Analytical Strategies for Assessing Cumulative Effects of Chemical and Nonchemical StressorsEPA Grant Number: R834580
Title: Analytical Strategies for Assessing Cumulative Effects of Chemical and Nonchemical Stressors
Investigators: Lai, Dejian , Linder, Stephen H. , Marko, Dritana , Sexton, Ken , Peek, M. Kristin , Cutchin, Malcolm , Stowe, Raymond
Current Investigators: Lai, Dejian , Linder, Stephen H. , Sexton, Ken , Peek, M. Kristin , Cutchin, Malcolm , Stowe, Raymond
Institution: The University of Texas School of Public Health , University of North Carolina at Chapel Hill , The University of Texas Medical Branch - Galveston
Current Institution: The University of Texas at Houston , Microgen LLC , The University of Texas Medical Branch - Galveston , The University of Texas at Austin , University of Minnesota , University of North Carolina at Chapel Hill
EPA Project Officer: Hahn, Intaek
Project Period: June 1, 2010 through May 31, 2014 (Extended to May 31, 2015)
Project Amount: $555,923
RFA: Understanding the Role of Nonchemical Stressors and Developing Analytic Methods for Cumulative Risk Assessments (2009) RFA Text | Recipients Lists
Research Category: Human Health
The project will assess the relative impact of community-level and individual-level stressors – including multiple chemical, social and psychosocial stressors -- on biologic markers of health effects across neighborhoods and vulnerable populations in Texas City, Texas and will employ these findings in a cumulative risk assessment.
We will examine how the spatial distribution of ambient chemical exposures across neighborhoods interacts with nonchemical stressors at both the neighborhood and individual levels to account for differences in adverse cumulative health effects. These adverse effects will be represented by biologic markers of allostatic load, cardiovascular risk, hormonal stress response, inflammation and organ dysfunction. From the quantification of these effects, we will construct a procedure for assigning cumulative risk estimates to different groups and neighborhoods.
The extensive set of measures for this study are drawn from an existing database, a randomized sample of individual and neighborhood characteristics collected for the Texas City Stress and Health Project, originating at the Center for Population Health and Health Disparities at the University of Texas Medical Branch (UTMB) in Galveston, Texas. The modeling of relationships for this project involves a complex family of statistical methods known as generalized linear latent and mixed models (GLLAMM), drawn principally from the social sciences and new to this area of investigation. The key assumption is that the true (or latent) variables are measured with error by multiple empirical indicators. The mixed aspect includes random and fixed coefficients, permitting cross-level analysis for causal pathways between individual and neighborhood stressors. The model’s parameter estimates then form the basis for the formation of risk profiles.
Our model incorporates a wide range of chemical and non-chemical stressors at the neighborhood and individual levels, with the biologic indicators of the possible physical pathways that these stressors might take in generating health disparities. This approach will quantify the direct and indirect effects of stressors and specify how these interact to have adverse biologic effects on disadvantaged populations. These linkages have not been examined in this way before and should advance the study of stressors and cumulative risk. These quantitative results will provide an empirical foundation for accommodating cumulative risks in conventional risk assessment procedures.