The Chemical Mixture Methodology (CMM) is used for an emergency response and safety planning for chemical mixtures that cause irreversible or serious health effects. There are three major components of the CMM: Health Code Numbers (HCNs), the Hazard Index, and the Protective Action Criteria values. The HCNs are akin to medical diagnostic codes; they categorize the adverse health outcome that could be induced by exposure to an individual hazardous chemical. Currently, 60 HCNs are used in the CMM to characterize potential health effects for over 3,000 chemicals. Chemicals may have one or more HCNs; however, a maximum of 10 HCNs may be listed in the CMM dataset for each chemical. The HCNs for each chemical are ranked based on their seriousness and the impact of the health effect on a person’s ability to take protective action, with the most serious being included in the CMM. Many chemicals in the CMM dataset have 10 HCNs. This study explored how CMM results would vary if an additional five HCNs were allowed, if needed, for each chemical. A total of 361 common chemicals from the CMM dataset were updated to include up to five additional HCNs. To evaluate the 15-HCN approach, we used 127 test mixtures and each mixture was assessed using three different concentration distributions. This provided a total of 381 test cases in our assessment. Comparing results using the 15-HCN approach to those using the 10-HCN approach, showed no substantial difference in CMM results. This suggests that it may not be necessary to include more HCNs in the CMM dataset. The CMM team continues to update the CMM to support its many users in the United States and around the world. For further information on the CMM, visit http://orise.orau.gov/emi/scapa/chem-mixture-methodolgy/default.htm.


Xiao-Ying Yu

Lab site

Pacific Northwest National Laboratory (PNNL)

Funding Acknowledgement

This material is based upon work supported by the S.D. Bechtel, Jr. Foundation and by the National Science Foundation under Grant No. 0952013. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the S.D. Bechtel, Jr. Foundation or the National Science Foundation. This project has also been made possible with support of the National Marine Sanctuary Foundation. The STAR program is administered by the Cal Poly Center for Excellence in Science and Mathematics Education (CESaME) on behalf of the California State University (CSU).



URL: https://digitalcommons.calpoly.edu/star/302


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