A Method for Identifying Prevalent Chemical Combinations in the U.S. Population
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 chemic...
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Veröffentlicht in: | Environmental health perspectives 2017-08, Vol.125 (8), p.087017 |
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creator | Kapraun, Dustin F Wambaugh, John F Ring, Caroline L Tornero-Velez, Rogelio Setzer, R Woodrow |
description | 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.
We seek to develop and demonstrate a method for identifying those mixtures that are most prevalent in humans.
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.
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.
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. |
doi_str_mv | 10.1289/EHP1265 |
format | Article |
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We seek to develop and demonstrate a method for identifying those mixtures that are most prevalent in humans.
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.
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.
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.</description><identifier>ISSN: 0091-6765</identifier><identifier>EISSN: 1552-9924</identifier><identifier>DOI: 10.1289/EHP1265</identifier><identifier>PMID: 28858827</identifier><language>eng</language><publisher>United States: National Institute of Environmental Health Sciences</publisher><subject>Acids ; Arsenic ; Biomarkers ; Biomonitoring ; Chemicals ; Consumer products ; Councils ; Data Mining ; Data processing ; Datasets ; Disease control ; Dosimetry ; Environmental Exposure ; Environmental Monitoring - methods ; Environmental Pollutants - analysis ; Environmental protection ; ENVIRONMENTAL SCIENCES ; Hazardous materials ; Humans ; Medical laboratories ; Metabolites ; Nutrition ; Nutrition Surveys ; Pollutants ; Population ; Risk assessment ; Toxicity ; United States ; Urine</subject><ispartof>Environmental health perspectives, 2017-08, Vol.125 (8), p.087017</ispartof><rights>Copyright National Institute of Environmental Health Sciences Aug 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c424t-273fc3bc9fd5ce151cdc166efd6425927ba1df916ca12ddd04a1e9dd67f7dbd83</citedby><cites>FETCH-LOGICAL-c424t-273fc3bc9fd5ce151cdc166efd6425927ba1df916ca12ddd04a1e9dd67f7dbd83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801475/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801475/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28858827$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/servlets/purl/1494692$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Kapraun, Dustin F</creatorcontrib><creatorcontrib>Wambaugh, John F</creatorcontrib><creatorcontrib>Ring, Caroline L</creatorcontrib><creatorcontrib>Tornero-Velez, Rogelio</creatorcontrib><creatorcontrib>Setzer, R Woodrow</creatorcontrib><creatorcontrib>Oak Ridge Inst. for Science and Education (ORISE), Oak Ridge, TN (United States)</creatorcontrib><title>A Method for Identifying Prevalent Chemical Combinations in the U.S. Population</title><title>Environmental health perspectives</title><addtitle>Environ Health Perspect</addtitle><description>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.
We seek to develop and demonstrate a method for identifying those mixtures that are most prevalent in humans.
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.
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.
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.</description><subject>Acids</subject><subject>Arsenic</subject><subject>Biomarkers</subject><subject>Biomonitoring</subject><subject>Chemicals</subject><subject>Consumer products</subject><subject>Councils</subject><subject>Data Mining</subject><subject>Data processing</subject><subject>Datasets</subject><subject>Disease control</subject><subject>Dosimetry</subject><subject>Environmental Exposure</subject><subject>Environmental Monitoring - methods</subject><subject>Environmental Pollutants - analysis</subject><subject>Environmental protection</subject><subject>ENVIRONMENTAL SCIENCES</subject><subject>Hazardous materials</subject><subject>Humans</subject><subject>Medical 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perspectives</jtitle><addtitle>Environ Health Perspect</addtitle><date>2017-08-24</date><risdate>2017</risdate><volume>125</volume><issue>8</issue><spage>087017</spage><pages>087017-</pages><issn>0091-6765</issn><eissn>1552-9924</eissn><abstract>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.
We seek to develop and demonstrate a method for identifying those mixtures that are most prevalent in humans.
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.
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.
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.</abstract><cop>United States</cop><pub>National Institute of Environmental Health Sciences</pub><pmid>28858827</pmid><doi>10.1289/EHP1265</doi><oa>free_for_read</oa></addata></record> |
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source | Jstor Complete Legacy; MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; PubMed Central Open Access |
subjects | Acids Arsenic Biomarkers Biomonitoring Chemicals Consumer products Councils Data Mining Data processing Datasets Disease control Dosimetry Environmental Exposure Environmental Monitoring - methods Environmental Pollutants - analysis Environmental protection ENVIRONMENTAL SCIENCES Hazardous materials Humans Medical laboratories Metabolites Nutrition Nutrition Surveys Pollutants Population Risk assessment Toxicity United States Urine |
title | A Method for Identifying Prevalent Chemical Combinations in the U.S. Population |
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