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<p>We aimed to verify if there is a direct relation between countries’ human development index (HDI) and running performance among non-professional runners of different countries. This is a cross-sectional and multicountry study. A web survey was used to assess sociodemographic factors, training characteristics, and information regarding the support provided by peers during long-term training. HDI data was obtained for each country. Network analysis was conducted using the Fruchternan-Reingold algorithm, and betweenness, closeness, and expected influence measures were reported. Data analysis was performed using JASP software. We sampled 279 runners from Brazil, Portugal, Spain, Poland, and Kenya (51.9% male; mean age 39.2 ± 9.4&#xa0;years). We found a direct and positive association between HDI and training volume, as well as the age at which individuals started their running training. Conversely, HDI showed a weaker, negative relationship with support for initiating training commitment and current performance level. Variables with higher betweenness values were training volume and support for current performance, while support for starting practice and running pace had higher closeness and expected influence values. The findings suggest that HDI, as a macroeconomic component, significantly influences running practice and is closely intertwined with sociodemographic factors, training characteristics, and peer support among non-professional runners from different nations.</p>

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Understanding the complex interplay of macro- and micro-level factors in non-professional runners’ performance: a cross-sectional study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月7日

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  • Mabliny Thuany,
  • Thayse Natacha Gomes,
  • Kevin Kipchumba,
  • Lucy-Joy Wachira,
  • Mateusz Rozmiarek,
  • Beat Knechtle,
  • Ewa Malchrowicz-Mośko,
  • Ramiro Rolim,
  • Marcos André Moura dos Santos

摘要

We aimed to verify if there is a direct relation between countries’ human development index (HDI) and running performance among non-professional runners of different countries. This is a cross-sectional and multicountry study. A web survey was used to assess sociodemographic factors, training characteristics, and information regarding the support provided by peers during long-term training. HDI data was obtained for each country. Network analysis was conducted using the Fruchternan-Reingold algorithm, and betweenness, closeness, and expected influence measures were reported. Data analysis was performed using JASP software. We sampled 279 runners from Brazil, Portugal, Spain, Poland, and Kenya (51.9% male; mean age 39.2 ± 9.4 years). We found a direct and positive association between HDI and training volume, as well as the age at which individuals started their running training. Conversely, HDI showed a weaker, negative relationship with support for initiating training commitment and current performance level. Variables with higher betweenness values were training volume and support for current performance, while support for starting practice and running pace had higher closeness and expected influence values. The findings suggest that HDI, as a macroeconomic component, significantly influences running practice and is closely intertwined with sociodemographic factors, training characteristics, and peer support among non-professional runners from different nations.