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Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products

The handling of data on food contamination frequently represents a challenge because these are often left-censored, being composed of both positive and non-detected values. The latter observations are not quantified and provide only the information that they are below a laboratory-specific threshold...

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Autores principales: Feraldi, Alessandro, De Santis, Barbara, Finocchietti, Marco, Debegnach, Francesca, Mandile, Antonio, Alfò, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536512/
https://www.ncbi.nlm.nih.gov/pubmed/37755947
http://dx.doi.org/10.3390/toxins15090521
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author Feraldi, Alessandro
De Santis, Barbara
Finocchietti, Marco
Debegnach, Francesca
Mandile, Antonio
Alfò, Marco
author_facet Feraldi, Alessandro
De Santis, Barbara
Finocchietti, Marco
Debegnach, Francesca
Mandile, Antonio
Alfò, Marco
author_sort Feraldi, Alessandro
collection PubMed
description The handling of data on food contamination frequently represents a challenge because these are often left-censored, being composed of both positive and non-detected values. The latter observations are not quantified and provide only the information that they are below a laboratory-specific threshold value. Besides deterministic approaches, which simplify the treatment through the substitution of non-detected values with fixed threshold or null values, a growing interest has been shown in the application of stochastic approaches to the treatment of unquantified values. In this study, a multiple imputation procedure was applied in order to analyze contamination data on deoxynivalenol, a mycotoxin that may be present in pasta and pasta substitute products. An application of the proposed technique to censored deoxynivalenol occurrence data is presented. The results were compared to those attained using deterministic techniques (substitution methods). In this context, the stochastic approach seemed to provide a more accurate, unbiased and realistic solution to the problem of left-censored occurrence data. The complete sample of values could then be used to estimate the exposure of the general population to deoxynivalenol based on consumption data.
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spelling pubmed-105365122023-09-29 Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products Feraldi, Alessandro De Santis, Barbara Finocchietti, Marco Debegnach, Francesca Mandile, Antonio Alfò, Marco Toxins (Basel) Article The handling of data on food contamination frequently represents a challenge because these are often left-censored, being composed of both positive and non-detected values. The latter observations are not quantified and provide only the information that they are below a laboratory-specific threshold value. Besides deterministic approaches, which simplify the treatment through the substitution of non-detected values with fixed threshold or null values, a growing interest has been shown in the application of stochastic approaches to the treatment of unquantified values. In this study, a multiple imputation procedure was applied in order to analyze contamination data on deoxynivalenol, a mycotoxin that may be present in pasta and pasta substitute products. An application of the proposed technique to censored deoxynivalenol occurrence data is presented. The results were compared to those attained using deterministic techniques (substitution methods). In this context, the stochastic approach seemed to provide a more accurate, unbiased and realistic solution to the problem of left-censored occurrence data. The complete sample of values could then be used to estimate the exposure of the general population to deoxynivalenol based on consumption data. MDPI 2023-08-24 /pmc/articles/PMC10536512/ /pubmed/37755947 http://dx.doi.org/10.3390/toxins15090521 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Feraldi, Alessandro
De Santis, Barbara
Finocchietti, Marco
Debegnach, Francesca
Mandile, Antonio
Alfò, Marco
Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products
title Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products
title_full Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products
title_fullStr Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products
title_full_unstemmed Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products
title_short Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products
title_sort evaluation of statistical treatment of left-censored contamination data: example involving deoxynivalenol occurrence in pasta and pasta substitute products
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536512/
https://www.ncbi.nlm.nih.gov/pubmed/37755947
http://dx.doi.org/10.3390/toxins15090521
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