In Senegal, particularly in rural areas, diets are often monotonous and primarily based on cereals, with limited intake of animal proteins, vegetables, fruits, and dairy products. The COVID-19 pandemic has exacerbated this situation by increasing the prices of staple foods, further reducing the quality of household diets. This study aimed to develop a nutritionally adequate and food basket adapted to households in the Niayes area, located along the northern maritime fringe of Senegal. A cross-sectional survey was conducted among 90 households to assess dietary diversity of the households and the adequacy of nutrient intake by the daily diet, among vulnerable groups such as women of reproductive age, children under five years old, and elderly individuals (60 years and above). Household dietary diversity was assessed using a 24-hour recall, with high dietary diversity defined as the consumption of at least eight out of twelve food groups. Foods commonly consumed by households were listed and their prices were collected from local food retailers identified through household purchasing practices. Linear programming (LP) was used to optimize a low-cost food basket covering daily energy and micronutrient requirements. Around 44.4% of households exhibited high dietary diversity. The coverage of daily requirements for certain micronutrients, including calcium, folate, and vitamin D, among vulnerable groups was less than 50%. The optimized food basket, costing 6,917 XOF (~11.48 USD) per day, contained nine food groups and successfully covered the daily energy, protein, and micronutrient requirements of a reference household of 13 individuals. These results highlight the potential of linear programming as a decision-support tool for designing nutritionally adequate food baskets adapted to local contexts.
Willane et al. (Wed,) studied this question.