Meta-Analysis and Meta-Regression Indicate Dynamic Prevalence and Moderators of Foodborne Pathogens in African

Joseph Wambui1, Patrick Murigu Kamau Njage2, Taurai Tasara1

  • 1Institute for Food Safety and Hygiene, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 272, 8057 Zurich, Switzerland.

Microorganisms
|November 20, 2019
PubMed

Insights

Microbial safety concerns in African indigenous fermented milk (IFM) are rising. A meta-analysis revealed Staphylococcus aureus as the most prevalent pathogen, highlighting the need for improved detection methods.

Area of Science:

  • Food Microbiology
  • Public Health
  • Food Safety

Background:

  • Microbiological data for indigenous fermented milk (IFM) is growing but fragmented.
  • Assessing and integrating this data is crucial for ensuring IFM microbial safety.
  • A data-driven approach is needed for informed decision-making regarding IFM safety.

Purpose of the Study:

  • To estimate the prevalence of foodborne pathogens in African IFM through meta-analysis.
  • To identify factors influencing pathogen prevalence in IFM.
  • To address the microbial safety concerns associated with IFM consumption.

Main Methods:

  • Systematic literature search for published data and grey literature on IFM microbial safety in Africa.
  • Meta-analysis and meta-regression of data from 18 studies across 15 African countries.
  • Analysis of pathogen prevalence, heterogeneity, and influencing factors.

Main Results:

  • A pooled prevalence of 12% for foodborne pathogens was estimated in African IFM.
  • Staphylococcus aureus (37%), pathogenic Escherichia coli (16%), Listeria monocytogenes (6%), and Salmonella spp. (3%) were the most common pathogens.
  • Prevalence estimates increased over time, with higher odds in studies from 2010 onwards. Sampling point and microbial group influenced heterogeneity.

Conclusions:

  • Staphylococcus aureus poses the most significant microbial safety risk in African IFM.
  • Factors like sampling point, country, and analytical methods influence pathogen prevalence.
  • Future research should focus on diverse sampling points and advanced methods for pathogen identification in IFM.

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