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. 2022 Apr 13;14(8):1626.
doi: 10.3390/nu14081626.

Dietary Intake of Toxic Heavy Metals with Major Groups of Food Products-Results of Analytical Determinations

Wojciech Koch  1 , Marcin Czop  2 , Katarzyna Iłowiecka  1 , Agnieszka Nawrocka  3 , Dariusz Wiącek  3
Affiliations

Dietary Intake of Toxic Heavy Metals with Major Groups of Food Products-Results of Analytical Determinations

Wojciech Koch et al. Nutrients. .

Abstract

Food contains a complex matrix of various substances, including essential nutrients, non-nutritive substances, and toxins, including metals. The main purpose of the study was to evaluate the contribution of major groups of food products to an overall intake of toxic heavy metals (Cd, Pb, Hg, and Ni) using a combination of the 24-dietary recall technique, the ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometry) method, and chemometric tools. The obtained results reveal that there is a high potential risk of developing nephrotoxicity through the dietary intake of Pb in the case of both genders. The dietary intake determined for other elements (Cd, Hg, and Ni) was far below the limits established by European Food Safety Authority (EFSA). Principal Component Analysis (PCA) supported analytical determinations and revealed that cereals and vegetables were major contributors to a total intake of Cd (39.6 and 17.4% of the total exposure, respectively), Ni (40.4 and 19.3%), and Hg (16.8 and 19.6%), while water and beverages were major dietary sources of Pb (31% of the total daily intake). In contrast, eggs, fats and oils, and milk and dairy products provided the smallest amounts of Cd, Pb, and Ni. Despite containing high amounts of Hg, considering very low consumption, fish were not found to be an important source of this element.

Keywords: ICP-OES; dietary intake; food; heavy metals.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
PCA biplot showing loadings (for heavy metals) and scores (for products) of the first two principal components of PCA in the group of women, explaining together 84.06% of the variability in the obtained dataset (61.20% and 22.86% in PC1 and PC2, respectively).
Figure 2
Figure 2
PCA biplot showing loadings (for heavy metals) and scores (for products) of the first two principal components of PCA in the group of men, explaining together 80.93% of the variability in the obtained dataset (61.74% and 19.19% in PC1 and PC2, respectively).
See this image and copyright information in PMC

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