Abstract:
Food composition databases (FCDBs) provide the nutritional content of foods and are
essential for developing nutrition guidance and effective intervention programs to improve nutrition
of a population. In public and nutritional health research studies, FCDBs are used in the estimation
of nutrient intake profiles at the population levels. However, such studies investigating nutrient
co-occurrence and profile patterns within the African context are very rare. This study aimed to
identify nutrient co-occurrence patterns within the South African FCDB (SAFCDB). A principal
component analysis (PCA) was applied to 28 nutrients and 971 foods in the South African FCDB to
determine compositionally similar food items. A second principal component analysis was applied to
the food items for validation. Eight nutrient patterns (NPs) explaining 73.4% of the nutrient variation
among foods were identified: (1) high magnesium and manganese; (2) high copper and vitamin B12;
(3) high animal protein, niacin, and vitamin B6
; (4) high fatty acids and vitamin E; (5) high calcium,
phosphorous and sodium; (6) low moisture and high available carbohydrate; (7) high cholesterol and
vitamin D; and (8) low zinc and high vitamin C. Similar food patterns (FPs) were identified from a
PCA on food items, yielding subgroups such as dark-green, leafy vegetables and, orange-coloured
fruit and vegetables. One food pattern was associated with high sodium levels and contained bread,
processed meat and seafood, canned vegetables, and sauces. The data-driven nutrient and food
patterns found in this study were consistent with and support the South African food-based dietary
guidelines and the national salt regulations.
