Anthropometric Characteristics of Ultramarathoners

Department of Physical Medicine & Rehabilitation, 10535 Hospital Way (117), Sacramento, California 95655-1200, United States.
International Journal of Sports Medicine (Impact Factor: 2.07). 04/2008; 29(10):808-11. DOI: 10.1055/s-2008-1038434
Source: PubMed


Little is known about the anthropometric characteristics of ultramarathon runners. The present work reports on the physical characteristics of the 392 (310 males, 82 females) starters and 270 (216 males, 54 females) finishers of the 2007 Western States Endurance Run, one of the largest 161-km trail runs in North America. Among the starters, mean (and 25th to 75th percentiles) body mass index (BMI) values were 23.2 (21.6 - 24.6) and 20.6 (19.4 - 21.9) kg . m (-2) for the men and women, respectively. Men were significantly taller, heavier and had greater BMI's across all age groups compared with the women. Among the top-5 overall finishers, mean BMI values were 23.2 (range 22.4 - 24.7) for the men and 19.8 (range 17.3 - 21.1) for the women. Average running speed and BMI were negatively correlated for both men (r (2) = 0.11, p < 0.0001) and women (r (2) = 0.10, p = 0.02). From this analysis, it is concluded that those participating in ultramarathon runs can vary widely in physical characteristics with BMI values that would classify some individuals as underweight and others as overweight. BMI varied considerably even among the top finishers, but lower BMI values were associated with faster running times.

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    • "Previous experience seems, however , to be the most important predictor variable in ultra-marathon running performance [22] [24] [29]. Personal best marathon time was a strong predictor in mountain ultra-marathoners [22]. In 24-hour ultra-marathoners, anthropometry and training volume had no major effect on ultra-marathon race time but a fast personal best marathon time showed the only significant association with ultra-marathon race time [24]. "
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    • "Potential explanations for these disparate findings could be the longer race time in 100 miles (i.e. 161 km) ultra-marathons (Hoffman and Wegelin 2009) compared to 100 km ultra-marathons (Knechtle et al. 2012b) and differences in anthropometry and physiology between female and male ultra-marathoners (Hoffman 2008). The fastest 100 km race times are 6:13:33 h:min:sec for men, set in 1998 by Takahiro Sunada, and 6:33:11 h:min:sec for women, set in 2000 by Tomoe Abe (IAAF Athletics, "
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    ABSTRACT: Improved performance has been reported for master runners (i.e. athletes older than 40 years) in both single marathons and single ultra-marathons. This study investigated performance trends of age group ultra-marathoners competing in all 100 km and 100 miles races held worldwide between 1971 and 2013. Changes in running speeds across years were investigated for the annual ten fastest 5-year age group finishers using linear, non-linear and multi-level regression analyses. In 100 km, running speed remained unchanged in women in 25-29 years, increased non-linearly in 30-34 to 55-59 years, and linearly in 60-64 years. In men, running speed increased non-linearly in 18-24 to 60-64 years and linearly in 65-69 to 75-79 years. In 100 miles, running speed increased in women linearly in 25-29 and 30-34 years, non-linearly in 35-39 to 45-49 years, and linearly in 50-54 and 55-59 years. For men, running speed increased linearly in 18-24 years, non-linearly in 25-29 to 45-49 years, and linearly in 50-54 to 65-69 years. Overall, the faster race times over the last 30 years are a result of all top ten finishers getting faster. These findings suggest that athletes in younger to middle age groups (i.e. 25-35 to 50-65 years depending upon sex and distance) have reached their limits due to a non-linear increase in running speed whereas runners in very young (i.e. younger than 25-35 years) and older age groups (i.e. older than 50-65 years) depending upon sex and distance might still improve their performance due to a linear increase in running speed.
    SpringerPlus 07/2014; 3(1):331. DOI:10.1186/2193-1801-3-331
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    • "Anthropometry also seems to play an important role in running times. Several studies, for example, have shown positive associations between anthropometric characteristics including body mass [20–22], body mass index [21, 23, 24], body fat percentage [21, 24, 25], skin-fold thickness of the lower body [26, 27], the circumference of upper arm [21, 22, 28] and the circumference of calf [29] and running times. On the other hand, no significant correlations have also been reported between anthropometric characteristics including body mass index, skeletal muscle mass, leg length, skinfold thicknesses or limb circumferences; and race time in multi-sports athletes competing in a Deca Iron ultra-triathlon [30]. "
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    ABSTRACT: Purpose Lower limb skin-fold thicknesses have been differentially associated with sex in elite runners. Front thigh and medial calf skin-fold appear to be related to 1,500m and 10,000m time in men but 400m time in women. The aim of the present study was to compare anthropometric and training characteristics in recreational female and male half-marathoners. Methods The association between both anthropometry and training characteristics and race time was investigated in 83 female and 147 male recreational half marathoners using bi- and multi-variate analyses. Results In men, body fat percentage (β=0.6), running speed during training (β=-3.7), and body mass index (β=1.9) were related to half-marathon race time after multi-variate analysis. After exclusion of body mass index, r2 decreased from 0.51 to 0.49, but body fat percentage (β=0.8) and running speed during training (β=-4.1) remained predictive. In women, body fat percentage (β=0.75) and speed during training (β=-6.5) were related to race time (r2=0.73). For women, the exclusion of body mass index had no consequence on the predictive variables for half-marathon race time. Conclusion To summarize, in both female and male recreational half-marathoners, both body fat percentage and running speed during training sessions were related to half-marathon race times when corrected with co-variates after multi-variate regression analyses.
    Asian Journal of Sports Medicine 03/2014; 5(1):10-20. DOI:10.5167/uzh-95130
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