OBJECTIVE: This scoping review aims to (i) summarize the use of LP in diet optimization to improve nutrient adequacy, (ii) evaluate nutrient requirements by using modelling techniques when the use of local foods is optimized, and (iii) identify and compare the problem nutrient(s).
METHODS: This scoping review was performed by searching PubMed and Wiley databases from 2012 to 2025, and also screened the reference lists of included publications to identify potentially eligible articles. Forward and backward citation searches were also performed to supplement the structured searches in the databases.
RESULTS: Fourteen studies were included after a systematic literature search. The objective functions and the final set of FBRs of the included studies were summarized. Moreover, the nutrient intakes in the optimized diets and the problem nutrients of the included studies were compared and discussed. When optimizing diets using the LP approach, most of the nutrient requirements can be achieved, except for iron and zinc and, in some studies, thiamine, niacin, folate, and calcium. Iron was identified as the problem nutrient in all studies involving infants aged 6 to 11 months old, followed by calcium and zinc. In children aged 12 to 23 months, iron and calcium were identified as the problem nutrients in almost all studies, followed by zinc and folate. In children aged 1 to 3 years, fat, calcium, iron, and zinc were recognized as the absolute problem nutrients, while fat, calcium, and zinc were the absolute problem nutrients for children aged 4 to 5 years. Findings on dietary inadequacy of nutrient intakes were remarkably consistent across studies conducted in different geographic and socioeconomic settings.
CONCLUSIONS: Modeled diets involving local foods are inadequate to meet the requirements for certain micronutrients, particularly iron and zinc. Cost-effective strategies are required to improve the dietary adequacy of young children.
METHODS: Therefore, using linear programming, this study is aimed to develop a healthy and balanced menu with minimal cost in accordance to individual needs that could in return help to prevent cancer. A cross sectional study involving 100 adults from a local university in Kuala Lumpur was conducted in 3 phases. The first phase is the data collection for the subjects, which includes their socio demographic, anthropometry and diet recall. The second phase was the creation of a balanced diet model at a minimum cost. The third and final phase was the finalization of the cancer prevention menu. Optimal and balanced menus were produced based on respective guidelines of WCRF/AICR (World Cancer Research Fund/ American Institute for Cancer Research) 2007, MDG (Malaysian Dietary Guidelines) 2010 and RNI (Recommended Nutrient Intake) 2017, with minimum cost.
RESULTS: Based on the diet recall, most of subjects did not achieve the recommended micronutrient intake for fiber, calcium, potassium, iron, B12, folate, vitamin A, vitamin E, vitamin K, and beta-carotene. While, the intake of sugar (51 ± 19.8 g), (13% ± 2%) and sodium (2585 ± 544 g) was more than recommended. From the optimization model, three menus, which met the dietary guidelines for cancer prevention by WCRF/AICR 2007, MDG 2010 and RNI 2017, with minimum cost of RM7.8, RM9.2 and RM9.7 per day were created.
CONCLUSION: Linear programming can be used to translate nutritional requirements based on selected Dietary Guidelines to achieve a healthy, well-balanced menu for cancer prevention at minimal cost. Furthermore, the models could help to shape consumer food choice decision to prevent cancer especially for those in low income group where high cost for health food has been the main deterrent for healthy eating.