Consumer product chemical weight fractions from ingredient lists.

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 prod

SUBMITTER: Isaacs KK 

PROVIDER: S-EPMC6082127 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature