Anthropometric characteristics of top-class Kenyan marathon runners

Not much to say:

Anthropometric characteristics of top-class Kenyan marathon runners.
Vernillo G, Schena F, Berardelli C, Rosa G, Galvani C, Maggioni M, Agnello L, La Torre A.
J Sports Med Phys Fitness. 2013 Aug;53(4):403-408.
Aim: This study aims to: 1) describe the current anthropometric profiles of Kenyan marathon runners and 2) establish a set of reference values useful for future investigations on athlete selection, talent identification, and training programme development.
Methods: The participants were 14 male top-class Kenyan marathon runners (mean [s] age 27.71 [3.75] yrs, height 171.21 [6.12] cm, body mass 57.71 [4.02] kg, marathon personal best 02h 07min 16s (01min 55s); training volume: 180-220 km·wk-1; high:low intensity training ratio: 1:2). The anthropometric profiles included the measurement of skinfolds, and segment lengths, breadths, and girths. To estimate body density (BD) multiple regression equations were calculated using the sum of 7-skinfolds method and then converted to percentage of body fat (%BF). The somatotype, somatotype dispersion mean (SDM), somatotype attitudinal mean (SAM), and height to weight ratio (HWR) as well as the skinfolds extremity to trunk ratio (E:T) were also calculated.
Results: The mean (s) of BD, %BF, SDM, SAM, HWR and E:T were 1.13 (0.02), 8.87 (0.07) %, 4.58 (3.62), 0.51 (0.09), 44.32 (1.06), and 0.36 (0.11), respectively. The mean (s) endomorphy, mesomorphy, and ectomorphy were 1.53 (0.32), 1.61 (1.81), and 3.86 (0.78), respectively.
Conclusion: Top-class Kenyan marathon runners seem to have ectomorphy as dominant, with endomorphy and mesomorphy more than one-half unit lower. Despite population comparisons would be required to identify any connection between specific anthropometric dimensions, these reference data should be useful to practitioners and researchers, providing useful information for talent identification and development and for the assessment of training progression in marathon.

Control group? Are they any different to non-elite runners?
Reference group? Are they any different to the general population?

Here is a 2006 study that did include a control group:

Demographic characteristics of elite Kenyan endurance runners.
Vincent O Onywera, Robert A Scott, Michael K Boit, Yannis P Pitsiladis
Journal of Sports Sciences 05/2006; 24(4):415-22
Kenyan athletes have dominated international distance running in recent years. Explanations for their success include favourable physiological characteristics, which could include favourable genetic endowment, and advantageous environmental conditions. The aim of this study was to compare the demographic characteristics of elite Kenyan runners with those of the general Kenyan population. Questionnaires, administered to 404 elite Kenyan runners specializing in distances ranging from the 800 m to the marathon and 87 Kenyan controls, obtained information on place of birth, language, and distance and method of travel to school. Athletes were separated into two groups according to athletic success: those who competed in international competition and those who competed in national competition. The athletes differed from controls in regional distribution, language, and distance and method of travel to school; athletes also differed from each other with the exception of method of travel to school. Most national and international athletes came from the Rift Valley province (controls 20%, national athletes 65%, international athletes 81%), belonged to the Kalenjin ethnic group (controls 8%, national athletes 49%, international athletes 76%) and Nandi sub-tribe (controls 5%, national athletes 25%, international athletes 44%), and spoke languages of Nilotic origin (controls 21%, national athletes 60%, international athletes 79%). A higher proportion of all athletes ran to school each day (controls 22%, national athletes 73%, international athletes 81%) and covered greater distances. In conclusion, Kenyan runners are from a distinctive environmental background in terms of geographical distribution, ethnicity and travelled further to school, mostly by running. These findings highlight the importance of environmental and social factors in the success of Kenyan runners.

See how much more valuable the results are when a control group is included.

As always: I go where the evidence takes me until convinced otherwise and without a control or reference group, the results don’t mean much.

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3 Responses to Anthropometric characteristics of top-class Kenyan marathon runners

  1. Russell E. Jackson October 30, 2013 at 5:39 pm #

    Craig,

    I believe that you are missing the point of the study by Vernillio et al. The intention was not to compare other groups with the kenyan group. The idea was to describe the current anthropometric profiles of Kenyan marathon runners and establish a set of reference values useful for future investigations on athlete selection, talent identification, and training programme development. This requires no control group. The study was actually very elegant and well received by academic peers.

    • Craig Payne October 30, 2013 at 5:56 pm #

      Thanks. But, without a control group how are we supposed to know if those same characteristics were not shared with non-elite runners or the general population? Are the characteristics they described common in elite runners or runners in general or even in the general population?

      One of the aims of the study was to: “establish a set of reference values useful for future investigations on athlete selection, talent identification, and training programme development“. Without a control group of non-elite runners it failed to achieve that aim.

      • Kevin A. Kirby, DPM November 7, 2013 at 4:52 pm #

        I agree Craig. Without a control group to see if other individuals who were actually very slow runners had identical anthropometic characteristics as the elite runners, or if the anthropetric characteristics of the elite runners were truly characteristic of elite runners only, then I don’t see the point in such a study.

        Here’s a novel idea. If you want to determine “reference data” that is “useful to practitioners and researchers, providing useful information for talent identification and development and for the assessment of training progression in marathon”, I would suggest bringing a stopwatch to a 10K race watch how the runners compete in that race. Those two things are probably more important than any “anthropometic characteristics” that any researcher can measure in determing marathon performance.

        I know, too simple. 😉

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