Bibliographic Details
| Title: |
Opportunities and Challenges for Dietary Arsenic Intervention. |
| Authors: |
Nachman, Keeve E.1,2,3,4 knachman@jhu.edu, Punshon, Tracy5,6,7, Rardin, Laurie6, Signes-Pastor, Antonio J.6,7,8, Murray, Carolyn J.7, Jackson, Brian P.6,9, Guerinot, Mary Lou5, Burke, Thomas A.1,3, Chen, Celia Y.5,6, Ahsan, Habibul10, Argos, Maria11, Cottingham, Kathryn L.5,7, Cubadda, Francesco12, Ginsberg, Gary L.13, Goodale, Britton C.6,14, Kurzius-Spencer, Margaret15,16, Meharg, Andrew A.17, Miller, Mark D.18, Nigra, Anne E.19, Pendergrast, Claire B.20 |
| Source: |
Environmental Health Perspectives. Aug2018, Vol. 126 Issue 8, p1-6. 6p. 1 Chart. |
| Subject Terms: |
*Arsenic, *Public health, Diet |
| Abstract: |
The diet is emerging as the dominant source of arsenic exposure for most of the U.S. population. Despite this, limited regulatory efforts have been aimed at mitigating exposure, and the role of diet in arsenic exposure and disease processes remains understudied. In this brief, we discuss the evidence linking dietary arsenic intake to human disease and discuss challenges associated with exposure characterization and efforts to quantify risks. In light of these challenges, and in recognition of the potential longer-term process of establishing regulation, we introduce a framework for shorter-term interventions that employs a field-to-plate food supply chain model to identify monitoring, intervention, and communication opportunities as part of a multisector, multiagency, science-informed, public health systems approach to mitigation of dietary arsenic exposure. Such an approach is dependent on coordination across commodity producers, the food industry, nongovernmental organizations, health professionals, researchers, and the regulatory community. [ABSTRACT FROM AUTHOR] |
|
Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
GreenFILE |