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Food insecurity remains a vital concern in Kenya. Vulnerable members of the population, such as children, the elderly, marginalised ethnic minorities, and low-income households, are disproportionately affected by food insecurity. Following the pioneering work of Sen, which examined exposure to food insecurity at a household level using his “entitlement approach”, this paper estimates households’ vulnerability to food insecurity. In turn, the outcome variable is decomposed in order to explain the food insecurity gap between households classified as “marginalised” and “non-marginalised”. We applied the Oaxaca-Blinder decomposition method to examine vulnerability to food insecurity and, in particular, contributions of observed differences in socio-demographic characteristics (endowments) or differences in the returns to these characteristics, which, in our context, is associated with poor public services and infrastructure in the vicinity of the household. The results indicated that differences in vulnerability to food insecurity were mainly attributable to observed differences in socio-demographic characteristics such as education, age, and household income. Therefore, policies seeking to attain equity by investment into targeted household characteristics in terms of access to food and other productive resources could effectively combat food insecurity. For example, policymakers could develop programs for household inclusiveness using education and social protection programs, including insurance schemes against risk of endowment loss.
We investigate the effects of diet diversity on health outcomes indicated by the body-mass index (BMI) of Kenyan women in their reproductive age (15-49 years). We estimate the demand for diet diversity (which is a proxy for diet quality) and analyse its relationship with BMI by allowing the effect of diet diversity to vary along the conditional BMI distribution. Results show that diet diversity is associated with a beneficial effect on the lower and upper tails of the BMI distribution, that is, dietary diversity improves BMI for underweight individuals while, at the same time, it reduces BMI for overweight/obese individuals. Specifically, doubling the diet diversity is associated with a 14.7% increase in BMI for underweight women and a 7.0% reduction in BMI of obese women. These results support the hypothesis that diet diversity is associated with optimal BMI and, thus, better health, contributing to the policy discourse concerning the double burden of malnutrition in developing countries.
The application of global indices of nutrition and food sustainability in public health and the improvement of product profiles has facilitated effective actions that increase food security. In the research reported here we develop index measurements further so that they can be applied to food categories and be used by food processors and manufacturers for specific food supply chains. This research considers how they can be used to assess the sustainability of supply chain operations by stimulating more incisive food loss and waste reduction planning. The research demonstrates how an index driven approach focussed on improving both nutritional delivery and reducing food waste will result in improved food security and sustainability. Nutritional improvements are focussed on protein supply and reduction of food waste on supply chain losses and the methods are tested using the food systems of Kenya and India where the current research is being deployed. Innovative practices will emerge when nutritional improvement and waste reduction actions demonstrate market success, and this will result in the co-development of food manufacturing infrastructure and innovation programmes. The use of established indices of sustainability and security enable comparisons that encourage knowledge transfer and the establishment of cross-functional indices that quantify national food nutrition, security and sustainability. The research presented in this initial study is focussed on applying these indices to specific food supply chains for food processors and manufacturers.
The adoption of modern agricultural technologies in Ethiopia’s dairy production system remains underutilized and under-researched yet it is a promising sector to aid in reducing poverty, improving the food security situation and the welfare of rural households, and in ensuring environmental sustainability. This paper uses the Negative Binomial regression model to examine determinants of multiple agricultural technology adoption in the Addis Ababa and Oromia regions of Ethiopia. Data was collected from 159 smallholder dairy farms in Ethiopia’s Addis Ababa and Oromia regions exploring 19 technologies used by the farmers during the study period. The findings show that farm location and herd size impact adoption decisions. Increasing herd size is associated with increased uptake of multiple technologies. Further, as farmer education level increases the more likely farmers are to adopt multiple technologies. The increase in the number of female workers is positively associated with the adoption of multiple dairy technologies. In terms of farmers’/workers’ years of experience, those with no years of work experience are less likely to have adopted multiple technologies than those with more than 5 years of experience. However, this could be due to a number of factors where experience stands as a proxy value. Trust in information from government agencies was associated with a higher propensity to adopt multiple dairy technology as was farmer perception of fellow farmers as peers compared to those who perceive them as competitors. This is an important finding as it may help policymakers or institutions explore knowledge exchange and diffusion of innovation strategies tailored to specific farming and community situations. Studies have shown that farmers within a social group learn from each other more fully about the benefits and usage of new technology. These findings are of value in future technology adoption studies, particularly which factors influence the intensity of adoption of multiple technologies by smallscale producers.
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