Journal of Exposure Science and Environmental Epidemiology最新文献

{"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}

{"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}

{"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^TM. 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/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.</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}

{"title":"Prenatal exposure to environmental contaminants and cord serum metabolite profiles in future immune-mediated diseases","authors":"Bagavathy Shanmugam Karthikeyan,&nbsp;Tuulia Hyötyläinen,&nbsp;Tannaz Ghaffarzadegan,&nbsp;Eric Triplett,&nbsp;Matej Orešič,&nbsp;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}

{"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_2.5 species concentrations is challenging due to the geographic sparsity of the stationary monitoring network. Recent advances have enabled valid estimation of PM_2.5 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_2.5 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_2.5 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 PM_2.5 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/m³ increase in speciated PM_2.5 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).</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}

{"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}

{"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":"https://doi.org/10.1038/s41370-024-00660-3","url":null,"abstract":"","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"9 1","pages":""},"PeriodicalIF":4.5,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","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":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"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,&nbsp;I. Holland,&nbsp;C. M. Kang,&nbsp;J. E. Hart,&nbsp;M. Hauptman,&nbsp;J. M. Wolfson,&nbsp;J. M. Gaffin,&nbsp;W. Phipatanakul,&nbsp;D. R. Gold,&nbsp;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 &lt; 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}

{"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_2.5 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_2.5 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.</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_2.5) 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 PM_2.5 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.</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}

{"title":"Leveraging low-cost sensors to predict nitrogen dioxide for epidemiologic exposure assessment.","authors":"Christopher Zuidema, Jianzhao Bi, Dustin Burnham, Nancy Carmona, Amanda J Gassett, David L Slager, Cooper Schumacher, Elena Austin, Edmund Seto, Adam A Szpiro, Lianne Sheppard","doi":"10.1038/s41370-024-00667-w","DOIUrl":"10.1038/s41370-024-00667-w","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Statistical models of air pollution enable intra-urban characterization of pollutant concentrations, benefiting exposure assessment for environmental epidemiology. The new generation of low-cost sensors facilitate the deployment of dense monitoring networks and can potentially be used to improve intra-urban models of air pollution.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;Develop and evaluate a spatiotemporal model for nitrogen dioxide (NO&lt;sub&gt;2&lt;/sub&gt;) in the Puget Sound region of WA, USA for the Adult Changes in Thought Air Pollution (ACT-AP) study and assess the contribution of low-cost sensor data to the model's performance through cross-validation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We developed a spatiotemporal NO&lt;sub&gt;2&lt;/sub&gt; model for the study region incorporating data from 11 agency locations, 364 supplementary monitoring locations, and 117 low-cost sensor (LCS) locations for the 1996-2020 time period. Model features included long-term time trends and dimension-reduced land use regression. We evaluated the contribution of LCS network data by comparing models fit with and without sensor data using cross-validated (CV) summary performance statistics.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The best performing model had one time trend and geographic covariates summarized into three partial least squares components. The model, fit with LCS data, performed as well as other recent studies (agency cross-validation: CV- root mean square error (RMSE) = 2.5 ppb NO&lt;sub&gt;2&lt;/sub&gt;; CV- coefficient of determination ( &lt;math&gt; &lt;msup&gt;&lt;mrow&gt;&lt;mi&gt;R&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt; &lt;/msup&gt; &lt;/math&gt; ) = 0.85). Predictions of NO&lt;sub&gt;2&lt;/sub&gt; concentrations developed with LCS were higher at residential locations compared to a model without LCS, especially in recent years. While LCS did not provide a strong performance gain at agency sites (CV-RMSE = 2.8 ppb NO&lt;sub&gt;2&lt;/sub&gt;; CV- &lt;math&gt; &lt;msup&gt;&lt;mrow&gt;&lt;mi&gt;R&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt; &lt;/msup&gt; &lt;/math&gt;  = 0.82 without LCS), at residential locations, the improvement was substantial, with RMSE = 3.8 ppb NO&lt;sub&gt;2&lt;/sub&gt; and &lt;math&gt; &lt;msup&gt;&lt;mrow&gt;&lt;mi&gt;R&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt; &lt;/msup&gt; &lt;/math&gt;  = 0.08 (without LCS), compared to CV-RMSE = 2.8 ppb NO&lt;sub&gt;2&lt;/sub&gt; and CV- &lt;math&gt; &lt;msup&gt;&lt;mrow&gt;&lt;mi&gt;R&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt; &lt;/msup&gt; &lt;/math&gt;  = 0.51 (with LCS).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Impact: &lt;/strong&gt;We developed a spatiotemporal model for nitrogen dioxide (NO&lt;sub&gt;2&lt;/sub&gt;) pollution in Washington's Puget Sound region for epidemiologic exposure assessment for the Adult Changes in Thought Air Pollution study. We examined the impact of including low-cost sensor data in the NO&lt;sub&gt;2&lt;/sub&gt; model and found the additional spatial information the sensors provided predicted NO&lt;sub&gt;2&lt;/sub&gt; concentrations that were higher than without low-cost sensors, particularly in recent years. We did not observe a clear, substantial improvement in cross-validation performance over a similar model fit without low-cost sensor dat","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140861441","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}