The development of national dietary guidelines promoting healthy food choices is a public health priority in Thailand. In developing the recent national complementary feeding guidelines (CFGs) for 6- to 12-month-old children, mathematical modeling was used to inform decisions. Model parameters were derived from nationally representative dietary data and analyzed for 11 micronutrients by age group, using linear programming analysis in Optifood. Models were run to identify micronutrients whose nutrient reference values could not be met using local foods as consumed (problem nutrients), evaluate the original 2012 Thai CFGs, and predict the nutritional benefits of a specific fortified complementary food. The results identified three problem nutrients (iron, calcium, and zinc), which, for 9- to 11-month-olds, were reduced to one when the fortified food was modeled. The number of servings/week of vegetables and meat, fish or eggs were higher, and of oil and fruit were lower, in the modeled nutritionally best rather than observed diets (medians). When modeled, the original Thai CFGs were not feasible because the energy constraint was exceeded; hence, in revising them, the recommended number of servings/week of oil and fruit were reduced. This study demonstrates the advantages of using mathematical modeling, when revising national CFGs, to evaluate and improve them.
Keywords: Thailand; complementary feeding recommendations; fortified complementary food; linear programming analysis.
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