Title: Nutritionally recommended food for semi- to strict vegetarian diets based on large-scale nutrient composition data,
Abstract: Diet design for vegetarian health is challenging due to the limited food
repertoire of vegetarians. This challenge can be partially overcome by
quantitative, data-driven approaches that utilise massive nutritional
information collected for many different foods. Based on large-scale data of
foods' nutrient compositions, the recent concept of nutritional fitness helps
quantify a nutrient balance within each food with regard to satisfying daily
nutritional requirements. Nutritional fitness offers prioritisation of
recommended foods using the foods' occurrence in nutritionally adequate food
combinations. Here, we systematically identify nutritionally recommendable
foods for semi- to strict vegetarian diets through the computation of
nutritional fitness. Along with commonly recommendable foods across different
diets, our analysis reveals favourable foods specific to each diet, such as
immature lima beans for a vegan diet as an amino acid and choline source, and
mushrooms for ovo-lacto vegetarian and vegan diets as a vitamin D source.
Furthermore, we find that selenium and other essential micronutrients can be
subject to deficiency in plant-based diets, and suggest nutritionally-desirable
dietary patterns. We extend our analysis to two hypothetical scenarios of
highly personalised, plant-based methionine-restricted diets. Our
nutrient-profiling approach may provide a useful guide for designing different
types of personalised vegetarian diets.