Applying the concept of Thai nutrient profiling as a model for the Thai school lunch planner
Journal Title: Journal of Public Health and Development - Year 2024, Vol 22, Issue 1
Abstract
This study aimed to develop the Thai school lunch planning program using nutrient profiling (NP). The intention was to create a user-friendly tool that aids teachers in preparing nutritionally balanced school lunch menus. The Thai school lunch planner was developed by gathering 53 popular lunch menus from a school lunch outsourcing company in Bangkok. Menus were grouped into ten categories based on food characteristics and cooking methods. Then, menus were graded according to their energy and 13 nutrients using NP criteria as ‘grade A’ (score >16), ‘grade B’ (scores 12-16), and ‘grade C’ (score <12), and menu category codes were created. Lunch sets were matched across the menu category codes and based on the two formats of school lunch standards. Finally, lunch sets were graded based on energy and 13 nutrient contents using NP criteria, with cut-off macronutrients set at 30% of Thai DRI 2020. Regarding the two formats of school lunch standards, this study found 63 uniquely matched patterns, with the possibility of forming 5,160 lunch sets. Lunch pattern format 1 had 57 patterns and 5,085 menu sets, of which 2,706 menu sets met 30% of the Thai DRI macronutrient requirement. The lunch pattern format 2 could create up to 75 sets from six patterns. Thirty-seven menu sets (49.3%) met the 30% Thai DRI macronutrient requirement. NP could be a valuable alternative for planning school lunch sets to guarantee high-quality and nutritious meals. This technique can be combined with the existing school food menu guidelines. Teachers, with or without basic nutrition knowledge, can find this strategy relatively user-friendly. Even though this technique is suitable for primary schools that serve two side dishes, schools serving one side dish can apply it by increasing the portion of the side dish.
Authors and Affiliations
Arisa Keeratichamroen, Panrawee Praditsorn, Piyanit Churak, Nuttarat Srisangwan, Kitti Sranacharoenpong, Punnee Ponprachanuvut, Kantanit Chammari.
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