Coping mechanisms of food insecure households in urban Ethiopia

Abstract

With an increasing rate of urbanisation in East Africa, and with the highest prevalence rate of undernourished population than any region in the developing world, the issue of food access insecurity in urban areas has received considerable attention. While there are noticeable differences between big, medium- and small-sized towns, the variation in the household’s response to food access insecurity across urban hierarchies remains largely unexplored. This study aimed to investigate the social, economic and demographic factors in coping with food access insecurity among households in urban slum areas of Ethiopia. The study used both secondary and primary data sources. The national surveys of household consumption and expenditure survey and welfare monitoring surveys of 2004/5, 2010/11, and 2015/16 was used to analyse the food security situation in Ethiopia across time and urban hierarchies. Primary data of 500 households and three focus group discussions were conducted from slum areas of Addis Ababa, Hawassa, and Sheki representing a big city, medium- and small-sized town, respectively. The household survey data were subjected to descriptive statistical analysis and a standard regression model to investigate the relationship between factors such as household structure and composition, economic resources, social protection programmes and projects, and urban-rural linkages with coping with food access insecurity across urban hierarchies. A global model and three site-specific regression models were constructed. Descriptive results from both the primary and the secondary data sources have revealed that the proportion of the households affected by food shortage varies across the urban hierarchy that food insecurity was highest in the small-sized town as compared with the medium-sized town and the big city. The quality of food consumed was consistently low among female-headed households regardless of their socio-economic characteristics when compared with male-headed households. The result of the regression analysis for the global model has shown that economic resources (asset and source of income) predict nearly half of the variability in coping with food access insecurity. Household structure and composition such as gender and education of the head of the household, family structure (nuclear/extended), and the ratio of young children in the household predict a quarter of the variability in coping. Social protection programs and services predict one-tenth; the remaining variability in coping is explained by the combined effect of all the factors involved. The significance of these factors in predicting coping with food access insecurity, however, varies across the urban hierarchies. The contribution of economic factors in predicting coping is the highest at the big city (Addis Ababa); household structure and composition took the leading role in predicting coping at the small-sized town (Sheki); the significant factors in predicting coping at the mediumsized town (Hawassa) was the combined effect of all the factors involved. Household characteristics such as female headship, a higher ratio of young children, low education of the household head, lack of access to the financial loan, asset and income poverty, and weak linkages with kin structure at rural areas increase vulnerability to food insecurity and put households under stress to cope with food access insecurity. The study results show that the traditional urban-rural dichotomy may not suffice to portray the degree of food insecurity, as well as the mechanisms how food insecure households strive to cope with food access insecurity, which varies across the continuum of urban hierarchies. Those who wish to support food insecurity challenges need to be sensitive to the variability of factors in coping with food access insecurity across urban hierarchies. During policy, design and program implementation policymakers and international partners need to consider that the needs and coping mechanisms of urban households vary across urban hierarchies besides the other social, economic and demographic variables.