Impact/Purpose:

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.

Description:

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.

URLs/Downloads:

2010 Progress Report

Record Details:

Record Type:PROJECT( ABSTRACT )

Start Date:06/01/2010

Completion Date:05/31/2014

Record ID: 248939

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Related Organizations:

Role :OWNER

Organization Name :UNIVERSITY OF NORTH CAROLINA

Mailing Address :103 S Bldg Cb 9100

Citation :Chapel Hill

State :NC

Zip Code :27599



Role :OWNER

Organization Name :UNIVERSITY OF TEXAS SCHOOL OF PUBLIC HEALTH

Mailing Address :P.O. Box 20036

Citation :Houston

State :TX

Zip Code :77225



Role :OWNER

Organization Name :UNIVERSITY OF TEXAS MEDICAL BRANCH - GALVESTON

Mailing Address :301 University Blvd

Citation :Galveston

State :TX

Zip Code :77550

Project Information:

Approach :

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.

Cost :$555,923.00

Research Component :Health Effects

Project IDs:

ID Code :R834580

Project type :EPA Grant