Background. Chronic undernutrition is prevalent in Mozambique, where children suffer from stunting, vitamin A deficiency, anemia, and other nutrition-related disorders. Complete diet formulation products (CDFPs) are increasingly promoted to prevent chronic undernutrition. Objective. Using linear programming, to investigate whether diet diversification using local foods should be prioritized in order to reduce the prevalence of chronic undernutrition. Methods. Market prices of local foods were collected in Tete City, Mozambique. Linear programming was applied to calculate the cheapest possible fully nutritious food baskets (FNFB) by stepwise addition of micronutrient-dense local foods. Results. Only the top quintile of Mozambican households, using average expenditure data, could afford the FNFB that was designed using linear programming from a spectrum of local standard foods. The addition of beef heart or liver, dried fish and fresh moringa leaves, before applying linear programming decreased the price by a factor of up to 2.6. As a result, the top three quintiles could afford the FNFB optimized using both diversification strategy and linear programming. CDFPs, when added to the baskets, were unable to overcome the micronutrient gaps without greatly exceeding recommended energy intakes, due to their high ratio of energy to micronutrient density. Conclusions. Dietary diversification strategies using local, low-cost, nutrient-dense foods can meet all micronutrient recommendations and overcome all micronutrient gaps. The success of linear programming to identify a low-cost FNFB depends entirely on the investigators' ability to select appropriate micronutrient-dense foods. CDFPs added to food baskets are unable to overcome micronutrient gaps without greatly exceeding recommended energy intake.
Food and Nutrition Bulletin, 2014, Vol 35, Issue 2, p. 191-199
food basket; linear programming; food prices; nutrition; Managers and employees in public institutions; Managers and employees at universities, research institutions etc.