Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, United States.
Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States.
J Expo Sci Environ Epidemiol. 2019 Oct;29(6):842-851. doi: 10.1038/s41370-018-0079-0. Epub 2018 Oct 9.
Polychlorinated dibenzo-p-dioxin and dibenzofuran (PCDD/F) emissions from industrial sources contaminate the surrounding environment. Proximity-based exposure surrogates assume accuracy in the location of PCDD/F sources, but locations are not often verified. We manually reviewed locations (i.e., smokestack geo-coordinates) in a historical database of 4478 PCDD/F-emitting facilities in 2009 and 2016. Given potential changes in imagery and other resources over this period, we re-reviewed a random sample of 5% of facilities (n = 240) in 2016. Comparing the original and re-review of this sample, we evaluated agreement in verification (location confirmed or not) and distances between verified locations (verification error), overall and by facility type. Using the verified location from re-review as a gold standard, we estimated the accuracy of proximity-based exposure metrics and epidemiologic bias. Overall agreement in verification was high (>84%), and verification errors were small (median = 84 m) but varied by facility type. Accuracy of exposure classification (≥1 facility within 5 km) for a hypothetical study population also varied by facility type (sensitivity: 69-96%; specificity: 95-98%). Odds ratios were attenuated 11-69%, with the largest bias for rare facility types. We found good agreement between reviews of PCDD/F source locations, and that exposure prevalence and facility type may influence associations with exposures derived from this database. Our findings highlight the need to consider location error and other contextual factors when using proximity-based exposure metrics.
工业源排放的多氯二苯并对二恶英和多氯二苯并呋喃（PCDD/F）污染了周围环境。基于位置的暴露替代物假设 PCDD/F 源的位置是准确的，但位置并不经常得到验证。我们在 2009 年和 2016 年的 4478 个 PCDD/F 排放设施的历史数据库中手动审查了位置（即烟囱地理坐标）。考虑到在此期间图像和其他资源可能发生变化，我们在 2016 年重新审查了随机抽样的 5%的设施（n=240）。通过比较原始和重新审查的样本，我们评估了验证（位置是否确认）和确认位置之间距离（验证误差）的一致性，整体和按设施类型进行评估。使用重新审查的验证位置作为金标准，我们估计了基于位置的暴露指标和流行病学偏倚的准确性。验证的总体一致性很高（>84%），验证误差很小（中位数=84m），但因设施类型而异。对于一个假设的研究人群，暴露分类（距离<5km 内有≥1 个设施）的准确性也因设施类型而异（敏感性：69-96%；特异性：95-98%）。比值比衰减了 11-69%，稀有设施类型的偏差最大。我们发现 PCDD/F 源位置审查之间具有良好的一致性，并且暴露的普遍性和设施类型可能会影响从该数据库中得出的暴露相关性。我们的研究结果强调了在使用基于位置的暴露指标时需要考虑位置误差和其他背景因素。
