Abstract
nners (TRs) must carry an extra load of equipment, food (bars and gels) and liquids, to delay the anticipation of fatigue and dehydration during their competitions. Therefore, we aimed to evaluate how an extra load can influence the metabolic level. Thirteen well-trained trail runners performed a randomized crossover study (totaln= 39), completing three treadmill running sessions with a weighted vest of 0%, 5% and 10% of their body mass during a combined test (rectangular test + ramp test). In addition, biomarkers of oxygen metabolism, acid–base and electrolyte status pre-, during and post-test, as well as the rectangular from capillary blood of the finger and time to exhaustion, were analyzed. Repeated-measures ANOVA showed no significant difference between conditions for any of the analyzed biomarkers of blood gas. However, one-way ANOVA showed a significant difference in trial duration between conditions (p≤0.001). Tukey’s post hoc analysis observed a significant decrease in time to exhaustion in the weighted vest of 10% compared to 0% (p≤0.001) and 5% (p≤0.01) and 5% compared to 0% (p= 0.030). In addition, repeated-measures ANOVA detected a significant difference in pH in the group x time interaction (p= 0.035). Our results show that increasing the weighted vest (5% and
Tukey’s post hoc analysis observed a significant decrease in time to exhaustion in the weighted vest of 10% compared to 0% (p≤0.001) and 5% (p≤0.01) and 5% compared to 0% (p= 0.030). In addition, repeated-measures ANOVA detected a significant difference in pH in the group x time interaction (p= 0.035). Our results show that increasing the weighted vest (5% and 10%) anticipates fatigue in runners trained in TR. In addition, increasing the load decreased pH by a smaller magnitude at 10% compared to 0% and 5% at the end of the exercise protocol. Keywords:endurance exercise; physiology; metabolism; lactate; oxygen saturation; hemoglobin 1. Introduction Trail running (TR) is a discipline of sport that takes place in a natural environment such as the mountains and with minimal paved or asphalted roads (<20% of the total duration of the competition) [1]. Due to the increasing popularity of TR, there is a great variety of distances, as we can find races of 20 km (about 1.5 h of competition), 42 km (marathon distance) and long distances (>100 km), although these distances are never fixed and are always combined with large slopes (ascent/descent) [2]. In addition to facing long competition times, trail runners also have to endure rough terrain and adverse weather conditions (such as cold, heat, humidity and altitude) com- pared to other running disciplines (trail or road), which entails the need to carry a loaded backpack during the competition (safety equipment, nutrition and hydration) [3]. This extra load is justified, as over medium (~42 km) and long (>100 km) distances, a food intake protocol is needed, especially at the ultramarathon distance and especially with several stages, as this type of race has very high minimum food (≥2000 kcal·day −1 ) and fluid requirements (~12 L·day −1 ), which means that runners have to carry a backpack loaded with up to 15 kg (including tent). This extra load on TRs can lead to metabolic and kinematic imbalances, which can affect race pace and performance compared to an unloaded situation. In this regard, previ- ous studies have shown that an extra weight load (5–30% of
(~12 L·day −1 ), which means that runners have to carry a backpack loaded with up to 15 kg (including tent). This extra load on TRs can lead to metabolic and kinematic imbalances, which can affect race pace and performance compared to an unloaded situation. In this regard, previ- ous studies have shown that an extra weight load (5–30% of body mass (BM)) augments Sports2024,12, 229.
Sports2024,12, 229 2 of 17 (~5.5%) ground contact time, vertical oscillation (~16.3%) [4–6] and leg spring stiffness (~10.5%) [4,5,7]. On the other hand, Purdom et al. [8] evaluated fat oxidation and energy expenditure during an incremental test (60, 65, 70, 75 and 80% VO2MAX) with different loads (0%, 5% and 10% of BM) in recreational trail runners. This author observed that with a load of 10% BM, there was a decrease in fat oxidation at an intensity of 70, 75 and 80% VO2MAXin the rectangular test compared to a load of 0% BM. In addition, he also observed an increase in caloric expenditure with a load of 10% BM at an intensity of 65, 70, 75 and 80% VO2MAXcompared to a load of 0 and 5% BM [8]. On the other hand, Keren et al. [9] evaluated VO2without load and with load (20 kg) at speeds of 6.4, 7.2, 8.0, 9.6 and 11.2 km/h in active sportsmen students, finding an increase in VO2at the different speeds analyzed with a load of 20 kg on the back compared to without load. A study has recently been published that evaluated the effect of increasing the load with a weighted vest (0%, 5% and 10% of body mass (BM)) through an incremental test to exhaustion on metabolic, mechanical and performance variables in trained trail runners, where it was observed that increasing the load of 5% (−2.2%) and 10% (−6.1%) BM using a weighted vest produced a loss in performance (they took less time to finish the test) compared to 0% [10]. In addition, they also found that increasing the load of the weighted vest resulted in a loss of speed (5% =−2.2%; 10% =−6.1%) and an increase in absolute power (5% = 2.2%; 10% = 6.1%) at the end of the incremental test compared to 0%. However, in relation to metabolic markers, they found no significant changes in lactate (Lac) and oxygen saturation (sO2), but they found a trend in pH in the comparison between conditions. The authors of this article established that an extra load of 5% does not induce noticeable physiological
10% = 6.1%) at the end of the incremental test compared to 0%. However, in relation to metabolic markers, they found no significant changes in lactate (Lac) and oxygen saturation (sO2), but they found a trend in pH in the comparison between conditions. The authors of this article established that an extra load of 5% does not induce noticeable physiological or mechanical changes, but 10% does [10]. Therefore, it is known how an increased extra load affects metabolic and performance markers in trail runners, as these athletes usually carry safety equipment and nutrition. However, it is not known how increasing an extra load specifically affects markers of oxygen metabolism, acid–base status and electrolytes that may explain the recent metabolic and performance changes [10]. Therefore, the main objective of this study is to evaluate the acute effects of running with an extra load (0% vs. 5% vs. 10% of BM) in a rectangular test on biomarkers related to oxygen metabolism, acid–base status and electrolytes (gasometry) utilizing blood gas analysis. We hypothesized that running with an extra load of 5% and 10% BM significantly decreases time to exhaustion in a combined test, a decrease in oxygen saturation and pH, and an increase in lactate. The data in this paper are part of a project where, due to the density of the data collected, they have been published in several papers, with secondary data appearing in the current paper. 2. Materials and Methods 2.1. Study Design This study utilized a randomized, crossover experimental design. To allocate condi- tions, a software called Randomizer was employed to assign codes [11]. Well-trained trail runners participated and completed a combined test involving a rectangular test and a ramp test under three different conditions: 0% (control; 0% BM load), 5% (5% BM load) and 10% (10% BM load). Biomarkers of oxygen metabolism, acid–base status and electrolytes were examined using finger capillary blood gasometry before, during and after the exercise. 2.2. Participants The study involved thirteen men who were amateur trail runners. You can find the details about the athletes in Table. The criteria for inclusion were as follows:
load), 5% (5% BM load) and 10% (10% BM load). Biomarkers of oxygen metabolism, acid–base status and electrolytes were examined using finger capillary blood gasometry before, during and after the exercise. 2.2. Participants The study involved thirteen men who were amateur trail runners. You can find the details about the athletes in Table. The criteria for inclusion were as follows: age between 18 and 35 years, BMI of 19.0–25.5 kg·m −2 , a minimum of three years of experience in trail running and 6–12 h of training per week (at least 4 sessions per week). Participants were excluded if they (a) were smokers or regular alcohol consumers; (b) had metabolic, cardiorespiratory or digestive health issues; (c) had experienced an injury in the last six months; (d) had taken any supplements or medication in the previous two weeks; and (e) had abnormal values for any baseline health blood test parameter. The sample size
Sports2024,12, 229 3 of 17 was determined using G*POWER 3.1.9.7 software (University of Düsseldorf, Düsseldorf, Germany). The setup used for this purpose was: F-ANOVA test: repeated measures, within-between interaction; A priori. Effect size f = 0.5;αerror prob = 0.05; power (1-β error prob = 0.80). The outcome indicated an appropriate total sample size of 12 subjects. The eligible participants provided informed consent before participating in the study. This study adhered to the guidelines of the Declaration of Helsinki on Human Research [12] and was approved by the Ethics Committee of the university (CE012104). All the participants successfully completed the study. Table 1.General characteristics of TR runners. Mean (standard deviation (SD)). Age (years) 28.0 (8.7) Body mass (kg) 62.5 (3.8) Height (cm) 173.3 (0.5) Distance/week (km) 58.8 (2.5) Elevation gain/week (m) 1662.5 (110.9) Fat mass (%) 9.3 (0.7) 2.3. Procedures The TR runners visited the laboratory five times at a minimum interval of 6 days. On the first visit, participants were informed about the procedures and tests to be performed during the study, and a medical examination was performed to check their health status. In addition, body composition was assessed by anthropometry. Participants were informed that they should follow a set diet (by a nutritionist) at all test visits and that they should not train in the previous 24 h. At the second visit, familiarization of the combined test (rectangular test + ramp test) was performed with a random load (0, 5 or 10% BM). On visits 3, 4 and 5, a combined test (rectangular test + ramp test) with the different loads (0, 5 and 10% BM) was performed in random order. The mean of the 5% condition was 3.12 kg and the mean of the 10% condition was 6.25 kg. All participants completed the study (totaln= 39). In the 24 h prior, no training could be performed, and in the 72 h prior, only low–moderate-intensity training could be performed. On the days before visits 3, 4 and 5, participants consumed a standardized diet consisting of 0.9 g/BM fat, 1.5 g/BM protein and 9.0 g/BM carbohydrate. In addition, athletes were
kg. All participants completed the study (totaln= 39). In the 24 h prior, no training could be performed, and in the 72 h prior, only low–moderate-intensity training could be performed. On the days before visits 3, 4 and 5, participants consumed a standardized diet consisting of 0.9 g/BM fat, 1.5 g/BM protein and 9.0 g/BM carbohydrate. In addition, athletes were instructed to eat a standardized breakfast 2 h before the tests, consisting of 0.43 g/BM protein, 1.3 g/BM carbohydrate and 0.57 g/BM fat. The previous day’s meals and pre-test breakfasts were prepared by a sports nutritionist and sent to participants 2 weeks before the start of the study. 2.4. Tests 2.4.1. Medical Exam The health assessment included a review of the participant’s medical history, a resting electrocardiogram and an examination by a medical doctor consisting of auscultation and measuring blood pressure to ensure the participants’ eligibility for the study based on their health. 2.4.2. Blood Samples A certified nurse performed the extraction of venous blood, obtaining one 3 mL tube of ethylenediaminetetraacetic acid (EDTA) for hemogram and another 3.5 mL tube with polyethene terephthalate (PET) for health analysis. An automated Cell-Dyn 3700 analyzer (Abbott Diagnostics, Chicago, IL, USA) was used to conduct a red blood cell count, with internal (Cell-Dyn 22) and external (Program of Excellence for Medical Laboratories- PEML) controls being utilized. The analyzer estimated values of erythrocytes, hemoglobin, hematocrit and hematimetric indexes. 2.4.3. Anthropometry A researcher certified at ISAK Level 1 conducted the anthropometric measurements (FJMN). A digital scale with a stadiometer for clinical use (SECA 780; Vogel & Halke GmbH
Sports2024,12, 229 4 of 17 & Co., Hamburg, Germany) was used to measure height and body weight. Skinfold thick- ness was assessed with Holtain Skinfold Calipers (Holtain, Ltd., Crymych Pembrokeshire, UK) in adherence to the guidelines of the International Society for the Advancement of Ki- nanthropometry [13]. Body fat percentage was determined using the Faulkner equation [14], and muscle mass percentage was calculated using the modified Matiegka equation [15]. The total of the eight skinfolds (triceps, subscapular, bicep, iliac crest, supraspinal, abdominal, thigh and calf) was also computed. 2.4.4. Familiarization and Incremental Test Protocol A combined test (rectangular test + ramp test) was performed as a two-phase protocol on a treadmill (Technogym Excite Med. Cesena, Italy). This combined method was used to assess ventilatory thresholds 1 and 2 (VT1 and VT2) with a step phase, followed by a ramp phase to assess peak value [16–18]. Step phase started at 5 km/h and velocity increased by steps of 1 km/h every 2 min. This first phase ended when RER reached a value of 1.00 for more than 30s (25% of the total step time) in the same step (POST1). At this point, athletes were asked to indicate their effort perception on a modified Borg Scale (RPE) from 1 to 10 [19]. Participants then proceeded to rest for 5 min in standing position. The objective of this resting period was to ensure the maximality of the second phase by reducing fatigue associated with the first one [20]. Second phase started at final first-phase velocity and increased 1.5 km/h each min as a ramp test (0.15 km/h every 3 s), ending at exhaustion (POST2). Athletes again indicated RPE at this point. 2.4.5. Blood Gas Analysis (ABL-90) The levels of oxygen metabolism, acid–base status and electrolyte biomarkers were assessed by analyzing arterialized capillary blood from the fingertip while at rest (PRE), at the conclusion of the initial phase (POST1) and after the exercise protocol (POST2). Hematocrit (Hct), hemoglobin (Hb), O2partial pressure (pO2), carbon dioxide (pCO2), O2 pressure (sO2), oxyhemoglobin (O2Hb), carboxy-hemoglobin (COHb), deoxyhemoglobin (RHb), methemoglobin (MetHb), total blood O2concentration (tO2), total blood carbon dioxide
and electrolyte biomarkers were assessed by analyzing arterialized capillary blood from the fingertip while at rest (PRE), at the conclusion of the initial phase (POST1) and after the exercise protocol (POST2). Hematocrit (Hct), hemoglobin (Hb), O2partial pressure (pO2), carbon dioxide (pCO2), O2 pressure (sO2), oxyhemoglobin (O2Hb), carboxy-hemoglobin (COHb), deoxyhemoglobin (RHb), methemoglobin (MetHb), total blood O2concentration (tO2), total blood carbon dioxide concentration (tCO2), O2partial pressure at 50% oxygen saturation (p50), non- oxygenated blood fraction (Shunt) and the difference between the alveolar concentration (A) of O2and the arterial (a) concentration of O2(AaDpO2) were all determined. The ABL 90 FLEX blood gas analyzer (Radiometer Medical ApS, Copenhagen, Denmark) was utilized to measure these parameters and underwent calibration at hourly intervals throughout the day using internal reference standards. Previous research has indicated that the ABL90 FLEX provides accurate results [21]. Plastic capillary tubes were pre-heparinized with electrolytically balanced solid heparin, significantly reducing clotting risk and ensuring unbiased and reliable electrolyte results. 2.4.6. Statistical Analysis The statistical analysis was conducted using IBM Social Sciences software (SPSS, v.21.0, Chicago, IL, USA). Mean±SD were used to present the data. The Levene and Shapiro–Wilk tests were employed to check the homogeneity and normality of the data, respectively. A two-way repeated-measures ANOVA was used to analyze each gasometry biomarker, with factors including time (PRE vs. POST1 vs. POST2) and condition (0% vs. 5% vs. 10% BM). A one-way ANOVA was performed for the trial duration. In the case of significance in the ANOVA models, Tukey’s post hoc analysis was carried out. Partial eta squared (ηp 2 ) was also calculated as an effect size for time, condition and time×condition interaction of all variables in the ANOVA analysis. The thresholds for partial eta squared were applied as follows: <0.01, irrelevant;≥0.01, small;≥0.059, moderate;≥0.138, large [22]. The significance level was set atp≤0.05. Pearson’s correlation (r) was used to evaluate the correlations between the parameters.
Sports2024,12, 229 5 of 17 3. Results After performing the two-way repeated-measures ANOVA, no significant difference was observed in the condition x time interaction for biomarkers of oxygen metabolism (Table; ??and Figure), but a trend was observed in the MetHb ( p= 0.064;ηp 2 = 0.166). On the other hand, when analyzing the differences in time to exhaustion between the three conditions during the combined test, one-way ANOVA detected a condition main effect (p≤0.001;ηp 2 = 0.641). Tukey’s post hoc analysis showed a significant difference between 0% and 5% (0.029), between 0% and 10% (p≤0.001) and between 5% and 10% (p= 0.003). Table 2.Changes in biomarkers of oxygen metabolism in capillary blood of the finger in pre, post1 and post2 incremental test. Values are mean (SD). 0% 5% 10% Time Condition C ×T Hematocrit (%) (HCT) Pre 50.4 (1.40) 50.5 (1.83) 50.2 (3.12) p= 0.261 p= 0.020 p= 0.712 Post1 51.3 (3.12) 50.2 (2.18) 50.5 (2.46) Post2 51.0 (2.30) 50.3 (1.92) 51.2 (2.80) ηp 2 0.106 0.279 0.051 Hemoglobin (g/dL) (Hb) Pre 16.7 (0.74) 16.5 (0.58) 16.4 (1.03) p= 0.261 p= 0.020 p= 0.825 Post1 16.8 (0.94) 16.4 (0.71) 16.5 (0.80) Post2 16.9 (0.99) 16.4 (0.64) 16.7 (0.92) ηp 2 0.106 0.279 0.030 Oxyhemoglobin (%) (O2Hb) Pre 91.8 (2.67) 91.6 (3.01) 92.1 (1.56) p≤0.001 p= 0.596 p= 0.814 Post1 94.3 (1.09) 94.1 (1.05) 94.0 (1.30) Post2 92.5 (1.25) 92.7 (1.47) 93.1 (1.58) ηp 2 0.507 0.042 0.032 Carboxy-hemoglobin (%) (COHb) Pre 0.577 (0.28) 0.593 (0.27) 0.569 (0.28) p≤0.001 p= 0.315 p= 0.505 Post1 0.377 (0.25) 0.400 (0.16) 0.454 (0.25) Post2 0.362 (0.17) 0.393 (0.16) 0.392 (0.17) ηp 2 0.519 0.092 0.066 Deoxyhemoglobin (%) (RHb) Pre 6.81 (2.68) 6.97 (2.96) 6.42 (1.53) p≤0.001 p= 0.496 p= 0.826 Post1 4.53 (1.07) 4.67 (0.99) 4.78 (1.25) Post2 6.26 (1.23) 6.00 (1.39) 5.62 (1.54) ηp 2 0.463 0.057 0.030 Methemoglobin (%) (MetHb) Pre 0.792 (0.80) 0.800 (0.23) 0.869 (0.31) p= 0.003 p= 0.487 p= 0.064 Post1 0.823 (0.25) 0.857 (0.29) 0.823 (0.31) Post2 0.854 (0.22) 0.893 (0.25) 0.900 (0.33) ηp 2 0.378 0.058 0.166 Oxygen saturation (%) (sO2) Pre 93.1 (2.70) 92.9 (3.02) 93.5
(0.99) 4.78 (1.25) Post2 6.26 (1.23) 6.00 (1.39) 5.62 (1.54) ηp 2 0.463 0.057 0.030 Methemoglobin (%) (MetHb) Pre 0.792 (0.80) 0.800 (0.23) 0.869 (0.31) p= 0.003 p= 0.487 p= 0.064 Post1 0.823 (0.25) 0.857 (0.29) 0.823 (0.31) Post2 0.854 (0.22) 0.893 (0.25) 0.900 (0.33) ηp 2 0.378 0.058 0.166 Oxygen saturation (%) (sO2) Pre 93.1 (2.70) 92.9 (3.02) 93.5 (1.57) p≤0.001 p= 0.655 p= 0.825 Post1 95.4 (1.10) 95.3 (1.02) 95.1 (1.41) Post2 93.6 (1.24) 93.9 (1.41) 94.2 (1.65) ηp 2 0.460 0.035 0.030 Oxygen partial pressure (mmHg) (pO2) Pre 70.0 (6.57) 68.8 (9.36) 70.7 (5.73) p≤0.001 p= 0.678 p= 1.000 Post1 81.7 (5.82) 82.2 (6.95) 82.9 (7.35) Post2 81.1 (6.74) 81.1 (9.67) 81.7 (5.52) ηp 2 0.840 0.032 0.001 Carbon dioxide partial pressure (mmHg) (pCO2) Pre 43.0 (3.63) 42.9 (4.51) 43.0 (2.73) p≤0.001 p= 0.964 p= 0.704 Post1 40.1 (2.56) 40.5 (3.27) 40.8 (3.05) Post2 39.8 (2.86) 38.9 (4.68) 39.5 (3.62) ηp 2 0.552 0.003 0.043 Total blood oxygen concentration (mmol/L) (tO2) Pre 9.62 (0.57) 9.46 (0.51) 9.48 (0.64) p= 0.007 p= 0.007 p= 0.752 Post1 9.92 (0.63) 9.68 (0.50) 9.72 (0.54) Post2 9.83 (0.58) 9.56 (0.39) 9.76 (0.57) ηp 2 0.335 0.341 0.038 Total blood carbon dioxide concentration (mmol/L) (tCO2) Pre 26.0 (5.62) 27.9 (2.63) 28.1 (1.77) p≤0.001 p= 0.214 p= 0.693 Post1 21.8 (4.22) 22.9 (2.64) 23.5 (1.49) Post2 17.2 (2.84) 18.0 (2.93) 19.0 (1.91) ηp 2 0.977 0.143 0.053 Oxygen partial pressure at 50% oxygen saturation (mmHg) (p50) Pre 27.2 (2.51) 26.4 (2.49) 27.1 (2.27) p≤0.001 p= 0.773 p= 0.136 Post1 27.6 (2.96) 28.1 (2.56) 28.7 (2.16) Post2 31.7 (1.82) 31.0 (3.40) 30.3 (2.80) ηp 2 0.639 0.021 0.133 Relative physiological Shunt (%) (Shunt) Pre 17.1 (5.80) 17.6 (7.15) 16.0 (3.92) p≤0.001 p= 0.491 p= 0.987 Post1 9.91 (3.07) 9.66 (2.66) 9.62 (4.26) Post2 13.6 (4.32) 13.0 (4.42) 12.0 (3.66) ηp 2 0.663 0.058 0.007 Alveolar–arterial gradient (mmHg) (AaDpO2) Pre 30.9 (4.98) 32.3 (8.08) 30.0 (4.80) p≤0.001 p= 0.531 p= 0.980 Post1 22.6 (6.01) 21.5 (5.39) 20.3 (6.55) Post2 23.5 (5.90) 24.3 (6.65) 23.0 (5.35) ηp 2 0.705 0.051 0.009
Description
The study investigates the effects of weighted vests on performance and gasometry biomarkers in trail runners.