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Abstract
Protecting the health of pregnant women from environmental stressors is crucial for reducing the burden of non-communicable diseases. In industrially contaminated sites, this action is particularly challenging due to the heterogeneous pollutant mixtures in environmental matrices. The aim of this study was to evaluate distribution patterns of mercury, hexachlorobenzene and polychlorobiphenyls in the serum of 161 pregnant women recruited in the framework of the Neonatal Environment and Health Outcomes (NEHO) cohort and living both inside and outside the National Priority Contaminated Site (NPCS) of Priolo. Food macro-categories were determined, and serum levels of contaminants were used to perform k-means cluster analysis and identify the role of food in pollutant transfer from the environment. Two groups of mothers with high and low measured pollutant levels were distinguished. Concentrations in mothers in the high-exposure cluster were at least twofold for all the evaluated pollutants (p < 0.0001) and included mothers living inside and outside NPCS, with a predominance of individuals from the NPCS (p = 0.045). Fish consumption was higher in the high-exposure cluster (p = 0.019). These findings suggest a link between contamination of environmental matrices such as sediment with maternal exposure, through the intake of local food. Such consideration appears poorly investigated in the context of contaminated sites.
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Details
1 National Research Council of Italy, Institute for Biomedical Research and Innovation, Palermo, Italy (GRID:grid.510483.b)
2 National Research Council of Italy, Institute of Marine Sciences, Venice, Italy (GRID:grid.466841.9) (ISNI:0000 0004 1755 4130)
3 National Research Council of Italy, Institute of Anthropic Impacts and Sustainability in Marine Environment, Palermo, Italy (GRID:grid.5326.2) (ISNI:0000 0001 1940 4177)
4 National Research Council of Italy, Institute of Anthropic Impacts and Sustainability in Marine Environment, Trapani, Italy (GRID:grid.5326.2) (ISNI:0000 0001 1940 4177)
5 National Research Council of Italy, Institute of Clinical Physiology, Pisa, Italy (GRID:grid.418529.3) (ISNI:0000 0004 1756 390X)
6 National Research Council of Italy, Institute for System Analysis and Computer Science-BioMatLab, Rome, Italy (GRID:grid.419461.f) (ISNI:0000 0004 1760 8338)




