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Estimating mouthing exposure to chemicals in children’s products

Abstract

Background

Existing models for estimating children’s exposure to chemicals through mouthing currently depends on the availability of chemical- and material-specific experimental migration rates, only covering a few dozen chemicals.

Objective

This study objective is hence to develop a mouthing exposure model to predict migration into saliva, mouthing exposure, and related health risk from a wide range of chemical-material combinations in children’s products.

Methods

We collected experimental data on chemical migration from different products into saliva for multiple substance groups and materials, identifying chemical concentration and diffusion coefficient as main properties of influence. To predict migration rates into saliva, we adapted a previously developed migration model for chemicals in food packaging materials. We also developed a regression model based on identified chemical and material properties.

Results

Our migration predictions correlate well with experimental data (R2 = 0.85) and vary widely from 8 × 10−7 to 32.7 µg/10 cm2/min, with plasticizers in PVC showing the highest values. Related mouthing exposure doses vary across chemicals and materials from a median of 0.005 to 253 µg/kgBW/d. Finally, we combined exposure estimates with toxicity information to yield hazard quotients and identify chemicals of concern for average and upper bound mouthing behavior scenarios.

Significance

The proposed model can be applied for predicting migration rates for hundreds of chemical-material combinations to support high-throughput screening.

Acknowledgements

This work was supported by the “Global Best Practices on Emerging Chemical Policy Issues of Concern under UN Environment’s Strategic Approach to International Chemicals Management (SAICM)” (GEF project ID 9771, grant no. S1-32GFL-000632), and by the “Safe and Efficient Chemistry by Design (SafeChem)” project funded by the Swedish Foundation for Strategic Environmental Research (grant no. DIA 2018/11).