Assessment of Hygiene Conditions in Sudanese Airlines Catering at Khartoum International Airport
Bibliographic record
Abstract
Background: Food safety has been recognized as a matter of importance to the airlines industry and airports must have the capacity to ensure a safe environment for passengers using point of entry facilities, including flight catering and other potential risks. The risk of food getting contaminated depends largely on the knowledge and practice of proper food hygiene measures among food handlers. The study aimed to assess the hygiene conditions in airlines catering services units at Khartoum Airport; to evaluate the level of knowledge and practice of food handlers towards food hygiene in addition to identify the microbial load on food handler’s hands.Methodology: Four airlines catering services units at Khartoum International Airport were studied. The data were collected by using structured questionnaire to assess food handler's knowledge onfood hygiene and their practices including 100 samples (56 samples from catering 1, 22 catering 2, 12 catering 3 and 10 samples from catering 4). Observational check list was used to assess the physical characteristics and hygienic situation in airlines catering premises and food handlers. Microbiological examinations used for Total Plate Count (TPC), isolate and identification Staphylococcus aureus, Escherichia coli and salmonella. Data were analyzed using the Statistical Package for Social Sciences (version 16.0).Results: The study showed that 56% of food handlers have higher secondary school certificate, 83% of food handlers knew causative agent of food borne disease,72% knew when washed their work surfaces and 72% knew how to care with open lesions during food handling. Analysis showed significant difference (p=0.023) between respondents’ knowledge and their educational level. More than half (58%) of food handlers did not report during illness; only 42% received training in food hygiene. seventy five percent of the catering managers were not trained on food safety management system. There was statistically significant difference between trained (professional) handlers and non-trained handlers with regard to food hygiene practices (P =0.038). Fifty percent of catering premises were in bad situation (ventilation, cleaning, lightening, pest control) and poor hand washing facilities; only 25% of these catering have quality control system. The highest bacterial count from the hands samples was 8.5x106 CFU /mland the lowest 1.2x106 CFU /ml; 54.5% of sample tested positive for E. coli; 72.7% for S. aureus and 36.6% for salmonella from food handler’s hands.Conclusion: This study revealed poor sanitary conditions in airlines catering, and poor food hygiene practices of some handlers indicating higher probability of food being contaminated before service. The occurrence of indicator microorganisms in most of the hand samples indicating a need for improvement in the environment hygiene and sanitary facilities. The study recommends hygiene education to improve the knowledge and practices of food handlers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".