Physiological Determinants of Ultramarathon Trail Running Performance
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Part of the Society for Transparency, Openness and Replication in Preprint Kinesiology (STORK) not peer reviewed Received: 23 June 2020 Physiological For correspondence: [email protected] Determinants of Ultramarathon Trail Running Performance Alexandra M. Coates1, Jordan A. Berard1, Trevor J. King1, and Jamie F. Burr1 1The Human Performance and Health Research Lab, Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, ON, Canada. Please cite as: Coates, A. M., Berard, J. A., King, T. J., & Burr, J. F. (2020). Physiological determinants of ultramarathon trail running performance. SportRχiv. https://doi.org/10.31236/osf.io/y2kdx ABSTRACT Context: The physiological determinants of ultramarathon success have rarely been assessed, and likely differ in their contributions to performance as race distance increases. Purpose: The aim of this study was to examine predictors of performance in athletes who completed either a 50km, 80km, or 160km trail race over a 20km-loop course on the same day. Methods: Measures of running history, aerobic fitness, running economy, body mass loss, hematocrit alterations, age, and cardiovascular health were examined in relation to race-day performance. Performance was defined as the percent difference from the winning time at a given race distance, with 0% representing the fastest possible time. Results: In the 50km race, training volumes, cardiovascular health, aerobic fitness, and a greater loss of body mass during the race were all related to better performance (all P<0.05). Using multiple linear regression, peak velocity achieved in the VO2max test (β=-11.7, P=0.002) and baseline blood pressure (β=3.1, P=0.007) were the best performance predictors for the men’s 50km race (r=0.98, r2=0.96, P<0.001), while peak velocity achieved in the VO2max test (β=-13.6, P=0.001) and loss of body mass (β=12.8, P=0.03) were the best predictors for women (r=0.94, r2=0.87, P=0.001). In the 80km race, only peak velocity All authors have read and approved this version of the Authors AMC @superalex_c and JFB manuscript. This article was last modified on July 2, 2020. @Dr_Burr can be reached on Twitter. 2 achieved in the VO2max test predicted performance (β =-20.3, r=0.88, r =0.78, P<0.001). In the 160km race, there were no significant performance determinants. Conclusions: While classic determinants of running performance including cardiovascular health, and running fitness predict 50km trail running success, performance in longer distance races appears to be less influenced by such physiological parameters. INTRODUCTION Predicting ultramarathon running performance is a unique challenge, as ultramarathon races can vary greatly in distance, duration, and physiological demand. Ultramarathon running races range from any race exceeding the marathon distance (>42.2km) to multi-day events, and commonly include diverse terrains, and environmental conditions1,2. This results in vastly different physiological requirements between races, and can make comparison across races challenging. The demographic of athletes racing ultramarathons is typically older than shorter-distances, and is comprised primarily of masters and recreational participants, rather than elite athletes1. Proposed contributors to successful ultramarathon performance include high aerobic fitness3,4, an ability to mitigate injuries5, avoidance of gastrointestinal issues6, delay of fatigue2, and psychological fortitude3. The physiological determinants of running performance in standard distances from 5000m to the marathon have been highly investigated, and primarily include measures of aerobic fitness including maximal 7 oxygen uptake (VO2max), lactate threshold or the percentage of sustainable VO2max, and running economy . Aerobic fitness seems likely as a determinant of ultramarathon performance as well, as lactate threshold and 4 VO2max are related to distance covered in a 24h treadmill run , and peak treadmill running velocity achieved during an incremental test is the best laboratory predictor of performance for races ≤90km8. Lower body mass index (BMI) and body fat percentage are typically related to improved endurance running performance9,10; however, the correlation of BMI and ultramarathon performance is equivocal6,9,11,12, and performance is more strongly related to training volumes than BMI9,12. Excessive dehydration has been shown to negatively alter endurance exercise performance13, yet faster marathon runners typically lose more weight over the course of a race than slower runners, and a loss of upwards of 3% of body mass has been demonstrated in runners who completed marathons in less than 3h14. Loss of body mass following 161km races is similar to that of marathons (~2%)15; however, there is only a weak relationship to faster racing times16. Furthermore, in contrast to shorter distance running, body mass loss cannot be solely attributable to dehydration in ultramarathon17, which may complicate the relationship between body mass loss and performance. Finally, while peak performance in the marathon is typically achieved around the age of 30yr, the age of the fastest 160km runners worldwide is approximately 37yr for men and 39yr for women18, with experience being a greater determinant of success than age18. This may further suggest a shift in the importance of certain physiological parameters, such as aerobic fitness, which decrease with age. To date, a comparison of the physiological determinants of performance across increasing ultramarathon race distances, and within similar racing conditions, has not been performed. The objective of this study was to examine whether common indicators of running performance could be used to predict performance in athletes who raced either a 50km, 80km, or 160km ultramarathon, on the same day and over a common course. METHODS Experimental Design Fifty-one recreational runners who were registered in the Sulphur Springs trail races (Ancaster, Canada) in the 50km, 80km, or 160km distances were recruited via email for this cross-sectional study. The race was comprised of 20km hilly trail loops (~620m of cumulative elevation gain per loop). Participants were all healthy DOI: 10.31236/osf.io/y2kdx SportRxiv is free to access, but not to run. Please consider donating at www.storkinesiology.org/annual 2 and non-smoking individuals between the ages of 18-60yr, and provided written informed consent prior to testing. In the month prior to the race (mean 12±7 days prior to race day), participants underwent baseline testing including a training and racing history questionnaire, basic anthropometrics, resting blood pressure (BP), heart rate (HR), and heart rate variability (HRV), a venous blood draw to assess hematocrit, and an incremental running test to exhaustion. Participants were asked to refrain from caffeine and heavy meals for ³3h, drugs and alcohol for ³24h, and intense exercise for ³48h prior to baseline testing. On race morning, all athletes were weighed immediately prior to racing. Immediately following the race, a post-race weight and hematocrit were collected to assess dehydration status. The study was carried out under approval of the University of Guelph ethics board, and in accordance with the Declaration of Helsinki, and was part of a larger study on ultramarathons and cardiovascular fatigue19,20. Training and Racing History Questionnaire In a written questionnaire, athletes were asked to report on their previous month of training, including how many hours and km per week they ran, how many hours of strength or resistance training they underwent each week, and how many additional hours were spent on cross-training. They were also asked to report the km/week completed on average in the past year. Lastly, athletes reported the number of years of past endurance run training, and how many marathons and ultramarathons they had previously completed. Cardiovascular Health Age, height, and body mass were recorded. Supine BP was taken in triplicate using an automated oscillometric device (BPtru, Vancouver, BC) once the participant was relaxed (~1-2min following positioning). The first recording was discarded and the remaining 2 were averaged. Following a minimum of 5min of quiet rest, a 4- min recording of heart rate variability (HRV) using a SphygmoCor CPVH single-lead ECG (AtCor Medical Ltd, NSW, Australia) was collected, during spontaneous breathing. Mean resting HR, the natural log of the square root of the mean of successive differences (lnRMSSD), and lnRMSSD divided by HR were selected as the measures of interest, as they provide reliable measures of parasympathetic activity over a short time frame21. Aerobic Fitness and Running Economy Following resting measures, an incremental running test to volitional fatigue, with measures of indirect calorimetry, was performed (HP Cosmos Treadmill, Cosmed Quark metabolic cart) to determine VO2max, ventilatory thresholds, and steady-state running economy. Participants completed three 3min submaximal stages at 1% grade to simulate outdoor running22. Paces were increased by 0.8kph (0.5mph) per stage from what was estimated to be a sustainable steady-pace for the individual. The initial velocity was chosen after discussing the protocol with the participant, and was often at a pace around or just below the individual’s half-marathon pace (ranging from 8.0-15.3kph). This ensured that by the end of the 3rd stage, all participants had surpassed their first ventilatory threshold. Following the 3 submaximal stages, speed was increased each minute by