Consumer exposure to parabens within cosmetics compared with population-scale urinary biomarkers

Abstract

Background The US National Health and Nutrition Examination Survey (NHANES) measures population-scale urinary biomarkers of many chemicals, for example parabens, which are often used in US cosmetics and may be harmful. Aims We aim to develop methods to consistently predict cosmetic chemical exposure and corroborate these predictions with urinary biomarkers. Methods A potential dose of several parabens, i.e., Dex [g-chemical/kg-bodyweight/day-of-use] is estimated by considering the fractions of chemical within and across cosmetics, the mass of cosmetic applied (e.g. ~4.5 g/day of lotion), and the product intake fraction calculated based on skin permeation of the chemical. Tests are performed to compare Dex with NHANES urinary biomarker data with and without considering the fraction excreted through urine (fue). Results When dose is adjusted by using the fraction of cosmetic products that typically contain each respective paraben, Dex_adj , it correlates well with urinary biomarkers for the 95th percentile of tested women (R2 = 0.99, n = 4). For instance, methylparaben is the most commonly used paraben in cosmetics and the highest concentration in urine. This correlation, however, does not provide absolute dose values. When fue is applied as a correction factor to back-calculate dose from the population geomean urinary biomarker data, it correlates well (R2 = 0.92, n=4) to Dex_adj and approaches the 1:1 line. Likewise, when the fue is applied as a correction factor to Dex_adj, the correlation with the general population’s geomean urinary levels remains high (R2=0.72, n=4), and the equation approaches the 1:1 line. Conclusions The fraction of cosmetics on the market containing a given chemical is important to understand population-scale exposure, especially for high-end users (95th percentile for women). When estimates of exposure are combined with estimates of urinary excretion fractions, doses for high-end consumers may be better estimated and are correlated well with general population NHANES urinary biomarker data.