Effects of six weeks outdoor versus treadmill running on physical fitness and body composition in recreationally active young males: a pilot study

Participants

To calculate the required sample size, a freeware statistical software tool (G*Power; University of Düsseldorf, Düsseldorf, Germany) was used. The following variables were included in the a priori power analysis: study design, two groups; test, retest; effect size of 0.66 based on a previous study that investigated the effects of training in unstable surface (i.e., similar to outdoor running) vs stable surface (i.e., similar to treadmill running) in adolescent male soccer players on countermovement jump (Granacher et al., 2015); alpha error < 0.05; nonsphericity correction = 1; correlation between repeated measures = 0.5; desired power (1-ß error) = 0.80.

The results of the a priori power analysis indicated that a minimum of eight participants would be needed for each group to achieve statistical significance for jump performance (i.e., standing long jump (SLJ)). Thereafter, 28 recreationally active (2–3 moderate-intensity exercise sessions per week; sporadic recreational sport participation) male participants were recruited for the study. A greater number of participants was recruited considering potential drop out due to injury (i.e., not associated to the intervention), lack of time, or related reasons. A graphical depiction of the study design is shown in Fig. 1. To be eligible, participants (i) had to be free of lower limbs injuries during the 6 months prior to the start of the study; (ii) had to participate in physical fitness training programs (i.e., three sessions per week). The participants were randomly assigned to an outdoor running group (OT; n = 14) or a treadmill running group (TT; n = 14) using an online randomization software (www.randomizer.org). The participants of each group possessed similar demographic characteristics (Table 1). Prior to the start of the study, all participants received information on potential risks and benefits of this study. Thereafter, informed consent was obtained. The local ethical committee of Rashtriya Raksha University approved this study (approval number: RRU/R&P/RRUEC/6^th/187/2021).

Procedure

One week before baseline assessment, the participants performed two familiarization sessions for the testing procedures. Demographic data were collected during the familiarization sessions. Participants were asked to refrain from any strenuous activity for 24 h and eating for three hours prior to testing. A two × two within-subject and between-subject, randomized design was used to compare the effect of training intervention (i.e., OT, TT) on physical fitness (i.e., 50 m linear sprint, 1,600 m run, SLJ, flexibility, push-up) and body composition variables (i.e., body mass, body mass index (BMI), fat percentage, fat free mass, segmental muscle mass (SMM) of legs). In addition, the participants were required to maintain their nutritional habits, and this was requested repeatedly during intervention training sessions. Measurements were performed during similar hours before and after the intervention, across two consecutive days, with 50 m sprint, 1,600 m run, SLJ, flexibility and push-up recorded on day one and body composition variables recorded on day two. The sequence of test order was similar for all the participants. Upon arrival for testing on days one participants underwent 10-min general warm-up procedure. For the outdoor assessments the temperature (31–34 °C), humidity (26–29%), and wind velocity (7 km.h⁻¹) were similar before and after the intervention.

Assessments

Statistical analysis

The analyses were conducted using IBM SPSS version 20.0.0 (IBM, Armonk, NY, USA). Data normality was verified using the Shapiro-Wilk test. Data are presented as means and standard deviations. A two (pre-post intervention) by two (OT, TT) mixed ANOVA was used to analyse the exercise-specific effects. In addition, in case of significant group-by-time interactions, Bonferroni adjusted paired (within-group) and independent (between-group comparisons at post) t-tests were used for post-hoc analyses. Percentage change scores were also calculated for each variable in each group using the equation in Microsoft excel sheet: [(mean_post − mean_pre)/mean_pre] × 100. Effects sizes (ES) in the form of partial eta squared (η_p²) were used from ANOVA output. Hedge’s g derived from paired t-test and independent t-test was calculated to assess changes between pre-post measurements testing for each group as well as between group differences at post measurements. The magnitude of effects for η_p² was interpreted as small (<0.06), moderate (≥0.06–0.13), and large (≥0.14) (Cohen, 1988), while Hedge’s g was interpreted as trivial (<0.2), small (0.2–0.6), moderate (>0.6–1.2), large (>1.2–2.0), very large (>2.0–4.0) and extremely large (>4.0) (Hopkins et al., 2009). The ICC between trials was interpreted as poor (<0.5), moderate (0.5–0.75), good (0.75–0.9), and excellent (>0.9) reliability based on the lower bound of the 95% confidence interval (CI; ICC_{95%CI lower bound}) (Koo & Li, 2016). Statistical significance was set at p ≤ 0.05.

Physical fitness variables

The physical fitness variables were significantly improved in both the running groups. These improvements may be attributed to myriad of factors associated with running. For example, improvement in 50 m sprint and 1,600 m performance may be associated with better running economy (Barnes & Kilding, 2015). Running endurance training can lead to a wide range of cardiorespiratory, metabolic, physiological, biomechanical or neuromuscular adaptations (Barnes & Kilding, 2015). Indeed, endurance training has shown to increase the morphology and functionality of skeletal muscle mitochondria (Holloszy et al., 1977). Furthermore, training induced changes may also have occurred such as improved skeletal muscle buffer capacity (Gore et al., 2001) and hematological changes (e.g., increased red blood cells) (Burtscher et al., 1996). In addition, we also observed improvement in SLJ performance. This improvement may be particularly attributed to enhanced stretch-shortening cycle function of the lower limbs following running intervention. Furthermore, we observed improvement in flexibility in both running groups. This improvement in flexibility may have occurred due to increased muscle and collagen strength of lower limbs, tensile strength of tendons and ligaments, and muscle contractility (Fatouros et al., 2002). Moreover, in our study the participants also performed static stretching following running sessions (i.e., during warming-down), which may also be responsible for improvement in flexibility (Hadjicharalambous, 2016). In addition, both running groups also underwent a supplementary strength training session (i.e., circuit training format) one session/week, involving push-ups and planks, which may explain the similar improvements in the push-up test in both running groups.

However, we observed a greater improvement in 50 m sprint, 1,600 m run, and SLJ after OT compared to TT. One possible mechanism for these findings may be the greater neuromuscular activation that occurred during OT compared to TT, contributing to more enhanced functional and neural adaptations. Indeed, Yaserifar & Souza Oliveira (2022) reported increased lower limbs muscle activity when running on grass (i.e., tibialis anterior, peroneus longus, soleus, gastrocnemius medialis, vastus medialis, and rectus femoris) and concrete (i.e., gastrocnemius lateralis, semitendinosus, gluteus maximus) compared to treadmill running. Moreover, lower leg swing amplitude, vertical displacement, and vertical and horizontal velocity variance was noted in treadmill running compared to synthetic surface running, leading to lower external work in treadmill running because of lower lifting of the body mass per step and lower range in cyclic re-acceleration (Wank, Frick & Schmidtbleicher, 1998). The greater intensity of OT compared to TT might have induced greater muscle recruitment, motor unit firing rate and synchronization in the timing of neural discharge during high intensity muscular contraction (Aagaard et al., 2002; Sale, 1987; Semmler et al., 2004), thus greater improvements in 50 m sprint, 1,600 m run, and SLJ. Similarly, the greater flexibility improvements after OT compared to TT (moderate vs small) may be attributed to physiological adaptations (e.g., larger increase in muscle and collagen strength). Nonetheless, as no physiological data was collected, any mechanistic explanation remain speculative.

Body composition variables

Body fat percentage was reduced in both OT and TT. Similar findings were observed in a study by Dorgo et al. (2020), who compared sprint training on treadmill vs over-ground surface. The finding in our study may be attributed to the aerobic nature of the running intervention, as a previous study reported aerobic training as a key contributor to fat loss (Ismail et al., 2012). Indeed, Hottenrott, Ludyga & Schulze (2012) reported decrease in fat percentage following a 12-weeks endurance running intervention in recreationally active runners. Similarly, Milanović et al. (2015) reported decrease in fat percentage following a 12-weeks running intervention program in healthy untrained males. However, greater fat percentage reduction was observed in OT compared to TT (small vs trivial). Compared to running on a treadmill surface, running on outdoor surfaces (e.g., grass, concrete) increase lower limbs muscle activity (Yaserifar & Souza Oliveira, 2022), vertical displacement, and vertical and horizontal velocity variance, leading to greater external work because of higher lifting of the body mass per step and greater range in cyclic re-acceleration (Wank, Frick & Schmidtbleicher, 1998). Therefore, OT may have induced greater total energy expenditure (i.e., negative energy balance), the main factor for fat loss (Slentz et al., 2004). It is then probable that OT may increase total energy expenditure in young males compared to TT, resulting in greater reduction of body fat percentage. In addition, we observed trivial negative changes (i.e., decrease) in SMM of both legs in TT but not in OT. This finding suggests that OT preserved the SMM while decreasing the body fat percentage. The possible mechanistic reason for this might be the higher neuromuscular activation achieved during running in outdoor surface (Yaserifar & Souza Oliveira, 2022), which may have induced sufficient adaptions required to preserve the SMM. Therefore, OT may be suggested to young individuals with the goal of body fat reduction while preserving SMM of leg. In addition, we observed no changes in body mass, BMI, or fat free mass in either running group. However, there was a large magnitude main effect of time on the body mass and BMI. Running as an intervention seems to be an effective strategy in reducing body mass and improve BMI.

Of note, the participants included in our study were recreationally active adult males. This population is usually characterized for a meaningful window of adaptation to training intervention, particularly neuromuscular adaptations (Sale, 1987). Indeed, running intervention may increase activation of prime movers during the running action, and improved changes in the activation of synergist and antagonists muscles (Sale, 1987), thereby increasing efficacy and delaying fatigue of the contractile mechanism (Tamaki et al., 1998). Since significant neuro-mechanical differences have been reported while running in different surfaces (Colino et al., 2020; Dorgo et al., 2020; Kerr et al., 2006; Singh et al., 2022; Wank, Frick & Schmidtbleicher, 1998; Yaserifar & Souza Oliveira, 2022), it would be interesting to hypothesise in future studies that differences observed in outcome measures between OT and TT (i.e., recreationally-active participants) in our study is related to initial neural adaptations. However, how high-level athletes (e.g., endurance runners) would respond to OT and TT is yet unknown. Indeed, previous studies which compared the differences between treadmill and outdoor running included only recreationally active participants (e.g., recreationally active men, physical education students, physically active males, recreational runners, college-age male students) (Dorgo et al., 2020; Kerr et al., 2006; Singh et al., 2022; Wank, Frick & Schmidtbleicher, 1998; Yaserifar & Souza Oliveira, 2022). Therefore, the findings of this study should not be extrapolated to high-level athletes.

Limitations

There are some limitations of our study which should be acknowledged. First, the participants involved in this study were recreationally active male individuals. Therefore, the validity of current findings in other populations (e.g., highly trained runners; females) needs future confirmation. Second, the training intervention was limited to 6-weeks of duration. Although significant changes for both running groups were noted after 6-weeks, a longer duration study may be needed to determine the long-term trend of adaptation after OT and TT for the different outcomes included in this study. Indeed, as a pilot study, our research was designed as proof-of-concept of the OT vs TT approach, and although we conducted a sample size estimation for two independent training groups, larger sample sizes, including a controlled design, may be required to sustain current findings. Indeed, as other pilot studies (Lichtenstein et al., 2020), current findings (e.g., effect sizes) serves as a basis for a long-term intervention. Third, future studies may clarify if the bodyweight strength training session, included in both intervention groups, affected current findings. Fourth, the absence of biomechanical or physiological comparisons in our study. Such comparison may provide better interpretation of the results. Finally, although we request the participants to maintain their habitual nutritional habits during the intervention, no formal measurement was performed, potentially affecting body composition measurements.