TOPLINE:

Step count thresholds for reducing the risk for type 2 diabetes (T2D) varied according to genetic susceptibility, with individuals at high polygenic risk requiring higher daily step counts to achieve risk reduction comparable to that in individuals at lower risk. Combining wearable-derived daily step counts with polygenic risk scores (PRSs) in prediction models improved the risk assessment of T2D.

METHODOLOGY:

• Limited evidence exists on whether one-size-fits-all step-count targets are appropriate or whether combining step counts with genetic risk improves the prediction of incident T2D.
• Researchers conducted a prospective cohort study of 4589 adults (median age, 58 years) from a research program in the US to assess the impact of daily step counts and PRSs on the risk for incident T2D.
• All participants had valid Fitbit step data (≥ 15 days/month) and whole genome-derived PRSs; participants with prevalent T2D or who developed T2D within 180 days of their first valid step record were excluded.
• The mean daily step count at baseline was calculated as the average of all valid daily step counts from each participant’s first valid step record until the end of the initial 180-day period.
• Incident T2D was defined as the earliest occurrence of an A1c level ≥ 6.5%, a plasma glucose level ≥ 126 mg/dL, or an electronic health record diagnosis of T2D over a median follow‑up duration of 2.92 years.

TAKEAWAY:

• During the follow-up period, 265 participants developed T2D, representing a cumulative incidence of 5.77%.
• Overall risk reduction was observed at around 7000 steps/day; however, this threshold increased to approximately 7800 steps/day for individuals at high genetic risk and decreased to about 5800 steps/day for those at lower risk (P < .001 for all).
• Each additional 1000 daily steps was associated with a 17% reduced risk for T2D (adjusted hazard ratio [aHR], 0.83; 95% CI, 0.79-0.88), whereas each one-standard deviation increase in PRSs was associated with a 2.62-fold increased risk for T2D (aHR, 2.62; 95% CI, 2.32-2.96).
• Adding mean daily step count to a model with clinical covariates improved T2D risk prediction, increasing the concordance index from 0.748 to 0.774; including PRSs further increased it to 0.867.

IN PRACTICE:

“Combining step counts with genetic risk could help identify individuals with elevated inherited risk who may require higher activity levels, enabling more personalized activity prescriptions, adaptive mobile health interventions, and targeted prevention strategies,” the authors wrote.

SOURCE:

This study was led by Md Hafizur Rahman, Institute for Population and Precision Health at the University of Chicago, Chicago. It was published online in the Journal of Clinical Endocrinology & Metabolism.

LIMITATIONS:

This study relied on baseline average step count, which did not capture longitudinal changes, seasonal variations, or behavioral shifts. It did not account for potential confounders such as diet, sleep, psychosocial factors, or medication use. Additionally, including only participants with sufficient wearable data may have introduced selection bias.

DISCLOSURES:

This study was supported by the Institute for Population and Precision Health. The authors declared having no competing interests.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.