IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i7p3781-d530280.html
   My bibliography  Save this article

Running Performance Variability among Runners from Different Brazilian States: A Multilevel Approach

Author

Listed:
  • Mabliny Thuany

    (Post-Graduation Program of Physical Education, Federal University of Sergipe (UFS), São Cristóvão, 49100-000 Sergipe, Brazil)

  • Thayse Natacha Gomes

    (Post-Graduation Program of Physical Education, Federal University of Sergipe (UFS), São Cristóvão, 49100-000 Sergipe, Brazil)

  • Lee Hill

    (Division of Gastroenterology & Nutrition, Department of Pediatrics, McMaster University, Hamilton, ON L8N 3Z5, Canada)

  • 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)

  • Marcos B. Almeida

    (Post-Graduation Program of Physical Education, Federal University of Sergipe (UFS), São Cristóvão, 49100-000 Sergipe, Brazil)

Abstract

The ecological model theory highlights that human development (or a given behavior) is the result of the interaction of variables derived from different levels, comprising those directly related to the subjects and those related to the environment. Given that, the purpose of this study is to establish whether runners’ performance may vary among different Brazilian states, as the factors associated with this difference. The sample comprised 1151 Brazilian runners (61.8% men) that completed an online questionnaire, providing information about biological (sex, age, height, and weight), training (running pace, frequency and volume/week, and motivation), sociodemographic (place of residence and wage) aspects, and perceptions about the environmental influences on the practice. Information about state variables was obtained from official institutes, and comprised the human development index (HDI), athletics events, and violence index. Multilevel analysis was conducted in HLM software. State-level characteristics explained ≈3% of the total variance in running performance. Of the total variance explained for the individual level, 56.4% was associated with male sex (β = −54.98; p < 0.001), age (β = 1.09; p < 0.001), body mass index (β = 6.86; p < 0.001), economic status (β = 6.23; p = 0.003), the perception of the natural environment (β = 7.58; p = 0.02), training frequency (β = −16.64; p < 0.001), and weekly volume (β = −0.30; p < 0.001). At the state level, only athletics events presented a positive and significant influence on performance. There is a significant role of the environment on the explanation of running performance variability, and 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.

Suggested Citation

  • Mabliny Thuany & Thayse Natacha Gomes & Lee Hill & Thomas Rosemann & Beat Knechtle & Marcos B. Almeida, 2021. "Running Performance Variability among Runners from Different Brazilian States: A Multilevel Approach," IJERPH, MDPI, vol. 18(7), pages 1-12, April.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:7:p:3781-:d:530280
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/7/3781/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/7/3781/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mark Janssen & Ruben Walravens & Erik Thibaut & Jeroen Scheerder & Aarnout Brombacher & Steven Vos, 2020. "Understanding Different Types of Recreational Runners and How They Use Running-Related Technology," IJERPH, MDPI, vol. 17(7), pages 1-18, March.
    2. Pravin K. Trivedi & David M. Zimmer, 2014. "Success at the Summer Olympics: How Much Do Economic Factors Explain?," Econometrics, MDPI, vol. 2(4), pages 1-34, December.
    3. Cristóbal Sánchez Muñoz & José J. Muros & Óscar López Belmonte & Mikel Zabala, 2020. "Anthropometric Characteristics, Body Composition and Somatotype of Elite Male Young Runners," IJERPH, MDPI, vol. 17(2), pages 1-10, January.
    4. Zhanbing Ren & Yifan Zuo & Yudan Ma & Mu Zhang & Lee Smith & Lin Yang & Paul D. Loprinzi & Qian Yu & Liye Zou, 2020. "The Natural Environmental Factors Influencing the Spatial Distribution of Marathon Event: A Case Study from China," IJERPH, MDPI, vol. 17(7), pages 1-17, March.
    5. Pantelis Theodoros Nikolaidis & Thomas Rosemann & Beat Knechtle, 2020. "Skinfold Thickness Distribution in Recreational Marathon Runners," IJERPH, MDPI, vol. 17(9), pages 1-7, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mabliny Thuany & Beat Knechtle & Thomas Rosemann & Marcos B. Almeida & Thayse Natacha Gomes, 2021. "Running around the Country: An Analysis of the Running Phenomenon among Brazilian Runners," IJERPH, MDPI, vol. 18(12), pages 1-9, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daphne Menheere & Mark Janssen & Mathias Funk & Erik van der Spek & Carine Lallemand & Steven Vos, 2020. "Runner’s Perceptions of Reasons to Quit Running: Influence of Gender, Age and Running-Related Characteristics," IJERPH, MDPI, vol. 17(17), pages 1-12, August.
    2. Francesco Campa & Analiza M. Silva & Catarina N. Matias & Cristina P. Monteiro & Antonio Paoli & João Pedro Nunes & Jacopo Talluri & Henry Lukaski & Stefania Toselli, 2020. "Body Water Content and Morphological Characteristics Modify Bioimpedance Vector Patterns in Volleyball, Soccer, and Rugby Players," IJERPH, MDPI, vol. 17(18), pages 1-12, September.
    3. Schlembach, Christoph & Schmidt, Sascha L. & Schreyer, Dominik & Wunderlich, Linus, 2022. "Forecasting the Olympic medal distribution – A socioeconomic machine learning model," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    4. San-Jun Yang & Fan Yang & Yuan Gao & Yan-Feng Su & Wei Sun & Sheng-Wei Jia & Yu Wang & Wing-Kai Lam, 2022. "Gender and Age Differences in Performance of Over 70,000 Chinese Finishers in the Half- and Full-Marathon Events," IJERPH, MDPI, vol. 19(13), pages 1-9, June.
    5. Raquel Vaquero-Cristóbal & Mario Albaladejo-Saura & Ana E. Luna-Badachi & Francisco Esparza-Ros, 2020. "Differences in Fat Mass Estimation Formulas in Physically Active Adult Population and Relationship with Sums of Skinfolds," IJERPH, MDPI, vol. 17(21), pages 1-12, October.
    6. Kobe Helsen & Mark Janssen & Steven Vos & Jeroen Scheerder, 2022. "Two of a Kind? Similarities and Differences between Runners and Walkers in Sociodemographic Characteristics, Sports Related Characteristics and Wearable Usage," IJERPH, MDPI, vol. 19(15), pages 1-17, July.
    7. Mario Albaladejo-Saura & Raquel Vaquero-Cristóbal & Noelia González-Gálvez & Francisco Esparza-Ros, 2021. "Relationship between Biological Maturation, Physical Fitness, and Kinanthropometric Variables of Young Athletes: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 18(1), pages 1-20, January.
    8. Nicolas Scelles & Wladimir Andreff & Liliane Bonnal & Madeleine Andreff & Pascal Favard, 2020. "Forecasting National Medal Totals at the Summer Olympic Games Reconsidered," Social Science Quarterly, Southwestern Social Science Association, vol. 101(2), pages 697-711, March.
    9. Mabliny Thuany & Sara Pereira & Lee Hill & Jean Carlos Santos & Thomas Rosemann & Beat Knechtle & Thayse Natacha Gomes, 2021. "Where Are the Best European Road Runners and What Are the Country Variables Related to It?," Sustainability, MDPI, vol. 13(14), pages 1-9, July.
    10. Mohamad Motevalli & Derrick Tanous & Gerold Wirnitzer & Claus Leitzmann & Thomas Rosemann & Beat Knechtle & Katharina Wirnitzer, 2022. "Sex Differences in Racing History of Recreational 10 km to Ultra Runners (Part B)—Results from the NURMI Study (Step 2)," IJERPH, MDPI, vol. 19(20), pages 1-10, October.
    11. Kufenko, Vadim & Geloso, Vincent, 2021. "Who are the champions? Inequality, economic freedom and the Olympics," Journal of Institutional Economics, Cambridge University Press, vol. 17(3), pages 411-427, June.
    12. Gaëtan Martini & Jean-François Brunelle & Vincent Lalande & Jean Lemoyne, 2022. "Elite Adolescent Ice Hockey Players: Analyzing Associations between Anthropometry, Fitness, and On-Ice Performance," IJERPH, MDPI, vol. 19(15), pages 1-19, July.
    13. Florin Valentin Leuciuc & Ileana Petrariu & Gheorghe Pricop & Dan Mihai Rohozneanu & Ileana Monica Popovici, 2022. "Toward an Anthropometric Pattern in Elite Male Handball," IJERPH, MDPI, vol. 19(5), pages 1-14, February.
    14. Francesco Campa & Catarina N. Matias & Pantelis T. Nikolaidis & Henry Lukaski & Jacopo Talluri & Stefania Toselli, 2020. "Prediction of Somatotype from Bioimpedance Analysis in Elite Youth Soccer Players," IJERPH, MDPI, vol. 17(21), pages 1-10, November.
    15. Mabliny Thuany & Raphael F. de Souza & Lee Hill & João Lino Mesquita & Thomas Rosemann & Beat Knechtle & Sara Pereira & Thayse Natacha Gomes, 2021. "Discriminant Analysis of Anthropometric and Training Variables among Runners of Different Competitive Levels," IJERPH, MDPI, vol. 18(8), pages 1-9, April.
    16. Yi Ouyang & Xiaomei Cai & Jie Li & Quan Gao, 2021. "Investigating the “Embodied Spaces of Health” in Marathon Running: The Roles of Embodiment, Wearable Technology, and Affective Atmospheres," IJERPH, MDPI, vol. 19(1), pages 1-13, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:7:p:3781-:d:530280. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.