Exposure Assessment Methods Research Articles

Concentrations, Sources and Health Risk Assessment of Polycyclic Aromatic Hydrocarbons in Chinese Herbal Medicines.

The determination and evaluation of 16 polycyclic aromatic hydrocarbons (PAHs) in seven Chinese herbal medicines (CHMs) were conducted through a rapid and straightforward extraction and purification method, coupled with GC-MS. A sample-based solid-phase extraction (SPE) pretreatment technique, incorporating isotopic internal standards, was employed for detecting various medicinal parts of CHMs. The assay exhibited linearity within the range of 5 to 500 ng/mL, with linear coefficients (R2) for PAHs exceeding 0.999. The recoveries of spiked standards ranged from 63.37% to 133.12%, with relative standard deviations (RSDs) ranging from 0.75% to 14.54%. The total PAH content varied from 176.906 to 1414.087 μg/kg. Among the 16 PAHs, phenanthrene (Phe) was consistently detected at the highest levels (47.045-168.640 μg/kg). Characteristic ratio analysis indicated that oil, coal, and biomass combustion were the primary sources of PAHs in CHMs. The health risk associated with CHMs was assessed using the lifetime carcinogenic risk approach, revealing potential health risks from the consumption of honeysuckle, while the health risks of consuming Lycium chinense berries were deemed negligible. For the other five CHMs (glycyrrhizae, Coix lacryma, ginseng, lotus seed, seed of Sterculia lychnophora), the health risk from consumption fell within acceptable ranges. Furthermore, sensitivity analyses utilizing Monte Carlo exposure assessment methods identified PAH levels in CHMs as health risk sensitizers. It is crucial to recognize that the consumption of herbal medicines is not a continuous process but entails potential health risks. Hence, the monitoring and risk assessment of PAH residues in CHMs demand careful attention.

Assessing occupational pesticide exposure in Latin America and the Caribbean: Methods review for agricultural vulnerability reduction

B A rapid review was conducted to describe pesticide exposure assessment methodologies in Agricultural Work Contexts (AWC)s in Latin America and the Caribbean (LAC), in order to provide elements to reduce vulnerabilities within the agricultural population. A final number of 79 articles were selected from Medline via Pubmed, LILACS, and SciELO. In the region, family agriculture is the predominant form of agricultural production (72%) in informal agricultural work contexts (AWCs), which are characterized by small-scale diversified agricultural production, lower educational attainment, limited income, and a lack of social and healthcare security for the families. Indirect exposure assessment methods were the most commonly reported (58%), and its use was associated with informal AWCs (p = 0.011). Understanding AWCs and employing appropriate assessment methods can contribute to addressing vulnerabilities in the agricultural sector.

Development of a job-exposure matrix-like exposure assessment method for the US general population based on Occupational Information Network (O*NET) job tasks.

Job-exposure matrices (JEMs) are often used for exposure assessment in occupational exposure and epidemiology studies. However, general population JEMs are difficult to find and access for workers in the United States of America. We aimed to use publicly available information to develop a JEM-like exposure assessment method to determine exposure to a wide range of occupational agents in a wide range of occupations for US general population studies. We used information from the US Department of Labor's Occupational Information Network database (O*NET) for 19,636 job tasks and 974 civilian occupations. We used automated keyword searches to identify 1,804 job tasks that involved exposure to 50 occupational agents. We had 2 reviewers determine whether each identified job task actually involved exposure to the 50 occupational agents. We had a third reviewer, a certified industrial hygienist, assess any job task and exposure for which the first 2 reviewers disagreed. For each U.S. Census 2010 occupation code, we used this information to derive 3 exposure variables for each occupational agent: ever exposure, number of job tasks of exposure, and frequency of exposure. Our keyword searches identified a median of 10 (interquartile range [IQR]: 43.75) job tasks for each occupational agent, and the maximum was 308. We determined job tasks actually involved exposure to 45 occupational agents, including solvents, air pollution, pesticides, radiation, metals, etc. We derived the 3 exposure variables for these 45 occupational agents for 516 U.S. Census 2010 occupation codes. The median percentage for ever exposure to individual occupational agents was 1.16% (IQR: 1.74%), and the maximum was 11.43%. Our JEM-like exposure assessment method based on O*NET information can be used to determine exposure to a wide range of occupational agents in a wide range of occupations for the US general population.

Association of air pollution and risk of chronic kidney disease: A systematic review and meta-analysis.

Although epidemiological studies have evaluated the association between ambient air pollution and chronic kidney disease (CKD), the results remain mixed. To clarify the nature of the association, we conducted a comprehensive systematic review and meta-analysis to assess the global relationship between air pollution and CKD. The Web of Science, PubMed, Embase and Cochrane Library databases systematically were searched for studies published up to July 2023 and included 32 studies that met specific criteria. The random effects model was used to derive overall risk estimates for each pollutant. The meta-analysis estimated odds ratio (ORs) of risk for CKD were 1.42 (95% confidence interval [CI]: 1.31-1.54) for each 10 μg/m3 increase in PM2.5 ; 1.20 (95% CI: 1.14-1.26) for each 10 μg/m3 increase in PM10 ; 1.07 (95% CI: 1.05-1.09) for each 10 μg/m3 increase in NO2 ; 1.03 (95% CI: 1.02-1.03) for each 10 μg/m3 increase in NOX ; 1.07 (95% CI: 1.01-1.12) for each 1 ppb increase in SO2 ; 1.03 (95% CI: 1.00-1.05) for each 0.1 ppm increase in CO. Subgroup analysis showed that this effect varied by gender ratio, age, study design, exposure assessment method, and income level. Furthermore, PM2.5 , PM10 , and NO2 had negative effects on CKD even within the World Health Organization-recommended acceptable concentrations. Our results further confirmed the adverse effect of air pollution on the risk of CKD. These findings can contribute to enhance the awareness of the importance of reducing air pollution among public health officials and policymakers.

Long-Term Exposure to Low-Level and Mortality: Investigation of Heterogeneity by Harmonizing Analyses in Large Cohort Studies in Canada, United States, and Europe.

Studies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter () exposure with large heterogeneity in the magnitude of reported associations and the shape of concentration-response functions (CRFs). We aimed to evaluate the impact of key study design factors (including confounders, applied exposure model, population age, and outcome definition) on effect estimates by harmonizing analyses on three previously published large studies in Canada [Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE), 1991-2016], the United States (Medicare, 2000-2016), and Europe [Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), 2000-2016] as much as possible. We harmonized the study populations to individuals years of age, applied the same satellite-derived exposure estimates, and selected the same sets of potential confounders and the same outcome. We evaluated whether differences in previously published effect estimates across cohorts were reduced after harmonization among these factors. Additional analyses were conducted to assess the influence of key design features on estimated risks, including adjusted covariates and exposure assessment method. A combined CRF was assessed with meta-analysis based on the extended shape-constrained health impact function (eSCHIF). More than 81 million participants were included, contributing 692 million person-years of follow-up. Hazard ratios and 95% confidence intervals (CIs) for all-cause mortality associated with a increase in were 1.039 (1.032, 1.046) in MAPLE, 1.025 (1.021, 1.029) in Medicare, and 1.041 (1.014, 1.069) in ELAPSE. Applying a harmonized analytical approach marginally reduced difference in the observed associations across the three studies. Magnitude of the association was affected by the adjusted covariates, exposure assessment methodology, age of the population, and marginally by outcome definition. Shape of the CRFs differed across cohorts but generally showed associations down to the lowest observed levels. A common CRF suggested a monotonically increased risk down to the lowest exposure level. https://doi.org/10.1289/EHP12141.

Studying full-shift inhalation exposures to volatile organic compounds (VOCs) among Latino workers in very small-sized beauty salons and auto repair shops.

One in every 200 US jobs is in a beauty salon or auto repair shop, where workers are regularly exposed to volatile organic compounds (VOCs) that may cause a range of short- and long-term health issues. In these shops, Latino workers are overrepresented and lack culturally and linguistically appropriate industrial hygiene resources. This leaves a gap in knowledge on inhalation exposures to VOCs in this hard-to-reach and ubiquitous worker population. Our goal was to recruit hard-to-reach, predominantly Spanish-speaking workers in beauty salons and auto repair shops and monitor total VOC inhalation exposures for over entire work shifts, with minimal impact on workers, clients, and business. We developed and refined measurement and exposure assessment methods for personal and area full-shift VOC inhalation exposures. With minimal participant loss, we measured over 500 h of real-time, personal VOC exposures and recorded activities and other exposure factors for 47 participants, while also documenting chemical inventories and quantifying indoor area concentrations of specific VOCs among 10 auto repair shops and 10 beauty salons. Lessons learned from our study can assist future studies of inhalation exposures in other hard-to-reach occupational populations.

Comparison of diagnostic methods for assessment of Ostertagia ostertagi exposure in Norwegian dairy herds

BackgroundThe gastrointestinal nematode (GIN) Ostertagia ostertagi can cause severe disease in first season grazers (FSG) and impaired performance due to subclinical infections in adult cows. Diagnostic methods to assess exposure include faecal egg count and detection of specific antibodies using antibody-ELISAs resulting in an optical density ratio (ODR). Using the ELISA test on bulk tank milk (BTM) allows for a herd level diagnosis. Appropriate use of diagnostic methods for evaluation of O. ostertagi exposure is required to optimize herd parasite surveillance and aid in a sustainable control regime. The aim of this study was to describe the relationship between different diagnostic tests used to assess GIN exposure in Norwegian production systems. A cross-sectional field study was carried out in twenty herds in Norway in the fall of 2020. Serum and faecal samples were taken from 380 individuals, of which 181 were FSG and 199 were cows. In addition, milk was collected from every cow and one BTM sample was taken from each herd. Faecal egg counts were performed. The distribution of ODR values in individual samples within and between herds and the associations between BTM ODR and individual ODR values were described. The data were analysed using visual assessment of scatter plots, Pearson correlation coefficients and linear regression.ResultsA high variability of the within-herd individual ODR values in serum and milk in every herd was detected. The ODR in BTM explained a low degree of the variation in the individual serum and milk samples. When plotting the ODR results in milk or serum according to four BTM categories, the distribution of ODR values were notably different in the highest and lowest BTM categories. The correlation between individual milk and serum samples was moderate (r = 0.68), while the highest correlation (r = 0.81) was between the BTM ODR and the group average individual milk samples.ConclusionsA poor predictive ability for BTM ODR to assess individual ODR values in both FSG and cows was demonstrated. However, the study indicates that the evaluation by ELISA test on BTM to assess exposure to GIN could be useful in herds with a very high or low BTM ODR.

Determination of persistent organochlorine pollutants in human serum by combining liquid-liquid extraction and solid-phase extraction with gas chromatography-tandem mass spectrometry

Persistent organochlorine pollutants (POCPs) are a group of “forever chemicals” that are ubiquitous in the environment and pose adverse health effects to humans. However, the lack of sensitive and widely applicable analytical method for internal POCPs exposure assessment puts limits on the researches of health risk evaluations. Therefore, we developed a method for the measurement of 43 POCPs in human serum using gas chromatography-tandem mass spectrometry (GC-MS/MS). Serum samples were treated with methanol and acid to precipitate protein and remove lipids, respectively. 13C-labeled analogue was spiked and liquid-liquid extraction (LLE) was performed to extract target analytes by hexane and methyl tert-butyl ether. The extract was purified by solid-phase extraction (SPE) and eluted with dichloromethane. The eluate was concentrated under nitrogen stream and reconstituted with toluene. Samples were analyzed by GC-MS/MS operated in electron impact (EI) and multiple reaction monitoring (MRM) mode. Calibration curves of all target analytes showed favorable linearity within the concentration range of 0.008 to 10 μg/L for different POCPs, with regression coefficients above 0.991. The method detection limits and limits of quantification ranged from 0.005 to 0.10 μg/L and 0.017 to 0.34 μg/L, respectively. The recoveries and precision of all analytes at 3 different spike levels were in the range of 65.3 % to 121.8 % and 1.8 % to 13.9 %, respectively. The matrix effects (ME) ranged from 74.9 % to 125.6 %. The results of measuring quality control samples from the National Institute of Standards and Technology (NIST) were with relative deviations of less than 30 %. With an optimized sample preparation procedure, the proposed method has successfully achieved in improving extraction efficiency and reducing ME. It was applied in the simultaneous determination of POCPs in a small volume of human serum in China National Human Biomonitoring.

Accurate low-dose exposure assessment of benzene and monoaromatic compounds by diffusive sampling: sampling and analytical method validation according to ISO 23320 for radiello® samplers packed with activated charcoal.

The research study aimed at providing an accurate low-dose benzene exposure assessment method, by validating diffusive monitoring techniques for benzene personal exposure measurements at workplaces where benzene concentrations are expected in the low ppb range, such as in the present-day chemical, petrochemical, foundry, and pharmaceutical industry. The project was aimed at addressing the need for a robust and fully validated method to perform personal exposure measurements considering that the occupational exposure limit value for benzene is going to be significantly lowered in the next few years. Diffusive sampling offers a reliable alternative to pumped sampling methods, intrinsic safety in potentially explosive atmospheres, lightness, and ease of use. In this study, the radiello® diffusive sampler, with the packed activated charcoal RAD130 adsorbing substrate [suitable for solvent desorption and analysis by high-resolution gas chromatography-flame ionization detection (HRGC-FID)], was used. The experiments have been conducted following the ISO 23320 standard in the range from 0.005 to 0.1 ppm (16 to 320 μg/m3), yielding a full validation of the sampling and analytical method. The sampler performances have fulfilled all requisites of the ISO 23320 standard, in particular: bias due to the selection of a non-ideal sorbent is lower than 10% (no significant back diffusion of benzene due to concentration change in the atmosphere); bias due to storage of samples for up to 2 months is lower than 10%; nominal uptake rate for benzene on RAD130 is 74.65 mL/min; and expanded uncertainty of the sampling and analytical method is 20.6%. The sampling and analytical method is therefore fit-for-purpose for the personal exposure measurements aimed at testing compliance with occupational exposure limit values for benzene. The method is also fit for short-duration exposure monitoring related to specific tasks, and other volatile organic compounds, usually found in the same workplaces, such as aliphatic and aromatic hydrocarbons and some oxygenated compounds, have also been studied. In particular, n-hexane and isopropyl benzene, whose classification is currently under revision, can be efficiently monitored by this technique.

Risk Classification Assessment and Early Warning of Heavy Metal Contamination in Meat Products

Risk classification assessment and early warning systems are indispensable tools and technologies in the realm of regulatory control. Evaluating and issuing early warnings regarding heavy metal contaminants in meat products play a pivotal role in ensuring public safety and maintaining societal stability. In this study, we focused on heavy metal pollutants such as lead, cadmium, chromium, and arsenic. We collected national inspection data for meat products from 20 provinces in 2020. Combining dietary structure data, toxicology information, and dietary exposure assessment methods, we constructed a risk assessment model for heavy metal contaminants in food. Furthermore, we employed an entropy weight-based analytic hierarchy process (AHP-EW) to classify the results of the risk assessment for heavy metal contaminants in food. This involved determining risk rating levels and thresholds. Finally, we constructed a multi-step food contaminant risk prediction model based on the Transformer framework. To validate the model’s performance, comparative assessments were conducted across 20 datasets using various models. The results clearly indicate that the Transformer model outperformed the others in 14 datasets, excelling in its ability to provide advanced warnings for heavy metal risks in meat products. This empowers relevant authorities to strengthen their regulatory oversight of meat products based on the procedures and models proposed in this study, ultimately enhancing the efficiency of food safety risk management.

Associations between exposure to organochlorine pesticides and diabetes risk: a systematic review

Abstract Background The prevalence of diabetes is on the rise worldwide, and recent studies have suggested that exposure to organochlorine pesticides (OCPs) may contribute to this development. However, the evidence remains inconclusive. Our study aimed to consolidate the existing evidence to understand better the association between OCP exposure and the risk of gestational diabetes mellitus (GDM) and type 2 diabetes (T2D). Methods We searched for longitudinal and cross-sectional studies in PubMed, Web of Science, and Google Scholar until April 1st, 2023. We included peer-reviewed, English-language studies focused on the general population with clearly stated exposure and outcome measures related to OCP, GDM, and T2D. We collected data on study type, sample size, covariates, and effect measures. The National Toxicology Program's Office of Health Assessment and Translation approach was used to ensure the study quality. Results We identified 33 studies, including 8 cohorts, 7 nested case-control, and 18 cross-sectional studies. The focus was mainly on p,p'-DDE, and p,p'-DDT exposures. Findings on the association between OCPs and GDM or T2D risks were mixed, with no conclusive evidence across the studies. For p,p'-DDT, and p,p'-DDE, GDM studies found no significant associations, while T2D studies showed non-significant and positive associations. Other OCP exposures showed mixed results for GDM and T2D. The majority of studies had a probably low risk of bias. Conclusions The association between OCP exposure and diabetes risk is inconclusive. Differences in study design, exposure assessment methods, and statistical approaches may contribute to inconsistent findings. Further research, including well-designed prospective studies and meta-analyses, is required. We must prioritize alternative pest control, raise awareness of OCP dangers, enforce regulations, and screen at-risk populations. OCP levels monitoring and healthcare guidance for high-exposure populations are also crucial. Key messages • Inconclusive evidence on the association between OCP exposure and the risk of GDM and T2D calls for further research, including prospective studies and meta-analyses. • Prioritizing OCP risk reduction, raising awareness, and at-risk populations are critical to protect public health.

Artificial light at night and breast cancer risk: The findings from CECILE study (France)

Abstract Background Environmental exposure to artificial light at night (LAN) has become ubiquitous in modern societies. Experimental and epidemiological studies suggested that LAN exposure disrupts circadian rhythm, inhibits melatonin production, and increases the risk of breast cancer. Objectives We aimed to assess the association of exposure to outdoor LAN with breast cancer risk, along with possible effect modifications of this association. Methods We used data from a population-based case-control study, including 1185 incident breast cancer cases and 1282 healthy controls enrolled in 2005-2007 from two French departments- Côte d’Or and Ille-et-Vilaine. Data for outdoor LAN exposure was obtained using radiance-calibrated images from Defense Meteorological Satellite Program (DMSP) for 1995-2006. Exposure was assessed for 10 years before inclusion in the study by cross-referencing the DMSP images and the geocoded locations of residences in ArcGIS. Logistic regression was used to obtain odds ratios (OR) and 95% confidence intervals (CI) for the association, adjusting for sociodemographic factors, urbanization, reproductive factors, lifestyle-related factors, night shift work, and air pollution. Results The overall OR for breast cancer per 1 interquartile range (IQR) increase in LAN exposure (159.9 nW/cm2/sr) was 0.98 (95% CI: 0.81-1.17). Subgroup analyses showed slightly higher ORs in post-menopausal women (OR: 1.15; 95% CI: 0.97-1.37) and a stronger association for HER2-positive breast tumors (OR: 1.55; 95% CI: 1.03-2.31). Conclusions We did not find any overall association between outdoor LAN and breast cancer; however, possible associations in certain subgroups were indicated. The strength of this study was the use of calibrated satellite images for exposure assessment and the consideration of a large set of potential confounders. Further large-scale studies using improved exposure assessment methods, including blue light and indoor exposure measurement, are required. Key messages • Light pollution is growing as the newest form of environmental pollution in modern society, potentially affecting health. • More studies are required to explore and ascertain its public health impact.

A Comparison of Measured Airborne and Self-Reported Secondhand Smoke Exposure in the MADRES Pregnancy Cohort Study.

Secondhand smoke (SHS) exposure during pregnancy is linked to adverse birth outcomes, such as low birth weight and preterm birth. While questionnaires are commonly used to assess SHS exposure, their ability to capture true exposure can vary, making it difficult for researchers to harmonize SHS measures. This study aimed to compare self-reported SHS exposure with measurements of airborne SHS in personal samples of pregnant women. SHS was measured on 48-hour integrated personal PM2.5 Teflon filters collected from 204 pregnant women, and self-reported SHS exposure measures were obtained via questionnaires. Descriptive statistics were calculated for airborne SHS measures, and analysis of variance tests assessed group differences in airborne SHS concentrations by self-reported SHS exposure. Participants were 81% Hispanic, with a mean (standard deviation [SD]) age of 28.2 (6.0) years. Geometric mean (SD) personal airborne SHS concentrations were 0.14 (9.41) µg/m3. Participants reporting lower education have significantly higher airborne SHS exposure (p = .015). Mean airborne SHS concentrations were greater in those reporting longer duration with windows open in the home. There was no association between airborne SHS and self-reported SHS exposure; however, asking about the number of smokers nearby in the 48-hour monitoring period was most correlated with measured airborne SHS (Two + smokers: 0.30 µg/m3 vs. One: 0.12 µg/m3 and Zero: 0.15 µg/m3; p = .230). Self-reported SHS exposure was not associated with measured airborne SHS in personal PM2.5 samples. This suggests exposure misclassification using SHS questionnaires and the need for harmonized and validated questions to characterize this exposure in health studies. This study adds to the growing body of evidence that measurement error is a major concern in pregnancy research, particularly in studies that rely on self-report questionnaires to measure SHS exposure. The study introduces an alternative method of SHS exposure assessment using objective optical measurements, which can help improve the accuracy of exposure assessment. The findings emphasize the importance of using harmonized and validated SHS questionnaires in pregnancy health research to avoid biased effect estimates. This study can inform future research, practice, and policy development to reduce SHS exposure and its adverse health effects.

Exposure to outdoor artificial light at night and breast cancer risk: a population-based case-control study in two French departments (the CECILE study)

BackgroundExposure to outdoor artificial light at night (LAN) disrupts circadian rhythms and is suspected of increasing the risk of breast cancer. To date, this is an understudied aspect of environmental pollution. In this study, we sought to assess the specific role of exposure to outdoor artificial light at night in breast cancer, independently of air pollution-related effects.MethodsData from a French population-based case-control study, including 1,185 incident breast cancer cases and 1,282 controls enrolled in 2005–2007, were used. Outdoor LAN exposure data were obtained using radiance-calibrated images from the Defense Meteorological Satellite Program (DMSP) for 1995–2006 by cross-referencing the DMSP images and the geocoded locations of residences in ArcGIS. The odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were obtained using logistic regression adjusting for multiple potential confounders, including air pollution.ResultsThe OR for overall breast cancer unadjusted for air pollution per interquartile range increase in LAN exposure was 1.05 (95% CI: 0.92–1.20). The OR decreased to 0.98 (95% CI: 0.81–1.17) after adjustment for ambient NO2 levels. Subgroup analyses showed slightly higher ORs in postmenopausal women (OR per IQR increase: 1.07; 95% CI: 0.85–1.35) and a positive association for HER2-positive breast tumors (OR: 1.55; 95% CI: 1.03–2.31).ConclusionOur results do not provide evidence that outdoor LAN exposure is associated with increased risk of breast cancer. However, an association was suggested for the HER2-positive subtype of breast cancer. Further large-scale studies with more precise exposure assessment methods, including blue light and indoor exposure measurements, and considering environmental exposures correlated with LAN exposure such as air pollution, are needed.

Beyond Residence: A Mobility-based Approach for Improved Evaluation of Human Exposure to Environmental Hazards.

Standard environmental hazard exposure assessment methods have been primarily based on residential places, neglecting individuals' hazard exposures due to activities outside home neighborhood and underestimating peoples' overall hazard exposures. To address this limitation, this study proposes a novel mobility-based index for the hazard exposure evaluation. Using large-scale human mobility data, we quantify the extent of population dwell time in high environmental hazard places in 239 US counties for three environmental hazards. We explore how human mobility extends the reach of environmental hazards and leads to the emergence of latent exposure for populations living outside high-hazard areas. Notably, neglect of mobility can lead to over 10% underestimation of hazard exposures. The interplay of spatial clustering in high-hazard regions and human movement trends creates "environmental hazard traps." Poor and ethnic minority residents disproportionately face multiple types of environmental hazards. This data-driven evidence supports the severity of these injustices. We also studied latent exposure arising from visits outside residents' home areas, revealing millions of the population having 5 to 10% of daily activities occur in high-exposure zones. Despite living in perceived safe areas, human mobility could expose millions of residents to different hazards. These findings provide crucial insights for targeted policies to mitigate these severe environmental injustices.

Investigating associations of exposure to blue spaces with natural and cause-specific mortality in Greece using different exposure assessment methods

Investigating associations of exposure to blue spaces with natural and cause-specific mortality in Greece using different exposure assessment methods

γ-H2AX and phospho-ATM enzyme-linked immunosorbent assays as biodosimetry methods for radiation exposure assessment: a pilot study.

In the event of a radiological incident, a fast and accurate biological dosimetry (biodosimetry) method for evaluating people who have been potentially exposed to ionising radiation is crucial. Among the many biodosimetry methods available, the immunodetection of phosphorylated H2AX (γ-H2AX) stands as a promising method to be used in the triage of patients exposed to radiation. Currently, the most common way to measure γ-H2AX levels is through fluorescence microscopy. In this pilot study, we assessed the feasibility of using an enzyme-linked immunosorbent assay (ELISA) for quantifying γ-H2AX for biodosimetry purposes. Moreover, the usefulness of measuring phosphorylated ATM (pATM) levels through ELISA for biodosimetry was also evaluated. Blood samples were obtained from three male donors (38y) and were irradiated with 60Co (0, 1, 2 and 6Gy). Peripheral blood mononuclear cells (PBMCs) were isolated and lysed before measuring γ-H2AX, total H2AX protein and pATM using ELISA kits. The dicentric chromosome assay (DCA) using whole blood was also performed for comparison. Data from all donors at each dose were pooled before statistical analysis. The ratio of γ-H2AX/total H2AX and pATM levels increased in a radiation-dose-dependent manner. The average γ-H2AX/total H2AX ratios were 0.816±0.219, 0.830±0.685, 1.276±1.151 and 1.606±1.098, whereas the average levels of pATM were 59.359±3.740, 63.366±0.840, 66.273±2.603 and 69.936±4.439, in PBMCs exposed to 0, 1, 2 and 6Gy, respectively. The linear-quadratic dose-response calibration curve for DCA was Y=0.0017 (±0.0010)+0.0251 (±0.0142)×D+0.0342 (±0.0039)×D2 $\boldsymbol{Y}=\mathbf{0.0017}\left(\pm \mathbf{0.0010}\right)+\mathbf{0.0208}\left(\pm \mathbf{0.0218}\right)\times \boldsymbol{D}+\mathbf{0.0350}\left(\pm \mathbf{0.0050}\right)\times{\boldsymbol{D}}^{\mathbf{2}}$. Overall, despite a large variability in the ratio of γ-H2AX/total H2AX among donors, the present study revealed the suitability of using the ratio of γ-H2AX/total H2AX and pATM for biodosimetry. Still, more research with a larger group of subjects is necessary to construct a reliable calibration curve for the ratio of γ-H2AX/total H2AX and pATM levels for biodosimetry.

Neighborhood gentrification, displacement, and severe maternal morbidity in California

Gentrification, a racialized and profit-driven process in which historically disinvested neighborhoods experience an influx of development that contributes to the improvement of physical amenities, increasing housing costs, and the dispossession and displacement of existing communities, may influence the risk of severe maternal morbidity (SMM). Leveraging a racially diverse population-based sample of all live hospital births in California between 2006 and 2017, we examined associations between neighborhood-level gentrification and SMM. SMM was defined as having one of 21 procedures and diagnoses, as described in the SMM index developed by Centers for Disease Control and Prevention. We compared three gentrification measures to determine which operationalization best captures aspects of gentrification most salient to SMM: Freeman, Landis 3-D, and Urban Displacement Project Gentrification and Displacement Typology. Descriptive analysis assessed bivariate associations between gentrification and birthing people's characteristics. Overall and race and ethnicity-stratified mixed-effects logistic models assessed associations between gentrification and SMM, adjusting for individual sociodemographic and pregnancy factors while accounting for clustering by census tract. The study sample included 5,256,905 births, with 72,718 cases of SMM (1.4%). The percentage of individuals living in a gentrifying neighborhood ranged from 5.7% to 11.7% across exposure assessment methods. Net of individual and pregnancy-related factors, neighborhood-level gentrification, as measured by the Freeman method, was protective against SMM (OR = 0.89, 95% CI: 0.86–0.93); in comparison, gentrification, as measured by the Gentrification and Displacement Typology, was associated with greater risk of SMM (OR = 1.18, 95% CI: 1.14–1.23). These associations were significant among non-Hispanic White, non-Hispanic Black, and Hispanic individuals. Findings demonstrate that gentrification plays a role in shaping the risk of SMM among birthing people in California. Differences in how gentrification is conceptualized and measured, such as an emphasis on housing affordability compared to a broader characterization of gentrification's multiple aspects, may explain the heterogeneity in the directions of observed associations.

Determinants of Pesticide Exposure in Occupational Studies: A Meta-Analysis.

Few epidemiological studies use exposure determinants specifically tailored to assess pesticide or plant protection product (PPP) exposures when assessing presumed association between occupational exposure and health outcomes among agricultural workers. This lack of exposure specificity could lead to results that fail to detect an association. It could be related to the lack of consensus on exposure assessment methods and the choice of exposure determinants. We conducted a meta-analysis following the PRISMA checklist to identify PPP exposure determinants used in occupational studies and identified exposure determinants that best characterized agricultural exposures to PPPs. Out of 1436 studies identified, 71 were included. The exposure determinants identified were active ingredients, chemical classes, types of PPP, crops, tasks, frequencies, duration, lifetime exposure days, and intensity-weighted exposure days. Only six over 17 associations between exposure determinants and health outcomes were found with moderate quality of evidence. Overall, epidemiological studies had difficulty defining relevant determinants to characterize PPP exposures for agricultural workers. We recommend that a standardized list of determinants for PPP exposures in occupational exposure studies should include information on formulations, intensity, duration, and frequency of PPP exposure. Harmonized data collection on exposure and health outcomes are required as well as standard units for each exposure determinant.

Developing high-resolution PM2.5 exposure models by integrating low-cost sensors, automated machine learning, and big human mobility data

Introduction: Traditional methods to estimate exposure to PM2.5 (particulate matter with less than 2.5 µm in diameter) have typically relied on limited regulatory monitors and do not consider human mobility and travel. However, the limited spatial coverage of regulatory monitors and the lack of consideration of mobility limit the ability to capture actual air pollution exposure.Methods: This study aims to improve traditional exposure assessment methods for PM2.5 by incorporating the measurements from a low-cost sensor network (PurpleAir) and regulatory monitors, an automated machine learning modeling framework, and big human mobility data. We develop a monthly-aggregated hourly land use regression (LUR) model based on automated machine learning (AutoML) and assess the model performance across eight metropolitan areas within the US.Results: Our results show that integrating low-cost sensor with regulatory monitor measurements generally improves the AutoML-LUR model accuracy and produces higher spatial variation in PM2.5 concentration maps compared to using regulatory monitor measurements alone. Feature importance analysis shows factors highly correlated with PM2.5 concentrations, including satellite aerosol optical depth, meteorological variables, vegetation, and land use. In addition, we incorporate human mobility data on exposure estimates regarding where people visit to identify spatiotemporal hotspots of places with higher risks of exposure, emphasizing the need to consider both visitor numbers and PM2.5 concentrations when developing exposure reduction strategies.Discussion: This research provides important insights for further public health studies on air pollution by comprehensively assessing the performance of AutoML-LUR models and incorporating human mobility into considering human exposure to air pollution.