The potential of spatial information in human biomonitoring by example of two German environmental epidemiology studies |
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Authors: | Gunther Schmidt Roland Pesch Winfried Schröder André Conrad Marike Kolossa-Gehring Stefan Feigenspan Lorenz Dobler Gerhard A Wiesmüller Manfred Birke Jens Utermann |
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Institution: | 1.Chair of Landscape Ecology,University of Vechta,Vechta,Germany;2.Federal Environment Agency,Berlin,Germany;3.Federal Environment Agency,Dessau-Ro?lau,Germany;4.Environmental Specimen Bank, Section: human specimens,Westphalian Wilhelms University Münster,Münster,Germany;5.Federal Institute for Geosciences and Natural Resources,Hannover,Germany |
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Abstract: | This study aimed at statistically investigating the association between the internal exposure of children and young adults
to uranium (U) and epidemiologically relevant external determinants of exposure. The investigation was performed with data
from two studies within the framework of the German health-related environmental monitoring program: The German Environmental Survey for Children (GerES IV) conducted by the Federal Environment Agency (Umweltbundesamt) with data on 1,780 children 3–14 years of age and their home environment and the German Environmental Specimen Bank (ESB, section: human specimens) with data on 2,253 students 20–29 years of age. Both studies provided data on the U levels in human urine for all probands.
GerES IV furthermore provided an extensive environmental and demographic database on, e.g., U levels in drinking water. The
data from GerES IV and ESB were linked by GIS to spatially relevant exposure information, including background values of U
in stream sediments and in upper and lower soils, U levels in mosses and particulate matter in the lower atmosphere, precipitation
and elevation as well as forest density. Bivariate correlation analysis and two decision tree models showed moderate but significant
associations between U in human urine and U levels in drinking water, stream sediments and upper and lower soils. Future investigations
considering additional epidemiologically relevant data sets may differentiate the results. Furthermore, the sample design
of future environmental epidemiology studies should take the spatial evaluation of the data into greater account. |
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