Teferi Daba (PhD)Bewket Belayneh2025-06-162025-06-162025-02-11https://etd.aau.edu.et/handle/123456789/5559The purpose of this study was to examine household food security and its determinants in Addis Ababa by using household socio economic survey data collected by ESS and logistic regression method. The logistic regression results revealed that the sex and education level of household head, adult male equivalent, share of food consumption expenditure and household income are significant factors of food security. Accordingly male-headed households are significantly more likely to achieve kilocalorie sufficiency, with an odds ratio of 1.79 (p = 0.010). The results revealed that a thousand unit increases in income raises the likelihood of being food secured by approximately 2.97 times, holding other variables constant. Therefore income is found to be a strong positive association with calorie sufficiency. Another strong factor is education of household. A change in in education level give raise to the odds of kilocalorie sufficiency by 27% (p = 0.016). on the other hand, family composition has negative association with food security such that each additional adult equivalent decreases the odds of sufficiency by 39% (p < 0.001) implying the chance of large adult equivalent families for greater strain on financial and food resources. In this study a percentage increase in the share of expenditure on food raises the odds by 3% (p < 0.001), implying the more food budget the more likely to achieve dietary adequacy and the lower the income the more vulnerable the households are. Each unit increase in log of household income raises the odds by 8% (p = 0.011) revealing better financial capacity in ensuring access to adequate and nutritious food. Therefore, a policy option of supporting female-headed households, promotion of educational and enabling access to income-generating initiatives could help to improve food security. Key Words: food, security, insecurity, vulnerability, household, determinant, variable, logistic regression.enThesis