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Lookup NU author(s): Dr Carlos Celis Morales, Professor John Mathers
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6·56 (sd 1·29) %), carotenoids (2·15 (sd 0·71) µm) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.
Author(s): O'Donovan CB, Walsh MC, Woolhead C, Forster H, Celis-Morales C, Fallaize R, Macready AL, Marsaux CFM, Navas-Carretero S, Rodrigo San-Cristobal S, Kolossa S, Tsirigoti L, Mvrogianni C, Lambrinou CP, Moschonis G, Godlewska M, Surwillo A, Traczyk I, Drevon CA, Daniel H, Manios Y, Martinez JA, Saris WHM, Lovegrove JA, Mathers JC, Gibney MJ, Gibney ER, Brennan L
Publication type: Article
Publication status: Published
Journal: The British journal of nutrition
Year: 2017
Volume: 118
Issue: 8
Pages: 561-569
Print publication date: 28/10/2017
Online publication date: 23/10/2017
Acceptance date: 14/07/2017
Date deposited: 20/12/2017
ISSN (print): 1475-2662
Publisher: Cambridge University Press
URL: https://doi.org/10.1017/S0007114517002069
DOI: 10.1017/S0007114517002069
PubMed id: 29056103
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