Graduate Program in Environmental Science, Center for Environmental Medicine and Informatics, SUNY College of Environmental Science and Forestry, Syracuse, NY 13210, USA.
Graduate Program in Environmental Science, Center for Environmental Medicine and Informatics, SUNY College of Environmental Science and Forestry, Syracuse, NY 13210, USA.
Environ Res. 2021 Feb;193:110557. doi: 10.1016/j.envres.2020.110557. Epub 2020 Dec 3.
Exposure to air pollution has been linked to individual health effects in occupational environments and communities proximate to air pollution sources. Use of estimated chemical concentrations from the Risk Screening Environmental Indicators (RSEI) model, derived from the Toxics Release Inventory, can help approximate some contributions to individual lifetime exposure to risk from air pollution and holds potential for linkages with specific health outcome data.
Our objectives were: (1) use regression modeling to test for associations between observed blood metal concentrations in children and RSEI total air concentrations of the same metals released from proximate manufacturing facilities; (2) determine the relative contribution of RSEI air pollution to blood metal concentrations; and (3) examine associations between chronic metal exposure and cardiovascular functioning and structure in study participants.
Using data synthesis methods and regression modeling we linked individual blood-based levels of lead, mercury, and cadmium(Pb, Hg, Cd) and cardiovascular functioning and structure to proximate industrial releases of the same metals captured by the Environmental Protection Agency's (EPA) RSEI geographic microdata.
We found that RSEI-derived ground-level ambient air concentrations of Hg and Cd were a significant predictor of blood metal levels, when controlling for covariates and other exposure variables. In addition to associations with blood metal findings, RSEI concentrations also predicted cardiovascular dysfunction and risk including changes in left-ventricular mass, blood pressure, and heart rate.
Right-to-know data, such as EPA's RSEI, can be linked to objective health outcomes, rather than simply serving as a non-specific risk estimate. These data can serve as a proxy for hazard exposure and should be used more widely to understand the dynamics of environmental exposure. Furthermore, since these data are both a product of and contribute to regulatory decision making, they could serve as an important link between disease risk and translation-orientated national environmental health policy.
暴露于空气污染与职业环境和接近空气污染源的社区中的个体健康影响有关。使用风险筛选环境指标 (RSEI) 模型估算的化学浓度，该模型源自有毒物质释放清单，有助于近似估算个体对空气污染的终生暴露风险，并且有可能与特定的健康结果数据相关联。
我们的目标是：(1) 使用回归模型测试从附近制造设施释放的相同金属的 RSEI 总空气浓度与儿童观察到的血液金属浓度之间的关联；(2) 确定 RSEI 空气污染对血液金属浓度的相对贡献；(3) 研究慢性金属暴露与研究参与者心血管功能和结构之间的关联。
使用数据综合方法和回归模型，我们将个体血液中的铅、汞和镉 (Pb、Hg、Cd) 水平与心血管功能和结构与环境保护署 (EPA) 的 RSEI 地理微观数据捕获的相同金属的附近工业排放联系起来。
我们发现，在控制协变量和其他暴露变量的情况下，RSEI 衍生的地面水平环境空气浓度 Hg 和 Cd 是血液金属水平的重要预测因子。除了与血液金属发现有关外，RSEI 浓度还预测了心血管功能障碍和风险，包括左心室质量、血压和心率的变化。
知情权数据，例如 EPA 的 RSEI，可以与客观健康结果相关联，而不仅仅是作为非特定风险估计。这些数据可以作为暴露危险的替代物，并应更广泛地用于了解环境暴露的动态。此外，由于这些数据既是监管决策的产物，也是其贡献者，因此它们可以成为疾病风险与面向翻译的国家环境健康政策之间的重要联系。
