The research is based on analysis data of Cr, Cu, Mn, Ni, V, Zn (metals) and S in the hair of 47 girls and 63 boys from eight Vilnius kindergartens and the distribution pattern of high metal concentrations and bioavailability in snow-cover dust, also dust samples from vents of characteristic pollution sources. The kindergartens were selected according to topsoil total contamination index and dust-related indices. Significantly higher Cu, Mn, Ni and Zn concentrations in the hair of girls (means are 1.1, 1.9, 1.3, 1.2 times higher) and the differences between hair of genders according to inter-element correlation and clustering were found. Analysis of Spearman correlation coefficients between metal concentrations in hair of each gender and dust metal concentrations or metal loading rates at their residence sites revealed that for Mn, Cu and Zn, they are insignificant, while for Cr, Ni, Pb and V, they are mainly significant positive (except V in female hair). The correlation of the contents of Cr, Ni and V in dust with respective concentrations in hair was more significant for boys (p < 0.001) than for girls. Only a few cases with a significant Cr, Ni, Cu, Pb and Zn increase were revealed in hair of children attending polluted kindergartens in comparison with control. It was concluded that relationship between metal concentrations in hair and dust-related indices is more expressed for children’s residence sites than for their kindergarten sites. The gender-based grouping and site-by-site study design are recommended in the studies of reflection of environmental exposure in hair.
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We are grateful to doctor of medicine Laima Paplauskaitė for hair sampling, all anonymous reviewers for their valuable comments and suggestions that helped to improve our manuscript and to Stephen Conlon (Brussels) for his linguistic advice.
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Taraškevičius, R., Zinkutė, R., Gedminienė, L. et al. Hair geochemical composition of children from Vilnius kindergartens as an indicator of environmental conditions. Environ Geochem Health 40, 1817–1840 (2018). https://doi.org/10.1007/s10653-017-9977-7
- Heavy metals
- EDXRF analysis
- Snow-cover dust metal concentrations
- Metal loading rates
- Gender-related elements