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

Area of Science:

• Pediatric Development
• Motor Control Research
• Childhood Health Studies

Background:

• Gross motor coordination (GMC) is crucial for children's physical development and participation in activities.
• Understanding GMC development and its influencing factors in specific populations is essential for targeted interventions.
• Previous studies often used mean-based models, potentially obscuring variations in development across different levels of coordination.

Purpose of the Study:

• To investigate the developmental trajectory of gross motor coordination (GMC) in Azorean school-aged children.
• To identify predictors of GMC and analyze their influence across different levels of coordination.
• To compare the efficacy of mean-modeling versus quantile regression in understanding GMC development.

Main Methods:

• Longitudinal study of 181 Azorean children (90 girls) aged 6 to 9 years.
• GMC assessed using the Körperkoordinationstest für Kinder.
• Predictors included body mass index, standing long jump, 50-yard dash, and shuttle run.
• Analyses employed mean-modeling and quantile regression (Q20, Q50, Q80) using R software.

Main Results:

• GMC changes exhibited a curvilinear pattern in both mean and quantile models.
• Quantile regression provided a more comprehensive view of GMC changes across low, median, and high coordination levels in both sexes.
• Predictors demonstrated varying effect sizes across different GMC quantiles, unlike the constant effects observed in the mean-model.

Conclusions:

• Quantile regression offers a more nuanced understanding of GMC development compared to traditional mean-modeling.
• Predictor effects on GMC are not uniform and vary significantly across different levels of motor coordination.
• This study highlights the importance of considering diverse developmental pathways when assessing GMC in children.