Ethical approvals were obtained from the International Livestock Research Institute’s Research Ethics Committee (IREC); ILRI-IREC2021-62 and the National Commission for Science, Technology, and Innovation (NACOSTI); Ref No: 259467 and the Nairobi County; REF: EOP/NMS/HS/132. Approval was also obtained from the Faculty of Veterinary Medicine Biosafety, Animal Use and Ethics Committee, University of Nairobi; REF: FVM BAUEC/2022/416. More importantly, consent was sought from all participating butchery attendants/owners during the study.

This cross-sectional study was conducted between May and October 2022 in Nairobi County and specifically focused on four wards namely Kawangware, Kangemi, Huruma, and Waithaka (Figure 1). These sites were purposively selected based on their high concentration of butchery outlets and because most residents are low and middle-income class (Owuor et al., 2017). The study unit was the butchery, which was randomly selected, visited only once, and only one person from the outlet was interviewed, i.e., either the owner or the attendant, depending on who was available and directly involved in handling and selling meat. Butcheries selling beef and having meat available at the time of the study were included. The sample size was estimated in Stata® 15, for comparison of two proportions: p1 = estimate of the proportion of meat samples with unacceptable coliform counts, in the control group, and p2 = proportion of meat with unacceptable coliform counts, in the intervention group. Using p1 = 0.65, p2 = 0.50, alpha = 0.05, and power = 0.80, the minimum sample size required to detect a difference of 15% is 170 samples per group which translated to enrolling 340 butcheries. A correction for the finite population was done (as a prior mapping activity had established that there were 430 butcheries in the study areas). Considering possible withdrawals/ refusal to participate, a total of 200 butcheries were included in the study (100 butcheries per group).

The meat was processed to evaluate the levels of E. coli and other coliforms using the 3M™ Petrifilm^® E. coli/coliform count plate following the manufacturer’s instructions. Ten grams of the beef cubes were weighed ensuring that different surfaces of the meat were included and placed into a stomacher bag together with 90 mL of phosphate buffered saline and homogenized using a Stomacher® 400 circulator lab blender (United Kingdom) for 5 min at 300 rpm. This formed the 10⁻¹ dilution, which was then further serially diluted to 10⁻⁴, giving four dilutions in total. One ml from each dilution was plated on the 3M^™ Petrifilm^® and incubated at 35°C for 24 h. No replicates were included. After incubation, the plates were evaluated according to the interpretation guidelines from the manufacturer. The colonies were counted and classified as either E. coli (blue colonies with bubbles) or total coliforms (blue and red colonies with and without bubbles; 3M Food Safety, 2017). From each Petrifilm with presumptive E. coli, one colony was selected and sub-cultured on MacConkey agar, and the bacterial species was confirmed by Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass spectrometry (MALDI-TOF MS) on the Bruker Biotype system (Bruker, Bremen, Germany).

Twenty microliters from each dilution from 2.4 were spotted on MacConkey agar plates supplemented with either 8 mg/L tetracycline hydrochloride (TET; Carl ROTH, Karlsruhe Germany) or 0.25 mg/L cefotaxime (CTX; Sigma-Aldrich Darmstadt, Germany,) and incubated aerobically overnight. The concentrations chosen are above the epidemiological cut-off values for each antibiotic (CTX = 0.25 μg/mL and TET = 8 μg/mL).¹ After overnight incubation, colonies were counted on each dilution and the colony-forming units (CFU/g) were calculated. A single reddish/pink colony from each plate (i.e., lactose fermenters such as E. coli, Klebsiella, Enterobacter and Citrobacter) was further sub-cultured on nutrient agar and stored at -80°C for bacterial species confirmation by MALDI-TOF MS. These were chosen because tetracycline is the most used antibiotic in livestock production (WOAH, 2022) thus was used as an indicator of resistance most likely originating from livestock. Cefotaxime, which is a critically important antibiotic in human health, is registered for use in livestock but is rarely used in Africa (WOAH, 2022). Moreover, 3^rd generation cephalosporin resistant Enterobacteriaceae are identified as a critical priority group in the WHO priority pathogen list (WHO, 2024) hence, we investigated the presence of these clinically relevant bacteria in meat.

Descriptive statistics were used to analyze the detection of selected microbiological determinants, CFU counts, and frequencies of meat handling practices. A non-parametric test was used to compare the mean colony-forming units of different study sites and a pairwise comparison of the mean colony-forming units of the different sites was calculated using Dunn’s test. Statistical significance was determined using a p-value at the critical probability of p < 0.05.

Most of the participants were male (96.9%), aged between 20 to 30 years old (42.7%), had a secondary level of education (50%), and had >5 years working in meat selling (51.6%). Two hundred meat samples were collected which included 59 from Kawangware, 47 from Kangemi, 38 from Huruma, and 56 from Waithaka. Correspondingly, observation data were collected from all the butcheries, however, the data from one butchery was lost during the process of data cleaning.

Coliforms were present in 98% (n = 196) of samples; the counts ranged between 1.0 log₁₀–8.0 log₁₀ CFU/g, with a mean of 3.8 log₁₀ CFU/g (Figure 2). E. coli were present in 78% (n = 156) of the samples, and the counts ranged between 1.0 log₁₀–8.0 log₁₀ CFU/g with a mean of 2.3 log₁₀ CFU/g (Figure 3). According to Kenyan standards, 72% of the samples were contaminated with E. coli above the accepted level (>100 CFU/g). Eighty-four percent of the samples had mean total coliform (>316 coliform CFU/g) as the South African and European Commission cut offs, with variations between the four study areas. There were significant differences between the means of total coliform counts from the four study sites (p-value = 0.003). The mean total coliform CFU/g for samples between Kawangware and Waithaka was statistically different compared to those from Huruma and Kangemi, respectively (Figure 2). Likewise, there was a significant difference between the E. coli counts (p-value = 0.0003) from the different study sites. There was a significant difference between the mean E. coli CFU counts for Kawangware and Kangemi and between Huruma and Waithaka. Meat samples from Huruma had relatively higher contamination by E. coli with all the samples having counts above the mean (Figure 3). The meat samples from Waithaka had relatively low counts of both E. coli and other coliforms.

Of the 70 meat samples (35%) that had reddish-pink colonies on MacConkey agar plates containing TET, were identified as E. coli (51%), C. braakii (3%), C. freundii (34%), Moellerella wisconsensis (6%), Raoultella ornithinolytica (4%) and Lelliottia amnigena (2%). Nineteen (9.5%) meat samples had growth on CTX-containing MacConkey plates and were identified as E. coli (22%), A. veronii (6%), C. freundii (39%), Kluyvera cryocrescens (21%), Acinetobacter johnsonii (6%) and E. cloacae (6%). TET counts were between 1.0–4.8 log₁₀ CFU/g while CTX counts were between 1.0–4.6 log₁₀ CFU/g.

Forty-three percent of butcheries (n = 86) also sold in the same outlet, ready-to-eat meat, i.e., meat that has either boiled, fried or roasted. The mean temperature and humidity inside the butcher shops were 24 ⁰c and 46%, respectively. Table 1 and Figures 4, 5 show the frequencies of the observed handling practices. Only 28% (56/199) of butcheries had hand-washing facilities, either a permanently placed water dispenser, e.g., a sink or a mobile water container, and half of these butcheries were found in Waithaka, while the remaining butcheries were scattered among the other three study sites. Seventy-five percent (n = 150) of the butcher attendants did not wash their hands before handling the raw meat and 85% (n = 170) did not wash their hands after handling the raw meat. Ninety-one percent handled money while selling meat simultaneously and neither washed nor wiped their hands after handling money. Almost all the butchery attendants did not wear gloves while handling meat, and 36% had either dirty hands (i.e., had visible dirt and/or meat debris) or long untrimmed nails. Fifty-eight percent of attendants did not use an apron while selling meat, 32% wore jewelry (such as rings, watches, and or bracelets) and only 39% covered their hair with a hair cover.

We observed flies inside the butcher shops and/ or on the meat surface in 170 (85%) of the butcheries. Moreover, live cockroaches were observed in 19 (10%) butcheries during the visit. More than half (55%) of butcheries had clean floors, i.e., free of dust and/or gross dirt while only 39% had clean walls, i.e., free of gross dirt and or blood. Most meat preparation surfaces (74%) were clean and free from blood, dust, and or meat debris. However, 26% (n = 52) of butcher shops had very dirty surfaces (i.e., blood and dried meat debris). In some butcheries, meat from different species was sold and displayed together, while in some, the meat types were mixed and placed in the same freezer together with offal (Figure 5). There was no significant association between any of the observed handling practices and microbial loads. Lastly, we observed that most of the butcheries in Kawangware were located along an open sewer line compared to the other study sites. And Huruma butcheries sourced their meat from multiple suppliers, combining them in their butcher shop.

In this study, we assessed the microbiological contamination of raw beef purchased from selected butcheries and observed the handling practices to identify the critical points of bacterial contamination. Butcher shops play a key role in the food chain and are critical control points to improve food safety and reduce the burden of foodborne diseases. Hygiene practices during the handling, storage, and sale of meat can influence the level of contamination of the meat (Wambui et al., 2017).

Out of the 200 meat samples, 196 (98%) were contaminated with bacteria at various levels. We found that 84% of meat samples had total coliform counts above the acceptable limit of 316 CFU/g (Commission Regulation, 2005; NDVQPH, 2010). Additionally, almost three quarters of our samples (72%) harbored E. coli at concentrations exceeding the acceptable levels (100 CFU/g) according to the Kenya Bureau of Standards (KEBS; KEBS, 2020). Meat above the acceptable microbiological limits for either coliforms or E. coli can have several negative consequences including foodborne diseases, especially if contaminated with known food-borne pathogens such as Salmonella, E. coli, Campylobacter, and Listeria. High bacterial loads accelerate meat spoilage and reduce shelf life resulting in economic losses to the butchery owners. The presence of E. coli and other coliforms in beef has been documented in previous studies in Kenya; E. coli loads found in this study were nearly the same as those found by Chepkemei et al. (2022) but higher than those isolated by Catherine et al. (2021). These findings are also like those of other studies where the bacteria found in meat exceeded acceptable levels (Jaja et al., 2018; Kassem et al., 2020; Zelalem et al., 2022).

Meat sold in Huruma and Kawangware was relatively more contaminated than other sites. It was observed next to the butcher shops in Kawangware, untreated sewage flowed openly along the streets. It is unclear if this directly had an impact on meat contamination but open sewage can increase vermin activity, and potentially can contaminate local water sources. If this water is used for washing meat, workers’ hands, shop surfaces or equipment, it can lead to contamination of meat with foodborne pathogens. Moreover, we frequently observed flies and cockroaches inside the butcher shops, which are known to carry a variety of pathogens and play a role in meat contamination. Studies have shown that flies can be vectors of foodborne pathogens such as E. coli and Salmonella, which can contaminate meat and cause food poisoning if consumed (Barreiro et al., 2013; Heilmann et al., 2017). Similar findings were found in other low- and middle-income areas of Nairobi (Kariuki, 2018; Maina et al., 2021). Lastly, beef from Huruma had relatively higher loads of E. coli as compared to the other sites. Here we noted that butcher shops sourced their meat from different abattoirs, which can affect contamination levels as it depends on factors such as hygiene practices of the abattoirs, transport conditions, and how meat is stored upon arrival. If meat from different abattoirs is mixed during storage, it can lead to cross-contamination (Rani et al., 2023).

Antibiotics are frequently used in livestock farms and antibiotic-resistant bacteria can be transferred to humans indirectly through ASFs. Between 9 and 35% of samples were contaminated with TET and CTX-resistant Enterobacteriaceae, respectively. We found more TET-resistant coliforms, which is expected as tetracycline is the most used antibiotic in animal production (WOAH, 2022; Mulchandani et al., 2023). Third generation cephalosporins are critically important antibiotics for humans and are also licensed for veterinary use (e.g., ceftiofur), but they are rarely used in animals in Africa (WOAH, 2022). The presence of CTX-resistant coliforms in meat is of clinical relevance, and could have originated from cattle or a result of human or environmental contamination during the slaughter, transport and storage processes (Mitman et al., 2022). Third generation cephalosporin resistant Enterobacterales is a critical group on the WHO global priority pathogens list of antibiotic-resistant bacteria as they can cause severe and often fatal infections (Shrivastava et al., 2018; WHO, 2024).

Close contact between the meat and the meat handler during retail operations highlights the importance of hand washing to prevent cross-contamination. Despite the existence of food safety regulations in Kenya, which include the requirement to have handwashing facilities (Kang’ethe et al., 2020; NFSP Draft, 2021; Sirma et al., 2023), most butcheries (72%) did not have hand-washing stations which could explain why most of the butcher attendants (85.4%) neither washed their hands before nor after handling raw meat.

Previous studies have shown various bacteria found under the fingernails of food handlers (Nel et al., 2004), reinforcing proper hand washing (Montville et al., 2002). We also noted that some meat handlers had visibly dirty hands and long, untrimmed fingernails, and did not wear gloves while handling meat. Mirembe (2002) found that hand-washing facilities were present in 76.7% of surveyed butcher shops in Uganda and Nepal showing that only 19% of the meat sellers washed their hands before and after handling meat (Bhattarai et al., 2017).

Personal protective equipment (PPE) including aprons, hairnets, and gloves is essential to prevent cross-contamination and the spread of pathogens while handling raw meat. Most attendants in our study did not wear PPE despite it being a requirement in Kenyan regulations (Government of Kenya, 2016). In addition, some attendants wore jewelry and watches while selling meat. Wearing jewelry during meat handling operations not only increases the presence of bacteria on hands but also reduces the effectiveness of hand washing (Lombar M et al., 2016). The proportion of butchery attendants who wore jewelry and who did not wear gloves while selling meat was comparable to the study by Siluma et al. (2023) and Azuamah et al. (2018). Moreover, handling money while selling meat using the same uncleaned hands was observed in most of the butcheries (91%) comparable to what (Chepkemoi et al., 2015; Subedi et al., 2022) found. Money is noxious for being contaminated with bacteria (Kuria et al., 2009) and concurrent handling of money and meat also poses a high risk of cross-contamination.

The Kenya Meat Control Act (chapter 256) stipulates that all equipment for preparing, handling, or storing meat should be kept clean (Government of Kenya, 2016). While most of the butcheries had clean equipment and meat preparation surfaces, in some butcher shops, meat was prepared on dirty surfaces, and others reused dirty equipment for cutting meat for subsequent customers. Meat preparation surfaces and equipment can harbor bacteria that can contaminate meat (Carrascosa et al., 2021). Therefore, ensuring the cleanliness of the meat preparation surfaces and the cutting equipment is key to improving meat microbial safety in butcheries.

Our study had some limitations such as: restricting sampling to beef filets only. Beef was found to be the dominant meat sold in butcher shops during the initial mapping exercise which was conducted before the study. We requested that the beef be cut into smaller pieces to mimic the usual consumer practice. However, butcher shops sold meat from other livestock species including offal, which were displayed side by side, and therefore contamination may have come from these other meat types. Offals can easily contaminated meat with Enterobacteriaceae from the gastrointestinal tract during slaughtering, dressing, evisceration and transportation and because of their nutritional content they promote the multiplication of these bacteria. Hence, selling of both offals and meat can give rise to cross-contamination in butcher shops especially if they are placed together or the same equipment is used (Fatena et al., 2013).

We found that 98% of the raw meat sold in peri-urban areas of Nairobi is contaminated with coliforms and E. coli above the accepted regulatory levels. We also observed poor meat handling practices among the butchery attendants which are known to affect the microbiological quality of meat. Despite the existence of food safety regulations, they appear to be poorly implemented. Public health authorities need to enforce the existing regulations to improve food safety in the beef supply chain.

Our study faced limitations. Initially, our sampling was confined to beef fillets, given that beef was the predominant meat available in the surveyed butcheries, as determined by the pre-study mapping exercise. Furthermore, the study specified cutting the meat into smaller pieces, mirroring customer practices. However, the display also featured meat from other species and offal alongside beef. The observed contamination might have originated from these additional meat types. Additionally, the potential sources of contamination include the cutting equipment, surfaces, water used in preparation, and the handlers’ hands.

Secondly, certain butcheries were observed storing leftover meat in the freezer overnight. Notably, some establishments practiced mixing different types of meat and offal during storage, potentially leading to cross-contamination. Limited resources also constrained the assessment of other potentially present bacteria. Finally, the antimicrobial susceptibility test was conducted to only two antibiotics, reflecting resource limitations.

This study found that most of the meat sold in peri-urban areas of Nairobi is contaminated with coliforms and E. coli above the accepted regulatory levels. The presence of cefotaxime-resistant Enterobacteriaceae albeit at low levels in raw meat, poses a threat to public health, as 3rd generation cephalosporins are critically important in human health. Poor meat handling practices were observed among the butchery attendants in peri-urban areas of Nairobi.

The appropriate authorities in the government enforce the application of Hazard analysis and critical control points (HACCP) principles along the beef supply chain. Regular basic and continuous meat hygiene training should be provided to the new and experienced meat handlers, respectively. More research should be done along the entire beef supply chain to determine the most likely sources of meat contamination.