An Aerobic Cooldown After Morning, Fasted Resistance Exercise Has Limited Impact on Post-exercise Hyperglycemia in Adults With Type 1 Diabetes: A Randomized Crossover Study.

OBJECTIVES: Expert guidelines recommend an aerobic cooldown to lower blood glucose for the management of post-exercise hyperglycemia. This strategy has never been empirically tested. Our aim in this study was to compare the glycemic effects of performing an aerobic cooldown vs not performing a cooldown after a fasted resistance exercise session. We hypothesized that the cooldown would lower blood glucose in the 30 minutes after exercise and would result in less time in hyperglycemia in the 6 hours after exercise. METHODS: Participants completed 2 identical resistance exercise sessions. One was followed by a low-intensity (30% of peak oxygen consumption) 10-minute cycle ergometer cooldown, and the other was followed by 10 minutes of sitting. We compared the changes in capillary glucose concentration during these sessions and continuous glucose monitoring (CGM) outcomes over 24 hours post-exercise. RESULTS: Sixteen participants completed the trial. Capillary glucose was similar between conditions at the start of exercise (p=0.07). Capillary glucose concentration decreased by 0.6±1.0 mmol/L during the 10-minute cooldown, but it increased by 0.7±1.3 mmol/L during the same time in the no-cooldown condition. The resulting difference in glucose trajectory led to a significant interaction (p=0.02), with no effect from treatment (p=0.7). Capillary glucose values at the end of recovery were similar between conditions (p>0.05). There were no significant differences in CGM outcomes. CONCLUSIONS: An aerobic cooldown reduces glucose concentration in the post-exercise period, but the small and brief nature of this reduction makes this strategy unlikely to be an effective treatment for hyperglycemia occurring after fasted exercise.

Exploring Technology's Influence on Health Behaviours and Well-being in Type 1 Diabetes: a Review.

PURPOSE OF REVIEW: Maintaining positive health behaviours promotes better health outcomes for people with type 1 diabetes (T1D). However, implementing these behaviours may also lead to additional management burdens and challenges. Diabetes technologies, including continuous glucose monitoring systems, automated insulin delivery systems, and digital platforms, are being rapidly developed and widely used to reduce these burdens. Our aim was to review recent evidence to explore the influence of these technologies on health behaviours and well-being among adults with T1D and discuss future directions. RECENT FINDINGS: Current evidence, albeit limited, suggests that technologies applied in diabetes self-management education and support (DSME/S), nutrition, physical activity (PA), and psychosocial care areas improved glucose outcomes. They may also increase flexibility in insulin adjustment and eating behaviours, reduce carb counting burden, increase confidence in PA, and reduce mental burden. Technologies have the potential to promote health behaviours changes and well-being for people with T1D. More confirmative studies on their effectiveness and safety are needed to ensure optimal integration in standard care practices.

Systematic Review and Meta-analysis of Blood Glucose Response to High-intensity Interval Exercise in Adults With Type 1 Diabetes.

OBJECTIVES: Exercise-induced hyperglycemia is recognized in type 1 diabetes (T1D) clinical guidelines, but its association with high-intensity intermittent exercise (HIIE) in acute studies is inconsistent. In this meta-analysis, we examined the available evidence of blood glucose responses to HIIE in adults with T1D. The secondary, aim was to examine predictors of blood glucose responses to HIIE. We hypothesized that there would be no consistent effect on blood glucose from HIIE, unless examined in the context of participant prandial status. METHODS: We conducted a literature search using key words related to T1D and HIIE. Studies were required to include at least 6 participants with T1D with a mean age >18 years, involve an HIIE intervention, and contain pre- and postexercise measures of blood glucose. Analyses of extracted data were performed using a general inverse variance statistical method with a random effects model and a weighted multiple regression. RESULTS: Nineteen interventions from 15 reports were included in the analysis. A mean overall blood glucose decrease of -1.3 mmol/L (95% confidence interval [CI], -2.3 to -0.2 mmol/L) was found during exercise, albeit with high heterogeneity (I2=84%). When performed after an overnight fast, exercise increased blood glucose by +1.7 mmol/L (95% CI, 0.4 to 3.0 mmol/L), whereas postprandial exercise decreased blood glucose by -2.1 mmol/L (95% CI, -2.8 to -1.4 mmol/L), with a statistically significant difference between groups (p<0.0001). No associations with fitness (p=0.4), sex (p=0.4), age (p=0.9), exercise duration (p=0.9), or interval duration (p=0.2) were found. CONCLUSION: The effect of HIIE on blood glucose is inconsistent, but partially explained by prandial status.