Mining of Consumer Product Ingredient and Purchasing Data to Identify Potential Chemical Coexposures.

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From: Environmental Health Perspectives(Vol. 129, Issue 6)
Publisher: National Institute of Environmental Health Sciences
Document Type: Report
Length: 10,157 words
Lexile Measure: 1560L

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Abstract :

Background: Chemicals in consumer products are a major contributor to human chemical coexposures. Consumers purchase and use a wide variety of products containing potentially thousands of chemicals. There is a need to identify potential real-world chemical coexposures to prioritize in vitro toxicity screening. However, due to the vast number of potential chemical combinations, this identification has been a major challenge. OBJECTIVES: We aimed to develop and implement a data-driven procedure for identifying prevalent chemical combinations to which humans are exposed through purchase and use of consumer products. METHODS: We applied frequent item set mining to an integrated data set linking consumer product chemical ingredient data with product purchasing data from 60,000 households to identify chemical combinations resulting from co-use of consumer products. Results: We identified co-occurrence patterns of chemicals over all households as well as those specific to demographic groups based on race/ethnicity, income, education, and family composition. We also identified chemicals with the highest potential for aggregate exposure by identifying chemicals occurring in multiple products used by the same household. Last, a case study of chemicals active in estrogen and androgen receptor in silico models revealed priority chemical combinations co-targeting receptors involved in important biological signaling pathways. Discussion: Integration and comprehensive analysis of household purchasing data and product-chemical information provided a means to assess human near-field exposure and inform selection of chemical combinations for high-throughput screening in in vitro assays. https://doi.org/10.1289/ EHP8610

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Gale Document Number: GALE|A667734655