Consumer product chemical weight fractions from ingredient lists
Consumer product chemical weight fractions from ingredient lists
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DOI：
10.1038/jes.2017.29
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发表时间：
2018-05-01
影响因子：
4.5
通讯作者：
Price, Paul S.
中科院分区：
文献类型：
--
作者：
Isaacs, Kristin K.;Phillips, Katherine A.;Price, Paul S.
评估人类对消费品中化学品的接触需要成分信息。然而，商业产品的全面成分数据通常不可用。许多消费品都报告了使用特定指南构建的成分列表。开发了一种概率模型来估计定量重量分数（WF）值，这些值与列表中成分的排名、报告成分的数量和标签规则一致。该模型提供了任何长度列表中任何等级成分的平均值、中位数和95%置信上限和下限WF。与材料安全数据表上报告的相比，该模型预测的工作流有利。对已知在产品中提供特定功能的化学品的预测也被认为与报告的WF合理一致。该模型被应用到选择公开的成分列表，从而估计在81个产品类别的1123种产品中的1293种独特成分的WF。预测的WF虽然不如报告的值精确，但可以对大量的产品-化学品组合进行估计，从而为高通量或筛选水平的暴露评估提供有用的数据来源。
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.