27 research outputs found

    Assessing the potential of wild foods to reduce the cost of a nutritionally adequate diet: an example from eastern Baringo District, Kenya

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    A study of the role of wild food biodiversity in achieving a cost reduction of a nutritionally adequate diet for women and young children in Kenya using linear programming.An ethnobiological inventory of available food biodiversity was carried out by means of focus group discussions, and five wild foods selected for further modeling. A market survey assessed available food prices by season. Diets were modeled to minimize cost and maximize nutrient adequacy using the Cost of Diet linear programming tool. Modeling was done without and with wild foods.The modeled diets without wild species were deficient in iron for all age groups during the dry season, deficient in vitamin B6 and calcium for infants aged 6 to 8 months during the dry season, and deficient in iron and zinc for infants aged 6 to 8 months over the whole year. Adding wild foods to the modeled diets resulted in a lower-cost diet, while meeting recommended iron intakes for women and children between 12 and 23 months of age

    Cost of the Diet: a method and software to calculate the lowest cost of meeting recommended intakes of energy and nutrients from local foods

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    Background When food is available, the main obstacle to access is usually economic: people may not be able to afford a nutritious diet, even if they know what foods to eat. The Cost of the Diet method and software was developed to apply linear programming to better understand the extent to which poverty may affect people’s ability to meet their nutritional specifications. This paper describes the principles of the method; the mathematics underlying the linear programming; the parameters and assumptions on which the calculations are based; and then illustrates the output of the software using examples taken from assessments. Results The software contains five databases: the energy and nutrient content of foods; the energy and nutrient specifications of individuals; predefined groups of individuals in typical households; the portion sizes of foods; and currency conversion factors. Data are collected during a market survey to calculate the average cost of foods per 100 g while focus group discussions are used to assess local dietary habits and preferences. These data are presented to a linear programming solver within the software which selects the least expensive combination of local foods for four standard diets that meet specifications for: energy only; energy and macronutrients; energy, macronutrients and micronutrients; and energy, macronutrients and micronutrients but with constraints on the amounts per meal that are consistent with typical dietary habits. Most parameters in the software can be modified by users to examine the potential impact of a wide range of theoretical interventions. The output summarises for each diet the costs, quantity and proportion of energy and nutrient specifications provided by all the foods selected for a given individual or household by day, week, season and year. When the cost is expressed as a percentage of income, the affordability of the diet can be estimated. Conclusions The Cost of the Diet method and software could be used to inform programme design and behaviour change communication in the fields of nutrition, food security, livelihoods and social protection as well as to influence policies and advocacy debates on the financial cost of meeting energy and nutrient specifications

    Screening wild foods for reducing the cost of a nutritionally adequate diet in Kenya

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    Deptford City Challenge Work, education and economic activity II

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