Meta-analysis and meta-regression indicate dynamic prevalence and moderators of foodborne pathogens in African indigenous fermented milk

Abstract

As more microbiological data for indigenous fermented milk (IFM) becomes available, concern about their microbial safety becomes eminent. Nonetheless, these data are highly fragmented, and a tool is required to integrate existing data and to provide a basis for data-driven decision making for IFM’s safety. Therefore, meta-analysis and meta-regression were conducted to estimate the prevalence of foodborne pathogens in IFM and to determine factors influencing the estimated values. Using Africa as a case, searches were systematically made for published data and relevant grey literature. Data from 18 studies in 15 countries were analyzed. Staphylococcus aureus (37%), pathogenic Escherichia coli (16%), Listeria monocytogenes (6%), and Salmonella spp. (3%) were the most prevalent pathogens with a pooled prevalence estimate of 12%. Heterogeneity among prevalence estimates was attributed to sampling point and microbial group but could be moderated by publication year, country cluster, and methods for microbial confirmation. The pooled prevalence estimates increased over time as more studies became available, whereby the odds were higher in studies from 2010 onwards than studies before 2010. From the analyses, S. aureus presented the greatest safety concern in African IFM. Future microbiological studies should take into consideration different IFM sampling points and advanced analytical methods to identify pathogens.