Sports Medicine

, Volume 33, Issue 4, pp 285–300 | Cite as

Secular Trends in the Performance of Children and Adolescents (1980–2000)

An Analysis of 55 Studies of the 20m Shuttle Run Test in 11 Countries
  • Grant R. Tomkinson
  • Luc A. Léger
  • Tim S. Olds
  • Georges Cazorla
Review Article


It is widely believed that the performance of children and adolescents on aerobic fitness tests is declining. To test this hypothesis, this meta-analysis compared the results of 55 reports of the performance of children and adolescents aged 6–19 years who have used the 20m shuttle run test (20mSRT). All data were collected in the period 1981–2000.

Following corrections for methodological variation, the results of all studies were expressed using the common metric of running speed (km/h) at the last completed stage. Raw data were combined with pseudodata generated from reported means and standard deviations using Monte Carlo simulation. Where data were available on children and adolescents from the same country of the same age and sex, but tested at different times, linear regression was used to calculate rates of change. This was possible for 11 (mainly developed) countries, representing a total of 129 882 children and adolescents in 151 age × sex × country slices.

There has been a significant decline in performance in the 11 countries where data were available, and in most age × sex groups, with a sample-weighted mean decline of 0.43% of mean values per year. The decline was most marked in older age groups and the rate of decline was similar for boys and girls.

There has been a very rapid secular decline in the 20mSRT performance of children and adolescents over the last 20 years, at least in developed countries. The rate of decline is not related to the change in the country’s relative wealth, as quantified by per capita gross domestic product (GDP).


Gross Domestic Product Secular Trend Aerobic Fitness Australian Child Aerobic Performance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank the following people for allowing them access to their data: Scott Baker and the South Australian Sports Institute, Georges Baquet, Serge Berthoin, Alberto Buonaccorsi, Sara Mulkearns and Jeff Walkley and the Australian Council for Health, Physical Education and Recreation. Thank you also to the following people for their kindness in providing extra information about their studies: Natalie Balagué, Mario Bellucci, Michael Booth, Colin Boreham, Jan Borms, Valerie Burke, Dean Cooley, William Duquet, Juan García, Giorgos Georgiadis, Beth Hands, Deborah Hoare, Johan Lefèvre, Matt Mahar, Craig Mahoney, Denis Massicotte, Lars McNaughton, Tony Okely, Ryszard Przeweda, Chris Riddoch, Javier Rivas, Willem van Mechelen and Emmanuel Van Praagh. No sources of funding were used to assist in the preparation of this manuscript. The authors have no conflicts of interest that are directly relevant to the content of this manuscript.


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Copyright information

© Adis Data Information BV 2003

Authors and Affiliations

  • Grant R. Tomkinson
    • 1
  • Luc A. Léger
    • 2
  • Tim S. Olds
    • 1
  • Georges Cazorla
    • 3
  1. 1.Computer Simulation Laboratory, School of Health SciencesUniversity of South AustraliaUnderdaleAustralia
  2. 2.Department of KinesiologyUniversity of Montreal, Centre-Ville BranchMontrealCanada
  3. 3.Association for Research and Evaluation of Physical Activity and Sports, Faculty of Sport SciencesUniversity of Bordeaux IITalenceFrance

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