Analysis of consumer behavior for the estimation of the exposure to chemicals in personal care products

In this study, the main objective was to implement an integrative modelling framework in order to support the prioritization and screening of chemicals present in personal care products (PCPs) regarding their potential to expose users across multiple possible pathways. Here, we implemented an exposure-based framework based on product intake fractions (PiFs) calculated using a two-compartment model reproducing the skin uptake and the competing volatilization of chemicals applied on skin during PCP use. The implemented framework enabled to simultaneously and comprehensively accommodate coupled chemical specific parameters (i.e. physical and chemical properties of the candidate chemicals), exposure information specific for product-chemical combinations, and survey data informing on consumer behavior. A case-study, based on the usage pattern data of 22 PCPs investigated among Swiss individuals (Garcia-Hidalgo et al., 2017a) and 113 candidate chemicals chosen for their suspected presence in the PCP categories of interest was defined to evaluate the applicability of the framework. Nonnegative matrix factorization (NMF) and hierarchical clustering were subsequently applied to identify chemicals with the highest exposure potential and to highlight most relevant mixtures of chemicals on the basis of the specific usage patterns of the considered survey individuals.