Wearable Step Counts and Genetic Risk Improve Prediction of Type 2 Diabetes: Study Shows
USA: A study published in The Journal of Clinical Endocrinology & Metabolism shows that the number of daily steps needed to reduce the risk of type 2 diabetes (T2D) varies according to an individual’s genetic susceptibility.
Led by Md Hafizur Rahman from the Institute for Population and Precision Health at The University of Chicago, the research demonstrates that combining wearable-derived activity data with polygenic risk scores (PRSs) improves the prediction of incident T2D and supports a more personalized approach to diabetes prevention.
Although daily step targets such as 7,000 or 10,000 steps are commonly recommended, evidence supporting uniform activity goals has been limited. It has also remained unclear whether integrating objective physical activity data with genetic risk can enhance early identification of people at higher risk of T2D. To address these gaps, the researchers conducted a prospective cohort study using data from the NIH All of Us Research Program.
The analysis included 4,589 adults with a median age of 58 years who had valid Fitbit step-count data for at least 15 days per month and whole-genome-derived PRSs. Individuals with existing T2D or those diagnosed within 180 days of their first valid step record were excluded. Baseline activity was defined as the average daily step count during an initial 180-day period. Participants were followed for a median of 2.92 years, and incident T2D was identified using standard clinical criteria, including elevated HbA1c, high plasma glucose levels, or a documented diagnosis in electronic health records.
Key Findings:
- During follow-up, 265 participants developed type 2 diabetes, representing a cumulative incidence of 5.77%.
- A reduction in diabetes risk was observed at approximately 7,000 steps per day overall.
- The step-count threshold for risk reduction varied by genetic susceptibility.
- Individuals with high polygenic risk scores required around 7,800 steps per day to achieve meaningful risk reduction.
- Participants with lower genetic risk experienced benefit at approximately 5,800 steps per day.
- Each additional 1,000 daily steps was associated with a 17% lower risk of developing type 2 diabetes after adjustment for clinical factors.
- Each one–standard deviation increase in polygenic risk score was associated with more than a twofold increase in diabetes risk.
- Daily step counts and polygenic risk scores contributed independent and complementary information to diabetes risk assessment.
- Risk prediction improved notably when wearable and genetic data were added to clinical models. Incorporating daily step counts enhanced discrimination, and inclusion of PRSs led to a further substantial gain.
The authors concluded that step-count targets should not be uniform and that combining activity data with genetic risk could support more personalized activity prescriptions, digital health interventions, and targeted prevention strategies for type 2 diabetes.
Reference:
Rahman, M. H., Arian, A., Konda, S., McGuinn, L. A., Islam, H., Chowdhury, M. A., Shahriar, M. H., Rayna, S. E., Farzana, S., Tasmin, S., Manna, R. M., Haider, M. R., & Ahsan, H. Predicting Incident Type 2 Diabetes Using Wearable Activity and Polygenic Risk: A Survival-Modeling Study in All of Us. The Journal of Clinical Endocrinology & Metabolism. https://doi.org/10.1210/clinem/dgaf673
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