Title: A Method for Identifying Prevalent Chemical Combinations in the U.S. Population

Abstract

Background: Through the food and water they ingest, the air they breathe, and the consumer products with which they interact at home and at work, humans are exposed to tens of thousands of chemicals, many of which have not been evaluated to determine their potential toxicities. Furthermore, while current chemical testing tends to focus on individual chemicals, the exposures that people actually experience involve mixtures of chemicals. Unfortunately, the number of mixtures that can be formed from the thousands of environmental chemicals is enormous, and testing all of them would be impossible. Objectives: We seek to develop and demonstrate a method for identifying those mixtures that are most prevalent in humans. Methods: We applied frequent itemset mining, a technique traditionally used for market basket analysis, to biomonitoring data from the 2009–2010 cycle of the continuous National Health and Nutrition Examination Survey (NHANES) to identify combinations of chemicals that frequently co-occur in people. Results: We identified 90 chemical combinations consisting of relatively few chemicals that occur in at least 30% of the U.S. population, as well as three supercombinations consisting of relatively many chemicals that occur in a small but nonnegligible proportion of the U.S. population. Conclusions: We demonstrated how FIMmore » can be used in conjunction with biomonitoring data to narrow a large number of possible chemical combinations down to a smaller set of prevalent chemical combinations. https://doi.org/10.1289/EHP1265« less

Authors:

Kapraun, Dustin F. ^[1]; Wambaugh, John F. ^[1]; Ring, Caroline L. ^[2]; Tornero-Velez, Rogelio ^[1]; Setzer, R. Woodrow ^[1]

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+ Show Author Affiliations

1. U.S. Environmental Protection Agency, Research Triangle Park, NC (United States). National Center for Computational Toxicology
2. U.S. Environmental Protection Agency, Research Triangle Park, NC (United States). National Center for Computational Toxicology; Oak Ridge Inst. for Science and Education (ORISE), Oak Ridge, TN (United States)

Publication Date:

Thu Aug 24 00:00:00 EDT 2017

Research Org.:

Oak Ridge Inst. for Science and Education (ORISE), Oak Ridge, TN (United States)

Sponsoring Org.:

USDOE

OSTI Identifier:

1494692

Resource Type:

Accepted Manuscript

Journal Name:

Environmental Health Perspectives

Additional Journal Information:

Journal Volume: 125; Journal Issue: 8; Journal ID: ISSN 0091-6765

Publisher:

National Institute of Environmental Health Sciences

Country of Publication:

United States

Language:

English

Subject:

54 ENVIRONMENTAL SCIENCES