Predicting motor competence in school-aged children using biological, contextual and behavioural data.

The purpose of this study was to identify clusters of Motor Competence (MC) in school-aged children and to examine their biological, contextual, and behavioural predictors. A total of 880 children aged 6-10 years (53.9% boys) were included. MC was assessed using the Motor Competence Assessment (MCA). Two-Step Cluster Analysis based on MCA total percentiles identified three groups: Higher (range = 55-91, n = 375), Intermediate (range = 35-54, n = 319), and Lower (range = 3-34, n = 86). Predictors of cluster membership were examined through multinomial logistic regression in a subsample of 283 children (48.1% girls) with complete data. The model significantly predicted cluster membership [χ2(26) = 129.39; p = .001; Nagelkerke R2 = 0.399]. Cardiorespiratory fitness, assessed by the 20-m shuttle run test, emerged as the strongest predictor (p < .001). Each additional repetition increased the odds of belonging to the Higher MC group versus Lower MC by 11% (OR = 1.11, 95% CI: 1.06-1.17; p < .001), and to the Intermediate MC group by 6% (OR = 1.06, 95% CI: 1.01-1.11, p = .013). Age was also significant (p = .001): older children had lower odds of belonging to the Higher MC group relative to the Lower MC group (OR = 0.57, 95% CI: 0.38-0.85; p = .006), while higher body mass index reduced the odds of belonging to the Higher MC cluster (OR 0.83, 95% CI: 0.70-0.98; p = .028). The results identify cardiorespiratory fitness and age as significant predictors of MC, emphasising the importance of promoting physical activity and movement opportunities during childhood to support motor development and long-term health.