Optimization of Food Expenditures in Nigeria: A Case Study of Lafia, Nasarawa State

Abstract

Currently, the prices of commodities in Nigeria are consistently rising owing to several variables, including economic conditions, political influences, and technical progress. Consequently, the cost of essential items, including food, has risen significantly. Consequently, they often disregard nutritious dietary habits and fail to obtain adequate daily nutrients. This will lead to several repercussions, including diseases, disorders, and less vitality for daily activities. Meeting daily fundamental nutritional requirements has become a considerable challenge in Nigeria, where the average individual earns around N3,500 per day. The simplex method, an iterative algorithm in linear programming, is utilized to identify and select the most cost-effective food items from a range that includes orange, maize, rice, goat meat, eggplant, palm oil, cassava, beniseed, bean cake, ogbonoh, bread, beans, banana, chicken, carrot, and catfish. These foods provide vital elements like calories, lipids, proteins, carbohydrates, calcium, iron, potassium, salt, vitamin A, thiamin, riboflavin, and vitamin C, fulfilling the required daily dietary standards for the average individual in Lafia, Nasarawa State. The data was structured into an objective function and constrained by limitations. The matrices generated were computed using MATLAB code throughout eight iterations. Recent studies reveal that a typical Nigerian in Lafia need N1,904.54 daily from the N3,500 earned to meet fundamental nutritional needs at little cost. This may be accomplished using a food basket consisting of rice, eggplant, cassava, benniseed, and carrot. Given the ideal value of food, some commodities such as oranges, maize, goat meat, palm oil, cassava, bean cake, ogbonoh, beans, bananas, chicken, and catfish have been reported to have detrimental consequences resulting from excessive nutrient intake. A typical individual would allocate 54.42 percent of their daily income to food, based on this food basket and the projected food expenditure. A sensitivity analysis was conducted to assess the robustness of the results.