Food for Thought at the final Food4Me Conference on Personalised Nutrition
Written by Creme Global
Professor Mike Gibney, from University College Dublin, opened the conference by asking the question “Why Food4Me?” What followed was a series of presentations attempting to bring some light to the answer to this question from a range of viewpoints.
Dr. John Mathers, from The University of Newcastle, explained how current strategies to encourage people to improve their diets, and certain health markers, have had limited success and asked if personalised nutrition can do better than these “One size fits all” approaches. To provide a scientific answer to this question, utilizing the data provided as part of the Food4Me project, a comparison was made between participants in the study based on the level of advice/treatment given to them during the project. Overall, there were four different levels of treatment allocated and are summarised below. This ranges from the Level 0 treatment which mimics the “One size fits all’ approach to the Level 4 treatment where an individual is provided personalised nutrition advice taking into consideration their dietary intake, as well as their phenotypic and genomic type.
Level 0 (L0): Generic dietary advice
Level 1 (L1): Personalisation based on DIETARY analysis
Level 2 (L2): Personalisation based on DIETARY and PHENOTYPIC analysis
Level 3 (L3): Personalisation based on DIETARY and PHENOTYPIC and GENOMIC analysis
The graphs below allow a comparison of the reduction in ‘Energy Intake’ and ‘Red Meat Intake’ after a period of six months for the four different treatment levels. Note that the extra bar in both graphs, identified as the ‘Personalised Nutrition Group (L1 + L2 + L3)’, indicates an average of Levels 1, 2, and 3. The inclusion of this bar allows a comparison between those who had received generic dietary advice (i.e. L0) and those who had received personalised advice (i.e. a member of one of the groups L1, L2 or L3).
Comparing the ‘Control Group’ with the ‘Personalised Nutrition Group’ in both graphs shows a marked reduction in both the ‘Energy Intake’ and ‘Red Meat Intake’ for the latter group. This outcome indicates the dietary benefits of the study for the ‘Personalised Nutrition Group’, and that the delivery of this information through the medium of the internet worked.
Cronan McNamara, CEO of Creme Global (the software and algorightms partner in Food4Me) stated: “It was exciting to experience the real sense of celebration at the event. There was a strong feeling that this meeting marked the successful completion of an exciting and innovative project and that personalised nutrition has worked. Congratulations to Prof. Mike Gibney and his team for leading this project to a successful outcome.”
He added “There was also a palpable sense of optimism for the future of personalised nutrition and a drive to take the results forward in whatever form that may take. From a research point of view, there are plans to write a raft of secondary analysis papers on the data from the project. Industry were also keen to find a way to implement the results of the research in tangible market opportunities to enhance nutrition for European consumers.”
Other speakers focused on personalised nutrition under the following headings
• Consumer attitudes towards, and the adoption of, personalised nutrition
• Personalised nutrition: a commercial opportunity or the responsibility of health care providers?
• Do we know enough (to personalise nutrition)?
• Business and Value Creation Models of Personalised Nutrition
• What legislative issues need to addressed in Europe?
Silvia Kolossa, from the Technical University of Munich (TUM), examined personalised nutrition technologies and the meal planning tool (MPT) implemented in the Food4Me software. Given relevant nutrient information for food portions and individuals, as well as the food and ingredient preferences of the individual, a mathematical technique called ‘linear optimisation’ is invoked to allocate a weekly menu to the individual who ensures that
• their nutrient intake falls within defined thresholds
• at least one breakfast, snack, main and light meal each, and five portions of fruit and vegetables are included per day
• preferences of the recipes are maximised
So, in conclusion to answer the question: “Does Personalised Nutrition work?” the answer coming from Food4Me is a resounding yes. The studies have clearly shown that internet delivery of personalised nutrition was effective in that they had a significantly higher positive effect on the dietary habits of participants over and above the control group.
In the closing discussion at the meeting, Cronan McNamara stated that he believes that the opportunity for personalised nutrition lies not in the food industry being able to produce products customised to each individual’s requirements – this would be highly impractical – but in smart, analytics-based services which can help consumers to choose between the multitude of food products and services available to tailor a diet exactly to their individual needs. With the success of internet delivery dietary advice in Food4Me proof of principle study, the opportunity for accessible personalised nutrition services for every consumer in the EU and further afield has moved a big step closer.
About the Food4Me Project
The Food4Me project is an EU FP7 funded project on personalised nutrition in which Creme Global are amongst 25 partners from 12 European countries.
As part of the project, participants from 7 member states were required to complete food frequency questionnaires which detailed the foods consumed by the individual over a fixed period of time. Based on the consumption levels of each individual, the intakes of a selection of nutrients were calculated and presented to the participant along with dietary advice on food choice. Also, based on phenotypic and genetic information provided by participants, experts were able to provide tailored advice for individuals on their consumption habits.
Creme Global developed the Food Frequency Questionnaire (FFQ) software, data warehousing system, researcher tools and the decision tree software to provide automated nutrition feedback to participants.