Personalised nutrition advice reduces intake of discretionary foods and beverages: findings from the Food4Me randomised controlled trial

Katherine M Livingstone, Carlos Celis-Morales, Santiago Navas-Carretero, Rodrigo San-Cristobal, Hannah Forster, Clara Woolhead, Clare B O'Donovan, George Moschonis, Yannis Manios, Iwona Traczyk, Thomas E Gundersen, Christian A Drevon, Cyril F M Marsaux, Rosalind Fallaize, Anna L Macready, Hannelore Daniel, Wim H M Saris, Julie A Lovegrove, Mike Gibney, Eileen R Gibney, Marianne Walsh, Lorraine Brennan, J Alfredo Martinez, John C Mathers, Food4Me Study, Katherine M Livingstone, Carlos Celis-Morales, Santiago Navas-Carretero, Rodrigo San-Cristobal, Hannah Forster, Clara Woolhead, Clare B O'Donovan, George Moschonis, Yannis Manios, Iwona Traczyk, Thomas E Gundersen, Christian A Drevon, Cyril F M Marsaux, Rosalind Fallaize, Anna L Macready, Hannelore Daniel, Wim H M Saris, Julie A Lovegrove, Mike Gibney, Eileen R Gibney, Marianne Walsh, Lorraine Brennan, J Alfredo Martinez, John C Mathers, Food4Me Study

Abstract

Background: The effect of personalised nutrition advice on discretionary foods intake is unknown. To date, two national classifications for discretionary foods have been derived. This study examined changes in intake of discretionary foods and beverages following a personalised nutrition intervention using these two classifications.

Methods: Participants were recruited into a 6-month RCT across seven European countries (Food4Me) and were randomised to receive generalised dietary advice (control) or one of three levels of personalised nutrition advice (based on diet [L1], phenotype [L2] and genotype [L3]). Dietary intake was derived from an FFQ. An analysis of covariance was used to determine intervention effects at month 6 between personalised nutrition (overall and by levels) and control on i) percentage energy from discretionary items and ii) percentage contribution of total fat, SFA, total sugars and salt to discretionary intake, defined by Food Standards Scotland (FSS) and Australian Dietary Guidelines (ADG) classifications.

Results: Of the 1607 adults at baseline, n = 1270 (57% female) completed the intervention. Percentage sugars from FSS discretionary items was lower in personalised nutrition vs control (19.0 ± 0.37 vs 21.1 ± 0.65; P = 0.005). Percentage energy (31.2 ± 0.59 vs 32.7 ± 0.59; P = 0.031), percentage total fat (31.5 ± 0.37 vs 33.3 ± 0.65; P = 0.021), SFA (36.0 ± 0.43 vs 37.8 ± 0.75; P = 0.034) and sugars (31.7 ± 0.44 vs 34.7 ± 0.78; P < 0.001) from ADG discretionary items were lower in personalised nutrition vs control. There were greater reductions in ADG percentage energy and percentage total fat, SFA and salt for those randomised to L3 vs L2.

Conclusions: Compared with generalised dietary advice, personalised nutrition advice achieved greater reductions in discretionary foods intake when the classification included all foods high in fat, added sugars and salt. Future personalised nutrition approaches may be used to target intake of discretionary foods.

Trial registration: Clinicaltrials.gov NCT01530139 . Registered 9 February 2012.

Keywords: Adults, Food4Me; Discretionary; Discretionary foods and beverages; European; Internet-based; Intervention; Personalised nutrition.

Conflict of interest statement

TEG is the CEO of Vitas Ltd. TEG and CAD have shares in Vitas Ltd., and CAD is a board member and consultant in Vitas Ltd.; no other conflict of interests. KML is a consultant for HeadUp Labs Pty Ltd. WHMS has received research support from several food companies such as Nestle, DSM, Unilever, Nutrition et Sante and Danone as well as pharmaceutical companies such as GSK, Novartis and Novo Nordisk and grants from the European Union. He is an unpaid scientific adviser for the International Life Science Institute, ILSI Europe. MG reports that he is a non-remunerated member of the Google Food Innovation Lab Community of Practice on Personalized Nutrition. JCM reports grants from European Union, during the conduct of the study; grants and personal fees from Medical Research Council, grants and personal fees from Biotechnology and Biological Sciences Research Council, personal fees and non-financial support from Waltham Pet Nutrition, personal fees and non-financial support from University of Wageningen, The Netherlands, non-financial support from Technical University Munich, non-financial support from University College Dublin, non-financial support from University of Groningen, The Netherlands, non-financial support from University of Maastricht, The Netherlands, outside the submitted work. JAL has received research funding outside of the submitted work from Medical Research Council, Biotechnology and Biological Sciences Research Council and European Union with in kind provision of foods from Arla, AAK and Unilever and research funding from the Dairy Council, UK. She was a member of the UK Government’s Scientific Advisory Committee for Nutrition (SACN) and a member of SACNs Carbohydrate Working Group and Saturated Fats Working Group during and after the study. For all other authors no conflict of interest is reported.

Figures

Fig. 1
Fig. 1
Intakes of discretionary foods and beverages (%E) at baseline for participants in seven European countries. Values represent means ± SE. FSS, Food Standards Scotland classification of discretionary foods and beverages. ADG, Australian Dietary Guidelines classification of discretionary foods and beverages

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