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Data Mining Approaches for Assessing Chemical Coexposures Using Consumer Product Purchase Data
Citation:
Tornero-Velez, R., K. Isaacs, K. Dionisio, S. Prince, H. Laws, M. Nye, P. Price, AND T. Buckley. Data Mining Approaches for Assessing Chemical Coexposures Using Consumer Product Purchase Data. RISK ANALYSIS. Blackwell Publishing, Malden, MA, 41(9):1716-1735, (2021). https://doi.org/10.1111/risa.13650
Impact/Purpose:
Here we show the feasibility of use of purchasing data to identify likely differences in product use by demographics (including concurrent product use assumed from cooccurrence of product purchases).
Description:
The use of consumer products presents a potential for chemical exposures to humans. Toxicity testing and exposure models are routinely employed to estimate risks from their use; however, a key challenge is the sparseness of information concerning who uses products and which products are used contemporaneously. Our goal was to demonstrate a method to infer use patterns by way of purchase data. We examined purchase patterns for three types of personal care products (cosmetics, hair care, and skin care) and two household care products (household cleaners and laundry supplies) using data from 60,000 households collected over a one-year period in 2012. The market basket analysis methodology frequent itemset mining (FIM) was used to identify co-occurring sets of product purchases for all households and demographic groups based on income, education, race/ethnicity, and family composition. Our methodology captured robust co-occurrence patterns for personal and household products, globally and for different demographic groups. FIM identified cosmetic co-occurrence patterns captured in prior surveys of cosmetic use, as well as a trend of increased diversity of cosmetic purchases as children mature to teenage years. We propose that consumer product purchase data can be mined to inform person-oriented use patterns for high-throughput chemical screening applications, for aggregate and combined chemical risk evaluations.
URLs/Downloads:
DOI: Data Mining Approaches for Assessing Chemical Coexposures Using Consumer Product Purchase Data
https://pubmed.ncbi.nlm.nih.gov/33331033/