Abstract
arbohydrate (CHO) metabolism is crucial for short-duration, high-intensity exercise per- formance, but the effects of variations in glycogen availability have not been investigated in field trials of trained athletes. This study was designed to test how 1500 m time trial (TT) performance is affected by the manipulation of pre-race glycogen reserves. Competitive middle-distance runners (n= 11 (4 females)) completed a 1500 m individually paced indoor TT after abundant (high, >5 g/kg/d) or restricted (low, <1.5 g/kg/d) dietary CHO intake for 2 days after a glycogen-depleting session. Stride pattern, heart rate (HR), capillary blood lactate, and glucose and plasma malondialdehyde (MDA) response were determined. The TT was slower in low vs. high condition by 4.5 (4.5) s (~2%; p< 0.01), with a tendency toward shorter stride length. Blood lactate and glucose were lower before the TT in low vs. high condition (1.8 (0.5) vs. 2.2 (0.7) mmol/L and 5.4 (0.7) vs. 5.9 (0.8) mmol/L, p= 0.022 and 0.007, respectively), and peak lactate was higher in high vs. low condition (16.8 (3.1) vs. 14.5 (4.2) mmol/L,p= 0.039). Plasma MDA was the same before the
toward shorter stride length. Blood lactate and glucose were lower before the TT in low vs. high condition (1.8 (0.5) vs. 2.2 (0.7) mmol/L and 5.4 (0.7) vs. 5.9 (0.8) mmol/L, p= 0.022 and 0.007, respectively), and peak lactate was higher in high vs. low condition (16.8 (3.1) vs. 14.5 (4.2) mmol/L,p= 0.039). Plasma MDA was the same before the TT, and 15 min after the TT, it increased similarly by 15% in low (p= 0.032) and high (p= 0.005) conditions. The restriction of pre-test CHO intake impaired 1500 m TT performance and reduced baseline and peak blood lactate concentrations but not blood glucose or MDA response. Keywords:glycogen depletion; middle-distance race; sports performance; oxidative stress 1. Introduction The ability to perform muscular exercise is affected by the preceding diet. Christensen and Hansen (1939) [1] showed that endurance capacity in prolonged work was enhanced if a diet high in carbohydrate was consumed in the days prior to exercise and was reduced by consumption of a low-carbohydrate diet. Krogh and Lindhard (1920) [2] had previously shown that subjects exercising after a high-carbohydrate diet were less fatigued, and when exercise was preceded by a low-carbohydrate diet, they were more fatigued than after their habitual diet. Soon after this, the benefits of ingesting carbohydrate during exercise were shown in studies of competitors in the Boston marathon race [3]. These studies provided experimental support for the earlier observations of Zuntz (1901) [4] that carbohydrate is a more efficient fuel than fat in terms of oxygen cost: this is important when oxygen availability is a limiting factor in exercise. The crucial role of carbohydrate availability in exercise performance was confirmed when the needle biopsy technique was applied to investigations of muscle metabolism in the 1960s. Bergström and Hultman (1966) [5] showed that the glycogen content of the exercising muscles is dramatically reduced during prolonged exercise. Hermansen et al. Nutrients2024,16, 2763.
Nutrients2024,16, 2763 2 of 14 (1967) [6] reported that during cycling exercise at a work rate corresponding to approxi- mately 75% of maximum oxygen uptake (VO2max), marked depletion of the glycogen stores of the quadriceps muscles occurred at exhaustion. Bergström and Hultman (1966) [5] had already shown that consumption of a diet rich in carbohydrate for a few days af- ter exercise-induced glycogen depletion resulted in a rapid resynthesis of the glycogen stores; after 2–3 days on a high-carbohydrate diet, muscle glycogen content, in those mus- cles which had been exercised, was about 2–3 times greater than the resting value. If a low-carbohydrate diet is consumed in the days after exercise-induced glycogen depletion, the muscle glycogen content remains low for several days [7]. Thus, by using a combina- tion of exercise and dietary modification to manipulate the glycogen content of the mus- cles, Bergström et al. (1967) [8] were able to show a close relationship between the pre- exercise muscle glycogen content and the endurance time during cycling exercise at about 70–75%VO2max. The obvious conclusion from these studies was that the availability of carbohydrate in the form of liver and muscle glycogen stores represents a limiting factor in this type of exercise, and although there might be some qualifications, this remains generally true. A second conclusion is that performance is strongly influenced by the pre-exercise diet and exercise regimen. By contrast, the cause of fatigue in high-intensity exercise of a short duration (a few minutes) has been less studied and is not clearly understood, though many differ- ent mechanisms have been proposed. Here, fatigue can be defined as the inability to main- tain the expected or required power output. The rate of muscle glycogen degradation during exercise increases exponentially with respect to exercise intensity [9], but the du- ration is necessarily short when the intensity is high. Saltin and Karlsson (1971) [10] and Hermansen (1981) [11] concluded that the availability of muscle glycogen does not normally limit endurance capacity at work rates in excess of about 90%VO2max. The normal muscle glycogen content is about 100 mmol glucosyl units kg −1
respect to exercise intensity [9], but the du- ration is necessarily short when the intensity is high. Saltin and Karlsson (1971) [10] and Hermansen (1981) [11] concluded that the availability of muscle glycogen does not normally limit endurance capacity at work rates in excess of about 90%VO2max. The normal muscle glycogen content is about 100 mmol glucosyl units kg −1 wet weight (w.w.) [12]. During exercise at 100%VO2max, the glycogen depletion rate is about 11 mmol glucosyl units kg −1 w.w·min −1 [13]. Endurance time at this work rate is generally in the order of 3–6 min, so there should be adequate glycogen available. Some researchers (e.g., [14]) have measured muscle glycogen concentration at the point of fatigue during intense cycling exercise of a short duration and have reported values in excess of 50 mmol glucosyl units kg −1 w.w. This value is well above theKm for phosphorylase and suggests that substrate availability should not be limiting. These values relate to the whole muscle, however, and it is of course possible that with low pre-exercise muscle glycogen stores, high-intensity exercise performance could be limited by glycogen depletion in a few large motor units and most likely in some fast-twitch (Type II) fibers. With normal pre-exercise glycogen levels, the glycogen content of Type II fibers during repeated sprints decreases sooner and to a greater extent than that of Type I fibers [15], but over 60% of the initial pre-exercise muscle glycogen content was still left in the Type II fibers at exhaustion. More recently, it has been shown that the total muscle glycogen content might be less relevant than the specific pools of glycogen located at different sites within the muscle cell [16]. Key cellular functions, including those of the sodium–potassium and calcium pumps, the calcium-release channels, and the proteins that interact to generate force in the muscle fibers, occur at specific locations within the muscle cell. There are also specific pools of glycogen molecules, and studies from Ørtenblad et al. (2011) [17] and Gejl et al. (2014) [18] have shown that the intramyofibrillar pool may be particularly important during high-intensity
and calcium pumps, the calcium-release channels, and the proteins that interact to generate force in the muscle fibers, occur at specific locations within the muscle cell. There are also specific pools of glycogen molecules, and studies from Ørtenblad et al. (2011) [17] and Gejl et al. (2014) [18] have shown that the intramyofibrillar pool may be particularly important during high-intensity exercise. Preferential utilization of this storage pool occurs and seems to be correlated with an impaired release of calcium ions from the sarcoplasmic reticulum. This in turn leads to impaired excitation–contraction coupling within affected muscle fibers that may contribute to, or even be the cause of, fatigue during high-intensity exercise. In spite of the evidence supporting a potential role for glycogen availability as a deter- mining factor in the performance of high-intensity exercise, relatively few studies are available to provide experimental support. Maughan and Poole (1981) [19] showed that exercise time to
Nutrients2024,16, 2763 3 of 14 exhaustion on a cycle ergometer at a work rate equivalent to 105%VO2max was affected by a pattern of diet and exercise intended to manipulate pre-exercise glycogen availability: exercise time after normal diet was 4.87±1.07 min; after a low-carbohydrate diet, it was reduced to 3.32±0.93 min, and after a high-carbohydrate diet, endurance time was longer than on the normal diet (6.65±1.39 min). Pizza et al. (1995) [20] also found that glycogen loading above normal levels with abundant CHO intake can augment laboratory-based exercise cycling performance in tests lasting a few minutes. Notwithstanding, most laboratory studies have found no effect of this glycogen supercompensation on exercise of a short duration [21–26]. In addition, the laboratory evidence of possible improved physiological function or ergometer performance does not necessarily translate to real-world scenarios [ The main aim of the present study, therefore, was to test whether dietary carbohy- drate restriction after glycogen-depleting exercise affects subsequent middle-distance time trial performance in well-trained runners. It was hypothesized that perturbations in glu- cose metabolism could have negative consequences on racing ability. In addition to racing performance, gross running biomechanics, and physiological responses, an oxidative stress biomarker, plasma malondialdehyde (MDA), an end product of lipid peroxidation, was also measured. The latter addressed the hypothesis that relative glucose deprivation within working muscles under conditions of low CHO availability induced higher oxidative stress. 2. Methods 2.1. Participants Eleven (4 females) well-trained competitive middle-distance runners (mean (SD) age 21 (4) y, height 180 (11) cm, BMI 21 (2) kg/m 2 , and training experience 8 (range 3 to 13) y) volunteered to participate in this study. This study was performed during the athletes’ cross- country racing season (spring), and during the last 4 months, participants were competing indoors until about 2 months before the start of the study, when they switched to largely outdoor training and preparation for cross-country races. Their mean weekly training volume (calculated as the average over the previous month) was 12.3 (1.8) h and included 69 (25) km of running. The personal best IAAF score of the whole group was 841 (103)
competing indoors until about 2 months before the start of the study, when they switched to largely outdoor training and preparation for cross-country races. Their mean weekly training volume (calculated as the average over the previous month) was 12.3 (1.8) h and included 69 (25) km of running. The personal best IAAF score of the whole group was 841 (103) on average [men 779 (24), range 750–827, women 950 (98), range 812–1040], which would correspond to tier 3, as suggested to classify the level of athletes recently [28]. Exclusion criteria were illness or injury that precluded normal regular training for longer than a week during the previous 6 months; dietary manipulations such as energy restriction or avoidance of carbohydrates; 1500 m personal best time slower than 4:20 for male and 5:00 for female participants. All the participants read a description of the study before providing their written informed consent for voluntary participation. The study was conducted in alignment with the recent update of the Declaration of Helsinki and was approved by the Lithuanian Sports University Biomedical Research Ethics Committee (No. TRS(M)-29912, 1 February 2024). 2.2. Organization of the Study This study was a repeated-measures randomized crossover design study, with partici- pants completing a 1500 m time trial (TT) on an indoor 200 m running track after abundant (high) or restricted (low) dietary CHO consumption for 2 days after a glycogen-depleting training session (GDS). Time trials were performed 4 weeks apart, with training and diet during the study period, and especially during the last week preceding the TT, kept as similar as possible. Both the GDS and TT were performed on the same indoor 200 m track in the afternoon at always about the same individual time for the participant. 2.3. Diet Analyses and Manipulations Habitual diet before each period of diet manipulation was recorded daily for the three consecutive days before the GDS by weighing foods, supplements, and beverages and recording intake in a 24 h food diary; a photographic record was made (for verification) of everything consumed. Participants were instructed to email their food tracking data either at the
Diet Analyses and Manipulations Habitual diet before each period of diet manipulation was recorded daily for the three consecutive days before the GDS by weighing foods, supplements, and beverages and recording intake in a 24 h food diary; a photographic record was made (for verification) of everything consumed. Participants were instructed to email their food tracking data either at the end of the same day or the next morning. This timely submission enabled the
Nutrients2024,16, 2763 4 of 14 researchers to monitor food intake in real time, to clarify any ambiguous entries, and to provide feedback to improve the accuracy of the collected data. Food data were collected and analyzed by one of the researchers (PM), who calculated energy and macronutrient in- take using the Cronometer program (https://cronometer.com/, accessed on 1 March 2024). Entries for the foods reported by the participants were selected from institutional databases, including the NCCDB (Nutrition Coordinating Center Food & Nutrient Database) and USDA SR28 (United States Department of Agriculture National Nutrient Database for Standard Reference). For the two days between the GDS and the TT, participants either ate >5 g/kg (aiming for at least ~10 g/kg to meet the recommended amount for CHO loading (which is currently agreed to be 10–12 g/kg/d for 36–48 h [29]; high CHO intake)) or <1.5 g/kg (aiming for ~1 g/kg) of CHO per day (low CHO intake). Since the study employed a crossover design, participants underwent both dietary ma- nipulations with a 4-week washout period in between; the order of treatment allocation was randomized. Before starting the dietary CHO manipulation, participants were thoroughly instructed for practical recommendations on how to modify their diet to achieve the desired dietary intake until the TT. To keep the diets after the GDS until the TT either low or high in CHO, participants on the low-CHO intake trial were required to substitute most of their habitual CHO intake by fat, while the high-CHO intervention required consuming foods high in CHO and low in fats. The amount of protein intake was aimed to be unchanged. Participants were contacted at least once daily by the same researcher to make sure that the recommendations were clear, and the dietary log and food snapshots were checked at the same time to make sure that the instructions were followed. If needed, additional counsel- ing and corrections were made. The diet analysis for major macronutrients (carbohydrates, fats, and proteins) and water content (from beverages and food) was conducted in the same manner as the habitual food intake assessment. Dietary parameters were expressed as
and food snapshots were checked at the same time to make sure that the instructions were followed. If needed, additional counsel- ing and corrections were made. The diet analysis for major macronutrients (carbohydrates, fats, and proteins) and water content (from beverages and food) was conducted in the same manner as the habitual food intake assessment. Dietary parameters were expressed as absolute values and normalized to participants’ body mass. 2.4. Glycogen-Depleting Exercise Session (GDS) A glycogen-depleting exercise session (GDS) was conducted on an indoor 200 m running track 48 h before each TT and comprised 60 min of running at 66% of the intended 1500 m TT speed followed a few minutes after by 10 sets of 200 m (with 200 m jog for recovery) at 1500 m TT pace. A similar training session using stationary cycling was shown in our previous study of recreationally active participants to reduce them. vastus lateralis glycogen content to very low levels [30]. To reduce gluconeogenesis from lactate produced by the 10×200 m sprints and to minimize glycogen replenishment at least in Type I muscle fibers [31], 15 min of jogging at 50% of 1500 m TT speed was completed immediately after the last 200 m bout. Participants were supervised during the GDS and were wearing either their own HR meter or one provided by the researchers. Blood lactate was measured after the 60 min of the steady-state run, after the intervals, and then after 15 min of jogging. During the next day after the GDS, a 30 min running session at 66% of the planned 1500 m TT speed was completed to help keep glycogen levels low in the low-CHO trial and at the same time to allow for the nearly maximal accumulation of muscle glycogen until the TT for the high-CHO trial. No additional training and no caffeine, alcohol, or supplements were allowed within 48 h of the TT. 2.5. 1500 m Time Trial (TT) Participants arrived around midday at the indoor track and field arena after having their last meal 2 to 5 h before (following their habitual pre-competition eating pattern). After
muscle glycogen until the TT for the high-CHO trial. No additional training and no caffeine, alcohol, or supplements were allowed within 48 h of the TT. 2.5. 1500 m Time Trial (TT) Participants arrived around midday at the indoor track and field arena after having their last meal 2 to 5 h before (following their habitual pre-competition eating pattern). After visiting the toilet, their nude body mass was measured and body composition was estimated by bioelectric impedance analysis (Tanita TBF-300, Tokyo, Japan). The athletes then warmed-up by jogging for 10 min at their usual comfortable easy pace and performing 10–15 min of dynamic stretching, skipping, short strides, etc., as part of their standard routine. Before starting, an HR sensor (Polar H10, Kempele, Finland) was securely strapped on the chest and an HR monitor was attached on the wrist for continuous measurements
Nutrients2024,16, 2763 5 of 14 of HR during the TT. Capillary blood lactate and glucose concentrations were measured ~1 min before the TT, and the instructions were repeated. Runners started the 1500 m individual TT at the half-way point of the arena after being instructed to complete the TT in the fastest possible time. A custom-made red lamp leader installed on the balcony of the arena was pre-set at the intended (pre-arranged) pace of the participant, which was agreed between the coach and the runner based on the current capacity. It was not obligatory to follow the pacing lamp, but runners were recommended to keep with the lamp for at least the initial 400 m and then decide on their further pacing strategy depending on how they were feeling. Timing gates (Witty, Microgate, Bolzano, Italy) were placed at the start and finish lines, and thus interim times were automatically recorded every 100 m. The researchers, who were blinded to the dietary intake data, cheered and encouraged the runners with every lap completed. The time trial was run individually with spikes and competitive attire. The ambient temperature in the arena was 19.5 to 20.5 ◦ C, and the relative humidity was 45 to 55%. Gross running mechanics (running spatiotemporal parameters) were measured by placing 10 m light beam gates (the Optojump system, Microgate, Bolzano, Italy) on the first lane 50 m from the finish line to record the step rate and length and contact and flight phase durations during each 200 m lap. Analysis of the data showed no consistent pattern of change over time, so the values of each parameter were averaged across all eight laps. After crossing the finish line, participants lay down on a soft mat for 15 min of passive recovery with continued HR recording, and fingertip blood lactate (Lactate Pro2, Arkray, Kyoto, Japan) and glucose (Ascensia Contour Plus, Bayer Healthcare AG, Leverkusen, Germany) levels were measured at 1, 3, 5, and 15 min post-exercise. Recovery jogging was then allowed as desired. Within 1 min after the completion of the TT, participants were asked to rate their
Description
This study tests how carbohydrate intake affects 1500 m run performance in trained athletes.