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.

Acute Fluid Intake Impacts Assessment of Body Composition via Bioelectrical Impedance Analysis. A Randomized, Controlled Crossover Pilot Trial.

Bioelectrical impedance analysis (BIA) has proven to be particularly useful due to its inexpensive and rapid assessment of total body water and body density. However, recent fluid intake may confound BIA results since equilibration of fluid between intra- and extracellular spaces may take several hours and furthermore, ingested fluids may not be fully absorbed. Therefore, we aimed to evaluate the impact of different fluid compositions on the BIA. A total of eighteen healthy individuals (10 females, mean ± SD age of 23.1 ± 1.8 years) performed a baseline measurement of body composition before they consumed isotonic 0.9% sodium-chloride (ISO), 5% glucose (GLU) or Ringer (RIN) solutions. During the visit of the control arm (CON), no fluid was consumed. Further impedance analyses were conducted every 10 min after the fluid consumption for 120 min. We found statistically significant interactions between the effects of solution ingestion and time for intra- (ICW, p < 0.01) and extracellular water (ECW, p < 0.0001), skeletal muscle mass (SMM, p < 0.001) and body fat mass (FM, p < 0.01), respectively. Simple main effects analysis showed that time had a statistically significant effect on changes in ICW (p < 0.01), ECW (p < 0.01), SMM (p < 0.01) and FM (p < 0.01), while fluid intake did not have a significant effect. Our results highlight the importance of a standardized pre-measurement nutrition, with particular attention to hydration status when using a BIA for the evaluation of body composition.

Blood glucose response to running or cycling in individuals with type 1 diabetes: A systematic review and meta-analysis.

AIMS: The aim of this systematic review and meta-analysis was to assess how running and cycling influence the magnitude of blood glucose (BG) excursions in individuals with type 1 diabetes. METHODS: A systematic literature search was conducted in EMBASE, PubMed, Cochrane Central Register of Controlled Trials, and ISI Web of Knowledge for publications from January 1950 until February 2021. Parameters included for analysis were population (adults and adolescents), exercise type, intensity, duration and insulin preparation. The meta-analysis was performed to estimate the pooled mean with a 95% confidence interval (CI) of delta BG levels. In addition, sub-group and meta-regression analyses were performed to assess the influence of these parameters on delta BG. RESULTS: The database search identified 3192 articles of which 69 articles were included in the meta-analysis. Due to crossover designs within articles, 151 different results were included for analysis. Data from 1901 exercise tests of individuals with type 1 diabetes with a mean age of 29 ± 4 years were included. Overall, exercise tests BG decreased by -3.1 mmol/L [-3.4; -2.8] within a mean duration of 46 ± 21 min. The pooled mean decrease in BG for running was -4.1 mmol/L [-4.7; -2.4], whilst the pooled mean decrease in BG for cycling was -2.7 mmol/L [-3.0; -2.4] (p < 0.0001). Overall results can be found in Table S2. CONCLUSIONS: Running led to a larger decrease in BG in comparison to cycling. Active individuals with type 1 diabetes should be aware that current recommendations for glycaemic management need to be more specific to the mode of exercise.

Glucose and Fructose Supplementation and Their Acute Effects on Anaerobic Endurance and Resistance Exercise Performance in Healthy Individuals: A Double-Blind Randomized Placebo-Controlled Crossover Trial.

BACKGROUND: The effects of glucose, fructose and a combination of these on physical performance have been subject of investigation, resulting in diverse findings. OBJECTIVE: The aim of this study was to investigate how an individualized amount of glucose, fructose, and a combination of these compared to placebo (sucralose) alter endurance performance on a cycle ergometer, lower and upper body resistance exercise performance at individualized thresholds in healthy young individuals. METHODS: A total of 16 healthy adults (9 females) with an age of 23.8 ± 1.6 years and a BMI of 22.6 ± 1.8 kg/m2 (body mass (BM) 70.9 ± 10.8 kg, height 1.76 ± 0.08 m) participated in this study. During the screening visit, the lactate turn point 2 (LTP2) was defined and the weights for chest-press and leg-press were determined. Furthermore, 30 min prior to each exercise session, participants received either 1 g/kg BM of glucose (Glu), 1 g/kg BM of fructose (Fru), 0.5 g/kg BM of glucose/fructose (GluFru) (each), or 0.2 g sucralose (placebo), respectively, which were dissolved in 300 mL of water. All exercises were performed until volitional exhaustion. Time until exhaustion (TTE) and cardio-pulmonary variables were determined for all cycling visits; during resistance exercise, repetitions until muscular failure were counted and time was measured. During all visits, capillary blood glucose and blood lactate concentrations as well as venous insulin levels were measured. RESULTS: TTE in cycling was 449 ± 163 s (s) (Glu), 443 ± 156 s (Fru), 429 ± 160 s (GluFru) and 466 ± 162 s (Pla) (p = 0.48). TTE during chest-press sessions was 180 ± 95 s (Glu), 180 ± 92 s (Fru), 172 ± 78 s (GluFru) and 162 ± 66 s (Pla) (p = 0.25), respectively. CONCLUSIONS: Pre-exercise supplementation of Glu, Fru and a combination of these did not have an ergogenic effect on high-intensity anaerobic endurance performance and on upper and lower body moderate resistance exercise in comparison to placebo.

Glucose and Fructose Supplementation and Their Acute Effects on Electrocardiographic Time Intervals during Anaerobic Cycling Exercise in Healthy Individuals: A Secondary Outcome Analysis of a Double-Blind Randomized Crossover-Controlled Trial.

The impact of glucose and fructose supplementation on acute cardiac effects during cardiopulmonary exercise testing (CPET) is a topic that is rarely investigated. The aim of the presented secondary outcome analysis of a double-blind, randomized crossover-controlled trial was to investigate the impact of glucose (Glu), fructose (Fru), glucose and fructose (GluFru), and sucralose on electrocardiogram (ECG), heart rate variability (HRV), premature ventricular complexes (PVCs), and heart rate turn points (HRTP) during CPET. Fourteen healthy individuals (age 25.4 ± 2.5 years, body mass index (BMI) 23.7 ± 1.7 kg/m2, body mass (BM) of 76.3 ± 12.3 kg) participated in this study, of which 12 were included for analysis. Participants received 1 g/kg BM of Glu, 1 g/kg BM of Fru, 0.5 g/kg BM of GluFru (each), and 0.2 g sucralose dissolved in 300 mL 30 min prior to each exercise session. No relevant clinical pathology or significant inter-individual differences between our participants could be revealed for baseline ECG parameters, such as heart rate (HR) (mean HR 70 ± 16 bpm), PQ interval (146 ± 20 ms), QRS interval (87 ± 16 ms) and the QT (405 ± 39 ms), and QTc interval (431 ± 15 ms). We found preserved cardiac autonomic function by analyzing the acute effects of different Glu, Fru, GluFru, or sucralose supplementation on cardiac autonomic function by Schellong-1 testing. SDNN and RMSSD revealed normal sympathetic and parasympathetic activities displaying a balanced system of cardiac autonomic regulation across our participating subjects with no impact on the metabolism. During CPET performance analyses, HRV values did not indicate significant changes between the ingested drinks within the different time points. Comparing the HRTP of the CPET with endurance testing by variable metabolic conditions, no significant differences were found between the HRTP of the CPET data (170 ± 12 bpm), Glu (171 ± 10 bpm), Fru (171 ± 9 bpm), GluFru (172 ± 9 bpm), and sucralose (170 ± 8 bpm) (p = 0.83). Additionally, the obtained time to reach HRTP did not significantly differ between Glu (202 ± 75 s), Fru (190 ± 88 s), GluFru (210 ± 89 s), and sucralose (190 ± 34 s) (p = 0.59). The significance of this study lies in evaluating the varying metabolic conditions on cardiac autonomic modulation in young healthy individuals. In contrast, our participants showed comparable cardiac autonomic responses determined by ECG and CPET.

Accuracy of Real Time Continuous Glucose Monitoring during Different Liquid Solution Challenges in Healthy Adults: A Randomized Controlled Cross-Over Trial.

Continuous glucose monitoring (CGM) represents an integral of modern diabetes management, however, there is still a lack of sensor performance data when rapidly consuming different liquids and thus changing total body water. 18 healthy adults (ten females, age: 23.1 ± 1.8 years, BMI 22.2 ± 2.1 kg·m−2) performed four trial visits consisting of oral ingestion (12 mL per kg body mass) of either a 0.9% sodium chloride, 5% glucose or Ringer's solution and a control visit, in which no liquid was administered (control). Sensor glucose levels (Dexcom G6, Dexcom Inc., San Diego, CA, USA) were obtained at rest and in 10-min intervals for a period of 120 min after solution consumption and compared against reference capillary blood glucose measurements. The overall MedARD [IQR] was 7.1% [3.3−10.8]; during control 5.9% [2.7−10.8], sodium chloride 5.0% [2.7−10.2], 5% glucose 11.0% [5.3−21.6] and Ringer's 7.5% [3.1−13.2] (p < 0.0001). The overall bias [95% LoA] was 4.3 mg·dL−1 [−19 to 28]; during control 3.9 mg·dL−1 [−11 to 18], sodium chloride 4.8 mg·dL−1 [−9 to 19], 5% glucose 3.6 mg·dL−1 [−33 to 41] and Ringer's solution 4.9 mg·dL−1 [−13 to 23]. The Dexcom G6 CGM system detects glucose with very good accuracy during liquid solution challenges in normoglycemic individuals, however, our data suggest that in people without diabetes, sensor performance is influenced by different solutions.

Acute Effects of Esports on the Cardiovascular System and Energy Expenditure in Amateur Esports Players.

Introduction: Esports is practiced by millions of people worldwide every day. On a professional level, esports has been proven to have a high stress potential and is sometimes considered equivalent to traditional sporting activities. While traditional sports have health-promoting effects through muscle activity and increased energy expenditure, amateur esports could represent a purely sedentary activity, which would carry potentially harmful effects when practiced regularly. Therefore, this study aims to investigate the acute effects of esports on the cardiovascular system and energy expenditure in amateur esports players to show whether esports can be considered as physical strain or mental stress or whether amateur esports has to be seen as purely sedentary behavior. Methods: Thirty male subjects participated in a 30-min gaming session, playing the soccer simulation game FIFA 20 or the tactical, first-person multiplayer shooter Counter-Strike: Global Offensive. Respiratory and cardiovascular parameters, as well as energy expenditure, blood glucose, lactate, and cortisol, were determined pre-, during, and post-gaming. Results: There were no significant changes in oxygen uptake, carbon dioxide output, energy expenditure, stroke volume, or lactate levels. Heart rate, blood glucose and cortisol decreased through the intervention until reaching their minimum levels 10 min post-gaming (Cortisolpre: 3.1 ± 2.9 ng/ml, Cortisolpost: 2.2 ± 2.3 ng/ml, p < 0.01; HRmin0.5: 82 ± 11 bpm, HRpost: 74 ± 13 bpm, p < 0.01). Conclusion: A 30-min esports intervention does not positively affect energy expenditure or metabolism in amateur esports players. Therefore, it cannot provide the same health-promoting effects as traditional sports participation, but could in the long-term rather cause the same potentially health-damaging effects as purely sedentary behavior. However, it does not trigger a negative stress response in the players. Deliberate physical activity and exercise routines adapted to these demands should therefore be part of the daily life of amateur esports players.

The Impact of a High-Carbohydrate/Low Fat vs. Low-Carbohydrate Diet on Performance and Body Composition in Physically Active Adults: A Cross-Over Controlled Trial.

Background: Recently, high-carbohydrate or low-carbohydrate (HC/LC) diets have gained substantial popularity, speculated to improve physical performance in athletes; however, the effects of short-term changes of the aforementioned nutritional interventions remain largely unclear. Methods: The present study investigated the impact of a three-week period of HC/low-fat (HC) diet followed by a three-week wash-out-phase and subsequent LC diet on the parameters of physical capacity assessed via cardiopulmonary exercise testing, body composition via bioimpedance analysis and blood profiles, which were assessed after each of the respective diet periods. Twenty-four physically active adults (14 females, age 25.8 ± 3.7 years, body mass index 22.1 ± 2.2 kg/m2), of which six participants served as a control group, were enrolled in the study. Results: After three weeks of each diet, VO2peak was comparable following both interventions (46.8 ± 6.7 (HC) vs. 47.2 ± 6.7 mL/kg/min (LC; p = 0.58)) while a significantly higher peak performance (251 ± 43 W (HC) vs. 240 ± 45 W (LC); (p = 0.0001), longer time to exhaustion (14.5 ± 2.4 min (HC) vs. 14.1 ± 2.4 min (LC); p = 0.002) and greater Watt/kg performance (4.1 ± 0.5 W/kg (HC) vs. 3.9 ± 0.5 W/kg (LC); p = 0.003) was demonstrated after the HC diet. In both trial arms, a significant reduction in body mass (65.2 ± 11.2 to 63.8 ± 11.8 kg (HC) vs. 64.8 ± 11.6 to 63.5 ± 11.3 kg (LC); both p < 0.0001) and fat mass (22.7% to 21.2%; (HC) vs. 22.3% to 20.6% (LC); both p < 0.0001) but not in lean body mass or skeletal muscle mass was shown when compared to baseline. Resting metabolic rate was not different within both groups (p > 0.05). Total cholesterol and LDL-cholesterol significantly decreased after the HC diet (97.9 ± 33.6 mg/dL at baseline to 78.2 ± 23.5 mg/dL; p = 0.02) while triglycerides significantly increased (76 ± 38 mg/dL at baseline to 104 ± 44 mg/dL; p = 0.005). Conclusion: A short-term HC and LC diet showed improvements in various performance parameters in favor of the HC diet. Some parameters of body composition significantly changed during both diets. The HC diet led to a significant reduction in total and LDL-cholesterol while triglycerides significantly increased.

Acute Metabolic Responses to Glucose and Fructose Supplementation in Healthy Individuals: A Double-Blind Randomized Crossover Placebo-Controlled Trial.

The aim of this study was to investigate the impact of glucose (Glu), fructose (Fru), glucose and fructose (GluFru) and sucralose on blood glucose response in healthy individuals. Fifteen healthy individuals (five females, age of 25.4 ± 2.5 years, BMI of 23.7 ± 1.7 kg/m2 with a body mass (BM) of 76.3 ± 12.3 kg) participated in this double-blind randomized crossover placebo-controlled trial. Participants received a mixture of 300 mL of water with 1 g/kg BM of Glu, 1 g/kg BM of Fru, 0.5 g/kg BM of GluFru (each), and 0.2 g sucralose as a placebo. Peak BG values Glu were reached after 40 ± 13 min (peak BG: 141 ± 20 mg/dL), for Fru after 36 ± 22 min (peak BG: 98 ± 7 mg/dL), for GluFru after 29 ± 8 min (BG 128 ± 18 mg/dL), and sucralose after 34 ± 27 min (peak BG: 83 ± 5 mg/dL). Significant differences regarding the time until peak BG were found only between Glu and GluFru supplementation (p = 0.02). Peak blood glucose levels were significantly lower following the ingestion of Fru compared to the supplementation of Glu and GluFru (p < 0.0001) while Glu and GluFru supplementation showed no difference in peak values (p = 0.23). All conditions led to a significantly higher peak BG value compared to sucralose (p < 0.0001). Blood lactate increased in Glu (p = 0.002), Fru and GluFru (both p < 0.0001), whereas sucralose did not increase compared to the baseline (p = 0.051). Insulin levels were significantly higher in all conditions at peak compared to sucralose (p < 0.0001). The findings of this study prove the feasibility of combined carbohydrate supplementations for many applications in diabetic or healthy exercise cohorts.

Time in Range for Closed-Loop Systems versus Standard of Care during Physical Exercise in People with Type 1 Diabetes: A Systematic Review and Meta-Analysis.

The aim of this systematic review and meta-analysis was to compare time in range (TIR) (70-180 mg/dL (3.9-10.0 mmol/L)) between fully closed-loop systems (CLS) and standard of care (including hybrid systems) during physical exercise in people with type 1 diabetes (T1D). A systematic literature search was conducted in EMBASE, PubMed, Cochrane Central Register of Controlled Trials, and ISI Web of Science from January 1950 until January 2020. Randomized controlled trials including studies with different CLS were compared against standard of care in people with T1D. The meta-analysis was performed using the random effects model and restricted maximum likelihood estimation method. Six randomized controlled trials involving 153 participants with T1D of all age groups were included. Due to crossover test designs, studies were included repeatedly (a-d) if CLS or physical exercise interventions were different. Applying this methodology increased the comparisons to a total number of 266 participants. TIR was higher with an absolute mean difference (AMD) of 6.18%, 95% CI: 1.99 to 10.38% in favor of CLS. In a subgroup analysis, the AMD was 9.46%, 95% CI: 2.48% to 16.45% in children and adolescents while the AMD for adults was 1.07% 95% CI: -0.81% to 2.96% in favor of CLS. In this systematic review and meta-analysis CLS moderately improved TIR in comparison to standard of care during physical exercise in people with T1D. This effect was particularly pronounced for children and adolescents showing that the use of CLS improved TIR significantly compared to standard of care.

Eat, Train, Sleep-Retreat? Hormonal Interactions of Intermittent Fasting, Exercise and Circadian Rhythm.

The circadian rhythmicity of endogenous metabolic and hormonal processes is controlled by a complex system of central and peripheral pacemakers, influenced by exogenous factors like light/dark-cycles, nutrition and exercise timing. There is evidence that alterations in this system may be involved in the pathogenesis of metabolic diseases. It has been shown that disruptions to normal diurnal rhythms lead to drastic changes in circadian processes, as often seen in modern society due to excessive exposure to unnatural light sources. Out of that, research has focused on time-restricted feeding and exercise, as both seem to be able to reset disruptions in circadian pacemakers. Based on these results and personal physical goals, optimal time periods for food intake and exercise have been identified. This review shows that appropriate nutrition and exercise timing are powerful tools to support, rather than not disturb, the circadian rhythm and potentially contribute to the prevention of metabolic diseases. Nevertheless, both lifestyle interventions are unable to address the real issue: the misalignment of our biological with our social time.