Daily Steps for Prediabetes and Type 2 Diabetes Over Two Years: Seasonal and Monthly Variation

Abstract
Background: Individuals living with chronic diseases like type 2 diabetes may find it challenging to engage in physical activity when the weather is unfavorable. However, research on how the season affects their physical activity levels is lacking.
Aim: This study examines the influence of season and months of the year on self-monitored step counts in individuals with prediabetes and type 2 diabetes.
Methods: This study is a secondary analysis of Sophia Step Study. In eight rounds, participants were recruited through primary care centers. The study measured physical activity using step counters (Yamax Digiwalker), and the participants wore step counters and reported daily steps on a website. Daily step patterns were examined seasonally (summer, fall, winter, and spring) and monthly. Two linear mixed models analyzed the association between independent variables (seasons and months) and dependent variables (steps). The model was adjusted for sex, age, and body mass index, and a random intercept by subject was employed.
Result: The step counts were significantly higher during summer (7824, 95% CI [7762, 7889]) and spring (7805, 95% CI [7757, 7852]) when compared to winter (7097, 95% CI [7052, 7145]) and fall (7422, 95% CI [7349, 7490]). The analysis also indicated that the highest number of step counts was registered in May (7992, 95% CI [7904, 8070]), followed by June (7967, 95% CI [7895,8062]). The lowest step counts were registered in January (6943, 95% CI 68855, 7033) and November with step counts of (7208, 95% CI [7112,7289]).
Conclusion: This study revealed a noticeable variation in self-reported daily steps self-monitored by people with prediabetes and type 2 diabetes over two years, along with seasonal and monthly weather patterns. The study also indicated that specific weather conditions during certain months, such as May, June, and July, may be more favorable for physical activity.