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Variation and Predictors of Gross Motor Coordination Development in Azorean Children: A Quantile Regression Approach

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  • Sara Pereira

    (Centre of Research, Education, Innovation and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
    Research Center in Sport, Physical Education, and Exercise and Health (CIDEFES), Faculty of Physical Education and Sports, Lusófona University, 1749-024 Lisboa, Portugal)

  • Flávio Bastos

    (Motor Behavior Laboratory, School of Physical Education and Sports, University of São Paulo, São Paulo 05508-030, Brazil)

  • Carla Santos

    (Centre of Research, Education, Innovation and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal)

  • José Maia

    (Centre of Research, Education, Innovation and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal)

  • Go Tani

    (Motor Behavior Laboratory, School of Physical Education and Sports, University of São Paulo, São Paulo 05508-030, Brazil)

  • Leah E. Robinson

    (Child Movement, Activity, & Developmental Health Laboratory, School of Kinesiology, University of Michigan, Ann Arbor, MI 48109, USA)

  • Peter T. Katzmarzyk

    (Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA)

Abstract

We investigated the development of gross motor coordination (GMC) as well as its predictors in school-aged Azorean children. The sample included 181 children (90 girls), followed consecutively for 4 years from 6 to 9 years of age. GMC was assessed with the Körperkoordinationstest für Kinder, and predictors included body mass index, standing long jump, 50-yard dash, and shuttle run. The changes in GMC and the effects of predictors were analyzed with mean-modeling as well as quantile regression. In the latter, we considered the following three quantiles (Q): Q20, Q50, and Q80 as markers of low, median, and high GMC levels, respectively. All analyses were conducted using R software and alpha was set at 5%. The GMC changes were curvilinear in both models, but the quantile approach showed a more encompassing picture of the changes across the three quantiles in both boys and girls with different rates of change. Further, the predictors had different effect sizes across the quantiles in both sexes, but in the mean-model their effects were constant. In conclusion, quantile regression provides more detailed information and permits a more thorough understanding of changes in GMC over time and the influence of putative predictors.

Suggested Citation

  • Sara Pereira & Flávio Bastos & Carla Santos & José Maia & Go Tani & Leah E. Robinson & Peter T. Katzmarzyk, 2022. "Variation and Predictors of Gross Motor Coordination Development in Azorean Children: A Quantile Regression Approach," IJERPH, MDPI, vol. 19(9), pages 1-13, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5417-:d:805259
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    References listed on IDEAS

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    1. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    2. Nebojša Trajković & Špela Bogataj, 2020. "Effects of Neuromuscular Training on Motor Competence and Physical Performance in Young Female Volleyball Players," IJERPH, MDPI, vol. 17(5), pages 1-12, March.
    3. Geraci, Marco, 2014. "Linear Quantile Mixed Models: The lqmm Package for Laplace Quantile Regression," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 57(i13).
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