The Relationship between Anthropometry and Split Performance in Recreational Male Ironman Triathletes

Maximal Oxygen Uptake, Muscular Oxidative Capacity, and Ventilatory Threshold in Amateur Triathletes: Eight-Month Training Follow-Up

Purpose

Endurance sports performance is influenced by several factors, including maximal oxygen uptake (⩒O2max), the percentage of ⩒O2max that can be sustained in endurance events, running economy, and body composition. Traditionally, ⩒O2max can be measured as an absolute value, adjusted for body mass, reflecting the athlete's central capacity (maximal cardiac output), or adjusted for lean mass (LM), reflecting the athlete's peripheral capacity (muscular oxidative capacity). The present study aims to evaluate absolute, total body mass, and lower limb LM-adjusted ⩒O2max, ventilatory thresholds (VT), respiratory compensation points (RCP), and body composition during two training periods separated by 8 months.

Patients and Methods

Thirteen competitive amateur triathletes [seven men (40.7±13.7 years old, 76.3±8.3kg, and 173.9±4.8cm) and six women (43.5±6.9 years old, 55.0±2.7kg, 164.9±5.2cm)] were evaluated for body composition with dual-energy X-ray absorptiometry and ⩒O2max, VT, RPC, and maximal aerobic speed (MAS) with a cardiorespiratory maximal treadmill test.

Results

The absolute ⩒O2max (p = 0.003, d = 1.05), body mass-adjusted ⩒O2max (p < 0.001, d = 1.2859), and MAS (p = 0.047, d = 0.6139) values differed significantly across evaluation periods. Lower limb LM-adjusted ⩒O2max (p = 0.083, d = -0.0418), %⩒O2max at VT (p = 0.541, d = -0.1746), speed at VT (p = 0.337, d = -0.2774), % ⩒O2max at RCP (p = 0.776, d = 0.0806), and speed at RCP (p = 0.436, d = 0.2234) showed no difference.

Conclusion

The sensitivities of ⩒O2max adjusted for body mass and ⩒O2max adjusted for LM to detect changes in physical training state differ. Furthermore, decreases in physical fitness level, as evaluated by ⩒O2max values, are not accompanied by changes in VT.

Do Triathletes Periodize Their Diet and Do Their Mineral Content, Body Composition and Aerobic Capacity Change during Training and Competition Periods?

The triathlon is a demanding endurance multisport, which may strongly affect the nutritional status of athletes. The aim of this study was to find whether there are any differences in energy value and nutrient intake, body mass and body composition, aerobic performance and hair mineral status between training and competition periods and to assess whether there is a link between hair mineral content and physical capacity and nutrition. This observational study covered 20 triathletes aged 32 ± 7 years. The results of our study indicated performance improvement during the competition period (longer time to exhaustion (p = 0.025) and lower maximal oxygen uptake at the ventilatory threshold (%VO_{2max_VT}; p = 0.047)). However, no differences were recorded in nutrition and body composition between two training vs. competition periods. There was a significant depletion in hair iron content during the competition period (p = 0.010). Furthermore, there were significant relationships between hair calcium content and absolute maximal oxygen uptake and %VO_{2max_VT} during the training period. It is necessary to introduce nutritional education in the group of triathletes focused on exercise-oriented nutritional periodization following the requirements of the training and competition periods, thus preventing the risk of nutrient deficiencies.

Concordance Analysis between the Segments and the Overall Performance in Olympic Triathlon in Elite Triathletes

Simple Summary

Due to the complexity of the triathlon, it is difficult to analyse overall performance. To date, the analysis of performance in triathlon has been widely studied through time or position in the three segments and in the overall result, which is what defines the medals and the goal of the competition, but it can have some limitations. As an alternative, the purpose of this study is to analyse the concordance between each of the triathlon segments (swimming, cycling, and running) and the overall performance in the Olympic triathlon in elite triathletes. The main results of the present study show that performance in the cycling segment presents the best concordance with overall performance. In conclusion, the cycling performance indicator could be an alternative to anticipate the overall performance in the competition. For this reason, the cycling segment would not be a smooth transition toward running in the Olympic distance event.

Abstract

To date, the performance in triathlon has been measured through time or position. Although this is what defines the medals and the goal of the competition, it can have some limitations. As an alternative, the purpose of this study is to assess the degree of concordance of performance between each of the triathlon disciplines with overall performance through the triathlon performance indicator for the Olympic distance event. The official results from the World Triathlon Series for Olympic distance events from 2000 to 2019 were examined. A total of 11,263 entries were analysed, 6273 corresponding to elite men and 4990 to elite women. Moderate agreement was found between the running performance and overall performance in both elite men ICCa = 0.538 and elite women ICCa = 0.581. Moreover, moderate agreement was found between swimming performance and overall performance in both elite men ICCa = 0.640 and elite women ICCa = 0.613. Finally, good agreement was found between cycling performance and overall performance also in both elite men ICCa = 0.777 and elite women ICCa = 0.816. The main results of the present study show that the cycling performance indicator could be an alternative to anticipate the overall performance in the competition for the Olympic distance event.

Morphological Asymmetries Profile and the Difference between Low- and High-Performing Road Cyclists Using 3D Scanning

The aims of this study are: (1) to identify morphological asymmetries in road cycling by using a novel 3D scanning method and electrical bioimpedance, (2) to investigate possible asymmetries in road cyclists of low (LPG) and high (HPG) performance group, (3) to compare the number of morphological asymmetries between HPG and LPG of cyclists, and (4) to explore correlations between asymmetry scores and competition performance. Body composition and 3D anthropometric measurements were conducted on 48 top-level male road cyclists (178.98 ± 5.39 cm; 68.37 ± 5.31 kg) divided into high (n = 22) and low (n = 26) performance groups. Competition performance (CP) is represented through racing points gathered at the end of the competition season. The latter was used to divide road cyclists into low- and high-performing groups. One-way ANOVA was used to determine differences between groups, while paired-samples T-test and Absolute Asymmetry index (AA) were calculated (p ≤ 0.05) for paired variables inside the groups, and the Spearman correlation coefficient was used to explore correlations between AA and CP. Results showed statistically significant differences between the left and right side of different body segments (16 paired variables) among low-performing road cyclists in five paired variables of the upper body: elbow girth (4.35, p = 0.000), forearm girth (6.31, p = 0.000), arm surface area (2.54, p = 0.018), and arm volume (2.71, p = 0.012); and six paired variables of the lower body: leg lean mass (5.85, p = 0.000), leg length (3.04, p = 0.005), knee girth (4.93, p = 0.000), calf girth (5.25, p = 0.000), leg surface area (4.03, p = 0.000), and leg volume (5.3, p = 0.000). Altogether, the high-performing group of road cyclists statistically differed only in 2 out of 16 paired variables of the upper body: elbow girth (4.93, p = 0.000) and in forearm girth (5.12, p = 0.000). Low- and high-performing groups were statistically significantly different in the asymmetry of leg lean mass F(1,46) = 6.25, p = 0.016 and asymmetry of the calf girth F(1,46) = 7.44, p = 0.009. AA of calf girth on the total sample (n = 48) showed a significant correlation with CP (r = -0.461; p = 0.001). In conclusion, the study's main finding was that high-performance road cyclists are more symmetrical than the low-performance group, for which it is significant to have a higher amount of morphological asymmetries.

Urinary Steroid Profile in Ironman Triathletes

The aim of this study was to determine variations in the urinary steroid profile of triathletes following an Ironman event. A total of 10 male participants (age = 36.0 ± 1.27 years; body height = 179.29 ± 10.77 cm; body mass = 74.50 ± 1.04 kg) completed an Ironman Championship. Urine samples were collected before, immediately after, and 24 hours following the race. Gas chromatography-mass spectrometry (GC/MS) was used to detect and quantify catabolic and anabolic hormones: Androsterone, Dehydroepiandrosteone (DHEA), Androstenedione and Testosterone (T), Betaestradiol, Estrone, Progesterone, Cortisol (C), Cortisone, Tetrahydrocortisol (THE) and Tetrahydrocortisone (THF). These were measured in their glucuroconjugated and free forms. Androsterone (3297.80 ± 756.83 vs. 2154.26 ± 1375.38), DHEA (47.80 ± 19.21 vs. 32.62 ± 15.96) and Beta-estradiol (59.36 ± 11.7 vs. 41.67 ± 10.59) levels decreased after the event. The significant decrease of DHEA (47.80 ± 19.21 vs. 32.11 ± 14.03) remained at 24 hours. Cortisol (200.38 ± 56.60 vs. 257.10 ± 74.00) and THE (238.65 ± 81.55 vs. 289.62 ± 77.13) increased after exercise and remained elevated 24 hours later (200.38 ± 56.60 vs. 252.48 ± 62.09; 238.65 ± 81.55 vs. 284.20 ± 66.66). The following anabolic/catabolic ratios fell after exercise: T/C (0.85 ± 0.54 vs. 0.54 ± 0.29), T/THE (0.66 ± 0.29 vs. 0.40 ± 0.08), T/THE+THF (0.38 ± 0.17 vs. 0.24 ± 0.06), DHEA/THE (0.22 ± 0.05 vs. 0.12 ± 0.05), DHEA/THF (0.34 ± 0.02 vs. 0.21 ± 0.01) and DHEA/THE+THF (0.12 ± 0.02 vs. 0.08 ± 0.03). The steroid profile showed that athletes were fatigued after finishing the competition and a catabolic state remained 24 hours later.

Changes in Contributions of Swimming, Cycling, and Running Performances on Overall Triathlon Performance Over a 26-Year Period

Figueiredo, P, Marques, EA, and Lepers, R. Changes in contributions of swimming, cycling, and running performances on overall triathlon performance over a 26-year period. J Strength Cond Res 30(9): 2406-2415, 2016-This study examined the changes in the individual contribution of each discipline to the overall performance of Olympic and Ironman distance triathlons among men and women. Between 1989 and 2014, overall performances and their component disciplines (swimming, cycling and running) were analyzed from the top 50 overall male and female finishers. Regression analyses determined that for the Olympic distance, the split times in swimming and running decreased over the years (r = 0.25-0.43, p ≤ 0.05), whereas the cycling split and total time remained unchanged (p > 0.05), for both sexes. For the Ironman distance, the cycling and running splits and the total time decreased (r = 0.19-0.88, p ≤ 0.05), whereas swimming time remained stable, for both men and women. The average contribution of the swimming stage (∼18%) was smaller than the cycling and running stages (p ≤ 0.05), for both distances and both sexes. Running (∼47%) and then cycling (∼36%) had the greatest contribution to overall performance for the Olympic distance (∼47%), whereas for the Ironman distance, cycling and running presented similar contributions (∼40%, p > 0.05). Across the years, in the Olympic distance, swimming contribution significantly decreased for women and men (r = 0.51 and 0.68, p < 0.001, respectively), whereas running increased for men (r = 0.33, p = 0.014). In the Ironman distance, swimming and cycling contributions changed in an undulating fashion, being inverse between the two segments, for both sexes (p < 0.01), whereas running contribution decreased for men only (r = 0.61, p = 0.001). These findings highlight that strategies to improve running performance should be the main focus on the preparation to compete in the Olympic distance; whereas, in the Ironman, both cycling and running are decisive and should be well developed.

Variables that influence Ironman triathlon performance - what changed in the last 35 years?

OBJECTIVE

This narrative review summarizes findings for Ironman triathlon performance and intends to determine potential predictor variables for Ironman race performance in female and male triathletes.

METHODS

A literature search was performed in PubMed using the terms "Ironman", "triathlon", and "performance". All resulting articles were searched for related citations.

RESULTS

Age, previous experience, sex, training, origin, anthropometric and physiological characteristics, pacing, and performance in split disciplines were predictive. Differences exist between the sexes for anthropometric characteristics. The most important predictive variables for a fast Ironman race time were age of 30-35 years (women and men), a fast personal best time in Olympic distance triathlon (women and men), a fast personal best time in marathon (women and men), high volume and high speed in training where high volume was more important than high speed (women and men), low body fat, low skin-fold thicknesses and low circumference of upper arm (only men), and origin from the United States of America (women and men).

CONCLUSION

These findings may help athletes and coaches to plan an Ironman triathlon career. Age and previous experience are important to find the right point in the life of a triathlete to switch from the shorter triathlon distances to the Ironman distance. Future studies need to correlate physiological characteristics such as maximum oxygen uptake with Ironman race time to investigate their potential predictive value and to investigate socio-economic aspects in Ironman triathlon.

What predicts performance in ultra-triathlon races? - a comparison between Ironman distance triathlon and ultra-triathlon

Objective

This narrative review summarizes recent intentions to find potential predictor variables for ultra-triathlon race performance (ie, triathlon races longer than the Ironman distance covering 3.8 km swimming, 180 km cycling, and 42.195 km running). Results from studies on ultra-triathletes were compared to results on studies on Ironman triathletes.

Methods

A literature search was performed in PubMed using the terms “ultra”, “triathlon”, and “performance” for the aspects of “ultra-triathlon”, and “Ironman”, “triathlon”, and “performance” for the aspects of “Ironman triathlon”. All resulting papers were searched for related citations. Results for ultra-triathlons were compared to results for Ironman-distance triathlons to find potential differences.

Results

Athletes competing in Ironman and ultra-triathlon differed in anthropometric and training characteristics, where both Ironmen and ultra-triathletes profited from low body fat, but ultra-triathletes relied more on training volume, whereas speed during training was related to Ironman race time. The most important predictive variables for a fast race time in an ultra-triathlon from Double Iron (ie, 7.6 km swimming, 360 km cycling, and 84.4 km running) and longer were male sex, low body fat, age of 35–40 years, extensive previous experience, a fast time in cycling and running but not in swimming, and origins in Central Europe.

Conclusion

Any athlete intending to compete in an ultra-triathlon should be aware that low body fat and high training volumes are highly predictive for overall race time. Little is known about the physiological characteristics of these athletes and about female ultra-triathletes. Future studies need to investigate anthropometric and training characteristics of female ultra-triathletes and what motivates women to compete in these races. Future studies need to correlate physiological characteristics such as maximum oxygen uptake (VO_2max) with ultra-triathlon race performance in order to investigate whether these characteristics are also predictive for ultra-triathlon race performance.

Relationship of anthropometric and training characteristics with race performance in endurance and ultra-endurance athletes

A variety of anthropometric and training characteristics have been identified as predictor variables for race performance in endurance and ultra-endurance athletes. Anthropometric characteristics such as skin-fold thicknesses, body fat, circumferences and length of limbs, body mass, body height, and body mass index were bi-variately related to race performance in endurance athletes such as swimmers in pools and in open water, in road and mountain bike cyclists, and in runners and triathletes over different distances. Additionally, training variables such as volume and speed were also bi-variately associated with race performance. Multi-variate regression analyses including anthropometric and training characteristics reduced the predictor variables mainly to body fat and speed during training units. Further multi-variate regression analyses including additionally the aspects of previous experience such as personal best times showed that mainly previous best time in shorter races were the most important predictors for ultra-endurance race times. Ultra-endurance athletes seemed to prepare differently for their races compared to endurance athletes where ultra-endurance athletes invested more time in training and completed more training kilometers at lower speed compared to endurance athletes. In conclusion, the most important predictor variables for ultra-endurance athletes were a fast personal best time in shorter races, a low body fat and a high speed during training units.

Sex and age-related differences in performance in a 24-hour ultra-cycling draft-legal event - a cross-sectional data analysis

Background

The purpose of this study was to examine the sex and age-related differences in performance in a draft-legal ultra-cycling event.

Methods

Age-related changes in performance across years were investigated in the 24-hour draft-legal cycling event held in Schötz, Switzerland, between 2000 and 2011 using multi-level regression analyses including age, repeated participation and environmental temperatures as co-variables.

Results

For all finishers, the age of peak cycling performance decreased significantly (β = −0.273, p = 0.036) from 38 ± 10 to 35 ± 6 years in females but remained unchanged (β = −0.035, p = 0.906) at 41.0 ± 10.3 years in males. For the annual fastest females and males, the age of peak cycling performance remained unchanged at 37.3 ± 8.5 and 38.3 ± 5.4 years, respectively. For all female and male finishers, males improved significantly (β = 7.010, p = 0.006) the cycling distance from 497.8 ± 219.6 km to 546.7 ± 205.0 km whereas females (β = −0.085, p = 0.987) showed an unchanged performance of 593.7 ± 132.3 km. The mean cycling distance achieved by the male winners of 960.5 ± 51.9 km was significantly (p < 0.001) greater than the distance covered by the female winners with 769.7 ± 65.7 km but was not different between the sexes (p > 0.05). The sex difference in performance for the annual winners of 19.7 ± 7.8% remained unchanged across years (p > 0.05). The achieved cycling distance decreased in a curvilinear manner with advancing age. There was a significant age effect (F = 28.4, p < 0.0001) for cycling performance where the fastest cyclists were in age group 35–39 years.

Conclusion

In this 24-h cycling draft-legal event, performance in females remained unchanged while their age of peak cycling performance decreased and performance in males improved while their age of peak cycling performance remained unchanged. The annual fastest females and males were 37.3 ± 8.5 and 38.3 ± 5.4 years old, respectively. The sex difference for the fastest finishers was ~20%. It seems that women were not able to profit from drafting to improve their ultra-cycling performance.

Nation related participation and performance trends in 'Ironman Hawaii' from 1985 to 2012

BACKGROUND

This study examined participation and performance trends in 'Ironman Hawaii' regarding the nationality of the finishers.

METHODS

Associations between nationalities and race times of 39,706 finishers originating from 124 countries in the 'Ironman Hawaii' from 1985 to 2012 were analyzed using single and multi-level regression analysis.

RESULTS

Most of the finishers originated from the United States of America (47.5%) followed by athletes from Germany (11.7%), Japan (7.9%), Australia (6.7%), Canada (5.2%), Switzerland (2.9%), France (2.3%), Great Britain (2.0%), New Zealand (1.9%), and Austria (1.5%). German women showed the fastest increase in finishers (r(2) = 0.83, p < 0.0001), followed by Australia (r(2) = 0.78, p < 0.0001), Canada (r(2) = 0.78, p < 0.0001) and the USA (r(2) = 0.69, p < 0.0001). Japanese women showed no change in the number of finishers (r(2) = 0.01, p > 0.05). For men, athletes from France showed the steepest increase (r(2) = 0.85, p < 0.0001), followed by Austria (r(2) = 0.68, p < 0.0001), Australia (r(2) = 0.67, p < 0.0001), Brazil (r(2) = 0.60, p < 0.0001), Great Britain (r(2) = 0.46, p < 0.0001), Germany (r(2) = 0.26, p < 0.0001), the United States of America (r(2) = 0.21, p = 0.013) and Switzerland (r(2) = 0.14, p = 0.0044). The number of Japanese men decreased (r(2) = 0.35, p = 0.0009). The number of men from Canada (r(2) = 0.02, p > 0.05) and New Zealand (r(2) = 0.02, p > 0.05) remained unchanged. Regarding female performance, the largest improvements were achieved by Japanese women (17.3%). The fastest race times in 2012 were achieved by US-American women. Women from Japan, Canada, Germany, Australia, and the United States of America improved race times. For men, the largest improvements were achieved by athletes originating from Brazil (20.9%) whereas the fastest race times in 2012 were achieved by athletes from Germany. Race times for athletes originating from Brazil, Austria, Great Britain, Switzerland, Germany, Australia, Canada, Japan, New Zealand and France decreased. Race times in athletes originating from Australia and the United States of America showed no significant changes. Regarding the fastest race times ever, the fastest women originated from the United States (546 ± 7 min) followed by Great Britain (555 ± 15 min) and Switzerland (558 ± 8 min). In men, the fastest finishers originated from the United States (494 ± 7 min), Germany (496 ± 6 min) and Australia (497 ± 5 min).

CONCLUSIONS

The 'Ironman Hawaii' has been dominated by women and men from the United States of America in participation and performance.

Age and gender difference in non-drafting ultra-endurance cycling performance - the 'Swiss Cycling Marathon'

Background

In recent years, there was an increased interest in investigating the gender difference in performance and the age of peak performance in ultra-endurance performances such as ultra-triathlon, ultra-running, and ultra-swimming, but not in ultra-cycling. The aim of the present study was to analyze the gender difference in ultra-cycling performance and the age of peak ultra-cycling performance in the 720-km ‘Swiss Cycling Marathon’, the largest European qualifier for the ‘Race Across America’.

Methods

Changes in the cycling speed and age of 985 finishers including 38 women and 947 men competing in the Swiss Cycling Marathon from 2001 to 2012 covering a distance of 720 km with a change of altitude of 4,993 m were analyzed using linear regression.

Results

The gender difference in performance was 13.6% for the fastest cyclists ever, 13.9% ± 0.5% for the three fastest cyclists ever and 19.1% ± 3.7% for the ten fastest cyclists ever. The gender difference in performance for the annual top three women and men decreased from 35.0% ± 9.5% in 2001 to 20.4% ± 7.7% in 2012 (r² = 0.72, p = 0.01). The annual top three women improved cycling speed from 20.3 ± 3.1 km h⁻¹ in 2003 to 24.8 ± 2.4 km h⁻¹ in 2012 (r² = 0.79, p < 0.01). The cycling speed of the annual top three men remained unchanged at 30.2 ± 0.6 km h⁻¹ (p > 0.05). The age of peak performance for the ten fastest finishers ever was 35.9 ± 9.6 years for men and 38.7 ± 7.8 years for women, respectively (p = 0.47).

Conclusions

The gender difference in ultra-cycling performance decreased over the 2001 to 2012 period in the 720-km Swiss Cycling Marathon for the annual top three cyclists and reached approximately 14%. Both women and men achieved peak performance at the age of approximately 36 to 39 years. Women might close the gender gap in ultra-endurance cycling in longer cycling distances. Future studies need to investigate the gender difference in performance in the Race Across America, the longest nonstop and non-drafting ultra-cycling race in the world.

Age of peak performance in elite male and female Ironman triathletes competing in Ironman Switzerland, a qualifier for the Ironman world championship, Ironman Hawaii, from 1995 to 2011

Background

The age of peak performance in elite endurance athletes has been investigated for elite marathoners, but not for elite Ironman triathletes. The aim of this study was to analyze the age of peak performance in swimming (3.8 km), cycling (180 km), running (42 km), and overall race time for elite female and male Ironman triathletes competing in Ironman Switzerland, a qualifier for the Ironman world championship, known as the Ironman Hawaii.

Methods

The age of the annual top ten overall swimmers, cyclists, runners, and annual overall finishers for both male and female elite triathletes and their corresponding split and overall race times at the Ironman Switzerland were analyzed between 1995 and 2011.

Results

The mean age of the elite Ironman triathletes was 33 ± 3 years for men and 34 ± 4 years for women. For women, the age of peak performance was not significantly different between the three disciplines (P > 0.05), while for men, the best swimmers (29 ± 3 years) were significantly (P < 0.05) younger than the best runners (35 ± 5 years). During the study period, the age of peak performance remained unchanged for men at 31 ± 3 years (P > 0.05), but increased for women from 30 ± 4 years in 1995 to 36 ± 5 years in 2011 (P < 0.01).

Conclusion

Although both women and men improved their overall race times during the 1995–2011 period, the age of peak performance was similar between women and men in the three disciplines and in overall race time. Future studies need to examine the change in age of peak performance across years in the Ironman Hawaii world championship event.