Pollutants (Jul 2023)

Mercury Intake Estimation in Adult Individuals from Trieste, Italy: Hair Mercury Assessment and Validation of a Newly Developed Food Frequency Questionnaire

  • Andrea De Giovanni,
  • Vincenzo Iannuzzi,
  • Gianni Gallello,
  • Cristina Giuliani,
  • Mauro Marini,
  • M. Luisa Cervera,
  • Donata Luiselli

DOI
https://doi.org/10.3390/pollutants3030022
Journal volume & issue
Vol. 3, no. 3
pp. 320 – 336

Abstract

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Seafood constitutes the primary source of exposure to the organic form of mercury in the general population, and the Trieste Gulf is considered a hotspot of mercury contamination. We used a newly developed quantitative food frequency questionnaire to obtain an estimation of the intake of mercury through seafood consumption in a sample of 32 individuals from Trieste. Then, we validated the results obtained from the questionnaire against those of the analysis of total mercury measured in the hair of the same individuals through Spearman rank correlation coefficients, Cohen’s weighted Kappa statistic, and a Bland–Altman plot. The Spearman rank correlation coefficient and Cohen’s weighted Kappa statistic were 0.76 and 0.69, respectively. In the Bland–Altman plot, 93.75% of the data points lay within the acceptability range. The plot revealed an ever-increasing overestimation of mercury intake by the questionnaires as the hair mercury increased. By applying a standardized filtering procedure to the results of the questionnaires, we obtained a Spearman rank correlation coefficient and Cohen’s weighted Kappa statistic of 0.69 and 0.57, respectively. In this Bland–Altman plot, 93.75% of the data points lay within the acceptability range. In this latter plot, the proportionality between the mean difference and the magnitude of the measurement was more subtle compared to that observed in the plot built upon the non-filtered questionnaires. This preliminary study shows the high accuracy of the reported questionnaire in the estimation of habitual mercury intake, similar to the one measured through the analysis of hair.

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