Where Are the Best European Road Runners and What Are the Country Variables Related to It?

Mabliny Thuany, Sara Pereira, Lee Hill, Jean Carlos Santos, Thomas Rosemann, Beat Knechtle and Thayse Natacha Gomes
Additional contact information
Mabliny Thuany: CIFI2D, Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
Sara Pereira: CIFI2D, Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
Lee Hill: Department of Pediatrics, Division of Gastroenterology & Nutrition, McMaster University, Hamilton, ON L8N 3Z5, Canada
Jean Carlos Santos: Department of Physical Education, Federal University of Sergipe, São Cristóvão 49100-000, Brazil
Thomas Rosemann: Institute of Primary Care, University of Zurich, 8091 Zurich, Switzerland
Beat Knechtle: Medbase St. Gallen Am Vadianplatz, Vadianstrasse 26, 9001 St. Gallen, Switzerland
Thayse Natacha Gomes: Department of Physical Education, Federal University of Sergipe, São Cristóvão 49100-000, Brazil

Sustainability, 2021, vol. 13, issue 14, 1-9

Abstract: Background: The environment can play a relevant role in performance in runners. This study aimed to verify the distribution of the best European road runners across the continent, and to investigate variables related to country representatives in the European Senior outdoor top list 2019. Methods: The sample comprised 563 European runners, aged 18–48 years, ranked in the European Senior outdoor top list 2019 for distances of 10–42 km. Country-related variables were gross domestic product (GDP), competition place, population size, and sports investment. The countries were categorized as “top ten countries” or “other countries”. Binary logistic regression was used for analysis. Results: The United Kingdom showed the highest prevalence of runners in the ranking (men—17.6%; women—23.0%), followed by Spain (male ranking—12.1%) and Germany (female ranking—8.6%). For men, sports investment (OR = 1.13; CI95% = 1.03–1.28) and country GDP (OR = 0.96; CI95% = 0.93–0.98) showed an association with the chances of the athlete to reach the Top 10 ranking, while among women, the only variable significantly related was the competition venue (OR = 3.97; CI95% = 1.40–11.23). Conclusion: As in other sports considered “non-expensive”, the economic and demographic characteristics of the place where athletes train can provide advantages in performance.

Keywords: running; predictors; socioeconomic (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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