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People with a preference for sweets are at a higher risk of developing depression, diabetes, and suffering a stroke, according to new research from the University of Surrey.

The study, published in the Journal of Translational Medicine, took anonymised information on the food preferences of 180,000 volunteers within the UK Biobank and used artificial intelligence to group them into three general profiles:

• Health-conscious: prefer fruits and vegetables over animal-based and sweet foods.

• Omnivore: Likes most foods, including meats, fish, and some vegetables, as well as sweets and desserts.

• Sweet tooth: Prefer sweet foods and sugary drinks and is less interested in healthier options like fruit and vegetables.

The Surrey team looked at UK Biobank data on blood samples where 2,923 proteins and 168 metabolites had been measured to see how these levels changed in each group.

Proteins are the workhorses of the body and do everything from fighting infections to muscle contractions and thinking. Metabolites are small molecules produced during digestion and other chemical processes in the body, and they can tell us a lot about how well our body is functioning. By comparing these blood-based proteins and metabolites, the researchers could get a clearer picture of the biological differences between the groups.

Professor Nophar Geifman, senior author of the study and Professor of Health and Biomedical Informatics at the University of Surrey, said:

“The foods that you like or dislike seem to directly link to your health. If your favourite foods are cakes, sweets, and sugary drinks, then our study’s results suggest that this may have negative effects on your health. We found that the sweet tooth group are 31% more likely to have depression. We also found that the sweet tooth group had higher rates of diabetes, as well as vascular heart conditions, compared to the other two groups.

“Importantly, by using data-driven Artificial Intelligence methods, we were able to identify groups of people defined by their food preferences, and these groups are meaningful in that they are linked to health outcomes as well as biological markers.

“Processed sugar is a key factor in the diet of many, and these results are yet more evidence that, as a society, we should do all that we can to think before we eat, stressing that no one wants to tell people what to do, our job is just informing people.”

The researchers also looked at differences between the three groups in standard blood biochemistry tests.

Professor Geifman continues:

“In the sweet tooth group, they had higher levels of C reactive protein, which is a marker for inflammation. Their blood results also show higher levels of glucose and poor lipid profiles, which is a strong warning sign for diabetes and heart disease.”

Conversely, the health-conscious group, which also had higher dietary fibre intake, had lower risks for heart failure, chronic kidney diseases and stroke, while the omnivore group had moderate health risks.

According to the British Nutrition Foundation, on average, in the UK, between 9% to 12.5% of an individual’s calories come from free sugar – this is defined as sugar that is added to food or drink. Biscuits, buns, cakes, pastries and fruit pies are the biggest single contributors for adults, but together, sugary soft drinks and alcoholic drinks contribute the most to free sugar intake.

Reference:

Navratilova, H.F., Whetton, A.D. & Geifman, N. 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. J Transl Med 22, 881 (2024). https://doi.org/10.1186/s12967-024-05663-0.

Recent studies have revealed promising results regarding the use of fenugreek (Trigonella foenum-graecum L.) seed extract in modifying the properties of wheat (Triticum aestivum L.) starch. The research by Vivek Chandra Verma, Department of Biochemistry, Panjab University, Chandigarh, India, and colleagues highlights the extract’s potential to lower the glycemic index (GI) and improve in vitro digestibility, making it a valuable addition to functional food formulations.

Diabetes is a significant global health challenge, nearing epidemic levels. In 2021, diabetes mellitus accounted for 6.7 million deaths worldwide, with projections suggesting a nearly tenfold increase in mortality by 2030, potentially reaching 783 million by 2045. Wheat starch, which makes up about 70% of the wheat grain’s endosperm, is crucial in this issue. The rapid hydrolysis of wheat starch can lead to spikes in postprandial glucose levels, contributing to diabetes. The action of enzymes like α-amylase and α-glucosidase on carbohydrates primarily drives this rise in blood glucose. While various medications exist for diabetes management, they often come with high costs and potential side effects. In contrast, natural remedies such as fenugreek have been used in traditional medicine for their ability to help regulate blood glucose levels.

The glycemic index is a critical measure of how quickly carbohydrate-containing foods raise blood glucose levels. Foods with a high GI can lead to spikes in blood sugar, which is particularly concerning for individuals with diabetes or insulin sensitivity. Considering this, Dr. Chandra Verma and colleagues aimed to study the impact of fenugreek seed extract (FSE) on in vitro starch hydrolysis by pancreatic α-amylase and the ultrastructural characteristics of starch.

For this purpose, the researchers evaluated wheat cultivars for total starch, amylose content, and resistant starch levels while also being screened for their predicted glycemic index. Microscopic analysis was performed to assess the size and shape of starch granules, comparing native starch with that treated with FSE. They found that FSE significantly inhibited enzymatic starch hydrolysis, with the strongest inhibitory effect observed at a concentration of 0.2% FSE.

“These findings indicate that fenugreek may help regulate blood glucose levels by diminishing the hydrolysis of wheat starch, making it a promising option for diabetes management,” the researchers wrote.

Incorporating fenugreek seed extract into wheat starch presents an innovative approach to reducing glycemic responses and enhancing digestibility, as highlighted by the study authors. As researchers continue to explore its potential, this natural ingredient could pave the way for healthier dietary options that align with the growing focus on preventive health and nutrition.

Reference:

Mate, P. S., Verma, V. C., Agrawal, S., Jaiswal, J. P., Kumari, V. V., Kumar, R., Kumari, M., Gaber, A., & Hossain, A. Effect of fenugreek (Trigonella foenum-graecum L.) seed extract on glycemic index, in vitro digestibility, and physical characterization of wheat (Triticum aestivum L.) starch. Journal of Food Science. https://doi.org/10.1111/1750-3841.17411

The study found that chest CT scans, conducted for other medical reasons, can predict hip fracture risk by assessing the pectoral muscle index (PMI) and the attenuation values of vertebral bodies. Using CT scans in this manner demonstrates an impressive area under the receiver operating curve of 0.86.

The research team noted, “Our findings reveal that, compared to the healthy control group, individuals with hip fractures were older and exhibited lower body mass index, bone mineral density, T4 Hounsfield Units (T4HU) at the fourth thoracic vertebra, and pectoral muscle index volume.”

Hip fractures (HF) are often referred to as the “last fracture of life” for the elderly, making their risk assessment critically important. While research into the link between chest computed tomography (CT) imaging and HF has been limited, recent findings offer new insights.

Sheng Pan, Department of Osteoporosis, The Second Affiliated Hospital of Soochow University, Suzhou, China, and colleagues showed that PMI and vertebral body attenuation values obtained from chest CT scans can predict HF risk. This approach provides an opportunistic method to evaluate HF risk in patients without access to bone mineral density (BMD) testing, leveraging chest CT scans performed for other medical conditions.

In a retrospective study from January 2021 to January 2024, 800 participants with BMD measurements and chest CT scans were initially enrolled. Following exclusions, 472 patients were included in the final analysis, categorized into a healthy control (HC) group and a hip fracture (HF) group.

Clinical data were gathered and compared between the two groups. A predictive model was developed using logistic regression, incorporating the pectoral muscle index (PMI) and the Hounsfield units of the fourth thoracic vertebra (T4HU). The model’s predictive accuracy was evaluated through receiver operating characteristic (ROC) curve analysis. Additionally, decision curve analysis (DCA) and clinical impact curves were used to assess the model’s practical utility in a clinical setting.

The following were the key findings of the study:

• PMI and T4HU were lower in the HF group than in the HC group; low PMI and low T4HU were risk factors for HF.
• The predictive model incorporating PMI and T4HU based on age and BMI had excellent diagnostic efficacy with an area under the curve (AUC) of 0.865, sensitivity, and specificity of 0.820 and 0.754, respectively.
• The clinical utility of the model was validated using calibration curves and DCA.
• The AUC of the predictive model incorporating BMD based on age and BMI was 0.865, with sensitivity and specificity of 0.698 and 0.711, respectively.
• There was no significant difference in diagnostic efficacy between the two models.

The researchers concluded that PMI and T4HU are effective predictors of hip fractures. In the absence of dual-energy x-ray absorptiometry (DXA), they found that assessing PMI and T4HU from chest CT scans performed for other medical conditions can reliably gauge HF risk. This method allows for timely intervention and treatment, potentially reducing the incidence of hip fractures.

Reference:

Wang, X. Y., Yun, S. M., Liu, W. F., Wang, Y. K., Pan, S., & Xu, Y. J. Opportunistic Assessment of Hip Fracture Risk Based on Chest CT. Orthopaedic Surgery. https://doi.org/10.1111/os.14224