1. Introduction
Trail running (TR) races are characterized by courses that mostly cover natural ground (at most 25% road), and do not require orienteering skills for the runners. This combination of unique characteristics has contributed to a remarkable growth in both the volume of participants and the professionalization of TR as a sport [
1,
2]. Furthermore, TR includes a wide variety of modalities. These go from shorter races such as vertical kilometer (1000m of elevation gain without exceeding 5km length) to mountain ultra-marathons (longer than marathon) [
3].
Metabolic requirements and performance factors for TR have been proven different from road running [
4,
5,
6,
7]. One of the main reasons for these differences is the different slopes that are part of the courses, and that produce biomechanical, neuromuscular and metabolic changes within running [
8]. Although irregular terrain generates irregular running patterns [
9], during uphill running (UR) athletes tend to take smaller steps with greater ground contact time and usually stepping with the forefoot [
8]. On the other hand, athletes tend to take greater steps with smaller ground contact times while stepping with the rear foot while downhill running (DR) [
8]. The need to create movement during UR versus the need to brake during DR also results in neuromuscular differences [
10]. While UR relies more on concentric muscle actions, DR requires repeated eccentric muscle actions [
10]. The nature of these muscle contractions also leads to greater muscle damage as well as lower energy expenditure during DR [
8,
11,
12,
13,
14].
TR athlete’s performance relies on different factors. Aerobic capacity, expressed as high VO
2max, and well-optimized lactate thresholds, has been described as an important characteristic [
6,
15,
16]. Low body fat mass has also been shown relevant to TR performance [
17].
As an endurance sport, TR metabolic demands usually require nutritional as well as water intake, especially during longer races [
18]. In fact, many participants choose to self-carry provisioning, which becomes an additional load. This extra load can be considered another particular characteristic of TR, and the effect it can have on athletes needs to be understood. This overload characteristic presents a disadvantage for athletes and coaches in shaping training strategies.
Resisted running has been widely studied as a training method for developing speed, change of direction, and other neuromuscular actions. Sleds, parachutes, loaded running (LR) with vests and other devices have been used for this purpose [
19,
20,
21,
22]. When sprinting with a vest, higher loads seem to limit maximal speed and flight time while increasing contact time [
23]. Similar results have been obtained for submaximal velocities with an extra load [
24]. Shorter flight time and steps, and greater ground contact time were again characteristics associated with running with heavier loads [
24].
In the other hand, there is limited evidence about metabolic changes induced by loaded walking or LR. Some studies have shown how an increase in slope when walking with extra load can lead to an increase in metabolic demands such as an increase in oxygen consumption (VO
2), heart rate (HR), respiratory exchange ratio (RER), ventilation (V’E), energy expenditure (EE), and carbohydrates (CHO) or lipids oxidation [
25,
26]. The other way around, an increase in load at a fixed slope may also increase the metabolic demands of walking [
27]. As for LR, the present research suggests greater CHO utilization when LR respect to running without an additional load [
25,
28]. In addition, blood lactate has also been found to reach higher values when LR [
25], but there is no evidence about the behavior of other biochemical parameters such as pH or oxygen saturation (sO
2). The changes in metabolic zones during training or competition under overload compared to normal conditions have not yet been described in the scientific literature. The determination of metabolic zones, such as ventilatory thresholds 1 and 2 (VT1 and VT2), maximal fat oxidation zone (FatMax), and/or maximal/peak oxygen consumption (VO
2max/VO
2peak) is decisive for configuring training loads and paces. Therefore, understanding the behavior of these zones is fundamental when working with overload conditions.
The aim of this study is to analyze physiological-metabolic changes produced by different loads in trail runners when performing a maximal incremental metabolic test. We hypothesized that extra load would trigger differences with respect to unloaded running.
4. Discussion
To the best of our knowledge, this is the first investigation in TR that aims to understand the physiological differences produced by running with different loads (L0, L5, and L10) in a maximal incremental test. The experimental design has being developed as a pilot study. Thus, results only show some tendencies that need to be proven with a larger sample and with some protocol adaptations, following feedback obtained during the trials. As hypothesized, running with extra load seems to trigger differences with respect to running without additional load. L10 appears to create differences in Vpeak and power values while L5 might bring out differences within physiological parameters at submaximal velocities.
WV showed an effect on V
peak reached during the tests. V
peak reached for L5 and L10 represented 97,6% and 94,7% respectively of V
peak reached for L0. On the other hand, relative and absolute power achieved tended to reach greater values with greater loads regardless of V
peak. With respect to physiological parameters, only RER showed differences, and it reached higher values in L0 than in L5. There is only one other study that has investigated the effects of running at speeds close to maximum VO
2 with WV [
24]. However, it focused on other biomechanical variables such as flight and contact time, frequency, and stride length so a direct comparison cannot be made. V
peak in a maximal incremental test is a crucial variable for performance control and race time prediction in TR [
6].
VT2 occurred at intensities between 79.1% and 87.5% of VO
2peak. These intensities are around the highest intensity used by Purdom et al. [
28] compares energy expenditure and substrate utilization at different fixed intensities with different added loads in recreational runners. These researchers suggested higher EE with L10 compared to L0 and L5 during the last minute of 3-minute intervals of running at 65%, 70%, 75%, and 80% of previously tested maximal aerobic speed (MAS). Although the present work does not aim to study EE, it has been found that L5, but not L10, might bring changes compared to the other loads. VT2 with L5 tends to occur at a higher %VO
2peak, allowing greater V than with L10. These differences could be due to the characteristics of the sample, as TR practitioners may be lighter (62.5 ± 3.8 versus 78.6 ± 3.9) and could be more adapted to this load, while the recreational runners might not be.
An explanation to understand this outcome could involve a greater contribution of the elastic component of the muscle-tendon system when running with L5. Although running economy showed no differences at any point (VT1, VT2, FatMax), a potentiation warm-up [
42], and more recently as an intra-trial effect [
43] have been previously described. Cartón-Llorente et al. [
43] used similar loads as used for the present investigation and showed higher leg spring stiffness for L5 than L0 and L10. A second explanation to understand why this has only been observed in trail runners could be an upper load limit. In other cases, this limit might be reached by either higher BM or by lack of specific strength and adaptation.
On the other hand, VT1 was observed at intensities between 42.4% and 59.4% of VO
2peak. Gaffney et al. [
25] used intensity within that range (55% VO
2max) to observe physiological differences in a 30-minute run in CrossFit practitioners. At the corresponding speed to unloaded 55% VO
2max, the addition of a WV of 9.07 kg for men and 6.35 kg for women resulted in significant physiological changes. Significant VO
2 (+0.22 L/min in men, p < 0.01; +0.07 L/min in women, p < 0.05), HR (7% men, p < 0.01; 7% women, p < 0.05), and RER (+0.04 in men, p < 0.001; +0.02 in women, p < 0.05) increases were reported [
25]. Speeds and %VO
2peak at which VT1 occurred in the current investigation were not different with different loads (p = 0.670 and p = 0.256 respectively). Also, observing the increase in RER values experienced by CrossFit practitioners with higher loads [
25], the same increase could be expected for TR athletes when running with the extra load. Contrary to that, RER showed no significant differences. RER is a parameter of interest at submaximal intensities (below VT2) due to the fact that changes in this variable reflect bioenergetic behavior, showing different macronutrient contributions.
Considering that, there seem to be differences compared to the existing evidence [
25]. This could be due to various reasons, such as the weight of the external added load, the duration of the test, and the characteristics of the athletes. First, the additional load used by Gaffney et al. [
25] represents a higher BM percentage for men (12.99% relative to average sample BM) than our highest load (L10), and it is close to equal for women (9.94% relative to average BM). Moreover, the test duration was longer. Participants ran at that fixed speed for 30 minutes, whereas athletes of the present study reached that range of speeds after 10 to 12 minutes of running at lower intensities. Lastly, subjects’ characteristics, such as BM (the difference between average BM was up to 14.25 kg for men and 1.45 kg for women), and familiarization with the stimulus could be key for showing these differences.
Although Purdom et al. (2019) studied fat consumption at different intensities, they did not determine FatMax. Additionally, no value reported any statistical difference at this point. It’s important to note that FatMax is a parameter that usually shows high variability due to additional conditions of carbohydrate and fat intake and absorption. Therefore, considering the small sample size, a significant dispersion of values is normal despite controlling for previous 24-hour diet.
Unlike previous evidence that described an increase in blood lactate (+0.6 mmol/L, p < 0.05) associated to loaded running [
25], final blood lactate in this study showed no differences. However, this could be due because, despite matching the speed, participants in that other study exerted efforts at different intensities in different tests. On the other hand, our trail runners reached almost maximum intensity with each load.
Lastly, the results of different studies could support the idea that greater changes in different variables might occur in UR. It has been shown how a positive slope results in greater concentric load and greater energy expenditure [
8], while BMI has been proven a predictor of UR performance [
6]. The mass of the vest would artificially increase that BMI, while the predominance of concentric contraction would eliminate the hypothetical increased stiffness that a certain load might provide in level running [
43]. Additionally, an increase in load has been used in previous studies [
27] to raise metabolic intensity in uphill walking.
The nature of this pilot study brings some limitations. First of all, the small sample size (n = 4) needs to be increased for future investigations in order to either corroborate or deny the results obtained. Another limitation identified after carrying out this pilot study is the discomfort created by the WV. We suggest the use of proper TR vests for future trials in order to minimize discomfort and to assess the most specificity possible.
Also in order to understand more specific conditions of TR different slopes, both positive and negative, should be taken into account. Finally, different samples of TR subpopulations (elite, females, recreational) should be tested to observe possible differences between groups.
Author Contributions
Conceptualization, GJR, FJMN, PEA and CMP; methodology, GJR, FJMN and CMP; software, GJR, FJMN and CMP; formal analysis, GJR, FJMN and CMP; investigation, GJR, FJMN and CMP; resources, FJMN, PEA and CMP; data curation, GJR, FJMN and CMP; writing—original draft preparation, GJR, FJMN and CMP; writing—review and editing, GJR, FJMN, PEA and CMP; visualization, GJR, FJMN, PEA and CMP; supervision, CMP; project administration, GJR, FJMN and CMP; funding acquisition, PEA and CMP. All authors have read and agreed to the published version of the manuscript.