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评估基于接近度的度量与空气污染监测数据在非常规资源开发的流行病学研究中暴露分类的一致性。

Assessing Agreement in Exposure Classification between Proximity-Based Metrics and Air Monitoring Data in Epidemiology Studies of Unconventional Resource Development.

机构信息

Shell Health Risk Science Team, Shell Oil Company, 150 North Dairy Ashford, Houston, TX 77079, USA.

Shell Health Risk Science Team, Shell International B.V., Carel Van Bylandtlaan 16, 2596 HR The Hague, The Netherlands.

出版信息

Int J Environ Res Public Health. 2019 Aug 23;16(17):3055. doi: 10.3390/ijerph16173055.

Abstract

Recent studies of unconventional resource development (URD) and adverse health effects have been limited by distance-based exposure surrogates. Our study compared exposure classifications between air pollutant concentrations and "well activity" (WA) metrics, which are distance-based exposure proxies used in Marcellus-area studies to reflect variation in time and space of residential URD activity. We compiled Pennsylvania air monitoring data for benzene, carbon monoxide, nitrogen dioxide, ozone, fine particulates and sulfur dioxide, and combined this with data on nearly 9000 Pennsylvania wells. We replicated WA calculations using geo-coordinates of monitors to represent residences and compared exposure categories from air measurements and WA at the site of each monitor. There was little agreement between the two methods for the pollutants included in the analysis, with most weighted kappa coefficients between -0.1 and 0.1. The exposure categories agreed for about 25% of the observations and assigned inverse categories 16%-29% of the time, depending on the pollutant. Our results indicate that WA measures did not adequately distinguish categories of air pollutant exposures and employing them in epidemiology studies can result in misclassification of exposure. This underscores the need for more robust exposure assessment in future analyses and cautious interpretation of these existing studies.

摘要

最近对非常规资源开发 (URD) 和不良健康影响的研究受到基于距离的暴露替代物的限制。我们的研究比较了空气污染物浓度和“井活动”(WA)指标之间的暴露分类,WA 是马塞勒斯地区研究中用于反映住宅 URD 活动时间和空间变化的基于距离的暴露替代物。我们编制了宾夕法尼亚州的苯、一氧化碳、二氧化氮、臭氧、细颗粒物和二氧化硫的空气监测数据,并将其与近 9000 口宾夕法尼亚州油井的数据相结合。我们使用监测器的地理坐标复制了 WA 计算,以代表住宅,并比较了每个监测器位置的空气测量和 WA 的暴露类别。在分析中包含的污染物中,两种方法之间的一致性很小,大多数加权 kappa 系数在-0.1 到 0.1 之间。暴露类别在大约 25%的观察中是一致的,并且根据污染物,反类别在 16%-29%的时间内被分配。我们的结果表明,WA 测量并不能充分区分空气污染物暴露类别,在流行病学研究中使用它们可能导致暴露的错误分类。这突显了在未来分析中需要更强大的暴露评估,并对这些现有研究进行谨慎解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e5d/6747456/666729966eb4/ijerph-16-03055-g001.jpg

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