Loneliness, poor sleep, and mental stress may quietly increase the risk of developing type 2 diabetes much more than people realize.
A new study led by Anglia Ruskin University has used advanced artificial intelligence to explore how everyday life experiences shape long-term health.
The findings, published in the journal Frontiers in Digital Health, suggest that emotional and social factors may be just as important as diet and physical health when it comes to predicting diabetes.
Type 2 diabetes is one of the fastest growing health problems worldwide. It affects more than 500 million people and happens when the body cannot properly use insulin to control blood sugar levels.
Unlike type 1 diabetes, which is caused by the immune system, type 2 diabetes is strongly linked to lifestyle and daily habits.
Because of this, scientists have long tried to predict who is most at risk, but traditional models often rely on simple measures such as body weight, age, and blood pressure.
In this new study, researchers took a different approach. They used a “digital twin” model, which is a type of artificial intelligence that creates a virtual copy of a person’s health profile.
This model can simulate how changes in daily behavior might affect health over many years. The research team used data from 19,774 adults in the UK Biobank and followed their health for up to 17 years.
Instead of focusing on medical tests, the model looked at lifestyle and emotional factors such as loneliness, sleep problems, and mental health. The results were striking. Each of these factors alone was linked to a large increase in the risk of developing type 2 diabetes. When all three were present together, the predicted risk rose dramatically.
The researchers believe this is connected to how the body responds to stress. Long-term stress can increase certain hormones, cause inflammation, and disrupt the way the body controls blood sugar. Over time, these changes may lead to diabetes.
The study also found that people experiencing stress and poor mental health were more likely to have unhealthy diets, including higher intake of processed foods and sugar. This shows how different lifestyle factors can combine to increase risk.
Another important finding was the difference between ethnic groups. People from South Asian, African, and Caribbean backgrounds had higher estimated risks, which supports earlier public health findings.
This research is important because it shows that diabetes risk is more complex than previously thought. By using digital twin technology, health professionals may be able to identify high-risk individuals earlier and provide support before the disease develops.
However, the study also has limitations. The results are based on predictions from an AI model rather than direct cause-and-effect proof. More studies are needed to confirm these findings and understand how best to use them in real-world care.
Overall, this study highlights the strong connection between mental well-being and physical health. It suggests that improving sleep, reducing loneliness, and supporting mental health could play a major role in preventing type 2 diabetes in the future.
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