Optimizing nutritionally adequate food basket using linear programming in Niayes Households, Senegal

Area of Science:

• Nutritional Science
• Public Health
• Agricultural Economics

Background:

• Rural Senegalese diets are monotonous, cereal-based, with low intake of essential food groups.
• The COVID-19 pandemic worsened food security by increasing staple food prices.
• Vulnerable groups (women, young children, elderly) are disproportionately affected by poor diet quality.

Purpose of the Study:

• To design a nutritionally adequate and affordable food basket for households in Senegal's Niayes region.
• To assess current dietary diversity and nutrient intake adequacy among vulnerable populations.
• To utilize linear programming for optimizing a local food basket.

Main Methods:

• Cross-sectional survey of 90 households to assess dietary diversity and nutrient intake.
• 24-hour dietary recall used to evaluate household dietary diversity (≥8 food groups = high diversity).
• Linear programming (LP) applied to optimize a low-cost food basket meeting energy and micronutrient needs.

Main Results:

• 44.4% of households demonstrated high dietary diversity.
• Micronutrient deficiencies (calcium, folate, vitamin D) affected over 50% of vulnerable groups.
• The optimized food basket (6,917 XOF/day) met all nutritional requirements for a 13-person household.

Conclusions:

• Linear programming is an effective tool for creating context-specific, nutritionally sound food baskets.
• The optimized food basket offers a viable solution to improve dietary quality in the Niayes area.
• Addressing dietary inadequacies is crucial for public health, especially for vulnerable populations in Senegal.