Associations between Biological Maturation, Chronological Age, Body Mass Index, Sex, and Motor Competence in Prepubertal Children: A Network Analysis.

BACKGROUND: The development of motor competence (MC) during childhood is crucial for future physical activity and health outcomes, and it is affected by both biological and psychosocial factors. Most MC research has focused on children's age, with fewer studies examining separate associations between MC and biological maturation. METHODS: This cross-sectional study used network analysis to assess the nonlinear associations between biological maturation (the child's percentage of predicted mature stature to indicate somatic maturation), chronological age, sex, BMI, and MC (Test of Gross Motor Development, third edition) in 218 children (100 boys, 118 girls) aged 7-9 years. RESULTS: Biological maturation was not significantly associated with MC in boys and weakly associated with MC in girls for the dribble, under-hand throw, and gallop. Age was positively associated with MC in girls and boys. Centrality measures indicated that the gallop and slide in girls and the dribble, catch, and run in boys were the most important network variables. Positive associations were observed between maturation and BMI for girls (r = 0.579) and, to a lesser degree, for boys (r = 0.267). CONCLUSIONS: The findings suggest that age, rather than biological maturation, is positively associated with MC in 7- to 9-year-olds. Centrality measures showed that some skills may influence other skills.

Sex differences in 3- to 5-year-old children's motor competence: A pooled cross-sectional analysis of 6241 children.

There is some, albeit inconsistent, evidence supporting sex differences in preschoolers' motor competence (MC), with these observations not uniform when analyzed by age, and cultural groups. Thus, this study examined sex differences across ages in 3- to 5-year-old children's MC. A cross-country pooled sample of 6241 children aged 3-5 years (49.6% girls) was assessed for MC using the Test of Gross Motor Development-2nd/3rd edition, and children were categorized into groups of age in months. Multiple linear regression models and predictive margins were calculated to explore how sex and age in months affect scores of MC (i.e., locomotor and ball skills), with adjustments for country and BMI. The Chow's Test was used to test for the presence of a structural break in the data. Significant differences in favor of girls were seen at 57-59 and 66-68 months of age for locomotor skills; boys performed better in ball skills in all age periods, except for 42-44 and 45-47 months of age. The higher marginal effects were observed for the period between 45-47 and 48-50 months for locomotor skills (F = 30.21; and F = 25.90 for girls and boys, respectively), and ball skills (F = 19.01; and F = 42.11 for girls and boys, respectively). A significantly positive break point was seen at 45-47 months, highlighting the age interval where children's MC drastically improved. The identification of this breakpoint provides an evidence-based metric for when we might expect MC to rapidly increase, and an indicator of early delay when change does not occur at that age.

Investigating the Construct Validity and Reliability of the Test of Motor Competence Across Iranians' Lifespan.

Motor competence (MC) has been extensively examined in children and adolescents, but has not been studied among adults nor across the lifespan. The Test of Motor Competence (TMC) assesses MC in people aged 5-85 years. Among Iranians, aged 5-85 years, we aimed to determine the construct validity and reliability of the TMC and to examine associations between TMC test items and the participants' age, sex, and body mass index (BMI). We conducted confirmatory factor analysis (CFA) to evaluate the TMC's factorial structure by age group and for the whole sample. We explored associations between the TMC test items and participant age, sex, and BMI using a network analysis machine learning technique (Rstudio and qgraph). CFA supported the construct validity of a unidimensional model for motor competence for the whole sample (RMSEA = 0.003; CFI = 0.998; TLI = 0.993) and for three age groups (RMSEA <0.08; CFI and TLI >0.95). Network analyses showed fine motor skills to be the most critical centrality skills, reinforcing the importance of fine motor skills for performing and participating in many daily activities across the lifespan. We found the TMC to be a valid and reliable test to measure MC across Iranians' lifespan. We also demonstrated the advantages of using a machine learning approach via network analysis to evaluate associations between skills in a complex system.