Linking metal (Pb, Hg, Cd) industrial air pollution risk to blood metal levels and cardiovascular functioning and structure among children in Syracuse, NY

Background: 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.

Objectives: 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.

Methods: 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.

Results: 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.

Discussion: 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.