Incorporating locally available food using linear programming to improve food-based recommendation for preelderly diabetic patients

Background: Dietary adherence is essential for glycemic control in diabetic patients, yet cultural preferences, availability, and affordability often hinder acceptance of recommended foods. Thus, it requires food-based recommendations (FBRs) tailored to local contexts. Aim: This study identified locally available foods to develop FBR using linear programming (LP) in WHO Optifood for preelderly diabetic patients. Methods: A descriptive cross-sectional study was conducted on 174 type 2 diabetic patients aged 50–64 years in Malang, Indonesia, selected through multistage random sampling. Dietary data were collected over seven days using a 24-h recall, a one-day estimated food record, and a five-day food tally to capture habitual intake patterns. Optifood analysis incorporated demographic data, commonly consumed local foods, and nutrient targets based on Perkeni and Indonesian RDA. Dietary adequacy assessment used a modeled scenario using the 65% Recommended Nutrient Intake (RNI) threshold in the worst-case intake analysis. Results: Several nutrients showed dietary inadequacy in the modeled analysis, rather than actual individual deficiencies. Protein, fiber, vitamins A, C, E, B12, iron, and omega-3 could be optimized to exceed 65% of the RNI using local foods such as tempeh, corn rice, moringa leaves, tongkol, kepok banana, and koro beans. However, calcium, vitamin B6, and zinc did not meet the 65% adequacy threshold. Conclusion: Locally available food was successfully incorporated into dietary recommendations, fulfilling eight key nutrients. Nevertheless, vitamin B6, calcium, and zinc remained below the recommended thresholds in worst-case modeling, highlighting the need for additional interventions such as food fortification or dietary diversification.