Geographic enrolment of the top 100 in athletics running events from 1996 to 2012

J Sports Med Phys Fitness. 2017 Apr;57(4):418-425. doi: 10.23736/S0022-4707.16.06019-9. Epub 2015 Dec 2.

Abstract

Background: It is widely accepted in the literature that athletes of West African origins achieve the best sprint performances, while athletes originating from East Africa are the most efficient at long distances. So far, no study has measured the evolution of these groups' contribution from 100 m to the marathon.

Methods: Speed, morphology and geographic origin of the top 100 male and female athletes (from 100 m to the marathon) were collected and analyzed over the 1996-2012 period.

Results: The amount of male sprinters (100, 200 and 400 m) originating from West Africa increased from 57.7% in 1996 to 72.3% in 2012, while female sprinters from West Africa increased from 55% to 65% over the same period. This contribution gradually increases from 400 m to 100 m for both sexes. For long-distance runs (3000 m, 10,000 m and marathon), male athletes from East Africa represented 32% in 1996 ; this proportion increased to 65.7% in 2012. It also increased over the same period from 9% to 39% for women. In addition, male and female sprinters originating from West Africa have a significantly higher Body Mass Index (BMI, P<0.05) than athletes of other geographic origin. Conversely, long distances runners' with an East African origin have a significantly lower BMI (P<0.05).

Conclusions: Running best performances are dominated by a few groups including runners with West African ancestry for the sprint distances and East African runners for the long distances. This dominance strengthened from 1996 to 2012 for both sexes in parallel with a reduction of Caucasian and Asian athletes contribution and in relation to muscle mass repartition.

MeSH terms

  • Athletes / statistics & numerical data*
  • Athletic Performance / physiology
  • Athletic Performance / statistics & numerical data*
  • Body Height
  • Body Mass Index
  • Body Weight
  • Cross-Sectional Studies
  • Demography
  • Female
  • Humans
  • Male
  • Racial Groups / statistics & numerical data*
  • Running / physiology
  • Running / statistics & numerical data*