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Multilevel linear regression analysis reveals key factors affecting food safety practices in households.
The total weighted sample included in this analysis was 62,432,197. Model with the lowest DIC, AIC and BIC values was selected as the best-fitting model. Safe food handling practice among households was 42.4%. Being completed primary school, secondary/vocational education, and university-level education had higher safe food handling practices by 0.21 (95% CI: 0.10, 0.32), 0.49 (95% CI: 0.36, 0.63), and 0.84 (95% CI: 0.64, 1.05), respectively. Working in government, the private sector, self-employed, and retired had significantly higher safe food handling practices by 0.28 (95% CI: 0.05, 0.51), 0.45 (95% CI: 0.17, 0.72), 0.34 (95% CI: 0.14, 0.54), and 0.35 (95% CI: 0.07, 0.64), respectively. Being poorer, middle, richer, and richest wealth index had significantly higher safe food handling practices by 0.33 (95% CI: 0.16, 0.50), 0.52 (95% CI: 0.33, 0.71), 0.84 (95% CI: 0.60, 1.08), and 1.37 (95% CI: 1.09, 1.65), respectively. Being married, female respondents, households having access to basic hygiene services, residing in urban areas, and being exposed to health information were significantly associated with the outcome. There is a significant gap in safe food handling practices. Core household and community-level factors that influence safe food handling practices were identified. Policymakers should implement targeted interventions.
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Girmay et al. (2026) studied this question.
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