Introduction

The body composition is one of the determining factors of physical performance of athletes, including cyclists1. In this sense fat accumulation, especially in the abdominal area, is closely linked to metabolic disturbances2,which are well known for impairing performance. A better body composition, characterized by a greater percentage of muscle mass and an adequate percentage of body fat, tends to improve physical performance in several ways. This includes increasing aerobic capacity and muscular endurance, which are the main ways to assess cyclists’ exercise capacity3. Ensuring optimal body composition is essential not only for the athlete’s performance but also for their longevity in sport, health, and general well-being4.

The assessment of body composition is fundamental for measuring the efficiency of a diet and evaluating the nutritional status of athletes. Bioelectrical impedance analysis (BIA) has gained prominence in both sports and research5. In many sports, athletes gain an advantage by altering their body mass or body composition. For example, sports such as gymnastics, which have aesthetic and gravitational components, depend on specific anthropometric characteristics for success6. Additionally, weight-classified sports require athletes to maintain a specific range of body mass7. Therefore, athletes adjust their training and diet according to the demands of their sport, making the monitoring of body composition necessary for accurate assessments.

Additionally, proper hydration is vital for optimal performance as it enhances muscle function, coordination, and endurance, supporting cardiovascular function and temperature regulation8.Understanding the ideal physique for each athlete and avoiding harmful practices that can cause rapid and/or extensive changes in body composition is of paramount importance9.With this purpose, BIA has gain significant popularity in the context of several sports, including badminton10, handball11, and soccer12. In view of the above, it is important to assess the anthropometric aspects of mountain bike cyclists, as these directly affect both performance and results in competitions. Therefore, the objective of this study was to analyze the influence of body composition on physical performance in mountain bike athletes.

The hypothesis of this study is that the body composition of mountain bike athletes, including fat percentage, muscle mass and hydration levels, directly affect physical performance. Greater muscle mass is expected to result in better race times and more strength in the upper and lower limbs, while a higher percentage of body fat is associated with worse performance.

Results

A total of 151 participants began this study, but only 83 (72 men and 11 women) completed all stages. Table 1 presents the participants’ characteristics. The participants’ test time was 168.09 ± 30.55 min.

Table 1 Characteristics of mountain bike athletes (n=83)
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Correlation analysis showed a significant relationship between standing long jump performance and body composition variables (Fig. 1).

Fig. 1
figure 1

Correlation between horizontal jump and body fat (A), skeletal muscle mass (B), total body water (C), intracellular water (D), and extracellular water (E). The r and p values are shown in each figure.

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There was a negative correlation between body fat percentage and skeletal muscle mass with the strength of both the dominant and non-dominant hands, as shown in Fig. 2. Similarly, intracellular, extracellular, and total body water were positively related to the strength of both hands (Fig. 3).

Fig. 2
figure 2

Correlation between dominant hand strength and body fat percentage (A), non-dominant hand strength and body fat percentage (B), dominant hand strength and skeletal muscle mass (C), non-dominant hand strength and skeletal muscle mass (D). The r and p values are shown in each figure.

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Fig. 3
figure 3

Correlation between dominant hand strength and total body water (A), non-dominant hand strength and total body water (B), dominant hand strength and intracellular water (C), non-dominant hand strength and intracellular water (D), dominant hand strength and extracellular water (E), non-dominant hand strength and extracellular water (F). The r and p values are shown in each figure.

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Finally, as seen in Fig. 4, we found a positive correlation between race time and body fat percentage (r = 0,415, p = 0,000). race time was negatively correlated with skeletal muscle (r = − 0,427, p = 0,000), as well as with water total body(r = − 0,400, p = 0,000, intracellular(r = − 0.420, p = 0.000) and extracellular water(r = − 0.370, p = 0.000).

Fig. 4
figure 4

Correlation between race time and body fat (A), skeletal muscle mass (B), total body water (C), intracellular water (D) and extracellular water (E). The r and p values are shown in each figure.

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Table 2 details the correlations between body composition and physical performance of mountain bike athletes according to sex.

Table 2 Correlation of body composition variables of mountain bike athletes, by sex, with physical performance variables.
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Discussion

The present study aimed to analyze the influence of body composition on physical performance in mountain bike athletes during a real race event. Cyclists with greater amounts of total body water, intracellular water, extracellular water, and muscle mass, and a lower percentage of fat, exhibited more strength in their upper and lower limbs and achieved shorter race times. Previous studies have also associated body composition and a lower percentage of body fat with improved cycling performance13,14. Our findings align with these results, showing that cyclists with a lower percentage of fat had better race times and more strength in their upper and lower limbs.

The data from our study align with findings by Hetherington-Rauth et al.15, which showed that bioimpedance body water measurements are associated with total muscle strength of the lower limbs and handgrip strength, indicating these parameters as useful markers for evaluating physical performance. Indeed, handgrip strength is well known as a significant indicator of physical performance and general health, being correlated with overall body strength16,17.

Supporting our findings, Arriel et al.18 found that body fat negatively influenced relative peak power output in mountain bike athletes. Similarly, it was observed that a lower percentage of body fat correlated with better physical performance in cross-country skiers19. Finally, a study pointed out that recreational Ironman ultracyclists with a lower body fat percentage achieve better race times20. Indeed, excess body fat percentages are well known for negatively affecting aerobic capacity (VO2 max), leading to quicker fatigue and decreased endurance21. Furthermore, excess body fat can impair thermoregulation, causing the body to overheat more easily during intense activities22.

Trained athletes have a greater amount of body water distributed in intracellular and extracellular compartments, likely due to greater muscle mass, increased plasma volume, and muscle glycogen reserves, which can increase water transport to the muscles23. Body composition, particularly skeletal muscle mass and fat-free mass, is associated with strength and power24, which supports the results found in our study. Total body water and its constituents (intracellular water and extracellular water) provide an additional approach to monitor possible changes in body composition linked to physical performance. Silva et al.25 found that intracellular water showed a moderate correlation with vertical jump performance, indicating it as a good predictor of lower limb performance. Jump tests are often used to assess neuromuscular fatigue, especially fatigue induced by ultradistance events26. In this sense, Correas-Gómez et al.27 found that athletes with better quality and distribution of body water had better vertical jump performance while Donahue et al.28 found that hydration status impacts both the countermovement and squat jumps. This highlights the importance of hydration status in lower limbs strength, which directly affects performance in mountain bike athletes.

Cyclists with greater muscle volume in the quadriceps tend to have greater strength, which can result in better physical performance during sprints and short-duration efforts29. Additionally, greater muscle mass may be associated with higher anaerobic energy storage capacity, allowing cyclists to maintain intense efforts for longer periods before fatigue sets in14. Although cycling is a sport that demands cardiovascular fitness and efficiency, muscle mass remains a critical component for achieving and maintaining high performance levels, particularly in terms of power production and endurance. In this sense, incorporating lower-body heavy strength training alongside endurance-cycling workouts can enhance both short- and long-term endurance performance. This improvement may be due to delaying the activation of less efficient type II muscle fibers, converting type IIX fibers into more fatigue-resistant IIA fibers, and increasing muscle mass and the rate of force development30 .

Regarding body composition assessment methods, dual-energy X-ray absorptiometry (DEXA) is considered the most objective and accurate device and one of the reference methods for measuring body fat percentage31.

However, its use is limited to clinical settings and is difficult to use in the field. Likewise, the scientific literature has focused mainly on healthy or pathological populations, but not on athletic populations.As for BIA systems, these are methods that allow non-invasive measurements of body composition with advantages over DEXA of portability, simplicity, speed, safety and low cost. However, measurements are conditioned by sex, age, ethnicity, body fat percentage, hydration level and day and time of measurement, which requires systematic conditions for a correct assessment32.

This study presents limitations that should be addressed in future research. Firstly, the cross-sectional design limits the ability to establish causality. Longitudinal studies are recommended to better understand the causal relationships between changes in body composition and performance over time. Secondly, the sample size was relatively small and included a higher proportion of males, which may limit the generalizability of the findings to a broader population of cyclists. Future research should aim to include a larger and more diverse sample to validate these results. Additionally, the use of bioimpedance analysis for body composition assessment, while practical, may not be as accurate as other methods such as DEXA scans. Employing more precise measurement techniques could enhance the reliability of the findings. Lastly, the study focused solely on mountain bike athletes, so exploring different cycling disciplines and their specific demands could provide a more comprehensive understanding of how body composition impacts cycling performance across various contexts.

Body composition significantly influences the physical performance of mountain bike cyclists, particularly in terms of lower limb strength, hand grip strength, and race time duration. Total body water, intracellular water, extracellular water, and skeletal muscle mass showed a positive correlation with standing long jump and hand grip strength. Conversely, the percentage of body fat demonstrated a negative correlation with general physical performance. Finally, race time was positively associated with body fat percentage and negatively associated with skeletal muscle mass, total body water, intracellular water, and extracellular water were negatively related to race time.

Methods

Study design

This cross-sectional study was carried out with cycling athletes who participated in a mountain bike race. The race had a total distance of 75 km, an altitude of 601 m, and was classified in the Mountain Bike Marathon (XCM) format. The completion time of the race was measured by the organization using an electronic timing system, supplemented manually by staff, and included filming and a finish judge. One day before the race, the study participants underwent anthropometric evaluation, body composition analysis, and physical tests to assess the strength of their lower and upper limbs.

Subjects

83 cyclists (11 women) aged between 18 and 60 years participated in the study. They had been training for at least one year, with a weekly frequency of at least four training sessions and a minimum volume of 120 km per week. Participants who had any kind of musculoskeletal injury that would prevent their performance in the tests were excluded from the study. All procedures were approved by the Research Ethics Committee of the Federal University of Piauí (protocol no. 6,494,725). All methods were performed in accordance with the relevant guidelines and regulations. A survey was conducted in accordance with the Declaration of Helsinki.

All participants agreed to participate in the research and signed a Informed Consent form.

Anthropometry

Body mass was measured using a calibrated electronic scale (Filizzola PL 50, São Paulo, Brazil) with a precision of 100 g. The athlete stood on the equipment and remained upright, with arms extended along the body and head oriented in the Frankfurt plane until the evaluator recorded the measurement. Stature was measured using a stadiometer (AVANUTRI, São Paulo, Brazil) with precision of 0.1 cm. The measurement was taken with the athletes standing, with their arms extended along the body and head oriented in the Frankfurt plane. For all evaluations, the participants were asked to wear light clothing and to be barefoot.

Bioimpedance analysis

Body composition metrics, such as body fat percentage, body water levels and skeletal muscle mass, were assessed using a multi-tactile impedance meter with eight electrodes operating at 50 kHz (InBody S10, Biospace, Seoul, South Korea). The InBody S10 is a validated tool for estimating skeletal muscle mass in young individuals, comparable to the gold standard dual-energy X-ray absorptiometry33. Bioimpedance analysis was conducted with participants lying supine. They were advised to abstain from exercise, diuretics, and caffeine for 12 h, and from food or drink for 30 min prior to the measurements. Women who were menstruating were asked to notify the researchers and reschedule the exam 24 h in advance. The participants skin was cleaned with alcohol, and touch-type electrodes were placed on the thumb and middle fingers of both hands and between the anklebone and heel of both feet. Participants rested in a supine position for 10 to 15 min before the test to ensure even distribution of body water. Arms were positioned away from the trunk at a 15-degree angle, and legs were spread shoulder-width apart to prevent thigh contact. Measurements were taken in the morning in a room with controlled temperature (22–23 °C) and humidity (50–60%).

Standing long jump

The standing long jump test was conducted by securing a tape measure on the ground, perpendicular to the starting line. The starting line was marked with masking tape, with the zero point of the measuring tape at the starting line. The participant stood just behind the line, with feet parallel and slightly apart, knees slightly bent, and torso slightly leaning forward. At the signal, the participant jumped as far as possible, landing on both feet simultaneously. Each participant performed two attempts, with the best result used for evaluation. The jump distance was measured from the starting line to the heel closest to it34.

The standing long jump is a practical, inexpensive, and easy-to-administer and interpret assessment that demonstrates reliability and validity, having been recommended by the National Academy of Medicine as a measure of physical fitness35,36.

Handgrip strength test

Upper limb strength was assessed using a Crown® 100 Kgf/1 Kgf handgrip dynamometer (measuring capacity: 5 to 100 kg; resolution: 0.05 kg; accuracy: ±0.5%). Athletes were seated with shoulders adducted in a neutral position, elbows flexed at 90°, and forearms in semi-pronation. They were instructed to squeeze the device as hard as possible, with the arm remaining stationary except for flexion of the interphalangeal and metacarpophalangeal joints. Verbal encouragement was provided during the tests. Each hand (dominant and non-dominant) was measured three times, and the arithmetic mean of these measurements was used as the final value. Handgrip strength values were categorized as dominant hand (right for right-handers and left for left-handers) and non-dominant hand (left for right-handers and right for left-handers)37. The study flowchart is presented in Fig. 5.

Fig. 5
figure 5

Study flowchart.

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Statistical analysis

Data are presented as mean and standard deviation. Normality and homogeneity were verified with the Levene and Shapiro-Wilk tests respectively. Pearson’s correlation was performed to compare the relationship between body composition and physical performance. A significance level of 5% was adopted for all statistical analyses. Statistical analysis was performed using the IBM SPSS Statistics 24 software for Windows.