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Schematic of the different stages in the 2012 GODZone adventure race, and the timing of physiological outcomes before, during and after the race.
Source publication
Background/Objective
Adventure racing is an ultra-endurance activity that imposes a unique multifaceted stress on the human body. The purpose of this field study was to examine the physiological responses to a 5-day adventure race.
Methods
Eight competitors, two teams (1 female each) in the 2012 GODZone adventure race volunteered. Competitors trek...
Context in source publication
Context 1
... Measures. A continuous glucose monitor (CGM) was positioned in the subcutaneous layer of the abdomen to measure glucose the day before, and throughout the race (Fig. 1). Data are validated against capillary samples obtained during the race (Carelink, iPro Medtronic). Glycemic variability variables were analysed via spreadsheet (EasyGV, Oxford, UK). Urine samples were collected and measured for hydration (USG), electrolytes (Na þ , K þ ) using the Ion Selective Electrode technique, and urine glucose, ...
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Regular physical activity during childhood is important for optimal physical and psychological development. For individuals with Type 1 Diabetes (T1D), physical activity offers many health benefits including improved glycemic control, cardiovascular function, blood lipid profiles, and psychological well-being. Despite these benefits, many young peo...
Citations
... While [iG] was elevated during exercise, the maximum and minimum concentrations were experienced outside of exercise but within the day-time period. This is potentially an effect of increased variability often observed post-exercise (Francois et al., 2018;Kulawiec et al., 2021;Thomas et al., 2016). Though access to data quantifying the riders' nutritional intake throughout the camp was unavailable, the riders in the present study consumed a meal soon after exercise. ...
... However, the integration of continuous CGM over consecutive days' worth of data capture including daily bouts of cycle training expands our current knowledge base of glycaemia in an all-female elite cycling cohort.This study focussed on collecting measures of glycaemic variability throughout a 9-day training camp. While others have also tracked some measures of variability(Francois et al., 2018;Thomas et al., 2016), few have collected data during the recovery period postexercise in a free living, real-life training camp environment. CGM allows for a constant stream of data, which improves the ability to detect rapid fluctuations which might be missed if adopting a fixed timepoint collection schedule, which would be typical of finger prick sampling, the impracticability of which makes for difficulty in obtaining real-time information. ...
Nine cyclists (age: 26 ± 5 years, height: 168 ± 5 cm and mass 58.5 ± 4.5 kg) were observed using continuous glucose monitoring devices throughout a training camp. Interstitial glucose [iG] data were captured via the Abbott libre sense biosensor (Abbott Laboratories) and paired with the Supersapiens software (TT1 Products Inc.). [iG] data were split into time ranges, that is, overall (24‐hourly), day‐time (06:00–23:59), night‐time (00:00–05:59) and exercise. [iG] data were stratified into percentage of time, below range ([TBR] < 70 mg/dl), in range ([TIR] 70–140 mg/dl) and above range ([TAR] ≥ 141 mg/dl). Differences in diurnal and nocturnal data were analysed via repeated measures analysis of variance and paired t‐tests where appropriate. p‐value of ≤0.05 was accepted as significant. Riders spent an average of 3 ± 1% TAR, 93 ± 2% TIR and 8 ± 3% TBR. Mean 24 h [iG] was 93 ± 2 mg/dl with a coefficient of variation (CV) of 18 ± 1%. Mean (day: 95 ± 3 vs. night: 86 ± 3 mg/dl and p < 0.001) and CV (day: 18 ± 1 vs. night: 9 ± 1% and p < 0.001) in [iG] were higher during the day‐time hours. TAR was greater during the day (day: 3 ± 1 vs. night: 0 ± 0% and p < 0.001) but TBR and TIR were similar. Glucose levels below the clinical range may have implications for those without diabetes and warrants further investigation.
... CX1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8K2+Ya6H515kE= on 04/10/2024 previous studies which indicated that glucose levels do not necessarily reach hypoglycemia during endurance tasks lasting up to 3h, often with task failure still developing in healthy nondiabetic individuals (23, 46,47). It is unclear what explains the discrepancy as to whether hypoglycemia is observed following exercise without CHO ingestion but there could be a variety of factors including the type and duration of exercise, the extent of fatigue induced during the exercise, as well as training status which affects both glucose and glycogen utilization. ...
Introduction
We aimed to investigate the neuromuscular contributions to enhanced fatigue resistance with carbohydrate ingestion, and to identify whether fatigue is associated with changes in interstitial glucose levels assessed using a continuous glucose monitor (CGM).
Methods
Twelve healthy participants (6 males, 6 females) performed isokinetic single-leg knee extensions (90°/s) at 20% of the maximal voluntary contraction (MVC) torque until MVC torque reached 60% of its initial value (i.e, task failure). Central and peripheral fatigue were evaluated every 15 min during the fatigue task using the interpolated twitch technique (ITT), and electrically evoked torque. Using a single-blinded cross-over design, participants ingested carbohydrates (CHO) (85 g sucrose/h), or a placebo (PLA), at regular intervals during the fatigue task. Minute-by-minute interstitial glucose levels measured via CGM, and whole blood glucose readings were obtained intermittently during the fatiguing task.
Results
CHO ingestion increased time to task failure over PLA (113 ± 69 vs. 81 ± 49 min; mean ± SD; p < 0.001) and was associated with higher glycemia as measured by CGM (106 ± 18 vs 88 ± 10 mg/dL, p < 0.001) and whole blood glucose sampling (104 ± 17 vs 89 ± 10 mg/dL, p < 0.001). When assessing the values in the CHO condition at a similar timepoint to those at task failure in the PLA condition (i.e., ~81 min), MVC torque, % voluntary activation, and 10 Hz torque were all better preserved in the CHO vs. PLA condition (p < 0.05).
Conclusions
Exogenous CHO intake mitigates neuromuscular fatigue at both the central and peripheral levels by raising glucose concentrations rather than by preventing hypoglycemia.
... The IGC was continuously evaluated by a continuous glucose monitoring (CGM) system (FreeStyle Libre Flash Glucose Monitoring Device, FreeStyle Libre; Abbott Diabetes Care, Alameda, CA, USA; [24][25][26]). The subjects wore the device from day 1 (9:00 a.m.) until day 4 (9:00 a.m.). ...
We compared the 24 h changes in interstitial fluid glucose concentration (IGC) following a simulated soccer match between subjects consuming a high-carbohydrate (HCHO; 8 g/kg BW/day) diet and those consuming a moderate-carbohydrate (MCHO; 4 g/kg BW/day) diet. Eight active healthy males participated in two different trials. The subjects were provided with the prescribed diets from days 1 to 3. On day 3, the subjects performed 90 min (2 bouts × 45 min) of exercise simulating a soccer match. The IGC of the upper arm was continuously monitored from days 1 to 4. No significant difference in the IGC was observed between trials during exercise. The total area under the curve (t-AUC) value during exercise did not significantly differ between the HCHO (9719 ± 305 mg/dL·90 min) and MCHO (9991 ± 140 mg/dL·90 min). Serum total ketone body and beta-hydroxybutyrate concentrations were significantly higher in the MCHO than in the HCHO after a second bout of exercise. No significant differences in the IGC were observed between trials at any time point during the night after exercise (0:00–7:00). In addition, t-AUC value during the night did not significantly differ between the HCHO (32,378 ± 873 mg/dL·420 min) and MCHO (31,749 ± 633 mg/dL·420 min). In conclusion, two days of consuming different carbohydrate intake levels did not significantly affect the IGC during a 90 min simulated soccer match. Moreover, the IGC during the night following the exercise did not significantly differ between the two trials despite the different carbohydrate intake levels (8 vs. 4 g/kg BW/day).
... Although CGMs were initially designed to assist in the clinical management of both insulin-dependent and noninsulin-dependent diabetes, there is now interest in the application of real-time glucose monitoring to athletic populations (Petrovski et al., 2004). Several case studies have incorporated the use of CGMs to report interstitial glucose responses to exercise in an effort to characterize CHO availability of athletes when participating in endurance and ultra-endurance events (Doering et al., 2019;Francois et al., 2018;Ishihara et al., 2020;Sengoku et al., 2015). However, manufacturers of CGM devices have either identified or created a wider interest among athletes to maintain optimal glucose levels during training (Abbott Laboratories, 2020) and now market these products as a tool to enable athletes to "push their limits longer and get bigger gains" (Supersapiens INC, 2021). ...
... Because of the recent advent of CGM use by athletes, there are few published studies and case histories of its use (summarized in Table 4). The most popular study theme has been monitoring of athlete glucose profiles during single-day (Ishihara et al., 2020;Sengoku et al., 2015) and multi-day (Francois et al., 2018) ultraendurance events. During a single-day 165-km ultra-trail race, athletes who consumed less CHO throughout the race tended to have lower glucose levels and took longer to complete the race (Ishihara et al., 2020). ...
... Furthermore, the ambient temperature and humidity level reduce sensor durability as higher rates of sweating present challenges for securing the CGM, which prevents transmission of data from the sensor to the CGM receiver (Englert et al., 2014). Indeed, studies have reported the dislodging of CGM devices during endurance events, resulting in the subsequent loss of glucose data (Francois et al., 2018). ...
This review discusses the potential value of tracking interstitial glucose with continuous glucose monitors (CGMs) in athletes, highlighting possible applications and important considerations in the collection and interpretation of interstitial glucose data. CGMs are sensors that provide real time, longitudinal tracking of interstitial glucose with a range of commercial monitors currently available. Recent advancements in CGM technology have led to the development of athlete-specific devices targeting glucose monitoring in sport. Although largely untested, the capacity of CGMs to capture the duration, magnitude, and frequency of interstitial glucose fluctuations every 1–15 min may present a unique opportunity to monitor fueling adequacy around competitive events and training sessions, with applications for applied research and sports nutrition practice. Indeed, manufacturers of athlete-specific devices market these products as a “fueling gauge,” enabling athletes to “push their limits longer and get bigger gains.” However, as glucose homeostasis is a complex phenomenon, extensive research is required to ascertain whether systemic glucose availability (estimated by CGM-derived interstitial glucose) has any meaning in relation to the intended purposes in sport. Whether CGMs will provide reliable and accurate information and enhance sports nutrition knowledge and practice is currently untested. Caveats around the use of CGMs include technical issues (dislodging of sensors during periods of surveillance, loss of data due to synchronization issues), practical issues (potential bans on their use in some sporting scenarios, expense), and challenges to the underpinning principles of data interpretation, which highlight the role of sports nutrition professionals to provide context and interpretation.
... One of the challenges in diabetes, especially in children, is the measurement of capillary blood glucose. Many children do not measure blood glucose due to pain, loss of time and shame, and do not adequately manage The importance of exercise in the treatment of diabetes is indisputably known, but each individual's glycemic variability with exercise is different and the effect on blood glucose depends on the duration and type of exercise (10,11). Although exercise rules are determined by many associations, there are individual differences in practice (12,13). ...
... It was found to be related to microvascular complications (21). In non-diabetic persons, after intense exercise, despite no changes in mean blood glucose levels, there is increased glycemic variability and increased periods of hypoglycemia (10). Although light exercise and glycemic variability in type 2 diabetes mellitus has been studied, the information about the effect of exercise on glycemic variability in children with type 1 diabetes was inadequate (11,22). ...
Aim:Glycemic variability can be affected in diabetes camps as a result of sports, social activities and nutrition. Close glucose monitoring is necessary to reduce glycemic variability, especially hypoglycemia. The aim assessment of glycemic variability and time in range by use of the flash glucose monitoring system (FGMS) in children and adolescents with type 1 diabetes.Materials and Methods:Thirty-three children and adolescents between 10-18 years of age who participated in the 2018 diabetes camp of Ege University were included. Their glycemic variability indexes were recorded.Results:The mean age and duration of diabetes mellitus in the study group was 13.3±0.5 and 4.9±0.7 years respectively. Twelve (43%) of the participants were boys and 16 (57%) were girls. Ten (35.7%) of the participants used continuous subcutaneous insulin infusion (CSII) pump therapy while 18 (64.3%) used multiple dose insulin therapy. When the participants were evaluated according to time in range (TIR), the duration of TIR increased, and level 1 and level 2 hyperglycemia decreased during the camp. Participants using CSII had spent more time in level 2 hypoglycemia before camp, but during and after the camp, similar values were reached for both groups. Before the camp, participants with good metabolic control had a longer duration of hypoglycemia than those participants with poor metabolic control. During and after the camp, level 1 and level 2 hypoglycemia periods were similar between the two groups.Conclusion:In diabetes camp, healthy diet, regular exercise, and close glycemic control improve glycemic variability. By using FGMS, normoglycemia periods can be increased without increasing hypoglycemic attacks. As a result, using FGMS had a positive effect on diabetes management and the control of hypoglycemia periods during the diabetes camp.
