Food Handling Practices Among Food Businesses in Jigjiga, Eastern Ethiopia, During the COVID-19 Pandemic: Cross-Sectional Study
Notice bibliographique
Résumé
Background: The COVID-19 pandemic has posed significant challenges to food safety practices globally, profoundly affecting the knowledge, attitudes, and practices of both food handlers and consumers. Objective: This study aimed to investigate food safety knowledge and practices of food handlers in the context of COVID-19. Methods: A cross-sectional study was conducted in Jigjiga during the pandemic. A total of 384 food handlers were surveyed using a structured questionnaire and an observational checklist. The questionnaire assessed knowledge of COVID-19 symptoms, transmission, and prevention measures, and the checklist evaluated food safety practices and the implementation of COVID-19 prevention measures in food businesses. Categorical variables (eg, sufficient vs insufficient COVID-19 knowledge and good vs poor food-safety practice) were summarized as frequencies and percentages. Pearson chi-square test was used to assess differences in these binary outcomes across demographic and other categorical subgroups (eg, sex, age category, education level, and source of COVID-19 information). A P value <.05 was considered statistically significant. Results: A total of 384 food handlers were approached, and all responded (response rate=100%). The majority of participants (276/384, 71.9%) had received food hygiene training, and the main source of COVID-19 information was government news media (170/384, 44.3%). The majority of respondents (264/384, 68.8%) correctly identified the key COVID‑19 symptoms, and 52.1% (200/384) accurately understood that respiratory droplets from coughs or sneezes drive transmission. However, less than 50% of participants consistently practiced preventive measures such as avoiding handshaking, frequently sanitizing food contact surfaces, and reminding customers to follow physical distancing. Participants who obtained information from government sites and the media had sufficient knowledge compared to other participants (P=.07). Females (P=.03), younger adults (P=.03), married individuals (P=.04), those with secondary education (P=.014), and those who had received previous food safety training (P=.004) demonstrated better food handling practices than their counterparts. Furthermore, 61.4% (236/384) of food businesses had handwashing facilities at the entrance, 70.2% (270/384) implemented crowd control measures, and 56.1% (215/384) used floor markings to facilitate physical distancing. However, only 57.7% (221/384) of food establishments routinely cleaned and disinfected their work surfaces and touch points. Conclusions: These findings highlight the need for targeted education and training interventions to improve food handlers' knowledge and practices, particularly during the COVID-19 pandemic.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».