Sport Sciences for Health

, Volume 15, Issue 2, pp 393–398 | Cite as

Human Development Index and the frequency of nations in Athletics World Rankings

  • Patrick Anderson Santos
  • Caio Victor Sousa
  • Samuel da Silva AguiarEmail author
  • Beat Knechtle
  • Pantelis Theodoros Nikolaidis
  • Marcelo Magalhães Sales
  • Thiago dos Santos Rosa
  • Lysleine Alves de Deus
  • Carmen Silvia Grubert Campbell
  • Higor Geovane de Sousa
  • Lucas Duarte Barbosa
  • Herbert Gustavo SimõesEmail author
Original Article



The influence of socioeconomic factors in the achievement of sport success is still a matter of debate. Due to the popularity and low-cost practice, analyses of the Athletics World Ranking (AWR) may provide valuable information. Therefore, we investigated the frequency of different socioeconomic status in the AWR for two events (100 m and 10 k) in three categories: Junior, Elite Professionals and Masters.


Data of 5,011 athletes from 99 nationalities were obtained from the official websites of International Association of Athletics Federations, and World Masters Rankings in the years of 2006–2016. The Human Development Index (HDI) for each nationality was used as a marker of socioeconomic status.


An HDI × age group association was observed (χ2 = 0.001, p = 0.001, φC = 0.322), where the analysis of frequency rate demonstrated a high prevalence of very elevated and elevated HDI in the AWR for the 100 m. For the endurance 10 k race analysis, the HDI × age group association was also observed, with a high prevalence of moderate and low HDI in Junior and Professionals. Regarding the Masters, the prevalence of moderate and low HDI is almost zero. In addition, multiple linear regressions indicate that the HDI, gross domestic product per capita (GDP/capita) and population can predict the frequency of a country in athletics ranking.


There is a high prevalence of elevated and very elevated HDI nationalities in the AWR in sprint races in all age groups. For endurance races, Junior and Professionals had a great prevalence of low/moderate HDI, and Masters are dominated by very elevated HDI. A nation’s frequency in the World Masters Ranking could be indicative of HDI, since an association was found among them.


Sociology Aging Performance Policy 



The authors are thankful to World Masters Rankings and Mr. John Seto (main organizer), as well as the International Athletics Federation (IAAF), the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES - financial code 001), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de Apoio à Pesquisa do Distrito Federal (FAP/DF).

Compliance with ethical standards

Conflict of interest

No potential conflict of interest relevant to this article was reported.

Human and animal rights

All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional research committee and with the 2012 Helsinki declaration.

Informed consent

Informed consent was obtained from all individual participants included in the study.


  1. 1.
    Sharma H, Sharma D (2015) Human development index—revisited: integration of human values. J Hum Values 21(1):23–36CrossRefGoogle Scholar
  2. 2.
    Costa ITD, Cardoso FDSL, Garganta JO (2013) Índice de Desenvolvimento Humano e a Data de Nascimento podem condicionar a ascensão de jogadores de Futebol ao alto nível de rendimento. Motriz 19(1):34–35Google Scholar
  3. 3.
    Eime RM, Harvey J, Charity MJ, Casey M, Westerbeek H, Payne WR (2017) The relationship of sport participation to provision of sports facilities and socioeconomic status: a geographical analysis. Aust NZ J Public Health 41(3):248–255CrossRefGoogle Scholar
  4. 4.
    Zenha V, Resende R, Gomes AR (2009) Desporto de alto rendimento e sucesso escolar: Análise e estudo de factores influentes no seu êxito. Editorial y Centro de Formación Alto Rendimiento 978-84-613-1659-5Google Scholar
  5. 5.
    Starkes JL, Ericsson KA (2003) Expert performance in sports: advances in research on sport expertise. Human Kinetics, pp 251–272Google Scholar
  6. 6.
    Bloom BS, Sosniak LA (1985) Developing talent in young people. Ballantine Books, New York, pp 507–549Google Scholar
  7. 7.
    Côté J, Macdonald DJ, Baker J, Abernethy B (2006) When “where” is more important than “when”: Birthplace and birthdate effects on the achievement of sporting expertise. J Sports Sci 24(10):1065–1073CrossRefPubMedGoogle Scholar
  8. 8.
    Lang JJ, Tremblay MS, Léger L, Olds T, Tomkinson GR (2018) International variability in 20 m shuttle run performance in children and youth: who are the fittest from a 50-country comparison? A systematic literature review with pooling of aggregate results. Br J Sports Med 52(4):276–276CrossRefPubMedGoogle Scholar
  9. 9.
    Kyttä M (2002) Affordances of children’s environments in the context of cities, small towns, suburbs and rural villages in Finland and Belarus. J Environ Psychol 22(1–2):109–123CrossRefGoogle Scholar
  10. 10.
    Bale J, Sang J (2013) Kenyan running: Movement culture, geography and global change. Routledge, AbingdonCrossRefGoogle Scholar
  11. 11.
    Noland RC, Thyfault JP, Henes ST, Whitfield BR, Woodlief TL, Evans JR, Dohm GL (2007) Artificial selection for high-capacity endurance running is protective against high-fat diet-induced insulin resistance. Am J Physiol-Endocrinol Metab 293(1):E31–E41CrossRefPubMedGoogle Scholar
  12. 12.
    Wisløff U, Najjar SM, Ellingsen Ø, Haram PM, Swoap S, Al-Share Q, … Britton SL (2005) Cardiovascular risk factors emerge after artificial selection for low aerobic capacity. Science 307(5708):418–420CrossRefPubMedGoogle Scholar
  13. 13.
    UNDP (2015) 2014 Human Development ReportGoogle Scholar
  14. 14.
    Morin P, Lebel A, Robitaille É, Bisset S (2016) Socioeconomic factors influence physical activity and sport in Quebec schools. J Sch Health 86(11):841–851CrossRefPubMedGoogle Scholar
  15. 15.
    Federico B, Falese L, Marandola D, Capelli G (2013) Socioeconomic differences in sport and physical activity among Italian adults. J Sports Sci 31(4):451–458CrossRefPubMedGoogle Scholar
  16. 16.
    Jayantha K, Ubayachandra EG (2015) Going for gold medals: factors affecting Olympic performance. Int J Sci Res Publ 5(6):2250–3153Google Scholar
  17. 17.
    Beyer JM, Hannah DR (2000) The cultural significance of athletics in US higher education. J Sport Manag 14(2):105–132CrossRefGoogle Scholar
  18. 18.
    Chu D (1982) The American conception of higher education and the formal incorporation of intercollegiate sport. Quest 34(1):53–71CrossRefGoogle Scholar
  19. 19.
    Korhonen MT, Haverinen M, Degens H (2014) 16 Training and nutritional needs. In: Nutrition and performance in masters athletes. CRC Press, pp.291–322Google Scholar
  20. 20.
    Korhonen MT, Cristea A, Alén M, Hakkinen K, Sipila S, Mero A, Suominen H (2006) Aging, muscle fiber type, and contractile function in sprint-trained athletes. J Appl Physiol 101(3):906–917CrossRefPubMedGoogle Scholar
  21. 21.
    Saltin B, Larsen H, Terrados N, Bangsbo J, Bak T, Kim CK, Rolf CJ (1995) Aerobic exercise capacity at sea level and at altitude in Kenyan boys, junior and senior runners compared with Scandinavian runners. Scand J Med Sci Sports 5(4):209–221CrossRefPubMedGoogle Scholar
  22. 22.
    Pitsiladis YP, Onywera VO, Geogiades E, O’connell W, Boit MK (2004) The dominance of Kenyans in distance running. Equine Comp Exercise Physiol 1(4):285–291CrossRefGoogle Scholar
  23. 23.
    Vancini RL, Pesquero JB, Fachina RJ, dos Santos Andrade M, Borin JP, Montagner PC, de Lira CAB (2014) Genetic aspects of athletic performance: the African runners phenomenon. Open Access J Sports Med 5:123PubMedPubMedCentralGoogle Scholar
  24. 24.
    Scott RA, Moran C, Wilson RH, Goodwin WH, Pitsiladis YP (2004) Genetic influence on East African running success. Equine Comp Exercise Physiol 1(4):273–280CrossRefGoogle Scholar
  25. 25.
    Onywera VO, Scott RA, Boit MK, Pitsiladis YP (2006) Demographic characteristics of elite Kenyan endurance runners. J Sports Sci 24(4):415–422CrossRefPubMedGoogle Scholar
  26. 26.
    Guth LM, Roth SM (2013) Genetic influence on athletic performance. Curr Opin Pediatr 25(6):653CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    De Moor MH, Spector TD, Cherkas LF, Falchi M, Hottenga JJ, Boomsma DI, De Geus EJ (2007) Genome-wide linkage scan for athlete status in 700 British female DZ twin pairs. Twin Res Human Genet 10(6):812–820CrossRefGoogle Scholar
  28. 28.
    Silventoinen K, Magnusson PK, Tynelius P, Kaprio J, Rasmussen F (2008) Heritability of body size and muscle strength in young adulthood: a study of one million Swedish men. Genet Epidemiol 32(4):341–349CrossRefPubMedGoogle Scholar
  29. 29.
    Peeters MW, Thomis MA, Loos RJF, Derom CA, Fagard R, Claessens AL, Beunen GP (2007) Heritability of somatotype components: a multivariate analysis. Int J Obesity 31(8):1295CrossRefGoogle Scholar
  30. 30.
    Carter JL (1970) The somatotypes of athletes—a review. Hum Biol 42(4):535–569PubMedGoogle Scholar
  31. 31.
    Conzelmann A (1993) Competitive sport in the second half of life as exemplified by track and field master athletes. Sport und Buch Strauβ, Köln, pp 128 (In German) Google Scholar
  32. 32.
    Kusy K, Zielinski J (2015) Sprinters versus long-distance runners: how to grow old healthy. Exercise Sport Sci Rev 43(1):57–64CrossRefGoogle Scholar
  33. 33.
    Moghani Lankarani M, Assari S (2017) Diabetes, hypertension, obesity, and long-term risk of renal disease mortality: Racial and socioeconomic differences. J Diabetes Investig 8(4):590–599CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Hostinar CE, Ross KM, Chen E, Miller GE (2017) Early-life socioeconomic disadvantage and metabolic health disparities. Psychosom Med 79(5):514CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Nikolaidis PT, Onywera VO, Knechtle B (2017) Running performance, nationality, sex, and age in the 10-km, half-marathon, marathon, and the 100-km ultramarathon IAAF 1999–2015. J Strength Cond Res 31(8):2189–2207CrossRefPubMedGoogle Scholar
  36. 36.
    Nikolaidis P, Zingg M, Knechtle B (2017) Performance trends in age-group runners from 100 m to marathon—The World Championships from 1975 to 2015. Scand J Med Sci sports 27(12):1588–1596CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Italia S.r.l., part of Springer Nature 2019

Authors and Affiliations

  • Patrick Anderson Santos
    • 1
  • Caio Victor Sousa
    • 1
  • Samuel da Silva Aguiar
    • 1
    Email author
  • Beat Knechtle
    • 2
  • Pantelis Theodoros Nikolaidis
    • 3
  • Marcelo Magalhães Sales
    • 4
  • Thiago dos Santos Rosa
    • 1
  • Lysleine Alves de Deus
    • 1
  • Carmen Silvia Grubert Campbell
    • 1
  • Higor Geovane de Sousa
    • 1
  • Lucas Duarte Barbosa
    • 1
  • Herbert Gustavo Simões
    • 1
    Email author
  1. 1.Graduate Program in Physical EducationCatholic University of Brasilia, UCBBrasíliaBrazil
  2. 2.Institute of Primary CareUniversity of ZurichZurichSwitzerland
  3. 3.Exercise Physiology LaboratoryNikaiaGreece
  4. 4.Physical Education DepartmentUniversidade Estadual de GoiásQuirinópolisBrazil

Personalised recommendations