TY - JOUR
T1 - How to use human biomonitoring in chemical risk assessment
T2 - Methodological aspects, recommendations, and lessons learned from HBM4EU
AU - Santonen, Tiina
AU - Mahiout, Selma
AU - Alvito, Paula
AU - Apel, Petra
AU - Bessems, Jos
AU - Bil, Wieneke
AU - Borges, Teresa
AU - Bose-O'Reilly, Stephan
AU - Buekers, Jurgen
AU - Cañas Portilla, Ana Isabel
AU - Calvo, Argelia Castaño
AU - de Alba González, Mercedes
AU - Domínguez-Morueco, Noelia
AU - López, Marta Esteban
AU - Falnoga, Ingrid
AU - Gerofke, Antje
AU - Caballero, María del Carmen González
AU - Horvat, Milena
AU - Huuskonen, Pasi
AU - Kadikis, Normunds
AU - Kolossa-Gehring, Marike
AU - Lange, Rosa
AU - Louro, Henriqueta
AU - Martins, Carla
AU - Meslin, Matthieu
AU - Niemann, Lars
AU - Díaz, Susana Pedraza
AU - Plichta, Veronika
AU - Porras, Simo P.
AU - Rousselle, Christophe
AU - Scholten, Bernice
AU - Silva, Maria João
AU - Šlejkovec, Zdenka
AU - Tratnik, Janja Snoj
AU - Joksić, Agnes Šömen
AU - Tarazona, Jose V.
AU - Uhl, Maria
AU - Van Nieuwenhuyse, An
AU - Viegas, Susana
AU - Vinggaard, Anne Marie
AU - Woutersen, Marjolijn
AU - Schoeters, Greet
N1 - This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 733032 HBM4EU, and co-funding from the authors' organisations. The results presented here are based on a huge body of work performed as part of Task 5.3 of the HBM4EU in 2017–2022. First and foremost, we would like to acknowledge all our Task 5.3 colleagues for their valuable contribution to the project work, including the individual RAs and EBoD calculations. In addition, we would like to thank all our other HBM4EU colleagues, the HBM4EU-aligned study data owners, and the other stakeholders who provided support for and feedback on our work during its course.
PY - 2023
Y1 - 2023
N2 - One of the aims of the European Human Biomonitoring Initiative, HBM4EU, was to provide examples of and good practices for the effective use of human biomonitoring (HBM) data in human health risk assessment (RA). The need for such information is pressing, as previous research has indicated that regulatory risk assessors generally lack knowledge and experience of the use of HBM data in RA. By recognising this gap in expertise, as well as the added value of incorporating HBM data into RA, this paper aims to support the integration of HBM into regulatory RA. Based on the work of the HBM4EU, we provide examples of different approaches to including HBM in RA and in estimations of the environmental burden of disease (EBoD), the benefits and pitfalls involved, information on the important methodological aspects to consider, and recommendations on how to overcome obstacles. The examples are derived from RAs or EBoD estimations made under the HBM4EU for the following HBM4EU priority substances: acrylamide, o-toluidine of the aniline family, aprotic solvents, arsenic, bisphenols, cadmium, diisocyanates, flame retardants, hexavalent chromium [Cr(VI)], lead, mercury, mixture of per-/poly-fluorinated compounds, mixture of pesticides, mixture of phthalates, mycotoxins, polycyclic aromatic hydrocarbons (PAHs), and the UV-filter benzophenone-3. Although the RA and EBoD work presented here is not intended to have direct regulatory implications, the results can be useful for raising awareness of possibly needed policy actions, as newly generated HBM data from HBM4EU on the current exposure of the EU population has been used in many RAs and EBoD estimations.
AB - One of the aims of the European Human Biomonitoring Initiative, HBM4EU, was to provide examples of and good practices for the effective use of human biomonitoring (HBM) data in human health risk assessment (RA). The need for such information is pressing, as previous research has indicated that regulatory risk assessors generally lack knowledge and experience of the use of HBM data in RA. By recognising this gap in expertise, as well as the added value of incorporating HBM data into RA, this paper aims to support the integration of HBM into regulatory RA. Based on the work of the HBM4EU, we provide examples of different approaches to including HBM in RA and in estimations of the environmental burden of disease (EBoD), the benefits and pitfalls involved, information on the important methodological aspects to consider, and recommendations on how to overcome obstacles. The examples are derived from RAs or EBoD estimations made under the HBM4EU for the following HBM4EU priority substances: acrylamide, o-toluidine of the aniline family, aprotic solvents, arsenic, bisphenols, cadmium, diisocyanates, flame retardants, hexavalent chromium [Cr(VI)], lead, mercury, mixture of per-/poly-fluorinated compounds, mixture of pesticides, mixture of phthalates, mycotoxins, polycyclic aromatic hydrocarbons (PAHs), and the UV-filter benzophenone-3. Although the RA and EBoD work presented here is not intended to have direct regulatory implications, the results can be useful for raising awareness of possibly needed policy actions, as newly generated HBM data from HBM4EU on the current exposure of the EU population has been used in many RAs and EBoD estimations.
KW - Human biomonitoring
KW - Risk assessment
KW - HBM4EU
KW - Chemicals
KW - Exposure biomarkers
KW - Environmental burden of disease
U2 - 10.1016/j.ijheh.2023.114139
DO - 10.1016/j.ijheh.2023.114139
M3 - Journal article
C2 - 36870229
SN - 0934-8859
VL - 249
JO - International Journal of Hygiene and Environmental Medicine
JF - International Journal of Hygiene and Environmental Medicine
M1 - 114139
ER -