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Is a better understanding of management strategies for type 1 diabetes associated with a lower risk of developing hypoglycemia during and after physical activity?
Abstract
Aims
To determine for physical activity (PA)-induced hypoglycemia among people with type 1 diabetes (PWT1D) how knowledge and T1D management strategies are associated with hypoglycemic risk.
Methods
137 active adults PWT1D completed diabetes management, PA habits and PA-associated hypoglycemia questionnaires.
Results
PA-associated hypoglycemia (during, within 1h and overnight after PA) was reported by 49 to 61% and 18% of participants felt inadequately equipped to perform regular PA safely. During PA, more hypoglycemia was reported by PWT1D with more knowledge of hypoglycemia prevention strategies and those using continuous subcutaneous insulin infusion (CSII) vs. multiple injections, decreasing basal rate 30-60 min before PA vs. no adjustment before PA and those taking snacks for unplanned PA vs. no snack. In the hour following PA, more hypoglycemia was reported by PWT1D less knowledgeable about insulin pharmacokinetics and those practicing pre-dinner vs. post-dinner PA. Overnight following PA, more hypoglycemia was reported by patients with shorter diabetes duration, CSII users having a greater understanding of exercise-induced glucose fluctuations, those reporting reducing nocturnal insulin infusion rates vs. no adjustment at night, those engaged in PA lasting at least 31 min, moderate and vigorous PA (vs. light PA) as well as regularly performing interval training vs. non-regular practice. Glycated hemoglobin and using continuous glucose monitoring system were not associated with any timing of reported PA-associated hypoglycemia.
Conclusion
PA-associated hypoglycemia is frequent. Greater knowledge of PA and T1D management is not associated with less PA-associated hypoglycemia. Diabetes management confidence could encourage higher tolerance for hypoglycemic risk.
... Rates of ''in exercise'' hypoglycemia were surprisingly higher in those on continuous subcutaneous insulin infusion (CSII) and in those who report to be knowledgeable about hypoglycemia prevention strategies for exercise (i.e., insulin dose reductions, carbohydrate feeding), compared with those on multiple daily injections (MDI) or those less knowledgeable about the typical hypoglycemia prevention strategies. 6 The reasons for the higher hypoglycemia reporting rates during exercise in those on CSII are unclear but might be related to lower glucose levels before exercise start time and/or higher levels of circulating insulin levels pre-exercise compared with those on MDI. ...
... Experimental and commercially available HCL systems have been found to improve glycemic control in laboratory settings, such as minimizing hypoglycemia while maximizing time in glycemic target range, 24 and the results presented in this analysis can help generalize this ability as the exercise sessions were free-living. However, in this analysis, the insulin modality had little effect on the probability of hypoglycemia during exercise, although the probability of developing hypoglycemia was indeed numerically less in those on MDI than for those on both types of CSII systems ( Supplementary Fig. S5), which is in line with the recent survey data by Paiement et al. 6 The reasons for the apparent differences in hypoglycemia risk rate during exercise between MDI (7.8%), HCL (8.2%), and pump (8.7%) may be related to behavioral differences on how individuals manage planned and unplanned exercise 6 and/or differences in IOB levels (median IOB at exercise start is 0.90 U for MDI, 1.51 U for HCL, and 1.12 U for pump). In any event, we found little evidence here that HCL systems were superior to MDI or CSII pump for the prevention of exercise-associated hypoglycemia when starting with the same glucose concentration, glucose rate of change, IOB, and prior time with glucose <70 mg/dL. ...
... Experimental and commercially available HCL systems have been found to improve glycemic control in laboratory settings, such as minimizing hypoglycemia while maximizing time in glycemic target range, 24 and the results presented in this analysis can help generalize this ability as the exercise sessions were free-living. However, in this analysis, the insulin modality had little effect on the probability of hypoglycemia during exercise, although the probability of developing hypoglycemia was indeed numerically less in those on MDI than for those on both types of CSII systems ( Supplementary Fig. S5), which is in line with the recent survey data by Paiement et al. 6 The reasons for the apparent differences in hypoglycemia risk rate during exercise between MDI (7.8%), HCL (8.2%), and pump (8.7%) may be related to behavioral differences on how individuals manage planned and unplanned exercise 6 and/or differences in IOB levels (median IOB at exercise start is 0.90 U for MDI, 1.51 U for HCL, and 1.12 U for pump). In any event, we found little evidence here that HCL systems were superior to MDI or CSII pump for the prevention of exercise-associated hypoglycemia when starting with the same glucose concentration, glucose rate of change, IOB, and prior time with glucose <70 mg/dL. ...
Objective:
Exercise is known to increase the risk for hypoglycemia in type 1 diabetes but predicting when it may occur remains a major challenge. The objective of this study was to develop a hypoglycemia prediction model based on a large real-world study of exercise in type 1 diabetes.
Research design and methods:
Structured study-specified exercise (aerobic, interval, and resistance training videos) and free-living exercise sessions from the Type 1 Diabetes Exercise Initiative study were used to build a model for predicting hypoglycemia, a CGM value <70 mg/dL, during exercise. Repeated measures random forest (RMRF) and repeated measures logistic regression (RMLR) models were constructed to predict hypoglycemia using predictors at the start of exercise and baseline characteristics. Models were evaluated with area under the receiver operating characteristic curve (AUC) and balanced accuracy.
Results:
RMRF and RMLR had similar AUC (0.833 vs 0.825, respectively) and both models had a balanced accuracy of 77%. The probability of hypoglycemia was higher for exercise sessions with lower pre-exercise glucose levels, negative pre-exercise glucose rates of change, greater percent time <70 mg/dL in the 24 hours before exercise, and greater pre-exercise bolus insulin-on-board. Free-living aerobic exercises, walking/hiking, and physical labor had the highest probability of hypoglycemia, while structured exercises had the lowest probability of hypoglycemia.
Conclusions:
RMRF and RMLR accurately predict hypoglycemia during exercise and identify factors that increase risk of hypoglycemia. Lower glucose, decreasing levels of glucose prior to exercise, and greater pre-exercise insulin-on-board largely predict hypoglycemia risk in adults with type 1 diabetes. .
... 13 It would be interesting to understand why better knowledge of PA and T1D management is not associated to less PA-associated hypoglycemia. 37 This could be due to diabetes management confidence that encourages higher tolerance for hypoglycemic risk. 37 Also, in this regard, the HL group attenuated glycemic variability between AH and SBH was possibly observed because of insulin sensitivity than the LL group, which could have also led to a higher TBR overnight that the PLGS was not able to manage to recommended levels. ...
... 37 This could be due to diabetes management confidence that encourages higher tolerance for hypoglycemic risk. 37 Also, in this regard, the HL group attenuated glycemic variability between AH and SBH was possibly observed because of insulin sensitivity than the LL group, which could have also led to a higher TBR overnight that the PLGS was not able to manage to recommended levels. According to Basu et al, 38 this could be related to an increment of insulin sensitivity occurring in a trained muscle, associated with training-induced GLUT4 availability to the cell surface. ...
... In order to help safely set higher PA goals, avoiding extreme glucose levels, management strategies should be incorporated and optimized. 37 Our study shows active people living with T1D need different diabetes management according to their PA load to avoid hypoglycemia recurrency during nighttime in people with higher PA loads probably because insulin sensitivity remained for longer or maintained at a higher level, which meant it carried over to sedentary hours, whereas the LL group possibly did not perform enough PA to get the carryover effect on insulin sensitivity during SBH, hence higher glycemic variability throughout these hours. Consequently, strategies in LL group should aim for reducing glycemic fluctuations during SBH. ...
Introduction
Maintaining glycemic control during and after physical activity (PA) is a major challenge in type 1 diabetes (T1D). This study compared the glycemic variability and exercise-related diabetic management strategies of adults with T1D achieving higher and lower PA loads in nighttime–daytime and active– sedentary behavior hours in free-living conditions.
Research design and methods
Active adults (n=28) with T1D (ages: 35±10 years; diabetes duration: 21±11 years; body mass index: 24.8±3.4 kg/m ² ; glycated hemoglobin A1c: 6.9±0.6%) on continuous subcutaneous insulin delivery system with predictive low glucose suspend system and glucose monitoring, performed different types, duration and intensity of PA under free-living conditions, tracked by accelerometer over 14 days. Participants were equally divided into lower load (LL) and higher load (HL) by median of daily counts per minute (61122). Glycemic variability was studied monitoring predefined time in glycemic ranges (time in range (TIR), time above range (TAR) and time below range (TBR)), coefficient of variation (CV) and mean amplitude of glycemic excursions (MAGE). Parameters were studied in defined hours timeframes (nighttime–daytime and active–sedentary behavior). Self-reported diabetes management strategies were analysed during and post-PA.
Results
Higher glycemic variability (CV) was observed in sedentary hours compared with active hours in the LL group (p≤0.05). HL group showed an increment in glycemic variability (MAGE) during nighttime versus daytime (p≤0.05). There were no differences in TIR and TAR across all timeframes between HL and LL groups. The HL group had significantly more TBR during night hours than the LL group (p≤0.05). Both groups showed TBR above recommended values. All participants used fewer post-PA management strategies than during PA (p≤0.05).
Conclusion
Active people with T1D are able to maintain glycemic variability, TIR and TAR within recommended values regardless of PA loads. However, the high prevalence of TBR and the less use of post-PA management strategies highlights the potential need to increase awareness on actions to avoid glycemic excursions and hypoglycemia after exercise completion.
... In addition to therapeutic education, new technologies, and specifically continuous-glucose monitoring systems with alarms, may represent promising solutions for reducing barriers to PA related to glycemic excursions while lightening the mental burden. The use of artificial pancreas is even suggested as effective for reducing the risk of hypoglycemia during exercise and especially at night [43,44]. ...
... Based on these, the following paragraph of the discussion: [43]. ...
... Besides, this association could also show that adults who are less afraid of suffering from hypoglycemia feel less stressful about an exercise-induced decrease in glycemia. A somewhat comparable association had been suggested in a recent study, in which adults with greater awareness of strategies for hypoglycemia preventiona correlate of fewer barriers to PA [11] mentioned more hypoglycemic episodes during exercise (subjectively reported, not measured with CGM) [43]. Our results raise the clinical issue of striking a balance between reducing barriers to PA in order to increase PA commitment [10] but at the expense of a certain risk-taking behavior towards glycemia management. ...
Objective
Ever since the first research on barriers to physical activity (PA) highlighting fear of hypoglycemia as a major barrier, many studies have attempted to understand their demographic and behavioral determinants. However, no research has been conducted on whether these perceived barriers towards PA are based on real life-experienced adverse glycemic effects of exercise.
Research design and methods
Sixty-two adults, and 53 children/adolescents living with type 1 diabetes along with their parents, completed the BAPAD-1 questionnaire on barriers to PA. Continuous glucose monitoring data were collected during one week of everyday life for 26 adults and 33 children/adolescents. Multiple linear regressions were used to explore links between BAPAD-1 scores and glycemic excursions experienced during and after everyday life self-reported PA sessions, controlling for behavioral (accelerometry) and demographic confounders.
Results
In children/adolescents, the more time spent in hypoglycemia on nights following PA sessions, the more they reported hypoglycemic risk as a barrier (ß = +0.365, P = 0.034). Conversely, in adults, the higher the proportion of PA sessions accompanied by a drop in blood glucose, the less hypoglycemia was a barrier (ß = –0.046, P = 0.004). In parents, BAPAD-1 scores were unrelated to children/adolescents’ everyday life exercise-induced hypo/hyperglycemia.
Conclusions
In children/adolescents, fear of hypoglycemia was predominant in those exposed to nocturnal hypoglycemia associated with PA sessions. In adults, fewer barriers may mean they accept a bigger drop in their glycemia during PA. This shows the importance of finding and promoting age specific solutions to prevent exercise-induced hypoglycemia.
... [2][3][4] Physical activity (PA) also provides a plethora of health benefits, including glycemic control but can be limited by fear and increased risk of hypoglycemia, even with AID systems. [5][6][7] Glucose regulation during exercise is contingent on several factors, including exercise timing and modality (type, intensity, duration, etc.) with prolonged aerobic exercise being associated with the highest hypoglycemic risk. 8 A metaanalysis, including six randomized controlled trials recently concluded that closed-loop systems (CLS) significantly increase glucose time in range by 6.2% (TIR; 3.9-10.0 ...
... Instead, preventing exerciseinduced hypoglycemia should remain the main priority for most patients. 5,6,31 To avoid hypoglycemia, several experts suggested that exercise should not be undertaken early after a meal at peak insulin action. 32,33 However, this is not always possible for PWT1D with time constraints or those performing active transportation immediately after a meal. ...
Aims:
To assess the safety and efficacy of two exercise sessions performed 60- and 120-minutes post-meal with a combination of meal bolus reduction and increased glucose target to the automated insulin delivery (AID) system.
Methods:
A randomized crossover trial in 13 adult participants (6 females) living with type 1 diabetes using AID (A1c = 7.9 ± 0.6%, Age = 53.5 ± 15.5 years, T1D duration = 29.0 ± 16.0 years) was conducted. Just before breakfast, at the time of meal bolus, the AID glucose target was increased from 6 to 9 mmol/L, and a meal bolus reduction of 33% was applied. Two 60-minute exercise sessions (60% of VO2 peak) were undertaken either 60 minutes (60EX) or 120 minutes (120EX) after a standardized breakfast, followed by a 90-minute recovery period.
Results:
The mean reduction in plasma glucose levels from pre-breakfast to post-exercise (-0.8 ± 2.4 mmol/L vs. +0.3 ± 2.3 mmol/L, p = 0.082) were similar between 60EX and 120EX. From pre-breakfast to post-exercise, plasma glucose times in range (3.9-10.0 mmol/L; 63.4 ± 43.1% 60EX vs. 51.9 ± 29.7% 120EX, p = 0.219) and time above range (>10.0 mmol/L; 36.3 ± 43.3% 60EX vs. 48.1 ± 29.7% 120EX, p = 0.211) did not differ between interventions. 60EX attenuated the glucose rise between pre-meal to pre-exercise (+1.8 ± 2.1 mmol/L 60EX vs. +3.9 ± 2.1 mmol/L 120EX, p = 0.001). No hypoglycemic events (<3.9 mmol/L) occurred during the study.
Conclusion:
Pre-meal announcement combining meal bolus reduction and increased glucose target was effective and safe during 60 minutes of moderate-intensity aerobic exercise, whether exercise onset was 60 or 120 minutes following a meal.
... An important feature of the safety module is the ability to predict in advance hypo-and hyperglycemia for their early detection of potential occurrence, suspension of insulin delivery, or avoiding insulin overdosing 43,44 . Additionally, predicting potential hypo-and hyperglycemia can be used to adjust the conservativeness or aggressiveness of the controller. ...
Background
Hybrid closed-loop control of glucose levels in people with type 1 diabetes mellitus (T1D) is limited by the requirements on users to manually announce physical activity (PA) and meals to the artificial pancreas system. Multivariable automated insulin delivery (mvAID) systems that can handle unannounced PAs and meals without any manual announcements by the user can improve glycemic control by modulating insulin dosing in response to the occurrence and intensity of spontaneous physical activities.
Methods
An mvAID system is developed to supplement the glucose measurements with additional physiological signals from a wristband device, with the signals analyzed using artificial intelligence algorithms to automatically detect the occurrence of PA and estimate its intensity. This additional information gained from the physiological signals enables more proactive insulin dosing adjustments in response to both planned exercise and spontaneous unanticipated physical activities.
Results
In silico studies of the mvAID illustrate the safety and efficacy of the system. The mvAID is translated to pilot clinical studies to assess its performance, and the clinical experiments demonstrate an increased time in range and reduced risk of hypoglycemia following unannounced PA and meals.
Conclusions
The mvAID systems can increase the safety and efficacy of insulin delivery in the presence of unannounced physical activities and meals, leading to improved lives and less burden on people with T1D.
... It is interesting to note, however, that a recent study demonstrated that greater knowledge about the management of T1D and physical activity was not associated with less hypoglycemia during and after physical [25]. ...
Aims
Exercise is an important practice for control in type 1 diabetes (T1D). This study aims to assess de association between exercise and glycemic management in people with T1D and to identify the main barriers to exercise in T1D.
Methods
We evaluated 95 people with T1D treated with insulin pump therapy. Participants answered a questionnaire about 1) exercise habits, 2) usual adjustments in insulin and food intake with exercise and 3) main barriers to exercise.
Continuous glucose monitoring (CGM) was used to evaluate time in range (TIR), time below range (TBR) and time above range (TAR) during the last 60 days before the evaluation. CGM data during, before (2 h before) and after (24 h after) the last bout of exercise was also evaluated.
Results
The mean age was 30.1 ± 12.1 years, and 51.6% were women. Participants that reported practicing exercise (55.8%) had a higher TIR (59.6 ± 16.3 vs. 48.7 ± 15.7, p = 0.012) and a lower TAR (32.6 ± 15.8 vs. 45.4 ± 17.7, p = 0.006). Comparing with the 60 days CGM data, the TBR was lower in the 2 h before exercise (− 1.8 ± 3.8, p = 0.0454) and TAR was lower during (− 16.9 ± 33.6, p = 0.0320) and in the 24 h after (− 8.7 ± 17.2, p = 0.032) the last bout of exercise. The absence of adjustments on insulin and food intake was associated with higher TBR after the exercise (13.44 ± 3.5, p < 0.05). Eating before the exercise and turning off the pump during the exercise were associated with lower TBR after exercise (food booster: − 7.56 ± 3.49, p < 0.05; turning off insulin pump − 8.87 ± 3.52, p < 0.05). The main barriers reported for exercise practicing were fear of hypoglycemia, lack of free time and work schedule.
Conclusion
Exercise was associated with better glycemic management in people with T1D. Addressing common barriers may allow a higher adherence to exercise in T1D.
... Survival of subjects with T1DM is dependent on exogenous insulin administrations [1]. In order to calculate and then inject an appropriate insulin dose, subjects must frequently monitor their glucose values, taking into account not only the exact amount of carbohydrates ingested, but also physical activity [2], [3], disease states [4], and stress episodes [5]. The main goal of glycemic control is to avoid or at least mitigate events such as hypoglycemia and hyperglycemia [6]. ...
Background:
Available studies comparing the efficacy of dual-hormone (DH)- algorithm-assisted insulin delivery (AID), single-hormone (SH)-AID and usual care on post-exercise overnight glucose in people with type 1 diabetes (T1D) have had different outcomes. By pooling data from all available studies, we aim to draw stronger conclusions.
Methods:
Data were pooled from two three-arm, open-label, randomized, controlled, crossover studies. Forty-one adults [median (Q1-Q3) age: 34.0 years (29.5, 51.0), mean HbA1c: 7.5 ± 1.0%] and 17 adolescents with type 1 diabetes [age: 14.0 (13.0, 16.0), HbA1c: 7.8 ± 0.8%] underwent DH-AID, SH-AID and usual care. Each intervention involved evening aerobic exercise (60-minutes). The primary outcome, time in range% (TIR%) overnight (00:00-06:00) post-exercise based on continuous glucose monitoring, was compared among treatments using linear mixed effect model or generalized linear mixed model.
Results:
Among adults, mean TIR% was 94.0% ± 11.9%, 83.1% ± 20.5% and 65.1% ± 37.0% during DH-AID, SH-AID and usual care intervention, respectively (P<0.05 for all between-group comparisons). DH-AID was superior to SH-AID and usual care, and SH-AID was superior to usual care regarding hypo- and hyperglycemia prevention but not glycemic variability. Among adolescents, DH-AID and SH-AID reduced dysglycemia, but not glycemic variability, better than usual care. Glycemic outcomes were similar between DH-AID and SH-AID.
Conclusion:
AID systems allow improved post-exercise nocturnal glycemic management than usual care for both adults and adolescents. DH-AID was better than SH-AID among adults but not adolescents.
Regular exercise is beneficial and recommended for people with type 1 diabetes, but increased glucose demand and changes in insulin sensitivity require treatment adjustments to prevent exercise-induced hypoglycemia. Several different adjustment strategies based on insulin bolus reductions and additional carbohydrate intake have been proposed, but large inter- and intraindividual variability and studies using different exercise duration, intensity, and timing impede a direct comparison of their effects. In this study, we use a mathematical model of the glucoregulatory system and implement published guidelines and strategies in-silico to provide a direct comparison on a single ‘typical’ person on a standard day with three meals. We augment this day by a broad range of exercise scenarios combining different intensity and duration of the exercise session, and different timing with respect to adjacent meals. We compare the resulting blood glucose trajectories and use summary measures to evaluate the time-in-range and risk scores for hypo- and hyperglycemic events for each simulation scenario, and to determine factors that impede prevention of hypoglycemia events. Our simulations suggest that the considered strategies and guidelines successfully minimize the risk for acute hypoglycemia. At the same time, all adjustments substantially increase the risk of late-onset hypoglycemia compared to no adjustment in many cases. We also find that timing between exercise and meals and additional carbohydrate intake during exercise can lead to non-intuitive behavior due to superposition of meal- and exercise-related glucose dynamics. Increased insulin sensitivity appears as a major driver of non-acute hypoglycemic events. Overall, our results indicate that further treatment adjustment might be required both immediately following exercise and up to several hours later, but that the intricate interplay between different dynamics makes it difficult to provide generic recommendations. However, our simulation scenarios extend substantially beyond the original scope of each model component and proper model validation is warranted before applying our in-silico results in a clinical setting.
Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (i.e. before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes.
Graphical abstract
Aims/hypothesis:
For individuals living with type 1 diabetes, closed-loop insulin delivery improves glycaemic control. Nonetheless, maintenance of glycaemic control during exercise while a prandial insulin bolus remains active is a challenge even to closed-loop systems. We investigated the effect of exercise announcement on the efficacy of a closed-loop system, to reduce hypoglycaemia during postprandial exercise.
Methods:
A single-blind randomised, crossover open-label trial was carried out to compare three strategies applied to a closed-loop system at mealtime in preparation for exercise taken 90 min after eating at a research testing centre: (1) announced exercise to the closed-loop system (increases target glucose levels) in addition to a 33% reduction in meal bolus (A-RB); (2) announced exercise to the closed-loop system and a full meal bolus (A-FB); (3) unannounced exercise and a full meal bolus (U-FB). Participants performed 60 min of exercise at 60% [Formula: see text] 90 min after eating breakfast. The investigators were not blinded to the interventions. However, the participants were blinded to the sensor glucose readings and to the insulin infusion rates throughout the intervention visits.
Results:
The trial was completed by 37 adults with type 1 diabetes, all using insulin pumps: mean±SD, 40.0 ± 15.0 years of age, HbA1c 57.1 ± 10.8 mmol/mol (7.3 ± 1.0%). Reported results were based on plasma glucose values. During exercise and the following 1 h recovery period, time spent in hypoglycaemia (<3.9 mmol/l; primary outcome) was reduced with A-RB (mean ± SD; 2.0 ± 6.2%) and A-FB (7.0 ± 12.6%) vs U-FB (13.0 ± 19.0%; p < 0.0001 and p = 0.005, respectively). During exercise, A-RB had the least drop in plasma glucose levels: A-RB -0.3 ± 2.8 mmol/l, A-FB -2.6 ± 2.9 mmol/l vs U-FB -2.4 ± 2.7 mmol/l (p < 0.0001 and p = 0.5, respectively). Comparison of A-RB vs U-FB revealed a decrease in the time spent in target (3.9-10 mmol/l) by 12.7% (p = 0.05) and an increase in the time spent in hyperglycaemia (>10 mmol/l) by 21% (p = 0.001). No side effects were reported during the applied strategies.
Conclusions/interpretation:
Combining postprandial exercise announcement, which increases closed-loop system glucose target levels, with a 33% meal bolus reduction significantly reduced time spent in hypoglycaemia compared with the other two strategies, yet at the expense of more time spent in hyperglycaemia.
Trial registration:
ClinicalTrials.gov NCT0285530 FUNDING: JDRF (2-SRA-2016-210-A-N), the Canadian Institutes of Health Research (354024) and the Fondation J.-A. DeSève chair held by RR-L.
Abstract Adding vigorous-intensity intervals (VII) to moderate-intensity exercise prevents immediate declines in blood glucose in type 1 diabetes (T1D) however the intensity required to minimize post-exercise hypoglycemia is unknown. To examine this question, ten sedentary T1D individuals completed four treadmill exercise sessions: a control session of 45 minutes of walking at 45–55% of heart rate reserve (HRR) and three sessions consisting of 60 seconds (VII) at 70%, 80%, or 90% of HRR every 4 minutes during exercise at 45–55% of HRR. We used continuous glucose monitoring (CGM) to measure time ≤3.9 mmol/L, glucose variability, hypoglycemia frequency and area under the curve (AUC) for hypoglycemia and hyperglycemia for 12 hours post-exercise. We also examined growth hormone and cortisol responses during and following exercise. In the 12 hours post-exercise, the percentage of time ≤3.9 mmol/L, glucose variability, and AUC for hypoglycemia and hyperglycemia were similar across conditions. The frequency of hypoglycemic events was highest after the 90% intervals compared to the control arm (12 vs 3 events, p = 0.03). There was a trend towards elevated growth hormone with increasing exercise intensity but cortisol levels were similar across conditions. Adding VII to moderate intensity exercise may increase hypoglycemia risk at higher intensities.
To validate strategies to prevent exercise-induced hypoglycaemia via insulin-dose adjustment in adult patients with type 1 diabetes on pump therapy.
20 patients randomly performed four 30-minute late post-lunch exercise (bicycle) sessions (3hrs post-lunch) and a rest session: 2 moderate sessions (50%VO2max) with 50% or 80% basal rate (BR) reduction during exercise+2hrs; 2 intense sessions (75%VO2max) with 80% BR reduction or with their pump stopped. Two additional early post-lunch sessions (90min post-lunch) compared hypoglycaemia incidence for BR vs. bolus reduction.
100 late post-lunch sessions were analysed: regardless of exercise type and BR reduction, no more hypoglycaemic events occurred until the next morning than for the rest sessions. In the afternoon, no more hypoglycaemic events occurred with 80% BR reduction/moderate exercise or with pump discontinuation/intense exercise than for the rest session, whereas more hypoglycaemic events occurred with 50% BR reduction/moderate exercise and 80% BR reduction/intense exercise. After early post-lunch exercise (n=37), a trend towards fewer hypoglycaemic episodes was observed with bolus reduction vs. BR reduction (p=0.07). Mean blood glucose fell by approximately 3.3 mmol/l after 30 min of exercise, irrespective of dose reduction, remaining stable until next morning with no rebound hyperglycaemia.
To limit hypoglycaemic risk in adult patients associated with 30 minutes of exercise 3hrs after lunch, without carbohydrate supplements, the best options seem to be to reduce BR by 80% or to stop the pump for moderate or intense exercise, or for moderate exercise 90 minutes after lunch, to reduce the prandial bolus rather than the BR.
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Hypoglycemia is common in type 1 diabetes mellitus (T1DM). We aimed to update the incidence of severe and symptomatic hypoglycemia and investigate several correlated factors.
In this multicenter, observational retrospective study, the data of 206 T1DM patients from a sample of 2,229 consecutive patients seen at 18 diabetes clinics were analyzed. Sociodemographic and clinical characteristics, severe hypoglycemia in the past 12 months, and symptomatic hypoglycemia in the past 4 weeks were recorded with a self-report questionnaire and a clinical form during a routine visit. Poisson multivariate models were applied.
A minority of patients accounted for the majority of both severe and symptomatic episodes. The incidence rate (IR) of severe hypoglycemia was 0.49 (0.40-0.60) events/person-years. The incidence rate ratio (IRR) was higher in patients with previous severe hypoglycemia (3.71; 2.28-6.04), neuropathy (4.16; 2.14-8.05), long duration (>20 years, 2.96; 1.60-5.45), and on polypharmacy (1.24; 1.13-1.36), but it was lower when a complication was present. The IR of symptomatic hypoglycemia was 53.3 events/person-years, with an IRR significantly higher among women or patients with better education, or shorter duration or on pumps. The IRR was lower in patients with higher BMI or neuropathy or aged more than 50 years.
Fewer than 20 % of T1DM patients are free from hypoglycemia, with one in six having experienced at least one severe episode in the last year. The distribution is uneven, with a tendency of episodes to cluster in some patients. Severe and symptomatic episodes have different correlates and reflect different conditions.
Regular physical activity has recognised health benefits for people with T1DM. However a significant proportion of them do not undertake the recommended levels of activity. Whilst questionnaire-based studies have examined barriers to exercise in people with T1DM, a formal qualitative analysis of these barriers has not been undertaken. Our aims were to explore attitudes, barriers and facilitators to exercise in patients with T1DM.A purposeful sample of long standing T1DM patients were invited to participate in this qualitative study. Twenty-six adults were interviewed using a semi-structured interview schedule to determine their level of exercise and barriers to initiation and maintenance of an exercise programme.Six main barriers to exercise were identified: lack of time and work related factors; access to facilities; lack of motivation; embarrassment and body image; weather; and diabetes specific barriers (low levels of knowledge about managing diabetes and its complications around exercise). Four motivators to exercise were identified: physical benefits from exercise; improvements in body image; enjoyment and the social interaction of exercising at gym or in groups. Three facilitators to exercise were identified: free or reduced admission to gyms and pools, help with time management, and advice and encouragement around managing diabetes for exercise.Many of the barriers to exercise in people with T1DM are shared with the non-diabetic population. The primary difference is the requirement for education about the effect of exercise on diabetes control and its complications. There was a preference for support to be given on a one to one basis rather than in a group environment. This suggests that with the addition of the above educational requirements, one to one techniques that have been successful in increasing activity in patients with other chronic disease and the general public should be successful in increasing activity in patients with T1DM.
OBJECTIVE
In type 1 diabetes, small studies have found that resistance exercise (weight lifting) reduces HbA(1c). In the current study, we examined the acute impacts of resistance exercise on glycemia during exercise and in the subsequent 24 h compared with aerobic exercise and no exercise.RESEARCH DESIGN AND METHODS
Twelve physically active individuals with type 1 diabetes (HbA(1c) 7.1 ± 1.0%) performed 45 min of resistance exercise (three sets of seven exercises at eight repetitions maximum), 45 min of aerobic exercise (running at 60% of Vo(2max)), or no exercise on separate days. Plasma glucose was measured during and for 60 min after exercise. Interstitial glucose was measured by continuous glucose monitoring 24 h before, during, and 24 h after exercise.RESULTSTreatment-by-time interactions (P < 0.001) were found for changes in plasma glucose during and after exercise. Plasma glucose decreased from 8.4 ± 2.7 to 6.8 ± 2.3 mmol/L (P = 0.008) during resistance exercise and from 9.2 ± 3.4 to 5.8 ± 2.0 mmol/L (P = 0.001) during aerobic exercise. No significant changes were seen during the no-exercise control session. During recovery, glucose levels did not change significantly after resistance exercise but increased by 2.2 ± 0.6 mmol/L (P = 0.023) after aerobic exercise. Mean interstitial glucose from 4.5 to 6.0 h postexercise was significantly lower after resistance exercise versus aerobic exercise.CONCLUSIONS
Resistance exercise causes less initial decline in blood glucose during the activity but is associated with more prolonged reductions in postexercise glycemia than aerobic exercise. This might account for HbA(1c) reductions found in studies of resistance exercise but not aerobic exercise in type 1 diabetes.
Exercise is a cornerstone of diabetes therapy in type 1 diabetes mellitus (DMT1) patients. The type of exercise is important in determining the propensity to hypoglycemia. We assessed, by continuous glucose monitoring (CGM), the glucose profiles during and in the following 20h after a session of two different types of exercise.
Eight male volunteers with well-controlled DMT1 were studied. They underwent 30min of both intermittent high-intensity exercise (IHE) and moderate-intensity exercise (MOD) in random order. Expired air was recorded during exercise, while metabolic and hormonal determinations were performed before and for 120 min after exercises. The CGM system and activity monitor were applied for the subsequent 20h.
Blood glucose level declined during both type of exercise. At 150 min following the start of exercise, plasma glucose content was slightly higher after IHE. No changes were observed in plasma insulin concentration. A significant increase of norepinephrine concentration was noticed during IHE. Between midnight and 6:00 a.m. the glucose levels were significantly lower after IHE than those observed after MOD (area under the curve, 23.3 ± 3 vs. 16 ± 3 mg/dL/420 min [P = 0.04]; mean glycemia at 3 a.m., 225 ± 31 vs. 147 ± 17 mg/dL [P<0.05]). The number of hypoglycemic episodes after IHE was higher than that observed after MOD (seven vs. two [P<0.05]).
We demonstrate that (1) CGM is a useful approach in DMT1 patients who undergo an exercise program and (2) IHE is associated with delayed nocturnal hypoglycemia.
To determine, in an adult population with type 1 diabetes, barriers to regular physical activity using a diabetes-specific barriers measure (the Barriers to Physical Activity in Diabetes [type 1] [BAPAD1] scale) and factors associated with these barriers.
One hundred adults with type 1 diabetes answered a questionnaire assessing perceived barriers to physical activity and related factors. A1C was obtained from the medical chart of each individual.
Fear of hypoglycemia was identified as being the strongest barrier to physical activity. Greater knowledge about insulin pharmacokinetics and using appropriate approaches to minimize exercise-induced hypoglycemia were factors associated with fewer perceived barriers. Greater barriers were positively correlated with A1C levels (r = 0.203; P = 0.042) and negatively with well-being (r = -0.45; P < 0.001).
Fear of hypoglycemia is the strongest barrier to regular physical activity in adults with type 1 diabetes, who should therefore be informed and supported in hypoglycemia management.
To determine the risk of frequent and severe hypoglycemia and the associated demographic and clinical risk factors.
Demographic and diabetes self-management factors were measured in 415 subjects followed prospectively for 4-6.5 years of type 1 diabetes duration as participants in a population-based incident cohort. Blood samples were collected up to three times yearly to test glycosylated hemoglobin (GHb) levels. Reports of frequent (2-4 times/week) and severe (lost consciousness) hypoglycemia as well as other diabetes self-management data were collected by questionnaires.
Frequent hypoglycemia was common (33 and 35% of participants reported this on the 4- and 6.5-year questionnaires, respectively), whereas severe hypoglycemia occurred much less often. Better glycemic control (odds ratio [OR] 1.3 per 2% decrease in GHb, 95% CI 1.1-1.5) and more frequent self-monitored blood glucose (1.5 per blood glucose check, 1.3-1.7) were independently related to frequent hypoglycemia. The association of frequent hypoglycemia with intensive insulin therapy increased with age. Better glycemic control (1.5 per 2% decrease in GHb, 1.2-2.0) and older age were related to severe hypoglycemic reactions. No sociodemographic factors other than age increased the risk of hypoglycemia.
Frequent hypoglycemia was common in a population representing the full range of glycemic control in the community. Intensive insulin management and blood glucose monitoring independently predicted frequent but not severe hypoglycemia. This information may be useful for updating patients such that minor changes in diabetes management might decrease the daily burden of this condition while maintaining intensive insulin therapy.
Previously, the decline in glycemia in individuals with type 1 diabetes has been shown to be less with intermittent high-intensity exercise (IHE) compared with continuous moderate-intensity exercise (MOD) despite the performance of a greater amount of total work. The purpose of the present study was to determine whether this lesser decline in glycemia can be attributed to a greater increment in endogenous glucose production (Ra) or attenuated glucose utilization (Rd). Nine individuals with type 1 diabetes were tested on two separate occasions, during which either a 30-min MOD or IHE protocol was performed under conditions of a euglycemic clamp in combination with the infusion of [6,6-(2)H]glucose. MOD consisted of continuous cycling at 40% VO2 peak, whereas IHE involved a combination of continuous exercise at 40% VO2 peak interspersed with additional 4-s maximal sprint efforts performed every 2 min to simulate the activity patterns of intermittent sports. During IHE, glucose Ra increased earlier and to a greater extent compared with MOD. Similarly, glucose Rd increased sooner during IHE, but the increase by the end of exercise was comparable with that elicited by MOD. During early recovery from IHE, Rd rapidly declined, whereas it remained elevated after MOD, a finding consistent with a lower glucose infusion rate during early recovery from IHE compared with MOD (P<0.05). The results suggest that the lesser decline in glycemia with IHE may be attributed to a greater increment in Ra during exercise and attenuated Rd during exercise and early recovery.
Physical activity (PA) is important for individuals living with type 1 diabetes (T1D) due to its various health benefits. Nonetheless, maintaining adequate glycemic control around PA remains a challenge for many individuals living with T1D because of the difficulty to properly manage circulating insulin levels around PA. While the most common problem is increased incidence of hypoglycemia during and after most types of PA, hyperglycemia can also occur. Accordingly, a large proportion of people living with T1D are sedentary partly due to the fear of PA-associated hypoglycemia.
Continuous subcutaneous insulin infusion (CSII) offers a higher precision and flexibility to adjust insulin basal rates and boluses according to the individual’s specific needs around PA practice. Indeed, for physically active patients with T1D, CSII can be a preferred option to facilitate glucose regulation. To our knowledge, there are no guidelines to manage exercise-induced hypoglycemia during PA, specifically for individuals living with T1D and using CSII. This review highlights the current state of knowledge on exercise-related glucose variations, especially the hypoglycemic risk as well as its underlying physiology. Further, we detail the current recommendations for insulin modulations according to the different PA modalities (type, intensity, duration, frequency) in individuals living with T1D using CSII.
Objective
This project aimed to use educational sessions and exercise classes to improve exercise self-efficacy in individuals with type 1 diabetes (T1D) and diabetes care providers (DCP).
Methods
We recruited 12 T1D participants and 12 DCP who participated in 4 weekly group sessions to learn about exercise physiology and experience different exercise types. We provided participants with T1D with real-time continuous glucose monitors (CGM) and heart rate monitors to enhance experiential learning. Both groups completed questionnaires before and after the study to assess confidence around exercise. Following the study, focus groups assessed the impact of the study on knowledge and self-efficacy.
Results
There was an improvement in DCP attitudes toward exercise (p=0.004). DCP confidence in providing clients with advice regarding the time, type, and intensity of exercise (p=0.005), and strategies for overcoming barriers to exercise (p=0.016) improved significantly. We found no significant changes in results from T1D participant questionnaires. Focus group analysis suggested that the study improved awareness of the importance of exercise in T1D as well as knowledge about the effects of exercise in T1D in both DCP and T1D participants. CGM use alleviated fear of hypoglycemia among T1D participants.
Conclusion
These findings suggest that a 4-week education and exercise-focused program improves DCP self-efficacy in providing exercise advice to patients. T1D did not experience an improvement in exercise self-efficacy; however, the study supports the use of CGM and the grouping of DCP and individuals with T1D to facilitate experiential learning.
We reinvestigated the prevailing concept that muscle contractions only elicit increased muscle glucose uptake in the presence of a so-called “permissive” concentration of insulin (Berger et al., Biochem. J. 146: 231–238, 1975; Vranic and Berger, Diabetes 28: 147–163, 1979). Hindquarters from rats in severe ketoacidosis were perfused with a perfusate containing insulin antiserum. After 60 min perfusion, electrical stimulation increased glucose uptake of the contracting muscles fivefold. Also, subsequent contractions increased glucose uptake in hindquarters from nondiabetic rats perfused for 1.5 h in the presence of antiserum. 3-O-methylglucose uptake was increased markedly by contractions in fast-twitch red and white fibers that were severely glycogen depleted but not in slow-twitch red fibers that were not glycogen depleted. In hindquarters from ketoacidotic rats perfused exactly as by Berger et al., 3-O-methylglucose uptake increased during contractions and glucose uptake was negative at rest and zero during contractions. An increase in muscle transport and uptake of glucose during contractions does not require the presence of insulin. Furthermore, glucose transport in contracting muscle may only increase if glycogen is depleted.
Type 1 diabetes is a challenging condition to manage for various physiological and behavioural reasons. Regular exercise is important, but management of different forms of physical activity is particularly difficult for both the individual with type 1 diabetes and the health-care provider. People with type 1 diabetes tend to be at least as inactive as the general population, with a large percentage of individuals not maintaining a healthy body mass nor achieving the minimum amount of moderate to vigorous aerobic activity per week. Regular exercise can improve health and wellbeing, and can help individuals to achieve their target lipid profile, body composition, and fitness and glycaemic goals. However, several additional barriers to exercise can exist for a person with diabetes, including fear of hypoglycaemia, loss of glycaemic control, and inadequate knowledge around exercise management. This Review provides an up-to-date consensus on exercise management for individuals with type 1 diabetes who exercise regularly, including glucose targets for safe and effective exercise, and nutritional and insulin dose adjustments to protect against exercise-related glucose excursions.
The adoption and maintenance of physical activity are critical foci for blood glucose management and overall health in individuals with diabetes and prediabetes. Recommendations and precautions vary depending on individual characteristics and health status. In this Position Statement, we provide a clinically oriented review and evidence-based recommendations regarding physical activity and exercise in people with type 1 diabetes, type 2 diabetes, gestational diabetes mellitus, and prediabetes.
Objectives:
People with type 1 diabetes are at risk for early- and late-onset hypoglycemia following exercise. Reducing this risk may be possible with strategic modifications in carbohydrate intake and insulin use. We examined the exercise preparations and management techniques used by individuals with type 1 diabetes before and after physical activity and sought to determine whether use of differing diabetes technologies affects these health-related behaviours.
Methods:
We studied 502 adults from the Type 1 Diabetes Exchange's online patient community, Glu, who had completed an online survey focused on diabetes self-management and exercise.
Results:
Many respondents reported increasing carbohydrate intake before (79%) and after (66%) exercise as well as decreasing their meal boluses before (53%) and after (46%) exercise. Most reported adhering to a target glucose level before starting exercise (77%). Despite these accommodations, the majority reported low blood glucose (BG) levels after exercise (70%). The majority of users of both insulin pump therapy (CSII) and continuous glucose monitoring (CGM) (Combined) reported reducing basal insulin around exercise (55%), with fewer participants adjusting basal insulin when using other devices (SMBG only = 20%; CGM = 34%; CSII = 42%; p<0.001). However, CSII and Combined users reported that exercise makes their BG levels harder to control (p<0.05) and makes them feel less able to predict their BG levels while exercising (p<0.001); they show agreement that fear of low BG levels keeps them from exercising (p<0.01).
Conclusions:
These findings highlight the need for exercise-management strategies tailored to individuals' overall diabetes management, for despite making exercise-specific adjustments for care, many people with type 1 diabetes still report significant difficulties with BG control when it comes to exercise.
Aim:
To determine the impact of physical fitness level on hypoglycaemia risk during exercise in people with Type 1 diabetes.
Methods:
A total of 44 patients [34 adults (aged 22-70 years) and 10 adolescents (aged 12-18 years)] with Type 1 diabetes, treated with insulin pump therapy, underwent a standardized exercise session. Cardiorespiratory fitness (maximum oxygen uptake) was measured and classified, based on established norms for age and sex, into either poor (<25th percentile) or good fitness level (>25th percentile). Plasma glucose levels were measured every 10 min, each patient performed physical activity at 60% maximum oxygen uptake either on a treadmill for 1 h or on a bicycle for 30 min. Frequency of hypoglycaemia (plasma glucose < 4 mmol/l) and decline in plasma glucose level during exercise were assessed.
Results:
In all, 23 patients had a good exercise fitness level. Hypoglycaemic events occurred in 17/23 patients (74.0%) in the good fitness level group compared with 8/21 patients (38.0%) in the poor fitness level group (P=0.02). Both groups had similar pre-exercise plasma glucose levels. The plasma glucose values during exercise in the good fitness level group compared with the poor fitness level group were: plasma glucose nadir 3.9 ± 1.6 vs 5.5 ± 2.4 mmol/l (P=0.01) and plasma glucose change -4.6 ± 3.4 vs. -2.1 ± 3.1 mmol/l (P=0.01). The correlation between the plasma glucose nadir and maximum oxygen uptake was r =- 0.38 (P=0.01).
Conclusions:
Patients with good fitness level seem to be more prone to hypoglycaemia during exercise. This could be the result of better insulin sensitivity and the fact that they tend to exercise at greater work thresholds. These results are a step toward a better understanding of the association between physical fitness and exercise-induced hypoglycaemia. This article is protected by copyright. All rights reserved.
Physical activity (PA) can improve cardiovascular risk in the general population and in patients with type 2 diabetes. Studies also indicate an HbA1c-lowering effect in patients with type 2 diabetes. Since reports in patients with type 1 diabetes are scarce, this analysis aimed to investigate whether there is an association between PA and glycemic control or cardiovascular risk in subjects with type 1 diabetes.
A total of 18,028 adults (≥18 to <80 years of age) from Germany and Austria with type 1 diabetes from the Diabetes-Patienten-Verlaufsdokumentation (DPV) database were included. Patients were stratified according to their self-reported frequency of PA (PA0, inactive; PA1, one to two times per week; PA2, more than two times per week). Multivariable regression models were applied for glycemic control, diabetes-related comorbidities, and cardiovascular risk factors. Data were adjusted for sex, age, and diabetes duration. P values for trend were given. SAS 9.4 was used for statistical analysis.
An inverse association between PA and HbA1c, diabetic ketoacidosis, BMI, dyslipidemia (all P < 0.0001), and hypertension (P = 0.0150), as well as between PA and retinopathy or microalbuminuria (both P < 0.0001) was present. Severe hypoglycemia (assistance required) did not differ in PA groups (P = 0.8989), whereas severe hypoglycemia with coma was inversely associated with PA (P < 0.0001).
PA seemed to be beneficial with respect to glycemic control, diabetes-related comorbidities, and cardiovascular risk factors without an increase of adverse events. Hence, our data underscore the recommendation for subjects with type 1 diabetes to perform regular PA.
© 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
Aims
To describe (i) current bedtime nutritional practices and (ii) the association between post-dinner dietary intake and the occurrence of non-severe nocturnal hypoglycemia (NH) in real-life conditions among adult patients with type 1 diabetes using insulin analogues.
Methods
One hundred adults (median [interquartile range]: age 46.4 [36.0-55.8] years, HbA1c 7.9 [7.3-8.6] % (63 [56–70] mmol/mol)) using multiple daily injections (n = 67) or insulin pump (n = 33) wore a blinded continuous glucose monitoring system and completed a food diary for 72-hours.
Results
NH occurred on 28% of 282 nights analysed. (i) Patients reported post-dinner dietary intakes on 63% of the evenings. They injected rapid-acting insulin boluses on 64 occasions (23% of 282 evenings). These insulin boluses were mostly injected with (n = 37) dietary intakes. (ii) Post-dinner dietary intake was not associated with NH occurrence in univariate analyses. In multivariate analyses, the injection of rapid-acting insulin modulated the association between post-dinner dietary intake and NH: with insulin, post-dinner carbohydrate intake was positively associated with NH (Odds Ratio (OR): 1.16 [95% confidence interval, CI: 1.04-1.29] per 5 g increase, p = 0.008); without insulin, post-dinner protein intake was inversely associated with NH occurrence (OR [95% CI]: 0.88 [0.78-1.00] per 2 g increase, p = 0.048).
Conclusions
NH remains frequent in adults with type 1 diabetes. There is a complex relationship between post-dinner dietary intake and NH occurrence, including the significant role of nutrient content and rapid-acting insulin injection that requires further investigation.
Individuals living with type 1 or type 2 diabetes are at increased risk for depression, anxiety, and eating disorder diagnoses. Mental health comorbidities of diabetes compromise adherence to treatment and thus increase the risk for serious short- and long-term complications, which can result in blindness, amputations, stroke, cognitive decline, decreased quality of life, and premature death. When mental health comorbidities of diabetes are not diagnosed and treated, the financial cost to society and health care systems is substantial, as are the morbidity and health consequences for patients. In this Viewpoint, we summarize the prevalence and consequences of mental health problems for patients with type 1 or type 2 diabetes and suggest strategies for identifying and treating patients with diabetes and mental health comorbidities.
Physical inactivity is highly common in adults with type 1 diabetes (T1D) as specific barriers (i.e., hypoglycemia) may prevent them from being active. The objective of this study was to examine the efficacy of the Physical Exercise Promotion program in type 1 diabetes (PEP-1) program, a group program of physical activity (PA) promotion (intervention) compared with an information leaflet (control), to improve total energy expenditure (TEE) in adults with T1D after 12 weeks. TEE was measured with a motion sensor over a 7-day period at inclusion, after the program (12 weeks) and 1-year after inclusion. The 12 weekly sessions of the program included a 30-min information session (glycemic control and PA) and 60 min of PA. A total of 48 adults, aged 18 to 65 years with a reported PA practice <150 min per week, were recruited (45.8% men; aged 44.6 ± 13.3 years; 8.0% ± 1.1% glycated hemoglobin (A1c)) and randomized in this pilot trial. Ninety percent of participants completed the program and 88% completed the 1-year follow-up. No change was observed for TEE and A1c in both groups. After the 12-week program, the mean peak oxygen uptake increased (14%; p = 0.003) in the intervention group; however, at the 1-year follow-up, it was no longer different from baseline. In the control group, no difference was observed for the peak oxygen uptake. These results suggest that the PEP-1 pilot program could increase cardiorespiratory fitness. However, this benefit is not sustained over a long-term period. The PEP-1 program did not increase TEE in patients with T1D and other strategies remain necessary to counteract physical inactivity in this population.
To compare the glycemic and metabolic responses to simulated intermittent games activity and continuous running exercise in type 1 diabetes. Nine patients (seven male, two female; 35 ± 4 years; HbA1c 8.1 ± 0.2%/65 ± 2 mmol/mol) treated on a basal-bolus regimen completed two main trials, a continuous treadmill run (CON) or an intermittent running protocol (INT). Patients arrived to the laboratory fasted at ∼ 08:00 h, replicating their usual pre-exercise meal and administering a 50% reduced dose of rapid-acting insulin before exercising. Blood glucose (BG), K+, Na++, pH, triglycerides, serum cortisol and NEFA were measured at baseline and for 60 min post-exercise. Interstitial glucose was measured for a further 23 h under free-living conditions. Following exercise, BG declined under both conditions but was less under INT (INT −1.1 ± 1.4 vs CON −5.3 ± 0.4 mmol/L, P = 0.037), meaning more patients experienced hypoglycemia (BG ≤ 3.5 mmol/L; CON n = 3 vs INT n = 2) but less hyperglycemia (BG ≥ 10.9 mmol/L; CON n = 0 vs INT n = 6) under CON. Blood lactate was significantly greater, and pH lower, with a temporal delay in K+ under INT (P < 0.05). No conditional differences were observed in other measures during this time, or in interstitial glucose concentrations during the remaining 23 h after exercise. Simulated games activity carries a lower risk of early, but not late-onset hypoglycemia than continuous running exercise in type 1 diabetes.
The technical potential of the Internet offers survey researchers a wide range of possibilities for web surveys in terms of questionnaire design; however, the abuse of technical facilities can detract respondents from cooperating rather than motivating them. Within the web survey methodology literature, many contributions can be found on how to write a ‘‘good’’ questionnaire. The outcomes are however scattered and researchers and practitioners may find it difficult to obtain an overall picture. The article reviews the latest empirical research on how questionnaire characteristics affect response rates. The article is divided into three main sections: an introduction where the various forms of nonresponse in web surveys are described; a second section presenting questionnaire features affecting nonresponse— general structure, length, disclosure of survey progress, visual presentation, interactivity, and question/response format—and a final section that summarizes the options in terms of questionnaire design and its implications for nonresponse rate.
Background:
Aerobic exercise typically decreases blood glucose levels in individuals with type 1 diabetes. It is currently unknown if glucose responses to exercise and recovery differ between patients on multiple daily insulin injections (MDI) and continuous subcutaneous insulin infusion (CSII).
Subjects and methods:
Nineteen (16 male, three female) physically active individuals with type 1 diabetes took part in this observational study. Interstitial glucose levels (blinded) were compared during 45 min of standardized aerobic exercise (cycling or running at 60% peak aerobic capacity) and during 6 h of postexercise recovery between individuals using MDI (n=9) and CSII (n=10) therapy.
Results:
Both MDI and CSII groups had similar reductions in glucose levels during exercise, but responses in early and late recovery differed (group × time interaction, P<0.01). Participants using MDI had greater increases in glucose throughout recovery compared with individuals with CSII. Two-thirds of the MDI patients experienced late-onset post-exercise hyperglycemia (blood glucose >12 mmol/L) compared with only 1/10(th) of the CSII patients (P<0.01).
Conclusions:
Among individuals performing regular moderate-to-heavy intensity aerobic exercise, use of CSII helped to limit post-exercise hyperglycemia compared with MDI therapy and is not associated with increased risk for post-exercise late-onset hypoglycemia.
Aims:
Physical activity is part of a healthy lifestyle and contributes to prevent weight gain and cardiometabolic disorders. Adults with Type 1 diabetes are at risk of weight gain attributable to various factors, including a high prevalence of sedentary lifestyle related to fear of exercise-induced hypoglycaemia. This project aims to observe the association between physical activity level and body composition in adults with Type 1 diabetes.
Methods:
Cross-sectional study; 75 adults with and 75 adults without diabetes (52% men; 41.8 ± 11.8 years old) wore a motion sensor for 1 week and performed a cardiorespiratory fitness test on an ergocycle (VO(2peak)). Body composition was assessed by dual energy X-ray absorptiometry and circumferences measures.
Results:
Mean body composition was not different between the two groups. VO(2peak) was lower among the group with diabetes than the control subjects (29.3 ± 9.2 vs. 33.5 ± 9.0 ml kg(-1) min(-1); P = 0.005), but their physical activity level (ratio total/resting energy expenditure) was similar (1.68 ± 0.37 vs. 1.65 ± 0.26; P = 0.572). In both groups, having an active lifestyle (physical activity level ≥ 1.7) compared with a more sedentary lifestyle (physical activity level < 1.7) was associated with lower BMI and percentage of total and truncal fat mass (P ≤ 0.030 to P ≤ 0.001). Among adults with diabetes, physical activity level was not associated with diabetes treatment (insulin doses) and control (HbA(1c) and hypoglycaemia) or cardiovascular risk factors (blood pressure and lipid profile).
Conclusion:
As in the population without diabetes, an active lifestyle is associated with a better body composition profile in adults with Type 1 diabetes.
Utilization of carbohydrate in the form of intramuscular glycogen stores and glucose delivered from plasma becomes an increasingly important energy substrate to the working muscle with increasing exercise intensity. This review gives an update on the molecular signals by which glucose transport is increased in the contracting muscle followed by a discussion of glycogen mobilization and synthesis by the action of glycogen phosphorylase and glycogen synthase, respectively. Finally, this review deals with the signalling relaying the well-described increased sensitivity of glucose transport to insulin in the post-exercise period which can result in an overshoot of intramuscular glycogen resynthesis post exercise (glycogen supercompensation).
Individuals with Type 1 diabetes mellitus are susceptible to hypoglycaemia during and after continuous moderate-intensity exercise, but hyperglycaemia during intermittent high-intensity exercise. The combination of both forms of exercise may have a moderating effect on glycaemia in recovery. The aims of this study were to compare the physiological responses and associated glycaemic changes to continuous moderate-intensity exercise vs. continuous moderate-intensity exercise + intermittent high-intensity exercise in athletes with Type 1 diabetes.
Interstitial glucose levels were measured in a blinded fashion in 11 trained athletes with Type 1 diabetes during two sedentary days and during 2 days in which 45 min of afternoon continuous moderate-intensity exercise occurred either with or without intermittent high-intensity exercise. The total amount of work performed and the duration of exercise was identical between sessions.
During exercise, heart rate, respiratory exchange ratio, oxygen utilization, ventilation and blood lactate levels were higher during continuous moderate-intensity + intermittent high-intensity exercise vs. continuous moderate-intensity exercise (all P < 0.05). Despite these marked cardiorespiratory differences between trials, there was no difference in the reduction of interstitial glucose or plasma glucose levels between the exercise trials. Nocturnal glucose levels were higher in continuous moderate-intensity + intermittent high-intensity exercise and in sedentary vs. continuous moderate-intensity exercise (P < 0.05). Compared with continuous moderate-intensity exercise alone, continuous moderate-intensity + intermittent high-intensity exercise was associated with less post-exercise hypoglycaemia (5.2 vs. 1.5% of the time spent with glucose < 4.0 mmol/l) and more post-exercise hyperglycaemia (33.8 vs. 20.4% of time > 11.0 mmol/l).
Although the decreases in glucose level during continuous moderate-intensity exercise and continuous moderate-intensity + intermittent high-intensity exercise are similar, the latter form of exercise protects against nocturnal hypoglycaemia in athletes with Type 1 diabetes.