Journal of Exposure Science and Environmental Epidemiology最新文献

{"title":"USEtox modeling of children’s exposures to Bisphenol A (BPA) and alternatives in toys","authors":"Lei Huang, Lynn Nakayama Wong, Xiaoying Zhou, Michelle Romero-Franco, Nathalie Pham, Hyeong-Moo Shin, Thomas McKone, Qingyu Meng, Olivier Jolliet","doi":"10.1038/s41370-025-00827-6","DOIUrl":"10.1038/s41370-025-00827-6","url":null,"abstract":"Bisphenol A (BPA) is a known endocrine disruptor, raising concerns about its presence in children’s toys. Despite its well-studied health effects, there is limited research addressing aggregate exposure to BPA in toys. Moreover, hazard and exposure information on BPA alternatives on the market is scarce. This study applies USEtox modeling to systematically evaluate young children’s exposure to BPA in toys and to compare the exposure between BPA and potential alternatives. We assessed the exposure to BPA and alternatives across representative toy archetypes and identified dominant exposure pathways and key influencing factors. We also estimated aggregate exposure for 3–6-year-olds and evaluated health risks by comparing exposure doses to toxicity benchmarks. We assumed a mass fraction of 300 ppm of BPA and alternatives across all toys. Among individual toy archetypes, the teething ring, cowboy suit, and doll resulted in the highest daily exposure dose, with the exposure dose generally decreasing with age. Direct dermal contact, mouthing, and dust ingestion were the primary exposure pathways. The estimated dose varied with the toy’s material, the chemical’s properties and initial mass fraction, and children’s use patterns. For aggregate exposure from multiple toys used by 3–6-year-olds, bisphenol F resulted in the highest daily exposure (2.6 µg/kg/d), while bisphenol AP had the lowest (0.14 µg/kg/d). Aggregate exposure to BPA and alternatives was dominated by different pathways depending on chemical properties. We also estimated the aggregate exposure mass of BPA during early childhood (6 months to <12 yrs) to be 13.4 mg. This study offers insights into children’s exposure to BPA and its alternatives in toys, filling in the knowledge gaps on exposures to these chemicals. USEtox modeling identifies dominant exposure pathways and evaluates aggregate exposure from the use of different toy types, demonstrating the ability of USEtox to quantify exposures to both well-known chemicals as well as new alternatives. The research underscores the variability in exposure doses based on toy material, chemical properties, and children’s behavior, providing valuable science-based and quantified data to guide safer product design. Policymakers can leverage these findings to prioritize products for regulation and protect public health.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"425-437"},"PeriodicalIF":4.7,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00827-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146183990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A personalized tutorial to improve understanding of individual chemical results and opportunities for reducing exposure","authors":"Katherine E. Boronow, Aaron Maruzzo, Rachel A. Morello-Frosch, Anisha Nakagawa Patil, Erin DeMicco, Phil Brown, Amy M. Padula, Sarah D. Geiger, Julia Green Brody","doi":"10.1038/s41370-026-00840-3","DOIUrl":"10.1038/s41370-026-00840-3","url":null,"abstract":"Environmental health studies frequently measure levels of harmful chemicals in people or personal spaces, and returning those individual levels is an ethical responsibility and important opportunity to teach people about chemical exposures and how to reduce them. We sought to enhance meaningful report-back by quantitatively evaluating a personalized tutorial designed to support environmental health literacy about personal chemical exposures. We developed a novel smartphone-based tutorial that used the Predict-Observe-Explain educational framework to increase understanding of personal results graphs and promote taking actions to lower exposure. We deployed the tutorial as part of report-back in the Illinois Kids Development Study and Chemicals in Our Bodies pregnancy cohorts, and we collected digital analytics on how participants (n = 295) interacted with it. We tested the effect of the tutorial on participants’ accuracy at answering four graph-reading questions and examined differences by educational attainment and socioeconomic status. The tutorial prompted participants to select exposure sources that were relevant to them, and we calculated response frequencies of participants’ self-reported interest in taking related actions. A total of 92% of participants (n = 270) completed the Predict and Observe phases of the tutorial. Among those participants, 70% (n = 188) correctly answered all four graph-reading questions on their first attempt (without tutorial assistance), and success increased to 96% (n = 258) after the tutorial provided feedback and participants could make a second attempt. Improvement was greatest among participants without a bachelor’s degree. Participants who answered the Explain phase (n = 182) expressed high interest in trying new behaviors to reduce exposure. While most participants understood their personal exposure graph without assistance, the tutorial successfully reduced differences in understanding by educational attainment. The tutorial was also effective at creating intentions to adopt health-protective behaviors. Scalable tools like this can support effective report-back in populations with all levels of environmental health literacy. To help people at all educational levels learn about their chemical levels and how to reduce them, we developed a personalized tutorial for use in reporting back results in environmental exposure studies. Before tutorial assistance, participants without a bachelor’s degree had lower understanding of their personal results graphs. Tutorial assistance successfully reduced differences in understanding between those with and without a bachelor’s degree. In addition, the tutorial was effective at creating intentions to adopt health-protective behaviors based on personalized recommendations for each participant. This scalable digital tool supports understanding and action during report-back of chemical exposure results.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"511-520"},"PeriodicalIF":4.7,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-026-00840-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146137683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of 18 mercapturic acids in urine samples from the German Environmental Specimen Bank—tackling the data gap in the human biomonitoring of VOCs in Europe","authors":"Nikola Pluym, Therese Burkhardt, Till Weber, Gerhard Scherer, Max Scherer, Marike Kolossa-Gehring","doi":"10.1038/s41370-026-00838-x","DOIUrl":"10.1038/s41370-026-00838-x","url":null,"abstract":"Human biomonitoring (HBM) plays a pivotal role in assessing exposure to toxicologically relevant chemicals, with urinary metabolites serving as key indicators. Despite the widespread implementation of HBM programs globally, certain metabolites, such as mercapturic acids (MAs) derived from volatile organic compounds (VOCs), remain understudied in non-occupationally exposed populations. To bridge this data gap, we analyzed 18 MAs in 360 24-h urine samples collected over a time span of 21 years from 2000 to 2021 in Germany. Two LC-MS/MS methods were utilized to quantify MAs in urine samples obtained from the Environmental Specimen Bank. Statistical analyses, including Kruskal-Wallis tests and Spearman correlations, were employed to evaluate temporal trends, sex-specific differences, and correlations between MAs. Quantification rates between 95 and 100% were obtained for 14 of the 18 MAs, with notable variations in concentrations among different metabolites. The most pronounced decrease in MA levels was observed from 2010/2015 to 2019 with a significant trend for 8 MAs, potentially reflecting changes in environmental exposures and regulations. Moreover, significant differences in urinary excretion per 24 h between males and females were observed for several MAs, highlighting the importance of considering sex in exposure assessments. Comprehensive human biomonitoring (HBM) data with regard to the exposure to volatile organic compounds (VOCs) in Europe is lacking. This prompted us to quantify 18 mercapturic acids as urinary VOC metabolites in 360 samples from the Environmental Specimen Bank collected between 2000 and 2021 in Germany. Our study demonstrates the ubiquitous exposure to numerous VOCs of high toxicological relevance, albeit with a decreasing trend over time for most of the metabolites. This emphasizes the need for a broader HBM to better understand the risk of VOC exposure in Germany and more general in Europe.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"490-503"},"PeriodicalIF":4.7,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-026-00838-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147808312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Co-exposure to environmental cadmium and arsenic leads to kidney damage even at lower concentrations","authors":"Jung-Eum Lee, Ju-Young Baek, Jung-Duck Park, Jun Young Chang, Byung-Sun Choi","doi":"10.1038/s41370-025-00828-5","DOIUrl":"10.1038/s41370-025-00828-5","url":null,"abstract":"While many studies have examined the effects of single heavy metal exposure, the impact of combined exposure to multiple heavy metals on kidney health remains underexplored. This study aims to assess the risk of kidney damage associated with relatively low concentrations of Cd and As, below established reference levels, and to investigate whether simultaneous exposure leads to synergistic or additive harmful effects. In this cross-sectional study of 1948 non-occupationally exposed individuals, we explored the relationship between environmental exposure to heavy metals at sub-occupational levels and the prevalence of kidney damage in this population. The risk of kidney damage was increased proportionally to urinary cadmium (uCd) and urinary arsenic (uAs) levels. Co-exposure to Cd and As at Co3 (both metals were above the 3rd tertile) resulted in a 2.65-fold increase in β2-microglobulin (MG) and a 4.41-fold increase in urinary total protein compared to those at Co1 (both metals were below the 3rd tertile). N-acetyl-beta-D-glucosaminidase (NAG) level was 7.42-fold higher at Co3 than at Co1. Subgroup analysis showed that the odds ratio of NAG level elevation increased by 2.74 folds when uCd level was >0.96 μg/g Creatinine (Cr) and uAs level was >8.17 μg/g Cr, and by 3.04-fold when uCd level was >1.86 μg/g Cr (3rd tertile) and uAs level was >4.71 μg/g Cr (2nd tertile). This suggests that co-exposure to both metals can cause kidney damage at concentrations lower than the reference level and even lower than the single metal concentration (uCd 1.86 μg/g Cr) that caused kidney damage. In this study, combined exposure to cadmium and arsenic causes kidney damage even at levels below reference thresholds. The findings highlight synergistic effects, with significant increases in biomarkers like β2-microglobulin and NAG.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"603-612"},"PeriodicalIF":4.7,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145844660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of residential and mobility-integrated air pollution exposures from tracking campaigns and agent-based modelling in Switzerland and the Netherlands","authors":"Kees de Hoogh, Benjamin Flückiger, Nicole Probst-Hensch, Ayoung Jeong, Medea Imboden, Aletta Karsies, Oliver Schmitz, Roel Vermeulen, Kalliopi Kyriakou, Aisha Ndiaye, Youchen Shen, Derek Karssenberg, Danielle Vienneau, Gerard Hoek","doi":"10.1038/s41370-025-00836-5","DOIUrl":"10.1038/s41370-025-00836-5","url":null,"abstract":"Studies investigating the health effects of long-term exposure to air pollution generally rely on the outdoor air pollution exposure assigned at the residential address. By ignoring time activity, population exposure misclassification could potentially lead to loss of precision or bias in epidemiological studies. We aimed to assess how residential-based air pollution exposures compared with “real” tracking-based exposures. We conducted two tracking campaigns in Switzerland (CH) and the Netherlands (NL) with 686 participants followed for 2 weeks with GPS trackers whilst keeping time activity diaries. In addition, we simulated mobility and commuting tracks for the same subjects using agent-based modeling (ABM) with information from census and travel survey data to estimate mobility-integrated air pollution exposures. Exposures were calculated by overlaying residential address, measured (GPS) and modeled (ABM) tracks with annual average hourly NO2 and PM2.5 concentration surfaces. We found strong agreements between residential and tracking-based exposures in CH for both pollutants (R2 > 0.76) and NL for NO2 (R2 = 0.79), and weaker agreement in NL for PM2.5 (R2 = 0.56). Similarly, the agreement between ABM and tracking-based exposures was strong for NO2 (R2 > 0.77 in CH and NL), while for PM2.5 it was stronger in CH (R2 = 0.80) than in NL (R2 = 0.54). The highest correlations were between residential and ABM exposures (R2 > 0.96 for both pollutants). Using information commonly available even in large administrative cohorts, we found that exposures derived from the tracking campaigns agreed well with ABM in our two study areas. Our study supports the use of residential exposures in epidemiological studies on long-term health effects of air pollution, whilst acknowledging that ABM, especially if the work location is known, can be a useful tool to estimate mobility-integrated exposures.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"469-478"},"PeriodicalIF":4.7,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00836-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145844672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comparative study of urinary mycotoxin biomarkers co-occurrence patterns and cumulative risk assessment in population from three typical areas in China","authors":"Ying-Ying Zhou, Ming-Lu Li, Xiao-Dan Wang, Hai-Bin Xu, Jiang Liang","doi":"10.1038/s41370-025-00830-x","DOIUrl":"10.1038/s41370-025-00830-x","url":null,"abstract":"This biomonitoring study investigated levels of multi-mycotoxin biomarkers in the urine of subjects living in three different geographic locations and dietary patterns in China. This study provides a comprehensive understanding of the inner-exposure characteristics to multiple mycotoxins within the Chinese population. The study involved a total of 311 healthy volunteers, with 103 from Anhui Province, 102 from Henan Province, and 106 from Sichuan Province. UHPLC-MS/MS was employed to analyze seven mycotoxin biomarkers [total deoxynivalenol (DONt), β-zearalenol (β-ZEL), nivalenol (NIV), α-zearalenol (α-ZEL), diacetoxycyclohexenol (DAS), zearalenone (ZEN), aflatoxin M1 (AFM1)] in urine samples. Urinary biomarker concentrations were used to estimate probable daily intake (PDI), further calculate hazard quotient (HQ), and hazard index (HI). In the study population, DON was the most prevalent (100%) with a mean concentration of 90.77 ng/ml, followed by β-ZEL (27.97%), NIV (24.76%), α-ZEL (24.12%), DAS (12.86%), ZEN (6.11%) and AFM1 (10.96%) in urine samples. The mean PDI for DONt, ZENt and NIV in the total population were 3.02 µg/kg bw/d, 0.01 µg/kg bw/d and 0.79 µg/kg bw/d, respectively. There were 61.09% of the total population with an HQ > 1 for DONt, while 0.96% and 10.93% had an HQ > 1 for ZENt and NIV, respectively. Moreover, approximately 64.31% of urine samples exhibited the co-occurrence of two or more mycotoxins. The most common binary and ternary combinations were DONt-ZENt (46.34%) and DONt-ZENt-NIV (19.02%). The percentages of HI > 1 for DONt-ZENt and DONt-ZENt-NIV were 61.09% and 69.77% respectively. In the present study, the co-occurrence pattern and cumulative risk of the metabolite biomarkers of multi-mycotoxins were firstly revealed in three typical areas with different climate types and dietary patterns. This study helps assess the health risks of mycotoxin exposure under different environmental and dietary conditions, reveals the relationship between diet and mycotoxin exposure, and provides scientific support for mitigating the harmful effects of mycotoxins on human health.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"438-449"},"PeriodicalIF":4.7,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sociodemographic predictors of PFAS exposure among a combined sample of U.S. pregnant women: an Environmental influences on Child Health Outcomes (ECHO) public-use dataset analysis","authors":"Jessie A. Gleason, Kristen Lyall, Jerald A. Fagliano, Lucy F. Robinson, Gloria B. Post, Anneclaire J. De Roos","doi":"10.1038/s41370-025-00833-8","DOIUrl":"10.1038/s41370-025-00833-8","url":null,"abstract":"Per- and polyfluoroalkyl substances (PFAS) are chemicals widely used in manufacturing since the 1940s and are associated with developmental and immune effects at exposure levels observed in the general population. To evaluate differences in exposure to 14 PFAS by sociodemographic factors among U.S. pregnant women. We combined maternal PFAS measurements from pregnant women from twelve pediatric cohorts drawn from the Environmental influences on Child Health Outcomes (ECHO) consortium’s public-use dataset (n = 3,043). Geometric means were estimated by race, ethnicity, and education. We used multivariable linear regression to estimate percent difference in log-transformed PFAS levels and logistic regression to assess odds of detectable PFAS levels by sociodemographic factors, adjusting for cohort, maternal age, trimester, year of sample collection, parity, BMI, fish consumption, and breastfeeding. Compared with White mothers, Black mothers had lower levels of PFOA (−23%; 95% CI −29%, −16%), PFOS (−9%; 95% CI −16%, −1%), and PFHxS (−23%; 95% CI −29%, −14%) based on linear analysis, and lower detection of PFOSA, EtFOSAA, PFDoDA, and PFPeA and higher detection of PFBS and PFHxA based on logistic analysis. Compared with White mothers, Asian mothers had higher levels of PFNA ( + 26%; 95% CI 13%, 40%), PFDA ( + 60%, 95% CI 36%, 89%), and PFUnDA (+95%; 95% CI 63%, 134%) based on linear analysis and higher detection of PFPeA based on logistic regression. Greater weekly fish consumption was found to be a significant predictor of PFAS concentrations but did not attenuate associations with Asian race. Compared with non-Hispanic mothers, Hispanic mothers had lower levels of most of PFAS analytes studied. Higher levels of maternal education were associated with increased levels of most PFAS analytes. In data drawn from this US consortium, documents continued widespread PFAS exposure, with higher levels noted for certain racial groups, non-Hispanic ethnicity, and higher educational attainment. We analyzed data from a combined sample of U.S. pregnant women (n = 3043) in the ECHO public-use dataset to assess exposure to 14 per- and polyfluoroalkyl substances (PFAS), including both legacy and less-studied compounds. Higher levels of some PFAS were observed by race, ethnicity, and education. Our findings document continued widespread PFAS exposure in the U.S., including among fetuses and newborns who may be especially vulnerable to developmental and immune effects. Ongoing biomonitoring is critical for understanding changing exposure patterns across racial, ethnic, and socioeconomic groups.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"459-468"},"PeriodicalIF":4.7,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00833-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145764940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Indoor dust, immune activation, and household exposure risk after Hurricane Maria: a two-year pilot prospective cohort study in Puerto Rico","authors":"Felix E. Rivera-Mariani, Hayat Srour, Filipa Godoy-Vitorino, Benjamín Bolaños-Rosero, Lorraine N. Vélez-Torres, Juan P. Maestre, Kerry Kinney, Humberto Cavallin","doi":"10.1038/s41370-025-00835-6","DOIUrl":"10.1038/s41370-025-00835-6","url":null,"abstract":"Hurricane Maria left many homes in Puerto Rico with prolonged flooding, structural damage, and indoor microbial growth, conditions that can drive respiratory illness and immune dysregulation. To assess the pro-inflammatory potential of post-flooding indoor dust and track two-year shifts in household risk profiles by integrating pro-inflammatory biomarkers, fungal exposure, and self-reported structural damage, mental health, and respiratory outcomes. Dust samples were collected from 50 households in a San Juan community one year and again from 35 of those same households two years after the hurricane. Dust sample extracts (DSEs) were prepared and incubated with pooled peripheral blood from volunteers residing outside Puerto Rico. Pro-inflammatory cytokines interleukin-1β (IL-1β), IL-6, and IL-8 were quantified using ELISA; airborne fungal abundance was assessed on malt extract and G25N agars. Survey data captured self-reported respiratory and mental-health scores using the SF-12v2 Health Survey, structural water damage, and remediation efforts. Principal component analysis (PCA) and k-means clustering were applied to identify household clusters, while Sankey plots were used to visualize the transitions of household risk. IL-1β emerged as the most responsive cytokine, showing the greatest median reduction from Year 1 to Year 2 and across household water-damage categories. Three clusters emerged in Year 1, driven by structural damage, IL-1β, and fungal load. By Year 2, only two clusters remained, shaped more by self-reported respiratory and psychological distress than by structural damage. Sankey analysis revealed that some households transitioned into higher-risk profiles over time despite apparent household structural recovery.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"521-530"},"PeriodicalIF":4.7,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145759101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint impact of prenatal polycyclic aromatic hydrocarbons, anxiety and depression exposure on birth outcomes across pre-pregnancy BMI categories","authors":"Yunfei Jia, Hualong Zhen, Shuilan Liu, Beibei Zhu, Fengying Hu, Hengshun Cheng, Wei Jv, Yiran Li, Mengjuan Lu, Haiyan Li, Yue Gu, Fangbiao Tao, Minmin Jiang","doi":"10.1038/s41370-025-00829-4","DOIUrl":"10.1038/s41370-025-00829-4","url":null,"abstract":"While polycyclic aromatic hydrocarbons (PAHs) and maternal psychological distress (anxiety/depression) are risk factors for adverse birth outcomes, their joint effects remain poorly understood, particularly across different pre-pregnancy BMI categories. To examine the individual and combined effects of prenatal PAHs exposure and maternal psychological distress on birth outcomes, with emphasis on effect modification by pre-pregnancy BMI. In this prospective cohort study, we enrolled 699 pregnant women from two primary hospitals in Hefei, China, from April 2020 through October 2022. Urinary PAHs were assessed using gas chromatography tandem triple quadrupole mass spectrometry (GC-MS/MS). Anxiety and depression symptoms were assessed via Generalized Anxiety Disorder Scale (GAD-7) and Edinburgh Postnatal Depression Scale (EPDS), respectively. Logistic regression and BKMR models were used to explore the individual and combined effects of prenatal PAHs exposure and psychological distress on birth outcomes. Logistic regression revealed significant associations between PAHs and anxiety symptoms with adverse birth outcomes. In the overall population, 1-OHPHe is significantly associated with low birth weight (LBW) (OR: 2.21, 95% CI: 1.25, 4.03), 2-OHDBF and 2-OHPHe were significantly associated with preterm birth (PTB), respectively (1.43, 95% CI: 1.04, 1.98; 1.38, 95% CI: 1.02, 1.90). GAD-7 score in the third tertile was positively linked to macrosomia (OR: 3.27, 95% CI: 1.28, 10.06). BKMR demonstrated that among pre-pregnancy overweight/obese women (BMI ≧ 24.0), combined exposure to PAHs, depression, and anxiety was positively associated with LBW. Meanwhile, among the women with normal pre-pregnancy BMI (18.5–23.9), combined exposure was positively associated with macrosomia and PTB. Study results indicate that combined exposure to PAHs, anxiety, and depression increases the risk of adverse birth outcomes in pregnant women.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"594-602"},"PeriodicalIF":4.7,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145752414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing microenvironment classification models for personal exposure assessment based on global positioning system tracking data","authors":"Jiwoong Yu, Hyunwoo Jeon, Kiyoung Lee, Woojoo Lee","doi":"10.1038/s41370-025-00832-9","DOIUrl":"10.1038/s41370-025-00832-9","url":null,"abstract":"Accurate personal exposure assessment to air pollution is crucial in environmental epidemiological studies, but it remains challenging due to substantial differences in pollutant concentrations between indoor and outdoor environments. Indirect assessment methods estimate personal exposure by incorporating microenvironment-specific pollutant concentrations and personal time-activity patterns, while requiring participants to record detailed time-location diaries. This study aims to develop microenvironment classification models using global positioning system (GPS) tracking data. We used data from the Korean Air pollutant EXposure (KAPEX) model project, which reflects seasonal and daily activity patterns of the Korean urban population. Three microenvironment categorizations were defined: Two-level (indoor and outdoor), Three-level (indoor, walk, and transit), and Four-level (home and workplace, other indoor, walk, and transit), where the outdoor category is subdivided into walk and transit in Three- and Four-level. Classification models were developed for each categorization using various machine learning (ML) and deep learning (DL) methods, incorporating both individual mobility patterns and GPS signal quality information. Important variables contributing to classification accuracy were identified using interpretable ML or DL methods. Random forest achieved the highest test AUROC of 0.963 and 0.958 for the Two-level and Three-level categorization, respectively, while boosting achieved the highest test AUROC of 0.918 for the Four-level categorization. Variables related to both mobility patterns and GPS signal quality were found to enhance classification accuracy. These findings highlight that incorporating both mobility patterns and signal quality into ML models significantly improves classification accuracy.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 3","pages":"450-458"},"PeriodicalIF":4.7,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145728085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}