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Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling

Listeria outbreaks and food recalls is on the raise globally. Milk particularly is highly susceptible to Listeria as its production and storage adequately support Listeria growth. The extent of milk contamination with Listeria monocytogenes (Lm) and preventative actions to halt milk associated outbr...

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Autores principales: Oluwafemi, Yinka D., Igere, Bright E., Ekundayo, Temitope C., Ijabadeniyi, Oluwatosin A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403535/
https://www.ncbi.nlm.nih.gov/pubmed/37542148
http://dx.doi.org/10.1038/s41598-023-39955-0
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author Oluwafemi, Yinka D.
Igere, Bright E.
Ekundayo, Temitope C.
Ijabadeniyi, Oluwatosin A.
author_facet Oluwafemi, Yinka D.
Igere, Bright E.
Ekundayo, Temitope C.
Ijabadeniyi, Oluwatosin A.
author_sort Oluwafemi, Yinka D.
collection PubMed
description Listeria outbreaks and food recalls is on the raise globally. Milk particularly is highly susceptible to Listeria as its production and storage adequately support Listeria growth. The extent of milk contamination with Listeria monocytogenes (Lm) and preventative actions to halt milk associated outbreaks in Africa are unknown. Hence, this study aimed at assessing the national and subregional prevalence of Lm in milk in Africa and identify impacting factors via generalized logistic mixed-effects (GLMEs) and meta-regression modelling. Lm-milk-specific data acquired from primary studies according to standard protocol were fitted using a GLMEs. The GLMEs was subjected to leave-one-study-out-cross-validation (LOSOCV). Factors impacting Lm prevalence in milk were assayed via a 1000-permutation-assisted meta-regression-modelling. The pooled prevalence of Lm in milk in Africa was 4.35% [2.73–6.86] with a prediction interval (PI) of 0.14–59.86% and LOSOCV value of 2.43% [1.62–3.62; PI: 0.32–16.11%]. Western Africa had the highest prevalence [20.13%, 4.13–59.59], then Southern Africa [5.85%, 0.12–75.72], Northern Africa [4.67%, 2.82–7.64], Eastern Africa [1.91%, 0.64–5.55], and there was no record from Central Africa. In term of country, Lm prevalence in milk significantly (p < 0.01) varied from 0.00 to 90.00%. Whereas the Lm prevalence was negligibly different (p = 0.77) by milk type, raw-milk had the highest prevalence [5.26%], followed by fermented-milk [4.76%], boiled-milk [2.90%], pasteurized-milk [1.64%], and powdered-milk [1.58%]. DNA extraction approach did not significantly (p = 0.07) affect Lm prevalence (Boiling [7.82%] versus Kit [7.24%]) as well as Lm detection method (p = 0.10; (ACP [3.64%] vs. CP [8.92%] vs. CS [2.27%] vs. CSP [6.82%]). Though a bivariate/multivariate combination of all tested variables in meta-regression explained 19.68–68.75% (R(2)) variance in Lm prevalence in milk, N, nation, and subregion singly/robustly accounted for 17.61% (F(1;65) = 7.5994; p = 0.005), 63.89% (F(14;52) = 4.2028; p = 0.001), and 16.54% (F(3;63) = 3.4743; p = 0.026), respectively. In conclusion, it is recommended that adequate sample size should be prioritized in monitoring Lm in milk to prevent spuriously high or low prevalence to ensure robust, plausible, and credible estimate. Also, national efforts/interests and commitments to Lm monitoring should be awaken.
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spelling pubmed-104035352023-08-06 Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling Oluwafemi, Yinka D. Igere, Bright E. Ekundayo, Temitope C. Ijabadeniyi, Oluwatosin A. Sci Rep Article Listeria outbreaks and food recalls is on the raise globally. Milk particularly is highly susceptible to Listeria as its production and storage adequately support Listeria growth. The extent of milk contamination with Listeria monocytogenes (Lm) and preventative actions to halt milk associated outbreaks in Africa are unknown. Hence, this study aimed at assessing the national and subregional prevalence of Lm in milk in Africa and identify impacting factors via generalized logistic mixed-effects (GLMEs) and meta-regression modelling. Lm-milk-specific data acquired from primary studies according to standard protocol were fitted using a GLMEs. The GLMEs was subjected to leave-one-study-out-cross-validation (LOSOCV). Factors impacting Lm prevalence in milk were assayed via a 1000-permutation-assisted meta-regression-modelling. The pooled prevalence of Lm in milk in Africa was 4.35% [2.73–6.86] with a prediction interval (PI) of 0.14–59.86% and LOSOCV value of 2.43% [1.62–3.62; PI: 0.32–16.11%]. Western Africa had the highest prevalence [20.13%, 4.13–59.59], then Southern Africa [5.85%, 0.12–75.72], Northern Africa [4.67%, 2.82–7.64], Eastern Africa [1.91%, 0.64–5.55], and there was no record from Central Africa. In term of country, Lm prevalence in milk significantly (p < 0.01) varied from 0.00 to 90.00%. Whereas the Lm prevalence was negligibly different (p = 0.77) by milk type, raw-milk had the highest prevalence [5.26%], followed by fermented-milk [4.76%], boiled-milk [2.90%], pasteurized-milk [1.64%], and powdered-milk [1.58%]. DNA extraction approach did not significantly (p = 0.07) affect Lm prevalence (Boiling [7.82%] versus Kit [7.24%]) as well as Lm detection method (p = 0.10; (ACP [3.64%] vs. CP [8.92%] vs. CS [2.27%] vs. CSP [6.82%]). Though a bivariate/multivariate combination of all tested variables in meta-regression explained 19.68–68.75% (R(2)) variance in Lm prevalence in milk, N, nation, and subregion singly/robustly accounted for 17.61% (F(1;65) = 7.5994; p = 0.005), 63.89% (F(14;52) = 4.2028; p = 0.001), and 16.54% (F(3;63) = 3.4743; p = 0.026), respectively. In conclusion, it is recommended that adequate sample size should be prioritized in monitoring Lm in milk to prevent spuriously high or low prevalence to ensure robust, plausible, and credible estimate. Also, national efforts/interests and commitments to Lm monitoring should be awaken. Nature Publishing Group UK 2023-08-04 /pmc/articles/PMC10403535/ /pubmed/37542148 http://dx.doi.org/10.1038/s41598-023-39955-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Oluwafemi, Yinka D.
Igere, Bright E.
Ekundayo, Temitope C.
Ijabadeniyi, Oluwatosin A.
Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling
title Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling
title_full Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling
title_fullStr Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling
title_full_unstemmed Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling
title_short Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling
title_sort prevalence of listeria monocytogenes in milk in africa: a generalized logistic mixed-effects and meta-regression modelling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403535/
https://www.ncbi.nlm.nih.gov/pubmed/37542148
http://dx.doi.org/10.1038/s41598-023-39955-0
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