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

Abstract 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.

Authors

Institutions

Publication Details

Journal
Sport Sciences for Health
Published
2026-03-07
DOI
https://doi.org/10.1007/s11332-026-01696-8
Primary Topic
Physical Activity and Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Kevin Kipchumba, Lucy-Joy Wachira, Mabliny Thuany, Thayse Natacha Gomes et al.
Sport Sciences for Health
Physical Activity and Health
article

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

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

Abstract

Abstract 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.

Sport Sciences for HealthVol. 22(2)
Kenyatta University (KE), Universidade Federal da Paraíba (BR), Universidade do Porto (PT), Universidade Federal de Sergipe (BR), University of Zurich (CH), Universidade do Estado do Pará (BR), Hungarian University of Sports Science (HU), Medbase (CH), Universidade Federal do Pará (BR), Universidade de Pernambuco (BR), Józef Piłsudski University of Physical Education in Warsaw (PL)
Partnerships for the goals
Openalex Percentile: Top 29%
Physical Activity and Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.