Consumer product chemical weight fractions from ingredient lists

J Expo Sci Environ Epidemiol. 2018 May;28(3):216-222. doi: 10.1038/jes.2017.29. Epub 2017 Nov 8.

Abstract

Assessing human exposures to chemicals in consumer products requires composition information. However, comprehensive composition data for products in commerce are not generally available. Many consumer products have reported ingredient lists that are constructed using specific guidelines. A probabilistic model was developed to estimate quantitative weight fraction (WF) values that are consistent with the rank of an ingredient in the list, the number of reported ingredients, and labeling rules. The model provides the mean, median, and 95% upper and lower confidence limit WFs for ingredients of any rank in lists of any length. WFs predicted by the model compared favorably with those reported on Material Safety Data Sheets. Predictions for chemicals known to provide specific functions in products were also found to reasonably agree with reported WFs. The model was applied to a selection of publicly available ingredient lists, thereby estimating WFs for 1293 unique ingredients in 1123 products in 81 product categories. Predicted WFs, although less precise than reported values, can be estimated for large numbers of product-chemical combinations and thus provide a useful source of data for high-throughput or screening-level exposure assessments.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Consumer Product Safety
  • Environmental Exposure / analysis*
  • Humans
  • Inorganic Chemicals / analysis*
  • Material Safety Data Sheets
  • Models, Statistical
  • Monte Carlo Method
  • Organic Chemicals / analysis*
  • Product Labeling*
  • Risk Assessment / methods*
  • United States
  • United States Food and Drug Administration

Substances

  • Inorganic Chemicals
  • Organic Chemicals