Effects-Based Cumulative Risk Assessment in a Low-Income Urban Community near a Superfund SiteEPA Grant Number: R834577
Title: Effects-Based Cumulative Risk Assessment in a Low-Income Urban Community near a Superfund Site
Investigators: Levy, Jonathan , Ezzati, Majid , French, Robert , Fuentes, Freddie , Hammitt, James K. , Korrick, Susan A. , Rosario, Maria , Sexton, Ken , Subramanian, S V
Current Investigators: Levy, Jonathan , Ayala, Arlene , Fabian, Maria Patricia , French, Robert , Korrick, Susan A. , Peters, Junenette , Pina, Jordan , Rosario, Maria
Institution: Boston University , Channing Laboratory , NorthStar Learning Centers
Current Institution: Boston University , NorthStar Learning Centers
EPA Project Officer: Hahn, Intaek
Project Period: September 1, 2010 through February 28, 2014 (Extended to February 28, 2015)
Project Amount: $749,662
RFA: Understanding the Role of Nonchemical Stressors and Developing Analytic Methods for Cumulative Risk Assessments (2009) RFA Text | Recipients Lists
Research Category: Health Effects , Human Health Risk Assessment , Health
The objective of our proposed study is to develop and apply novel statistical and analytical methods for cumulative risk assessment, focusing on a low-income community (New Bedford, MA) living near a Superfund site. We will focus on specific neurobehavioral and cardiovascular outcomes and consider contributions of multiple chemical stressors to these outcomes in the presence of significant non-chemical stressors.
For each health endpoint, we will develop multilevel models of exposures to multiple relevant chemical and non-chemical stressors in the New Bedford area, leveraging data from an ongoing birth cohort study and public databases to predict exposures as a function of individual and neighborhood characteristics. We will develop dose-response functions for all chemical stressors of interest, taking account of possible effect modification and synergistic or antagonistic effects, and will link these functions with baseline disease data and exposure models. The resulting health risk characterization will include geospatial and demographic variability as well as trends over time, and we will estimate relative contributions of chemical stressors to the burden of disease. The outputs of our models will be communicated to community partners in a manner that informs future studies or intervention strategies.
We will introduce into the cumulative risk assessment framework novel methods for non-cancer risk assessment, techniques for dose-response modeling that extend insights from chemical mixtures frameworks to non-chemical stressors, multilevel statistical methods used to address individual vs. contextual effects on both exposures and health outcomes, and methods used in global burden of disease and comparative risk assessment studies to attribute disease outcomes to multiple interacting factors and to consider time-varying trends. These methods can be extended to numerous pollutants and health outcomes and can allow for informative assessments of the population health implications of exposure to chemical stressors in the presence of relevant non-chemical stressors.