Food and Nutrition Security in Urban Myanmar
Abstract
This study examines the prevalence of and factors associated with food insecurity among urban households in Myanmar using secondary data from the Food Insecurity Experience Scale (FIES) survey developed by the Food and Agriculture Organization (FAO). The analysis encompasses 1,912 urban households sampled between 2021 and 2024. We employ descriptive statistics and two complementary econometric approaches: Tobit regression models to estimate factors associated with the latent probability of households experiencing (i) moderate or severe food insecurity and (ii) severe food insecurity only; and an Ordered Logistic regression model to analyze factors associated with ordered categories of food insecurity severity. The findings consistently identify education and household income as the strongest protective factors against food insecurity. Higher educational attainment and belonging to richer income quintiles significantly reduce the probability of experiencing both moderate/severe and severe food insecurity. Conversely, the poorest households face substantially elevated risk across all severity levels. Demographic factors also play important roles: female respondents and households with more adults exhibit lower probabilities of food insecurity, likely attributable to additional income earners and enhanced resource-sharing mechanisms. The results underscore that persistent socioeconomic and educational disparities are the primary drivers of household vulnerability to food insecurity in urban Myanmar. Policy implications emphasize the critical need for investments in education and expanded income-generating opportunities to build a more resilient and equitable urban food system. These findings contribute to the growing literature on food security in transitional economies and provide evidence-based guidance for targeted interventions in urban contexts.
Keywords: Food Security,ordered logit,Tobit Model,food insecurity experience scale,urban,Myanmar
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