1. Introduction

Sports performance is a multifactorial trait, determined by different predictors related to both the subject and the environment^[1]. According to ecological model theory, human development (or a given behaviour) is the result of the interaction of variables derived from different levels, organized in a hierarchical structure, comprising variables directly related to the subjects as well as those related to social, physical, and natural environments^[2][3][4]. In this context, athletes have different life stories, train with different coaches, and live in given neighbourhoods, which are located in cities/states/countries with distinct sports policies, different natural environments, and designs^[5]. All of these aspects act together to produce the different athletes’ profiles and performance^[5][6].

2. Running Performance Variability

These relationships can be illustrated when considering changes in runners’ performance worldwide during the last decades^[7]. As the largest South American country, Brazil presents nearly continental dimensions and sociocultural contrasts^[8], making such differences in runners’ performances notable. In the manuscript “Running performance variability among runners from different Brazilian states: a multilevel approach”, published in International Journal of Environmental Research and Public Health (doi: 10.3390/ijerph18073781), we have identified a relevant between- and within-state variance in running performance (figure 1).

Figure 1. Running pace variance between Brazilian states, sorted by the median. Box-plot elements are as follow: cross, median; superior and inferior box limits, mean 75th and 25th percentiles, respectively; top and bottom bars, maximum and minimum normal values, respectively; circles indicate outliers.

. Running pace variance between Brazilian states, sorted by the median. Box-plot elements are as follow: cross, median; superior and inferior box limits, mean 75th and 25th percentiles, respectively; top and bottom bars, maximum and minimum normal values, respectively; circles indicate outliers.

In addition, we have identified state-level differences explained 3% of the total variance in Brazilian runners’ performance, with 54.4% of this variance being explained by running events, Human Development Index, and violence index. At the individual level, biological (sex, age, and BMI), socio-demographic (SES), and training (training frequency and volume/week) variables explained 56.4% of the 97% of the variance fraction associated with individual-level characteristics.

These results reinforce the significant role of the environment on the explanation of running performance variability; given the diversity across states, environmental variables should not be neglected, as they are relevant to the exploration of other variables possibly related to running performance.