Background: Chemicals in consumer products are a major contributor to human chemical co-exposures. Consumers purchase and use a wide variety of products containing potentially thousands of chemicals. There is a need to identify potential real-world chemical co-exposures in order to prioritize in vitro toxicity screening. However, due to the vast number of potential chemical combinations, this has been a major challenge.

Objectives: We aim 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 itemset mining on an integrated dataset linking consumer product chemical ingredient data with product purchasing data from sixty thousand 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. Lastly, 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.

This dataset is associated with the following publication: Stanfield, Z., C. Addington, K. Dionisio, D. Lyons, R. Tornero-Velez, K. Phillips, T. Buckley, and K. Isaacs. Mining of consumer product and purchasing data to identify potential chemical co-exposures.. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 129(6): N/A, (2021).