The WHO is urging countries to promote improved complementary feeding practices to ensure optimal health, growth, and development of young children. To help achieve this, a rigorous 4-phase approach for designing optimal population- specific food-based complementary feeding recommendations (CFRs) was developed and is illustrated here. In phase I, an optimized diet is selected, using goal programming (Model #1), which aims to provide a desired nutrient content with respect to habitual diet patterns and cost. Based on its food patterns, a set of draft CFRs is designed. In phase II, their success for ensuring a nutritionally adequate diet is assessed via linear programming (Model type #2) by sequentially minimizing and maximizing the level of each nutrient (i.e., worst and best-case scenarios) while respecting the CFRs. For nutrients that are <70% of desired levels, the best food sources are identified via linear programming in phase III (Model #3). Different combinations of these foods are incorporated into the original draft of the CFRs to produce alternative CFRs, which are then compared on the basis of their cost, flexibility, and "worst-case scenario" nutrient levels (Model type #2) to select, in phase IV, a final set of CFRs. A hypothetical example is used to illustrate this approach. Outcomes include a set of optimal, population-specific CFRs and practical information regarding key "problem nutrients" in the local diet. Such information is valuable for nutrition promotion, as well as nutrition program planning and advocacy, to help achieve global initiatives for improving the complementary feeding practices of young children living in disadvantaged environments.

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Effective food-based dietary guidelines (FBDGs) are required to combat micronutrient deficiencies. This study aimed to develop a rigorous approach for designing population-specific FBDGs. A 4-phase approach based on linear programming analysis was used to design, test, and refine the FBDGs. This was illustrated for Malawian children. In phase I, the objective function minimized the difference in the energy contributed by different food groups between modeled and observed diets for 16 observed diet types, while preferentially selecting foods most often consumed. Constraints ensured nutrient adequacy and diet palatability. In phase II, the meal/snack patterns of the phase I modeled diets were examined to develop season-specific FBDGs. In phase III, the robustness of these FBDGs, for ensuring a nutritionally adequate diet, was tested. The objective function, in this analysis, minimized selected nutrient levels in the modeled diets (i.e., chose the "worst-case scenario"), while respecting the FBDGs, palatability, and energy constraints. The FBDGs were refined in phase IV. In the Malawian example used to illustrate our approach, the FBDGs promoted daily consumption of maize flour, small dry fish (>or=20 g), leaf relish, and 2-3 snacks. The last mentioned included mangoes, in the food-shortage season, and pumpkin in the food-plenty season. In addition, legume relish was recommended in the food-shortage season. The approach presented here can be used to design and then test the robustness of FBDGs for meeting nutrient recommendations.

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