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A Method for Identifying Prevalent Chemical Combinations in the U.S. Population
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 cu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Environmental Health Perspectives
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801475/ https://www.ncbi.nlm.nih.gov/pubmed/28858827 http://dx.doi.org/10.1289/EHP1265 |
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author | Kapraun, Dustin F. Wambaugh, John F. Ring, Caroline L. Tornero-Velez, Rogelio Setzer, R. Woodrow |
author_facet | Kapraun, Dustin F. Wambaugh, John F. Ring, Caroline L. Tornero-Velez, Rogelio Setzer, R. Woodrow |
author_sort | Kapraun, Dustin F. |
collection | PubMed |
description | 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 FIM 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 |
format | Online Article Text |
id | pubmed-5801475 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Environmental Health Perspectives |
record_format | MEDLINE/PubMed |
spelling | pubmed-58014752018-03-15 A Method for Identifying Prevalent Chemical Combinations in the U.S. Population Kapraun, Dustin F. Wambaugh, John F. Ring, Caroline L. Tornero-Velez, Rogelio Setzer, R. Woodrow Environ Health Perspect Research 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 FIM 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 Environmental Health Perspectives 2017-08-24 /pmc/articles/PMC5801475/ /pubmed/28858827 http://dx.doi.org/10.1289/EHP1265 Text en EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted. |
spellingShingle | Research Kapraun, Dustin F. Wambaugh, John F. Ring, Caroline L. Tornero-Velez, Rogelio Setzer, R. Woodrow A Method for Identifying Prevalent Chemical Combinations in the U.S. Population |
title | A Method for Identifying Prevalent Chemical Combinations in the U.S. Population |
title_full | A Method for Identifying Prevalent Chemical Combinations in the U.S. Population |
title_fullStr | A Method for Identifying Prevalent Chemical Combinations in the U.S. Population |
title_full_unstemmed | A Method for Identifying Prevalent Chemical Combinations in the U.S. Population |
title_short | A Method for Identifying Prevalent Chemical Combinations in the U.S. Population |
title_sort | method for identifying prevalent chemical combinations in the u.s. population |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801475/ https://www.ncbi.nlm.nih.gov/pubmed/28858827 http://dx.doi.org/10.1289/EHP1265 |
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