268222 Impact of environmental chemicals, sociodemographic variables, depression, and clinical indicators of health and nutrition on self-reported health status

Monday, October 29, 2012 : 11:10 AM - 11:30 AM

Alissa Cordner , Sociology Department, Brown University, Providence, RI
Tim Wade , National Health and Environmental Effects Research Laboratory, US Environmental Protection Agency, Research Triangle Park, NC
Elaine Cohen Hubal , National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC
Edward E. Hudgens , National Health Effects Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC
Stephen W. Edwards , National Health Effects Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC
Jane E. Gallagher , National Health Effects Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC
Public health researchers ideally integrate social, environmental, and clinical measures to identify predictors of poor health. Chemicals measured in human tissues are often evaluated in relation to intangible or rare health outcomes, or are studied one chemical at a time. Using US nationally representative data from the 2003-2004 NHANES survey, this research evaluated whether self-reported health status (fair/poor or good/very good/excellent) was a reasonable proxy for health status by assessing bivariate associations between self reported health and obesity, depression, and hypertension for adults ages 20-50. Statistically significant (p-value <0.005) relationships were observed for all but hypertension (p-value <0.2). Self reported health status was then analyzed in relation to biomonitored chemicals (mercury, lead and cadmium, toluene, benzene, and cotinine), clinical indicators (C-reactive protein and glycohemoglobin), nutritional markers (vitamin D and phytoflurene), race, gender, income, and educational attainment. In unadjusted logistic regression models, chemical levels and clinical indicators of health risk were statistically significant predictors of self-reported health. After adjusting for sociodemographic variables using multivariate logistic regression, some associations were no longer statistically significant. Family income (p-value <0.001), age (p-value <0.001), education (p-value <0.001), Body Mass Index (p-value <0.005), depression (p-value <0.001), and being a current smoker (p-value <0.05) remained statistically significant predictors of poor self-reported health. Additional models investigate the impact of combined chemical exposures on self-reported health. This research moves beyond linking single chemical exposures to single health outcomes, to provide a more comprehensive understanding of the complex relationships between cumulative environmental exposures, clinical indicators, and socioeconomic determinates. This abstract does not necessarily represent EPA policy.

Learning Areas:
Environmental health sciences
Public health or related research
Social and behavioral sciences

Learning Objectives:
Describe the relationship between self-reported health status and multiple clinical measures of health. Compare methods of modeling exposure to a single chemical, multiple chemicals, or cumulative chemical exposure.

Keywords: Health Risks, Environmental Health

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a PhD candidate in the sociology department at Brown University studying environmental health, environmental sociology, and policy and regulation.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.