Datasets associated with "Mining of Consumer Product and Purchasing Data to Identify Potential Chemical Co-exposures"
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ScienceHub_FIMofNielsenAndCPCat_2020-06-03.xlsx
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "020:00" ] |
| contactPoint |
{ "fn": "Kristin Isaacs", "hasEmail": "mailto:isaacs.kristin@epa.gov" } |
| description | 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). |
| distribution |
[ { "title": "ScienceHub_FIMofNielsenAndCPCat_2020-06-03.xlsx", "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1519316/ScienceHub_FIMofNielsenAndCPCat_2020-06-03.xlsx" } ] |
| identifier | https://doi.org/10.23719/1519316 |
| keyword |
[ "Aggregate exposure", "ExpoCast", "chemical exposure", "consumer products", "frequent itemset mining (FIM)" ] |
| license | https://pasteur.epa.gov/license/sciencehub-license.html |
| modified | 2021-06-10 |
| programCode |
[ "020:095" ] |
| publisher |
{ "name": "U.S. EPA Office of Research and Development (ORD)", "subOrganizationOf": { "name": "U.S. Environmental Protection Agency", "subOrganizationOf": { "name": "U.S. Government" } } } |
| references |
[ "https://doi.org/10.1289/ehp8610" ] |
| rights |
null
|
| title | Datasets associated with "Mining of Consumer Product and Purchasing Data to Identify Potential Chemical Co-exposures" |