Effects of 120 vs. 60 and 90 g/h carbohydrate intake during a trail marathon on neuromuscular function and high intensity run capacity recovery

nutrients Article Effects of 120 vs. 60 and 90 g/h Carbohydrate Intake during a Trail Marathon on Neuromuscular Function and High Intensity Run Capacity Recovery Aritz Urdampilleta 1, Soledad Arribalzaga 2, Aitor Viribay 3, Arkaitz Castañeda-Babarro 4, Jesús Seco-Calvo 5and Juan Mielgo-Ayuso 6,* 1Centro Investigación y Formación ElikaSport, Cerdanyola del Valles, 08290 Barcelona, Spain; [email protected] 2 Institute of Biomedicine (IBIOMED), Physiotherapy Department, University of Leon, Campus de Vegazana, 24071 Leon, Spain; [email protected] 3Glut4Science, Physiology, Nutrition and Sport, 01004 Vitoria-Gasteiz, Spain; [email protected] 4 Health, Physical Activity and Sports Science Laboratory, Department of Physical Activity and Sports, Faculty of Psychology and Education, University of Deusto, 48007 Bizkaia, Spain; [email protected] 5Institute of Biomedicine (IBIOMED), Physiotherapy Department, University of Leon, Researcher at the Basque Country University, Campus de Vegazana, 24071 Leon, Spain; dr[email protected] 6Department of Biochemistry, Molecular Biology and Physiology, Faculty of Health Sciences, University of Valladolid, 42004 Soria, Spain *Correspondence: [email protected]; Tel.: +34-975-129187 Received: 3 June 2020; Accepted: 11 July 2020; Published: 15 July 2020   Abstract: Background: Current carbohydrate (CHO) intake recommendations for ultra-trail activities lasting more than 2.5 h is 90 g/h. However, the benefits of ingesting 120 g/h during a mountain marathon in terms of post-exercise muscle damage have been recently demonstrated. Therefore, the aim of this study was to analyze and compare the effects of 120 g/h CHO intake with the recommendations (90 g/h) and the usual intake for ultra-endurance athletes (60 g/h) during a mountain marathon on internal exercise load, and post-exercise neuromuscular function and recovery of high intensity run capacity. Methods: Twenty-six elite trail-runners were randomly distributed into three groups: LOW (60 g/h), MED (90 g/h) and HIGH (120 g/h), according to CHO intake during a 4000-m cumulative slope mountain marathon. Runners were measured using the Abalakov Jump test, a maximum a half-squat test and an aerobic power-capacity test at baseline (T1) and 24 h after completing the race (T2). Results: Changes in Abalakov jump time (ABK JT ), Abalakov jump height (ABK H ), half-squat test 1 repetition maximum (HST 1RM ) between T1 and T2 showed significant differences by Wilcoxon signed rank test only in LOW and MED (p<0.05), but not in the HIGH group (p>0.05). Internal load was significantly lower in the HIGH group (p=0.017) regarding LOW and MED by Mann Whitney utest. A significantly lower change during the study in ABK JT (p=0.038), ABK H (p=0.038) HST 1RM (p=0.041) and in terms of fatigue (p=0.018) and lactate (p=0.012) within the aerobic power-capacity test was presented in HIGH relative to LOW and MED. Conclusions: 120 g/h CHO intake during a mountain marathon might limit neuromuscular fatigue and improve recovery of high intensity run capacity 24 h after a physiologically challenging event when compared to 90 g/h and 60 g/h. Keywords: resistance; carbohydrates; fatigue; recovery; gut training; performance; gastrointestinal discomfort; absorption Nutrients 2020,12, 2094; doi:10.3390/nu12072094 www.mdpi.com/journal/nutrients Nutrients 2020,12, 2094 2 of 17 1. Introduction Participation in ultra-endurance mountain race events (>4 h) has increased in recent years [ 1 ]. The different distances run by participants range from mountain marathons (42,195 m) to multistage ultra-marathons (up to 350 km), with an accumulative altitude gain of 24,000 m during the most extreme events [ 2 ]. In addition, mountain athletes are exposed to different environmental conditions, such as irregular terrains with a variety of geographical and topographic characteristics, climatic conditions, altitude exposure and temperature fluctuations [ 2 – 4 ]. This results in extreme physiological demands which may cause, among other things, negative energy balance, dehydration, decrease in blood glucose levels, muscle and hepatic glycogen depletion, exercise induced muscle damage (EIMD) and inflammation [ 2 – 5 ], and therefore might induce high levels of neuromuscular fatigue [ 2 , 6 ]. In this sense, the fatigue experienced by the runner could be quantified by monitoring the internal exercise load (determined by intensity (measured or perceived) × time) endured by an athlete during exercise [ 7 , 8 ] and by looking for different strategies that allow it to be delayed [7]. Carbohydrate (CHO) intake during endurance exercise has been shown to delay neuromuscular fatigue and improve exercise capacity and work rate significantly in a dose–response relationship [ 9 , 10 ]. In this sense, although the current recommendations in events lasting more than 2.5 h include the 90 g /h CHO intake [ 11 , 12 ], a gut training avoids gastrointestinal discomfort that it could facilitate the intake of greater amounts of CHO to the recommendations [ 13 ]. In this sense, although >90 g/h CHO intake may have controversial results [ 9 , 14 ], Pfeiffer et al. showed that athletes who consumed 120 g/h were among the fastest during two ultraendurance events, indicating a delay in the onset of fatigue [ 10 ]. In addition a study carried out by our lab has recently demonstrated that higher CHO intake (120 g/h) than recommended could be a determining factor in the internal exercise load response and could limit exercise-induced muscle damage (EIMD) in elite trail runners 24 h after completing a mountain marathon, suggesting that recovery time after such an endurance event could be shortened by a suitable CHO intake during exercise [ 15 ]. In addition, it is well known that CHO substrate availability plays a central role in peripheral fatigue, but also within the central nervous system and, thus, in central fatigue [ 16 ]. Stewart et al. [ 17 ] showed that glucose intake (1.23 ± 0.11 g/kg body mass) during exercise with a 15-min frequency in 15 untrained participants improved muscle function due to attenuated disturbances in the membrane excitability, suggesting that peripheral fatigue could be delayed by CHO intake during exercise. Peripheral fatigue is understood as the failure of local mechanisms in the muscle and, therefore, the decrease in the contraction and relaxation function that are related with the energetic status of the muscle cell [ 18 , 19 ]. Among these mechanisms, the potential action in the sarcolemma, the excitation–contraction (E-C) coupling and the interaction between actin and myosin proteins that allowed the muscle to contract and relax [ 20 ]. In this sense, the link between localized intramyofibrillar glycogen content and muscle function, mediated by the Ca 2+ release from the sarcoplasmic reticulum (SR), has been established in the literature [ 21 , 22 ]. A study conducted on elite cross-country skiers showed a correlation between the reduction in skeletal muscle glycogen and release rate of Ca 2+ after completing 1 h of maximum effort [ 22 ]. Moreover, significant differences were found in glycogen content and Ca 2+ release after 4 h post-exercise between the group that consumed CHO (1 g/kg body weight/h) and the placebo one (water), suggesting that CHO intake during exercise might take on a major role in improving short term glycogen replenishment and muscle function [22]. Additionally, both shortand long-term recovery periods following exercise play an important role in ensuring a suitable return to physiological and metabolic homeostasis in athletes. When the neuromuscular function has been affected, replenishment of glycogen stores is required to restore muscle function [ 23 , 24 ]. After exhaustive exercise and glycogen depletion, 36–48 h of high CHO diet (>7–9 g/kg body mass-BM) is needed to compensate muscle glycogen content [ 25 ]. However, when EIMD takes place, replenishment capacity is highly compromised, delaying this process by up to 10 days [ 26 ]. Moreover, the recovery kinetics of the neuromuscular function were studied following an ultra-marathon race, showing interesting results regarding peripheral and central fatigue [ 3 ]. Nutrients 2020,12, 2094 3 of 17 While maximal voluntary activation and low frequency fatigue were recovered within 2 days, plasmatic Ca 2+ was still reduced at this point and muscle damage biomarkers returned to the baseline on day 5 [ 3 ]. In general, authors found that the majority of central and peripheral function indexes were recovered within 9 days [3], although it is generally accepted that central fatigue persists longer than peripheral fatigue [ 27 ]. Furthermore and with regard to glycogen replenishment and Ca 2+ release from the SR, Ortenblad et al. [ 22 ] found that after ingesting a high CHO diet within 22 h post-exercise, both glycogen content and the Ca2+release rate returned to baseline levels. Optimal nutritional protocolstoensurerecoveryfollowingexercise havebeenextensivelydocumented in the literature regarding glycogen resynthesis, protein synthesis and rehydration [ 25 , 28 – 30 ]. Although few studies have been conducted with the ingestion of protein and carbohydrates during the exercise with the aim of improving recovery [ 31 – 33 ], ingested CHO quantities were lower than currently recommended [ 11 ]. To the best of the authors’ knowledge, no research has been conducted using only CHO in high doses during exercise to optimize post-exercise recovery, which could prove very interesting when it comes to improving training capacity and performance in multi-stage competitions. As CHO intake represents a possible methodology not only to help improve performance during exercise, but also to improve recovery through different mechanisms such as limiting EIMD, decreasing internal exercise load and neuromuscular fatigue, maintaining suitable levels of blood glucose and sparing muscle and hepatic glycogen, the purpose of this research was to analyze the effects of a high CHO (120 g/h) intake during a mountain marathon on 24 h recovery in elite runners in terms of neuromuscular function and high intensity run capacity in elite male ultra-endurance athletes. The main hypothesis of this research was to ascertain whether 120 g /h CHO intake could reduce neuromuscular fatigue by internal exercise load and improve long term recovery compared to current recommendations for ultra-endurance events (90 g/h) [ 34 , 35 ], and regular CHO intake on the part of athletes during such races (60 g/h) [36]. 2. Materials and Methods 2.1. Participants and Experimental Protocol The current research was put together as a randomized trial with the aim of examining the effects of 120 g/h of CHO intake during a trail marathon race on internal exercise load during exercise and muscle recovery 24 h following exercise. The 120 g/h of CHO supplementation was compared to international references for ultra-endurance events (90 g/h) [ 34 , 35 ], and regular CHO intake of athletes during such races (60 g/h) [ 36 ]. The use of 120 g/h was determined because previous studies have shown that after a training of gut tract it is possible to tolerate this amount [ 10 , 37 ] and because 120 g/h of CHO during an ultraendurance race has shown a lower internal exercise load and lower EIMD [ 15 ]. Thirty-one elite male athletes were assessed for eligibility in this study (including 2 trail skyrunner world champions from the International Trail Running Association (ITRA) and the International Association of Athletics Federations (IAAF)). After removing 5 athletes because they failed to meet the inclusion criteria (>5 years’ experience in ultra-endurance training, having undertaken personalized training of the gut tract to enhance CHO absorption capacity and tolerance and not taken any drugs or performance supplements [ 38 ] to avoid any possible interference in the recovery process during the 1-week period prior to the race), 26 athletes were involved in the randomization process and went on to take part in the mountain marathon race. These 26 athletes were inspected by a medical doctor prior to the study in order to check they had no injury or disease. None of the runners were suffering from any disease, and none of them were taking any medication. The runners were randomized into three different groups by an independent statistician via a randomization sequence using SPSS software as follows: (I) group that was supplemented with 60 g/h of CHO (LOW; n=8; BMI: 23.0 ± 2.9 kg/m 2 ), (II) group that was supplemented with 90 g/h of CHO (MED; n=9; BMI: 22.4 ± 2.6 kg/m 2 ) and (III) group that was supplemented with 120 g/h of CHO (HIGH; n=9; BMI: 22.1 ± 3.0 kg/m 2 ). The runners were instructed that as soon as they felt any damage and/or Nutrients 2020,12, 2094 4 of 17 gastrointestinal distress which might compromise their athletic performance, they should withdraw from the marathon to avoid interference in the results. As a result, 6 athletes withdrew during the race (3 with gastrointestinal discomfort–flatulence and/or reflux and 3 with injury). The remaining athletes finished the marathon without experiencing any injuries and/or gastrointestinal difficulties. Consequently, the sample included in the current research comprised 20 athletes, including 2 world champions (6 runners for the LOW, 7 runners for the MED and 7 runners for the HIGH) [15]. All participants ingested CHO during the race using the same gels made for this research at the University of Valladolid Physiology Laboratory (Soria) by an experienced pharmacist using a gel packaging machine. The gels contained 30 g of maltodextrin (glucose) and fructose (ratio 2:1) to increase exogenous CHO oxidation during exercise [ 39 ]. The athletes carried previously configured GPS alarms to notify them that they should intake CHO gels every 15, 20 and 30 min during the mountain marathon race, with runners needing to consume 1/4, 1/3 or 1/2 of the total g of CHO per hour according to their group (HIGH, MED, LOW, respectively) (Figure 1). Although athletes drank water ad libitum during the race, the participants ingested no food other than the gels. The athletes were instructed to extract the maximum content of the gels so that the residual amount was minimal. Likewise, all the athletes who finished the race confirmed through a questionnaire that all the gels had been taken at the time and in the manner previously indicated. Nutrients 2020, 12, x FOR PEER REVIEW 4 of 17 remaining athletes finished the marathon without experiencing any injuries and/or gastrointestinal difficulties. Consequently, the sample included in the current research comprised 20 athletes, including 2 world champions (6 runners for the LOW, 7 runners for the MED and 7 runners for the HIGH) [15]. All participants ingested CHO during the race using the same gels made for this research at the University of Valladolid Physiology Laboratory (Soria) by an experienced pharmacist using a gel packaging machine. The gels contained 30 g of maltodextrin (glucose) and fructose (ratio 2:1) to increase exogenous CHO oxidation during exercise [39]. The athletes carried previously configured GPS alarms to notify them that they should intake CHO gels every 15, 20 and 30 min during the mountain marathon race, with runners needing to consume 1/4, 1/3 or 1/2 of the total g of CHO per hour according to their group (HIGH, MED, LOW, respectively) (Figure 1). Although athletes drank water ad libitum during the race, the participants ingested no food other than the gels. The athletes were instructed to extract the maximum content of the gels so that the residual amount was minimal. Likewise, all the athletes who finished the race confirmed through a questionnaire that all the gels had been taken at the time and in the manner previously indicated. Figure 1. Experimental design of study including preand posttests and race fueling protocol and timing. CHO: Carbohydrate. The “marathon of Oiartzun” is a mountain marathon race (42.195 km) which began at 9:00 am in Oiartzun (Guipúzcoa-Spain) (10 °C, 60% humidity and 10 km/h wind speed) and was controlled by official chronometers. The race consisted of an entry and exit to a circuit that the runners had to complete 3 times. The height accumulated gradient of the mountain marathon race was 3980.80 m (1990.40 m positive and negative, respectively) (Figure 1), while the maximum and minimum height was 638.20 m and 3.80 m, respectively. During the race, the heat rate (HR) was documented using a HR monitor, and the mean HR (HRmean) and maximum HR (HRmax) during the event were also recorded. Prior to commencement of the study, all athletes received information about the purpose of it and associated risks and benefits. Subsequently, everyone signed an informed consent. The study was designed according to the guidelines laid out in the Declaration of Helsinki and approved by the Human Ethics Committee at the Valladolid Health Area, Valladolid, Spain (PI 19-1345). 2.2. Dietary Assessment Figure 1. Experimental design of study including preand posttests and race fueling protocol and timing. CHO: Carbohydrate. The “marathon of Oiartzun” is a mountain marathon race (42.195 km) which began at 9:00 am in Oiartzun (Guip ú zcoa-Spain) (10 ◦ C, 60% humidity and 10 km/h wind speed) and was controlled by official chronometers. The race consisted of an entry and exit to a circuit that the runners had to complete 3 times. The height accumulated gradient of the mountain marathon race was 3980.80 m (1990.40 m positive and negative, respectively) (Figure 1), while the maximum and minimum height was 638.20 m and 3.80 m, respectively. During the race, the heat rate (HR) was documented using a HR monitor, and the mean HR (HRmean) and maximum HR (HRmax) during the event were also recorded. Prior to commencement of the study, all athletes received information about the purpose of it and associated risks and benefits. Subsequently, everyone signed an informed consent. The study was designed according to the guidelines laid out in the Declaration of Helsinki and approved by the Human Ethics Committee at the Valladolid Health Area, Valladolid, Spain (PI 19-1345). Nutrients 2020,12, 2094 5 of 17 2.2. Dietary Assessment By way of an inclusion criterion, it was stated that all athletes should have undertaken gut training which involved ensuring >90 g/h CHO intakes >2 days/week over the 4 weeks prior to the race [ 13 , 40 ]. Regarding diets and menus during the research period, all were put together individually for each athlete in accordance with international recommendations for ultra-endurance sports [ 34 , 35 ] by the same certified sport dietitian-nutritionist. The athletes obtained a personalized diet for a 48-h period prior to T1 and marathon race day with 9 g CHO/kg BM/day, 1.5 g protein/kg BM/day and 0.5 g fat/kg BM/day to adjust their glycogen content. This diet comprised, among other foods, vegetables, olive oil and fish, although it did not contain any fatty meat or butter [ 41 ]. Moreover, runners had breakfast (2 g CHO/kg BM) at the ElikaEsport Health Center 3 h prior to commencement of the mountain marathon race. This breakfast consisted of rice or paste, corn cereals with oat drink, cooked fruit and biscuits with jam, sweet quince or cheese. At the end of the marathon, each athlete ingested 1.2 g of CHO/kg BM with 0.3 g of whey isolate protein/kg BM in the recovery shakes. Within the next 24 h until T2, each runner consumed a suitable diet (9g CHO/kg BM, 1.5 g protein/kg BM and 0.5 g fat/kg BM) in order to replenish glycogen levels to almost 90–93% of previous muscle glycogen [25,42]. 2.3. Athletic Performance Test Runners attended the laboratory for an athletic performance test the week prior to the trail marathon race (T1) and 24 h after it (T2). The internal exercise load was estimated by training impulse (TRIMP) and athletic recovery was assessed using the Abalakov jump test (ABK), Drop jump test (DJ), Half Squat test (HST) and aerobic power-capacity test. The two test sessions were carried out at the ElikaEsport Health Center under standard conditions (temperature: 20 ◦ C and humidity: 55%) for both test sessions, and the tests were completed following a standardized 15-min warm-up. The warm-up involved 10 min of running with two 1-min speeding up (at 3 min and 5 min) and 5 min of injury prevention drills consisting of general movements, dynamic/static stretching and core stability. 2.3.1. Neuromuscular Function Abalakov jump test [ 43 ] and half squat [ 44 ] test were chosen to measure the neuromuscular function of leg extensor muscles in athletes and recreationally active men given that they can achieve this with a high degree of reliability. Abalakov jump test: Participants made 3 countermovement with 30-s breaks between jumps [ 45 ]. All runners had to start from an upright position and performed a knee flexion of 90 ◦ followed by an extension as fast as possible to reach the highest possible jump height. An optical (infrared) data collection was used (Optojump Next Microgate, Bolzano, Italy) to measure jump time (ABK JT ), and Abalakov jump height (ABK H ) was calculated [ 46 ]. The best of the three records was used for statistical analysis. Half Squat test: 5-min following Abalakov jump test, runners performed a 1-repetition maximum test (1RM) of half squat test (HST 1-RM ) using a Multipower machine (BH Max Rack LD400, Vitoria, Spain). After 5 min rest from HST 1-RM the runners performed three repetitions at maximal speed for a load of 70% of their 1-RM in this half-squad exercise, with 1-min rest between repetitions to determinate the concentric movement speed of half-squad test (HSTSpeed). During half squat test the athletes performed a knee flexion until the thigh was parallel to the ground (90 ◦ knee angle) and, following a command, moved the bar up as fast as possible, without their shoulder losing contact with the bar [ 47 ]. They then had to wait 3 s to remove the elastic component, after which they were given an external signal to perform a concentric extension of the lower limbs until reaching 180 ◦ at the highest Nutrients 2020,12, 2094 6 of 17 possible speed. The average concentric movement speed was measured using the PowerLiftversion 4.2.4 app for Iphone [48]. 2.3.2. High Intensity Run Capacity Aerobic power-capacity test: Runners performed a maximum aerobic power test on an ergometric tape (Tunturi Pure 6.1, Almere, The Netherlands). The protocol used involved maintaining a constant speed of 20 km/h, with a slope of 1%—this being the maximum possible time until exhaustion [ 46 ]. During the test, the maximum HR (HRmax) was recorded using HR monitors (Polar V800, Kempele, Finland) taking as reference the highest HR achieved by the athletes during the test. Likewise, at the end of this test a blood sample was obtained from the earlobe to detect blood lactate using a Lactate Scout analyzer (SensLab GmbH, Leipzig, Germany), and at the end of the test athletes also indicated the rate of perceived exertion (RPE) based on the Borg scale [49]. 2.4. Internal Exercise Load During the mountain marathon racing, the heat rate (HR) of all runners was monitored continuously using the same HR monitors as used in the aerobic power-capacity test. Likewise, during the race the HR mean and HRmax were recorded, and internal exercise load was also calculated using individualized training impulse (TRIMP) [ 49 , 50 ]. TRIMP was obtained as the product of trail marathon duration and intensity multiplied by a nonlinear metabolic adjustment factor. For its part, the trail marathon intensity was calculated as: ∆HR =(HRmean −resting HR)/(HRmax −resting HR). 2.5. Anthropometry and Body Composition All anthropometric and measurements were administered by an internationally certified level 3 anthropometrist. The anthropometrist administered measurements at T1 in accordance with the International Society for the Advancement of Kineanthrometry (ISAK). All measurements were taken in duplicate, with the exception of those that exceeded 5% difference between each other, which required a third measurement. BM (kg) and height (cm) were measured using a scale (Mod. 220; SECA Medical, Bradford, MA, USA), with 0.1 kg and 1 mm precision respectively. Body Mass Index (BMI) was considered in accordance with the equation: BM/height 2 (kg/m 2 ), while triceps, subscapular, suprailiac, abdominal, front thigh and medial calf skinfolds were examined using a skinfold caliber (Harpenden Skinfold Caliber, British Indicators Ltd., London, UK), with 0.2 mm precision. The sum of these 6 skinfolds (mm) was then calculated. A Lufkin model W606PM measuring tape with 1 mm precision was used to measure the perimeters (relaxed arm, mid-thigh and calf) in cm. These girths were all corrected for the skinfold at the site using the following formula: (corrected girth =girth − ( π× skinfold thickness at the site)). Relaxed arm girth was corrected for triceps skinfold (CAG), mid-thigh girth corrected for front thigh skinfold (CTG), and calf girth was corrected for medial calf skinfold (CCG). Muscle mass (MM) was predicted using the Lee [51] equation for males and Caucasian athletes: MM =height ×(0.00744 ×CAG2+0.00088 ×CTG2+0.00441 ×CCG2)+2.4 −0.048 ×age +7.8. 2.6. Statistical Data Analyses Statistical analysis was completed by Statistical Package for the Social Sciences 24.0 (SPSS Inc., Chicago, IL, USA), with results being shown as mean and standard deviation. The significance level for all analyses was set at p<0.05. Although the data obtained presented a parametric distribution after using the Shapiro–Wilk test (n<50), non-parametric tests were performed because the sample in each of the study group was very small. The percentage changes of the physical test between T1 and T2 were considered as ∆ (%): ((T2 − T1)/T1) × 100. ∆ (%) of athletic recovery (Abalakov jump test, half-squad test and aerobic power-capacity test) was compared among 3 CHO intake groups using Kruskal–Wallis test with the Nutrients 2020,12, 2094 7 of 17 CHO intake groups as the fixed factor. A Mann Whitney utests test was completed for pairwise comparisons between groups. Similarly, differences between T1 and T2 in each athletic recovery test in each CHO intake group were assessed using a Wilcoxon signed rank test. 3. Results Table 1shows race time, age, body composition and anthropometric characteristics of subjects at T1 according to each study group. No significant differences were observed for race time, age or anthropometric characteristics between groups (p>0.05). Table 1. Race time, age, anthropometric characteristics and body composition in low (LOW), medium (MED) and high (HIGH) groups at baseline (T1). Variables LOW MED HIGH p Race Time (min) 278.2 ±43.6 284.1 ±40.0 271.7 ±41.7 0.063 Age (years) 37.8 ±9.4 37.2 ±5.4 38.0 ±6.8 0.639 Height (cm) 175.6 ±10.3 172.3 ±7.0 174.2 ±3.5 0.361 Weight (kg) 71.8 ±10.3 66.6 ±10.1 67.4 ±11.1 0.607 BMI 23.3 ±2.9 22.4 ±2.6 22.1 ±3.0 0.747 P6S (mm) 58.8 ±21.5 55.4 ±21.6 43.7 ±21.6 0.467 Muscle Mass (kg) 29.8 ±4.7 28.4 ±5.1 30.4 ±3.2 0.412 Table 2shows the values obtained from the Abalakov and half-squat test at T1 and T2 in the three study groups. A significant decrease was noted in ABK JT and ABK H in LOW and MED (p<0.05), while the HIGH did not show any significant differences in these parameters between T1 and T2 (p>0.05). Table 2. Results of the Abalakov jump and half-squad test in low (LOW), medium (MED) and high (HIGH) groups at T1 and T2. Study Time LOW MED HIGH p ABKJT (s) T1 0.54 ±0.05 0.53 ±0.06 0.53 ±0.05 0.867 T2 0.51 ±0.05 * 0.50 ±0.04 * 0.53 ±0.04 0.867 ABKH(cm) T1 36.57 ±6.36 34.86 ±7.37 34.46 ±6.55 0.861 T2 32.42 ±6.52 * 31.06 ±4.97 * 34.47 ±4.78 0.584 HST1-RM (kg) T1 103.32 ± 35.67 109.07 ±33.62 97.17 ±8.60 0.991 T2 81.66 ±32.42 91.91 ±25.54 90.09 ±14.20 0.659 HSTSpeed (m/s) T1 0.65 ±0.06 0.63 ±0.10 0.57 ±0.14 0.728 T2 0.60 ±0.11 0.50 ±0.09 * 0.55 ±0.18 0.370 Data are indicated as mean ± standard deviation. p: Statistical differences among groups in each time point by Kruskal–Wallis test. * Significant differences (p<0.05) between time points (T1 vs. T2) within the same group as determined by Wilcoxon signed rank test. On the other hand, although there was a tendency towards a smaller loss in HST 1-RM in HST Speed in the HIGH (HST 1-RM : T1: 97.17 ± 8.60 vs. T2: 90.09 ± 14.20 Kg; HST Speed : T1: 0.57 ± 0.14 vs. T2: 0.55 ± 0.18 m/s) in terms of LOW (HST 1-RM : T1: 103.32 ± 35.67 vs. T2: 81.66 ± 32.42 Kg; HST Speed : T1: 0.65 ± 0.06 vs. T2: 0.60 ± 0.11 m/s) and MED (HST 1-RM : T1: 109.07 ± 33.62 vs. T2: 91.91 ± 25.54 Kg; HST Speed : T1: 0.63 ± 0.10 vs. T2: 0.50 ± 0.09 m/s), no significant differences were observed in the Nutrients 2020,12, 2094 8 of 17 group-by-time for these parameters (p>0.05). However, there were significant declines in HST Speed in MED between T1 and T2 (p<0.05). Table 3. Sets out the aerobic power-capacity test results of the three groups at T1 and T2. A significant decrease was shown in aerobic power-capacity test time in MED between T1 (104.0 ± 48.1 s) and T2 (87.9 ± 39.4 s) (p<0.05). Moreover, although there was a tendency for a decreased lactate in MED (T1: 5.80 ± 0.91 vs. T2: 4.79 ± 1.35 mmol/l; p<0.05)), only LOW evidenced a significant reduction in lactate between T1 (7.45 ± 1.42 mmol/l) and T2 (5.65 ± 1.27 mmol/l) (p<0.05). However, HR max showed significant declines both in LOW and MED between T1 and T2 (p<0.05). On the other hand, Borg showed a significant decrease in HIGH throughout the study (T1: 18.29 ± 0.76 vs. T2: 17.00 ± 1.00; p<0.05), and the Borg value in T2 was significantly less compared to LOW (18.83 ± 0.98) and MED (18.71 ±1.38) (p<0.05). Table 3. Results of the aerobic power-capacity test in low (LOW), medium (MED) and high (HIGH) groups before (T1) and after (T2) completing the competition. Study Time LOW MED HIGH p Time (s) T1 102.8 ±38.3 104.0 ±48.1 108.0 ±46.5 0.962 T2 89.8 ±37.1 87.9 ±39.4 * 110.1 ±48.4 0.537 Lactate (mmol/L) T1 7.45 ±1.42 5.80 ±0.91 6.79 ±2.30 0.200 T2 5.65 ±1.27 * 4.79 ±1.35 6.70 ±2.07 0.131 HR max (bpm) T1 184.8 ±14.2 186.0 ±11.0 179.6 ±9.0 0.791 T2 174.7 ±11.0 * 173.7 ±8.1 * 174.9 ±7.7 0.970 BORG T1 18.83 ±1.17 18.43 ±1.40 18.29 ±0.76 0.008 T2 18.83 ±0.98 &18.71 ±1.38 &17.00 ±1.00 * 0.028 Data are indicated as mean ± standard deviation. p: Statistical differences among groups in each time point by Kruskal–Wallis test. * Significant differences (p<0.05) between time points (T1 vs. T2) within the same group as determined by Wilcoxon signed rank. &Significant differences regarding HIGH group by Mann Whitney utest. Figure 2shows the TRIMP during the trail marathon, with a significant difference in TRIMP being evidenced between groups (p=0.017). Specifically, a significant higher TRIMP was observed in LOW (399.8 ±17.5) and MED (371.2 ±16.2) compared to HIGH (314.8 ±16.2). Figure 3displays the percentage of change of ABK and HST between T1 and T2 in the three study groups. Significant differences were observed among groups in ABK JT (p=0.038) and ABK H (p=0.038). In this sense, there were significant improvements (p<0.05) in ABK JT in the HIGH (0.53 ± 5.12%) compared to LOW ( − 5.90 ± 4.18%) and MED ( − 5.02 ± 4.22%). Likewise, there was a significant improvement (p<0.05) in ABK H in the HIGH (1.19 ± 8.05%) regarding LOW ( − 11.33 ± 8.00%) and MED ( − 9.66 ± 8.19%). Figure 4also shows significant percentage differences in HST 1-RM among groups between T1 and T2 (p=0.041). Specifically, a significant smaller decline was noted (p<0.05) in HST 1-RM in HIGH ( − 2.35 ± 7.23%) compared to LOW (15.30 ± 7.54%) and MED ( − 13.84 ± 9.74%) between T1 and T2, while HIGH ( − 4.19 ± 11.31%) evidenced a significant smaller decline (p<0.05) in HST Speed compared to MED (−20.06 ±14.75%) during the study. Nutrients 2020,12, 2094 9 of 17 Nutrients 2020, 12, x FOR PEER REVIEW 8 of 17 0.05). However, HR max showed significant declines both in LOW and MED between T1 and T2 (p < 0.05). On the other hand, Borg showed a significant decrease in HIGH throughout the study (T1: 18.29 ± 0.76 vs. T2: 17.00 ± 1.00; p<0.05), and the Borg value in T2 was significantly less compared to LOW (18.83 ± 0.98) and MED (18.71±1.38) (p < 0.05). Table 3. Results of the aerobic power-capacity test in low (LOW), medium (MED) and high (HIGH) groups before (T1) and after (T2) completing the competition. Study Time LO W MED HIGH p Time (s) T1 102.8 ± 38.3 104.0 ± 48.1 108.0 ± 46.5 0.962 T2 89.8 ± 37.1 87.9 ± 39.4* 110.1 ± 48.4 0.537 Lactate (mmol/L) T1 7.45 ± 1.42 5.80 ± 0.91 6.79 ± 2.30 0.200 T2 5.65 ± 1.27* 4.79 ± 1.35 6.70 ± 2.07 0.131 HR max (bpm) T1 184.8 ± 14.2 186.0 ± 11.0 179.6 ± 9.0 0.791 T2 174.7 ± 11.0* 173.7 ± 8.1* 174.9 ± 7.7 0.970 BORG T1 18.83 ± 1.17 18.43 ± 1.40 18.29 ± 0.76 0.008 T2 18.83 ± 0.98& 18.71 ± 1.38& 17.00 ± 1.00* 0.028 Data are indicated as mean ± standard deviation. p: Statistical differences among groups in each time point by Kruskal–Wallis test. * Significant differences (p < 0.05) between time points (T1 vs. T2) within the same group as determined by Wilcoxon signed rank. & Significant differences regarding HIGH group by Mann Whitney U test. Figure 2 shows the TRIMP during the trail marathon, with a significant difference in TRIMP being evidenced between groups (p = 0.017). Specifically, a significant higher TRIMP was observed in LOW (399.8 ± 17.5) and MED (371.2 ± 16.2) compared to HIGH (314.8 ± 16.2). Figure 2. Internal exercise load by training impulse (TRIMP) for each group during trail marathon. * Significant differences in terms of HIGH using Mann Whitney utest (p<0.05). Nutrients 2020, 12, x FOR PEER REVIEW 9 of 17 Figure 2. Internal exercise load by training impulse (TRIMP) for each group during trail marathon. * Significant differences in terms of HIGH using Mann Whitney u test (p < 0.05). Figure 3 displays the percentage of change of ABK and HST between T1 and T2 in the three study groups. Significant differences were observed among groups in ABKJT (p = 0.038) and ABKH (p = 0.038). In this sense, there were significant improvements (p < 0.05) in ABKJT in the HIGH (0.53 ± 5.12%) compared to LOW (−5.90 ± 4.18%) and MED (−5.02 ± 4.22%). Likewise, there was a significant improvement (p < 0.05) in ABKH in the HIGH (1.19 ± 8.05%) regarding LOW (−11.33 ± 8.00%) and MED (−9.66 ± 8.19%). Figure 4 also shows significant percentage differences in HST1-RM among groups between T1 and T2 (p = 0.041). Specifically, a significant smaller decline was noted (p < 0.05) in HST1RM in HIGH (−2.35 ± 7.23%) compared to LOW (15.30 ± 7.54%) and MED (−13.84 ± 9.74%) between T1 and T2, while HIGH (−4.19 ± 11.31%) evidenced a significant smaller decline (p < 0.05) in HSTSpeed compared to MED (−20.06 ± 14.75%) during the study. Figure 3. Percentage of changes of neuromuscular function using the Abalakov jump test and half squat test between T1 and T2. * Significant differences compared to HIGH using Mann Whitney u test (p < 0.05). Figure 4 shows significant differences in percentage change of time in aerobic power-capacity test (p = 0.018) between T1 and T2. Specifically, HIGH (1.28 ± 8.55%) showed a significantly better change in time in aerobic power-capacity test compared to LOW (−14.09 ± 14.98%) and MED (−14.87 ± 11.86%) between T1 and T2 (p < 0.05). Likewise, HIGH (1.69 ± 11.78%) displayed a significantly higher increase in lactate (p = 0.012) compared to LOW (−22.69 ± 9.38%) and MED (−13.94 ± 12.41%). Furthermore, although the percentage change in HIGH showed a tendency towards better values in Borg compared to LOW and MED, these differences were not significant (p = 0.066). Figure 3. Percentage of changes of neuromuscular function using the Abalakov jump test and half squat test between T1 and T2. * Significant differences compared to HIGH using Mann Whitney utest (p<0.05). Figure 4shows significant differences in percentage change of time in aerobic power-capacity test (p=0.018) between T1 and T2. 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