Abstract
n addition to various physiological parameters that affect athletes’ performance and outcomes, anthropometric variables are also related to athletic performance. In par- ticular, the length of the lower limbs is closely associated with human mobility and stride length, making it a crucial factor in various movement-based sports. Furthermore, favor- able body proportions may vary depending on the sport, and a better understanding of how body proportions affect physical performance across different levels of athletes is needed. Therefore, the purpose of this study is to investigate the relationship between leg length and physical performance by measuring body dimensions (tibia and femur length) for athletes categorized by sports characteristics and performance levels. The study involved 312 athletes from 23 sports, divided into three activity levels. Anthropometric measure- ments of tibia and femur length were taken, and physical performance tests, including strength, muscular endurance, cardiovascular endurance, agility, explosiveness, flexibil- ity, and anaerobic power, were conducted in the laboratory. The relationships between variables (leg length×physical performance) were analyzed using Pearson’s correlation coefficients. Leg length via activity levels was verified through one-way analysis of variance (ANOVA) testing, including normality and homoscedasticity. Post hoc analysis (Tukey’s HSD test) was used to compare specific differences when significance was found. Statistical significance was accepted at the 0.05 level. As a result, an increase in lower limb length was
length×physical performance) were analyzed using Pearson’s correlation coefficients. Leg length via activity levels was verified through one-way analysis of variance (ANOVA) testing, including normality and homoscedasticity. Post hoc analysis (Tukey’s HSD test) was used to compare specific differences when significance was found. Statistical significance was accepted at the 0.05 level. As a result, an increase in lower limb length was found to have a relationship with physical performance components, including power (r = 0.302,p= 0.001), agility (r =−0.289,p= 0.001), endurance capacity (r = 0.168,p= 0.005), and anaerobic peak power (r = 0.265,p= 0.001). However, in the LD group, which consisted of athletes in static sports, no significant relationship was observed between lower limb length and physical performance components. However, in the LD group, which included static sports, no significant relationship was found between lower limb length and physical performance components. These findings may serve as foundational data for athlete talent identification and performance prediction. Keywords:lower limb; athletic performance; strength; power; anthropometric measurement 1. Introduction As humans age, various parts of the body naturally grow and mature. Athletes, from a young age, select a specific sport and develop physically in conjunction with that sport. During their growth phase, it is expected that athletes’ bodies will respond to the contin- uous stimuli of the chosen sport, growing in a way that maximizes athletic performance. In addition to various physiological mediators that influence athletic performance and outcomes, anthropometric variables such as body fat and lean mass [1], arm circumfer- ence [2], and skinfold thickness [3,4] are also known to be related to athletic performance. Appl. Sci.2025,15, 3836 https://doi.org/10.3390/app15073836
Appl. Sci.2025,15, 3836 2 of 11 The length of the femur and tibia, especially in the lower body, is closely related to human mobility and stride length, making it an important factor in sports that require movement on the ground [5]. Recent studies have reported a positive correlation between the absolute and relative total lengths of the upper leg (femur) and lower leg (tibia) with running performance [6]. This suggests that longer legs require less energy to accelerate leg movements, allowing endurance runners to move more efficiently and economically [7–9]. Leg length is an im- portant morphological factor that influences stride length [5,10], and as leg length increases, stride length also increases, potentially enhancing sprint performance [11]. Additionally, Nasrulloh et al. [12] found significant differences in lower body power between volleyball players with longer and shorter leg lengths, indicating that a longer lower body length is associated with greater lower body power. However, according to the data analysis of Bakti et al. [13], a negative correlation of−0.369 was found between leg length and leg explosive power, suggesting that shorter legs may be more capable of generating explosive power. The conflicting results of these studies, which were conducted on athletes, indicate that controversy over the conclusions still remains. Traditionally, body measurements using tape measures have been employed to assess leg length, but this method has faced issues with ambiguity (low reliability) and technical limitations. Recently, advancements in equipment have introduced alternative methods such as leg length measurement using Dual Energy X-ray Absorptiometry (DEXA) [14] or the use of Magnetic Resonance Imaging (MRI) to measure the length of the femur or tibia and evaluate their relationship with physical performance [15]. However, while DEXA and MRI provide high accuracy and reliability, the high cost of these methods makes them less practical for use in sports and health sciences, where timely data are crucial. Therefore, it is suggested that using specialized body measurement equipment, such as the Martin Anthropometer operated by a trained expert, may offer a more cost-effective and efficient solution for practical applications in the field. Based on the results of previous
cost of these methods makes them less practical for use in sports and health sciences, where timely data are crucial. Therefore, it is suggested that using specialized body measurement equipment, such as the Martin Anthropometer operated by a trained expert, may offer a more cost-effective and efficient solution for practical applications in the field. Based on the results of previous studies, it is evident that leg length (thigh, lower leg) is strongly correlated with endurance capacity, sprinting ability, lower body power, and jumping ability [8,12,15,16]. However, prior studies have primarily focused on runners or athletes from a single sport, and most have looked at the total leg length rather than segment-specific measurements. There is a noticeable gap in the research that considers the diversity of sports and the specific characteristics of each different sport, as well as studies exploring the relationship between agility and other physical elements. It is likely that there is an advantageous leg length depending on the nature of each sport, and a deeper understanding of the interaction between leg length and physical performance in athletes across various levels is needed. This study was conducted with the hypothesis that leg length could have an impact on agility, speed, and muscular power. The results of this study could play a crucial role in identifying potential athletes across various sports, guiding sport selection, and developing effective training programs tailored to specific sports. Therefore, this study aimed to identify the correlation between leg length and physical performance to help develop a deeper understanding of the physical factors influencing athletic performance by classifying athletes based on sports characteristics and dynamic levels [17,18] and to enhance our understanding of the relationship between leg length and physical performance through anthropometric measurements. 2. Materials and Methods 2.1. Participants This study was conducted at the Center for Sport Science in Incheon. A total of 312 elite athletes (179 males and 133 females) were recruited for the study. Participants were selected
and Methods 2.1. Participants This study was conducted at the Center for Sport Science in Incheon. A total of 312 elite athletes (179 males and 133 females) were recruited for the study. Participants were selected
Appl. Sci.2025,15, 3836 3 of 11 from the following sports: archery (n = 5), diving (n = 1), gymnastics (n = 3), judo (n = 15), shooting (n = 13), weightlifting (n = 4), baseball (n = 28), fencing (n = 6), seppak takraw (n = 8), running sprinter (n = 13), Taekwondo (n = 14), tennis (n = 8), wrestling (n = 10), badminton (n = 6), field hockey (n = 11), fin swimming (n = 8), soccer (n = 22), swimming (n = 16), team handball (n = 83), boxing (n = 7), cycling (n = 17), modern pentathlon (n = 5), and rowing (n = 9). Athletes with a history of cardiac, pulmonary, or inflammatory diseases or other medical contraindications were excluded from the study. All participants who agreed to participate were provided with a detailed description of the study, including its purpose and the methods used, in accordance with the ethical standards outlined in the Declaration of Helsinki. Additionally, all participants signed an informed consent form prior to participation. This study was approved by the University’s Institutional Review Board for Human Subjects (1041459-202411-HR-008-01). 2.2. Procedures The participants (athletes) visited the laboratory as teams based on their respective sports disciplines. During their visit, anthropometric measurements, including lower limb length (tibia length and femur length) and body composition assessments (height, weight, body fat mass, etc.) were conducted. After a sufficient warm-up, tests for basic physical performance (muscular strength, muscular endurance, muscular power, cardiorespiratory endurance, agility, and flexibility) and anaerobic power (peak power) were performed. The collected data were categorized according to the classification table of sports disciplines based on activity level, as outlined by Pelliccia et al. [17] and Mitchell et al. [18]. Participants were grouped into three categories: low dynamic sports (LD; n = 41), moderate dynamic sports (MD; n = 87), and high dynamic sports (HD; n = 184). The participant information is presented in Table. Table 1.The characteristics of the subjects and their classification according to activity level. Variable Low Dynamic Sports (LD; n = 41) Moderate Dynamic Sports (MD; n = 87) High Dynamic
categories: low dynamic sports (LD; n = 41), moderate dynamic sports (MD; n = 87), and high dynamic sports (HD; n = 184). The participant information is presented in Table. Table 1.The characteristics of the subjects and their classification according to activity level. Variable Low Dynamic Sports (LD; n = 41) Moderate Dynamic Sports (MD; n = 87) High Dynamic Sports (HD; n = 184) Total Athletes (N = 312) Age (years) 17.46 ±0.60 17.87 ±1.34 18.04 ±1.93 17.92 ±1.67 Height (cm) 166.94 ±7.37 171.36 ±8.62 169.41 ±7.33 169.63 ±7.81 Weight (kg) 67.89 ±15.81 65.85 ±15.74 68.54 ±12.92 67.70 ±14.15 BMI (kg/m 2 ) 24.20±4.43 22.37 ±4.58 23.77 ±3.39 23.43 ±3.95 Career (years) 7.46 ±0.60 7.55 ±1.53 7.94 ±1.48 7.84 ±1.73 I. Low static Baseball Badminton Fencing Field hockey Seppak takraw Running (sprint) Taekwondo Tennis II. Moderate static Fin swimming Diving Soccer Gymnastics Swimming Judo Team handball Shooting III. High static Weightlifting Wrestling Boxing Cycling Modern pentathlon Rowing Values are presented as Mean±SD, Abbreviations: BMI: body mass index. The lengths of the leg were normalized with body height to calculate relative leg lengths, which were expressed as percentages (i.e., the % of body height).
Appl. Sci.2025,15, 3836 4 of 11 2.2.1. Body Composition and Anthropometric Measurements (Femur and Tibia Length) Leg length measurements were conducted by trained professionals using a sliding caliper (Martin’s Anthropometer, Japan), as shown in Figure. The femoral length was measured as the distance between the tip of the greater trochanter and the distal end of the lateral condyle of the femur. The tibial length was measured as the distance between the proximal end of the lateral condyle and the distal inferior surface of the tibia (lateral malleolus). Anthropometric measurements included body weight (BW), body mass index (BMI), and body fat percentage (%FAT); these measurements were obtained using the body composition analyzer InBody 770 (InBody Co., Seoul, Republic of Korea) using the simul- taneous multi-frequencies impedance measurement method. To increase measurement accuracy, alcohol consumption and strenuous exercises on the day before the measurement and any form of drinking or eating 2 h before the measurement was prohibited.Appl. Sci. 2025, 15, x FOR PEER REVIEW 4 of 12 Judo Team handball Shooting III. High static Weightlifting Wrestling Boxing Cycling Modern pentathlon Rowing Values are presented as Mean ± SD, Abbreviations: BMI: body mass index. The lengths of the leg were normalized with body height to calculate relative leg lengths, which were expressed as per- centages (i.e., the % of body height). 2.2.1. Body Composition and Anthropometric Measurements (Femur and Tibia Length) Leg length measurements were conducted by trained professionals using a sliding caliper (Martin’s Anthropometer, Japan), as shown in Figure 1. The femoral length was measured as the distance between the tip of the greater trochanter and the distal end of the lateral condyle of the femur. The tibial length was measured as the distance between the proximal end of the lateral condyle and the distal inferior surface of the tibia (lateral malleolus). Anthropometric measurements included body weight (BW), body mass index (BMI), and body fat percentage (%FAT); these measurements were obtained using the body composition analyzer InBody 770 (InBody Co., Seoul, Republic of Korea) using the simultaneous multi-frequencies impedance measurement method. To increase measure- ment accuracy, alcohol consumption and strenuous exercises
condyle and the distal inferior surface of the tibia (lateral malleolus). Anthropometric measurements included body weight (BW), body mass index (BMI), and body fat percentage (%FAT); these measurements were obtained using the body composition analyzer InBody 770 (InBody Co., Seoul, Republic of Korea) using the simultaneous multi-frequencies impedance measurement method. To increase measure- ment accuracy, alcohol consumption and strenuous exercises on the day before the meas- urement and any form of drinking or eating 2 h before the measurement was prohibited. Figure 1. The measurement position of upper leg length and lower leg length. 2.2.2. Basic Physical Performance Assessments The athletes underwent basic physical performance assessments (muscular strength, muscular endurance, muscular power, cardiorespiratory endurance, agility, and flexibil- ity) using sensor-based equipment. To evaluate leg power, the standing long jump and Sargent jump tests [19] were conducted. Lower body agility was assessed using the 10 m Figure 1.The measurement position of upper leg length and lower leg length. 2.2.2. Basic Physical Performance Assessments The athletes underwent basic physical performance assessments (muscular strength, muscular endurance, muscular power, cardiorespiratory endurance, agility, and flexibility) using sensor-based equipment. To evaluate leg power, the standing long jump and Sargent jump tests [19] were conducted. Lower body agility was assessed using the 10 m shuttle run and side-step test [20,21]. Cardiovascular endurance was measured with the shuttle run test [22], while flexibility was evaluated using the sit-and-reach test [23]. Grip strength was used to assess muscular strength [24]. 2.2.3. Anaerobic Test The Wingate anaerobic test (WAnT) was used following experiments performed by Castañeda-Babarro [25]. The WAnT was performed on a cycle ergometer (Monark 824 E, Monark, Sweden) equipped with a photoelectric sensor for recording 1.0 kg resistance baskets and flywheel revolutions. Data for each 30 s WAnT were collected using POWER software (SMI, St. Cloud, MN, USA) and an IBM-compatible microcomputer. Each partici- pant completed a self-selected stretching exercise and a five-minute cycle at the ergometer
Appl. Sci.2025,15, 3836 5 of 11 without applying a time limit. At the end of the 1 min warm-up, each participant performed an “all-out” sprint for 4 to 5 s to simulate the actual test. Before starting the WAnT, the resistance for each participant was calculated using a body weight of kilograms multiplied by 7.5% for males and 5% for females, and the determined amount was placed in the basket. At the start of the test, the assistant lifted the resistance basket, and no resistance was applied to the flywheel; each participant was instructed to begin pedaling to reach the maximum rpm at the end of the 5 s countdown. The resistance basket was released, and data collection began, subsequently ending after 30 s [26]. Among the test results, we analyzed peak power data in relation to leg length. 2.3. Statistical Analysis All values are presented as means with standard deviations. GraphPad Prism 10.0 (GraphPad Software Inc., San Diego, CA, USA) was used for the statistical evaluation and preparation of graphs. Data analysis was conducted with the Statistical Package for the Social Sciences, version 23.0 (IBM SPSS Statistics for Windows, Version 23.0: IBM Corp., Armonk, NY, USA). The relationships among variables (leg length×physical performance) were analyzed using Pearson’s correlation coefficients. Leg length by activity levels were verified through one-way analysis of variance (ANOVA) testing, including normality and homoscedasticity. Post hoc analysis (Tukey’s HSD test) was used to compare specific differences (leg length between groups) when significance was found. Statistical significance was accepted at the 0.05 level. 3. Results The results of the analysis on leg length differences by sport type revealed that the absolute lengths of the tibia and tibia + femur were significantly shorter in the LD group compared to the MD group (p= 0.019;p= 0.011, respectively). However, no significant differences were observed between the groups when leg length was expressed as a relative value to height (Table). Table 2.Differences in leg length according to activity level. Variable Groups LD (n = 41) MD (n = 87) HD (n = 184) F p -Value absolute leg length tibia (cm)
to the MD group (p= 0.019;p= 0.011, respectively). However, no significant differences were observed between the groups when leg length was expressed as a relative value to height (Table). Table 2.Differences in leg length according to activity level. Variable Groups LD (n = 41) MD (n = 87) HD (n = 184) F p -Value absolute leg length tibia (cm) 34.80±2.86 b 36.35±2.93 a 35.86±3.09 3.695 0.026 * femur (cm) 42.84 ±3.05 44.17 ±3.72 43.69 ±2.71 2.655 0.072 femur + tibia (cm) 77.63±4.93 b 80.52±5.90 a 79.55±4.97 4.244 0.015 * relative leg length tibia, % of body length 20.82 ±1.10 21.20 ±1.10 21.15 ±1.26 1.495 0.226 femur, % of body height 25.65 ±1.28 25.75 ±1.23 25.78 ±1.01 0.240 0.787 femur + tibia, % of body height 46.47±1.41 46.95 ±1.48 46.93 ±1.40 1.869 0.156 LD: low dynamic sport; MD: moderate dynamic sport; HD: high dynamic sport. Significance (p< 0.05) is denoted by the following: a : relative to LD, b : relative to MD. Differences between groups: *:p< 0.05. A significant correlation was observed between the tibia length relative to height and physical performance variables, including muscular strength, muscular endurance, muscular power, agility, flexibility, and lower limb anaerobic peak power (p< 0.05 for both).
Appl. Sci.2025,15, 3836 6 of 11 A significant correlation was found between femur length relative to the height and physical performance variables, specifically muscular power and flexibility (p< 0.05 for both). A significant correlation was observed between the tibia + femur length relative to the height and physical performance variables, including muscular strength, muscular power, agility, flexibility, cardiorespiratory endurance, and lower limb anaerobic peak power (p< 0.05 for both) (Table; Figure).Appl. Sci. 2025, 15, x FOR PEER REVIEW 7 of 12 MD 0.184 0.503 ** 0.426 ** −0.317 ** 0.493 ** 0.196 −0.239 * 0.322 ** 0.458 ** HD −0.145 0.183 * 0.180 * −0.238 ** 0.145 0.085 −0.504 ** 0.347 ** 0.248 ** SU: sit-up test; SLJ: standing long jump; SJ: Sargent jump test; 10mRT: 10 m round trip; SS: side-step test; 20mSRT: 20 m shuttle run; SR: Seated Reach; GS: grip strength; PP: peak power. *: p < 0.05; **: p < 0.01. (A) (B) (C) Figure 2. Relationships between the relative leg lengths and physical performance. (A) Tibia length; (B) femur length; and (C) tibia + femur length. The leg lengths were normalized with body height to calculate relative leg lengths, which were expressed as percentages (i.e., the % of body height). In the correlation analysis between relative leg length by sport group and physical performance, tibia length showed a stronger correlation with agility (10 m shuttle run test) in the HD group. On the other hand, femur length exhibited a higher correlation with muscular power (standing long jump test) in the MD group compared to the other groups (Table 3; Figure 3). Figure 2.Relationships between the relative leg lengths and physical performance. (A) Tibia length; (B) femur length; and (C) tibia + femur length. The leg lengths were normalized with body height to calculate relative leg lengths, which were expressed as percentages (i.e., the % of body height).
Description
The study analyzes how leg length affects athletic performance across various sports.