Abstract
und. Middle-distance running performance depends on the body's ability to efficiently utilize oxygen, maintain cardiovascular fitness, and sustain endurance
Journal of Human Movement and Sports Sciences, 13(5), 1003 - 1015. DOI: 10.13189/saj.2025.130501. Copyright©2025 by authors, all rights reserved. Authors agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License Abstract Background. Middle-distance running performance depends on the body's ability to efficiently utilize oxygen, maintain cardiovascular fitness, and sustain endurance through structured training. However, excessive training can lead to fatigue and a higher risk of injury. Diet and physiological factors like muscle composition and oxygen transport capacity can also affect performance. Objective. This study investigates how training load, aerobic capacity, and cardiovascular efficiency influence performance in middle-distance runners, while also analysing gender-based differences in race outcomes. Materials and methods. A cross-sectional study was conducted with 50 amateur middle-distance runners (25 men, 25 women) aged 21 to 28. Data collection included a questionnaire on demographics, race times, and weekly mileage, followed by physiological assessments. VO2max was measured using the Bruce Treadmill Protocol, and RHR was recorded with a digital heart rate monitor. Weekly mileage was tracked via GPS and manual lap counting. Statistical analyses included t-tests, ANOVA, Pearson’s correlation, and multiple regressions to determine performance predictors. Results. Higher weekly mileage significantly (p < 0.05) improved 1500m times, while greater VO2max was correlated with better 800m performance. Lower RHR was linked to enhanced endurance. Males ran faster than females, though no significant gender differences were found in injury rates. Dietary preferences did not significantly impact performance. Conclusion: Structured endurance training, aerobic development, and cardiovascular efficiency assessment are crucial for optimizing middle-distance performance. Implementing evidence-based training strategies can enhance athletic potential while minimizing injury risks.
1004 Analysis of Performance Determinants in Middle-Distance Runners: The Influence of Training Load, Physiological Traits, and Recovery Indicators Keywords Middle-Distance Running, VO2max, Resting Heart Rate, Training Loads, Performance Determinants, Injury Rates 1. Introduction In athletics, running athletes occupy a unique position; particularly sprinters, middle-distance runners and long-distance runners, and they need specific physical qualities like speed, endurance, power, strength, and strategy. In running events, middle-distance runners particularly require careful planning and strategy to manage their pace, distribution of energy, and time and speed control to perform in competition [1]. The performance of runners depends on the influence of training load, physiological traits, and recovery, which play a significant role in an athlete. By juggling all these factors into an optimum proportion, running athletes can excel in their particular events up to the sky. Middle-distance runners face specific challenges due to physiological traits, training load and recovery [2], [3]. Maintaining the ideal balance between aerobic and anaerobic training is crucial [4]. While running more can help improve endurance, it can also lead to overtraining, fatigue, and a greater risk of injury [5]. To maintain speed in 800m running, athletes require a high level of VO2max, effective lactate clearance, and good muscle coordination [6], [7]. Long-distance runners focus on endurance, and middle-distance runners also require balance, speed, strength, and endurance. The athletes need to recover from these required training plans. VO2max is a key determinant of middle-distance running performance as it measures how well the body uses oxygen during their workout, and an increased level of it shows enhanced cardio-respiratory conditioning [8], [9]. Several studies have demonstrated the VO 2max performance of middle-distance runners in which they indicated that with an increased VO2max, athletes are able to run faster for a prolonged period without any exhaustion [1], [10], [11], [12], [13]. In 800m and 1500m events, the aerobic capacity and anaerobic strength have been challenged alongside maximal speed and running efficiency [14]. To meet these performance demands, middle-distance runners need VO2max more than long-distance runners and sprinters. Likewise, the existing body of literature suggests that Resting Heart Rate (RHR) is another physiological
period without any exhaustion [1], [10], [11], [12], [13]. In 800m and 1500m events, the aerobic capacity and anaerobic strength have been challenged alongside maximal speed and running efficiency [14]. To meet these performance demands, middle-distance runners need VO2max more than long-distance runners and sprinters. Likewise, the existing body of literature suggests that Resting Heart Rate (RHR) is another physiological attribute that determines performance and is measured during inactivity [15], [16]. RHR signifies an individual’s cardiovascular health and fitness and helps to analyze athletes’ recovery. Tracking of RHR helps athletes and coaches recognize how effective the training regimen is, how prepared the athletes are to perform, and whether there are signs of overtraining or tiredness [17]. If athletes have regularly high RHR, it may point to too much training, inadequate recovery and physiological stress [18]. In middle-distance runners, a lower RHR reflects improved aerobic capacity, efficient heart health, and better endurance. A consistently low RHR suggests the cardiovascular system is adapting well to training [19]. Gender-based differences also may influence athletic performance, and it’s been supported by numerous studies that reported some changes, especially in middle-distance runners. Men athletes have more muscle mass, greater haemoglobin levels, and enhanced oxygen transport than women [20]. These elements affect the overall output, such as VO2max and the anaerobic threshold, which are fundamental for middle-distance running. Weekly mileage measures the total distance a runner covers over a week [21] and is associated with training volume, essential to the performance of distance running athletes [22]. In these races, anaerobic capacity, lactate tolerance, and muscle efficiency also play a key role in performance [23]. This connection is mainly strong in events like 1500m, where aerobic endurance supports runners in keeping pace and resisting fatigue. High mileage training can improve lung and heart efficiency, muscle endurance, and running efficiency for endurance events. In the case of 800m, weekly mileage has a minimal impact. An effective weekly mileage plan for middle-distance runners should be based on their running experience, distance, and training goals [24]. Elite athletes’ training includes steady runs like 120 to 170 km running each week,
training can improve lung and heart efficiency, muscle endurance, and running efficiency for endurance events. In the case of 800m, weekly mileage has a minimal impact. An effective weekly mileage plan for middle-distance runners should be based on their running experience, distance, and training goals [24]. Elite athletes’ training includes steady runs like 120 to 170 km running each week, interval workouts and recovery jogs. On 800m, runners generally focus on lower mileage, around 50 to 120 km per week [25]. Their training highlights speed work, anaerobic conditioning, and high-intensity interval training (HIIT) to increase their speed endurance. Among the overall training load, weekly mileage highly affects middle-distance athletes’ performance. Higher mileage helps to develop aerobic fitness, but it is important to equalize it with other types of training like interval training, tempo runs, and strength training [26]. Excessive mileage without correct intensity leads to overtraining, which can affect the performance of athletes and increase injury risk [27]. A well-structured training plan combines endurance mileage with speed and strength work to adapt and improve performance. Monitoring training loads can examine how much an athlete runs, the workout intensity, and recovery strategies [28]. Endurance runners or distance runners also manage energy systems to perform at high intensity over extended periods, and dietary preferences play an important role in this regard. Carbohydrate intake and protein consumption are crucial to support high-intensity and endurance workouts [29]. Dietary preferences affect energy levels, muscle recovery, and overall endurance [30]. It also builds several opportunities for nutritional plans to help them adapt to training and perform development in races.
International Journal of Human Movement and Sports Sciences 13(5): 1003-1015, 2025 1005 Considering the intake of macronutrients (like protein and carbohydrates) and micronutrients (vitamins and minerals) is effective for all athletes, especially middle-distance runners [31]. Likewise, some distance runners consume various foods, while others prefer vegetarian or vegan diets. Researchers advise that plant-based diets might not easily deliver sufficient protein and iron [32]. Conversely, other research indicates that planned vegetarian and vegan diets support athletic performance [33]. A combination of speed, endurance and efficiency is the key factor of distance runners that supports athletes to perform at their best. Numerous research studies have independently investigated factors like Weekly mileage, RHR, VO2max and Gender difference in middle-distance runners. However, further exploration of their combined effects on middle-distance runners, specifically for races like the 800m and 1500m, is required. This study gives insights into the effects of training load and physiological variables on middle-distance runners’ and the recovery of athletes. It also examines the significance of VO2max, resting heart rate, and weekly mileage on their performance on the basis of physiological traits. It also considers gender differences, dietary prevalence, and recovery techniques. Understanding the essential elements that affect middle-distance running performance, the study will provide valuable opinions on training technologies to reduce the risk of overtraining and injury. This study aims to analyze the combined influence of training load, physiological traits, and recovery indicators specifically VO2max, resting heart rate, weekly mileage, and gender differences on the performance of middle-distance runners in 800m and 1500m events. 2. Materials and Methods 2.1. Research Design An observational cross-sectional methodology was used to evaluate which factors most influence middle-distance running performance outcomes. A multiphase data collection was used to analyse the variables. Participants completed a scheduled questionnaire during the first phase and underwent some physiological measurements in the second phase. 2.2. Participants This study includes fifty amateur middle-distance runners (twenty-five men and twenty-five women) between the ages of Men (age 24.8 ± 2.2); women (age 24.4 ± 2.0) who actively compete in 800m and 1500m events. To participate in this research, the athletes must have followed
questionnaire during the first phase and underwent some physiological measurements in the second phase. 2.2. Participants This study includes fifty amateur middle-distance runners (twenty-five men and twenty-five women) between the ages of Men (age 24.8 ± 2.2); women (age 24.4 ± 2.0) who actively compete in 800m and 1500m events. To participate in this research, the athletes must have followed a structured training program and need at least two years of competitive experience. The study excluded athletes who sustained major injuries that limited their training throughout the previous six months. A G*Power analysis was used to identify the needed sample size, which provided acceptable statistical power for this research [34]. The research method provided a complete view of the participants’ body performance and physical capabilities. Each participant provided consent before the information collection while meeting the standards of ethical research principles. A flow diagram illustrating participant enrollment, exclusion criteria, and group allocation is presented in Figure 1. 2.3. Procedure The data collection involved two distinct sessions with participants. The first session involved athletes completing a questionnaire, which obtained their demographic data (age and gender, height and weight) along with their performance data (800m and 1500m personal best times) and their weekly training mileage in kilometres. The second session included physiological measurements using a digital heart rate monitor (polar flow) to monitor heart rate in real-time [35]. Additionally, the Bruce Protocol treadmill test [36], measured VO2max by increasing the treadmill speed and incline levels until participants reached their maximum performance level. The resting heart rate was recorded 30 minutes before the session began. Participants received methodological descriptions of the research objectives and procedures before the sessions to ensure complete comprehension. 2.4. Instruments The Bruce Treadmill Protocol [36], was utilized to determine both maximal oxygen uptake (VO2max) and endurance capacity, applying validated equations explicitly designed for male and female participants. Bruce et al. (1973) developed this protocol that uses treadmill testing to evaluate cardiovascular fitness through sequential 3-minute intervals of increasing speed and incline, which yields detailed assessments of aerobic capacity. The test began with a 10-minute warm-up at 2.74 km/h and
both maximal oxygen uptake (VO2max) and endurance capacity, applying validated equations explicitly designed for male and female participants. Bruce et al. (1973) developed this protocol that uses treadmill testing to evaluate cardiovascular fitness through sequential 3-minute intervals of increasing speed and incline, which yields detailed assessments of aerobic capacity. The test began with a 10-minute warm-up at 2.74 km/h and a 10 % incline, followed by the commencement of the running test, during which the stopwatch was started. As outlined in Table 1, the speed and incline of the treadmill were adjusted every 3 minutes, progressing from 2.74 km/h until the participants reached volitional exhaustion. The total treadmill time (T) to volitional exhaustion was recorded and inserted into validated gender-specific equations to calculate VO2max. For men, the equation was: VO2max = 14.8 − (1.379 × T) + (0.451 × T²) − (0.012 × T³) for women: VO2max = (4.38 × T) − 3.9. These predictive equations have been widely validated and are considered reliable for field and laboratory use. Throughout the exercise, heart rates and perceived effort were monitored using a heart rate monitor and Borg’s 6-20 rating of perceived exertion (RPE) [37]. The criteria for
1006 Analysis of Performance Determinants in Middle-Distance Runners: The Influence of Training Load, Physiological Traits, and Recovery Indicators identifying volitional exhaustion consisted of achieving at least two of the following conditions. 1) RPE scores above 19; 2) while measuring peak heart rates that surpassed age limits; 3) along with respiratory exchange ratios greater than 1.10; 4) and a plateau in VO2 with less than 2 ML/KG/min [38], [39]. Endurance performance measurement relied on two key results: 1) time to exhaustion and 2) VO2max. The following formulas were used to calculate the maximum oxygen uptake (VO2max) for men and women. VO2max for men = 14.8-(1.379×T)+(0.451×T2)-(0.012×T3) [41]. VO2max for women = (4.38×T)-3.9 [42]. Figure 1. Flow chart of participants enrolment, exclusion, and group allocation Table 1. Bruce Treadmill Test Protocol [36], [40] Stage Time (minutes) Speed km/h Incline 1 0 2.74 10 2 3 4.02 12 3 6 5.47 14 4 9 6.76 16 5 12 8.05 18 6 15 8.85 20 7 18 9.65 22 8 21 10.46 24 9 24 11.26 26 10 27 12.07 28
International Journal of Human Movement and Sports Sciences 13(5): 1003-1015, 2025 1007 The polar flow digital heart rate monitor measured the resting heart rate (RHR) of athletes in a validated research environment that serves the study for accurate physiological evaluation [35]. A temperature controlled quiet room was designed for the assessment, where the participants completed supine rest positions in a private place to support physical and mental relaxation. The assessment began with a 30-minute rest period to establish a baseline in accordance with RHR protocols. After the rest, the athletes wore heart rate sensors with flexible straps for skin contact and stable signal acquisition. Following a 1-minute acclimatisation period, the researcher instructed them to take peaceful breaths with no monitoring display visibility to prevent conscious regulation of their heart rate. During this time, the minimum heart rate was measured. The weekly mileage of athletes was measured with dual methods to establish reliability and accuracy. The athletes recorded their running distance through a GPS fitness tracking tool that delivered immediate feedback about the distance they ran during each training session [43]. Additionally, athletes maintained running logs by manually counting track laps on standard 400-meter tracks in order to verify their self-reported measurements. Participants reported the distance covered for every training session [44]. GPS measurement results were validated by manual counting, which created a strong foundation for accurately assessing weekly running distance. The track counting method enabled comparison between GPS readings and manually measured distances 2.5. Ethical Statement This study followed the ethical standards of Alagappa University's institutional review board. Informed consent was obtained from all participants, ensuring voluntary participation and confidentiality. Data were concealed to protect privacy, and no identifying information was included in the analysis or presentation 2.6. Statistical Analysis All statistical analyses were performed using IBM Statistical Package for Social Science, version 26.0. Descriptive statistics, including means and standard deviations (SDs), were used to summarize participants’ demographic characteristics, training metrics and performance outcomes. The normality of continuous variables was assessed using the Shapiro-Wilk test and confirmed through inspection of Q-Q plots. All variables met the assumptions of normality (p
All statistical analyses were performed using IBM Statistical Package for Social Science, version 26.0. Descriptive statistics, including means and standard deviations (SDs), were used to summarize participants’ demographic characteristics, training metrics and performance outcomes. The normality of continuous variables was assessed using the Shapiro-Wilk test and confirmed through inspection of Q-Q plots. All variables met the assumptions of normality (p > 0.05), supporting the use of parametric tests. Independent t-tests were used to compare performance and injury rates between male and female athletes. To determine the relationship between key training variables (weekly mileage, VO2max, and resting heart rate) and race performance (800m and 1500m times), it was evaluated using Pearson’s correlation coefficient (r). Correlation strength is classified based on Cohen [45]. Additionally, a multiple linear regression model was employed to identify the most influential predictors of middle-distance performance, with race time as the dependent variable and training and physiological traits as the independent variable. These analyses provided deeper insights into the extent to which training load and physiological capacity impact race outcome. 3. Results 3.1. Data Screening & Assumption Testing The dataset was examined for outliers and statistical assumptions prior to conducting inferential analyses. The Shapiro–Wilk test indicated that all continuous variables were normally distributed (p > 0.05), and this was further supported by Q–Q graphs. No significant outliers were detected, and the assumptions for parametric tests, such as linearity and homoscedasticity, were satisfied. These initial evaluations confirmed the data's suitability for correlation, group comparison, and regression analyses. The study sample consisted of fifty middle-distance runners (25 males and 25 females) with a mean age of 24.6 years (SD = 2.1 years). The anthropometric data indicated that male runners had a significantly higher mean height (180 cm) and weight (70 kg) compared to female runners (165 cm, 52 kg). Training characteristics revealed that athletes ran an average of 69.2 km per week (SD = 5.7), with individual values ranging from 60 km to 80 km. The mean VO2 max was 58.7 ml/kg/min (SD = 3.2), reflecting a high level of aerobic capacity within the sample. Performance metrics showed considerable variations,
kg) compared to female runners (165 cm, 52 kg). Training characteristics revealed that athletes ran an average of 69.2 km per week (SD = 5.7), with individual values ranging from 60 km to 80 km. The mean VO2 max was 58.7 ml/kg/min (SD = 3.2), reflecting a high level of aerobic capacity within the sample. Performance metrics showed considerable variations, with the best 800m times averaging 1:47.5 minutes (SD = 2.1 seconds) and best 1500m times averaging 4:04.2 minutes (SD = 5.3 seconds). These results highlight the competitive standard of the participants, with their physiological characteristics and training regimens aligned with high-level middle-distance performance. The detailed descriptive statistics of the study sample are presented in Table 2. Since performance comparisons between male and female athletes were a key component of the analysis, female-specific descriptive values are provided separately in Table 2a to highlight group-specific trends. 3.1.1. Correlation Analysis The correlation analysis revealed in Table 3 shows significant relationships between training load, physiological characteristics, and performance outcomes. A strong negative correlation between weekly mileage and best 1500m time (r = -0.78, p < 0.01) indicated that increased weekly mileage was associated with improved performance, reinforcing the importance of aerobic base training for middle-distance runners. Similarly, a moderate negative correlation between VO2max and best 800m time (r = -0.65, p < 0.01) suggested that higher VO2max values contributed to faster race times, supporting existing
Description
The study analyzes factors affecting middle-distance running performance.