IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i9p5417-d805259.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/9/5417/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/9/5417/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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).
    3. 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).
    Full references (including those not matched with items on IDEAS)

    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. Koller, Manuel, 2016. "robustlmm: An R Package for Robust Estimation of Linear Mixed-Effects Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 75(i06).
    2. Xiaoming Lu & Zhaozhi Fan, 2020. "Generalized linear mixed quantile regression with panel data," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-16, August.
    3. JANSSENS, Jochen & DE CORTE, Annelies & SÖRENSEN, Kenneth, 2016. "Water distribution network design optimisation with respect to reliability," Working Papers 2016007, University of Antwerp, Faculty of Business and Economics.
    4. Raymond Hernandez & Elizabeth A. Pyatak & Cheryl L. P. Vigen & Haomiao Jin & Stefan Schneider & Donna Spruijt-Metz & Shawn C. Roll, 2021. "Understanding Worker Well-Being Relative to High-Workload and Recovery Activities across a Whole Day: Pilot Testing an Ecological Momentary Assessment Technique," IJERPH, MDPI, vol. 18(19), pages 1-17, October.
    5. Christopher Hassall & Michael Nisbet & Evan Norcliffe & He Wang, 2024. "The Potential Health Benefits of Urban Tree Planting Suggested through Immersive Environments," Land, MDPI, vol. 13(3), pages 1-12, February.
    6. Jie Zhao & Ji Chen & Damien Beillouin & Hans Lambers & Yadong Yang & Pete Smith & Zhaohai Zeng & Jørgen E. Olesen & Huadong Zang, 2022. "Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    7. Elisabeth Beckmann & Lukas Olbrich & Joseph Sakshaug, 2024. "Multivariate assessment of interviewer-related errors in a cross-national economic survey (Lukas Olbrich, Elisabeth Beckmann, Joseph W. Sakshaug)," Working Papers 253, Oesterreichische Nationalbank (Austrian Central Bank).
    8. F J Heather & D Z Childs & A M Darnaude & J L Blanchard, 2018. "Using an integral projection model to assess the effect of temperature on the growth of gilthead seabream Sparus aurata," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-19, May.
    9. Valentina Krenz & Arjen Alink & Tobias Sommer & Benno Roozendaal & Lars Schwabe, 2023. "Time-dependent memory transformation in hippocampus and neocortex is semantic in nature," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    10. Morán-Ordóñez, Alejandra & Ameztegui, Aitor & De Cáceres, Miquel & de-Miguel, Sergio & Lefèvre, François & Brotons, Lluís & Coll, Lluís, 2020. "Future trade-offs and synergies among ecosystem services in Mediterranean forests under global change scenarios," Ecosystem Services, Elsevier, vol. 45(C).
    11. Jack McDonnell & Thomas McKenna & Kathryn A. Yurkonis & Deirdre Hennessy & Rafael Andrade Moral & Caroline Brophy, 2023. "A Mixed Model for Assessing the Effect of Numerous Plant Species Interactions on Grassland Biodiversity and Ecosystem Function Relationships," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(1), pages 1-19, March.
    12. Ana Pinto & Tong Yin & Marion Reichenbach & Raghavendra Bhatta & Pradeep Kumar Malik & Eva Schlecht & Sven König, 2020. "Enteric Methane Emissions of Dairy Cattle Considering Breed Composition, Pasture Management, Housing Conditions and Feeding Characteristics along a Rural-Urban Gradient in a Rising Megacity," Agriculture, MDPI, vol. 10(12), pages 1-18, December.
    13. Damian M. Herz & Manuel Bange & Gabriel Gonzalez-Escamilla & Miriam Auer & Keyoumars Ashkan & Petra Fischer & Huiling Tan & Rafal Bogacz & Muthuraman Muthuraman & Sergiu Groppa & Peter Brown, 2022. "Dynamic control of decision and movement speed in the human basal ganglia," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    14. Kathrin Stenchly & Marc Victor Hansen & Katharina Stein & Andreas Buerkert & Wilhelm Loewenstein, 2018. "Income Vulnerability of West African Farming Households to Losses in Pollination Services: A Case Study from Ouagadougou, Burkina Faso," Sustainability, MDPI, vol. 10(11), pages 1-12, November.
    15. Dongyan Liu & Chongran Zhou & John K. Keesing & Oscar Serrano & Axel Werner & Yin Fang & Yingjun Chen & Pere Masque & Janine Kinloch & Aleksey Sadekov & Yan Du, 2022. "Wildfires enhance phytoplankton production in tropical oceans," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    16. Zhaogeng Yang & Yanhui Li & Peijin Hu & Jun Ma & Yi Song, 2020. "Prevalence of Anemia and its Associated Factors among Chinese 9-, 12-, and 14-Year-Old Children: Results from 2014 Chinese National Survey on Students Constitution and Health," IJERPH, MDPI, vol. 17(5), pages 1-10, February.
    17. Marco Lopez-Cruz & Fernando M. Aguate & Jacob D. Washburn & Natalia Leon & Shawn M. Kaeppler & Dayane Cristina Lima & Ruijuan Tan & Addie Thompson & Laurence Willard Bretonne & Gustavo los Campos, 2023. "Leveraging data from the Genomes-to-Fields Initiative to investigate genotype-by-environment interactions in maize in North America," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    18. Baumann, Elias & Kern, Jana & Lessmann, Stefan, 2019. "Usage Continuance in Software-as-a-Service," IRTG 1792 Discussion Papers 2019-005, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    19. Alexandra M. Cheney & Stephanann M. Costello & Nicholas V. Pinkham & Annie Waldum & Susan C. Broadaway & Maria Cotrina-Vidal & Marc Mergy & Brian Tripet & Douglas J. Kominsky & Heather M. Grifka-Walk , 2023. "Gut microbiome dysbiosis drives metabolic dysfunction in Familial dysautonomia," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    20. repec:cup:judgdm:v:16:y:2021:i:1:p:201-237 is not listed on IDEAS
    21. C. Gabriel Hidalgo Pizango & Eurídice N. Honorio Coronado & Jhon del Águila-Pasquel & Gerardo Flores Llampazo & Johan de Jong & César J. Córdova Oroche & José M. Reyna Huaymacari & Steve J. Carver & D, 2022. "Sustainable palm fruit harvesting as a pathway to conserve Amazon peatland forests," Nature Sustainability, Nature, vol. 5(6), pages 479-487, June.

    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:19:y:2022:i:9:p:5417-:d:805259. 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.