Discriminant Analysis of Anthropometric and Training Variables among Runners of Different Competitive Levels.

Mabliny Thuany,Thayse Natacha Gomes,João Lino Mesquita,Lee Hill,Thomas Rosemann,Beat Knechtle,Raphael F De Souza,Sara Pereira

doi:10.3390/ijerph18084248

Abstract

The purpose of this study was to investigate the multivariate profile of different types of Brazilian runners and to identify the discriminant pattern of the distinct types of runners, as a runners’ ability to self-classify well. The sample comprised 1235 Brazilian runners of both sexes (492 women; 743 men), with a mean age of 37.94 ± 9.46 years. Individual characteristics were obtained through an online questionnaire: Sex, age, body height (m) and body mass (kg), socioeconomic status, and training information (i.e., self-classification, practice time, practice motivation, running pace, frequency and training volume/week). Multivariate analysis of variance was conducted by sex and the discriminant analysis was used to identify which among running pace, practice time, body mass index and volume/training could differentiate groups such as “professional athletes”, “amateur athletes” and “recreational athletes”. For both sexes, running pace was the variable that better discriminated the groups, followed by BMI and volume/week. The practice time is not a good indicator to differentiate runner’s types. In both sexes, semi-professional runners were those that better self-classify themselves, with amateur runners presenting the highest classification error. This information can be used to guide the long-term training, athlete’s selection programs, and to identify the strengths and weaknesses of athletes.

Highlights

There is no one size fits all strategy to determine sport performance, given that performance differs across modalities and specific abilities [1]
Over the past 10 years there has been a growth of 57% in the number of runners participating in marathon and endurance events, with a notable decrease of the gender gap of participants [5]
We suggested that charts or reference values of running pace and body mass index (BMI) can be determined in future studies, considering the runner’s classification

Summary

Introduction

There is no one size fits all strategy to determine sport performance, given that performance differs across modalities and specific abilities [1]. Performance is multifactorial and the identification of variables that allow us to describe and differentiate an athlete’s athletic ability poses a unique challenge [2]. Interest in these variables has grown among amateur and non-professional athletes, especially in activities that are practiced on a large scale [3,4]. Over the past 10 years there has been a growth of 57% in the number of runners participating in marathon and endurance events, with a notable decrease of the gender gap of participants [5]. In 2019, a total of 459,029 marathon finishers were recorded, with most of the events held in the United States (61.6%), the United. Considering 19,614,975 marathon results from 2008–2018 across the globe, there was an increase in the number of participants from India, Portugal and Ireland, while the most representative countries were the United

Objectives

Methods

Results

Discussion

Conclusion