Pacing Variation in Multistage Ultramarathons: Internet-Based Cross-Sectional Study

BACKGROUND

Ultramarathon running is the most popular ultraendurance competition in terms of the number of races and runners competing annually worldwide; however, no study has compared pacing and performance over a long period.

OBJECTIVE

This study analyzes the pacing of successful finishers and nonfinishers in multistage ultramarathons worldwide.

METHODS

A total of 4079 athletes (men=3288; women=791) competing in 99 multistage ultramarathon events from 1983 to 2021 were analyzed, including the number of participants, age, gender, rank, and running speed of successful finishers.

RESULTS

The results showed a significant increase in the number of events (n=338) and a significant increase in the number of finishers and nonfinishers (n=5575) in the ultramarathons worldwide during this period. The general linear models (GLMs) of pacing variation showed nonsignificant effects for gender (F1,36.2=2.5; P=.127; ηp2=0.063) and age group (F10,10=0.6; P=.798; ηp2=0.367), but it showed a significant interaction (gender × age) effect (F10,2689=2.3; P=.008; ηp2=0.009). Post hoc analyses showed that men have a higher pacing variation than women in the under 30 years (U30), U35, U45, and U50 groups. Additionally, the fastest women's age group (U35) had the lowest pacing variation. The GLM of pacing variation by gender and event distance showed significant effects for both gender (F1,3=18.5; P<.001; ηp2=0.007) and distance (F2,3=20.1; P<.001; ηp2=0.015). Post hoc analyses showed a growing pacing variation with increasing race distance for both men and women. In addition, men had a higher variation in long events. Furthermore, there was a significant main effect for both genders (F1,3=33.7; P<.001; ηp2=0.012) and rank (F1,3=136.6; P<.001; ηp2=0.048) on performance, with men being faster than women. Pacing varied greatly due to gender (F1,3=4.0; P=.047; ηp2=0.001), with a lower (ie, more even) pacing variation for male athletes in the top 3 finishers. Male nonfinishers showed a higher performance than female nonfinishers (F1,1340=25.6; P<.001), and no difference was identified for pacing variation (F1,789=1.5; P=.228) based on gender. In addition, a weak but significant correlation (r=-0.130; P<.001) was identified between the average running speed and pacing variation for both female and male nonfinishers.

CONCLUSIONS

In summary, multistage ultramarathon competitions showed an increasing number of competitors and a higher performance challenge. Men have a higher pacing (ie, less even) variation than women, especially observed in longer events. A higher pacing variation was associated with lower performance for men, women, and nonfinishers.

What Is the Best Discipline to Predict Overall Triathlon Performance? An Analysis of Sprint, Olympic, Ironman® 70.3, and Ironman® 140.6

Objective: To analyze the proportion of dedication in each triathlon discipline (swimming, cycling, and running) and the importance of each separate discipline to predict overall performance of elite triathletes across different triathlon distances.

Methods: Data from 2015 to 2020 (n = 16,667) from official races and athletes in Sprint, Olympic distance, IM 70.3 (Half-Ironman distance), and IM 140.6 (Full-Ironman distance) competitions were included. The proportion of each discipline was calculated individually and compared using general linear models by event distance, sex, and performance level. Automatic linear regression models were applied for each distance considering overall performance as the dependent variable.

Results: A within-distance analysis showed that the best predictor for Sprint is cycling, for Olympic is swimming, for IM 70.3 is cycling, and for IM 140.6 is running. A between-distance analysis revealed that swimming is a better predictor in Olympic distance than in other triathlon distances. Cycling is a poor predictor for overall performance in IM 140.6, and the importance of running to predict overall performance is the highest in IM 140.6 and diminishes with decreasing race distance.

Conclusion: Each discipline represents a different relative portion and importance to predict overall performance depending on the triathlon distance. Swimming is the most important predictor discipline in Sprint- and Olympic-distance triathlon, cycling in IM 70.3, and running in IM 140.6.

Pacing in World-Class Age Group Swimmers in 200 and 400 m Individual Medley

The present research investigated pacing for world-class age group swimmers competing in individual medley in 200 m and 400 m. Data on 3,242 unique finishers (1,475 women and 1,767 men) competing in four Master World Championships [XV FINA WMC held in Montreal (Canada) in 2014, the XVI FINA WMC held in Kazan (RUS) in 2015, the FINA WMC held in Budapest (HUN) in 2017, and the XVIII FINA WMC held in Gwangju (KOR] in 2019) were analyzed. Men were faster than women among all age groups in both 200 and 400 m. Additionally, differences were found between almost all adjacent age groups, with the exception (p > 0.05) of age groups 25-29 to 30-34, 35-39 to 40-44 years in 200 m races and 25-29 to 30-34, 30-34 to 35-39, 35-39 to 40-44, and 45-49 to 50-54 years in 400 m races. Men showed a higher pacing variation in 200 m among all male age groups and all female age groups up to 69 years. Pace-variation pairwise comparisons between men and women showed no consistencies throughout age groups, with the exception of a higher variation in men in age groups ≥55-year-old. Men were faster for all splits and strokes in both 200 and 400 m, and significant changes were identified for each split and stroke for both men and women in both 200 and 400 m. Front crawl (freestyle, 4th split) was the fastest butterfly (1st split), backstroke (2nd split), and breaststroke (3rd split). In summary, men were faster than women for all age groups in both 200 and 400 m. Men showed a higher pacing variation in 200 m in all age groups, where women had a higher variation in age groups up to 69 years. The fastest stroke for the final spurt was front crawl, followed by butterfly, backstroke, and breaststroke. Based on these findings, coaches should advise their master athletes to focus on the final spurt in both 200 and 400 m individual medley for a fast final race time.

Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon

Cut-off points and performance-related tools are needed for the development of the Olympic distance triathlon. The purposes of the present study were (i) to determine cut-off values to reach the top three positions in an Olympic distance triathlon; (ii) to identify which discipline present the highest influence on overall race performance and if it has changed over the decades. Data from 1989 to 2019 (n = 52,027) from all who have competed in an official Olympic distance triathlon events (World Triathlon Series and Olympics) were included. The cut-off value to achieve a top three position was calculated. Linear regressions were applied for performance trends overall and for the top three positions of each race. Men had cut-off values of: swimming = 19.5 min; cycling = 60.7 min; running = 34.1 min. Women's cut-off values were: swimming = 20.7 min; cycling = 71.6 min; running = 38.1 min. The running split seemed to be the most influential in overall race time regardless of rank position or sex. In conclusion, cut-offs were established, which can increase the chances of achieving a successful rank position in an Olympic triathlon. Cycling is the discipline with the least influence on overall performance for both men and women in the Olympic distance triathlon. This influence pattern has not changed in the last three decades.

Blood pressure decrease in elderly after isometric training: does lactate play a role?

This study aimed to investigate the effect of isometric handgrip (IHG) training on the blood pressure (BP) reduction in prehypertensive and hypertensive elderly people, and the possible role of lactate and redox balance. Thirty-three older (75.3±1.3 years old) were allocated to a non-exercise control (CG, n=11), prehypertensive (PHG, n=10), and hypertensive (HG, n=12) groups. PHG and HG performed a total of 8 sets of 1-min bilateral contractions at 30% maximal voluntary isometric contraction, each separated by 1-minute rest-pause. IHG training was performed for 8-week, 3 times a week on non-consecutive days. Systolic BP (SBP) and heart rate (HR) decreased post-training on PHG (-10 mm Hg; -5 bpm) and HG (-16 mm Hg; -9 bpm), respectively. Diastolic BP (DBP) decreased for HG only (-9 mm Hg) (P < 0.05). In addition, the decrease in BP occurred in parallel to a better redox balance and increased bioavailability of nitric oxide in PHG and HG (P < 0.05). Also, the variables that most present association to SBP decrease were capillary blood lactate concentration and muscle strength (P < 0.05). In summary, IHG training may be practical in improving clinical status of prehypertensive and hypertensive patients, by improving BP control, NO- bioavailability and redox balance. Further studies are required to elucidate the pathways of lactate concentration in blood-flow during exercise.

Heart rate cost of running in track estimates velocity associated with maximal oxygen uptake

BACKGROUND

Running velocity associated with VO₂max (vVO₂max) is a parameter widely used for exercise prescription and is related to endurance performance. However, the vVO₂max determination usually requires a maximal effort test and equipped laboratory for expired gas analysis, what make difficulty its assessment.

OBJECTIVE

We aimed to test the validity of a simple method of vVO₂max prediction through the heart rate cost of running (HRC) in a submaximal 6-min running test, both in treadmill and in a 400-meter track.

METHODS

Male recreational runners (n = 16; 30.3 ± 8.0 years; VO₂max of 46.2 ± 3.2 ml·kg^-1·min^-1) randomly underwent an incremental test in treadmill with gas analysis, and a 3000-m time trial in a track, to determine vVO₂max. Before every maximal test, participants also performed a submaximal 6-min running (~85% HRmax), both in the treadmill and in a track, to assess HRC (bpm^-1m·min^-1) by dividing the submaximal running velocity by its respective HR. The vVO₂max (km·h^-1) was predicted by dividing the HRmax (bpm)/HRC (bpm^-1m·min^-1).

RESULTS

No differences were verified (p > .05) among vVO₂max determined both in the treadmill (13.8 ± 0.9 km·h^-1) and track (13.6 ± 0.9 km·h^-1) to those predicted by the HRC method both in treadmill (13.5 ± 0.8 km·h^-1) and track (13.6 ± 1.0 km·h^-1). The vVO₂max measured directly with expired gas analysis was highly correlated with vVO₂max estimated through HRC in treadmill and track (p < .05). Additionally, the intraclass correlation coefficient (ICC) and Bland-Altman technique revealed good agreement and reliability classified with substantial agreement [ICC = 0.673 (95% CI 0.064-0.886; p = .019)] and almost perfect agreement [ICC = 0.870 (95% CI 0.628-0.955 p = .0001)] between methods to identify vVO₂max, respectively.

CONCLUSION

A submaximal 6-min exercise test protocol to assess HRC of running was considered valid to estimate vVO₂max of recreational runners both in treadmill and outdoor track.