Impact/Purpose:

Arsenic exposure is associated with cancer, diabetes, cardiovascular and respiratory disease. Although most studies have focused on arsenic exposure through water, dietary sources are likely to be of greater importance in populations with low levels of arsenic in their drinking water. In addition, dietary protein, micronutrients and methyl donors such as folate influence the extent of arsenic methylation, and methylation of inorganic arsenic to monomethylarsonic acid (MMA) increases arsenic toxicity. Our objectives are to utilize existing and archived population-based questionnaire and biological data that describe food and water consumption histories to construct predictive models for urinary arsenic biomarkers that can then be used as indicators of arsenic exposure and health effect outcome.

Description:

This study will generate and validate arsenic exposure indicators based on diet over a range of drinking water arsenic concentrations and a health outcome indicator modeling the effect of diet on arsenic methylation. These indicators will provide a means of assessing the impact of the new EPA maximum contaminant level (MCL) for arsenic in drinking water of 10 ppb. In addition, the effect of Hispanic ethnicity on the dietary contribution of arsenic will be assessed. This information will assist the EPA in making further regulatory decisions regarding arsenic exposure limits and the media to be regulated.

Record Details:

Record Type:PROJECT( ABSTRACT )

Start Date:07/01/2008

Completion Date:06/30/2010

Record ID: 202933

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Related Organizations:

Role :OWNER

Organization Name :MEL AND ENID ZUCKERMAN COLLEGE OF PUBLIC HEALTH

Citation :Tucson

State :AZ

Zip Code :85721

Project Information:

Approach :

Our team has conducted several recent studies assessing arsenic exposure, including the National Human Exposure Assessment Survey (NHEXAS) in Arizona, the Arizona Border Survey (ABS), and the Binational Arsenic Exposure Study (BAsES) in Arizona and Sonora, Mexico. These studies include dietary diaries and analysis of household, well water, and urine samples for over 700 subjects. Using multivariate regression, we will generate prediction models for the contribution of diet, including individual food items, dietary protein, micronutrients and methyl donors, to three different arsenic biomarkers in urine (total arsenic, sum of inorganic arsenic and metabolites, and percent MMA). At a regional level, variability of the models by population characteristics such as background drinking water arsenic levels and ethnicity will be compared, including analysis of NHEXAS Region 5. As a final step, we will conduct an independent validation of the final predictive indicator models using a national archived database, the National Health and Nutrition Examination Survey (NHANES).

Cost :$499,999.00

Research Component :Health Effects

Project IDs:

ID Code :R833992

Project type :EPA Grant