New research from the University of Surrey has established a link between a predilection for sugary foods and an increased risk of depression, diabetes, and stroke. Published in the Journal of Translational Medicine, this comprehensive study utilised anonymised dietary preferences from 180,000 participants sourced from the UK Biobank. By employing artificial intelligence, researchers were able to classify these individuals into three distinct dietary profiles:
The ‘Health-Conscious’ profile includes individuals favouring fruits and vegetables over animal products and sugary treats. The ‘Omnivore’ profile describes those with a diverse palate, including meats, fish, some vegetables, sweets, and desserts. Lastly, the ‘Sweet Tooth’ profile is characterised by a preference for sugary foods and beverages, with less interest in healthier alternatives like fruits and vegetables.
The Surrey research team further analysed the UK Biobank data, focusing on blood samples tested for 2,923 proteins and 168 metabolites. Proteins play a crucial role in the body, aiding in everything from infection defence to muscle function and cognitive processes. Metabolites, however, are small molecules that arise during digestion and other metabolic processes, providing insights into the body’s functional state. The researchers could discern significant biological differences by examining the variations in these proteins and metabolites across the groups.
Professor Nophar Geifman, the study’s senior author and a Professor of Health and Biomedical Informatics at the University of Surrey, commented on the findings, stating that one’s dietary preferences could be directly connected to one’s health outcomes. He highlighted that those with a strong inclination towards sugary foods — identified as the ‘Sweet Tooth’ group — were found to be 31% more likely to suffer from depression. This group also displayed elevated rates of diabetes and vascular heart issues in comparison to their counterparts.
Professor Geifman emphasised the significance of employing data-driven AI techniques to identify and categorise individuals based on their dietary habits, noting that these categories correlate meaningfully with health outcomes and biological markers. He pointed out the detrimental role processed sugars often play in modern diets, advocating for a societal shift towards more mindful eating habits while clarifying that the intent is not to dictate dietary choices but to provide information.
The study also examined the three groups via standard blood biochemistry tests. It was found that the ‘Sweet Tooth’ group had increased levels of C-reactive protein, a marker for inflammation, higher glucose levels and poor lipid profiles, indicative of heightened risks for diabetes and cardiovascular diseases. Conversely, the ‘Health-Conscious’ group reported higher dietary fibre intake and reduced risks for heart failure, chronic kidney diseases, and stroke. The ‘Omnivore’ group presented with moderate health risks.
These findings are further contextualised by data from the British Nutrition Foundation, which indicates that between 9% and 12.5% of caloric intake in the UK derives from free sugars —sugars added to foods or beverages. Notably, biscuits, buns, cakes, pastries, and fruit pies are significant sources of free sugars for adults. At the same time, sugary soft drinks and alcoholic beverages also contribute significantly to the overall intake of free sugars.
More information: Hana F. Navratilova et al, Artificial intelligence driven definition of food preference endotypes in UK Biobank volunteers is associated with distinctive health outcomes and blood based metabolomic and proteomic profiles, Journal of Translational Medicine. DOI: 10.1186/s12967-024-05663-0
Journal information: Journal of Translational Medicine Provided by University of Surrey
