Nutrient-Rich Foods in Western African Food Supply: Applying Nutrient Profiling Models to the FAO Food Composition Table for Western Africa (WAFCT 2019)

Abstract

Background: The Western Africa region faces a significant burden of malnutrition, including high rates of micronutrient deficiencies. Addressing this issue requires identifying and ensuring equitable access to local nutrient-dense foods. While nutrient profiling tools can serve for this purpose, most of them have been developed for high-income countries, requiring adaptation for the Western African context. Objective: This study aimed to adapt and apply nutrient profiling models to the FAO/INFOODS Food Composition Table for Western Africa (WAFCT) 2019. The goal was to identify locally available nutrient-dense foods across different food groups.Design: Analysis encompassed 909 WAFCT foods with complete data. The Nutrient-Rich Food (NRF) Index served as the nutrient density metric, employing three versions: two adapted for low- and middle-income countries (LMICs) (the NRF6.3 and NRF15.3), and the original NRF9.3, developed in a high-income country. The Carbohydrate Foods Quality Score (CFQS) assessed carbohydrate quality in 446 carbohydrate foods. Protein quality correction was conducted using the Protein Digestibility Corrected Amino Acid Score (PDCAAS) in 862 foods. Descriptive statistics, Pearson correlations, one-way ANOVAs, and independent and paired sample t-tests were employed for data analysis, with significance set at α=0.05. Results: Among food groups, vegetables obtained the highest NRF scores. African indigenous vegetables (AIV) demonstrated significantly higher nutrient density and protein content compared to non-indigenous vegetables. A considerable proportion (66.8%) of analyzed foods were classified as higher-quality carbohydrate foods. African indigenous grains (AIG) exhibited higher carbohydrate quality and nutrient density scores than non-indigenous grains, particularly when non-indigenous grains were unfortified. When utilizing nutrient profiling models specifically adapted for LMICs (NRF6.3 and NRF15.3), animal-sourced food groups attained higher nutrient density rankings compared to the ranking they obtained with the NRF9.3. Additionally, food groups had significant reductions in mean grams of protein per 100 grams of food after the PDCAAS adjustment; however, differences were most pronounced in plant-based foods. Conclusion: Adapting nutrient profiling tools to the West African context allowed the identification of local nutrient-dense foods. AIV and AIG were sources of priority micronutrients and higher-quality carbohydrates. Animal-sourced foods also played a crucial role in providing essential micronutrients of public health significance in Western Africa. Governments, public health institutions, and academic organizations in the region should work together to recognize the nutrient density of these foods, increase their accessibility and affordability, and promote their consumption through appropriate policies and programs.