Environment, physical activity (PA) and motor development are tightly interwoven during childhood. We examined the associations of environmental factors with motor competence (MC) in children. Children (N = 945, 50.1% boys, age = 3–7 years, mean = 5.4 years) from 37 childcare centres in the Southern (n = 17), Central (n = 13) and Northern Finland (n = 7) participated. The environmental factors comprised the geographical location (Southern, Central and Northern Finland) and residential density (metropolitan area, city, rural area and countryside) of the childcare centres’ based on postal codes and the national population density registry. MC was measured using the Test of Gross Motor Development (TGMD)-3, as well as by quantifying time spent outdoors and participation in organised sports via parental questionnaire. It was found that children from the countryside had better MC and spent most time outdoors, while children from the metropolitan area most frequently engaged in organised sports. Gender comparisons revealed that girls outperformed boys in locomotor skills, while boys were better in object control skills, had higher TGMD-3 score and spent more time outdoors. Time spent outdoors and participation in organised sports were associated positively with MC, but not in children from the countryside. In conclusion, higher population density was associated with lower MC and less time spent outdoors. The findings suggest that versatile outdoor environments may support motor development through PA.

Physical activity and motor competence (MC) have been considered to be closely related and prevent childhood obesity. The aim of the study was two-fold: to examine MC measured with two different tools in relation to individual, family, and environmental correlates and to investigate gender differences in MC. The Test of Gross Motor Development-Third Edition (TGMD-3) was administered to three- to seven-year-old children (n = 945), while the Körperkoordinationstest für Kinder (KTK) was also used for five- to seven-year-old children (n = 444). The parent questionnaire (n = 936) included questions about individual (e.g., participation in organized sports), family (e.g., parents’ education level), and environmental (e.g., access to sports facilities) correlates. The children’s temperament was assessed using the Colorado Childhood Temperament Inventory (CCTI) questionnaire. Data were analyzed using one-way analysis of variance and linear mixed-effects regression models. The regression models explained 57% and 38% of the variance in TGMD-3 and KTK, respectively. Individual correlates, including older age, more frequent participation in sports, and specific temperament traits of activity and attention span-persistence, were the strongest predictors for better MC. Small gender differences were found in both assessment tools, albeit in a different manner. In conclusion, socioecological correlates of MC in young children are multidimensional, and individual correlates appear to be the most important predictors of MC. Importantly, the correlates can differ according to the MC assessment tools.

We examined the relationship between physical activity parenting (PAP) and child, family, and environmental factors in families. The participants were 840 families with young children (n = 993; 5.40 ± 1.14 years) and parents (n = 993; 35.8 ± 5.29 years). Parents' self‐reported PAP (co‐participation, (in)direct support, and encouragement), child‐specific (sex, age, temperament, outdoor time, organized physical activity or sports, sedentary time, media time, PA enjoyment, motor skills compared to peers, PA, and sport facility use), family‐specific (respondent's sex, age, education, exercise frequency, family income, family status, number of children in the family, child's birth order and partner's PAP, and exercise frequency), and environment‐specific (residential density, access to sport and outdoor facilities, type of house, and access to electronic devices) factors were collected. Children's motor skills and anthropometrics were measured. After adjusting for the family cluster effect, child, family, and environmental factors were entered into a linear mixed‐effects model, with PAP as the response variable. The final model consisted of statistically significant factors, and parental education, which was forced into the model. Nine child‐ and family‐related factors explained 15% of parenting variance between the children and 52% between the families. Partner's PAP (B = 0.68, P < 0.001) had the strongest association, whereas the child's temperament (B = 0.08, P < 0.001) and birth order (B = −0.10, P < 0.001) had smaller but novel associations with the respondent's PAP. Partner's PAP and a range of child‐ and family‐related factors should be considered when promoting parental support for child PA.

The study aims were to (1) identify perceived motor competence (PMC) and actual motor competence (AMC) profiles in children at two time points (early and middle childhood) 3 years apart, (2) explore transitions between the profiles from T1 to T2, and (3) investigate how PMC‐AMC profiles at T1 differ in their mean values for AMC and PMC variables at T2. PMC was assessed by the pictorial scale of Perceived Movement Skill Competence for young children (PMSC). At T1, AMC was measured with Test of Gross Motor Development–third version (TGMD‐3), and at T2, a shortened TGMD‐3 was used. To identify the PMC‐AMC profiles using latent profile analysis, the Mplus statistical package (version 8.7) was used. For aim 3, the Bolck‐Croon‐Hagenaars (BCH) method was used. There were 480 children (mean age 6.26 years, 51.9% boys) at T1, 647 children (mean age 8.76 years, 48.8% boys) at T2 (some children were too young to have the PMC assessment at T1), and 292 at both time points. For aim 1, three profiles were identified at each time point for each gender. Boys had two realistic profiles with medium and low levels of PMC‐AMC, and an overestimation profile. Girls had a medium realistic profile, an overestimation, and an underestimation profile. The PMC‐AMC profile in early childhood predicted the PMC‐AMC profile (aim 2) and AMC and PMC variables (aim 3) in middle childhood, especially if a child had low PMC in early childhood. Children with low PMC in early childhood are at risk of low PMC and less AMC development in middle childhood.

This study longitudinally examined, in a cluster-randomised data sample (n = 627, 3-11 years, 51.0% girls), how participation in organised and non-organised physical activity (PA) in early childhood (T1) predicted motor competence (MC) in middle childhood (T2). Organised sports participation and non-organised PA (outdoor time) were investigated via guardian questionnaire (T1, T2). At T2, children's MC was assessed using two locomotor (LMS) and two object control (OCS) skills from the Test of Gross Motor Development - 3rd edition measurement, for a total of four fundamental movement skills (FMS). The Körperkoordinationstest Für Kinder jumping sideways (JS) test was used. A linear regression model demonstrated that children's multisport participation at T1 predicted higher performance in LMS, OCS, FMS, and JS (p < 0.001 to p = 0.003; R² = 16.4% to 23.5%) at T2. Outdoor time on weekdays at T1 predicted higher JS (p = 0.009, 8.4%), OCS (p = 0.006, 14.5%) and FMS (p = 0.003, 10.0%) scores for girls. Two-way analysis of variance examined the interaction effects of sports participation and outdoor time on MC, but interactions were not found. These results underline the independent role of organised and non-organised sports participation in motor development from early to middle childhood.