Browsing by Author "Schoeters, G."
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- Exposure assessment of total DON in urine of Portuguese adult population under the HBM4EU aligned studiesPublication . Alvito, P.C.; Silva, M.J.; Viegas, S.; Vasco, E.; Martins, C.; Assunção, R.; Silva, S.; Gilles, L.; Govarts, E.; Schoeters, G.; Namorado, S.Mycotoxins are secondary metabolites of fungi that can be found in food commodities. Exposure to mycotoxins has been associated with several adverse health effects, including hepatotoxicity. nephrotoxicity, immunotoxicity, mutagenicity and carcinogenicity.As such, from a public health perspective it is important to monitor and to assess the risk associated to mycotoxins’ exposure. In the scope of the European Human Biomonitoring Initiative (HBM4EU), exposure to mycotoxins, namely to deoxynivalenol (DON) was analysed in adults from several European countries, including Portugal. Data was collected under the project “Exposure of the Portuguese Population to Environmental Chemicals: a study nested in INSEF 2015”. INSEF-ExpoQuim, was an epidemiological study nested in the first Portuguese Health Examination Survey (INSEF), that enrolled individuals aged 28–39 years, living in Portugal for more than 12 months and able to follow an interview in Portuguese. Fieldwork was developed between May 2019 and March 2020 and first morning urine samples were collected along with data on socio-demographic characteristics, living conditions and residential history, habits/ lifestyle, nutrition, health, occupation and substance specific information covering nearly all exposure pathways. Procedures followed the guidelines of HBM4EU. Total DON (sum of free DON + DONglucuronides after deconjugation) was determined in 295 urine samples by a qualified laboratory and using a harmonized analytical method. Results: showed that the Portuguese population was exposed to DON (mean = 9.8 mg/L; 95% CI: 8.7–10.9 mg/L). DON concentrations were significantly higher for samples collected in spring and summer. Individuals living in rural areas and with a lower education levels presented higher exposures to DON, as well as individuals with a higher bread consumption frequency (≥4 times per week). No differences were found regarding sex, age, occupation, income or consumption of other foods. Comparing this study’s data with the human biomonitoring guidance value (HBM-GV) determined for DON in the scope of HBM4EU (Total DON: 0.69 μg DON/kg bw/total 24 h ≈ 23 μg DON/L urine) 12.5% of the participants presented values above the HBM-GV. Overall, the results from this study showed that the Portuguese population is currently exposed to DON, with a significant proportion of individuals presenting exposures to values that warrant further assessment, including a close monitoring of exposure in the future and the development and implementation of policy measures aimed at minimizing exposure and improving the health of the population.
- HBM4EU - Deliverable Report D 5.5: Human biomonitoring in risk assessment: 2nd set of examples on the use of HBM in risk assessments of HBM4EU priority chemicalsPublication . Santonen, Tiina; Mahiout, Selma; Bessems, J.; Buekers, J.; Baken, K.; Schoeters, G.; Woutersen, M.; Vermeire, T.; Bil, W.; Ougier, E.; Rousselle, C.; Šömen Joksić, A.; Kirinčič, S.; Louro, Henriqueta; Silva, Maria João; Assunção, Ricardo; Vinggaard, A. M.; Viegas, S.; Huuskonen, P.; Porras, S.; Kiilunen, M.; Uhl, M.; Hartmann, C.; Hauzenberger, I.; Losert, A.; Tratnik, J. Snoj; Horvat, M.; Schaddelee-Scholten, B.; Buist, H.; Westerhout, J.; Fletcher, T.; Rauscher-Gabernig, E.; Plichta, V.; Abraham, K.; Borges, T.; Kadikis, N.The aim of this work was to exemplify the inclusion of human biomonitoring (HBM) data in risk assessment (RA) and health impact assessment (HIA) strategies. RA was performed for six compound groups on HBM4EU’s first list of priority substances: anilines, cadmium/chromium, flame retardants, PAHs, PFAS and phthalates. In addition, burden of disease (BoD) calculations were made for cadmium. The general approach used included: 1) identification of an existing RA for the substance, 2) identification of possible existing biological limit or guidance values or biological equivalents (BEs), or if lacking, existing health based limit values for external exposure, 3) identification of relevant biomonitoring data to be used in the RA, 4) in case no existing biological limit or guidance values or BEs existed, identification of approaches for reverse/forward calculation, including the use of PBPK modelling or calculation of BE values based on one-compartment modelling, 5) RA or BoD calculation based on HBM data, 6) analysing the benefits and challenges of using HBM data in RA compared to the use of external exposure data. The overall result of the work was that HBM can be included in RA even when relatively few data are available, and its inclusion generally benefits the RA. Several methods exist, and a tiered approach is suggested, based on the amount and quality of data available. The recommended 1st tier method is a one-compartment modelling based derivation of BE values or reverse calculation of external exposure based on biomarker levels. This approach is simple and rough, and uses only very basic parameters. However, in many cases this approach can be considered sufficient, especially when conservative assumptions have been used for the FUE, and the calculated RCRs remain well below 1, indicating a low risk. Also, in cases in which risk assessment using this approach supports the RA made based on external exposure estimates, it is often a sufficient approach. Nevertheless, in some cases e.g. where the RCR is close to 1, a more detailed approach may be needed to refine the RA. For the 2nd tier, PBPK modelling is recommended. For the most robust, 3rd tier approach, measured data on correlations between external exposure and internal doses from well controlled studies would be needed. Certain cases were identified where inclusion of HBM would be particularly important for performing RA: for compounds, for which several exposure routes may contribute to the body burden and the health effects, as HBM reflects the total body burden, and cumulative compounds. For cumulative compounds, HBM could also be useful for hazard assessment in addition to exposure assessment. One of the major challenges for the inclusion of HBM into RA is the often limited data available on toxicokinetics. In addition, in some cases, there is an urgent need for more specific biomarkers or more sensitive analytic methods than currently available. It should be noted that these risk assessments were performed purely to determine how HBM data can contribute to the risk assessment of chemicals, and they have no regulatory implications. Overall for the substances on the HBM4EU’s first list of priority substances, more HBM data are needed. This work is ongoing in WP8, and the RAs presented here will be updated when new data become available.