Improving lifestyle behaviours has considerable potential for reducing the global burden of non-communicable diseases, promoting better health across the life-course and increasing well-being. However, realising this potential will require the development, testing and implementation of much more effective behaviour change interventions than are used conventionally. Therefore, the aim of this study was to conduct a multi-centre, web-based, proof-of-principle study of personalised nutrition (PN) to determine whether providing more personalised dietary advice leads to greater improvements in eating patterns and health outcomes compared to conventional population-based advice. A total of 5,562 volunteers were screened across seven European countries; the first 1,607 participants who fulfilled the inclusion criteria were recruited into the trial. Participants were randomly assigned to one of the following intervention groups for a 6-month period: Level 0—control group—receiving conventional, non-PN advice; Level 1—receiving PN advice based on dietary intake data alone; Level 2—receiving PN advice based on dietary intake and phenotypic data; and Level 3—receiving PN advice based on dietary intake, phenotypic and genotypic data. A total of 1,607 participants had a mean age of 39.8 years (ranging from 18 to 79 years). Of these participants, 60.9 % were women and 96.7 % were from white-European background. The mean BMI for all randomised participants was 25.5 kg m−2, and 44.8 % of the participants had a BMI ≥ 25.0 kg m−2. Food4Me is the first large multi-centre RCT of web-based PN. The main outcomes from the Food4Me study will be submitted for publication during 2015.
- Cosmetics & Fragrances
- Food Safety & Nutrition
- Agri-Food Science
Our platform hosts products designed and developed to advance global health and safety and improve the way your data is used. Find out more about the way we handle complex projects and help our clients gain valuable insights.
Dietary Analysis Tools
Creme Global Platform
We are on a mission to enable better decision-making in a complex world using science and data.