Auflistung nach Autor:in "Bopp, Stephanie"

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Chemical mixtures in the EU population: composition and potential risks
(2022) Socianu, Sebastian; Bopp, Stephanie; Govarts, Eva; Kolossa-Gehring, Marike
Regulating chemical mixtures is a complex scientific and policy task. The aim of this study was to investigate typical mixtures and their potential risks based on internal exposure levels in the European population. Based on human biomonitoring (HBM) data made available via the HBM4EU project, we derived generic mixtures representative of a median (P50) and a worst-case scenario (P95) for adults and children. We performed a mixture risk assessment based on HBM concentrations, health-based guidance values (HBGVs) as internal thresholds of concern, and the conservative assumption of concentration addition applied across different toxicological endpoints. Maximum cumulative ratios (MCRs) were calculated to characterize the mixture risk. The mixtures comprise 136 biomarkers for adults and 84 for children, although concentration levels could be quantified only for a fraction of these. Due to limited availability of HBGVs, the mixture risk was assessed for a subset of 20 substance-biomarker pairs for adults and 17 for children. The mixture hazard index ranged from 2.8 (P50, children) to 9.2 (P95, adults). Six to seven substances contributed to over 95% of the total risk. MCR values ranged between 2.6 and 5.5, which is in a similar range as in previous studies based on human external exposures assessments. The limited coverage of substances included in the calculations and the application of a hazard index across toxicological endpoints argue for caution in the interpretation of the results. Nonetheless the analyses of MCR and MAFceiling can help inform a possible mixture assessment factor (MAF) applicable to single substance risk assessment to account for exposure to unintentional mixtures. © 2022 by the authors
Position paper on management of personal data in environment and health research in Europe
(2022) Govarts, Eva; Gilles, Liese; Bopp, Stephanie; Vogel, Nina
Management of datasets that include health information and other sensitive personal information of European study participants has to be compliant with the General Data Protection Regulation (GDPR, Regulation (EU) 2016/679). Within scientific research, the widely subscribed 'FAIR' data principles should apply, meaning that research data should be findable, accessible, interoperable and re-usable. Balancing the aim of open science driven FAIR data management with GDPR compliant personal data protection safeguards is now a common challenge for many research projects dealing with (sensitive) personal data. In December 2020 a workshop was held with representatives of several large EU research consortia and of the European Commission to reflect on how to apply the FAIR data principles for environment and health research (E&H). Several recent data intensive EU funded E&H research projects face this challenge and work intensively towards developing solutions to access, exchange, store, handle, share, process and use such sensitive personal data, with the aim to support European and transnational collaborations. As a result, several recommendations, opportunities and current limitations were formulated. New technical developments such as federated data management and analysis systems, machine learning together with advanced search software, harmonized ontologies and data quality standards should in principle facilitate the FAIRification of data. To address ethical, legal, political and financial obstacles to the wider re-use of data for research purposes, both specific expertise and underpinning infrastructure are needed. There is a need for the E&H research data to find their place in the European Open Science Cloud. Communities using health and population data, environmental data and other publicly available data have to interconnect and synergize. To maximize the use and re-use of environment and health data, a dedicated supporting European infrastructure effort, such as the EIRENE research infrastructure within the ESFRI roadmap 2021, is needed that would interact with existing infrastructures. © 2022 The Authors