Thirteen years of the fight against doping in figures

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Bibliographische Detailangaben
Deutscher übersetzter Titel:13 Jahre Anti-Doping-Kampf in Zahlen
Autor:Aguilar, Millán; Muñoz-Guerra Revilla, Jesus Alberto; Mar Plata, María del; Del Coso, Juan
Erschienen in:Drug testing and analysis
Veröffentlicht:9 (2017), 5/6, S. 866-869, Lit.
Format: Literatur (SPOLIT)
Publikationstyp: Zeitschriftenartikel
Medienart: Elektronische Ressource (online) Gedruckte Ressource
Sprache:Englisch
ISSN:1942-7603, 1942-7611
DOI:10.1002/dta.2168
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Erfassungsnummer:PU201709008286
Quelle:BISp

Abstract des Autors

Every year, the World Anti-Doping Agency (WADA) publishes the main statistics reported by the accredited laboratories, which provide very valuable information for assessing changes in the patterns of doping in sports over time. Using the information provided since 2003 as the basis for the analysis, the evolution of doping/anti-doping figures over the last decade can be examined in reasonable detail, at least in reference to samples analyzed and categories of substances more commonly found in athletes' samples. This brief analysis of the WADA statistical reports leads us to the following outcomes: the increase in anti-doping pressure from 2003 to 2015, as evidenced by increased numbers of samples analyzed and banned substances, has not directly produced a higher frequency of adverse/atypical findings. Although this could be interpreted as steady state in the capacity to detect doping through this whole period, it also resulted in a significant increase in the absolute number of samples catalogued as doping (from 2247 in 2003 to 5912 in 2015). Anabolic agents have been the most common doping substances detected in all statistics reports while the remaining groups of substances are much less frequently found in doping control samples. Given that one might have expected the enhancement of the anti-doping programme led by WADA over this last decade to have increased the percentage of adverse/atypical findings, the fact that it did not might indicate the need to take another step in sampling strategies, such as ‘more intelligent testing’ based on the differences in the prevalence of doping substances among sports.