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  • Title: Inter- and intra-individual variation in urinary biomarker concentrations over a 6-day sampling period. Part 2: personal care product ingredients.
    Author: Koch HM, Aylward LL, Hays SM, Smolders R, Moos RK, Cocker J, Jones K, Warren N, Levy L, Bevan R.
    Journal: Toxicol Lett; 2014 Dec 01; 231(2):261-9. PubMed ID: 24956590.
    Abstract:
    An intensive study was conducted to provide data on intra- and inter-individual variation in urinary excretion of a series of ingredients in personal care products (parabens, triclosan, benzophenones) and bisphenol A (BPA, not expected to be an ingredient) in 8 volunteers over 6 days. Exposure diaries recorded use of personal care products with identified target analytes as ingredients. Participants' usual products were replaced with products without the target analytes for 2 of the 6 days. Urine void volumes and times were recorded. Methyl, ethyl, and n-propylparabens, triclosan, benzophenone-3, and BPA were frequently detected (≥70% of samples). Urinary concentrations of the parabens and triclosan were lower on product replacement days. First morning void concentrations correlated moderately to highly with 24-h composite concentrations for all analytes. Intraclass correlation coefficients (ICCs) for spot samples collected on days with usual product use were low for BPA (0.15), moderate for n-propylparaben and methylparaben (0.39 and 0.56, respectively), and high for ethylparaben, benzophenone-3, and triclosan (0.76, 0.81, and 0.934, respectively); ICCs were consistently higher on the basis of cr-adjusted concentrations. Hydration status adjustment methods were assessed by comparing unadjusted and adjusted concentrations to urinary excretion rates (ER, ng/kg-h) for all analytes and samples. Specific gravity-adjusted concentrations correlated slightly better with ER than creatinine-adjusted concentrations. Within-individual variation in biomarker concentrations was highest for methyl and ethylparabens (2 orders of magnitude variation in spot sample concentrations) and lower for the other analytes (1-1.5 orders of magnitude). This dataset provides insight into the design and interpretation of urinary biomonitoring studies for non-persistent chemicals.
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