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Leveraging low-cost sensors to predict nitrogen dioxide for epidemiologic exposure assessment. 利用低成本传感器预测二氧化氮，进行流行病学暴露评估。
IF 4.5 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-04-09 DOI: 10.1038/s41370-024-00667-w
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
<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>Develop and evaluate a spatiotemporal model for nitrogen dioxide (NO<sub>2</sub>) 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.</p><p><strong>Methods: </strong>We developed a spatiotemporal NO<sub>2</sub> 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.</p><p><strong>Results: </strong>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<sub>2</sub>; CV- coefficient of determination ( <math> <msup><mrow><mi>R</mi></mrow> <mrow><mn>2</mn></mrow> </msup> </math> ) = 0.85). Predictions of NO<sub>2</sub> 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<sub>2</sub>; CV- <math> <msup><mrow><mi>R</mi></mrow> <mrow><mn>2</mn></mrow> </msup> </math>  = 0.82 without LCS), at residential locations, the improvement was substantial, with RMSE = 3.8 ppb NO<sub>2</sub> and <math> <msup><mrow><mi>R</mi></mrow> <mrow><mn>2</mn></mrow> </msup> </math>  = 0.08 (without LCS), compared to CV-RMSE = 2.8 ppb NO<sub>2</sub> and CV- <math> <msup><mrow><mi>R</mi></mrow> <mrow><mn>2</mn></mrow> </msup> </math>  = 0.51 (with LCS).</p><p><strong>Impact: </strong>We developed a spatiotemporal model for nitrogen dioxide (NO<sub>2</sub>) 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<sub>2</sub> model and found the additional spatial information the sensors provided predicted NO<sub>2</sub> 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
背景：空气污染统计模型能够描述城市内部的污染物浓度，有利于环境流行病学的暴露评估。新一代低成本传感器有助于部署密集的监测网络，并有可能用于改进城市内的空气污染模型：为 "成人认为空气污染的变化"（ACT-AP）研究开发并评估美国华盛顿州普吉特海湾地区的二氧化氮（NO2）时空模型，并通过交叉验证评估低成本传感器数据对模型性能的贡献：方法：我们为研究区域开发了一个二氧化氮时空模型，该模型包含了 1996-2020 年期间来自 11 个机构地点、364 个补充监测地点和 117 个低成本传感器 (LCS) 地点的数据。模型特征包括长期时间趋势和降维土地利用回归。我们使用交叉验证（CV）性能统计摘要，通过比较有传感器数据和无传感器数据的拟合模型，评估了 LCS 网络数据的贡献：结果：表现最好的模型有一个时间趋势和地理协变量，归纳为三个偏最小二乘成分。使用 LCS 数据拟合的模型与近期的其他研究（机构交叉验证、CV-均方根误差（CV-root mean square error）、CV-均方根误差（CV-root mean square error）、CV-均方根误差（CV-root mean square error））一样性能良好：CV-均方根误差 (RMSE) = 2.5 ppb NO2；CV-判定系数 ( R 2 ) = 0.85）。与不使用 LCS 的模型相比，使用 LCS 预测的居民点二氧化氮浓度更高，尤其是在近几年。虽然 LCS 在机构地点的性能提升不大（CV-RMSE = 2.8 ppb NO2；无 LCS 时 CV- R 2 = 0.82），但在居民点的性能提升很大，RMSE = 3.8 ppb NO2，R 2 = 0.08（无 LCS），而 CV-RMSE = 2.8 ppb NO2，CV- R 2 = 0.51（有 LCS）：我们为华盛顿州普吉特海湾地区的二氧化氮（NO2）污染开发了一个时空模型，用于 "成人思想空气污染变化 "研究的流行病学暴露评估。我们研究了在二氧化氮模型中加入低成本传感器数据的影响，发现传感器提供的额外空间信息所预测的二氧化氮浓度高于没有低成本传感器的情况，尤其是在最近几年。与没有低成本传感器数据的类似模型相比，我们没有观察到交叉验证性能有明显的大幅提高；但是，在居民点使用低成本传感器后，预测性能有了大幅提高。由于其他补充监测数据提供了空间信息，低成本传感器带来的性能提升可能有所减弱。
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引用次数: 0
Identification of high lead exposure locations in Ohio at the census tract scale using a generalizable geospatial hotspot approach 利用可推广的地理空间热点方法，在俄亥俄州人口普查区范围内确定高铅暴露地点
IF 4.1 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-04-04 DOI: 10.1038/s41370-024-00666-x
Lindsay W. Stanek, Jianping Xue, Valerie G. Zartarian, Antonios G. Poulakos, Rogelio Tornero-Velez, Emily G. Snyder, Alan Walts, Kathy Triantafillou
Lead is a persistent, ubiquitous pollutant whose historical sources have been largely addressed through regulation and voluntary actions. The United States (U.S.) has achieved significant decreases in children’s blood lead levels (BLL) over the past 40 years; however, there is no known safe level of Pb exposure. Some communities continue to be disproportionately impacted by exposure to Pb, including Black children and families living in older homes. To identify Ohio (OH) census tracts with children exposed to Pb and evaluate potential exposure determinants. We obtained individual children’s blood Pb data from 2005–2018 in OH. The percent of children with elevated BLL (EBLL) was calculated for OH census tracts using three blood Pb reference values (3.5, 5, and 10 µg/dL). Getis-Ord Gi* geospatial hotspot or top 20th percentile methodologies were then applied to identify “hotspots.” Findings across multiple time periods and blood Pb reference values were evaluated and compared with existing Pb exposure indices and models. Consistency was observed across different blood Pb reference values, with the main hotspots identified at 3.5 µg/dL, also identified at 5 and 10 µg/dL. Substantial gains in public health were demonstrated, with the biggest decreases in the number of census tracts with EBLL observed between 2008–2010 and 2011–2013. Across OH, 355 census tracts (of 2850) were identified as hotspots across 17 locations, with the majority in the most populated cites. Generally, old housing and sociodemographic factors were indicators of these EBLL hotspots. A smaller number of hotspots were not associated with these exposure determinants. Variables of race, income, and education level were all strong predictors of hotspots. The Getis-Ord Gi* geospatial hotspot analysis can inform local investigations into potential Pb exposures for children living in OH. The successful application of a generalizable childhood blood Pb methodology at the census tract scale provides results that are more readily actionable. The moderate agreement of the measured blood Pb results with public Pb indices provide confidence that these indices can be used in the absence of available blood Pb surveillance data. While not a replacement for universal blood Pb testing, a consistent approach can be applied to identify areas where Pb exposure may be problematic.
背景铅是一种持久性的、无处不在的污染物，其历史来源主要是通过监管和自愿行动来解决的。在过去的 40 年中，美国儿童的血铅含量（BLL）已显著下降；然而，目前尚无已知的铅暴露安全水平。目标确定俄亥俄州（OH）有儿童暴露于铅的人口普查区，并评估潜在的暴露决定因素。方法我们获得了俄亥俄州 2005-2018 年的儿童血铅数据。我们使用三个血铅参考值（3.5、5 和 10 µg/dL）计算了俄亥俄州人口普查区血铅含量升高（EBLL）儿童的百分比。然后采用 Getis-Ord Gi* 地理空间热点或前 20 百分位数方法来确定 "热点"。结果在不同的血铅参考值中观察到了一致性，主要热点被确定为 3.5 µg/dL，也被确定为 5 和 10 µg/dL。在 2008-2010 年和 2011-2013 年期间，出现 EBLL 的人口普查区数量降幅最大。在整个俄亥俄州，355 个普查区（共 2850 个）被确定为 17 个地点的热点，其中大多数位于人口最稠密的城市。一般来说，旧住房和社会人口因素是这些 EBLL 热点的指标。少数热点地区与这些暴露决定因素无关。种族、收入和教育水平等变量都是热点的有力预测因素。影响声明Getis-Ord Gi*地理空间热点分析可为当地调查俄亥俄州儿童潜在的铅暴露提供信息。在人口普查区范围内成功应用可推广的儿童血铅方法可提供更易于操作的结果。测得的血铅结果与公共血铅指数基本一致，这使人们相信，在没有可用的血铅监测数据的情况下，这些指数是可以使用的。虽然不能取代普遍的血铅检测，但可以采用一致的方法来确定可能存在铅暴露问题的地区。
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引用次数: 0
Noise annoyance due to different sources is associated with tinnitus presence and distress in the general population 在普通人群中，不同来源的噪音干扰与耳鸣的存在和困扰有关
IF 4.5 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-04-03 DOI: 10.1038/s41370-024-00668-9
Omar Hahad, Julia Döge, Katharina Bahr-Hamm, Manfred E. Beutel, Konstantin Kontohow-Beckers, Alexander K. Schuster, Karsten Keller, Lukas Hobohm, Volker H. Schmitt, Emilio Gianicolo, Karl J. Lackner, Andreas Daiber, Philipp S. Wild, Berit Hackenberg, Thomas Münzel

Background

The pathophysiology of tinnitus is not yet fully understood. Although there is a large amount of evidence associating traffic noise exposure with non-auditory health outcomes, there is no evidence regarding the impact of noise annoyance on auditory disorders such as tinnitus.

Objective

Thus, we aimed to investigate the association between noise annoyance due to different sources and tinnitus presence and distress in the general population.

Methods

Data of 6813 participants from a large German population-based cohort were used (Gutenberg Health Study). Participants were asked about the presence of tinnitus and how much they were bothered by it. In addition, information on annoyance from road traffic, aircraft, railways, industrial, and neighborhood noise during the day and sleep was collected through validated questionnaires.

Results

The prevalence of tinnitus was 27.3%, and the predominant sources of noise annoyance in these subjects were aircraft, neighborhood, and road traffic noise. Overall, logistic regression results demonstrated consistent positive associations between annoyance due to different noise sources and prevalent risk of tinnitus with increases in odds ratios ranging from 4 to 11% after adjustment for sex, age, and socioeconomic status. Likewise, consistent increases in odds ratios were observed for tinnitus distress in subjects with prevalent tinnitus. For instance, neighborhood noise annoyance during the sleep was associated with a 26% increase in tinnitus distress (OR 1.26, 95% CI 1.13; 1.39).

Impact

This is the first study investigating the association between noise annoyance and tinnitus presence and distress in a large cohort of the general population. Our results indicate consistent and positive associations between various sources of noise annoyance and tinnitus. These unprecedented findings are highly relevant as noise annoyance and tinnitus are widespread. The precise etiology and locus of tinnitus remain unknown, but excessive noise exposure is thought to be among the major causes. This study suggests that transportation and neighborhood noise levels thought merely to contribute to annoyance and non-auditory health effects may be sufficient to cause or exacerbate tinnitus.

背景耳鸣的病理生理学尚未完全清楚。尽管有大量证据表明交通噪声暴露与非听觉健康后果有关，但没有证据表明噪声烦恼对耳鸣等听觉障碍的影响。因此，我们旨在调查普通人群中不同来源的噪声烦恼与耳鸣的存在和困扰之间的关系。研究人员询问了参与者是否存在耳鸣以及耳鸣对他们的困扰程度。此外，还通过有效问卷收集了白天和睡眠时受道路交通、飞机、铁路、工业和邻里噪音困扰的信息。结果耳鸣的患病率为 27.3%，这些受试者主要的噪音困扰来源是飞机、邻里和道路交通噪音。总体而言，逻辑回归结果表明，在对性别、年龄和社会经济地位进行调整后，不同噪声源造成的烦恼与耳鸣患病风险之间存在一致的正相关关系，几率增加了 4% 至 11%。同样，在耳鸣流行的受试者中，也观察到耳鸣困扰的几率持续增加。例如，睡眠期间邻里噪音干扰与耳鸣困扰增加 26% 相关（OR 1.26，95% CI 1.13; 1.39）。我们的研究结果表明，各种噪声烦恼源与耳鸣之间存在一致的正相关关系。由于噪声烦恼和耳鸣非常普遍，这些史无前例的发现具有重要意义。耳鸣的确切病因和发病部位仍不清楚，但过度暴露于噪声被认为是主要原因之一。这项研究表明，被认为仅会造成烦扰和非听觉健康影响的交通和邻里噪声水平可能足以导致或加剧耳鸣。
{"title":"Noise annoyance due to different sources is associated with tinnitus presence and distress in the general population","authors":"Omar Hahad, Julia Döge, Katharina Bahr-Hamm, Manfred E. Beutel, Konstantin Kontohow-Beckers, Alexander K. Schuster, Karsten Keller, Lukas Hobohm, Volker H. Schmitt, Emilio Gianicolo, Karl J. Lackner, Andreas Daiber, Philipp S. Wild, Berit Hackenberg, Thomas Münzel","doi":"10.1038/s41370-024-00668-9","DOIUrl":"https://doi.org/10.1038/s41370-024-00668-9","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>The pathophysiology of tinnitus is not yet fully understood. Although there is a large amount of evidence associating traffic noise exposure with non-auditory health outcomes, there is no evidence regarding the impact of noise annoyance on auditory disorders such as tinnitus.</p><h3 data-test=\"abstract-sub-heading\">Objective</h3><p>Thus, we aimed to investigate the association between noise annoyance due to different sources and tinnitus presence and distress in the general population.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Data of 6813 participants from a large German population-based cohort were used (Gutenberg Health Study). Participants were asked about the presence of tinnitus and how much they were bothered by it. In addition, information on annoyance from road traffic, aircraft, railways, industrial, and neighborhood noise during the day and sleep was collected through validated questionnaires.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>The prevalence of tinnitus was 27.3%, and the predominant sources of noise annoyance in these subjects were aircraft, neighborhood, and road traffic noise. Overall, logistic regression results demonstrated consistent positive associations between annoyance due to different noise sources and prevalent risk of tinnitus with increases in odds ratios ranging from 4 to 11% after adjustment for sex, age, and socioeconomic status. Likewise, consistent increases in odds ratios were observed for tinnitus distress in subjects with prevalent tinnitus. For instance, neighborhood noise annoyance during the sleep was associated with a 26% increase in tinnitus distress (OR 1.26, 95% CI 1.13; 1.39).</p><h3 data-test=\"abstract-sub-heading\">Impact</h3><p>This is the first study investigating the association between noise annoyance and tinnitus presence and distress in a large cohort of the general population. Our results indicate consistent and positive associations between various sources of noise annoyance and tinnitus. These unprecedented findings are highly relevant as noise annoyance and tinnitus are widespread. The precise etiology and locus of tinnitus remain unknown, but excessive noise exposure is thought to be among the major causes. This study suggests that transportation and neighborhood noise levels thought merely to contribute to annoyance and non-auditory health effects may be sufficient to cause or exacerbate tinnitus.</p>","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"37 1","pages":""},"PeriodicalIF":4.5,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570442","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}
引用次数: 0
Unmasking the sky: high-resolution PM2.5 prediction in Texas using machine learning techniques 揭开天空的面纱：利用机器学习技术对得克萨斯州 PM2.5 进行高分辨率预测。
IF 4.1 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-04-01 DOI: 10.1038/s41370-024-00659-w
Kai Zhang, Jeffrey Lin, Yuanfei Li, Yue Sun, Weitian Tong, Fangyu Li, Lung-Chang Chien, Yiping Yang, Wei-Chung Su, Hezhong Tian, Peng Fu, Fengxiang Qiao, Xiaobo Xue Romeiko, Shao Lin, Sheng Luo, Elena Craft
Although PM2.5 (fine particulate matter with an aerodynamic diameter less than 2.5 µm) is an air pollutant of great concern in Texas, limited regulatory monitors pose a significant challenge for decision-making and environmental studies. This study aimed to predict PM2.5 concentrations at a fine spatial scale on a daily basis by using novel machine learning approaches and incorporating satellite-derived Aerosol Optical Depth (AOD) and a variety of weather and land use variables. We compiled a comprehensive dataset in Texas from 2013 to 2017, including ground-level PM2.5 concentrations from regulatory monitors; AOD values at 1-km resolution based on images retrieved from the MODIS satellite; and weather, land-use, population density, among others. We built predictive models for each year separately to estimate PM2.5 concentrations using two machine learning approaches called gradient boosted trees and random forest. We evaluated the model prediction performance using in-sample and out-of-sample validations. Our predictive models demonstrate excellent in-sample model performance, as indicated by high R2 values generated from the gradient boosting models (0.94–0.97) and random forest models (0.81–0.90). However, the out-of-sample R2 values fall within a range of 0.52–0.75 for gradient boosting models and 0.44–0.69 for random forest models. Model performance varies slightly across years. A generally decreasing trend in predicted PM2.5 concentrations over time is observed in Eastern Texas. We utilized machine learning approaches to predict PM2.5 levels in Texas. Both gradient boosting and random forest models perform well. Gradient boosting models perform slightly better than random forest models. Our models showed excellent in-sample prediction performance (R2 > 0.9).
背景：尽管 PM2.5（空气动力学直径小于 2.5 µm 的细颗粒物）是德克萨斯州极为关注的一种空气污染物，但有限的监管监测器对决策和环境研究构成了重大挑战：本研究旨在利用新颖的机器学习方法，结合从卫星获取的气溶胶光学深度（AOD）以及各种天气和土地利用变量，预测每日精细空间尺度上的 PM2.5 浓度：我们汇编了 2013 年至 2017 年德克萨斯州的综合数据集，其中包括监管监测机构提供的地面 PM2.5 浓度；基于 MODIS 卫星图像检索的 1 千米分辨率 AOD 值；以及天气、土地使用、人口密度等。我们使用梯度提升树和随机森林两种机器学习方法，分别为每一年建立了预测模型，以估算 PM2.5 浓度。我们通过样本内和样本外验证对模型的预测性能进行了评估：梯度提升模型（0.94-0.97）和随机森林模型（0.81-0.90）产生的高 R2 值表明，我们的预测模型具有出色的样本内模型性能。然而，梯度提升模型的样本外 R2 值在 0.52-0.75 之间，随机森林模型的样本外 R2 值在 0.44-0.69 之间。不同年份的模型性能略有不同。在得克萨斯州东部，PM2.5 的预测浓度随时间呈总体下降趋势：我们利用机器学习方法来预测德克萨斯州的 PM2.5 浓度。梯度提升模型和随机森林模型都表现良好。梯度提升模型的表现略好于随机森林模型。我们的模型显示出出色的样本内预测性能（R2 > 0.9）。
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引用次数: 0
Temporal trend of microenvironmental time-activity patterns of the Seoul population from 2004 to 2022 and its potential impact on exposure assessment. 2004 至 2022 年首尔人口微环境时间活动模式的时间趋势及其对暴露评估的潜在影响。
IF 4.5 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-03-28 DOI: 10.1038/s41370-024-00662-1
Donghyun Kim, Sooyoung Guak, Kiyoung Lee

Background: Time-activity pattern (TAP) is an important parameter for determining personal exposure to environmental pollutants. Changes in TAPs could have significant implications for the alterations in outcomes of exposure assessments.

Objective: This study aimed to evaluate the Seoul population's long-term change in TAPs, along with variations by sociodemographic group.

Methods: In 2004, 2009, 2014, and 2019, the Time Use Survey of Statistics Korea collected the TAP information of 4036, 2610, 3337, and 2793 Seoul residents, respectively. In 2022, the TAP information of 4401 Seoul residents was collected for Korean Air Pollutant Exposure (KAPEX) research. The microenvironmental TAP changes in the Seoul population from 2004 to 2022 were assessed based on age, gender, work status, and day type.

Results: From 2004 to 2022, Seoul people increasingly spent more time in indoor residences (from 14.8 ± 5.1 h to 15.8 ± 4.5 h) and less time in other indoors (from 7.2 ± 4.5 h to 5.9 ± 4.2 h). Their transit time constantly decreased from 2004 (1.4 ± 1.8 h) to 2022 (1.2 ± 1.3 h), whereas the outdoor time fluctuated throughout the years. From 2004 to 2022, the time of the day spent by Seoul people in residential indoor shifted to later in the morning (2004: 8:30 am; 2022: 9:00 am) and earlier in the evening (2004: 9:30 pm; 2022: 7:00 pm); however, the opposite was true for other indoors (2004: from 8:30 am to 9:30 pm; 2022: from 9:00 am to 7:00 pm) and transits (2004: 7:30-9:30 am and 3:00-8:00 pm; 2022: 7:30-9:00 pm and 5:00-9:00). The time of the day spent in outdoors increased from 2004 to 2019, with a distinct peak observed in 2022 (12:00 pm-2:00 pm). The microenvironmental time trends of adolescents and late-adulthoods differed from those of the other age groups, while those of males differed from females. Also, the microenvironmental time trends of the employed differed from those of the unemployed, and those during weekdays differed from those during weekends.

Impact statement: Microenvironmental TAP should be essentially considered to estimate the actual exposure to pollutants. This study demonstrates the Seoul population's long-term changes in TAP throughout the 18 years as the significant parameter in exposure assessment. Notably, the microenvironmental TAPs of Seoul people shifted, with variations across different sociodemographic groups. Previous studies in Korea did not consider the TAP shifts in exposure assessment; this study highlights the importance of aligning TAP data with concurrent environmental pollutant data and emphasizes the need for refined data collection in future exposure assessments.

背景：时间活动模式（TAP）是确定个人暴露于环境污染物的一个重要参数。时间活动模式的变化可能会对暴露评估结果的改变产生重大影响：本研究旨在评估首尔人口 TAPs 的长期变化以及不同社会人口群体的变化：2004 年、2009 年、2014 年和 2019 年，韩国统计局的时间利用调查分别收集了 4036、2610、3337 和 2793 名首尔居民的 TAP 信息。2022 年，韩国空气污染物暴露（KAPEX）研究收集了 4401 名首尔居民的 TAP 信息。根据年龄、性别、工作状态和日照类型，评估了 2004 年至 2022 年首尔人口的微环境 TAP 变化：从 2004 年到 2022 年，首尔人在室内居住的时间越来越多（从 14.8 ± 5.1 小时增加到 15.8 ± 4.5 小时），而在其他室内活动的时间越来越少（从 7.2 ± 4.5 小时减少到 5.9 ± 4.2 小时）。从2004年（1.4±1.8小时）到2022年（1.2±1.3小时），它们的过境时间持续减少，而室外时间则逐年波动。从 2004 年到 2022 年，首尔人一天中在住宅室内逗留的时间变为早上较晚（2004 年：上午 8:30；2022 年：上午 9:00）和晚上较早（2004 年：晚上 9:30；2022 年：晚上 7：00）；但其他室内（2004 年：上午 8:30 至晚上 9:30；2022 年：上午 9:00 至晚上 7:00）和过境（2004 年：上午 7:30 至 9:30，晚上 3:00 至 8:00；2022 年：晚上 7:30 至 9:00，5:00 至 9:00）的情况则相反。从 2004 年到 2019 年，一天中户外活动的时间有所增加，2022 年出现了一个明显的高峰（中午 12:00-下午 2:00）。青少年和成年晚期的微环境时间趋势与其他年龄组不同，而男性与女性的微环境时间趋势也不同。此外，就业者与失业者的微环境时间趋势不同，工作日与周末的微环境时间趋势也不同：影响说明：要估算污染物的实际暴露量，应主要考虑微环境 TAP。本研究表明，首尔人口在 18 年间的总环境负荷率的长期变化是暴露评估的重要参数。值得注意的是，首尔人的微环境暴露量发生了变化，不同的社会人口群体之间也存在差异。韩国以往的研究在进行暴露评估时没有考虑到 TAP 的变化；本研究强调了 TAP 数据与同期环境污染物数据保持一致的重要性，并强调了在未来的暴露评估中进行精细化数据收集的必要性。
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引用次数: 0
United States house dust Pb concentrations are influenced by soil, paint, and house age: insights from a national survey 美国房屋灰尘中铅浓度受土壤、涂料和房龄的影响：一项全国调查的启示。
IF 4.1 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-03-28 DOI: 10.1038/s41370-024-00655-0
Tyler D. Sowers, Clay M. Nelson, Matthew D. Blackmon, Kevin Li, Marissa L. Jerden, Alicia M. Kirby, Kasey Kovalcik, David Cox, Gary Dewalt, Warren Friedman, Eugene A. Pinzer, Peter J. Ashley, Karen D. Bradham
Lead (Pb) in house dust contributes significantly to blood lead levels (BLLs) in children which may result in dire health consequences. Assessment of house dust Pb in the United States, relationships with Pb in soil and paint, and residential factors influencing Pb concentrations are essential to probing drivers of house dust Pb exposure. Pb concentrations in vacuum-collected house dust are characterized across 346 homes participating in the American Health Homes Survey II (AHHS II), a US survey (2018–2019) evaluating residential Pb hazards. Connections between house dust Pb and soil Pb, paint Pb, and other residential factors are evaluated, and dust Pb concentration data are compared to paired loading data to understand Pb hazard standard implications. Mean and median vacuum dust Pb concentrations were 124 µg Pb g−1 and 34 µg Pb g−1, respectively. Vacuum-collected dust concentrations and dust wipe Pb loading rates were significantly correlated within homes (α < 0.001; r ≥ 0.4). At least one wipe sample exceeded current house dust Pb loading hazard standards (10 µg ft−2 or 100 µg Pb ft−2 for floors and windowsills, respectively) in 75 of 346 homes (22%). House dust Pb concentrations were correlated with soil Pb (r = 0.64) and Pb paint (r = 0.57). Soil Pb and paint Pb were also correlated (r = 0.6). The AHHS II provides a window into the current state of Pb in and around residences. We evaluated the relationship between house dust Pb concentrations and two common residential Pb sources: soil and Pb-based paint. Here, we identify relationships between Pb concentrations from vacuum-collected dust and paired Pb wipe loading data, enabling dust Pb concentrations to be evaluated in the context of hazard standards. This relationship, along with direct ties to Pb in soil and interior/exterior paint, provides a comprehensive assessment of dust Pb for US homes, crucial for formulating effective strategies to mitigate Pb exposure risks in households.
背景：室内灰尘中的铅（Pb）是导致儿童血铅含量（BLLs）的重要因素，可能会对儿童的健康造成严重后果。评估美国住宅灰尘中的铅含量、与土壤和油漆中铅含量的关系以及影响铅含量的住宅因素，对于探究住宅灰尘铅暴露的驱动因素至关重要：在参与美国健康家庭调查 II（AHHS II）的 346 个家庭中，对真空收集的屋尘中的铅浓度进行了特征描述，该调查（2018-2019 年）对住宅铅危害进行了评估。评估了房屋灰尘铅与土壤铅、涂料铅和其他住宅因素之间的联系，并将灰尘铅浓度数据与配对加载数据进行了比较，以了解铅危害标准的影响：结果：真空吸尘铅浓度的平均值和中位数分别为 124 µg Pb g-1 和 34 µg Pb g-1。在 346 个家庭中，有 75 个家庭（22%）的吸尘器收集到的灰尘浓度与擦拭灰尘的铅负荷率在家庭内部存在显著相关性（地板和窗台的铅负荷率分别为 α -2 或 100 µg Pb ft-2）。房屋灰尘中的铅浓度与土壤中的铅浓度（r = 0.64）和涂料中的铅浓度（r = 0.57）相关。土壤中的铅和油漆中的铅也有相关性（r = 0.6）：影响：AHHS II 提供了一个了解住宅内和住宅周围铅含量现状的窗口。我们评估了房屋灰尘铅浓度与两种常见的住宅铅来源（土壤和含铅涂料）之间的关系。在此，我们确定了从真空收集的灰尘中提取的铅浓度与成对的铅擦拭负载数据之间的关系，从而能够根据危害标准对灰尘中的铅浓度进行评估。这种关系以及与土壤和内/外墙涂料中铅的直接联系，提供了对美国家庭灰尘中铅的全面评估，这对于制定有效策略以降低家庭中的铅暴露风险至关重要。
{"title":"United States house dust Pb concentrations are influenced by soil, paint, and house age: insights from a national survey","authors":"Tyler D. Sowers,&nbsp;Clay M. Nelson,&nbsp;Matthew D. Blackmon,&nbsp;Kevin Li,&nbsp;Marissa L. Jerden,&nbsp;Alicia M. Kirby,&nbsp;Kasey Kovalcik,&nbsp;David Cox,&nbsp;Gary Dewalt,&nbsp;Warren Friedman,&nbsp;Eugene A. Pinzer,&nbsp;Peter J. Ashley,&nbsp;Karen D. Bradham","doi":"10.1038/s41370-024-00655-0","DOIUrl":"10.1038/s41370-024-00655-0","url":null,"abstract":"Lead (Pb) in house dust contributes significantly to blood lead levels (BLLs) in children which may result in dire health consequences. Assessment of house dust Pb in the United States, relationships with Pb in soil and paint, and residential factors influencing Pb concentrations are essential to probing drivers of house dust Pb exposure. Pb concentrations in vacuum-collected house dust are characterized across 346 homes participating in the American Health Homes Survey II (AHHS II), a US survey (2018–2019) evaluating residential Pb hazards. Connections between house dust Pb and soil Pb, paint Pb, and other residential factors are evaluated, and dust Pb concentration data are compared to paired loading data to understand Pb hazard standard implications. Mean and median vacuum dust Pb concentrations were 124 µg Pb g−1 and 34 µg Pb g−1, respectively. Vacuum-collected dust concentrations and dust wipe Pb loading rates were significantly correlated within homes (α &lt; 0.001; r ≥ 0.4). At least one wipe sample exceeded current house dust Pb loading hazard standards (10 µg ft−2 or 100 µg Pb ft−2 for floors and windowsills, respectively) in 75 of 346 homes (22%). House dust Pb concentrations were correlated with soil Pb (r = 0.64) and Pb paint (r = 0.57). Soil Pb and paint Pb were also correlated (r = 0.6). The AHHS II provides a window into the current state of Pb in and around residences. We evaluated the relationship between house dust Pb concentrations and two common residential Pb sources: soil and Pb-based paint. Here, we identify relationships between Pb concentrations from vacuum-collected dust and paired Pb wipe loading data, enabling dust Pb concentrations to be evaluated in the context of hazard standards. This relationship, along with direct ties to Pb in soil and interior/exterior paint, provides a comprehensive assessment of dust Pb for US homes, crucial for formulating effective strategies to mitigate Pb exposure risks in households.","PeriodicalId":15684,"journal":{"name":"Journal of Exposure Science and Environmental Epidemiology","volume":"34 4","pages":"709-717"},"PeriodicalIF":4.1,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11303246/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140318437","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}
引用次数: 0
The joint effects of prenatal exposure to PM2.5 constituents and reduced fetal growth on children's accelerated growth in the first 3 years: a birth cohort study. 产前暴露于 PM2.5 成分和胎儿发育不良对儿童头 3 年加速生长的共同影响：一项出生队列研究。
IF 4.5 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-03-26 DOI: 10.1038/s41370-024-00658-x
Shuang Zhou, Tiantian Li, Na Han, Kai Zhang, Gongbo Chen, Yi Zhang, Qin Li, Yuelong Ji, Jue Liu, Hui Wang, Jianlin Hu, Ting Liu, Hein Raat, Yuming Guo, Haijun Wang

Background: Prenatal fine particulate matter (PM2.5) constituents exposure and reduced fetal growth may be risk factors for accelerated growth in early childhood, an important indicator for lifelong health.

Objective: The study investigated whether the joint effects are present between PM2.5 constituents and reduced fetal growth.

Methods: The study was embedded in a birth cohort in China, including 5424 mother-child pairs. Prenatal PM2.5 and its constituents' [organic carbon (OC), elementary carbon (EC), ammonium (NH4+), nitrate (NO3-), and sulfate (SO42-)] concentrations were estimated based on maternal residential addresses. Fetal growth was evaluated by fetal growth trajectory in utero and preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA). Children's accelerated growth was defined as body mass index (BMI) Z-score change of >0.67 between birth and 3 years. Generalized logistic regression was used to analyze the effects of prenatal PM2.5 constituents exposure and fetal growth on children's accelerated growth. Joint effect was tested on multiplicative scale and additive scale with the relative excess risk due to interaction (RERI).

Results: Children with lower fetal growth trajectory, PTB, LBW, and SGA had increased odds of children's accelerated growth, with odds ratios (ORs) ranging from 1.704 to 11.605. Compared with lower exposure (≤median), higher exposure (>median) of PM2.5, OC, and SO42- were significantly associated with increased odds of children's accelerated growth, varying in ORs from 1.163 to 1.478. Prenatal exposure to OC had joint effects with lower fetal growth on children's accelerated growth. We observed that the interaction was statistically significant on an additive scale in OC and lower fetal growth trajectory (RERI: 0.497, 95% CI: 0.033,0.962).

Impact: Fine particulate matter (PM2.5) is a huge threat to human health worldwide, causing 6.7 million death globally in 2019. According to the theory of DOHaD, prenatal PM2.5 exposure could influence early childhood growth, which is important for lifelong health. We found that prenatal exposure to PM2.5, OC, and SO42- was associated with higher risk of accelerated childhood growth in the first 3 years. More importantly, reduced fetal growth moderated these associations. Our findings highlight the need for policies and interventions on PM2.5 constituents to improve lifelong health, especially for those vulnerable populations with reduced fetal growth.

背景：产前细颗粒物（PM2.5）成分暴露和胎儿生长减慢可能是儿童早期生长加速的风险因素，而儿童早期生长加速是终身健康的重要指标：该研究调查了 PM2.5 成分与胎儿生长减慢之间是否存在联合效应：方法：该研究嵌入了中国的出生队列，包括 5424 对母婴。产前 PM2.5 及其成分[有机碳（OC）、基本碳（EC）、铵（NH4+）、硝酸盐（NO3-）和硫酸盐（SO42-）]的浓度是根据产妇居住地址估算的。胎儿生长情况通过宫内胎儿生长轨迹、早产（PTB）、低出生体重（LBW）和小于胎龄（SGA）进行评估。儿童加速生长的定义是出生至 3 岁期间体重指数（BMI）Z 值变化大于 0.67。采用广义逻辑回归分析产前PM2.5成分暴露和胎儿生长对儿童加速生长的影响。结果显示，胎儿生长轨迹较低的儿童在出生后 3 岁时的生长速度较快，而生长轨迹较高的儿童在出生后 3 岁时的生长速度较慢：结果：胎儿生长轨迹较低、PTB、LBW 和 SGA 的儿童出现生长加速的几率增加，几率比（ORs）从 1.704 到 11.605 不等。与较低的PM2.5、OC和SO42-暴露量（≤中位数）相比，较高的PM2.5、OC和SO42-暴露量（>中位数）与儿童生长加速几率的增加有显著相关性，几率比从1.163到1.478不等。产前暴露于 OC 与胎儿较低的生长速度共同影响了儿童的加速生长。我们观察到，OC 与胎儿较低的生长轨迹之间的交互作用在统计学上具有显著的加法效应（RERI：0.497，95% CI：0.033,0.962）：细颗粒物（PM2.5）是全球人类健康的巨大威胁，2019 年将导致全球 670 万人死亡。根据DOHaD理论，产前暴露于PM2.5会影响儿童的早期发育，而这对儿童的终生健康非常重要。我们发现，产前暴露于 PM2.5、OC 和 SO42- 与儿童头 3 年生长加速的较高风险有关。更重要的是，胎儿生长速度的降低缓和了这些关联。我们的研究结果突出表明，有必要制定有关 PM2.5 成分的政策和干预措施，以改善人们的终生健康，尤其是那些胎儿发育迟缓的弱势群体。
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引用次数: 0
Shaping a 21st century federal noise control program. 制定 21 世纪联邦噪声控制计划。
IF 4.5 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-03-23 DOI: 10.1038/s41370-024-00657-y
Charles L Elkins, Jamie L Banks
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引用次数: 0
Accuracy of self-reported distance to nearest unconventional oil and gas well in Pennsylvania, Ohio, and West Virginia residents and implications for exposure assessment 宾夕法尼亚州、俄亥俄州和西弗吉尼亚州居民自我报告与最近非常规油气井距离的准确性及其对暴露评估的影响。
IF 4.1 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-03-06 DOI: 10.1038/s41370-023-00637-8
Cassandra J. Clark, Joan A. Casey, Michelle L. Bell, Desiree L. Plata, James E. Saiers, Nicole C. Deziel
Self-reported distances to industrial sources have been used in epidemiology as proxies for exposure to environmental hazards and indicators of awareness and perception of sources. Unconventional oil and gas development (UOG) emits pollutants and has been associated with adverse health outcomes. We compared self-reported distance to the nearest UOG well to the geographic information system-calculated distance for 303 Pennsylvania, Ohio, and West Virginia residents using Cohen’s Weighted Kappa. Agreement was low (Kappa = 0.18), and self-reports by Ohioans (39% accuracy) were more accurate than West Virginians (22%) or Pennsylvanians (13%, both p < 0.05). Of the demographic characteristics studied, only educational attainment was related to reporting accuracy; residents with 12–16 years of education were more accurate (31.3% of group) than those with <12 or >16 years (both 16.7%). Understanding differences between objective and subjective measures of UOG proximity could inform studies of perceived exposures or risks and may also be relevant to adverse health effects. We compared objective and self-reported measures of distance to the nearest UOG well for 303 Appalachian Basin residents. We found that residents’ self-reported distance to the nearest UOG well had limited agreement with the true calculated distance category. Our results can be used to inform the collection and contextualize the use of self-reported data in communities exposed to UOGD. Self-reported metrics can be used in conjunction with objective assessments and can be informative regarding how potentially exposed populations perceive environmental exposures or risks and could provide insights into awareness of distance-related policies, such as setbacks.
在流行病学中，自我报告的与工业污染源的距离被用作暴露于环境危害的替代物以及对污染源的认识和感知指标。非常规油气开发（UOG）会排放污染物，并与不良健康后果相关。我们使用科恩加权卡帕法比较了 303 名宾夕法尼亚州、俄亥俄州和西弗吉尼亚州居民自我报告的与最近的 UOG 油井的距离和地理信息系统计算的距离。两者的一致性较低（Kappa = 0.18），俄亥俄州人的自我报告（准确率为 39%）比西弗吉尼亚州人（准确率为 22%）或宾夕法尼亚州人（准确率为 13%，P 均为 16 岁，均为 16.7%）更准确。了解客观和主观测量UOG邻近性之间的差异，可为有关感知暴露或风险的研究提供信息，也可能与不良健康影响有关。影响：我们比较了 303 位阿巴拉契亚盆地居民客观和自我报告的与最近的铀浓缩物井的距离。我们发现，居民自我报告的与最近 UOG 井的距离与真实计算距离类别的一致性有限。我们的研究结果可用于在受铀-氧化物-酸性气体排放影响的社区收集自我报告数据，并为其使用提供参考。自我报告的指标可与客观评估结合使用，可提供有关潜在暴露人群如何看待环境暴露或风险的信息，并可提供对距离相关政策（如后退）的认识。
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引用次数: 0
Construction of residential histories to estimate long-term environmental exposures in the California Teachers Study cohort 构建居住历史，估算加州教师研究队列中的长期环境暴露。
IF 4.1 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Journal of Exposure Science and Environmental Epidemiology
Pub Date : 2024-03-06 DOI: 10.1038/s41370-023-00631-0
Danielle N. Medgyesi, Emma S. Spielfogel, Mary H. Ward, Rena R. Jones, Kristen E. Savage, Jennifer L. Benbow, James V. Lacey Jr, Tiffany R. Sanchez
Environmental epidemiologic studies using geospatial data often estimate exposure at a participant’s residence upon enrollment, but mobility during the exposure period can lead to misclassification. We aimed to mitigate this issue by constructing residential histories for participants in the California Teachers Study through follow-up (1995–2018). Address records have been collected from the US Postal Service, LexisNexis, Experian, and California Cancer Registry. We identified records of the same address based on geo-coordinate distance (≤250 m) and street name similarity. We consolidated addresses, prioritizing those confirmed by participants during follow-up questionnaires, and estimating the duration lived at each address using dates associated with records (e.g., date-first-seen). During 23 years of follow-up, about half of participants moved (48%, including 14% out-of-state). We observed greater mobility among younger women, Hispanic/Latino women, and those in metropolitan and lower socioeconomic status areas. The cumulative proportion of in-state movers remaining eligible for analysis was 21%, 32%, and 41% at 5, 10, and 20 years post enrollment, respectively. Using self-reported information collected 10 years after enrollment, we correctly identified 94% of movers and 95% of non-movers as having moved or not moved from their enrollment address. This dataset provides a foundation for estimating long-term environmental exposures in diverse epidemiologic studies in this cohort.
使用地理空间数据进行的环境流行病学研究通常以参与者注册时的居住地估算暴露量，但暴露期间的流动性可能会导致分类错误。我们的目的是通过构建加州教师研究参与者的居住历史记录来缓解这一问题，并对其进行跟踪调查（1995-2018 年）。我们从美国邮政服务、LexisNexis、Experian 和加州癌症登记处收集了地址记录。我们根据地理坐标距离（≤250 米）和街道名称相似度确定了相同地址的记录。我们对地址进行了整合，优先考虑参与者在随访问卷中确认的地址，并利用与记录相关的日期（如首次出现日期）估算出在每个地址居住的时间。在 23 年的随访期间，约有一半的参与者搬家（48%，其中 14% 迁往州外）。我们观察到，年轻女性、西班牙裔/拉丁裔女性以及大都市和社会经济地位较低地区的女性流动性更大。在注册后 5 年、10 年和 20 年，仍符合分析条件的州内流动者的累计比例分别为 21%、32% 和 41%。利用入学 10 年后收集的自我报告信息，我们正确识别了 94% 的搬家者和 95% 的未搬家者是否搬离了入学地址。该数据集为估计该队列中不同流行病学研究的长期环境暴露奠定了基础。影响：我们为 "加州教师研究 "参与者建立的居住历史记录（1995-2018 年）有利于未来的环境流行病学研究。在暴露期间提供地址可以减少因居住地变化而导致的误分类，尤其是在评估长期暴露和慢性健康结果时。这可以减少流动性较强的亚组（包括年轻女性以及来自社会经济地位较低和城市地区的女性）中的不同错误分类。与自我报告的居住地信息相比，我们整合多种来源地址的方法显示出较高的准确性。本次分析所产生的居住地数据集为未来的研究提供了宝贵的工具，最终将加深我们对环境健康影响的理解。
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