Is Body Fat a Predictor Variable for Race Performance in Recreational Female Ironman Triathletes?

Knechtle, Beat; Wirth, Andrea; Rosemann, Thomas

doi:10.2478/v10036-011-0001-5

Cited by 9 publications

(10 citation statements)

References 21 publications

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“…In a small sample of recreational female triathletes, personal best time in a marathon ( r = 0.51), personal best time in an Olympic distance triathlon ( r = 0.70), and personal best time in an Ironman triathlon ( r = 0.70) were significantly and positively related to Ironman race time. Also, personal best time in an Olympic distance triathlon was significantly and positively related to personal best time in an Ironman triathlon ( r = 0.63) 29. Personal best times in both an Olympic distance triathlon and a marathon might also be strong and independent predictor variables for Ironman race time in female triathletes, as has been shown here for male athletes.…”

Section: Discussionsupporting

confidence: 75%

Personal best times in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male triathletes

Rüst¹,

Knechtle²,

Knechtle³

et al. 2011

OAJSM

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BackgroundThe purpose of this study was to define predictor variables for recreational male Ironman triathletes, using age and basic measurements of anthropometry, training, and previous performance to establish an equation for the prediction of an Ironman race time for future recreational male Ironman triathletes.MethodsAge and anthropometry, training, and previous experience variables were related to Ironman race time using bivariate and multivariate analysis.ResultsA total of 184 recreational male triathletes, of mean age 40.9 ± 8.4 years, height 1.80 ± 0.06 m, and weight 76.3 ± 8.4 kg completed the Ironman within 691 ± 83 minutes. They spent 13.9 ± 5.0 hours per week in training, covering 6.3 ± 3.1 km of swimming, 194.4 ± 76.6 km of cycling, and 45.0 ± 15.9 km of running. In total, 149 triathletes had completed at least one marathon, and 150 athletes had finished at least one Olympic distance triathlon. They had a personal best time of 130.4 ± 44.2 minutes in an Olympic distance triathlon and of 193.9 ± 31.9 minutes in marathon running. In total, 126 finishers had completed both an Olympic distance triathlon and a marathon. After multivariate analysis, both a personal best time in a marathon (P < 0.0001) and in an Olympic distance triathlon (P < 0.0001) were the best variables related to Ironman race time. Ironman race time (minutes) might be partially predicted by the following equation: (r2 = 0.65, standard error of estimate = 56.8) = 152.1 + 1.332 × (personal best time in a marathon, minutes) + 1.964 × (personal best time in an Olympic distance triathlon, minutes).ConclusionThese results suggest that, in contrast with anthropometric and training characteristics, both the personal best time in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male Ironman triathletes.

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Section: Discussionsupporting

confidence: 75%

Personal best times in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male triathletes

Rüst¹,

Knechtle²,

Knechtle³

et al. 2011

OAJSM

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“…Men have larger skeletal muscle mass [24], correlating with greater muscular strength [16], larger aerobic capacity [17], and lower relative body fatness [25-27] compared to women. Low body fat is an important predictor variable for overall race time in an Ironman triathlon [28].…”

Section: Discussionmentioning

confidence: 99%

“…Low body fat is an important predictor variable for overall race time in an Ironman triathlon [28]. Low body fat was associated with faster race times in male Ironman triathletes [28], while in female triathletes, anthropometric characteristics such as body fat seemed not to be related to Ironman race time [25,27]. However, women retain 7%–9% more percent body fat compared to men [25,26], which is likely to be an advantage for men.…”

Section: Discussionmentioning

confidence: 99%

The age of peak performance in Ironman triathlon: a cross-sectional and longitudinal data analysis

et al. 2013

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BackgroundThe aims of the present study were, firstly, to investigate in a cross-sectional analysis the age of peak Ironman performance within one calendar year in all qualifiers for Ironman Hawaii and Ironman Hawaii; secondly, to determine in a longitudinal analysis on a qualifier for Ironman Hawaii whether the age of peak Ironman performance and Ironman performance itself change across years; and thirdly, to determine the gender difference in performance.MethodsIn a cross-sectional analysis, the age of the top ten finishers for all qualifier races for Ironman Hawaii and Ironman Hawaii was determined in 2010. For a longitudinal analysis, the age and the performance of the annual top ten female and male finishers in a qualifier for Ironman Hawaii was determined in Ironman Switzerland between 1995 and 2010.ResultsIn 19 of the 20 analyzed triathlons held in 2010, there was no difference in the age of peak Ironman performance between women and men (p > 0.05). The only difference in the age of peak Ironman performance between genders was in ‘Ironman Canada’ where men were older than women (p = 0.023). For all 20 races, the age of peak Ironman performance was 32.2 ± 1.5 years for men and 33.0 ± 1.6 years for women (p > 0.05). In Ironman Switzerland, there was no difference in the age of peak Ironman performance between genders for top ten women and men from 1995 to 2010 (F = 0.06, p = 0.8). The mean age of top ten women and men was 31.4 ± 1.7 and 31.5 ± 1.7 years (Cohen's d = 0.06), respectively. The gender difference in performance in the three disciplines and for overall race time decreased significantly across years. Men and women improved overall race times by approximately 1.2 and 4.2 min/year, respectively.ConclusionsWomen and men peak at a similar age of 32–33 years in an Ironman triathlon with no gender difference. In a qualifier for Ironman Hawaii, the age of peak Ironman performance remained unchanged across years. In contrast, gender differences in performance in Ironman Switzerland decreased during the studied period, suggesting that elite female Ironman triathletes might still narrow the gender gap in the future.

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“…The personal best time in a marathon seems to be a strong predictor variable for female Ironman race time (24,34) and this finding raises the question whether female Ironman triathletes are similar to female marathoners. Since characteristics of both anthropometry and training were related in both marathoners and Ironman triathletes to their specific races times, we intended to investigate whether recreational female marathoners and recreational female Ironman triathletes were similar regarding anthropometry and training.…”

Section: Introductionmentioning

confidence: 95%

“…Leake and Carter (26) reported that training parameters were more important than anthropometric measurements in the prediction of performance for 16 female triathletes. In studies investigating small samples of recreational female Ironman triathletes, weekly training hours (21,22), personal best times in an Ironman triathlon (21,24), personal best time in a marathon (24,34), and personal best time in an Olympic distance triathlon (24,34) were related to an Ironman race time.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Anthropometric and Training Characteristics between Recreational Female Marathoners and Recreational Female Ironman Triathletes

Rüst

Knechtle

Knechtle³

et al. 2013

Chin. J. Physiol.

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A personal best marathon time has been reported as a strong predictor variable for an Ironman race time in recreational female Ironman triathletes. This raises the question whether recreational female Ironman triathletes are similar to recreational female marathoners. We investigated similarities and differences in anthropometry and training between 53 recreational female Ironman triathletes and 46 recreational female marathoners. The association of anthropometric variables and training characteristics with race time was investigated using bi- and multi-variate analysis. The Ironman triathletes were younger (P < 0.01), had a lower skin-fold thickness at pectoral (P < 0.001), axillar (P < 0.01), and subscapular (P < 0.05) site, but a thicker skin-fold thickness at the calf site (P < 0.01) compared to the marathoners. Overall weekly training hours were higher in the Ironman triathletes (P < 0.001). The triathletes were running faster during training than the marathoners (P < 0.05). For the triathletes, neither an anthropometric nor a training variable showed an association with overall Ironman race time after bi-variate analysis. In the multi-variate analysis, running speed during training was related to marathon split time for the Ironman triathletes (P = 0.01) and to marathon race time for the marathoners (P = 0.01). To conclude, although personal best marathon time is a strong predictor variable for performance in recreational female Ironman triathletes, there are differences in both anthropometry and training between recreational female Ironman triathletes and recreational female marathoners and different predictor variables for race performance in these two groups of athletes. These findings suggest that recreational female Ironman triathletes are not comparable to recreational female marathoners regarding the association between anthropometric and training characteristics with race time.

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Is Body Fat a Predictor Variable for Race Performance in Recreational Female Ironman Triathletes?

Cited by 9 publications

References 21 publications

Personal best times in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male triathletes

Personal best times in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male triathletes

The age of peak performance in Ironman triathlon: a cross-sectional and longitudinal data analysis

A Comparison of Anthropometric and Training Characteristics between Recreational Female Marathoners and Recreational Female Ironman Triathletes

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