A Method for Identifying Prevalent Chemical Combinations in the U.S. Population
Dustin F Kapraun1, John F Wambaugh1, Caroline L Ring1,2
1National Center for Computational Toxicology, U.S. Environmental Protection Agency , Research Triangle Park, North Carolina, USA.
Environmental Health Perspectives
|September 1, 2017
Summary
Scientists used market basket analysis to find common chemical mixtures in people. This method identifies prevalent chemical combinations in the U.S. population from biomonitoring data.
Area of Science:
- Environmental health
- Toxicology
- Data mining
Background:
- Humans are exposed to numerous unassessed chemicals via food, water, air, and consumer products.
- Current toxicological testing often examines single chemicals, not real-world mixtures.
- The vast number of potential chemical mixtures makes comprehensive testing infeasible.
Purpose of the Study:
- To develop and demonstrate a method for identifying prevalent chemical mixtures in humans.
- To address the challenge of assessing toxicity from complex chemical exposures.
Main Methods:
- Applied frequent itemset mining (FIM), a market basket analysis technique.
- Utilized biomonitoring data from the National Health and Nutrition Examination Survey (NHANES) 2009-2010.
- Identified co-occurring chemical combinations within the U.S. population.
Main Results:
- Identified 90 common chemical combinations found in at least 30% of the U.S. population.
- Discovered three 'supercombinations' of numerous chemicals present in a smaller population segment.
- Demonstrated the ability of FIM to prioritize prevalent chemical mixtures.
Conclusions:
- Frequent itemset mining effectively narrows down vast numbers of chemical combinations to prevalent ones.
- This approach aids in understanding human exposure to complex chemical mixtures.
- The study provides a scalable method for prioritizing chemical mixtures for toxicological assessment.
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