Associations between arm span, upper and lower limb power, and ball throwing speed in Goalball athletes

BackgroundThe biological maturation (BM) analyzed by peak height velocity (PHV) and bone age (BA), and lean body mass has been associated with the strength and muscle power of young athletes. However, the ability of BM (PHV and BA) and LM markers to predict muscle strength and power in young athletes remains uncertain.ObjectiveThe Aim was determine the predicting power of BM markers (PHV and BA) and LM in relation to muscle power of upper and lower limbs and muscle strength of upper limbs in adolescent athletes at puberty.MethodsNinety-two adolescent athletes (both sexes; age 12.4 ± 1.02 years) were assessed for body composition by dual-energy X-ray absorptiometry (DXA). Power of upper limbs (ULP), force handgrip (HG), vertical jump (VJ) and countermovement jump (CMJ) were recorded. BM was predicted by mathematical models to estimate PHV and BA. Multilayer artificial neural network analyses (MLP’s) were used to determine the power of prediction of LM, PHV and BA on muscle power and strength of upper- and lower-limbs of the athletes.ResultsLM, BA and PHV were associated with HG (r>0.74, p<0.05) and ULS (r>0.60, p<0.05) in both sexes. In both sexes BA was associated with VJ (r>0.55, p<0.05) and CMJ (r>0.53, p<0.05). LM indicated associations (r>0.60, p<0.05) with BA and with PHV (r<0.83, p<0.05) in both sexes. MLP’s analysis revealed that the LM provides > 72% of probability to predict the muscle power of upper- and lower-limbs, and the strength of the upper limbs; whereas PHV provides > 43% and bone age >64% in both female and male adolescent athletes.ConclusionWe identified that, like PHV and BA, LM is a strong predictor of low cost of both upper limbs muscle strength and upper and lower limbs power in adolescent athletes.

This study aimed to investigate relationships between peak power (PP) as measured by upper limb (PPUL) and lower limb (PPLL) force-velocity tests, maximal upper limb force assessed by 1 repetition maximum bench press (1RMBP), and pullover (1RMPO) exercises, estimates of local muscle volume and 3-step running handball throwing velocity (T3-Steps). Fourteen male handball players volunteered for the investigation (age: 19.6+/-0.6 years; body mass: 86.7+/-12.9 kg; and height 1.87+/-0.07 m). Lower and upper limb force-velocity tests were performed on appropriately modified forms of a Monark cycle ergometer, with measurement of PPUL and PPLL, and the corresponding respective maximal forces (F0UL and F0LL) and velocities (V0UL and V0LL). T3-Steps was assessed using a radar Stalker ATS system. Muscle volumes of the upper and lower limbs were estimated with a standard anthropometric kit. T3-Steps was closely related to absolute PPUL and to F0UL (r=0.69, p<0.01 for both relationships). T3-Steps was also moderately related to 1RMBP and 1RMPO (r=0.56, p<0.05; r=0.55, p<0.05 respectively), and to PPLL and F0LL (r=0.56, p<0.05; r=0.62, p<0.05, respectively). When PPLL was expressed per unit of limb muscle volume, the relationship with T3-Steps disappeared. This suggests the importance of muscle volume to performance in throwing events. Force-velocity data may prove useful in regulating conditioning and rehabilitation programs for handball players. Our results also highlight the contribution of both the lower and the upper limbs to handball throwing velocity, suggesting the need for coaches to include upper and lower limb strength and power programs when improving the throwing velocity of handball players.

Are there differences in anaerobic relative muscle power between upper and lower limbs in adolescent swimmers: A blinded study

AimThe aim of study was to investigate the influence of correct nutrition, creatine and glutamine supplements on anaerobic power, capacity of upper and lower limbs of the elite wrestlers of...

There is still no consensus on how biological maturation (BM) affects the muscle power of upper and lower limbs in young people. The objective was to verify associations between BM and muscle power, as well as to compare the muscle power of upper (ULP) and lower limbs (LLP) among young athletes in different stages of BM. The sample consisted of 79 female athletes (10.9 ± 1.11 years old). Regarding BM, the sample was divided into three groups: delayed BM, synchronized BM, and accelerated BM. BM was identified by subtracting chronological age from bone age (BA). BA was measured by a mathematical model based on anthropometry. The muscular power of the upper limbs was analyzed by the medicine ball launch test, and that of the lower limbs was analyzed by the countermovement jump on a force platform. BM and BA correlated with ULP (BA: r =0.74; BM: r =0.65) and LLP (BA: r = 0.50; BM: r =0.41). In the comparisons of the tests of ULP and LLP, the groups with synchronized and accelerated BM were superior to the group with delayed BM. The advance of BM is associated with the ULP and LLP, as well as the advance of the BM affects muscle power in young female athletes. This occurs due to the increase in body mass resulting from the advancement of BM, which may favor the predominance of lean body mass, assisting in the production of muscle strength.

Introduction: Physical capabilities are an important parameter of the functional development of adolescents, not only by chronological age but also by their maturational state, as individuals with the same chronological age can have different performance to their less mature counterparts. Objective: To compare and relate the physical capabilities and hormonal markers according to sex and maturity of adolescents. Method: The sample consisted of adolescents of both sexes, aged 10 to 14 years. We evaluated the maturity achieved by a predictive equation of skeletal age, physical capabilities (explosive power of upper and lower limbs, velocity of upper limbs and agility) and hormonal markers (testosterone and oestradiol) via chemiluminescence. Results: Females showed more advanced maturational status, higher weight, body height and oestradiol levels; males performed better in the explosive force of upper and lower limbs, upper limb speed, agility and testosterone levels. In the normal maturational state males showed greater skeletal age, body weight, body height, explosive strength of upper and lower limbs, and testosterone levels; the females in the normal maturational state had higher skeletal age, body weight, body height, explosive upper limb strength and oestradiol levels. In the male correlation analysis, bone age was related to the explosive strength of upper and lower limbs and testosterone; while bone age in females was related to explosive upper limb strength and oestradiol. Conclusion: It is concluded that maturation, testosterone and oestradiol levels play an important role in the physical aspects and performance of motor skills of adolescents, especially in upper limb force which was more related to the maturation obtained by skeletal age of males and females.

Background: There is still little understanding of the associations between physical fitness variables and bone health in children taking into account key confounders. Aim: The aim of this study was to analyze the associations between performance in tests of speed, agility, and musculoskeletal fitness (power of the upper and lower limbs) with bone mass of different regions in children, considering the adjustment to maturity-offset, lean percentage, and sex. Methods: Cross-sectional study design: the sample consisted of 160 children aged 6-11 years. The physical fitness variables tested were 1) speed, assessed with the running test at a maximum speed of 20m; 2) agility, assessed through the 4×4-m square test; 3) lower limb power, assessed using the standing long jump test, and 4) upper limb power, assessed using the 2-kg medicine ball throw test. Areal bone mineral density (aBMD) was obtained from the analysis of body composition by dual-energy X-ray absorptiometry (DXA). Simple and multiple linear regression models were performed using the SPSS software. Results: In the crude regression analyses, the results indicated a linear relationship between all the physical fitness variables and aBMD in all body segments, but maturity-offset, sex, and lean mass percentage seemed to have an effect on these relationships. Except for the upper limb power, the other physical capacities (speed, agility, and lower limb power) were associated with aBMD in at least three body regions in the adjusted analyses. These associations occurred in the spine, hip, and leg regions, and the aBMD of the legs presented the best association magnitude (R 2). Conclusion: There is a significant association between speed, agility, and musculoskeletal fitness, specifically the lower limb power and aBMD. That is, the aBMD is a good indicator of the relationship between fitness and bone mass in children, but it is essential to consider specific fitness variables and skeletal regions.

PurposeThere is no consensus in literature data about the influence of biological maturation (BM) on swim performance in young athletes. We analysed the relationship of BM, upper-limb power (ULP), and lower-limb power (LLP) with adolescent athletes’ performance in crawl swim.MethodsThis observational study determined the BM of 16 competitive swimmers (50% males and 50% females; 12.90 ± 0.88 years) by a mathematical model based on bone age and anthropometric measures. ULP and LLP were established by the horizontal launch test and the vertical and countermovement jump tests on a force platform, respectively. Swim performance was evaluated by the average speed in a 100-m crawl sprint.ResultsBM was related to ULP (males: &lt;i&gt;r&lt;/i&gt; = 0.76, &lt;i&gt;p&lt;/i&gt; = 0.001; females: &lt;i&gt;r&lt;/i&gt; = 0.39, &lt;i&gt;p&lt;/i&gt; = 0.02), LLP (males: vertical jump &lt;i&gt;r&lt;/i&gt; = 0.80, &lt;i&gt;p&lt;/i&gt; = 0.02, countermovement jump &lt;i&gt;r&lt;/i&gt; = 0.48, &lt;i&gt;p&lt;/i&gt; = 0.02; females: vertical jump &lt;i&gt;r&lt;/i&gt; = 0.30, &lt;i&gt;p&lt;/i&gt; = 0.04, countermovement jump &lt;i&gt;r&lt;/i&gt; = 0.80, &lt;i&gt;p&lt;/i&gt; = 0.01), and crawl swim performance (males: &lt;i&gt;r&lt;/i&gt; = –0.91, &lt;i&gt;p&lt;/i&gt; = 0.001; females: &lt;i&gt;r&lt;/i&gt; = –0.72, &lt;i&gt;p&lt;/i&gt; = 0.04). BM had a 87% contribution to crawl swim performance in males and a 66% contribution in females. ULP and LLP showed &lt; 50% contribution to crawl swim performance in both females and males.ConclusionsBM was associated with crawl swim performance of adolescent athletes of both sexes. BM exhibited a stronger contribution to crawl swim performance than ULP and LLP in adolescent swimmers at the puberty window.

The objective of this study was to investigate the association between physical fitness and body mass index categories (obesity, OB; overweight, OW; normal-weight, NW; and underweight, UW) in prepubertal children. Anthropometric and physical fitness characteristics were collected from a convenience sample of 30472 Italian schoolchildren (6–11 years old). Six field-based tests were used: Léger, agility shuttle, long jump, frontal throw of the basketball, Sit & Reach and standing balance. Significant differences were found in the anthropometric characteristics, physical fitness and weight status prevalence between girls and boys (p<0.05) and, except for flexibility, by age class (p<0.05). Obese children performed worse than their NW counterparts in aerobic capacity (p<0.001), agility (p<0.001), muscular power of the lower limb (p<0.001) and balance (p<0.001). Conversely, children with obesity showed greater upper limb power than NW children (p<0.001). The discrepancy in physical fitness between OB and NW children increased in older girls (flexibility, p = 0.002; muscular power of the lower and upper limb, p = 0.002 and p = 0.005) and boys (aerobic capacity, p = 0.009; agility, p = 0.006; standing balance, p = 0.019; muscular power of the lower and upper limb, p<0.001 and p = 0.011) compared to their younger counterparts. On the other hand, UW children performed worse than NW children mainly in terms of muscular power of the arms (p<0.001). Additionally, there was an increasing disparity in the frontal throw test scores of UW and NW girls (p = 0.003) and boys (p = 0.011) in older children compared to younger children. In conclusion, the effect of body mass index on children’s physical fitness intensifies with age. OB and OW negatively affect aerobic capacity, agility, lower limb power and balance but positively affect upper limb power. UW negatively affects upper limb power. This study underscores the importance of preventing childhood OW, OB, and UW in early life to promote children’s health and proper fitness development.

Background and Study Aim. Anaerobic power is a key determinant of athletic performance, influencing an athlete’s ability to perform short bursts of high-intensity activity. Monitoring and evaluating anaerobic power are essential for optimizing training strategies and improving competitive performance. Therefore, this study aims to compare the anaerobic power of the lower and upper extremities in female football players. Material and Methods. A total of 10 female football players, actively competing in Konya, voluntarily participated in this study. All participants were university students and engaged in regular training and competition schedules. The participants had an average age of 19.50±1.84 years, an average height of 163.90±5.38 cm, and an average weight of 54.00±3.91 kg. To assess anaerobic power in both upper and lower limbs, the Wingate Anaerobic Power Test (WAnT) was utilized. The test was conducted using a Monark 891E arm and 894E leg cycle ergometer. All data collected from the tests were automatically recorded by the system. For statistical analysis, SPSS version 27.0 was used. A paired sample t-test was applied to compare upper and lower extremity anaerobic power outputs. A p-value of &lt;0.05 was considered statistically significant. Results. A statistically significant difference in favor of the lower extremities was found when comparing both absolute and relative peak and mean power values of the upper and lower extremities (p &lt; 0.05). Peak power in the legs (402.76 ± 69.90 W) was significantly higher than in the arms (243.75 ± 71.62 W), with a large effect size (d = 3.63). Similarly, mean power was greater in the lower extremities (300.78 ± 53.04 W) compared to the upper extremities (127.01 ± 51.43 W, d = 4.53). When considering relative values, relative peak power in the legs (7.39 ± 0.92 W/kg) was significantly higher than in the arms (4.39 ± 1.12 W/kg, d = 3.46), and relative mean power also showed a significant difference (legs: 5.51 ± 0.66 W/kg; arms: 2.27 ± 0.81 W/kg, d = 4.71). Conclusions. The findings of this study confirm that female football players generate significantly greater anaerobic power in their lower extremities compared to their upper extremities. These results highlight the dominant role of lower-body power in football-specific movements such as sprinting, jumping, and rapid directional changes. Understanding these differences can help in optimizing training strategies for female football players.

This study aimed to examine the impact of an AI-designed functional resistance training program on selected physical and physiological variables among students enrolled in a swimming course in Jordan. A quasi-experimental pre-test–post-test design was used with two groups: experimental and control. The sample included 19 male students from Amman Al-Ahliyya University and Jadara University, with a mean age of 22.1 years. The experimental group (10 students from Al-Ahliyya Amman University) participated in a six-week AI-designed functional resistance training program, conducted three times per week. Each session consisted of 40 minutes of functional training followed by 30 minutes of swimming drills. In contrast, the control group (9 students from Jadara University) only engaged in swimming drills for 60 minutes per session. Physical variables measured included hand grip strength, upper and lower limb power and endurance, and trunk flexibility. Physiological variables included body mass, body mass index, body fat percentage, muscle mass, total body water, protein percentage, basal metabolic rate, bone mass, resting heart rate, systolic and diastolic blood pressure, visceral fat, and fasting blood glucose. Measurements were taken before and after the intervention. Statistical analysis revealed no significant differences between the experimental and control groups in the post-test measurements across all variables. Despite this, the experimental group showed significant improvements in several physical and physiological variables, including upper and lower limb power, trunk flexibility, body mass, along with a reduction in resting heart rate. In contrast, the control group showed significant improvements in bone mass and upper limb endurance.

The aim of this study was to investigate the effects of obesity on upper and lower limb functional strength and power in children, and to determine whether the ability to perform the daily activity of rising from a chair was compromised in obese children. It was hypothesised that obese children would display less upper and lower limb functionality compared to their non-obese counterparts. Upper and lower limb strength and power of 43 obese children (aged 8.4 +/- 0.5 y, BMI 24.1 +/- 2.3 kg/m(-2)) and 43 non-obese controls (aged 8.4 +/- 0.5 y, BMI 16.9 +/- 0.4 kg/m(-2)) were assessed using age-appropriate field-based tests: arm push/pull ability; basketball throw; vertical jump (VJ), and standing long jump (SLJ) performance. Functional lower limb strength was assessed for 13 obese and 13 non-obese children by quantifying their chair rising ability. Although obese children displayed significantly greater upper limb push (9.3 +/- 2.3 kg) and pull strength (9.6 +/- 3.0 kg) than their non-obese peers (push: 8.8 +/- 2.2 kg; pull: 8.8 +/- 2.3 kg; p < or = 0.05), their VJ (22.1 +/- 4.3 cm) and SLJ (94.6 +/- 12.8 cm) performance was significantly impaired relative to the non-obese children (VJ: 24.7 +/- 4.0 cm; SLJ: 101.7 +/- 14.0 cm; p < or = 0.05). Obese children spent significantly more time during all transfer phases of the chair rising task, compared to the non-obese children. Lower limb functionality in young obese children is impeded when they move their greater body mass against gravity.

Blood flow restriction (BFR) training stimulates muscle size and strength by increasing muscle activation, accumulation of metabolites and muscle swelling. This method has been used in different populations, but no studies have evaluated the effects of training on muscle power and submaximal strength (SS) in accounted for the menstrual cycle. The aim of this study was to analyse the effect of strength training (ST) with BFR on the muscle power and SS of upper and lower limbs in eumenorrheic women. Forty untrained women (18-40years) were divided randomly and proportionally into four groups: (i) high-intensity ST at 80% of 1RM (HI), (ii) low-intensity ST at 20% of 1RM combined with partial blood flow restriction (LI + BFR), (iii) low-intensity ST at 20% of 1RM (LI) and d) control group (CG). Each training group performed eight training sessions. Tests with a medicine ball (MB), horizontal jump (HJ), vertical jump (VJ), biceps curls (BC) and knee extension (KE) were performed during the 1st day follicular phase (FP), 14th day (ovulatory phase) and 26-28th days (luteal phase) of the menstrual cycle. There was no significant difference among groups in terms of the MB, HJ, VJ or BC results at any time point (P>0·05). SS in the KE exercise was significantly greater in the LI + BFR group compared to the CG group (P=0·014) during the LP. Therefore, ST with BFR does not appear to improve the power of upper and lower limbs and may be an alternative to improve the SS of lower limbs of eumenorrheic women.

Introduction: Whether high-intensity interval training (HIIT) can improve lean mass, strength, and power of the lower limbs in young and older people is still under discussion. This study aimed to determine the effect of HIIT on lean mass, maximal strength, rate of force development (RFD), and muscle power of both lower limbs in healthy young and older adults. Secondarily, to compare the effects of HIIT between dominant vs. non-dominant lower limbs of each group. Materials and methods: Healthy older (n = 9; 66 ± 6years; BMI 27.1 ± 3.1kgm-2) and young (n = 9; 21 ± 1years; BMI 26.2 ± 2.8kgm-2) men underwent 12weeks of HIIT (3x/week) on a stationary bicycle. The evaluations were made before and after the HIIT program by dual energy X-ray absorptiometry (DEXA), anthropometry, force transducer and, Sit-to-Stand test. The outcomes analyzed were limb lean mass, thigh circumference, maximal voluntary isometric strength, RFD (Time intervals: 0-50, 50-100, 100-200, and 0-200ms), and muscle power in both lower limbs. Results: After 12weeks of HIIT, non-dominant limb (NDL) showed increase in limb lean mass (p < 0.05) but without interaction (time*group). HIIT showed a gain in absolute maximal strength and also when adjusted for thigh circumference in the dominant lower limb (DL) in both groups. The RFD0-200ms showed differences between groups but without interaction. The RFD0-50ms of the NDL showed post-training improvements (p < 0.05) in both groups. Only the older group showed differences between DL vs. NDL in most of the RFD obtained post-intervention. In addition, post-HIIT muscle power gain was observed in both groups (p < 0.05), but mainly in older adults. Conclusion: HIIT promotes increases in lean mass, maximal strength, early RFD, and lower limb muscle power in healthy older and young individuals. The differences shown between the DL and the NDL must be analyzed in future studies.

Explainable artificial intelligence (XAI) models with Shapley additive explanation (SHAP) values allows multidimensional representation of movement performance interpreted on both global and local levels in terms understandable to human intuition. We aimed to evaluate the swimming performance (World Aquatics points) predictability of a combination of demographic, training, anthropometric, and biomechanical variables (inputs) through XAI. Forty-seven swimmers (16 males), after completing a training questionnaire (background and duration) and anthropometric assessment, performed, in a randomised order, a 25 m front crawl and three countermovement jumps, at maximal intensity. The predicted World Aquatics points (516 ± 159; mean ± SD) were highly correlated (r2 = 0.93) with the 529 ± 158 actual values. The duration of swimming training was the most important variable (95_SHAP), followed by the countermovement jump impulse (37_SHAP), both with a positive effect on performance. In contrast, a higher percentage of fat mass (21_SHAP) corresponded to lower World Aquatics points. Impulse, when interpreted together with dryland training duration and stroke rate, shows the positive effects of upper and lower limb power on swimming performance. Height should be interpreted together with arm span when exploring positive effects of anthropometric traits on swimming performance. The XAI modelling highlights the usefulness of specific training, technical and physical testing, and anthropometric factors for monitoring swimmers.