Physical Activity Evaluation Using Activity Trackers for Type 2 Diabetes Prevention in Patients with Prediabetes

Antanas Bliudzius, Kristina Svaikeviciene, Roma Puronaite and Vytautas Kasiulevicius
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Antanas Bliudzius: Family Medicine and Oncology, Clinic of Internal Diseases, Faculty of Medicine, Vilnius University, M.K. Ciurlionio Str. 21/27, LT-03101 Vilnius, Lithuania
Kristina Svaikeviciene: Family Medicine and Oncology, Clinic of Internal Diseases, Faculty of Medicine, Vilnius University, M.K. Ciurlionio Str. 21/27, LT-03101 Vilnius, Lithuania
Roma Puronaite: Institute of Data Science and Digital Technologies, Vilnius University, Akademijos Str. 4, LT-08412 Vilnius, Lithuania
Vytautas Kasiulevicius: Family Medicine and Oncology, Clinic of Internal Diseases, Faculty of Medicine, Vilnius University, M.K. Ciurlionio Str. 21/27, LT-03101 Vilnius, Lithuania

IJERPH, 2022, vol. 19, issue 14, 1-11

Abstract: Background: Prediabetes is a reversible condition, but lifestyle-changing measures, such as increasing physical activity, should be taken. This article explores the use of Fitbit activity trackers to assess physical activity and its impact on prediabetic patient health. Methods: Intervention study. In total, 30 volunteers (9 males and 21 females), aged 32–65 years, with impaired glucose levels and without diabetes or moving disorders, received Fitbit Inspire activity trackers and physical activity recommendations. A routine blood check was taken during the first and second visits, and body composition was analyzed. Physical activity variability in time was assessed using a Poincare plot. Results: The count of steps per day and variability differed between patients and during the research period, but the change in total physical activity was not statistically significant. Significant positive correlations between changes in lipid values, body mass composition, and variability of steps count, distance, and minutes of very active physical activity were observed. Conclusions: When assessing physical activity, data doctors should evaluate not just the totals or the medians of the steps count, but also physical activity variability in time. The study shows that most changes were better linked to the physical activity variability than the total count of physical activity.

Keywords: prediabetes; activity trackers; variability (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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