Person: Schmidt, Phillipp
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Phillipp
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Veröffentlichung Time Patterns in Internal Human Exposure Data to Bisphenols, Phthalates, DINCH, Organophosphate Flame Retardants, Cadmium and Polyaromatic Hydrocarbons in Europe(2023) Martin, Laura Rodriguez; Gilles, Liese; Helte, Emilie; Kolossa-Gehring, Marike; Lange, Rosa; Pack, Kim Laura; Schmidt, Phillipp; Vogel, Nina; Weber, TillHuman biomonitoring (HBM) data in Europe are often fragmented and collected in different EU countries and sampling periods. Exposure levels for children and adult women in Europe were evaluated over time. For the period 2000-2010, literature and aggregated data were collected in a harmonized way across studies. Between 2011-2012, biobanked samples from the DEMOCOPHES project were used. For 2014-2021, HBM data were generated within the HBM4EU Aligned Studies. Time patterns on internal exposure were evaluated visually and statistically using the 50th and 90th percentiles (P50/P90) for phthalates/DINCH and organophosphorus flame retardants (OPFRs) in children (5-12 years), and cadmium, bisphenols and polycyclic aromatic hydrocarbons (PAHs) in women (24-52 years). Restricted phthalate metabolites show decreasing patterns for children. Phthalate substitute, DINCH, shows a non-significant increasing pattern. For OPFRs, no trends were statistically significant. For women, BPA shows a clear decreasing pattern, while substitutes BPF and BPS show an increasing pattern coinciding with the BPA restrictions introduced. No clear patterns are observed for PAHs or cadmium. Although the causal relations were not studied as such, exposure levels to chemicals restricted at EU level visually decreased, while the levels for some of their substitutes increased. The results support policy efficacy monitoring and the policy-supportive role played by HBM. © 2023 by the authorsVeröffentlichung Identification of real-life mixtures using human biomonitoring data: a proof of concept study(2023) Martin, Laura Rodriguez; Kolossa-Gehring, Marike; Ottenbros, Ilse; Schmidt, Phillipp; Vogel, NinaHuman health risk assessment of chemical mixtures is complex due to the almost infinite number of possible combinations of chemicals to which people are exposed to on a daily basis. Human biomonitoring (HBM) approaches can provide inter alia information on the chemicals that are in our body at one point in time. Network analysis applied to such data may provide insight into real-life mixtures by visualizing chemical exposure patterns. The identification of groups of more densely correlated biomarkers, so-called "communities", within these networks highlights which combination of substances should be considered in terms of real-life mixtures to which a population is exposed. We applied network analyses to HBM datasets from Belgium, Czech Republic, Germany, and Spain, with the aim to explore its added value for exposure and risk assessment. The datasets varied in study population, study design, and chemicals analysed. Sensitivity analysis was performed to address the influence of different approaches to standardise for creatinine content of urine. Our approach demonstrates that network analysis applied to HBM data of highly varying origin provides useful information with regards to the existence of groups of biomarkers that are densely correlated. This information is relevant for regulatory risk assessment, as well as for the design of relevant mixture exposure experiments. © 2023 by the authors