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Do concentrations of pharmaceuticals in sewage reflect prescription figures?

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Abstract

In recent years, it has been demonstrated that sewage-based epidemiology can deliver interesting information on trends in illicit drug consumption. However, until now, no real evidence exists that the measured concentrations of drugs in sewage can be exactly correlated with the amounts of drugs used by a specific population. This study aimed therefore at correlating detailed monthly prescription figures of 11 pharmaceuticals (atenolol, bisoprolol, citalopram, fluoxetine, venlafaxine, losartan, telmisartan, valsartan, carbamazepine, metformin, and tramadol) with measured concentrations of these compounds in influent sewage from five sewage treatment plants in Belgium. For 7 out of the 11 substances, a ratio between loads calculated from the prescription figures and loads calculated from measured concentrations in the range of 0.30–3.00 was observed. For four pharmaceuticals (atenolol, bisoprolol, telmisartan, and venlafaxine), the observed relationship was less pronounced. The manuscript gives an overview of the possible uncertainties that are related with the calculated correlations. This study highlights the need for gathering all the necessary information regarding sewage sampling, stability of substances in sewage, pharmacokinetics, and analytical method performance when sewage-based epidemiology studies are performed.

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Acknowledgments

The Flanders Scientific Funds for Research (FWO) is acknowledged for the financial support through FWO research project G.0177.09M. Alexander van Nuijs acknowledges FWO for his scholarship. The authors would like to thank Alain Vandelannoote (Aquafin, Belgium) for his support with the sampling of sewage. Dr. Christoph Ort (Eawag, Switzerland) is acknowledged for his help with data analysis and presentation.

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Correspondence to Alexander L. N. van Nuijs.

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Responsible editor: Hongwen Sun

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van Nuijs, A.L.N., Covaci, A., Beyers, H. et al. Do concentrations of pharmaceuticals in sewage reflect prescription figures?. Environ Sci Pollut Res 22, 9110–9118 (2015). https://doi.org/10.1007/s11356-014-4066-2

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