Evidence mapPaperPMID 41769158Full record

ArticleFrontiers in sports and active living2026

Temporal gradient analysis of blood glucose responses to non-standard physical activity: a free-living study in type 1 diabetes.

Ahmad Bilal, Hood Thabit, Paul W Nutter, Simon Harper

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Article in Frontiers in sports and active living, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Ahmad BilalDepartment of Computer Science, The University of Manchester, Manchester, United Kingdom.
Hood ThabitDiabetes, Endocrine and Metabolism Centre, Manchester Royal Infirmary, Manchester University NHS, Manchester, United Kingdom.
Paul W NutterDepartment of Computer Science, The University of Manchester, Manchester, United Kingdom.
Simon HarperDepartment of Computer Science, The University of Manchester, Manchester, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Daily physical activity (PA) impacts blood glucose (BG) in individuals with Type 1 Diabetes Mellitus (T1DM), with effects varying by intensity, duration, and timing. Predicting BG changes during free-living activity remains challenging but may help prevent hypoglycaemia. Previous studies have focused on the impact of PA on BG levels, but only during exercise sessions, not throughout the entire day. Methods: Using retrospective data from eight individuals with T1DM (mean age 67 years; 3 female, 5 male), we analysed whether non-standard PA, defined as activity exceeding the individual's mean habitual level in a preceding interval, was associated with steeper downward trends in BG. PA was quantified using wrist-worn accelerometry, and BG responses were analysed using gradient-based methods across 20, 40, and 60 min time windows. Results: Two hypotheses were evaluated. Hypothesis 1 assessed whether BG decline intensified during existing downward trends and achieved an accuracy above 83.33%, with F1-scores exceeding 0.83 at shorter intervals. Hypothesis 2 examined BG declines following prior increases and showed greater variability; accuracy ranged from 73.53% to 88.33%, with the lowest F1-score of 0.75 at the 60 min window. Conclusion: We have found a reliable correlation between increased levels of PA and BG levels under free-living conditions. These findings establish a foundation for future work aimed at quantifying BG responses to PA and developing personalised decision-support tools for insulin or carbohydrate adjustment.

Indexed as

blood glucosecontinuous glucose monitoringfree-livinggradient analysispersonalised modellingphysical activitytype 1 diabeteswearable sensors

Identifiers

PMID41769158
PMCPMC12946094

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