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Publikationstyp
Wissenschaftlicher Artikel
Erscheinungsjahr
2019
Human biomonitoring reference values: Differences and similarities between approaches for identifying unusually high exposure of pollutants in humans
Human biomonitoring reference values: Differences and similarities between approaches for identifying unusually high exposure of pollutants in humans
Herausgeber
Quelle
International Journal of Hygiene and Environmental Health
222 (2019), Heft 1, Pages 30-33
222 (2019), Heft 1, Pages 30-33
Schlagwörter
Referenzwert, Human-Biomonitoring
Zitation
APEL, Petra, André CONRAD, Marike KOLOSSA-GEHRING, Enrico RUCIC und Nina VOGEL, 2019. Human biomonitoring reference values: Differences and similarities between approaches for identifying unusually high exposure of pollutants in humans. International Journal of Hygiene and Environmental Health [online]. 2019. Bd. 222 (2019), Heft 1, Pages 30-33. DOI 10.60810/openumwelt-850. Verfügbar unter: https://openumwelt.de/handle/123456789/5832
Zusammenfassung englisch
In exposure and risk assessment, the indication of unusually high exposure levels in humans to chemicals has been considered as an important objective for decades. To realize this objective, reference values (RV) need to be derived. However, while there is a tendency towards using the 95th percentile as a basis for deriving these reference values there is still no consensus. Moreover, side approaches have evolved including deriving RVs based on other percentiles, reporting multiple RVs or only reporting percentiles. The purpose of this article is to give an overview of the current literature, to point out differences and similarities between existing approaches, and to highlight important criteria for the derivation of RVs. We observe the majority of studies to base RVs on the 95th percentile and its 95% confidence interval which can been justified by statistical paradigms, present arguments for a single defined reference value, and discuss characteristics which call for more consistency. To conclude, our overview provides a first step towards a more homogenous and standardized derivation procedure to identify unusually high exposures in exposure science. © 2018 The Authors. Published by Elsevier GmbH.