Barriers to Physical Activity in Children and Adults Living With Type 1 Diabetes: A Complex Link With Real-life Glycemic Excursions

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 Factors That Influence Postexercise Glycemia in Youth With Type 1 Diabetes in the Real World: The Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) Study

OBJECTIVE

To explore 24-h postexercise glycemia and hypoglycemia risk, data from the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study were analyzed to examine factors that may influence glycemia.

RESEARCH DESIGN AND METHODS

This was a real-world observational study with participant self-reported physical activity, food intake, and insulin dosing (multiple daily injection users). Heart rate, continuous glucose data, and available pump data were collected.

RESULTS

A total of 251 adolescents (42% females), with a mean ± SD age of 14 ± 2 years, and hemoglobin A1c (HbA1c) of 7.1 ± 1.3% (54 ± 14.2 mmol/mol), recorded 3,319 activities over ∼10 days. Trends for lower mean glucose after exercise were observed in those with shorter disease duration and lower HbA1c; no difference by insulin delivery modality was identified. Larger glucose drops during exercise were associated with lower postexercise mean glucose levels, immediately after activity (P < 0.001) and 12 to <16 h later (P = 0.02). Hypoglycemia occurred on 14% of nights following exercise versus 12% after sedentary days. On nights following exercise, more hypoglycemia occurred when average total activity was ≥60 min/day (17% vs. 8% of nights, P = 0.01) and on days with longer individual exercise sessions. Higher nocturnal hypoglycemia rates were also observed in those with longer disease duration, lower HbA1c, conventional pump use, and if time below range was ≥4% in the previous 24 h.

CONCLUSIONS

In this large real-world pediatric exercise study, nocturnal hypoglycemia was higher on nights when average activity duration was higher. Characterizing both participant- and event-level factors that impact glucose in the postexercise recovery period may support development of new guidelines, decision support tools, and refine insulin delivery algorithms to better support exercise in youth with diabetes.

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.

Continuous moderate and intermittent high-intensity exercise in youth with type 1 diabetes: Which protection for dysglycemia?

AIM

From an early age, exercise is key to managing type 1 diabetes (T1D). However, hypoglycemia around aerobic exercise is a major barrier to physical activity in children. We explore whether intermittent high-intensity aerobic exercise (IHE), designed to mimic spontaneous childhood physical activity patterns, offers better protection against glycemic drop than continuous moderate-intensity exercise (CME).

METHODS

Five boys and 7 girls with T1D (9.8 ± 1.4y) performed ergo cycle-based randomized CME and IHE of identical duration and total mechanical load [50 %PWC170vs. 15sec(150 %PWC170)/30 sec passive recovery; both during two 10-min sets, 5 min in-between]. Capillary glycemia during exercise and interstitial glucose during recovery were compared between exercises and an inactive condition, controlling for baseline glycemia, carbohydrate and insulin.

RESULTS

The exercise-induced decrease in capillary glycemia was attenuated by 1.47 mmol·L-1 for IHE vs. CME (P < 0.05). No symptomatic hypoglycemic episodes occurred during exercises. Post-exercise time in hypoglycemia did not differ between conditions. During early recovery, CME reduced time spent > 16.7 mmol·L-1 compared with inactive days (P < 0.05; CME: 0 %; IHE: 16,7 %; INACTIVE: 41,7 %).

CONCLUSION

IHE appeared to limit the glycemic drop compared to CME. Performing 20-min CME or IHE was not associated with increased hypoglycemic risk compared to being inactive. CME appeared even transiently protective against serious hyperglycemia.

Impact of a 4-week intensive track and field training intervention on glycaemia in adolescents with type 1 diabetes: The ChilDFiT1 study

AIM

To investigate the safety and efficacy of track and field training compared with intensification of insulin treatment only in adolescents with type 1 diabetes (T1D).

MATERIALS AND METHODS

Eighteen adolescents (seven females) with T1D were included (age 15.1 ± 1.1 years, HbA1c 7.3% ± 1.0% [56.3 ± 10.9 mmol/mol]). After a 4-week observational control phase, participants were randomized to either stand-alone intensive glycaemic management (IT; telemedicine or on-site visits, three times/week) or additionally performed track and field exercise (EX; three 60-minute sessions/week) for 4 weeks. Glycaemia was assessed via continuous glucose monitoring during observational control and intervention phases.

RESULTS

Time in range (70-180 mg/dL; 3.9-10.0 mmol/L) significantly improved from the observational control phase to the exercise intervention phase in EX (69% ± 13% vs. 72% ± 11%, P = .049), but not in IT (59% ± 22% vs. 62% ± 16%, P = .399). Time below range 1 (54-69 mg/dL; < 3.9 mmol/L) improved in IT (3.1% ± 1.9% vs. 2.0% ± 0.8%, P = .017) and remained stable in EX (2.0% ± 1.7 vs. 1.9% ± 1.1%, P = .999). The EX group's HbA1c ameliorated preintervention to postintervention (mean difference: ΔHbA1c -0.19% ± 0.17%, P = .042), which was not seen within the IT group (ΔHbA1c -0.16% ± 0.37%, P = .40). Glucose standard deviation was reduced significantly in EX (55 ± 11 vs. 51 ± 10 mg/dL [3.1 ± 0.6 vs. 2.8 ± 0.6 mmol/L], P = .011), but not in IT (70 ± 24 vs. 63 ± 18 mg/dL [3.9 ± 1.3 vs. 3.5 ± 1.0 mmol/L], P = .186).

CONCLUSION

Track and field training combined with intensive glycaemic management improved glycaemia in adolescents with T1D, which was not observed in the non-exercise group.

The Acute Effects of Real-World Physical Activity on Glycemia in Adolescents With Type 1 Diabetes: The Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) Study

OBJECTIVE

Data from the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study were evaluated to understand glucose changes during activity and identify factors that may influence changes.

RESEARCH DESIGN AND METHODS

In this real-world observational study, adolescents with type 1 diabetes self-reported physical activity, food intake, and insulin dosing (multiple-daily injection users) using a smartphone application. Heart rate and continuous glucose monitoring data were collected, as well as pump data downloads.

RESULTS

Two hundred fifty-one adolescents (age 14 ± 2 years [mean ± SD]; HbA1c 7.1 ± 1.3% [54 ± 14.2 mmol/mol]; 42% female) logged 3,738 activities over ∼10 days of observation. Preactivity glucose was 163 ± 66 mg/dL (9.1 ± 3.7 mmol/L), dropping to 148 ± 66 mg/dL (8.2 ± 3.7 mmol/L) by end of activity; median duration of activity was 40 min (20, 75 [interquartile range]) with a mean and peak heart rate of 109 ± 16 bpm and 130 ± 21 bpm. Drops in glucose were greater in those with lower baseline HbA1c levels (P = 0.002), shorter disease duration (P = 0.02), less hypoglycemia fear (P = 0.04), and a lower BMI (P = 0.05). Event-level predictors of greater drops in glucose included self-classified "noncompetitive" activities, insulin on board >0.05 units/kg body mass, glucose already dropping prior to the activity, preactivity glucose >150 mg/dL (>8.3 mmol/L) and time 70-180 mg/dL >70% in the 24 h before the activity (all P < 0.001).

CONCLUSIONS

Participant-level and activity event-level factors can help predict the magnitude of drop in glucose during real-world physical activity in youth with type 1 diabetes. A better appreciation of these factors may improve decision support tools and self-management strategies to reduce activity-induced dysglycemia in active adolescents living with the disease.

(Hybrid) Closed-Loop Systems: From Announced to Unannounced Exercise

Physical activity and exercise have many beneficial effects on general and type 1 diabetes (T1D) specific health and are recommended for individuals with T1D. Despite these health benefits, many people with T1D still avoid exercise since glycemic management during physical activity poses substantial glycemic and psychological challenges - which hold particularly true for unannounced exercise when using an AID system. Automated insulin delivery (AID) systems have demonstrated their efficacy in improving overall glycemia and in managing announced exercise in numerous studies. They are proven to increase time in range (70-180 mg/dL) and can especially counteract nocturnal hypoglycemia, even when evening exercise was performed. AID-systems consist of a pump administering insulin as well as a CGM sensor (plus transmitter), both communicating with a control algorithm integrated into a device (insulin pump, mobile phone/smart watch). Nevertheless, without manual pre-exercise adaptions, these systems still face a significant challenge around physical activity. Automatically adapting to the rapidly changing insulin requirements during unannounced exercise and physical activity is still the Achilles' heel of current AID systems. There is an urgent need for improving current AID-systems to safely and automatically maintain glucose management without causing derailments - so that going forward, exercise announcements will not be necessary in the future. Therefore, this narrative literature review aimed to discuss technological strategies to how current AID-systems can be improved in the future and become more proficient in overcoming the hurdle of unannounced exercise. For this purpose, the current state-of-the-art therapy recommendations for AID and exercise as well as novel research approaches are presented along with potential future solutions - in order to rectify their deficiencies in the endeavor to achieve fully automated AID-systems even around unannounced exercise.