PM (PM1.0, PM2.5, and PM10, particle number concentration, lung-deposited surface area, equivalent mass concentrations of ultraviolet PM, black carbon, and brown carbon) collected from a mobile monitoring platform during the nonheating season in downtown Augsburg, Germany, along with synchronized street view images. Experimental comparisons were conducted between the LSTM model and other deep learning models (recurrent neural network and gated recurrent unit). The results clearly demonstrate a better performance of the LSTM model compared with other statistically based models. The LSTM-HSV model achieved impressive interpretability rates above 80%, for the eight PM metrics mentioned above, indicating the expected performance of the proposed model. Moreover, the successful application of the LSTM-HSV model in other seasons of Augsburg city and various environments (suburbs, villages, and harbor cities) demonstrates its satisfactory generalization capabilities in both temporal and spatial dimensions. The successful application of the LSTM-HSV model underscores its potential as a versatile tool for the estimation of air pollution after presampling of the studied area, with broad implications for urban planning and public health initiatives.

Material Flow Analysis and Occupational Exposure Assessment in Additive Manufacturing End-of-Life Material Management.

Additive manufacturing (AM) offers a variety of material manufacturing techniques for a wide range of applications across many industries. Most efforts at process optimization and exposure assessment for AM are centered around the manufacturing process. However, identifying the material allocation and potentially harmful exposures in end-of-life (EoL) management is equally crucial to mitigating environmental releases and occupational health impacts within the AM supply chain. This research tracks the allocation and potential releases of AM EoL materials within the US through a material flow analysis. Of the generated AM EoL materials, 58% are incinerated, 33% are landfilled, and 9% are recycled by weight. The generated data set was then used to examine the theoretical occupational hazards during AM EoL material management practices through generic exposure scenario assessment, highlighting the importance of ventilation and personal protective equipment at all stages of AM material management. This research identifies pollution sources, offering policymakers and stakeholders insights to shape pollution prevention and worker safety strategies within the US AM EoL management pathways.

Quantitative Microbial Risk Assessment of Antibiotic-Resistant E. coli, Legionella pneumophila, and Mycobacteria in Nonpotable Wastewater Reuse Applications.

Antibiotic-resistant bacteria (ARB) have become a major threat to public health and modern medicine. A simple death kinetics-based dose-response model (SD-DRM) was incorporated into a quantitative microbial risk assessment (QMRA) to assess the risks of exposure to reclaimed wastewater harboring antibiotic-resistant E. coli, Legionella pneumophila, and Mycobacterium avium for multiple exposure scenarios. The fractions of ARB and trace antibiotics present in the body were incorporated to demonstrate their impact on infection risks. Both ARB and antibiotic susceptible bacteria, ASB, are assumed to have the same dose-response in the absence of antibiotics but behave differently in the presence of residual antibiotics in the body. Annual risk of L. pneumophila infection exceeded the EPA 10-4 pppy (per person per year) benchmark at concentrations in reclaimed water greater than 103-104 CFU/L, depending on parameter variation. Enteropathogenic E. coli infection risks meet the EPA annual benchmark at concentrations around 105-106 total E. coli. The results illustrated that an increase in residual antibiotics from 0 to 40% of the minimum inhibitory concentration (MIC) reduced the risk by about 1 order of magnitude for E. coli but was more likely to result in an untreatable infection.

Validity of Mobility-Based Exposure Assessment of Air Pollution: A Comparative Analysis with Home-Based Exposure Assessment.

Air pollution exposure is typically assessed at the front door where people live in large-scale epidemiological studies, overlooking individuals' daily mobility out-of-home. However, there is limited evidence that incorporating mobility data into personal air pollution assessment improves exposure assessment compared to home-based assessments. This study aimed to compare the agreement between mobility-based and home-based assessments with personal exposure measurements. We measured repeatedly particulate matter (PM2.5) and black carbon (BC) using a sample of 41 older adults in the Netherlands. In total, 104 valid 24 h average personal measurements were collected. Home-based exposures were estimated by combining participants' home locations and temporal-adjusted air pollution maps. Mobility-based estimates of air pollution were computed based on smartphone-based tracking data, temporal-adjusted air pollution maps, indoor-outdoor penetration, and travel mode adjustment. Intraclass correlation coefficients (ICC) revealed that mobility-based estimates significantly improved agreement with personal measurements compared to home-based assessments. For PM2.5, agreement increased by 64% (ICC: 0.39-0.64), and for BC, it increased by 21% (ICC: 0.43-0.52). Our findings suggest that adjusting for indoor-outdoor pollutant ratios in mobility-based assessments can provide more valid estimates of air pollution than the commonly used home-based assessments, with no added value observed from travel mode adjustments.

Air Quality, Health, and Equity Benefits of Carbon Neutrality and Clean Air Pathways in China.

In the pursuit of carbon neutrality, China's 2060 targets have been largely anchored in reducing greenhouse gas emissions, with less emphasis on the consequential benefits for air quality and public health. This study pivots to this critical nexus, exploring how China's carbon neutrality aligns with the World Health Organization's air quality guidelines (WHO AQG) regarding fine particulate matter (PM2.5) exposure. Coupling a technology-rich integrated assessment model, an emission-concentration response surface model, and exposure and health assessment, we find that decarbonization reduces sulfur dioxide (SO2), nitrogen oxides (NOx), and PM2.5 emissions by more than 90%; reduces nonmethane volatile organic compounds (NMVOCs) by more than 50%; and simultaneously reduces the disparities across regions. Critically, our analysis reveals that further targeted reductions in air pollutants, notably NH3 and non-energy-related NMVOCs, could bring most Chinese cities into attainment of WHO AQG for PM2.5 5 to 10 years earlier than the pathway focused solely on carbon neutrality. Thus, the integration of air pollution control measures into carbon neutrality strategies will present a significant opportunity for China to attain health and environmental equality.

(Non)targeted Chemical Analysis and Risk Assessment of Organic Contaminants in Darkibor Kale Grown at Rural and Urban Farms.

This study investigated the presence and human hazards associated with pesticides and other anthropogenic chemicals identified in kale grown in urban and rural environments. Pesticides and related compounds (i.e., surfactants and metabolites) in kale samples were evaluated using a nontargeted data acquisition for targeted analysis method which utilized a pesticide mixture containing >1,000 compounds for suspect screening and quantification. We modeled population-level exposures and assessed noncancer hazards to DEET, piperonyl butoxide, prometon, secbumeton, terbumeton, and spinosyn A using nationally representative estimates of kale consumption across life stages in the US. Our findings indicate even sensitive populations (e.g., pregnant women and children) are not likely to experience hazards from these select compounds were they to consume kale from this study. However, a strictly nontargeted chemical analytical approach identified a total of 1,822 features across all samples, and principal component analysis revealed that the kale chemical composition may have been impacted by agricultural growing practices and environmental factors. Confidence level 2 compounds that were ≥5 times more abundant in the urban samples than in rural samples (p < 0.05) included chemicals categorized as "flavoring and nutrients" and "surfactants" in the EPA's Chemicals and Products Database. Using the US-EPA's Cheminformatics Hazard Module, we identified that many of the nontarget compounds have predicted toxicity scores of "very high" for several end points related to human health. These aspects would have been overlooked using traditional targeted analysis methods, although more information is needed to ascertain whether the compounds identified through nontargeted analysis are of environmental or human health concern. As such, our approach enabled the identification of potentially hazardous compounds that, based on their hazard assessment score, merit follow-up investigations.

Factors Determining Black Carbon Exposures among Pregnant Women Enrolled in the HAPIN Trial.

Residential biomass burning is an important source of black carbon (BC) exposure among rural communities in low- and middle-income countries. We collected 7165 personal BC samples and individual/household level information from 3103 pregnant women enrolled in the Household Air Pollution Intervention Network trial. Women in the intervention arm received free liquefied petroleum gas stoves and fuel throughout pregnancy; women in the control arm continued the use of biomass stoves. Median (IQR) postintervention BC exposures were 9.6 µg/m3 (5.2-14.0) for controls and 2.8 µg/m3 (1.6-4.8) for the intervention group. Using mixed models, we characterized predictors of BC exposure and assessed how exposure contrasts differed between arms by select predictors. Primary stove type was the strongest predictor (R2 = 0.42); the models including kerosene use, kitchen location, education, occupation, or stove use hours also provided additional explanatory power from the base model adjusted only for the study site. Our full, trial-wide, model explained 48% of the variation in BC exposures. We found evidence that the BC exposure contrast between arms differed by study site, adherence to the assigned study stove, and whether the participant cooked. Our findings highlight factors that may be addressed before and during studies to implement more impactful cookstove intervention trials.

Assessment of exposure to pesticides: residues in 24 h duplicate diets versus their metabolites in 24 h urine using suspect screening and target analysis.

Human biomonitoring can add value to chemical risk assessment by reducing the assumptions regarding consumption rates, residue occurrence, and processing effects and by integrating exposures from different sources (diet, household use, environmental). However, the relationship between exposure and concentration in human matrices is unknown for most pesticides. Therefore, we conducted a pilot study to gain more insight into the qualitative and quantitative relationship between dietary intake of pesticides (external exposure) and urinary excretion (reflecting internal exposure). In this cross-sectional observational study, 35 healthy consumers aged 18-65 years from the region of Wageningen, Netherlands, collected an exact duplicate portion of their diets during 24 h. On the same day, they also collected all their urine. The duplicate diets were analyzed using target screening by GC- and LC-HRMS; each duplicate diet contained at least five, up to 21, pesticide residues. The 24 h urine samples were analyzed using LC-HRMS in a suspect screening workflow. Metabolites were tentatively detected in all 24 h urine samples, ranging from six metabolites corresponding to four pesticides up to 40 metabolites originating from 16 pesticides in a single urine sample. In total, 65 metabolites originating from 28 pesticides were tentatively detected. After prioritization and additional confirmation experiments, 28 metabolites originating from 10 pesticides were identified with confidence level 1 or 2b. Next, quantitative analysis was performed for a selection of pesticides in duplicate diets and their metabolites in 24 h urine to assess quantitative relationships. In the quantitative comparisons between duplicate diet and 24 h urine, it was found that some metabolites were already present in the duplicate diet, which may give an overestimation of exposure to the parent pesticide based on measurement of the metabolites in urine. Additionally, the quantitative comparisons suggest a background exposure through other exposure routes. We conclude that suspect screening of 24 h urine samples can disclose exposure to mixtures of pesticide on the same day in the general population. However, more research is needed to obtain quantitative relationships between dietary intake and exposure.

Factors influencing occupational exposure to pyrethroids and glyphosate: An analysis of urinary biomarkers in Malaysia, Uganda and the United Kingdom.

BACKGROUND: Long-term exposure to pesticides is often assessed using semi-quantitative models. To improve these models, a better understanding of how occupational factors determine exposure (e.g., as estimated by biomonitoring) would be valuable. METHODS: Urine samples were collected from pesticide applicators in Malaysia, Uganda, and the UK during mixing/application days (and also during non-application days in Uganda). Samples were collected pre- and post-activity on the same day and analysed for biomarkers of active ingredients (AIs), including synthetic pyrethroids (via the metabolite 3-phenoxybenzoic acid [3-PBA]) and glyphosate, as well as creatinine. We performed multilevel Tobit regression models for each study to assess the relationship between exposure modifying factors (e.g., mixing/application of AI, duration of activity, personal protective equipment [PPE]) and urinary biomarkers of exposure. RESULTS: From the Malaysia, Uganda, and UK studies, 81, 84, and 106 study participants provided 162, 384 and 212 urine samples, respectively. Pyrethroid use on the sampling day was most common in Malaysia (n = 38; 47%), and glyphosate use was most prevalent in the UK (n = 93; 88%). Median pre- and post-activity 3-PBA concentrations were similar, with higher median concentrations post-compared to pre-activity for glyphosate samples in the UK (1.7 to 0.5 µg/L) and Uganda (7.6 to 0.8 µg/L) (glyphosate was not used in the Malaysia study). There was evidence from individual studies that higher urinary biomarker concentrations were associated with mixing/application of the AI on the day of urine sampling, longer duration of mixing/application, lower PPE protection, and less education/literacy, but no factor was consistently associated with exposure across biomarkers in the three studies. CONCLUSIONS: Our results suggest a need for AI-specific interpretation of exposure modifying factors as the relevance of exposure routes, levels of detection, and farming systems/practices may be very context and AI-specific.

False positives and false negatives in benzene biological monitoring.

Benzene is a commonly used industrial chemical that is a significant environmental pollutant. Occupational health specialists and industrial toxicologists are concerned with determining the exact amount of exposure to chemicals in the workplace. There are two main approaches to assess chemical exposure; air monitoring and biological monitoring. Air monitoring has limitations, which biological monitoring overcomes and could be used as a supplement to it. However, there are several factors that influence biological monitoring results. It would be possible to assess exposure more accurately if these factors were taken into account. This study aimed to review published papers for recognizing and discussing parameters that could affect benzene biological monitoring. Two types of effects can be distinguished: positive and negative effects. Factors causing positive effects will increase the metabolite concentration in urine more than expected. Furthermore, the parameters that decrease the urinary metabolite level were referred to as false negatives. From the papers, sixteen influential factors were extracted that might affect benzene biological monitoring results. Identified factors were clarified in terms of their nature and mechanism of action. It is also important to note that some factors influence the quantity and quality of the influence of other factors. As a result of this study, a decision-making protocol was developed for interpreting the final results of benzene biological monitoring.

Estimating ambient air pollutant concentrations outside and inside homes in the Subpopulations and Intermediate outcomes in COPD air pollution (SPIROMICS air) cohort.

BACKGROUND: Valid, high-resolution estimates of population-level exposure to air pollutants are necessary for accurate estimation of the association between air pollution and the occurrence or exacerbation of adverse health outcomes such as Chronic Obstructive Pulmonary Disease (COPD). OBJECTIVES: We produced fine-scale individual-level estimates of ambient concentrations of multiple air pollutants (fine particulate matter [PM2.5], NOX, NO2, and O3) at residences of participants in the Subpopulations and Intermediate Outcomes in COPD Air Pollution (SPIROMICS Air) study, located in seven regions in the US. For PM2.5, we additionally integrated modeled estimates of particulate infiltration based on home characteristics and measured total indoor concentrations to provide comprehensive estimates of exposure levels. METHODS: To estimate ambient concentrations, we used a hierarchical high-resolution spatiotemporal model that integrates hundreds of geographic covariates and pollutant measurements from regulatory and study-specific monitors, including ones located at participant residences. We modeled infiltration efficiency based on data on house characteristics, home heating and cooling practices, indoor smoke and combustion sources, meteorological factors, and paired indoor-outdoor pollutant measurements, among other indicators. RESULTS: Cross-validated prediction accuracy (R2) for models of ambient concentrations was above 0.80 for most regions and pollutants. Particulate matter infiltration efficiency varied by region, from 0.51 in Winston-Salem to 0.72 in Los Angeles, and ambient-source particles constituted a substantial fraction of total indoor PM2.5. CONCLUSION: Leveraging well-validated fine-scale approaches for estimating outdoor, ambient-source indoor, and total indoor pollutant concentrations, we can provide comprehensive estimates of short and long-term exposure levels for cohorts undergoing follow-up in multiple different regions.

A comparison of PM2.5 exposure estimates from different estimation methods and their associations with cognitive testing and brain MRI outcomes.

BACKGROUND: Reported associations between particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) and cognitive outcomes remain mixed. Differences in exposure estimation method may contribute to this heterogeneity. OBJECTIVES: To assess agreement between PM2.5 exposure concentrations across 11 exposure estimation methods and to compare resulting associations between PM2.5 and cognitive or MRI outcomes. METHODS: We used Visit 5 (2011-2013) cognitive testing and brain MRI data from the Atherosclerosis Risk in Communities (ARIC) Study. We derived address-linked average 2000-2007 PM2.5 exposure concentrations in areas immediately surrounding the four ARIC recruitment sites (Forsyth County, NC; Jackson, MS; suburbs of Minneapolis, MN; Washington County, MD) using 11 estimation methods. We assessed agreement between method-specific PM2.5 concentrations using descriptive statistics and plots, overall and by site. We used adjusted linear regression to estimate associations of method-specific PM2.5 exposure estimates with cognitive scores (n = 4678) and MRI outcomes (n = 1518) stratified by study site and combined site-specific estimates using meta-analyses to derive overall estimates. We explored the potential impact of unmeasured confounding by spatially patterned factors. RESULTS: Exposure estimates from most methods had high agreement across sites, but low agreement within sites. Within-site exposure variation was limited for some methods. Consistently null findings for the PM2.5-cognitive outcome associations regardless of method precluded empirical conclusions about the potential impact of method on study findings in contexts where positive associations are observed. Not accounting for study site led to consistent, adverse associations, regardless of exposure estimation method, suggesting the potential for substantial bias due to residual confounding by spatially patterned factors. DISCUSSION: PM2.5 estimation methods agreed across sites but not within sites. Choice of estimation method may impact findings when participants are concentrated in small geographic areas. Understanding unmeasured confounding by factors that are spatially patterned may be particularly important in studies of air pollution and cognitive or brain health.

Chronic exposure to drinking water nitrate and trihalomethanes in the French CONSTANCES cohort.

Trihalomethanes (THMs) and nitrate are widespread chemicals in drinking water. Chronic exposure has been associated with increased cancer risk despite inconclusive evidence, partly due to the challenges in long-term exposure assessment and potential exposure misclassification. We estimated concentrations of nitrate and THMs in drinking water using a public regulatory monitoring database (SISE-Eaux) for CONSTANCES, a French population-based prospective cohort. We obtained 26,322,366 measurements of drinking water parameters from 2000 to 2020. We excluded missing, implausible and duplicated measurements; we corrected or imputed missing geocodes of sampling locations; we calculated the annual median concentration of nitrate and THMs by surveillance area. To predict missing annual median concentrations, linear mixed models with random intercept using surveillance area as a clustering variable were developed for each region for nitrate and the four THM components (chloroform, chlorodibromomethane, bromodichloromethane and bromoform) separately. Concentrations in the nearest surveillance area from the household were merged per year among 75,462 participants with residential history geocoded for 2000-2020. Estimated concentrations resulting from this approach were compared with measured concentrations in 100 samples collected in Paris, Rennes and Saint-Brieuc in 2021. Median annual concentrations of total THMs and nitrate at study participants' homes for 2000-2020 were, respectively, 15.7 µg/l (IQR: 15.2) and 15.2 mg/l (IQR: 20.8). Among these, 35% were based on measurements for nitrate (16% for THMs), 44% (46%) were predicted using on linear mixed models, and 21% (38%) were based on distribution unit median values. Conditional R2 predictive models ranged from 0.71 to 0.91 (median: 0.85) for nitrate, and from 0.48 to 0.80 for THMs (median: 0.68). These concentrations will allow future association analyses with risk of breast and colorectal cancer. Our cleaning process introduced here could be adapted to other large drinking water monitoring data.

Multiple exposure pathways and health risk assessment of PAHs in Lanzhou city, a semi-arid region in northwest China.

In the sparse studies for multiple pathway exposure, attention has predominantly been directed towards developed regions, thereby overlooking the exposure level and health outcome for the inhabitants of the semi-arid regions in northwest China. However, cities within these regions grapple with myriad challenges, encompassing insufficient sanitation infrastructure and outdated heating. In this study, we analyzed the characteristics and sources of polycyclic aromatic hydrocarbons (PAHs) pollution in PM2.5, water, diet, and dust during different periods in Lanzhou, and estimated corresponding carcinogenic health risk through inhalation, ingestion, and dermal absorption. Our observations revealed the concentrations of PAHs in PM2.5, food, soil, and water are 200.11 ng m-3, 8.67 mg kg-1, 3.91 mg kg-1, and 14.5 ng L-1, respectively, indicating that the Lanzhou area was seriously polluted. Lifetime incremental cancer risk (ILCR) showed a heightened cancer risk to men compared to women, to the younger than the elderly, and during heating period as opposed to non-heating period. Notably, the inhalation was the primary route of PAHs exposure and the risk of exposure by inhalation cannot be ignored. The total environmental exposure assessment of PAHs can achieve accurate prevention and control of PAHs environmental exposure according to local conditions and targets.