Digital twin study highlights the need to consider psychosocial factors in T2D risk assessment and reduction efforts
By Dr Uffe Søholm [1]
Digital twin systems use data to build a virtual model, or “twin”, of a person. Researchers use this digital twin to study how health conditions may develop over time. They can also test how risk might be reduced. In simple terms, digital twins allow researchers to try out “what if” scenarios and support more personalised care.
Most research on type 2 diabetes (T2D) risk has focused on biomedical factors. These include body mass index (BMI) and blood pressure. Psychosocial factors, including mental health, are gaining more attention but are still often overlooked.
About the Study
Researchers from the UK added behavioural and psychosocial data to a digital twin model. The study [2] included data from 19,774 participants in the UK Biobank. The model was used to predict when T2D might develop and how T2D risk could be reduced or delayed.
Key findings
Loneliness, sleep difficulties, and mental health problems (such as depression or anxiety) were strong predictors of higher T2D risk. When all three occurred together, the combined increase in risk was substantially larger. The researchers also found several well-establisheed risk factors:
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- BMI had a strong and direct link to T2D risk. Note: BMI is most appropriate for population-level risk estimation rather than individual prediction.
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- Diet had modest but consistent effects. Higher intake of salt and processed foods increased risk. Lower intake of protective food also increased risk. In fact, diet played a bigger role when people experienced psychosocial stress.
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- Older adults had a higher risk of T2D.
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- Clear differences were observed across ethnic groups. People of Bangladeshi, Indian, Pakistani, African, and Caribbean descent had higher risk of T2D.
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Why does this matter
The researchers emphasise that psychosocial factors such as loneliness, sleep difficulties, and mental health should not be viewed as separate or secondary to physical health. Instead, they appear to be meaningfully connected to metabolic risk.
This reinforces the importance of integrating psychosocial assessment and support into risk reduction programs. We also need to recognise the role of social connection and wellbeing in shaping health behaviours and physiology.
The researchers suggested three main ways to help reduce T2D risk:
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- Behavioural counselling that considers mood, social connections, and sleep hygiene.
- Community programs that reduce isolation and build support networks.
- Care models that bring together primary care with mental health and sleep specialists.
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Overall, the study shows that while biomedical factors remain important, effective risk-reduction requires a holistic approach. Greater attention to psychosocial factors may strengthen health promotion initiatives and programs.
A note on risk
These findings do not mean that loneliness, sleep difficulties, or mental health problems directly cause T2D on their own. The findingsare based on patterns seen in a model, not exact predictions for any individual person. What the study does show is that these experiences often occur alongside higher diabetes risk, and they may play a role as part of a wider mix of factors that influence health over time.
Further reading
Interested in the role of behavioural and psychosocial factors in type 2 diabetes (T2D) risk reduction? Check out some of our past blogs:
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- A little less stigmatisation, a little more ACTion! [3]Can Acceptance and Commitment Therapy (ACT) make type 2 diabetes risk-reduction programs more supportive?
- How can behavioural science contribute to type 2 diabetes prevention research? [4] Seven recommendations from seven experts in the field
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Reference:
Kiran M, Xie Y, Ball G, Schutte R, Anjum N and Pierscionek B (2026) A digital twin framework for predicting and simulating type 2 diabetes onset using retrospective lifestyle data. [5] Front. Digit. Health 8:1710829. doi: 10.3389/fdgth.2026.1710829