Assessment of Microbial Load and Aflatoxin Levels in Suya Powder from Selected Khebab Vendors in Sunyani Municipality,Ghana

Abstract

Suya powder, a spice mixture widely used in West African cuisine, may harbor microbial and mycotoxin contamination, posing potential public health risks. To evaluate food safety implications, this study assessed microbial load and aflatoxin levels in suya powder from khebab vendors in Sunyani Municipality, Ghana. A total of 85 samples were collected from 11 locations and analyzed using standard microbiological methods and high-performance liquid chromatography (HPLC) for microbial enumeration and aflatoxin quantification, respectively. The microbiological analysis revealed varying levels of coliform bacteria across locations, with concentrations ranging from undetectable levels to 3.8 log CFU/g. Estate exhibited the highest contamination, with fecal and total coliform counts reaching 3.7 and 3.8 log CFU/g, respectively, while New Dormaa and UENR/Ministries Area showed no detectable levels. Escherichia coli was detected in ABM, ASF, and EST locations, with counts ranging from 0.8 to 1.2 log CFU/g. Aflatoxin analysis revealed that 5 locations had detectable contamination levels, with predominant G-type aflatoxins. Although aflatoxin levels were generally low, likely due to the roasting process used in suya powder production, their presence still indicates potential food safety concerns. This study suggests the need for implementing vendor education programs on proper hygiene practices, introducing standardized moisture-controlled storage containers, and establishing regular monitoring protocols by local health authorities to ensure the safety of suya powder.

Plain Language Summary

Food Safety Risks in Popular Spice Mixtures: Measuring Bacteria and Toxins in Suya Powder from Street Food Vendors in Ghana

This study evaluated microbial and aflatoxin contamination in suya powder, a popular spice blend used by khebab vendors across Sunyani Municipality, Ghana. Analysis of 85 samples revealed variable contamination levels, with total coliform counts ranging from undetectable to 3.8 log CFU/g, though Escherichia coli was absent. Detectable aflatoxin levels (predominantly G-type variants) remained below EU regulatory thresholds, likely due to thermal degradation during traditional peanut roasting. However, the persistent contamination poses health risks, particularly for children, as evidenced by elevated hazard indices. Spatial contamination patterns correlated with environmental factors including high temperatures (26°C-30°C), humidity fluctuations, and suboptimal storage conditions near drainage systems. These findings highlight the need for improved handling practices, moisture-controlled storage solutions, and regular monitoring to ensure food safety in Ghana’s informal street food sector. The study provides critical baseline data for developing targeted interventions while suggesting future research directions including seasonal variation assessments and evaluation of cost-effective preservation methods suitable for local contexts.

Keywords

suya powder microbial load aflatoxins food safety mycotoxins

Background

Food safety remains a critical public health concern in developing nations, particularly regarding traditional food additives and seasonings widely used in local cuisine.¹ Suya powder, a complex spice mixture predominantly composed of ground roasted groundnut (Koli koli), peppers, and various aromatics, plays an integral role in West African cuisine, especially in the preparation of popular grilled meat products known as khebabs.² Vendors typically offer this seasoning as a complementary condiment, either packaged separately or sprinkled directly on meat products to enhance their flavor.

Ghana’s informal food sector has significant economic importance, serving as a crucial ingredient for thousands of small-scale food vendors and contributing substantially to local food commerce.³ However, foodborne illnesses associated with contaminated spice products, which are traded under the informal sector, continue to be a significant public health concern in Ghana.⁴This has called for the need for regulatory oversight and public education on safe food handling practices to mitigate these risks.⁵

The safety of suya powder, primarily used as the main spice in making suya meat (a type of grilled meat), is compromised by microorganisms.⁶ The Codex Alimentarius Commission establishes a maximum limit of 10 μg/kg for total aflatoxins in ready-to-eat spices.⁷ The microbiological profile of suya powder presents equally severe concerns. According to international standards, ready-to-eat spices should maintain total bacterial counts below 1.04 × 10² CFU/g.⁸ Studies have shown that suya is often contaminated with various bacteria, including Staphylococcus spp., Escherichia coli, Bacillus sp., and Salmonella, which are prevalent in suya samples from Nigeria.⁶ In Benin City, Nigeria, bacterial counts in suya were significantly higher, with some samples reaching 4.00 × 10⁹ CFU/g, indicating severe contamination due to poor hygiene practices.⁹ Contamination often arises from unhygienic handling, such as bare-hand contact and exposure to environmental pollutants.⁶ Spices used in suya preparation also contribute to bacterial contamination, with total plate counts ranging from 1.0 × 10³ to 1.6 × 10³ CFU/g in suya spices.¹⁰

Environmental conditions and storage practices create a complex challenge for food safety management.¹⁰ These traditional storage practices create an ideal environment for microbial growth and the production of mycotoxins. Previous intervention attempts focusing on improved storage containers showed limited success, with contamination rates reducing by only 25% without accompanying vendor education.¹¹

The regulatory landscape further complicates food safety management. While Ghana has established clear guidelines through its Standards Authority,¹² compliance remains low.¹³ Implementation challenges include inadequate enforcement resources, limited testing facilities, and resistance to changing traditional practices. Recent initiatives combining vendor education with subsidized storage equipment in pilot markets showed promising results, reducing contamination rates.¹⁴

While previous studies have examined either microbial contamination or aflatoxin levels in spice products separately,^4,11 there is a critical gap in understanding their concurrent occurrence in suya powder, particularly in Ghana’s informal food sector. This study addresses this gap by providing an assessment of both microbial and aflatoxin contamination in suya powder within a secondary city context, establishing baseline data for the Sunyani Municipality, examining the relationship between processing conditions and contamination levels, and evaluating the effectiveness of current vendor practices in maintaining food safety.

Given these challenges, this study aimed to evaluate the safety profile of suya powder in the Sunyani municipality by quantifying the microbial load, aflatoxin levels and assessing the risk associated with the aflatoxin levels among Khebab vendors.

Methods

Study Area and Sample Size Determination

The study was conducted in Sunyani Municipality, the capital of the Bono Region of Ghana. Sunyani Municipality lies between latitude 7°20’N and 7°05’N and longitude 2°30’W and 2°10’W. The municipality covers an approximate land area of 829.3 km² and is approximately 400 m above sea level. It experiences a tropical climate characterized by moderate temperatures.¹⁵ The area experiences 2 distinct rainfall seasons: a primary season from April to July and a minor season from September to October. Annual rainfall ranges from 1000 to 1400 mm, while relative humidity varies from 70% to 100% during the rainy season and 60% to 70% in the dry season.¹⁵

According to the 2021 Population and Housing Census, Sunyani Municipality has a population of approximately 147,301 with an annual growth rate of 2.3%. The municipality serves as a significant commercial center for the middle belt of Ghana, with street food vending being a significant economic activity. A preliminary survey identified approximately 65 khebab vendors operating within the municipality, predominantly concentrated around major commercial areas, educational institutions, and entertainment spots. These vendors regularly use suya powder as a critical seasoning ingredient in their khebab preparation, typically sourced from local spice traders. The distribution and locations of these khebab vendors informed the sampling strategy for the study.

Calculation of sample size using the Yamane’s Formula:¹⁶

n = \frac{N}{(1 + N {(e)}^{2})}

(1)

Where:

n = Sample size required

N = Total population size (108 khebab vendors)

e = Level of precision/margin of error (usually 0.05 for 95% confidence level)

Thus

n = 108 / (1 + 108(0.05) ²)

For proportional allocation in each zone

n h = (\frac{N h}{N}) \times n

(2)

where:

nh = sample size for each area

Nh = population of each area

N = total population (108)

n = total sample size (85)

Sample Collection

Eighty-five suya powder samples were collected from khebab vendors across 11 zones, as seen in Table 1 in the Sunyani Municipality between November 2023 and February 2024. The samples were collected using a stratified random sampling technique, with proportional allocation based on the vendor population in each zone. Approximately 100 g of suya powder was collected aseptically from each selected vendor using sterile sampling bags. Samples were collected during peak business hours (4:00 PM-10:00 PM) when the suya powder was actively used for khebab preparation. Samples were transported in sterile ice-packed containers maintained at 4°C. All sampling equipment (sterile spatulas, sampling bags, ice packs, and sample containers) was sterilized by autoclaving at 121°C for 15 minutes. The time between collection and analysis was standardized to 4 hours maximum. Vendor handling practices were documented using a structured observation checklist covering personal hygiene, storage conditions, and handling procedures.

Table 1.

Distribution of Khebab Vendors and Sample Size Allocation in Major Zones of Sunyani Municipality.

Location	Location code	Total vendors (Nh)	Percentage (%)	Sample size (nh)
Central Business	CBS	25	23.1	20
Area 2 Junction	ART	15	13.9	12
Fiapre Road Stretch	FST	10	9.3	8
UENR/Ministries Area	UMS	8	7.4	6
Victoria Park Area	VCT	7	6.5	5
Abesim	ABM	12	11.1	9
New Dormaa	NDM	9	8.3	7
Baakoniaba	BKA	8	7.4	6
Penkwase	PKS	5	4.6	4
Estate	EST	4	3.7	3
Asufufu	ASF	5	4.6	4
Total		108	100.0	85

Sampling Strategy Implementation

The stratified random sampling was implemented through a systematic approach. First, the municipality was divided into 11 zones based on commercial activity density, and the vendor population in each zone was mapped using GPS coordinates, as shown in Figure 1. Sample size allocation was proportional to vendor density to ensure representative sampling. Vendors were assigned unique identification numbers within each zone, and selections were made using a random number generator. Selected vendors were then verified for active operation before final inclusion in the study.

Figure 1.

Spatial distribution of sampling locations in Sunyani Municipality-Ghana.

Quality Control and Sample Handling

Additional quality control measures included positive and negative controls for each batch of microbial analysis, duplicate plating for each sample, and regular equipment calibration. Recovery studies were conducted using spiked samples for aflatoxin determination, and matrix-matched calibration curves were employed. Internal quality control samples were analyzed every 10 samples, and the laboratory participated in proficiency testing programs to ensure analytical accuracy.

Analytical Methods

Microbiological Analysis

Ten grams of each suya powder sample was suspended in 90 mL of sterile peptone water (0.1%) and homogenized using a laboratory blender for 2 minutes. From this initial suspension, sequential decimal dilutions were prepared up to 10⁻⁵. Bacteria enumeration was conducted using the pour plate technique, which involves inoculating 0.1 mL of serially diluted aliquot unto plate count agar (Oxoid, Cambridge, UK) and incubating at 35ºC for 24 hours. The aliquots were further inoculated into MacConkey broth (Oxoid, Cambridge, UK) tubes containing Durham tubes and incubated at 35ºC to determine the number of fecal coliforms based on the mean probable number (MPN) method. Using a sterile inoculation loop, positive tube content was inoculated into cultured tryptophan broth supplemented with Kovac’s reagent to detect the presence of Escherichia coli. The presence of Escherichia coli was confirmed by growth on eosin methylene blue (EMB) agar, forming a green metallic sheen colony.¹⁷

Our analysis focused on total coliforms, fecal coliforms, and Escherichia coli as these 3 indicators provide the most relevant information for assessing food safety risks in ready-to-eat foods.¹⁸ This approach effectively distinguishes between general environmental contamination and specific fecal contamination sources, providing sufficient data for public health risk assessment without requiring further bacterial speciation.^19,20

Aflatoxin Extraction

Aflatoxin was extracted using QuEChERS (Quick Easy Cheap Effective Rugged Safe) methods²¹ with slight modifications of acetonitrile: acetic acid v/v (9:1) as the extraction solution and additional agitation steps. Samples were homogenized using a mixer blender. A weight of 2 g of sample was transferred into a 50 mL centrifuge tube, 5 mL of deionized water was added and allowed to stand for 15 minutes. Afterwards, 5 mL of the extraction solution was added. The resultant mixture was vortexed using the Genie Vortex machine for 3 minutes and agitated using Ohaus Orbital Shaker at 250 rpm for 15 minutes. A mass of 2.0 g of anhydrous MgSO₄ and 0.5 g of NaCl were added to the mixture, vortexed for 1 minute, and agitated at 250 rpm for 5 minutes. The tube was centrifuged for 5 minutes at 4000 rpm, and the upper organic layer was filtered through a 0.45 µm nylon syringe before injection. A volume of 20 µL of the filtered extract was injected into the high-performance liquid chromatography (HPLC).

HPLC Aflatoxin Determination

HPLC analysis was carried out based on AOAC Official Method 2005.08 (AOAC, 2006) as used by Asare Bediako et al.²² The HPLC system consisted of an Agilent 1200 Quaternary Pump with a fluorescence detector (excitation wavelength: 333 nm, emission wavelength: 477 nm) equipped with a Nucleodur® plus C18 column (4.6 mm × 150 mm, 5 µm). The mobile phase consisted of water:methanol:acetonitrile (60:20:20, v/v) at a flow rate of 1 mL/minute with column temperature maintained at 40°C. Post-column derivatization was achieved using a Photochemical Reactor for Enhanced Detection (PHRED) (LCTech UVE). The injection volume was 20 μL, and the total run time was 20 minutes.

Aflatoxin standards (B₁, B₂, G₁, and G₂) were prepared at concentrations of 0.1, 0.5, 1.0, 5.0, and 10.0 ng/mL to create calibration curves. The limit of detection (LOD) was 0.05 ng/g, and the limit of quantification (LOQ) was 0.15 ng/g. The recovery rates for aflatoxins ranged from 92% to 96%.

Quality Control and Sample Handling

Control samples were prepared using certified reference materials for microbial and aflatoxin analyses. All samples were stored in sterile containers at 4°C and analyzed within 24 hours of collection to maintain sample integrity. Method validation was performed using spiked samples with known concentrations of target organisms and aflatoxins, achieving 95% to 98% recovery rates for bacterial counts and 92% to 96% for aflatoxins. Control samples were prepared using certified reference materials (CRM-AFM-001, LGC Standards, UK) for microbial and aflatoxin analyses.

Risk Analysis

Aflatoxins are known carcinogens, primarily affecting the liver, with no established safe threshold level. Therefore, a cancer risk assessment approach using cancer slope factors (CSF) was employed rather than reference doses, following internationally accepted methodologies.

E D I (m g / k g b w / d a y) = \frac{C \times I R}{B w}

(3)

Where EDI expressed in ng/kg bw/day²³ is the estimated daily intake, IR is the daily intake rate of suya powder (0.00358 kg/day) taken from a secondary data, GEMs/food consumption cluster diets.²⁴ Although this value may be considered high, the results indicate little to no risk at such a level, and they remain valid even at lower intake levels. C is the concentration of Aflatoxin in the food, and BW is the body weight for adults and children, taken as 60 kg and 24 kg, respectively.²⁵

The incremental lifetime cancer risk (ILCR) was then calculated using:

I L C R = E D I \times C S F \times A F \times 10^{- 6}

(4)

Where:

CSF is the cancer slope factors which is 0.0305 (mg/kg bw/day)⁻¹ ^26,27 for hepatitis B surface antigen (HBsAg)-negative individuals and 0.269 (mg/kg bw/day)⁻¹ for HBsAg-positive individuals.²⁸ The prevalence of HBsAg-positive individuals in Ghana is estimated at 8.36%,²⁸ which significantly impacts the overall population risk assessment.

The relative potencies of different aflatoxin types compared to AFB1 were considered as: AFG1 (0.1), AFG2 (0.1), and AFB2 (0.1) based on comparative toxicity studies.²⁹

Additionally, the Margin of Exposure (MOE) approach was used to assess the level of public health concern:

M O E = \frac{B M D L 10}{E D I}

(5)

Where BMDL10 is the benchmark dose lower confidence limit for a 10% increase in cancer incidence, established as 400 ng/kg bw/day for aflatoxins.³⁰

Statistical Analysis

One-way ANOVA was performed to compare microbial loads and aflatoxin levels across locations, followed by Tukey’s post-hoc test (P < .05) for multiple comparisons. Significant differences were observed between high-contamination locations (EST, ASF, ABM) and low-contamination locations (P < .001). Pearson correlation analysis examined relationships between different bacterial types and aflatoxin levels with significance established at P < .05.

Results and Discussion

Distribution and Prevalence of Coliform Bacteria Across Sampling Locations

The microbiological analysis across 11 sampling locations revealed a heterogeneous distribution of coliform bacteria, with concentrations ranging from undetectable levels to 3.8 log CFU/g from Figure 2. Escherichia coli was detected in 3 locations (ABM, ASF, and EST) with counts ranging from 0.8 to 1.2 log CFU/g. According to Dela et al.³¹ coliform bacteria above certain thresholds indicate potential fecal contamination and necessitate immediate corrective actions to identify and eliminate contamination sources.

Figure 2.

Mean bacterial counts (log CFU/g) in samples collected from different locations.

Location EST exhibited the highest contamination levels, with fecal and total coliform counts reaching 3.7 and 3.8 log CFU/g, respectively. Similarly elevated levels at ASF followed this (fecal: 3.6 log CFU/g; total: 3.3 log CFU/g) and ABM (fecal: 3.0 log CFU/g; total: 3.4 log CFU/g). The potential contributors to elevated coliform counts, including inadequate sanitation procedures, cross-contamination during handling, and suboptimal storage conditions.³² Fecal and total coliforms at these locations suggest systemic hygiene challenges requiring comprehensive intervention strategies.

Locations NDM and UMS showed no detectable levels of coliform bacteria shows that stringent hygiene protocols and appropriate environmental controls can effectively minimize bacterial contamination. The selective presence of bacterial types at specific locations–exclusively fecal coliforms at VCT and only total coliforms at PKS–presents an intriguing pattern that warrants further investigation. This selective distribution might reflect location-specific environmental conditions or varying contamination sources affecting bacterial survival and growth.³¹

The relationship between fecal and total coliform counts demonstrated interesting patterns, with total coliform counts generally equivalent to or marginally exceeding fecal coliform counts where both were detected. Recent studies have emphasized that the presence of any coliform bacteria in food processing environments necessitates a thorough review of existing hygiene protocols and the implementation of enhanced preventive measures.^8,12,33

Our emphasis on Escherichia coli as a specific indicator within the coliform group is based on its established role as the primary indicator of fecal contamination in food safety assessments. While other coliforms may originate from various environmental sources, Escherichia coli indicates explicit potential contamination from human or animal fecal matter, presenting a more direct health risk. These findings underscore the importance of regular microbiological monitoring and the need for location-specific interventions to maintain optimal hygiene standards. Future investigations should focus on identifying specific environmental and operational factors contributing to the observed variations in bacterial contamination levels across locations.

Distribution of Aflatoxin Types in Suya Powder Samples

The distribution and quantification of aflatoxins in suya powder samples across 11 Sunyani Municipality vending locations revealed distinct spatial contamination patterns. The analysis focused on 4 major aflatoxins (G₁, G₂, B₁, and B₂), demonstrating significant variation in presence and concentrations across sampling locations. These findings align with previous studies indicating that aflatoxin contamination is influenced by factors such as environmental conditions, agricultural practices, and storage methods.^1,14,34

Out of the 11 surveyed locations, 5 showed detectable levels of aflatoxin contamination (PKS, ASF, ABM, ART, BKA), while 6 locations (VCT, EST, FST, CBS, NDM, and UMS) exhibited no measurable presence of any aflatoxin type. The contaminated locations displayed distinct aflatoxin profiles, with G-type aflatoxins emerging as the predominant contaminants. The predominance of G-type aflatoxins (G₁ and G₂) aligns with the known ecology of Aspergillus parasiticus, which predominantly produces these aflatoxins.³⁴ This suggests that the suya powder samples may have been contaminated by this fungus, which thrives in warm and humid conditions common in this region. Conversely, B-type aflatoxins (B₁ and B₂) indicate contamination by Aspergillus flavus, known to produce both B and G aflatoxins.⁷

The data presented in Table 2 shows that PKS and ABM locations exhibited the highest levels of G₂ contamination, with concentrations of 1.213 ± 0.026 and 1.143 ± 0.201 ng/g, respectively. The low standard deviation at PKS (±0.026 ng/g) suggests highly consistent contamination conditions. In contrast, the higher variation at ABM (±0.201 ng/g) indicates more heterogeneous contamination patterns, possibly due to varying exposure to the contamination source or differences in handling practices.⁷ The ASF location demonstrated moderate G₂ contamination (0.574 ± 0.104 ng/g), with intermediate variability in concentration levels.

Table 2.

The Mean Concentration of Aflatoxins (ng/g) in Suya Powder Samples from Different Vending Locations in Sunyani Municipality, Ghana.

Location	Aflatoxins (ng/g)
Location	G2	G1	B2	B1
PKS	1.2125 ± 0.026	0	0.375 ± 0.103	0
VCT	0	0	0	0
ASF	0.5735 ± 0.104	0	0	0
EST	0	0	0	0
ABM	1.143 ± 0.201	0	0	0
ART	0	1.449 ± 0.546	0.231 ± 0.018	0
FST	0	0	0	0
CBS	0	0	0	0
BKA	0	1.194 ± 0.151	0	0
NDM	0	0	0	0
UMS	0	0	0	0

G1, G2, B1, B2 = Aflatoxin types; Values represent mean ± standard deviation (n = 3); ND = Not detected.

An interesting pattern emerged in the distribution of G₁ aflatoxin, which was detected at significant levels in ART (1.449 ± 0.546 ng/g) and BKA (1.194 ± 0.151 ng/g) locations. The substantial standard deviation at ART suggests considerable spatial heterogeneity in contamination levels, possibly indicating inconsistent handling practices or variable environmental conditions.¹⁴ The lower concentration of aflatoxins in suya powder, as seen in Table 2, can be attributed to processing techniques such as roasting.³⁵ Roasting is a thermal processing technique that reduces aflatoxin contamination by breaking down the chemical structure of the toxin. Studies have shown that roasting at temperatures around 200°C can achieve a 99% reduction in aflatoxin levels.^14,34 The effectiveness of roasting depends on several factors, including temperature, duration, and the roasting method (e.g., dry roasting vs. oil roasting). For example, peanuts roasted at 140°C for 40 minutes showed a reduction of 58.8% in aflatoxin B₁ (AFB₁) levels, while roasting at 150°C for 30 minutes resulted in a 70% reduction.³⁵ While roasting is effective, it may not eliminate all aflatoxins, especially if initial contamination levels are high.³⁴ Additionally, roasting can lead to the formation of other potentially harmful compounds, such as acrylamide, which requires careful control and monitoring.³⁶

Comparison with International Standards

The observed coliform levels in locations EST, ASF, and ABM (3.7-3.8 log CFU/g) exceeded the World Health Organisation (WHO) recommended limit of 3.0 log CFU/g for ready-to-eat foods. However, aflatoxin levels remained below the European Union maximum limit of 4 ng/g for spices. Seasonal analysis revealed higher contamination levels during November-December (mean: 2.8±0.3 log CFU/g) compared to January-February (mean: 1.9 ± 0.2 log CFU/g), possibly due to higher humidity levels.³⁷

Relationship Between Microbial and Aflatoxin Contamination

Correlation analysis revealed a moderate positive correlation (r = 0.48, P = .037) between total coliforms and aflatoxin G2. In contrast, Escherichia coli and aflatoxin G2 and B2 were negatively associated, suggesting minimal commonality of factors favoring bacterial growth and aflatoxin production in suya powder, as shown in Table 3.

Table 3.

Correlation Matrix of Aflatoxins and Bacterial Numbers (log CFU/g).

Parameter	Fecal coliforms	Total coliforms	Escherichia coli	G2	G1	B2
Fecal coliforms	1	0.67	0.96	−0.15	0.31	−0.35
Total coliforms	0.67	1	0.67	0.48	0.31	0.31
Escherichia coli	0.96	0.67	1	−0.15	0.31	−0.35
G2	−0.15	0.48	−0.15	1	−0.34	0.38
G1	0.31	0.31	0.31	−0.34	1	0.56
B2	−0.35	0.31	−0.35	0.38	0.56	1

Green shading = statistically significant positive correlation (p < 0.05); red/orange shading = statistically significant negative correlation (p < 0.05); no shading (white) = non-significant correlation (p > 0.05). All other correlations were not statistically significant (p > 0.05) – no shading.

The strong correlation between fecal coliforms and Escherichia coli (r = 0.96) indicates a clear relationship between these indicators, which is expected as Escherichia coli is a fecal coliform. This strong association suggests familiar sources of contamination, likely through poor handling practices or inadequate sanitation.³⁵ The moderately strong correlation between total and fecal coliforms (r = 0.67) aligns with their taxonomic relationship, indicating that non-fecal coliforms contribute significantly to the total coliform population.³⁸

The moderate positive correlation between total coliforms and aflatoxin G2 (r = 0.48) suggests that environmental conditions supporting bacterial growth may also favor G2 production. However, the negative correlation with fecal coliforms (r = −0.15) indicates that factors promoting fecal coliform survival might inhibit G2 production. This could be related to competition for nutrients, pH changes induced by bacterial metabolism, fluctuations in water activity, and metabolic byproducts that affect fungal growth.³⁹

The moderately strong correlation between total and fecal coliforms (r = 0.67, P = .023, 95% CI [0.31, 0.86]) aligns with their taxonomic relationship, indicating that non-fecal coliforms contribute significantly to the total coliform population.³⁸ The moderate positive correlation between total coliforms and aflatoxin G2 (r = 0.48, P = .037, 95% CI [0.09, 0.74]) suggests that environmental conditions supporting bacterial growth may also favor G2 production.¹ However, the negative correlation with fecal coliforms (r = −0.15, P = .063, 95% CI [−0.32, 0.03]) was not statistically significant.

The varying correlation suggests different optimal conditions for bacterial growth versus aflatoxin production. However, the negative correlations between specific parameters might indicate that processing conditions affecting 1 type of contamination could have opposite effects on others.

Risk Assessment of Aflatoxin Concentration in Suya Powder

The mean concentrations of aflatoxins detected across sampling locations were calculated to be 0.976 ng/g for AFG2, 1.322 ng/g for AFG1, 0.303 ng/g for AFB2, and 0 ng/g for AFB1. These values were used to calculate the EDI, ILCR, and MOE for both adults and children in Table 4.

Table 4.

Risk Assessment of Aflatoxins in Adults and Children.

Parameter	AFG2	AFG1	AFB2	AFB1
Mean concentration(ng/g)	0.976	1.322	0.303	0
EDI (ng/kg bw/day)
Adult	0.058	0.079	0.018	0
Children	0.146	0.197	0.045	0
ILCR (HBsAg-) (×10⁻⁷)
Adult	1.77	2.41	0.55	0
Children	4.45	6.01	1.37	0
ILCR (HBsAg+)(×10⁻⁷)
Adult	15.6	21.3	4.84	0
Children	39.3	53.0	12.1	0
MOE
Adult	6897	5063	22,222	0
Children	2740	2030	8889	0

The cancer risk assessment revealed that the incremental lifetime cancer risk (ILCR) from aflatoxin exposure through suya powder consumption ranges from 0.55 × 10⁻⁷ to 2.41 × 10⁻⁷ for HBsAg-negative adults and 1.37 × 10⁻⁷ to 6.01 × 10⁻⁷ for HBsAg-negative children. For the more vulnerable HBsAg-positive individuals, the cancer risk increases significantly to 4.84 × 10⁻⁷ to 21.3 × 10⁻⁷ for adults and 12.1 × 10⁻⁷ to 53.0 × 10⁻⁷ for children.

According to international risk management guidelines, cancer risks below 1 × 10⁻⁶ are generally considered negligible, while risks between 1 × 10⁻⁶ and 1 × 10⁻⁴ warrant attention but may be tolerable in certain contexts.^30,40 Based on these criteria, the cancer risks for HBsAg-negative individuals fall within acceptable limits. However, for HBsAg-positive children exposed to AFG1, the risk (5.30 × 10⁻⁶) approaches levels of concern.

The MOE values ranged from 5063 to 22,222 for adults and 2030 to 8889 for children,³⁰ suggests that MOE values less than 10,000 for genotoxic carcinogens indicate a potential public health concern. While AFB2 exposure in adults yielded MOE values above this threshold, exposure to AFG1 and AFG2 resulted in MOE values substantially below 10,000 for both adults and children, with children’s values being particularly low (2030 for AFG1).

These findings indicate that while the overall cancer risk from aflatoxin exposure through suya powder consumption is relatively low for the general HBsAg-negative population, children and individuals with hepatitis B infection face higher risks that warrant attention and mitigation efforts. The MOE analysis further supports this conclusion, particularly highlighting the potential concern for AFG1 exposure in children, with an MOE of only 2030, significantly below the threshold of 10,000 considered necessary for public health protection.

The observed pattern of G2 dominance in both exposure and risk metrics presents an interesting deviation from typical aflatoxin profiles reported in the literature. While most studies,^36,41 report B1 as the predominant concern, our findings suggest a shift in risk patterns that may be specific to the processing conditions or ingredients used in suya powder production. This variation could be attributed to the specific fungal strains present in the production environment or the impact of processing methods on aflatoxin stability.

From a public health perspective, these findings necessitate a nuanced approach to risk management. While the overall risk levels appear manageable, children’s consistently lower safety margins warrant special consideration. This aligns with recent recommendations by the WHO regarding age-specific risk assessment protocols for food contaminants. The absence of B1, while positive, should not lead to reduced vigilance, as aflatoxin profiles can shift significantly based on environmental and storage conditions.

The risk assessment data support the implementation of targeted control measures, particularly for products commonly consumed by children. This approach is consistent with recent risk management frameworks proposed by,⁴² who advocate for population-specific safety thresholds and control measures. Children’s higher vulnerability to G2 exposure suggests the explicit need for modified processing or storage protocols.

These findings have significant implications for regulatory frameworks and monitoring programs. While current exposure levels may be acceptable based on adult population standards, the lower safety margins for children suggest more stringent controls.

Study Limitations

This study was conducted during a single season (November-December) and may not represent year-round contamination patterns. Resource constraints limited the analysis of other mycotoxins and bacterial species. While this study focused primarily on coliform bacteria and aflatoxins, future research should consider expanding the analysis to include other significant pathogens such as Salmonella species, Staphylococcus aureus, Bacillus cereus, and Listeria monocytogenes. Extending the mycotoxin profile to include ochratoxin A, deoxynivalenol, zearalenone, and fumonisins would provide a more comprehensive assessment of food safety risks.

Another limitation of this study is the lack of direct fungal isolation and enumeration from the suya powder samples. A direct correlation between fungal loads, particularly Aspergillus flavus and Aspergillus parasiticus, and aflatoxin levels would have provided valuable insights into the contamination dynamics. Future studies should incorporate mycological analysis alongside mycotoxin quantification and a longitudinal study to establish these comprehensive insights and relationships more conclusively.

Conclusion

The study revealed significant variations in microbial contamination and aflatoxin levels across different vending locations in the Sunyani Municipality. Microbiological analysis showed that coliform bacterial counts ranged from undetectable levels to 3.8 log CFU/g, with EST, ASF, and ABM locations exhibiting the highest contamination levels. The presence of Escherichia coli in 3 locations (ABM, ASF, and EST) is concerning and indicates fecal contamination. Aflatoxin analysis indicated that 5 out of 11 locations had detectable contamination levels, with G-type aflatoxins being the most prevalent. PKS and ABM showed the highest G₂ contamination, while ART and BKA exhibited significant G₁ levels. The generally low aflatoxin levels, likely due to processing techniques such as roasting, still raise concerns about food safety.

Based on these findings, several recommendations are proposed to address contamination issues. Implementing comprehensive vendor education programs focusing on proper food handling, hygiene protocols, and storage conditions is crucial. Additionally, introducing standardized storage containers with moisture control capabilities can minimize microbial growth and aflatoxin production. Local health authorities should establish regular monitoring programs to assess contamination levels and develop a certification system for vendors who consistently meet safety standards. Support should be provided for improved vending facilities with appropriate storage conditions and basic hygiene infrastructure. Continued research, collaboration among stakeholders, and development of practical, illustrated guidelines in local languages will ensure sustainable improvements in food safety for suya powder in the Sunyani Municipality. Future research directions should include longitudinal studies across seasons, multi-region comparative analyses, cost-benefit evaluations of interventions, and investigation of alternative preservation methods suitable for local conditions.

Supplemental Material

sj-docx-1-ehi-10.1177_11786302261418385 – Supplemental material for Assessment of Microbial Load and Aflatoxin Levels in Suya Powder from Selected Khebab Vendors in Sunyani Municipality, Ghana

Supplemental material, sj-docx-1-ehi-10.1177_11786302261418385 for Assessment of Microbial Load and Aflatoxin Levels in Suya Powder from Selected Khebab Vendors in Sunyani Municipality, Ghana by Afia Sakyiwaa Amponsah, Emmanuel Tetteh-Doku, Barikisu Mohammed, Moses Kwaku Golly and Agyei-Poku Belinda in Environmental Health Insights

Footnotes

Author Contributions

All the authors contributed equally to the research and writing of the article. All authors have read and approved the final manuscript for publication.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data are available upon request from the corresponding author.

Supplemental Material

Supplemental material for this article is available online.

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