Pub Date : 2024-05-06DOI: 10.1038/s41370-024-00681-y
Eva C M Vitucci, Oladayo Oladeji, Albert A Presto, Carolyn L Cannon, Natalie M Johnson
Background: On April 11th, 2023, the My Way Trading (MWT) recycling facility in Richmond, Indiana caught fire, mandating the evacuation of local residents and necessitating the U.S. Environmental Protection Agency (EPA) to conduct air monitoring. The EPA detected elevated levels of plastic combustion-related air pollutants, including hydrogen cyanide and benzene.
Objective: We aimed to identify these and other volatile organic compounds (VOCs) present as well as to identify the potential hazard of each compound for various human health effects.
Methods: To identify the VOCs, we conducted air monitoring at sites within and bordering the evacuation zone using proton transfer reaction mass spectrometry (PTR-MS) and non-targeted analysis (NTA). To facilitate risk assessment of the emitted VOCs, we used the EPA Hazard Comparison Dashboard.
Results: We identified 46 VOCs, within and outside the evacuation zone, with average detection levels above local background levels measured in Middletown, OH. Levels of hydrogen cyanide and 4 other VOCs were at least 1.8-fold higher near the incidence site in comparison to background levels and displayed unique temporal and spatial patterns. The 46 VOCs identified had the highest hazardous potential for eye and skin irritation, with approximately 45% and 39%, respectively, of the VOCs classified as high and very high hazards for these endpoints. Notably, all detected VOC levels were below the hazard thresholds set for single VOC exposures; however, hazard thresholds for exposure to VOC mixtures are currently unclear.
Impact: This study serves as a proof-of-concept that PTR-MS coupled with NTA can facilitate rapid identification and hazard assessment of VOCs emitted following anthropogenic disasters. Furthermore, it demonstrates that this approach may augment future disaster responses to quantify additional VOCs present in complex combustion mixtures.
背景：2023 年 4 月 11 日，位于印第安纳州里士满（Richmond）的 My Way Trading (MWT) 回收设施起火，当地居民被迫疏散，美国环保署（EPA）也不得不对其进行空气监测。EPA 检测到与塑料燃烧有关的空气污染物水平升高，其中包括氰化氢和苯：我们的目标是确定这些和其他挥发性有机化合物 (VOC)，并确定每种化合物对各种人体健康影响的潜在危害：为了确定挥发性有机化合物，我们使用质子转移反应质谱法（PTR-MS）和非目标分析法（NTA）对疏散区内和疏散区周边的地点进行了空气监测。为了便于对排放的挥发性有机化合物进行风险评估，我们使用了美国环保局的危害比较仪表板：结果：我们发现在俄亥俄州米德尔敦测量到的疏散区域内外有 46 种挥发性有机化合物的平均检测水平高于当地背景水平。与背景水平相比，氰化氢和其他 4 种挥发性有机化合物在事发地点附近的水平至少高出 1.8 倍，并呈现出独特的时空模式。已确定的 46 种挥发性有机化合物对眼睛和皮肤的潜在危害最大，分别有约 45% 和 39% 的挥发性有机化合物被归类为对这些终点的高危和极高危。值得注意的是，所有检测到的挥发性有机化合物水平都低于为接触单一挥发性有机化合物而设定的危害阈值；然而，接触挥发性有机化合物混合物的危害阈值目前尚不明确：本研究证明了 PTR-MS 与 NTA 联用可促进对人为灾害后排放的挥发性有机化合物进行快速识别和危害评估。此外，该研究还表明，这种方法可以增强未来的灾难应对能力，对复杂燃烧混合物中的其他挥发性有机化合物进行量化。
{"title":"The application of PTR-MS and non-targeted analysis to characterize VOCs emitted from a plastic recycling facility fire.","authors":"Eva C M Vitucci, Oladayo Oladeji, Albert A Presto, Carolyn L Cannon, Natalie M Johnson","doi":"10.1038/s41370-024-00681-y","DOIUrl":"10.1038/s41370-024-00681-y","url":null,"abstract":"<p><strong>Background: </strong>On April 11th, 2023, the My Way Trading (MWT) recycling facility in Richmond, Indiana caught fire, mandating the evacuation of local residents and necessitating the U.S. Environmental Protection Agency (EPA) to conduct air monitoring. The EPA detected elevated levels of plastic combustion-related air pollutants, including hydrogen cyanide and benzene.</p><p><strong>Objective: </strong>We aimed to identify these and other volatile organic compounds (VOCs) present as well as to identify the potential hazard of each compound for various human health effects.</p><p><strong>Methods: </strong>To identify the VOCs, we conducted air monitoring at sites within and bordering the evacuation zone using proton transfer reaction mass spectrometry (PTR-MS) and non-targeted analysis (NTA). To facilitate risk assessment of the emitted VOCs, we used the EPA Hazard Comparison Dashboard.</p><p><strong>Results: </strong>We identified 46 VOCs, within and outside the evacuation zone, with average detection levels above local background levels measured in Middletown, OH. Levels of hydrogen cyanide and 4 other VOCs were at least 1.8-fold higher near the incidence site in comparison to background levels and displayed unique temporal and spatial patterns. The 46 VOCs identified had the highest hazardous potential for eye and skin irritation, with approximately 45% and 39%, respectively, of the VOCs classified as high and very high hazards for these endpoints. Notably, all detected VOC levels were below the hazard thresholds set for single VOC exposures; however, hazard thresholds for exposure to VOC mixtures are currently unclear.</p><p><strong>Impact: </strong>This study serves as a proof-of-concept that PTR-MS coupled with NTA can facilitate rapid identification and hazard assessment of VOCs emitted following anthropogenic disasters. Furthermore, it demonstrates that this approach may augment future disaster responses to quantify additional VOCs present in complex combustion mixtures.</p>","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140850897","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}
Pub Date : 2024-05-04DOI: 10.1038/s41370-024-00663-0
Jessica L. Levasseur, Kate Hoffman, Sharon Zhang, Ellen M. Cooper, Heather M. Stapleton
People are exposed to a variety of chemicals each day as a result of their personal care product (PCP) use. This study was designed to determine if silicone wristbands provide a quantitative estimate of internal dose for phenols commonly associated with PCPs, with a focus on triclosan and four parabens: methyl-, ethyl-, propyl-, and butylparaben. Uptake of these compounds into wristbands and correlations with internal dose were assessed. Ten adults from central North Carolina wore five silicone wristbands, with one wristband removed each day for 5 days. Each participant provided a 24 h urine sample and a random spot urine sample each day, in which paraben and triclosan metabolites were evaluated. All parabens and triclosan were detected frequently in wristbands and, except for butylparaben, in urine samples. Wristband and spot urine concentrations of parabens and triclosan were both compared to a measurement of internal dose (i.e., the total metabolite mass excreted over 5 days as a measurement of internal dose). The two most hydrophobic compounds investigated, butylparaben and triclosan, displayed significant linear uptake in wristbands over 5 days, whereas concentrations of methyl- and ethylparaben displayed a steady state concentration. In general, wristbands and spot urine samples were similarly correlated to internal dose for frequently detected parabens and triclosan. However, wristbands have additional advantages including higher detection rates and reduced participant burden that may make them more suitable tools for assessing exposure to PCPs.
{"title":"Monitoring human exposure to four parabens and triclosan: comparing silicone wristbands with spot urine samples as predictors of internal dose","authors":"Jessica L. Levasseur, Kate Hoffman, Sharon Zhang, Ellen M. Cooper, Heather M. Stapleton","doi":"10.1038/s41370-024-00663-0","DOIUrl":"10.1038/s41370-024-00663-0","url":null,"abstract":"People are exposed to a variety of chemicals each day as a result of their personal care product (PCP) use. This study was designed to determine if silicone wristbands provide a quantitative estimate of internal dose for phenols commonly associated with PCPs, with a focus on triclosan and four parabens: methyl-, ethyl-, propyl-, and butylparaben. Uptake of these compounds into wristbands and correlations with internal dose were assessed. Ten adults from central North Carolina wore five silicone wristbands, with one wristband removed each day for 5 days. Each participant provided a 24 h urine sample and a random spot urine sample each day, in which paraben and triclosan metabolites were evaluated. All parabens and triclosan were detected frequently in wristbands and, except for butylparaben, in urine samples. Wristband and spot urine concentrations of parabens and triclosan were both compared to a measurement of internal dose (i.e., the total metabolite mass excreted over 5 days as a measurement of internal dose). The two most hydrophobic compounds investigated, butylparaben and triclosan, displayed significant linear uptake in wristbands over 5 days, whereas concentrations of methyl- and ethylparaben displayed a steady state concentration. In general, wristbands and spot urine samples were similarly correlated to internal dose for frequently detected parabens and triclosan. However, wristbands have additional advantages including higher detection rates and reduced participant burden that may make them more suitable tools for assessing exposure to PCPs.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"34 4","pages":"670-678"},"PeriodicalIF":4.1,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11303247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140863981","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}
Pub Date : 2024-05-02DOI: 10.1038/s41370-024-00674-x
Gyeyoon Yim, Katerina Margetaki, Megan E. Romano, Maria Kippler, Marina Vafeiadi, Theano Roumeliotaki, Vicky Bempi, Shohreh F. Farzan, Leda Chatzi, Caitlin G. Howe
Growing evidence suggests that cardiovascular disease develops over the lifetime, often beginning in childhood. Metal exposures have been associated with cardiovascular disease and important risk factors, including dyslipidemia, but prior studies have largely focused on adult populations and single metal exposures. To investigate the individual and joint impacts of multiple metal exposures on lipid levels during childhood. This cross-sectional study included 291 4-year-old children from the Rhea Cohort Study in Heraklion, Greece. Seven metals (manganese, cobalt, selenium, molybdenum, cadmium, mercury, and lead) were measured in whole blood using inductively coupled plasma mass spectrometry. Serum lipid levels included total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol. To determine the joint and individual impacts of child metal exposures (log2-transformed) on lipid levels, Bayesian kernel machine regression (BKMR) was employed as the primary multi-pollutant approach. Potential effect modification by child sex and childhood environmental tobacco smoke exposure was also evaluated. BKMR identified a positive association between the metal mixture and both total and LDL cholesterol. Of the seven metals examined, selenium (median 90.6 [IQR = 83.6, 96.5] µg/L) was assigned the highest posterior inclusion probability for both total and LDL cholesterol. A difference in LDL cholesterol of 8.22 mg/dL (95% CI = 1.85, 14.59) was observed when blood selenium was set to its 75th versus 25th percentile, holding all other metals at their median values. In stratified analyses, the positive association between selenium and LDL cholesterol was only observed among boys or among children exposed to environmental tobacco smoke during childhood. Growing evidence indicates that cardiovascular events in adulthood are the consequence of the lifelong atherosclerotic process that begins in childhood. Therefore, public health interventions targeting childhood cardiovascular risk factors may have a particularly profound impact on reducing the burden of cardiovascular disease. Although growing evidence supports that both essential and nonessential metals contribute to cardiovascular disease and risk factors, such as dyslipidemia, prior studies have mainly focused on single metal exposures in adult populations. To address this research gap, the current study investigated the joint impacts of multiple metal exposures on lipid concentrations in early childhood.
{"title":"Metal mixture exposures and serum lipid levels in childhood: the Rhea mother-child cohort in Greece","authors":"Gyeyoon Yim, Katerina Margetaki, Megan E. Romano, Maria Kippler, Marina Vafeiadi, Theano Roumeliotaki, Vicky Bempi, Shohreh F. Farzan, Leda Chatzi, Caitlin G. Howe","doi":"10.1038/s41370-024-00674-x","DOIUrl":"10.1038/s41370-024-00674-x","url":null,"abstract":"Growing evidence suggests that cardiovascular disease develops over the lifetime, often beginning in childhood. Metal exposures have been associated with cardiovascular disease and important risk factors, including dyslipidemia, but prior studies have largely focused on adult populations and single metal exposures. To investigate the individual and joint impacts of multiple metal exposures on lipid levels during childhood. This cross-sectional study included 291 4-year-old children from the Rhea Cohort Study in Heraklion, Greece. Seven metals (manganese, cobalt, selenium, molybdenum, cadmium, mercury, and lead) were measured in whole blood using inductively coupled plasma mass spectrometry. Serum lipid levels included total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol. To determine the joint and individual impacts of child metal exposures (log2-transformed) on lipid levels, Bayesian kernel machine regression (BKMR) was employed as the primary multi-pollutant approach. Potential effect modification by child sex and childhood environmental tobacco smoke exposure was also evaluated. BKMR identified a positive association between the metal mixture and both total and LDL cholesterol. Of the seven metals examined, selenium (median 90.6 [IQR = 83.6, 96.5] µg/L) was assigned the highest posterior inclusion probability for both total and LDL cholesterol. A difference in LDL cholesterol of 8.22 mg/dL (95% CI = 1.85, 14.59) was observed when blood selenium was set to its 75th versus 25th percentile, holding all other metals at their median values. In stratified analyses, the positive association between selenium and LDL cholesterol was only observed among boys or among children exposed to environmental tobacco smoke during childhood. Growing evidence indicates that cardiovascular events in adulthood are the consequence of the lifelong atherosclerotic process that begins in childhood. Therefore, public health interventions targeting childhood cardiovascular risk factors may have a particularly profound impact on reducing the burden of cardiovascular disease. Although growing evidence supports that both essential and nonessential metals contribute to cardiovascular disease and risk factors, such as dyslipidemia, prior studies have mainly focused on single metal exposures in adult populations. To address this research gap, the current study investigated the joint impacts of multiple metal exposures on lipid concentrations in early childhood.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"34 4","pages":"688-698"},"PeriodicalIF":4.1,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140848893","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}
Pub Date : 2024-04-27DOI: 10.1038/s41370-024-00675-w
Yi Shi, Kanak Choudhury, Xiaoyi Sopko, Sarah Adham, Edward Chikwana
Background: When experimentally determined dislodgeable foliar residue (DFR) values are not available, regulatory agencies use conservative default DFR values as a first-tier approach to assess post-application dermal exposures to plant protection products (PPPs). These default values are based on a limited set of field studies, are very conservative, and potentially overestimate exposures from DFRs.
Objective: Use Random Forest to develop classification and regression-type ensemble models to predict DFR values after last application (DFR0) by considering experimentally-based variability due to differences in physical and chemical properties of PPPs, agronomic practices, crop type, and climatic conditions.
Methods: Random Forest algorithm was used to develop in-silico ensemble DFR0 prediction models using more than 100 DFR studies from Corteva AgriscienceTM. Several variables related to the active ingredient (a.i.) that was applied, crop, and climate conditions at the time of last application were considered as model parameters.
Results: The proposed ensemble models demonstrated 98% prediction accuracy that if a DFR0 is predicted to be less than the European Food Safety Authority (EFSA) default DFR0 value of 3 µg/cm2/kg a.i./ha, it is highly indicative that the measured DFR value will be less than the default if the study is conducted. If a value is predicted to be larger than or equal to the EFSA default, the model has an 83% prediction accuracy.
Impact statement: This manuscript is expected to have significant impact globally as it provides: A framework for incorporating in silico DFR data into worker exposure assessment, A roadmap for a tiered approach for conducting re-entry exposure assessment, and A proof of concept for using existing DFR data to provide a read-across framework that can easily be harmonized across all regulatory agencies to provide more robust assessments for PPP exposures.
{"title":"In-silico prediction of dislodgeable foliar residues and regulatory implications for plant protection products.","authors":"Yi Shi, Kanak Choudhury, Xiaoyi Sopko, Sarah Adham, Edward Chikwana","doi":"10.1038/s41370-024-00675-w","DOIUrl":"https://doi.org/10.1038/s41370-024-00675-w","url":null,"abstract":"<p><strong>Background: </strong>When experimentally determined dislodgeable foliar residue (DFR) values are not available, regulatory agencies use conservative default DFR values as a first-tier approach to assess post-application dermal exposures to plant protection products (PPPs). These default values are based on a limited set of field studies, are very conservative, and potentially overestimate exposures from DFRs.</p><p><strong>Objective: </strong>Use Random Forest to develop classification and regression-type ensemble models to predict DFR values after last application (DFR0) by considering experimentally-based variability due to differences in physical and chemical properties of PPPs, agronomic practices, crop type, and climatic conditions.</p><p><strong>Methods: </strong>Random Forest algorithm was used to develop in-silico ensemble DFR0 prediction models using more than 100 DFR studies from Corteva Agriscience<sup>TM</sup>. Several variables related to the active ingredient (a.i.) that was applied, crop, and climate conditions at the time of last application were considered as model parameters.</p><p><strong>Results: </strong>The proposed ensemble models demonstrated 98% prediction accuracy that if a DFR0 is predicted to be less than the European Food Safety Authority (EFSA) default DFR0 value of 3 µg/cm<sup>2</sup>/kg a.i./ha, it is highly indicative that the measured DFR value will be less than the default if the study is conducted. If a value is predicted to be larger than or equal to the EFSA default, the model has an 83% prediction accuracy.</p><p><strong>Impact statement: </strong>This manuscript is expected to have significant impact globally as it provides: A framework for incorporating in silico DFR data into worker exposure assessment, A roadmap for a tiered approach for conducting re-entry exposure assessment, and A proof of concept for using existing DFR data to provide a read-across framework that can easily be harmonized across all regulatory agencies to provide more robust assessments for PPP exposures.</p>","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140853118","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}
Pub Date : 2024-04-27DOI: 10.1038/s41370-024-00680-z
Bagavathy Shanmugam Karthikeyan, Tuulia Hyötyläinen, Tannaz Ghaffarzadegan, Eric Triplett, Matej Orešič, Johnny Ludvigsson
Prenatal exposure to environmental contaminants is a significant health concern because it has the potential to interfere with host metabolism, leading to adverse health effects in early childhood and later in life. Growing evidence suggests that genetic and environmental factors, as well as their interactions, play a significant role in the development of autoimmune diseases. In this study, we hypothesized that prenatal exposure to environmental contaminants impacts cord serum metabolome and contributes to the development of autoimmune diseases. We selected cord serum samples from All Babies in Southeast Sweden (ABIS) general population cohort, from infants who later developed one or more autoimmune-mediated and inflammatory diseases: celiac disease (CD), Crohn’s disease (IBD), hypothyroidism (HT), juvenile idiopathic arthritis (JIA), and type 1 diabetes (T1D) (all cases, N = 62), along with matched controls (N = 268). Using integrated exposomics and metabolomics mass spectrometry (MS) based platforms, we determined the levels of environmental contaminants and metabolites. Differences in exposure levels were found between the controls and those who later developed various diseases. High contaminant exposure levels were associated with changes in metabolome, including amino acids and free fatty acids. Specifically, we identified marked associations between metabolite profiles and exposure levels of deoxynivalenol (DON), bisphenol S (BPS), and specific per- and polyfluorinated substances (PFAS). Abnormal metabolism is a common feature preceding several autoimmune and inflammatory diseases. However, few studies compared common and specific metabolic patterns preceding these diseases. Here we hypothesized that exposure to environmental contaminants impacts cord serum metabolome, which may contribute to the development of autoimmune diseases. We found differences in exposure levels between the controls and those who later developed various diseases, and importantly, on the metabolic changes associated with the exposures. High contaminant exposure levels were associated with specific changes in metabolome. Our study suggests that prenatal exposure to specific environmental contaminants alters the cord serum metabolomes, which, in turn, might increase the risk of various immune-mediated diseases.
{"title":"Prenatal exposure to environmental contaminants and cord serum metabolite profiles in future immune-mediated diseases","authors":"Bagavathy Shanmugam Karthikeyan, Tuulia Hyötyläinen, Tannaz Ghaffarzadegan, Eric Triplett, Matej Orešič, Johnny Ludvigsson","doi":"10.1038/s41370-024-00680-z","DOIUrl":"10.1038/s41370-024-00680-z","url":null,"abstract":"Prenatal exposure to environmental contaminants is a significant health concern because it has the potential to interfere with host metabolism, leading to adverse health effects in early childhood and later in life. Growing evidence suggests that genetic and environmental factors, as well as their interactions, play a significant role in the development of autoimmune diseases. In this study, we hypothesized that prenatal exposure to environmental contaminants impacts cord serum metabolome and contributes to the development of autoimmune diseases. We selected cord serum samples from All Babies in Southeast Sweden (ABIS) general population cohort, from infants who later developed one or more autoimmune-mediated and inflammatory diseases: celiac disease (CD), Crohn’s disease (IBD), hypothyroidism (HT), juvenile idiopathic arthritis (JIA), and type 1 diabetes (T1D) (all cases, N = 62), along with matched controls (N = 268). Using integrated exposomics and metabolomics mass spectrometry (MS) based platforms, we determined the levels of environmental contaminants and metabolites. Differences in exposure levels were found between the controls and those who later developed various diseases. High contaminant exposure levels were associated with changes in metabolome, including amino acids and free fatty acids. Specifically, we identified marked associations between metabolite profiles and exposure levels of deoxynivalenol (DON), bisphenol S (BPS), and specific per- and polyfluorinated substances (PFAS). Abnormal metabolism is a common feature preceding several autoimmune and inflammatory diseases. However, few studies compared common and specific metabolic patterns preceding these diseases. Here we hypothesized that exposure to environmental contaminants impacts cord serum metabolome, which may contribute to the development of autoimmune diseases. We found differences in exposure levels between the controls and those who later developed various diseases, and importantly, on the metabolic changes associated with the exposures. High contaminant exposure levels were associated with specific changes in metabolome. Our study suggests that prenatal exposure to specific environmental contaminants alters the cord serum metabolomes, which, in turn, might increase the risk of various immune-mediated diseases.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"34 4","pages":"647-658"},"PeriodicalIF":4.1,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41370-024-00680-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140811594","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}
Pub Date : 2024-04-25DOI: 10.1038/s41370-024-00673-y
Patrick S Reuther, Guannan Geng, Yang Liu, Lyndsey A Darrow, Matthew J Strickland
Background: Characterizing the spatial distribution of PM2.5 species concentrations is challenging due to the geographic sparsity of the stationary monitoring network. Recent advances have enabled valid estimation of PM2.5 species concentrations using satellite remote sensing data for use in epidemiologic studies.
Objective: In this study, we used satellite-based estimates of ambient PM2.5 species concentrations to estimate associations with birth weight and preterm birth in California.
Methods: Daily 24 h averaged ground-level PM2.5 species concentrations of organic carbon, elemental carbon, nitrate, and sulfate were estimated during 2005-2014 in California at 1 km resolution. Birth records were linked to ambient pollutant exposures based on maternal residential zip code. Linear regression and Cox regression were conducted to estimate the effect of 1 µg/m3 increases in PM2.5 species concentrations on birth weight and preterm birth.
Results: Analyses included 4.7 million live singleton births having a median 28 days with exposure measurements per pregnancy. In single pollutant models, the observed changes in mean birth weight (per 1 µg/m3 increase in speciated PM2.5 concentrations) were: organic carbon -3.12 g (CI: -4.71, -1.52), elemental carbon -14.20 g (CI: -18.76, -9.63), nitrate -5.51 g (CI: -6.79, -4.23), and sulfate 9.26 g (CI: 7.03, 11.49). Results from multipollutant models were less precise due to high correlation between pollutants. Associations with preterm birth were null, save for a negative association between sulfate and preterm birth (Hazard Ratio per 1 µg/m3 increase: 0.973 CI: 0.958, 0.987).
{"title":"Associations between satellite-derived estimates of PM2.5 species concentrations for organic carbon, elemental carbon, nitrate, and sulfate with birth weight and preterm birth in California during 2005-2014.","authors":"Patrick S Reuther, Guannan Geng, Yang Liu, Lyndsey A Darrow, Matthew J Strickland","doi":"10.1038/s41370-024-00673-y","DOIUrl":"10.1038/s41370-024-00673-y","url":null,"abstract":"<p><strong>Background: </strong>Characterizing the spatial distribution of PM<sub>2.5</sub> species concentrations is challenging due to the geographic sparsity of the stationary monitoring network. Recent advances have enabled valid estimation of PM<sub>2.5</sub> species concentrations using satellite remote sensing data for use in epidemiologic studies.</p><p><strong>Objective: </strong>In this study, we used satellite-based estimates of ambient PM<sub>2.5</sub> species concentrations to estimate associations with birth weight and preterm birth in California.</p><p><strong>Methods: </strong>Daily 24 h averaged ground-level PM<sub>2.5</sub> species concentrations of organic carbon, elemental carbon, nitrate, and sulfate were estimated during 2005-2014 in California at 1 km resolution. Birth records were linked to ambient pollutant exposures based on maternal residential zip code. Linear regression and Cox regression were conducted to estimate the effect of 1 µg/m<sup>3</sup> increases in PM<sub>2.5</sub> species concentrations on birth weight and preterm birth.</p><p><strong>Results: </strong>Analyses included 4.7 million live singleton births having a median 28 days with exposure measurements per pregnancy. In single pollutant models, the observed changes in mean birth weight (per 1 µg/m<sup>3</sup> increase in speciated PM<sub>2.5</sub> concentrations) were: organic carbon -3.12 g (CI: -4.71, -1.52), elemental carbon -14.20 g (CI: -18.76, -9.63), nitrate -5.51 g (CI: -6.79, -4.23), and sulfate 9.26 g (CI: 7.03, 11.49). Results from multipollutant models were less precise due to high correlation between pollutants. Associations with preterm birth were null, save for a negative association between sulfate and preterm birth (Hazard Ratio per 1 µg/m<sup>3</sup> increase: 0.973 CI: 0.958, 0.987).</p>","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11502512/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140855185","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}
Pub Date : 2024-04-23DOI: 10.1038/s41370-024-00664-z
Chuizhao Xue, Baixue Liu, Yan Kui, Weiping Wu, Xiaonong Zhou, Ning Xiao, Shuai Han, Canjun Zheng
Background
Geographical and meteorological factors have been reported to influence the prevalence of echinococcosis, but there’s a lack of indicator system and model.
Objective
To provide further insight into the impact of geographical and meteorological factors on AE prevalence and establish a theoretical basis for prevention and control.
Methods
Principal component and regression analysis were used to screen and establish a three-level indicator system. Relative weights were examined to determine the impact of each indicator, and five mathematical models were compared to identify the best predictive model for AE epidemic levels.
Results
By analyzing the data downloaded from the China Meteorological Data Service Center and Geospatial Data Cloud, we established the KCBIS, including 50 basic indicators which could be directly obtained online, 15 characteristic indicators which were linear combination of the basic indicators and showed a linear relationship with AE epidemic, and 8 key indicators which were characteristic indicators with a clearer relationships and fewer mixed effects. The relative weight analysis revealed that monthly precipitation, monthly cold days, the difference between negative and positive temperature anomalies, basic air temperature conditions, altitude, the difference between positive and negative atmospheric pressure anomalies, monthy extremely hot days, and monthly fresh breeze days were correlated with the natural logarithm of AE prevalence, with sequential decreases in their relative weights. The multinomial logistic regression model was the best predictor at epidemic levels 1, 3, 5, and 6, whereas the CART model was the best predictor at epidemic levels 2, 4, and 5.
{"title":"Developing a geographical–meteorological indicator system and evaluating prediction models for alveolar echinococcosis in China","authors":"Chuizhao Xue, Baixue Liu, Yan Kui, Weiping Wu, Xiaonong Zhou, Ning Xiao, Shuai Han, Canjun Zheng","doi":"10.1038/s41370-024-00664-z","DOIUrl":"https://doi.org/10.1038/s41370-024-00664-z","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>Geographical and meteorological factors have been reported to influence the prevalence of echinococcosis, but there’s a lack of indicator system and model.</p><h3 data-test=\"abstract-sub-heading\">Objective</h3><p>To provide further insight into the impact of geographical and meteorological factors on AE prevalence and establish a theoretical basis for prevention and control.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Principal component and regression analysis were used to screen and establish a three-level indicator system. Relative weights were examined to determine the impact of each indicator, and five mathematical models were compared to identify the best predictive model for AE epidemic levels.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>By analyzing the data downloaded from the China Meteorological Data Service Center and Geospatial Data Cloud, we established the KCBIS, including 50 basic indicators which could be directly obtained online, 15 characteristic indicators which were linear combination of the basic indicators and showed a linear relationship with AE epidemic, and 8 key indicators which were characteristic indicators with a clearer relationships and fewer mixed effects. The relative weight analysis revealed that monthly precipitation, monthly cold days, the difference between negative and positive temperature anomalies, basic air temperature conditions, altitude, the difference between positive and negative atmospheric pressure anomalies, monthy extremely hot days, and monthly fresh breeze days were correlated with the natural logarithm of AE prevalence, with sequential decreases in their relative weights. The multinomial logistic regression model was the best predictor at epidemic levels 1, 3, 5, and 6, whereas the CART model was the best predictor at epidemic levels 2, 4, and 5.</p>","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"65 1","pages":""},"PeriodicalIF":4.5,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140805864","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}
Pub Date : 2024-04-18DOI: 10.1038/s41370-024-00660-3
Daniel Fink
{"title":"What is the safe noise exposure level to prevent noise-induced hearing loss?","authors":"Daniel Fink","doi":"10.1038/s41370-024-00660-3","DOIUrl":"10.1038/s41370-024-00660-3","url":null,"abstract":"","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"35 1","pages":"124-128"},"PeriodicalIF":4.1,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41370-024-00660-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140616143","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}
Pub Date : 2024-04-13DOI: 10.1038/s41370-024-00669-8
V. N. Matthaios, I. Holland, C. M. Kang, J. E. Hart, M. Hauptman, J. M. Wolfson, J. M. Gaffin, W. Phipatanakul, D. R. Gold, P. Koutrakis
Since there are known adverse health impacts of traffic-related air pollution, while at the same time there are potential health benefits from greenness, it is important to examine more closely the impacts of these factors on indoor air quality in urban schools. This study investigates the association of road proximity and urban greenness to indoor traffic-related fine particulate matter (PM2.5), nitrogen dioxide (NO2), and black carbon (BC) in inner-city schools. PM2.5, NO2, and BC were measured indoors at 74 schools and outdoors at a central urban over a 10-year period. Seasonal urban greenness was estimated using the Normalized Difference Vegetation Index (NDVI) with 270 and 1230 m buffers. The associations between indoor traffic-related air pollution and road proximity and greenness were investigated with mixed-effects models. The analysis showed linear decays of indoor traffic-related PM2.5, NO2, and BC by 60%, 35%, and 22%, respectively for schools located at a greater distance from major roads. The results further showed that surrounding school greenness at 270 m buffer was significantly associated (p < 0.05) with lower indoor traffic-related PM2.5: −0.068 (95% CI: −0.124, −0.013), NO2: −0.139 (95% CI: −0.185, −0.092), and BC: −0.060 (95% CI: −0.115, −0.005). These associations were stronger for surrounding greenness at a greater distance from the schools (buffer 1230 m) PM2.5: −0.101 (95% CI: −0.156, −0.046) NO2: −0.122 (95% CI: −0.169, −0.075) BC: −0.080 (95% CI: −0.136, −0.026). These inverse associations were stronger after fully adjusting for regional pollution and meteorological conditions. More than 90% of children under the age of 15 worldwide are exposed to elevated air pollution levels exceeding the WHO’s guidelines. The study investigates the impact that urban infrastructure and greenness, in particular green areas and road proximity, have on indoor exposures to traffic-related PM2.5, NO2, and BC in inner-city schools. By examining a 10-year period the study provides insights for air quality management, into how road proximity and greenness at different buffers from the school locations can affect indoor exposure.
{"title":"The effects of urban green space and road proximity to indoor traffic-related PM2.5, NO2, and BC exposure in inner-city schools","authors":"V. N. Matthaios, I. Holland, C. M. Kang, J. E. Hart, M. Hauptman, J. M. Wolfson, J. M. Gaffin, W. Phipatanakul, D. R. Gold, P. Koutrakis","doi":"10.1038/s41370-024-00669-8","DOIUrl":"10.1038/s41370-024-00669-8","url":null,"abstract":"Since there are known adverse health impacts of traffic-related air pollution, while at the same time there are potential health benefits from greenness, it is important to examine more closely the impacts of these factors on indoor air quality in urban schools. This study investigates the association of road proximity and urban greenness to indoor traffic-related fine particulate matter (PM2.5), nitrogen dioxide (NO2), and black carbon (BC) in inner-city schools. PM2.5, NO2, and BC were measured indoors at 74 schools and outdoors at a central urban over a 10-year period. Seasonal urban greenness was estimated using the Normalized Difference Vegetation Index (NDVI) with 270 and 1230 m buffers. The associations between indoor traffic-related air pollution and road proximity and greenness were investigated with mixed-effects models. The analysis showed linear decays of indoor traffic-related PM2.5, NO2, and BC by 60%, 35%, and 22%, respectively for schools located at a greater distance from major roads. The results further showed that surrounding school greenness at 270 m buffer was significantly associated (p < 0.05) with lower indoor traffic-related PM2.5: −0.068 (95% CI: −0.124, −0.013), NO2: −0.139 (95% CI: −0.185, −0.092), and BC: −0.060 (95% CI: −0.115, −0.005). These associations were stronger for surrounding greenness at a greater distance from the schools (buffer 1230 m) PM2.5: −0.101 (95% CI: −0.156, −0.046) NO2: −0.122 (95% CI: −0.169, −0.075) BC: −0.080 (95% CI: −0.136, −0.026). These inverse associations were stronger after fully adjusting for regional pollution and meteorological conditions. More than 90% of children under the age of 15 worldwide are exposed to elevated air pollution levels exceeding the WHO’s guidelines. The study investigates the impact that urban infrastructure and greenness, in particular green areas and road proximity, have on indoor exposures to traffic-related PM2.5, NO2, and BC in inner-city schools. By examining a 10-year period the study provides insights for air quality management, into how road proximity and greenness at different buffers from the school locations can affect indoor exposure.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"34 5","pages":"745-752"},"PeriodicalIF":4.1,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41370-024-00669-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570081","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}
Pub Date : 2024-04-12DOI: 10.1038/s41370-024-00661-2
Amy McCarron, Sean Semple, Vivien Swanson, Colin Gillespie, Christine Braban, Heather D. Price
Background
Exposure to air pollution can exacerbate asthma with immediate and long-term health consequences. Behaviour changes can reduce exposure to air pollution, yet its ‘invisible’ nature often leaves individuals unaware of their exposure, complicating the identification of appropriate behaviour modifications. Moreover, making health behaviour changes can be challenging, necessitating additional support from healthcare professionals.
Objective
This pilot study used personal exposure monitoring, data feedback, and co-developed behaviour change interventions with individuals with asthma, with the goal of reducing personal exposure to PM2.5 and subsequently improving asthma-related health.
Methods
Twenty-eight participants conducted baseline exposure monitoring for one-week, simultaneously keeping asthma symptom and medication diaries (previously published in McCarron et al., 2023). Participants were then randomised into control (n = 8) or intervention (n = 9) groups. Intervention participants received PM2.5 exposure feedback and worked with researchers to co-develop behaviour change interventions based on a health behaviour change programme which they implemented during the follow-up monitoring week. Control group participants received no feedback or intervention during the study.
Results
All interventions focused on the home environment. Intervention group participants reduced their at-home exposure by an average of 5.7 µg/m³ over the monitoring week (−23.0 to +3.2 µg/m³), whereas the control group had a reduction of 4.7 µg/m³ (−15.6 to +0.4 µg/m³). Furthermore, intervention group participants experienced a 4.6% decrease in participant-hours with reported asthma symptoms, while the control group saw a 0.5% increase. Similarly, the intervention group’s asthma-related quality of life improved compared to the control group.
Impact statement
This pilot study investigated a novel behaviour change intervention, utilising personal exposure monitoring, data feedback, and co-developed interventions guided by a health behaviour change programme. The study aimed to reduce personal exposure to fine particulate matter (PM2.5) and improve self-reported asthma-related health. Conducting a randomised controlled trial with 28 participants, co-developed intervention successfully targeted exposure peaks within participants’ home microenvironments, resulting in a reduction in at-home personal exposure to PM2.5 and improving self-reported asthma-related health. The study contributes valuable insights into the environmental exposure-health relationship and highlights the potential of the intervention for individual-level decision-making to protect human health.
{"title":"Piloting co-developed behaviour change interventions to reduce exposure to air pollution and improve self-reported asthma-related health","authors":"Amy McCarron, Sean Semple, Vivien Swanson, Colin Gillespie, Christine Braban, Heather D. Price","doi":"10.1038/s41370-024-00661-2","DOIUrl":"https://doi.org/10.1038/s41370-024-00661-2","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>Exposure to air pollution can exacerbate asthma with immediate and long-term health consequences. Behaviour changes can reduce exposure to air pollution, yet its ‘invisible’ nature often leaves individuals unaware of their exposure, complicating the identification of appropriate behaviour modifications. Moreover, making health behaviour changes can be challenging, necessitating additional support from healthcare professionals.</p><h3 data-test=\"abstract-sub-heading\">Objective</h3><p>This pilot study used personal exposure monitoring, data feedback, and co-developed behaviour change interventions with individuals with asthma, with the goal of reducing personal exposure to PM<sub>2.5</sub> and subsequently improving asthma-related health.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Twenty-eight participants conducted baseline exposure monitoring for one-week, simultaneously keeping asthma symptom and medication diaries (previously published in McCarron et al., 2023). Participants were then randomised into control (<i>n</i> = 8) or intervention (<i>n</i> = 9) groups. Intervention participants received PM<sub>2.5</sub> exposure feedback and worked with researchers to co-develop behaviour change interventions based on a health behaviour change programme which they implemented during the follow-up monitoring week. Control group participants received no feedback or intervention during the study.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>All interventions focused on the home environment. Intervention group participants reduced their at-home exposure by an average of 5.7 µg/m³ over the monitoring week (−23.0 to +3.2 µg/m³), whereas the control group had a reduction of 4.7 µg/m³ (−15.6 to +0.4 µg/m³). Furthermore, intervention group participants experienced a 4.6% decrease in participant-hours with reported asthma symptoms, while the control group saw a 0.5% increase. Similarly, the intervention group’s asthma-related quality of life improved compared to the control group.</p><h3 data-test=\"abstract-sub-heading\">Impact statement</h3><p>This pilot study investigated a novel behaviour change intervention, utilising personal exposure monitoring, data feedback, and co-developed interventions guided by a health behaviour change programme. The study aimed to reduce personal exposure to fine particulate matter (PM<sub>2.5</sub>) and improve self-reported asthma-related health. Conducting a randomised controlled trial with 28 participants, co-developed intervention successfully targeted exposure peaks within participants’ home microenvironments, resulting in a reduction in at-home personal exposure to PM<sub>2.5</sub> and improving self-reported asthma-related health. The study contributes valuable insights into the environmental exposure-health relationship and highlights the potential of the intervention for individual-level decision-making to protect human health.</p>","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"50 1","pages":""},"PeriodicalIF":4.5,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570154","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}
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