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Background
Generating percentile values is helpful for the identification of children with specific fitness characteristics (i.e., low or high fitness level) to set appropriate fitness goals (i.e., fitness/health promotion and/or long-term youth athlete development). Thus, the aim of this longitudinal study was to assess physical fitness development in healthy children aged 9–12 years and to compute sex- and age-specific percentile values.
Methods
Two-hundred and forty children (88 girls, 152 boys) participated in this study and were tested for their physical fitness. Physical fitness was assessed using the 50-m sprint test (i.e., speed), the 1-kg ball push test, the triple hop test (i.e., upper- and lower- extremity muscular power), the stand-and-reach test (i.e., flexibility), the star run test (i.e., agility), and the 9-min run test (i.e., endurance). Age- and sex-specific percentile values (i.e., P10 to P90) were generated using the Lambda, Mu, and Sigma method. Adjusted (for change in body weight, height, and baseline performance) age- and sex-differences as well as the interactions thereof were expressed by calculating effect sizes (Cohen’s d).
Results
Significant main effects of Age were detected for all physical fitness tests (d = 0.40–1.34), whereas significant main effects of Sex were found for upper-extremity muscular power (d = 0.55), flexibility (d = 0.81), agility (d = 0.44), and endurance (d = 0.32) only. Further, significant Sex by Age interactions were observed for upper-extremity muscular power (d = 0.36), flexibility (d = 0.61), and agility (d = 0.27) in favor of girls. Both, linear and curvilinear shaped curves were found for percentile values across the fitness tests. Accelerated (curvilinear) improvements were observed for upper-extremity muscular power (boys: 10–11 yrs; girls: 9–11 yrs), agility (boys: 9–10 yrs; girls: 9–11 yrs), and endurance (boys: 9–10 yrs; girls: 9–10 yrs). Tabulated percentiles for the 9-min run test indicated that running distances between 1,407–1,507 m, 1,479–1,597 m, 1,423–1,654 m, and 1,433–1,666 m in 9- to 12-year-old boys and 1,262–1,362 m, 1,329–1,434 m, 1,392–1,501 m, and 1,415–1,526 m in 9- to 12-year-old girls correspond to a “medium” fitness level (i.e., P40 to P60) in this population.
Conclusions
The observed differences in physical fitness development between boys and girls illustrate that age- and sex-specific maturational processes might have an impact on the fitness status of healthy children. Our statistical analyses revealed linear (e.g., lower-extremity muscular power) and curvilinear (e.g., agility) models of fitness improvement with age which is indicative of timed and capacity-specific fitness development pattern during childhood. Lastly, the provided age- and sex-specific percentile values can be used by coaches for talent identification and by teachers for rating/grading of children’s motor performance.
Background
The aim of this study was to analyze the shoulder functional profile (rotation range of motion [ROM] and strength), upper and lower body performance, and throwing speed of U13 versus U15 male handball players, and to establish the relationship between these measures of physical fitness and throwing speed.
Methods
One-hundred and nineteen young male handball players (under (U)-13 (U13) [n = 85]) and U15 [n = 34]) volunteered to participate in this study. The participating athletes had a mean background of sytematic handball training of 5.5 ± 2.8 years and they exercised on average 540 ± 10.1 min per week including sport-specific team handball training and strength and conditioning programs. Players were tested for passive shoulder range-of-motion (ROM) for both internal (IR) and external rotation (ER) and isometric strength (i.e., IR and ER) of the dominant/non-dominant shoulders, overhead medicine ball throw (OMB), hip isometric abductor (ABD) and adductor (ADD) strength, hip ROM, jumps (countermovement jump [CMJ] and triple leg-hop [3H] for distance), linear sprint test, modified 505 change-of-direction (COD) test and handball throwing speed (7 m [HT7] and 9 m [HT9]).
Results
U15 players outperformed U13 in upper (i.e., HT7 and HT9 speed, OMB, absolute IR and ER strength of the dominant and non-dominant sides; Cohen’s d: 0.76–2.13) and lower body (i.e., CMJ, 3H, 20-m sprint and COD, hip ABD and ADD; d: 0.70–2.33) performance measures. Regarding shoulder ROM outcomes, a lower IR ROM was found of the dominant side in the U15 group compared to the U13 and a higher ER ROM on both sides in U15 (d: 0.76–1.04). It seems that primarily anthropometric characteristics (i.e., body height, body mass) and upper body strength/power (OMB distance) are the most important factors that explain the throw speed variance in male handball players, particularly in U13.
Conclusions
Findings from this study imply that regular performance monitoring is important for performance development and for minimizing injury risk of the shoulder in both age categories of young male handball players. Besides measures of physical fitness, anthropometric data should be recorded because handball throwing performance is related to these measures.
Background
The aim of this study was to analyze the shoulder functional profile (rotation range of motion [ROM] and strength), upper and lower body performance, and throwing speed of U13 versus U15 male handball players, and to establish the relationship between these measures of physical fitness and throwing speed.
Methods
One-hundred and nineteen young male handball players (under (U)-13 (U13) [n = 85]) and U15 [n = 34]) volunteered to participate in this study. The participating athletes had a mean background of sytematic handball training of 5.5 ± 2.8 years and they exercised on average 540 ± 10.1 min per week including sport-specific team handball training and strength and conditioning programs. Players were tested for passive shoulder range-of-motion (ROM) for both internal (IR) and external rotation (ER) and isometric strength (i.e., IR and ER) of the dominant/non-dominant shoulders, overhead medicine ball throw (OMB), hip isometric abductor (ABD) and adductor (ADD) strength, hip ROM, jumps (countermovement jump [CMJ] and triple leg-hop [3H] for distance), linear sprint test, modified 505 change-of-direction (COD) test and handball throwing speed (7 m [HT7] and 9 m [HT9]).
Results
U15 players outperformed U13 in upper (i.e., HT7 and HT9 speed, OMB, absolute IR and ER strength of the dominant and non-dominant sides; Cohen’s d: 0.76–2.13) and lower body (i.e., CMJ, 3H, 20-m sprint and COD, hip ABD and ADD; d: 0.70–2.33) performance measures. Regarding shoulder ROM outcomes, a lower IR ROM was found of the dominant side in the U15 group compared to the U13 and a higher ER ROM on both sides in U15 (d: 0.76–1.04). It seems that primarily anthropometric characteristics (i.e., body height, body mass) and upper body strength/power (OMB distance) are the most important factors that explain the throw speed variance in male handball players, particularly in U13.
Conclusions
Findings from this study imply that regular performance monitoring is important for performance development and for minimizing injury risk of the shoulder in both age categories of young male handball players. Besides measures of physical fitness, anthropometric data should be recorded because handball throwing performance is related to these measures.
The purpose of this study was to compare static balance performance and muscle activity during one-leg standing on the dominant and nondominant leg under various sensory conditions with increased levels of task difficulty. Thirty healthy young adults (age: 23 +/- 2 years) performed one-leg standing tests for 30 s under three sensory conditions (ie, eyes open/firm ground; eyes open/foam ground [elastic pad on top of the balance plate]; eyes closed/firm ground). Center of pressure displacements and activity of four lower leg muscles (ie, m. tibialis anterior [TA], m. soleus [SOL], m. gastrocnemius medialis [GAS], m. peroneus longus [PER]) were analyzed. An increase in sensory task difficulty resulted in deteriorated balance performance (P < .001, effect size [ES] = .57-2.54) and increased muscle activity (P < .001, ES = .50-1.11) for all but two muscles (ie, GAS, PER). However, regardless of the sensory condition, one-leg standing on the dominant as compared with the nondominant limb did not produce statistically significant differences in various balance (P > .05, ES = .06-.22) and electromyographic (P > .05, ES = .03-.13) measures. This indicates that the dominant and the nondominant leg can be used interchangeably during static one-leg balance testing in healthy young adults.
Walking while concurrently performing cognitive and/or motor interference tasks is the norm rather than the exception during everyday life and there is evidence from behavioral studies that it negatively affects human locomotion. However, there is hardly any information available regarding the underlying neural correlates of single- and dual-task walking. We had 12 young adults (23.8 ± 2.8 years) walk while concurrently performing a cognitive interference (CI) or a motor interference (MI) task. Simultaneously, neural activation in frontal, central, and parietal brain areas was registered using a mobile EEG system. Results showed that the MI task but not the CI task affected walking performance in terms of significantly decreased gait velocity and stride length and significantly increased stride time and tempo-spatial variability. Average activity in alpha and beta frequencies was significantly modulated during both CI and MI walking conditions in frontal and central brain regions, indicating an increased cognitive load during dual-task walking. Our results suggest that impaired motor performance during dual-task walking is mirrored in neural activation patterns of the brain. This finding is in line with established cognitive theories arguing that dual-task situations overstrain cognitive capabilities resulting in motor performance decrements.
Walking while concurrently performing cognitive and/or motor interference tasks is the norm rather than the exception during everyday life and there is evidence from behavioral studies that it negatively affects human locomotion. However, there is hardly any information available regarding the underlying neural correlates of single- and dual-task walking. We had 12 young adults (23.8 ± 2.8 years) walk while concurrently performing a cognitive interference (CI) or a motor interference (MI) task. Simultaneously, neural activation in frontal, central, and parietal brain areas was registered using a mobile EEG system. Results showed that the MI task but not the CI task affected walking performance in terms of significantly decreased gait velocity and stride length and significantly increased stride time and tempo-spatial variability. Average activity in alpha and beta frequencies was significantly modulated during both CI and MI walking conditions in frontal and central brain regions, indicating an increased cognitive load during dual-task walking. Our results suggest that impaired motor performance during dual-task walking is mirrored in neural activation patterns of the brain. This finding is in line with established cognitive theories arguing that dual-task situations overstrain cognitive capabilities resulting in motor performance decrements.
The aim of this study was to establish maturation-, age-, and sex-specific anthropometric and physical fitness percentile reference values of young elite athletes from various sports. Anthropometric (i.e., standing and sitting body height, body mass, body mass index) and physical fitness (i.e., countermovement jump, drop jump, change-of-direction speed [i.e., T-test], trunk muscle endurance [i.e., ventral Bourban test], dynamic lower limbs balance [i.e., Y-balance test], hand grip strength) of 703 male and female elite young athletes aged 8–18 years were collected to aggregate reference values according to maturation, age, and sex. Findings indicate that body height and mass were significantly higher (p<0.001; 0.95≤d≤1.74) in more compared to less mature young athletes as well as with increasing chronological age (p<0.05; 0.66≤d≤3.13). Furthermore, male young athletes were significantly taller and heavier compared to their female counterparts (p<0.001; 0.34≤d≤0.50). In terms of physical fitness, post-pubertal athletes showed better countermovement jump, drop jump, change-of-direction, and handgrip strength performances (p<0.001; 1.57≤d≤8.72) compared to pubertal athletes. Further, countermovement jump, drop jump, change-of-direction, and handgrip strength performances increased with increasing chronological age (p<0.05; 0.29≤d≤4.13). In addition, male athletes outperformed their female counterpart in the countermovement jump, drop jump, change-of-direction, and handgrip strength (p<0.05; 0.17≤d≤0.76). Significant age by sex interactions indicate that sex-specific differences were even more pronounced with increasing age. Conclusively, body height, body mass, and physical fitness increased with increasing maturational status and chronological age. Sex-specific differences appear to be larger as youth grow older. Practitioners can use the percentile values as approximate benchmarks for talent identification and development.
The aim of this study was to establish maturation-, age-, and sex-specific anthropometric and physical fitness percentile reference values of young elite athletes from various sports. Anthropometric (i.e., standing and sitting body height, body mass, body mass index) and physical fitness (i.e., countermovement jump, drop jump, change-of-direction speed [i.e., T-test], trunk muscle endurance [i.e., ventral Bourban test], dynamic lower limbs balance [i.e., Y-balance test], hand grip strength) of 703 male and female elite young athletes aged 8–18 years were collected to aggregate reference values according to maturation, age, and sex. Findings indicate that body height and mass were significantly higher (p<0.001; 0.95≤d≤1.74) in more compared to less mature young athletes as well as with increasing chronological age (p<0.05; 0.66≤d≤3.13). Furthermore, male young athletes were significantly taller and heavier compared to their female counterparts (p<0.001; 0.34≤d≤0.50). In terms of physical fitness, post-pubertal athletes showed better countermovement jump, drop jump, change-of-direction, and handgrip strength performances (p<0.001; 1.57≤d≤8.72) compared to pubertal athletes. Further, countermovement jump, drop jump, change-of-direction, and handgrip strength performances increased with increasing chronological age (p<0.05; 0.29≤d≤4.13). In addition, male athletes outperformed their female counterpart in the countermovement jump, drop jump, change-of-direction, and handgrip strength (p<0.05; 0.17≤d≤0.76). Significant age by sex interactions indicate that sex-specific differences were even more pronounced with increasing age. Conclusively, body height, body mass, and physical fitness increased with increasing maturational status and chronological age. Sex-specific differences appear to be larger as youth grow older. Practitioners can use the percentile values as approximate benchmarks for talent identification and development.
This study aimed to compare the training load of a professional under-19 soccer team (U-19) to that of an elite adult team (EAT), from the same club, during the in-season period. Thirty-nine healthy soccer players were involved (EAT [n = 20]; U-19 [n = 19]) in the study which spanned four weeks. Training load (TL) was monitored as external TL, using a global positioning system (GPS), and internal TL, using a rating of perceived exertion (RPE). TL data were recorded after each training session. During soccer matches, players’ RPEs were recorded. The internal TL was quantified daily by means of the session rating of perceived exertion (session-RPE) using Borg’s 0–10 scale. For GPS data, the selected running speed intensities (over 0.5 s time intervals) were 12–15.9 km/h; 16–19.9 km/h; 20–24.9 km/h; >25 km/h (sprint). Distances covered between 16 and 19.9 km/h, > 20 km/h and >25 km/h were significantly higher in U-19 compared to EAT over the course of the study (p = 0.023, d = 0.243, small; p = 0.016, d = 0.298, small; and p = 0.001, d = 0.564, small, respectively). EAT players performed significantly fewer sprints per week compared to U-19 players (p = 0.002, d = 0.526, small). RPE was significantly higher in U-19 compared to EAT (p = 0.001, d = 0.188, trivial). The external and internal measures of TL were significantly higher in the U-19 group compared to the EAT soccer players. In conclusion, the results obtained show that the training load is greater in U19 compared to EAT.
This study aimed to compare the training load of a professional under-19 soccer team (U-19) to that of an elite adult team (EAT), from the same club, during the in-season period. Thirty-nine healthy soccer players were involved (EAT [n = 20]; U-19 [n = 19]) in the study which spanned four weeks. Training load (TL) was monitored as external TL, using a global positioning system (GPS), and internal TL, using a rating of perceived exertion (RPE). TL data were recorded after each training session. During soccer matches, players’ RPEs were recorded. The internal TL was quantified daily by means of the session rating of perceived exertion (session-RPE) using Borg’s 0–10 scale. For GPS data, the selected running speed intensities (over 0.5 s time intervals) were 12–15.9 km/h; 16–19.9 km/h; 20–24.9 km/h; >25 km/h (sprint). Distances covered between 16 and 19.9 km/h, > 20 km/h and >25 km/h were significantly higher in U-19 compared to EAT over the course of the study (p = 0.023, d = 0.243, small; p = 0.016, d = 0.298, small; and p = 0.001, d = 0.564, small, respectively). EAT players performed significantly fewer sprints per week compared to U-19 players (p = 0.002, d = 0.526, small). RPE was significantly higher in U-19 compared to EAT (p = 0.001, d = 0.188, trivial). The external and internal measures of TL were significantly higher in the U-19 group compared to the EAT soccer players. In conclusion, the results obtained show that the training load is greater in U19 compared to EAT.
Objective: A role for microRNAs is implicated in several biological and pathological processes. We investigated the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on molecular markers of diabetic cardiomyopathy in rats.
Methods: Eighteen male Wistar rats (260 ± 10 g; aged 8 weeks) with streptozotocin (STZ)-induced type 1 diabetes mellitus (55 mg/kg, IP) were randomly allocated to three groups: control, MICT, and HIIT. The two different training protocols were performed 5 days each week for 5 weeks. Cardiac performance (end-systolic and end-diastolic dimensions, ejection fraction), the expression of miR-206, HSP60, and markers of apoptosis (cleaved PARP and cytochrome C) were determined at the end of the exercise interventions.
Results: Both exercise interventions (HIIT and MICT) decreased blood glucose levels and improved cardiac performance, with greater changes in the HIIT group (p < 0.001, η2: 0.909). While the expressions of miR-206 and apoptotic markers decreased in both training protocols (p < 0.001, η2: 0.967), HIIT caused greater reductions in apoptotic markers and produced a 20% greater reduction in miR-206 compared with the MICT protocol (p < 0.001). Furthermore, both training protocols enhanced the expression of HSP60 (p < 0.001, η2: 0.976), with a nearly 50% greater increase in the HIIT group compared with MICT.
Conclusions: Our results indicate that both exercise protocols, HIIT and MICT, have the potential to reduce diabetic cardiomyopathy by modifying the expression of miR-206 and its downstream targets of apoptosis. It seems however that HIIT is even more effective than MICT to modulate these molecular markers.
Objective: A role for microRNAs is implicated in several biological and pathological processes. We investigated the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on molecular markers of diabetic cardiomyopathy in rats.
Methods: Eighteen male Wistar rats (260 ± 10 g; aged 8 weeks) with streptozotocin (STZ)-induced type 1 diabetes mellitus (55 mg/kg, IP) were randomly allocated to three groups: control, MICT, and HIIT. The two different training protocols were performed 5 days each week for 5 weeks. Cardiac performance (end-systolic and end-diastolic dimensions, ejection fraction), the expression of miR-206, HSP60, and markers of apoptosis (cleaved PARP and cytochrome C) were determined at the end of the exercise interventions.
Results: Both exercise interventions (HIIT and MICT) decreased blood glucose levels and improved cardiac performance, with greater changes in the HIIT group (p < 0.001, η2: 0.909). While the expressions of miR-206 and apoptotic markers decreased in both training protocols (p < 0.001, η2: 0.967), HIIT caused greater reductions in apoptotic markers and produced a 20% greater reduction in miR-206 compared with the MICT protocol (p < 0.001). Furthermore, both training protocols enhanced the expression of HSP60 (p < 0.001, η2: 0.976), with a nearly 50% greater increase in the HIIT group compared with MICT.
Conclusions: Our results indicate that both exercise protocols, HIIT and MICT, have the potential to reduce diabetic cardiomyopathy by modifying the expression of miR-206 and its downstream targets of apoptosis. It seems however that HIIT is even more effective than MICT to modulate these molecular markers.
Background
Sand is an easy-to-access, cost-free resource that can be used to treat pronated feet (PF). Therefore, the aims of this study were to contrast the effects of walking on stable ground versus walking on sand on ground reaction forces (GRFs) and electromyographic (EMG) activity of selected lower limb muscles in PF individuals compared with healthy controls.
Methods
Twenty-nine controls aged 22.2±2.5 years and 30 PF individuals aged 22.2±1.9 years were enrolled in this study. Participants walked at preferred speed and in randomized order over level ground and sand. A force plate was included in the walkway to collect GRFs. Muscle activities were recorded using EMG system.
Results
No statistically significant between-group differences were found in preferred walking speed when walking on stable ground (PF: 1.33±0.12 m/s; controls: 1.35±0.14 m/s; p = 0.575; d = 0.15) and sand (PF: 1.19±0.11 m/s; controls: 1.23±0.18 m/s; p = 0.416; d = 0.27). Irrespective of the group, walking on sand (1.21±0.15 m/s) resulted in significantly lower gait speed compared with stable ground walking (1.34±0.13 m/s) (p<0.001; d = 0.93). Significant main effects of “surface” were found for peak posterior GRFs at heel contact, time to peak for peak lateral GRFs at heel contact, and peak anterior GRFs during push-off (p<0.044; d = 0.27–0.94). Pair-wise comparisons revealed significantly smaller peak posterior GRFs at heel contact (p = 0.005; d = 1.17), smaller peak anterior GRFs during push-off (p = 0.001; d = 1.14), and time to peak for peak lateral GRFs (p = 0.044; d = 0.28) when walking on sand. No significant main effects of “group” were observed for peak GRFs and their time to peak (p>0.05; d = 0.06–1.60). We could not find any significant group by surface interactions for peak GRFs and their time to peak. Significant main effects of “surface” were detected for anterior-posterior impulse and peak positive free moment amplitude (p<0.048; d = 0.54–0.71). Pair-wise comparisons revealed a significantly larger peak positive free moment amplitude (p = 0.010; d = 0.71) and a lower anterior-posterior impulse (p = 0.048; d = 0.38) when walking on sand. We observed significant main effects of “group” for the variable loading rate (p<0.030; d = 0.59). Pair-wise comparisons revealed significantly lower loading rates in PF compared with controls (p = 0.030; d = 0.61). Significant group by surface interactions were observed for the parameter peak positive free moment amplitude (p<0.030; d = 0.59). PF individuals exhibited a significantly lower peak positive free moment amplitude (p = 0.030, d = 0.41) when walking on sand. With regards to EMG, no significant main effects of “surface”, main effects of “group”, and group by surface interactions were observed for the recorded muscles during the loading and push-off phases (p>0.05; d = 0.00–0.53).
Conclusions
The observed lower velocities during walking on sand compared with stable ground were accompanied by lower peak positive free moments during the push-off phase and loading rates during the loading phase. Our findings of similar lower limb muscle activities during walking on sand compared with stable ground in PF together with lower free moment amplitudes, vertical loading rates, and lower walking velocities on sand may indicate more relative muscle activity on sand compared with stable ground. This needs to be verified in future studies.
Background
Sand is an easy-to-access, cost-free resource that can be used to treat pronated feet (PF). Therefore, the aims of this study were to contrast the effects of walking on stable ground versus walking on sand on ground reaction forces (GRFs) and electromyographic (EMG) activity of selected lower limb muscles in PF individuals compared with healthy controls.
Methods
Twenty-nine controls aged 22.2±2.5 years and 30 PF individuals aged 22.2±1.9 years were enrolled in this study. Participants walked at preferred speed and in randomized order over level ground and sand. A force plate was included in the walkway to collect GRFs. Muscle activities were recorded using EMG system.
Results
No statistically significant between-group differences were found in preferred walking speed when walking on stable ground (PF: 1.33±0.12 m/s; controls: 1.35±0.14 m/s; p = 0.575; d = 0.15) and sand (PF: 1.19±0.11 m/s; controls: 1.23±0.18 m/s; p = 0.416; d = 0.27). Irrespective of the group, walking on sand (1.21±0.15 m/s) resulted in significantly lower gait speed compared with stable ground walking (1.34±0.13 m/s) (p<0.001; d = 0.93). Significant main effects of “surface” were found for peak posterior GRFs at heel contact, time to peak for peak lateral GRFs at heel contact, and peak anterior GRFs during push-off (p<0.044; d = 0.27–0.94). Pair-wise comparisons revealed significantly smaller peak posterior GRFs at heel contact (p = 0.005; d = 1.17), smaller peak anterior GRFs during push-off (p = 0.001; d = 1.14), and time to peak for peak lateral GRFs (p = 0.044; d = 0.28) when walking on sand. No significant main effects of “group” were observed for peak GRFs and their time to peak (p>0.05; d = 0.06–1.60). We could not find any significant group by surface interactions for peak GRFs and their time to peak. Significant main effects of “surface” were detected for anterior-posterior impulse and peak positive free moment amplitude (p<0.048; d = 0.54–0.71). Pair-wise comparisons revealed a significantly larger peak positive free moment amplitude (p = 0.010; d = 0.71) and a lower anterior-posterior impulse (p = 0.048; d = 0.38) when walking on sand. We observed significant main effects of “group” for the variable loading rate (p<0.030; d = 0.59). Pair-wise comparisons revealed significantly lower loading rates in PF compared with controls (p = 0.030; d = 0.61). Significant group by surface interactions were observed for the parameter peak positive free moment amplitude (p<0.030; d = 0.59). PF individuals exhibited a significantly lower peak positive free moment amplitude (p = 0.030, d = 0.41) when walking on sand. With regards to EMG, no significant main effects of “surface”, main effects of “group”, and group by surface interactions were observed for the recorded muscles during the loading and push-off phases (p>0.05; d = 0.00–0.53).
Conclusions
The observed lower velocities during walking on sand compared with stable ground were accompanied by lower peak positive free moments during the push-off phase and loading rates during the loading phase. Our findings of similar lower limb muscle activities during walking on sand compared with stable ground in PF together with lower free moment amplitudes, vertical loading rates, and lower walking velocities on sand may indicate more relative muscle activity on sand compared with stable ground. This needs to be verified in future studies.
Aims: High intensity interval training (HIIT) improves mitochondrial characteristics. This study compared the impact of two workload-matched high intensity interval training (HIIT) protocols with different work:recovery ratios on regulatory factors related to mitochondrial biogenesis in the soleus muscle of diabetic rats.
Materials and methods: Twenty-four Wistar rats were randomly divided into four equal-sized groups: non-diabetic control, diabetic control (DC), diabetic with long recovery exercise [4–5 × 2-min running at 80%–90% of the maximum speed reached with 2-min of recovery at 40% of the maximum speed reached (DHIIT1:1)], and diabetic with short recovery exercise (5–6 × 2-min running at 80%–90% of the maximum speed reached with 1-min of recovery at 30% of the maximum speed reached [DHIIT2:1]). Both HIIT protocols were completed five times/week for 4 weeks while maintaining equal running distances in each session.
Results: Gene and protein expressions of PGC-1α, p53, and citrate synthase of the muscles increased significantly following DHIIT1:1 and DHIIT2:1 compared to DC (p ˂ 0.05). Most parameters, except for PGC-1α protein (p = 0.597), were significantly higher in DHIIT2:1 than in DHIIT1:1 (p ˂ 0.05). Both DHIIT groups showed significant increases in maximum speed with larger increases in DHIIT2:1 compared with DHIIT1:1.
Conclusion: Our findings indicate that both HIIT protocols can potently up-regulate gene and protein expression of PGC-1α, p53, and CS. However, DHIIT2:1 has superior effects compared with DHIIT1:1 in improving mitochondrial adaptive responses in diabetic rats.
Aims: High intensity interval training (HIIT) improves mitochondrial characteristics. This study compared the impact of two workload-matched high intensity interval training (HIIT) protocols with different work:recovery ratios on regulatory factors related to mitochondrial biogenesis in the soleus muscle of diabetic rats.
Materials and methods: Twenty-four Wistar rats were randomly divided into four equal-sized groups: non-diabetic control, diabetic control (DC), diabetic with long recovery exercise [4–5 × 2-min running at 80%–90% of the maximum speed reached with 2-min of recovery at 40% of the maximum speed reached (DHIIT1:1)], and diabetic with short recovery exercise (5–6 × 2-min running at 80%–90% of the maximum speed reached with 1-min of recovery at 30% of the maximum speed reached [DHIIT2:1]). Both HIIT protocols were completed five times/week for 4 weeks while maintaining equal running distances in each session.
Results: Gene and protein expressions of PGC-1α, p53, and citrate synthase of the muscles increased significantly following DHIIT1:1 and DHIIT2:1 compared to DC (p ˂ 0.05). Most parameters, except for PGC-1α protein (p = 0.597), were significantly higher in DHIIT2:1 than in DHIIT1:1 (p ˂ 0.05). Both DHIIT groups showed significant increases in maximum speed with larger increases in DHIIT2:1 compared with DHIIT1:1.
Conclusion: Our findings indicate that both HIIT protocols can potently up-regulate gene and protein expression of PGC-1α, p53, and CS. However, DHIIT2:1 has superior effects compared with DHIIT1:1 in improving mitochondrial adaptive responses in diabetic rats.
Introduction: Several sports demand an early start into long-term athlete development (LTAD) because peak performances are achieved at a relatively young age (e.g., gymnastics). However, the challenging combination of high training volumes and academic demands may impede youth athletes' cognitive and academic performances. Thus, the aims of this study were to examine the effects of a 1-year sport-specific training and/or physical education on physical fitness, body composition, cognitive and academic performances in youth athletes and their non-athletic peers. Methods: Overall, 45 prepubertal fourth graders from a German elite sport school were enrolled in this study. Participating children were either youth athletes from an elite sports class (n = 20, age 9.5 ± 0.5 years) or age-matched peers from a regular class (n = 25, age 9.6 ± 0.6 years). Over the 1-year intervention period, the elite sports class conducted physical education and sport-specific training (i.e., gymnastics, swimming, soccer, bicycle motocross [BMX]) during school time while the regular class attended physical education only. Of note, BMX is a specialized form of cycling that is performed on motocross tracks and affords high technical skills. Before and after intervention, tests were performed for the assessment of physical fitness (speed [20-m sprint], agility [star agility run], muscle power [standing long jump], flexibility [stand-and-reach], endurance [6-min-run], balance [single-leg stance]), body composition (e.g., muscle mass), cognitive (d2-test) and academic performance (reading [ELFE 1–6], writing [HSP 4–5], calculating [DEMAT 4]). In addition, grades in German, English, Mathematics, and physical education were documented. Results: At baseline, youth athletes showed better physical fitness performances (p < 0.05; d = 0.70–2.16), less relative body fat mass, more relative skeletal muscle mass (p < 0.01; d = 1.62–1.84), and similar cognitive and academic achievements compared to their non-athletic peers. Athletes' training volume amounted to 620 min/week over the 1-year period while their peers performed 155 min/week. After the intervention, significant differences were found in 6 out of 7 physical fitness tests (p < 0.05; d = 0.75–1.40) and in the physical education grades (p < 0.01; d = 2.36) in favor of the elite sports class. No significant between-group differences were found after the intervention in measures of body composition (p > 0.05; d = 0.66–0.67), cognition and academics (p > 0.05; d = 0.40–0.64). Our findings revealed no significant between-group differences in growth rate (deltas of pre-post-changes in body height and leg length). Discussion: Our results revealed that a school-based 1-year sport-specific training in combination with physical education improved physical fitness but did not negatively affect cognitive and academic performances of youth athletes compared to their non-athletic peers. It is concluded that sport-specific training in combination with physical education promotes youth athletes' physical fitness development during LTAD and does not impede their cognitive and academic development.
Introduction: Several sports demand an early start into long-term athlete development (LTAD) because peak performances are achieved at a relatively young age (e.g., gymnastics). However, the challenging combination of high training volumes and academic demands may impede youth athletes' cognitive and academic performances. Thus, the aims of this study were to examine the effects of a 1-year sport-specific training and/or physical education on physical fitness, body composition, cognitive and academic performances in youth athletes and their non-athletic peers.
Methods: Overall, 45 prepubertal fourth graders from a German elite sport school were enrolled in this study. Participating children were either youth athletes from an elite sports class (n = 20, age 9.5 ± 0.5 years) or age-matched peers from a regular class (n = 25, age 9.6 ± 0.6 years). Over the 1-year intervention period, the elite sports class conducted physical education and sport-specific training (i.e., gymnastics, swimming, soccer, bicycle motocross [BMX]) during school time while the regular class attended physical education only. Of note, BMX is a specialized form of cycling that is performed on motocross tracks and affords high technical skills. Before and after intervention, tests were performed for the assessment of physical fitness (speed [20-m sprint], agility [star agility run], muscle power [standing long jump], flexibility [stand-and-reach], endurance [6-min-run], balance [single-leg stance]), body composition (e.g., muscle mass), cognitive (d2-test) and academic performance (reading [ELFE 1–6], writing [HSP 4–5], calculating [DEMAT 4]). In addition, grades in German, English, Mathematics, and physical education were documented.
Results: At baseline, youth athletes showed better physical fitness performances (p < 0.05; d = 0.70–2.16), less relative body fat mass, more relative skeletal muscle mass (p < 0.01; d = 1.62–1.84), and similar cognitive and academic achievements compared to their non-athletic peers. Athletes' training volume amounted to 620 min/week over the 1-year period while their peers performed 155 min/week. After the intervention, significant differences were found in 6 out of 7 physical fitness tests (p < 0.05; d = 0.75–1.40) and in the physical education grades (p < 0.01; d = 2.36) in favor of the elite sports class. No significant between-group differences were found after the intervention in measures of body composition (p > 0.05; d = 0.66–0.67), cognition and academics (p > 0.05; d = 0.40–0.64). Our findings revealed no significant between-group differences in growth rate (deltas of pre-post-changes in body height and leg length).
Discussion: Our results revealed that a school-based 1-year sport-specific training in combination with physical education improved physical fitness but did not negatively affect cognitive and academic performances of youth athletes compared to their non-athletic peers. It is concluded that sport-specific training in combination with physical education promotes youth athletes' physical fitness development during LTAD and does not impede their cognitive and academic development.