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Nutritionally recommended food for semi- to strict vegetarian diets based on large-scale nutrient composition data.

Published on Dec 1, 2018in Scientific Reports4.01
· DOI :10.1038/s41598-018-22691-1
Seunghyeon Kim3
Estimated H-index: 3
(ICTP: International Centre for Theoretical Physics),
Michael Fenech56
Estimated H-index: 56
,
Pan-Jun Kim13
Estimated H-index: 13
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.
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References36
Newest
#1Jaeyun Sung (Broad Institute)H-Index: 8
#2Seunghyeon Kim (ICTP: International Centre for Theoretical Physics)H-Index: 3
Last.Pan-Jun Kim (POSTECH: Pohang University of Science and Technology)H-Index: 13
view all 8 authors...
#1Ambika Satija (Harvard University)H-Index: 14
#2Frank B. Hu (Harvard University)H-Index: 202
Last.Sanjay Kinra (Lond: University of London)H-Index: 29
view all 11 authors...
#1David Zeevi (Weizmann Institute of Science)H-Index: 13
#2Tal Korem (Weizmann Institute of Science)H-Index: 12
Last.Maya Lotan-Pompan (Weizmann Institute of Science)H-Index: 12
view all 23 authors...
#1Seunghyeon Kim (POSTECH: Pohang University of Science and Technology)H-Index: 3
#2Jaeyun Sung (Asia Pacific Center for Theoretical Physics)H-Index: 8
Last.Pan-Jun Kim (POSTECH: Pohang University of Science and Technology)H-Index: 13
view all 5 authors...
#1Sutapa Agrawal (Public Health Foundation of India)H-Index: 21
#2Christopher Millett (Imperial College London)H-Index: 38
Last.Shah B. J. Ebrahim Dm Frcp (Public Health Foundation of India)H-Index: 116
view all 5 authors...
#1Parisa Pouladzadeh (U of O: University of Ottawa)H-Index: 9
#2Shervin Shirmohammadi (U of O: University of Ottawa)H-Index: 23
Last.Rana Almaghrabi (U of O: University of Ottawa)H-Index: 5
view all 3 authors...
Cited By1
Newest
#1Weiqing Min (CAS: Chinese Academy of Sciences)H-Index: 8
#2Shuqiang Jiang (CAS: Chinese Academy of Sciences)H-Index: 25
Last.Ramesh Jain (UCI: University of California, Irvine)H-Index: 64
view all 3 authors...
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