Pub Date : 2025-08-22DOI: 10.1038/s41370-025-00798-8
J. M. Wright, K. M. Rappazzo, H. Ru, A. L. Lee, M. W. Dzierlenga, T. F. Bateson, E. G. Radke
Perfluorooctane sulfonic acid (PFOS) is a legacy chemical, that while banned in some countries, is still found in various environmental media and in nearly all humans given its long half-life. We examined mean birth weight (BW) differences in relation to PFOS exposure biomarkers using systematic review methods. We fit a random effects model to obtain the overall pooled effect and for stratified analyses examining biomarker sample type and timing, study confidence, scaling factors, and country of study origin. We also conducted a meta-regression to assess the impact of gestational age and other factors on the overall pooled effect. We found a 30-gram BW deficit (β = −30.3 g; 95%CI: −41.6, −18.9) with each ln-unit PFOS increase based on 53 studies identified in the systematic literature review. We detected BW deficits across all study confidence levels (β range: −27 to −37 g per ln-unit increase) with the largest deficit in the medium confidence grouping (β = −36.6 g; 95%CI: −56.3, −16.8). We did not see evidence of a gradient of BW deficits across biomarker sample timing (β range: −24 to −39 g per ln-unit increase), but the smallest deficit in our primary analyses was detected for the 18 early sample timing studies (β = −23.6 g; 95%CI: −38.7, −8.6). Robust deficits were also seen across various subgroups including by geographical region of study origin (e.g., Asian studies), more restrictive early biomarker sample collection, and post-partum samples (β range: −16.9 to −30.6 g). For meta-regression analyses, none of the investigated factors explained significant heterogeneity across studies. We detected a statistically significant BW deficit of 30 grams per each ln-unit PFOS increase across all 53 studies in our meta-analysis; results were comparable in magnitude across study confidence, sample timing, and other strata. Unlike previous meta-analyses based on fewer studies, our results suggest that pregnancy hemodynamics do not fully explain the overall association. Characterization of the potential risk of developmental effects related to PFOS and other legacy chemicals will have important risk assessment and risk management ramifications in the future.
{"title":"Birth weight in relation to maternal and neonatal biomarker concentration of perfluorooctane sulfonic acid: a meta-analysis and meta-regression from a systematic review","authors":"J. M. Wright, K. M. Rappazzo, H. Ru, A. L. Lee, M. W. Dzierlenga, T. F. Bateson, E. G. Radke","doi":"10.1038/s41370-025-00798-8","DOIUrl":"10.1038/s41370-025-00798-8","url":null,"abstract":"Perfluorooctane sulfonic acid (PFOS) is a legacy chemical, that while banned in some countries, is still found in various environmental media and in nearly all humans given its long half-life. We examined mean birth weight (BW) differences in relation to PFOS exposure biomarkers using systematic review methods. We fit a random effects model to obtain the overall pooled effect and for stratified analyses examining biomarker sample type and timing, study confidence, scaling factors, and country of study origin. We also conducted a meta-regression to assess the impact of gestational age and other factors on the overall pooled effect. We found a 30-gram BW deficit (β = −30.3 g; 95%CI: −41.6, −18.9) with each ln-unit PFOS increase based on 53 studies identified in the systematic literature review. We detected BW deficits across all study confidence levels (β range: −27 to −37 g per ln-unit increase) with the largest deficit in the medium confidence grouping (β = −36.6 g; 95%CI: −56.3, −16.8). We did not see evidence of a gradient of BW deficits across biomarker sample timing (β range: −24 to −39 g per ln-unit increase), but the smallest deficit in our primary analyses was detected for the 18 early sample timing studies (β = −23.6 g; 95%CI: −38.7, −8.6). Robust deficits were also seen across various subgroups including by geographical region of study origin (e.g., Asian studies), more restrictive early biomarker sample collection, and post-partum samples (β range: −16.9 to −30.6 g). For meta-regression analyses, none of the investigated factors explained significant heterogeneity across studies. We detected a statistically significant BW deficit of 30 grams per each ln-unit PFOS increase across all 53 studies in our meta-analysis; results were comparable in magnitude across study confidence, sample timing, and other strata. Unlike previous meta-analyses based on fewer studies, our results suggest that pregnancy hemodynamics do not fully explain the overall association. Characterization of the potential risk of developmental effects related to PFOS and other legacy chemicals will have important risk assessment and risk management ramifications in the future.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"35 6","pages":"1030-1040"},"PeriodicalIF":4.7,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00798-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144986387","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 : 2025-08-08DOI: 10.1038/s41370-025-00796-w
Joseph G. Allen, Parham Azimi, Gen Pei, Lauren Feguson, Lindsey Burghardt, Kari Nadeau
Urban wildfires in Los Angeles have highlighted the increased risk of soil lead exposure, especially for children. Current post-wildfire soil remediation protocols may not sufficiently protect public health, especially in communities returning after fire events. To evaluate the adequacy of existing soil remediation practices after urban wildfires in Los Angeles and present policy recommendations to reduce lead exposure risk. We reviewed current wildfire debris removal protocols, soil testing practices, and health risk benchmarks for lead exposure in California. We assessed recent data from post-fire soil testing and analyzed the scientific rationale underlying California’s existing Preliminary Remediation Goal (PRG) for lead in residential soil. We recommend two critical reforms: requiring post-clearance confirmatory soil testing after wildfire cleanup, as has been done for every major wildfire in California since 2007, and lowering California’s residential Preliminary Remediation Goal (PRG) for lead in soil from 80 to 55 mg/kg to reflect updated science and health-protective standards. The basis for these recommendations is that repeated testing after purported soil remediation is showing that greater than 20% of properties still have lead levels that exceed existing thresholds, and the 80 mg/kg PRG (1) does not adhere to the health-based toxicity criterion benchmark set by California, (2) is susceptible to high uncertainty based on the values for several exposure factors used, and (3) does not accurately reflect our current understanding of risks to children from lead.
{"title":"Post-fire soil hazards: recommendations for updated soil testing protocols and clearance thresholds","authors":"Joseph G. Allen, Parham Azimi, Gen Pei, Lauren Feguson, Lindsey Burghardt, Kari Nadeau","doi":"10.1038/s41370-025-00796-w","DOIUrl":"10.1038/s41370-025-00796-w","url":null,"abstract":"Urban wildfires in Los Angeles have highlighted the increased risk of soil lead exposure, especially for children. Current post-wildfire soil remediation protocols may not sufficiently protect public health, especially in communities returning after fire events. To evaluate the adequacy of existing soil remediation practices after urban wildfires in Los Angeles and present policy recommendations to reduce lead exposure risk. We reviewed current wildfire debris removal protocols, soil testing practices, and health risk benchmarks for lead exposure in California. We assessed recent data from post-fire soil testing and analyzed the scientific rationale underlying California’s existing Preliminary Remediation Goal (PRG) for lead in residential soil. We recommend two critical reforms: requiring post-clearance confirmatory soil testing after wildfire cleanup, as has been done for every major wildfire in California since 2007, and lowering California’s residential Preliminary Remediation Goal (PRG) for lead in soil from 80 to 55 mg/kg to reflect updated science and health-protective standards. The basis for these recommendations is that repeated testing after purported soil remediation is showing that greater than 20% of properties still have lead levels that exceed existing thresholds, and the 80 mg/kg PRG (1) does not adhere to the health-based toxicity criterion benchmark set by California, (2) is susceptible to high uncertainty based on the values for several exposure factors used, and (3) does not accurately reflect our current understanding of risks to children from lead.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"35 6","pages":"883-887"},"PeriodicalIF":4.7,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00796-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144805577","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 : 2025-08-08DOI: 10.1038/s41370-025-00797-9
Lara J. Cushing, Hasibe Caballero-Gomez, Stephanie M. Eick, Ana C. Pelegrini Guimaraes, Nicholas J. Depsky, Erin DeMicco, Jue Lin, Tracey J. Woodruff, Rachel Morello-Frosch
Shorter telomere length is a biomarker of cellular aging influenced in early life. Exposure to environmental hazards and psychosocial stressors disproportionately impact socially marginalized populations and have been linked with shorter telomeres. To estimate joint associations between residential neighborhood greenness, traffic, noise, and perceived neighborhood quality, psychosocial stress and depression on telomere length of birth parents and their newborns. Telomere length (T/S ratio) was measured in leukocytes from 354 2nd trimester parental and 488 umbilical cord blood samples collected at delivery from the Chemicals in Our Bodies cohort in San Francisco, California. Normalized difference vegetation index (NDVI), traffic volume, and noise were estimated based on residential address. Perceptions of neighborhood quality, psychosocial stress, and depression were collected via questionnaire. We used quantile g-computation to assess joint associations between all exposures and newborn and parental T/S in separate models controlling for parental age, race and ethnicity, education, pre-pregnancy body mass index, and gestational age (cord T/S only). We used interaction terms to assess effect measure modification by nativity, race and ethnicity, and educational attainment. Parental and newborn T/S were not correlated with individual measures of built environment or psychosocial stressors (rho from −0.08 to 0.08). A simultaneous one quartile increase in all adverse exposures was associated with a decrease in newborn T/S (mean difference [95% CI] = −0.03 [−0.08, 0.01]) that was stronger when restricting to paired parental-newborn samples and controlling for parental T/S (−0.08 [−0.15, −0.01]). Interaction analysis revealed stronger associations among immigrant (−0.08 [−0.16, 0.00]) vs. US-born (−0.02 [−0.07, 0.04]) and college-educated (−0.07 [−0.12, −0.02]) vs. non-college educated (0.03 [−0.07, 0.12]) participants. We saw no association with parental telomere length. Results suggest exposure to adverse neighborhood built environments and individual-level psychosocial stressors during pregnancy is associated with reductions in telomere length among newborns. Telomere length at birth predicts relative telomere length in adulthood, suggesting much of the link between telomere length and longevity is established early in life. While neighborhood environments have been linked with shorter telomeres in adulthood, few prior studies have assessed newborn telomere length or joint associations with psychosocial stressors. In a diverse birth cohort, we show that the mixture of neighborhood lack of greenness, traffic, and noise, coupled with individual-level poor perceptions of neighborhood quality, stress, and depression is associated with decreased telomere length among newborns, with slightly stronger effects among immigrants and college-educated birth parents.
{"title":"Neighborhood built environment, psychosocial stressors, and telomere length of birth parents and their newborns from San Francisco, California","authors":"Lara J. Cushing, Hasibe Caballero-Gomez, Stephanie M. Eick, Ana C. Pelegrini Guimaraes, Nicholas J. Depsky, Erin DeMicco, Jue Lin, Tracey J. Woodruff, Rachel Morello-Frosch","doi":"10.1038/s41370-025-00797-9","DOIUrl":"10.1038/s41370-025-00797-9","url":null,"abstract":"Shorter telomere length is a biomarker of cellular aging influenced in early life. Exposure to environmental hazards and psychosocial stressors disproportionately impact socially marginalized populations and have been linked with shorter telomeres. To estimate joint associations between residential neighborhood greenness, traffic, noise, and perceived neighborhood quality, psychosocial stress and depression on telomere length of birth parents and their newborns. Telomere length (T/S ratio) was measured in leukocytes from 354 2nd trimester parental and 488 umbilical cord blood samples collected at delivery from the Chemicals in Our Bodies cohort in San Francisco, California. Normalized difference vegetation index (NDVI), traffic volume, and noise were estimated based on residential address. Perceptions of neighborhood quality, psychosocial stress, and depression were collected via questionnaire. We used quantile g-computation to assess joint associations between all exposures and newborn and parental T/S in separate models controlling for parental age, race and ethnicity, education, pre-pregnancy body mass index, and gestational age (cord T/S only). We used interaction terms to assess effect measure modification by nativity, race and ethnicity, and educational attainment. Parental and newborn T/S were not correlated with individual measures of built environment or psychosocial stressors (rho from −0.08 to 0.08). A simultaneous one quartile increase in all adverse exposures was associated with a decrease in newborn T/S (mean difference [95% CI] = −0.03 [−0.08, 0.01]) that was stronger when restricting to paired parental-newborn samples and controlling for parental T/S (−0.08 [−0.15, −0.01]). Interaction analysis revealed stronger associations among immigrant (−0.08 [−0.16, 0.00]) vs. US-born (−0.02 [−0.07, 0.04]) and college-educated (−0.07 [−0.12, −0.02]) vs. non-college educated (0.03 [−0.07, 0.12]) participants. We saw no association with parental telomere length. Results suggest exposure to adverse neighborhood built environments and individual-level psychosocial stressors during pregnancy is associated with reductions in telomere length among newborns. Telomere length at birth predicts relative telomere length in adulthood, suggesting much of the link between telomere length and longevity is established early in life. While neighborhood environments have been linked with shorter telomeres in adulthood, few prior studies have assessed newborn telomere length or joint associations with psychosocial stressors. In a diverse birth cohort, we show that the mixture of neighborhood lack of greenness, traffic, and noise, coupled with individual-level poor perceptions of neighborhood quality, stress, and depression is associated with decreased telomere length among newborns, with slightly stronger effects among immigrants and college-educated birth parents.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 2","pages":"334-342"},"PeriodicalIF":4.7,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00797-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144805576","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 : 2025-08-02DOI: 10.1038/s41370-025-00799-7
Oliver Schmitz, Kees de Hoogh, Nicole Probst-Hensch, Ayoung Jeong, Benjamin Flückiger, Meng Lu, Aisha Ndiaye, Danielle Vienneau, Gerard Hoek, Kalliopi Kyriakou, Roel C. H. Vermeulen, Derek Karssenberg
Agent-based assessment of long-term personal exposure to environmental factors accounts for spatio-temporal variation in exposures along daily activity tracks of individuals. Application up to nationwide study populations requires integration of large data sets on environmental factors, personal behavior, and socio-economic status, as well as propagating uncertainties in these inputs to personal exposure values. To develop and illustrate a methodology and software framework for agent-based personal exposure assessment for large cohorts, including uncertainty assessment. We design an agent-based methodology that addresses the sparse information on individual activity patterns available in large cohorts. This methodology was implemented in a Python-based open-source and reusable framework, which was subsequently applied to assess exposure to air pollution and noise for 626,381 residential addresses in the province of Utrecht, the Netherlands. Air pollution exposures were also assessed across all addresses in Switzerland and the EPIC-NL cohort in the Netherlands. The designed framework aggregates time by divisions marked by a particular pattern in individual movement (e.g., weekdays, weekend days). Movement over a division is represented by a sequence of activities, each with a duration and spatial context, i.e., the geographical area where the activity takes place. Several activity types are included, each with a methodology to assess the spatial context, for instance, the route from home to work location. Uncertainty in inputs is defined by probability distributions constrained by observational data, if available, like statistics on origin and destination of trips, and propagated to calculated personal exposures through Monte Carlo simulation. The exposures assessed through our framework result in minor to moderate differences with those calculated using home-based exposure (for Utrecht an r2 of 0.79 for noise and 0.98 for nitrogen dioxide (NO2) and particulate matter with aerodynamic diameters of 2.5 microns or smaller (PM2.5), respectively), in particular leading to reduced contrast across the population in exposures. Epidemiological studies on long-term effects of air pollution typically use a residential-based exposure assessment. However, it fails to account for individual mobility and spatial contrasts in environmental concentrations. While there is thus a need to investigate activity-based methods, their implementation is constrained by the lack of conceptual frameworks and software, particularly for large cohorts, which present unique demands regarding data inputs and computation. To address this gap, we introduce general concepts and a reusable, open-source software framework, designed for cluster computing, that can be applied consistently across a wide array of environmental factors and cohort studies.
{"title":"A computational framework for agent-based assessment of multiple environmental exposures","authors":"Oliver Schmitz, Kees de Hoogh, Nicole Probst-Hensch, Ayoung Jeong, Benjamin Flückiger, Meng Lu, Aisha Ndiaye, Danielle Vienneau, Gerard Hoek, Kalliopi Kyriakou, Roel C. H. Vermeulen, Derek Karssenberg","doi":"10.1038/s41370-025-00799-7","DOIUrl":"10.1038/s41370-025-00799-7","url":null,"abstract":"Agent-based assessment of long-term personal exposure to environmental factors accounts for spatio-temporal variation in exposures along daily activity tracks of individuals. Application up to nationwide study populations requires integration of large data sets on environmental factors, personal behavior, and socio-economic status, as well as propagating uncertainties in these inputs to personal exposure values. To develop and illustrate a methodology and software framework for agent-based personal exposure assessment for large cohorts, including uncertainty assessment. We design an agent-based methodology that addresses the sparse information on individual activity patterns available in large cohorts. This methodology was implemented in a Python-based open-source and reusable framework, which was subsequently applied to assess exposure to air pollution and noise for 626,381 residential addresses in the province of Utrecht, the Netherlands. Air pollution exposures were also assessed across all addresses in Switzerland and the EPIC-NL cohort in the Netherlands. The designed framework aggregates time by divisions marked by a particular pattern in individual movement (e.g., weekdays, weekend days). Movement over a division is represented by a sequence of activities, each with a duration and spatial context, i.e., the geographical area where the activity takes place. Several activity types are included, each with a methodology to assess the spatial context, for instance, the route from home to work location. Uncertainty in inputs is defined by probability distributions constrained by observational data, if available, like statistics on origin and destination of trips, and propagated to calculated personal exposures through Monte Carlo simulation. The exposures assessed through our framework result in minor to moderate differences with those calculated using home-based exposure (for Utrecht an r2 of 0.79 for noise and 0.98 for nitrogen dioxide (NO2) and particulate matter with aerodynamic diameters of 2.5 microns or smaller (PM2.5), respectively), in particular leading to reduced contrast across the population in exposures. Epidemiological studies on long-term effects of air pollution typically use a residential-based exposure assessment. However, it fails to account for individual mobility and spatial contrasts in environmental concentrations. While there is thus a need to investigate activity-based methods, their implementation is constrained by the lack of conceptual frameworks and software, particularly for large cohorts, which present unique demands regarding data inputs and computation. To address this gap, we introduce general concepts and a reusable, open-source software framework, designed for cluster computing, that can be applied consistently across a wide array of environmental factors and cohort studies.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 2","pages":"231-243"},"PeriodicalIF":4.7,"publicationDate":"2025-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00799-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144765953","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 : 2025-07-19DOI: 10.1038/s41370-025-00794-y
Carson Mowrer, Andrew Larkin, Charlotte Roscoe, Stephanie T. Grady, Junenette L. Peters, Brendon Haggerty, Perry Hystad, Matthew Bozigar
Community noise pollution can adversely impact health, yet noise has rarely been systematically measured in United States (U.S.) cities for epidemiological research. Collaborating with the Multnomah County Health Department, we developed an exploratory measurement campaign to systematically capture community noise in Portland, Oregon, U.S. to inform environmental health research and practice. We identified short-term measurement locations using weighted probability sampling and developed a protocol for deploying Class 1 sound level meters at identified sites to measure sound levels continuously for at least five days. We calculated daytime, nighttime, and daily-average noise metrics including day-night average sound levels (DNL), day-evening-night levels (Lden), intermittency ratios (IR), and 10th- and 90th-percentile noise levels (L90, L10). We evaluated noise metrics by built environment and sociodemographic characteristics at the census tract level and performed machine learning-based cluster analysis to identify locations with similar exposure profiles. Nine additional locations were sampled continuously for one year to assess agreement between short- and long-term noise measurements. DNL ranged from 49.6 to 86.7 decibels across short-term sites (n = 217). DNL exceeded U.S. Environmental Protection Agency guidelines at 78% of sites, and nighttime noise exceeded World Health Organization guidelines at 90%. Short-term sites in census tracts with higher median income and proportion of white population had lower DNL compared to lower median income and proportion of white population census tracts. Cluster analysis revealed four noise profiles: low LAeq/moderate IR sites usually occurring in residential neighborhoods, high LAeq/moderate IR sites adjacent to major roads, moderate LAeq/high IR sites within 1–2 city blocks of major roads, and high LAeq/low IR and low LAeq/low IR sites near highways or parks, respectively.
背景：社区噪音污染会对健康产生不利影响，但在美国城市中，噪音很少被系统地测量用于流行病学研究。目的：我们与摩特诺玛县卫生局合作，开展了一项探索性测量活动，系统地捕捉美国俄勒冈州波特兰市的社区噪音，为环境卫生研究和实践提供信息。方法：我们使用加权概率抽样确定短期测量地点，并制定了在确定地点部署1级声级计的协议，以连续测量至少5天的声级。我们计算了白天、夜间和每日平均噪声指标，包括昼夜平均声级（DNL）、昼夜水平（Lden）、间歇比（IR）以及第10和第90百分位噪声水平（L90、L10）。我们根据人口普查区水平的建筑环境和社会人口特征评估了噪声指标，并进行了基于机器学习的聚类分析，以确定具有相似暴露概况的地点。另外九个地点连续采样一年，以评估短期和长期噪音测量之间的一致性。结果：短期部位的DNL范围为49.6至86.7分贝（n = 217）。在78%的地点，DNL超过了美国环境保护署（U.S. Environmental Protection Agency）的指导标准，而夜间噪音超过世界卫生组织（World Health Organization）指导标准的比例为90%。与收入中位数和白人人口比例较低的人口普查区相比，收入中位数和白人人口比例较高的人口普查区的短期站点的DNL较低。聚类分析结果显示：低LAeq/中IR站点主要分布在居民区；高LAeq/中IR站点主要分布在主要道路附近；中等LAeq/高IR站点分布在主要道路附近1-2个城市街区内；高LAeq/低IR站点分布在高速公路或公园附近；影响：这项研究揭示了在美国的一个中大型城市中，潜在有害的社区噪音暴露水平非常普遍，特别是在低收入和种族多样化的社区。通过识别具有相似噪声暴露概况的站点分组，我们为探索噪声的建筑环境驱动因素和多维噪声暴露的不同健康影响奠定了基础。所收集的噪声测量协议和数据库为研究人员和社区提供了工具（可应要求提供），以调查噪声暴露模式、环境正义问题和相关的健康影响，并进一步应用于预测建模，以估计流行病学研究中的个人水平暴露。
{"title":"Systematic measurement and machine learning-based profile characterization of community noise in a medium-large city in the United States","authors":"Carson Mowrer, Andrew Larkin, Charlotte Roscoe, Stephanie T. Grady, Junenette L. Peters, Brendon Haggerty, Perry Hystad, Matthew Bozigar","doi":"10.1038/s41370-025-00794-y","DOIUrl":"10.1038/s41370-025-00794-y","url":null,"abstract":"Community noise pollution can adversely impact health, yet noise has rarely been systematically measured in United States (U.S.) cities for epidemiological research. Collaborating with the Multnomah County Health Department, we developed an exploratory measurement campaign to systematically capture community noise in Portland, Oregon, U.S. to inform environmental health research and practice. We identified short-term measurement locations using weighted probability sampling and developed a protocol for deploying Class 1 sound level meters at identified sites to measure sound levels continuously for at least five days. We calculated daytime, nighttime, and daily-average noise metrics including day-night average sound levels (DNL), day-evening-night levels (Lden), intermittency ratios (IR), and 10th- and 90th-percentile noise levels (L90, L10). We evaluated noise metrics by built environment and sociodemographic characteristics at the census tract level and performed machine learning-based cluster analysis to identify locations with similar exposure profiles. Nine additional locations were sampled continuously for one year to assess agreement between short- and long-term noise measurements. DNL ranged from 49.6 to 86.7 decibels across short-term sites (n = 217). DNL exceeded U.S. Environmental Protection Agency guidelines at 78% of sites, and nighttime noise exceeded World Health Organization guidelines at 90%. Short-term sites in census tracts with higher median income and proportion of white population had lower DNL compared to lower median income and proportion of white population census tracts. Cluster analysis revealed four noise profiles: low LAeq/moderate IR sites usually occurring in residential neighborhoods, high LAeq/moderate IR sites adjacent to major roads, moderate LAeq/high IR sites within 1–2 city blocks of major roads, and high LAeq/low IR and low LAeq/low IR sites near highways or parks, respectively.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 1","pages":"199-210"},"PeriodicalIF":4.7,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144669270","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 : 2025-07-18DOI: 10.1038/s41370-025-00792-0
Yasrab N. Raza, Julia S. El-Sayed Moustafa, Xinyuan Zhang, Dongmeng Wang, Max Tomlinson, Mario Falchi, Cristina Menni, Ruth C. E. Bowyer, Claire J. Steves, Kerrin S. Small
{"title":"Correction: Longitudinal association of perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) exposure with lipid traits, in a healthy unselected population","authors":"Yasrab N. Raza, Julia S. El-Sayed Moustafa, Xinyuan Zhang, Dongmeng Wang, Max Tomlinson, Mario Falchi, Cristina Menni, Ruth C. E. Bowyer, Claire J. Steves, Kerrin S. Small","doi":"10.1038/s41370-025-00792-0","DOIUrl":"10.1038/s41370-025-00792-0","url":null,"abstract":"","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"35 6","pages":"1069-1069"},"PeriodicalIF":4.7,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00792-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144669269","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 : 2025-07-17DOI: 10.1038/s41370-025-00793-z
Soňa Smetanová, Akrem Jbebli, Jiří Kohoutek, Vladimíra Puklová, Milena Černá, Andrea Krsková, Martin Zvonař, Zdenko Reguli, Lenka Andrýsková, Pavel Piler, Petra Přibylová, Jana Klánová, Elliott J. Price, Klára Komprdová
Temporal trends of chemicals in the population are key to identifying changing sources of chemicals and determining the effectiveness of various legislative measures. The present study focused on time comparisons to explore a possible decrease in PAH metabolite levels in the Czech population. Legislative measures occurred between sampling periods, including restricting smoking and the Air Protection Act. Ten metabolites of PAHs were measured in urine samples collected in 2011–2012 from mothers and children from DEMOCOPHES-CZ study (N = 235) and in 2019–2020 from children, teenagers, and young adults from CELSPAC studies (N = 809). Multivariate linear regression, Kruskal-Wallis ANOVA, and Mann-Whitney test (MW) were used to investigate differences in OH-PAHs between periods, age categories, and exposure determinants. Median concentrations significantly decreased between 2011-2020 by 30–35% for 1-OH-NAP, 2-and 3-OH-FLUO, 85% for 1-OH-PHE, and 44% for 2/3-OH-PHE, while 2-OH-NAP increased by 29% in non-smoking adults. In children, median concentrations of all metabolites decreased by 10–51%, with 2-OH-NAP rising by 49%. Smokers showed the largest differences, with significant decreases of 46–59% in the median concentrations of 2-OH-NAP, 2/3-OH-PHE, 9-OH-PHE, and 1-OH-PYR, and 76–91% in OH-FLUOs, 1-OH-NAP, and 1-OH-PHE. Fish and offal consumption, season, locality, and type of cooking were significant factors associated with levels of OH-PAHs, explaining 4–9% of the variability. Smoking was the main contributor in 2011, explaining up to 45% variability; no difference was found between smokers and non-smokers in 2019. New reference values of OH-PAHs in urine were calculated for the Czech population.
{"title":"Changing pattern of exposure to polycyclic aromatic hydrocarbons over time in the Central European population","authors":"Soňa Smetanová, Akrem Jbebli, Jiří Kohoutek, Vladimíra Puklová, Milena Černá, Andrea Krsková, Martin Zvonař, Zdenko Reguli, Lenka Andrýsková, Pavel Piler, Petra Přibylová, Jana Klánová, Elliott J. Price, Klára Komprdová","doi":"10.1038/s41370-025-00793-z","DOIUrl":"10.1038/s41370-025-00793-z","url":null,"abstract":"Temporal trends of chemicals in the population are key to identifying changing sources of chemicals and determining the effectiveness of various legislative measures. The present study focused on time comparisons to explore a possible decrease in PAH metabolite levels in the Czech population. Legislative measures occurred between sampling periods, including restricting smoking and the Air Protection Act. Ten metabolites of PAHs were measured in urine samples collected in 2011–2012 from mothers and children from DEMOCOPHES-CZ study (N = 235) and in 2019–2020 from children, teenagers, and young adults from CELSPAC studies (N = 809). Multivariate linear regression, Kruskal-Wallis ANOVA, and Mann-Whitney test (MW) were used to investigate differences in OH-PAHs between periods, age categories, and exposure determinants. Median concentrations significantly decreased between 2011-2020 by 30–35% for 1-OH-NAP, 2-and 3-OH-FLUO, 85% for 1-OH-PHE, and 44% for 2/3-OH-PHE, while 2-OH-NAP increased by 29% in non-smoking adults. In children, median concentrations of all metabolites decreased by 10–51%, with 2-OH-NAP rising by 49%. Smokers showed the largest differences, with significant decreases of 46–59% in the median concentrations of 2-OH-NAP, 2/3-OH-PHE, 9-OH-PHE, and 1-OH-PYR, and 76–91% in OH-FLUOs, 1-OH-NAP, and 1-OH-PHE. Fish and offal consumption, season, locality, and type of cooking were significant factors associated with levels of OH-PAHs, explaining 4–9% of the variability. Smoking was the main contributor in 2011, explaining up to 45% variability; no difference was found between smokers and non-smokers in 2019. New reference values of OH-PAHs in urine were calculated for the Czech population.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 1","pages":"184-198"},"PeriodicalIF":4.7,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00793-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144661736","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 : 2025-07-17DOI: 10.1038/s41370-025-00795-x
Abas Shkembi, Keshav Patel, Lauren M. Smith, Helen C. S. Meier, Richard L. Neitzel
Racial and ethnic inequities in environmental noise exist in the US, partially attributable to historical structural racism. However, previous studies have not considered the totality of people’s exposures. Since people spend most of their waking time at work, there is a need to consider cumulative exposure to noise both in and out of the workplace to understand who is most at risk of noise pollution-related adverse health outcomes. To (1) investigate whether racial and ethnic minority communities are disproportionately burdened by transportation- and workplace-related noise pollution, and (2) assess whether structural racism through historically redlined neighborhoods with sustained mortgage discrimination partially contribute to the hypothesized inequity. We characterized the prevalence of workplace noise and transportation noise exposure by census tract across the US. We analyzed the census tract-level association between racial and ethnic composition and the population exposed to both transportation- and workplace-related noise pollution in the 2010s using geospatial models. We then assessed census tract-level associations with transportation and workplace noise pollution using historical redlining in the 1930s as the primary covariate, stratified by mortgage discrimination in the 1990s using a similar geospatial model, controlling for census tract-level indicators of low socioeconomic status. Higher percentages of racial and ethnic minority individuals, particularly Hispanic/Latino and non-Hispanic Black Americans, were associated with significantly higher odds of exposure to both transportation and workplace noise (odds ratio = 8.59, 95% CI: 7.38–10.0, when comparing within-metropolitan area, highest to lowest quintile percentages). These disparities are particularly profound in urban areas. Urban tracts which experienced residential segregation in the 1930s, even without sustained mortgage discrimination in the 1990s, have a significantly higher percentage of individuals exposed to both transportation and workplace noise today compared to those without historical segregation (1.55%, 95% CI: 1.37–1.74). This inequity is even higher among historically segregated tracts that experienced sustained mortgage discrimination (1.83%, 95% CI: 1.66–2.01). These findings can advance environmental justice initiatives by informing regulatory action to protect communities of color from noise pollution both environmentally and during work. Our study provides evidence that neighborhoods with a higher proportion of racial and ethnic minority individuals are cumulatively burdened by noise pollution both during work and from transportation sources in their home communities. This suggests that not incorporating workplace exposures when assessing environmental impacts may overlook the most burdened communities. Future environmental justice efforts and policies should consider assessing workplace exposures to reduce environmental health disparities more effectiv
{"title":"Racial and ethnic inequities to noise pollution from transportation- and work-related sources in the United States","authors":"Abas Shkembi, Keshav Patel, Lauren M. Smith, Helen C. S. Meier, Richard L. Neitzel","doi":"10.1038/s41370-025-00795-x","DOIUrl":"10.1038/s41370-025-00795-x","url":null,"abstract":"Racial and ethnic inequities in environmental noise exist in the US, partially attributable to historical structural racism. However, previous studies have not considered the totality of people’s exposures. Since people spend most of their waking time at work, there is a need to consider cumulative exposure to noise both in and out of the workplace to understand who is most at risk of noise pollution-related adverse health outcomes. To (1) investigate whether racial and ethnic minority communities are disproportionately burdened by transportation- and workplace-related noise pollution, and (2) assess whether structural racism through historically redlined neighborhoods with sustained mortgage discrimination partially contribute to the hypothesized inequity. We characterized the prevalence of workplace noise and transportation noise exposure by census tract across the US. We analyzed the census tract-level association between racial and ethnic composition and the population exposed to both transportation- and workplace-related noise pollution in the 2010s using geospatial models. We then assessed census tract-level associations with transportation and workplace noise pollution using historical redlining in the 1930s as the primary covariate, stratified by mortgage discrimination in the 1990s using a similar geospatial model, controlling for census tract-level indicators of low socioeconomic status. Higher percentages of racial and ethnic minority individuals, particularly Hispanic/Latino and non-Hispanic Black Americans, were associated with significantly higher odds of exposure to both transportation and workplace noise (odds ratio = 8.59, 95% CI: 7.38–10.0, when comparing within-metropolitan area, highest to lowest quintile percentages). These disparities are particularly profound in urban areas. Urban tracts which experienced residential segregation in the 1930s, even without sustained mortgage discrimination in the 1990s, have a significantly higher percentage of individuals exposed to both transportation and workplace noise today compared to those without historical segregation (1.55%, 95% CI: 1.37–1.74). This inequity is even higher among historically segregated tracts that experienced sustained mortgage discrimination (1.83%, 95% CI: 1.66–2.01). These findings can advance environmental justice initiatives by informing regulatory action to protect communities of color from noise pollution both environmentally and during work. Our study provides evidence that neighborhoods with a higher proportion of racial and ethnic minority individuals are cumulatively burdened by noise pollution both during work and from transportation sources in their home communities. This suggests that not incorporating workplace exposures when assessing environmental impacts may overlook the most burdened communities. Future environmental justice efforts and policies should consider assessing workplace exposures to reduce environmental health disparities more effectiv","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 1","pages":"211-220"},"PeriodicalIF":4.7,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00795-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144661737","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 : 2025-07-11DOI: 10.1038/s41370-025-00789-9
Seong-Uk Baek, Jin-Ha Yoon
Academic interest in the health impacts of air pollutant mixtures has increased in past years. Studies indicated that air pollutants exposure is linked to obesity and metabolic syndrome. This study aimed to explore the association of air pollutant mixture with metabolic obesity phenotypes. A nationwide sample of 68,675 adults was analyzed in our cross-sectional study. Participants were linked to modeled air pollution data from 2007 to 2019. The concentrations of PM2.5–10, PM2.5, NO2, CO, SO2, and O3 were estimated for 2-year moving averages. Metabolic obesity phenotypes were classified into metabolically healthy obesity (MHO; body mass index [BMI] ≥25 kg/m2; without metabolic abnormality) and metabolically unhealthy obesity (MUO; BMI ≥25 kg/m2; with metabolic abnormality). The quantile g-computation was used to determine the association of air pollutant mixture with MHO and MOU. In total, 46,061 individuals were classified as non-obese, 2724 individuals were classified as MHO, and 19,890 individuals were classified as MUO. In the quantile g-computation, one quartile increase in the concentration of air pollutant mixture was positively associated with MUO (OR [odds ratio]: 1.12, 95% CI [confidence interval]: 1.05–1.19) but not with MHO (OR: 1.00, 95% CI: 0.87–1.15). O3, CO, and PM2.5–10 accounted for 37.6%, 21.6%, and 21.3% of the positive association of air pollutant mixture with MUO, respectively. Mounting evidence shows that outdoor air pollution is linked to obesity. We explored the association between long-term exposure to air pollutant mixture and metabolic obesity phenotypes. Obesity phenotypes were classified as metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). A mixture analysis showed that quartile increase in the concentration of the air pollutant mixture is associated with 1.12-fold increase in the odds of MUO, but not with MHO. Our novel findings suggest that long-term exposure to air pollutants may affect both metabolic abnormalities and obesity, contributing to a shift towards a metabolically unfavorable obesity profile.
{"title":"Long-term exposure to ambient air pollutant mixture and metabolic obesity phenotypes: Results from a nationwide Korean study (2007–2019)","authors":"Seong-Uk Baek, Jin-Ha Yoon","doi":"10.1038/s41370-025-00789-9","DOIUrl":"10.1038/s41370-025-00789-9","url":null,"abstract":"Academic interest in the health impacts of air pollutant mixtures has increased in past years. Studies indicated that air pollutants exposure is linked to obesity and metabolic syndrome. This study aimed to explore the association of air pollutant mixture with metabolic obesity phenotypes. A nationwide sample of 68,675 adults was analyzed in our cross-sectional study. Participants were linked to modeled air pollution data from 2007 to 2019. The concentrations of PM2.5–10, PM2.5, NO2, CO, SO2, and O3 were estimated for 2-year moving averages. Metabolic obesity phenotypes were classified into metabolically healthy obesity (MHO; body mass index [BMI] ≥25 kg/m2; without metabolic abnormality) and metabolically unhealthy obesity (MUO; BMI ≥25 kg/m2; with metabolic abnormality). The quantile g-computation was used to determine the association of air pollutant mixture with MHO and MOU. In total, 46,061 individuals were classified as non-obese, 2724 individuals were classified as MHO, and 19,890 individuals were classified as MUO. In the quantile g-computation, one quartile increase in the concentration of air pollutant mixture was positively associated with MUO (OR [odds ratio]: 1.12, 95% CI [confidence interval]: 1.05–1.19) but not with MHO (OR: 1.00, 95% CI: 0.87–1.15). O3, CO, and PM2.5–10 accounted for 37.6%, 21.6%, and 21.3% of the positive association of air pollutant mixture with MUO, respectively. Mounting evidence shows that outdoor air pollution is linked to obesity. We explored the association between long-term exposure to air pollutant mixture and metabolic obesity phenotypes. Obesity phenotypes were classified as metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). A mixture analysis showed that quartile increase in the concentration of the air pollutant mixture is associated with 1.12-fold increase in the odds of MUO, but not with MHO. Our novel findings suggest that long-term exposure to air pollutants may affect both metabolic abnormalities and obesity, contributing to a shift towards a metabolically unfavorable obesity profile.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"36 1","pages":"1-9"},"PeriodicalIF":4.7,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144621740","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}
The accurate analysis of extractables and leachables (E&L) from medical devices is crucial for the reliable safety risk assessment of substances to which patients and users may be exposed. The extractable profile of medical devices is often complex and unpredictable, thus improper selection of reference standards can lead to irreproducible chemical analyses between laboratories. ISO 10993-18, the international consensus standard for chemical characterization of medical devices, does not specify a process for selection of appropriate chemical reference standards for non-targeted analysis of E&L, leading to a variety of approaches being used. This study seeks to set out requirements for building a comprehensive list of chemical reference standards for non-targeted analysis of E&L and propose suggestions for selecting appropriate standards to enhance the consistency of chemical analysis. Criteria for selecting reference standards for non-targeted analysis of E&L in medical devices were developed using relevant polymer additives as a model system. The Relative Response Factor (RRF) values of the selected reference standards were determined using GC-MS and LC-MS analysis across three different concentrations. A system was developed to rank the toxicological hazards of the selected reference standards. A list of 106 reference standards of polymer additives was compiled, encompassing a wide range of physicochemical properties and broad toxicological coverage. Statistical analyses of these chemicals revealed there was no significant correlation between their six physicochemical properties and the corresponding relative response factors measured by GC-MS and LC-MS techniques. Accurate chemical identification and quantification of extractable substances from medical devices is important for chemical characterization of medical devices. The accurate quantitation of extractable chemicals in medical devices through non-targeted analysis is dependent on the proper selection of reference standards. We have proposed a set of reference standards intended to enhance the confidence in quantitation of device extractables, covering a broad range of structural and physicochemical diversity. This set of reference standards may assist chemistry laboratories in developing robust screening methods for extractables in medical devices, supporting the accurate characterization of medical devices.
{"title":"Designing a set of reference standards for non-targeted analysis of polymer additives extracted from medical devices","authors":"Byeong Hwa Yun, Amali Herath, Ying Jin, Jamie Kim, Kerry Belton, Echoleah Rufer, Omar Rivera Betancourt","doi":"10.1038/s41370-025-00788-w","DOIUrl":"10.1038/s41370-025-00788-w","url":null,"abstract":"The accurate analysis of extractables and leachables (E&L) from medical devices is crucial for the reliable safety risk assessment of substances to which patients and users may be exposed. The extractable profile of medical devices is often complex and unpredictable, thus improper selection of reference standards can lead to irreproducible chemical analyses between laboratories. ISO 10993-18, the international consensus standard for chemical characterization of medical devices, does not specify a process for selection of appropriate chemical reference standards for non-targeted analysis of E&L, leading to a variety of approaches being used. This study seeks to set out requirements for building a comprehensive list of chemical reference standards for non-targeted analysis of E&L and propose suggestions for selecting appropriate standards to enhance the consistency of chemical analysis. Criteria for selecting reference standards for non-targeted analysis of E&L in medical devices were developed using relevant polymer additives as a model system. The Relative Response Factor (RRF) values of the selected reference standards were determined using GC-MS and LC-MS analysis across three different concentrations. A system was developed to rank the toxicological hazards of the selected reference standards. A list of 106 reference standards of polymer additives was compiled, encompassing a wide range of physicochemical properties and broad toxicological coverage. Statistical analyses of these chemicals revealed there was no significant correlation between their six physicochemical properties and the corresponding relative response factors measured by GC-MS and LC-MS techniques. Accurate chemical identification and quantification of extractable substances from medical devices is important for chemical characterization of medical devices. The accurate quantitation of extractable chemicals in medical devices through non-targeted analysis is dependent on the proper selection of reference standards. We have proposed a set of reference standards intended to enhance the confidence in quantitation of device extractables, covering a broad range of structural and physicochemical diversity. This set of reference standards may assist chemistry laboratories in developing robust screening methods for extractables in medical devices, supporting the accurate characterization of medical devices.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"35 6","pages":"943-955"},"PeriodicalIF":4.7,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41370-025-00788-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144602797","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}
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