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Randomized Controlled Trial
. 2017 Apr 1;46(2):578-588.
doi: 10.1093/ije/dyw186.

Effect of personalized nutrition on health-related behaviour change: evidence from the Food4Me European randomized controlled trial

Carlos Celis-Morales  1 , Katherine M Livingstone  1 , Cyril Fm Marsaux  2 , Anna L Macready  3 , Rosalind Fallaize  3 , Clare B O'Donovan  4 , Clara Woolhead  4 , Hannah Forster  4 , Marianne C Walsh  4 , Santiago Navas-Carretero  5 , Rodrigo San-Cristobal  5 , Lydia Tsirigoti  6 , Christina P Lambrinou  6 , Christina Mavrogianni  6 , George Moschonis  6 , Silvia Kolossa  7 , Jacqueline Hallmann  7 , Magdalena Godlewska  8 , Agnieszka Surwillo  8 , Iwona Traczyk  8 , Christian A Drevon  9 , Jildau Bouwman  10 , Ben van Ommen  10 , Keith Grimaldi  11 , Laurence D Parnell  1   2 , John Ns Matthews  1   3 , Yannis Manios  6 , Hannelore Daniel  7 , J Alfredo Martinez  5 , Julie A Lovegrove  3 , Eileen R Gibney  4 , Lorraine Brennan  4 , Wim Hm Saris  2 , Mike Gibney  4 , John C Mathers  1 ; Food4Me Study
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Free article
Randomized Controlled Trial

Effect of personalized nutrition on health-related behaviour change: evidence from the Food4Me European randomized controlled trial

Carlos Celis-Morales et al. Int J Epidemiol. .
Free article

Abstract

Background: Optimal nutritional choices are linked with better health, but many current interventions to improve diet have limited effect. We tested the hypothesis that providing personalized nutrition (PN) advice based on information on individual diet and lifestyle, phenotype and/or genotype would promote larger, more appropriate, and sustained changes in dietary behaviour.

Methods: : Adults from seven European countries were recruited to an internet-delivered intervention (Food4Me) and randomized to: (i) conventional dietary advice (control) or to PN advice based on: (ii) individual baseline diet; (iii) individual baseline diet plus phenotype (anthropometry and blood biomarkers); or (iv) individual baseline diet plus phenotype plus genotype (five diet-responsive genetic variants). Outcomes were dietary intake, anthropometry and blood biomarkers measured at baseline and after 3 and 6 months' intervention.

Results: At baseline, mean age of participants was 39.8 years (range 18-79), 59% of participants were female and mean body mass index (BMI) was 25.5 kg/m 2 . From the enrolled participants, 1269 completed the study. Following a 6-month intervention, participants randomized to PN consumed less red meat [-5.48 g, (95% confidence interval:-10.8,-0.09), P = 0.046], salt [-0.65 g, (-1.1,-0.25), P = 0.002] and saturated fat [-1.14 % of energy, (-1.6,-0.67), P < 0.0001], increased folate [29.6 µg, (0.21,59.0), P = 0.048] intake and had higher Healthy Eating Index scores [1.27, (0.30, 2.25), P = 0.010) than those randomized to the control arm. There was no evidence that including phenotypic and phenotypic plus genotypic information enhanced the effectiveness of the PN advice.

Conclusions: Among European adults, PN advice via internet-delivered intervention produced larger and more appropriate changes in dietary behaviour than a conventional approach.

Keywords: Personalized nutrition; diet; genotype; internet-based; metabolic health; obesity; phenotype; randomized controlled trial.

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