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Accounting for the impact of short-term variations in the levels of trihalomethane in drinking water on exposure assessment for epidemiological purposes. Part II: Biological aspects

Journal of Exposure Science & Environmental Epidemiology volume 23, pages 60–66 (2013)Cite this article

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Abstract

The variability of trihalomethane (THM) levels in drinking water raises the question of whether or not short-term variations (within-day) should be accounted for when assessing exposure to contaminants suspected of being carcinogenic and reprotoxic agents. The purpose of this study was to determine the magnitude of the impact on predicted biological levels of THMs (internal doses) exerted by within-day variations of THMs in drinking water. A database extracted from a campaign in the Québec City distribution system served to produce 81, 79 and 64 concentration profiles for the three most abundant THMs, namely chloroform (TCM), dichlorobromomethane (DCBM) and chlorodibromomethane (CDBM), respectively. Using a physiologically based toxicokinetic modeling approach, we simulated exposures (1.5 l water per day and a 10-min shower) based on each of these profiles and predicted, for 2000 individuals (Monte-Carlo simulations), maximum blood concentrations (Cmax), areas under the time versus blood concentrations curve (24 h-AUCcv) and total absorbed doses (ADs). Three different hypotheses were tested: [A] assuming a constant THM concentration in water (e.g., mean value of a day); [B] accounting for within-day variations in THM levels; and [C] a worst-case scenario assuming within-day variations and showering while THM levels were maximal. For each exposure profile, exposure indicator and individual, we calculated the ratios of values obtained according to each hypothesis (e.g., CmaxB/CmaxA and CmaxC/CmaxA) and the values corresponding to the 5th and 95th percentiles of these ratios. The closer these percentiles are to the value of 1, the smaller the error associated with assuming constant THM concentrations rather than their actual variability. Results showed that the minimal gap between these percentiles was TCM–AD(B)/TCM–AD(A) (5th=0.91; 95th=1.09), whereas the maximal gap was CDBM–Cmax(C)/CDBM–Cmax(A) (5th=0.50; 95th=3.40). Overall, TCM and ADs were the less affected (TCM<DCBM<CDBM and AD<AUCcv<Cmax) when accounting for within-day variations in water levels.

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Acknowledgements

We acknowledge the Réseau de recherche en santé environnementale (Québec) for funding. We thank Tarik Sadik for conducting the sampling campaigns. We also thank Jérôme Lavoué for his advice and Ms Janet Brownlee for idiomatic corrections.

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Authors and Affiliations

  1. Département de santé environnementale et santé au travail, École de santé publique de l’Université de Montréal, Pavillon Marguerite Youville, C.P.6128 Succursale Centre-Ville, Montréal, Quebec H3C 3J7 Canada,

    Cyril Catto, Ginette Charest-Tardif & Robert Tardif

  2. École supérieure d’aménagement du territoire, Université Laval, Pavillon Félix-Antoine Savard, Québec, Quebec G1V0A6 Canada,

    Manuel Rodriguez

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  1. Cyril Catto
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Correspondence to Robert Tardif.

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Catto, C., Charest-Tardif, G., Rodriguez, M. et al. Accounting for the impact of short-term variations in the levels of trihalomethane in drinking water on exposure assessment for epidemiological purposes. Part II: Biological aspects. J Expo Sci Environ Epidemiol 23, 60–66 (2013). https://doi.org/10.1038/jes.2012.88

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