The relationships between children’s motor competence, physical activity, perceived motor competence, physical fitness and weight status in relation to age

Anne R den Uil; Mirka Janssen; Vincent Busch; Ilse T Kat; Ron H J Scholte

doi:10.1371/journal.pone.0278438

. 2023 Apr 14;18(4):e0278438. doi: 10.1371/journal.pone.0278438

The relationships between children’s motor competence, physical activity, perceived motor competence, physical fitness and weight status in relation to age

Anne R den Uil ^1,^2,^*, Mirka Janssen ¹, Vincent Busch ³, Ilse T Kat ¹, Ron H J Scholte ²

Editor: Ender Senel⁴

PMCID: PMC10104338 PMID: 37058506

Abstract

The goal of this cross-sectional study was to further explore the relationships between motor competence, physical activity, perceived motor competence, physical fitness and weight status in different age categories of Dutch primary school children. Participants were 2068 children aged 4 to 13 years old, divided over 9 age groups. During physical education classes, they completed the 4-Skills Test, a physical activity questionnaire, versions of the Self-Perception Profile for Children, Eurofit test and anthropometry measurements. Results show that all five factors included in the analyses are related to each other and that a tipping point exists at which relations emerge or strengthen. Physical fitness is related to both motor competence and physical activity and these relationships strengthen with age. A relationship between body mass index and the other four factors emerges in middle childhood. Interestingly, at a young age, motor competence and perceived motor competence are weakly related, but neither one of these have a relation with physical activity. In middle childhood, both motor competence and perceived motor competence are related to physical activity. Our findings show that children in late childhood who have higher perceived motor competence are also more physically active, have higher physical fitness, higher motor competence and lower body mass index. Our results indicate that targeting motor competence at a young age might be a feasible way to ensure continued participation in physical activities throughout childhood and adolescence.

Introduction

Physical activity (PA) levels have been decreasing worldwide [1]. Of the Dutch population aged 4 and up, 51% does not meet the recommendations for daily physical activity [2]. Physical activity reduces the risk of cardiovascular disease, cancer and type-2 diabetes, improves musculoskeletal health and can reduce symptoms of depression [3]. Also, physical activity is an important factor influencing weight status, including obesity [4]. Obesity is one of the biggest health challenges around the world [5]. It increases the risk of type-2 diabetes, cardiovascular diseases and several forms of cancer. In addition, it imposes an economic burden on society [6]. In the Netherlands, 43.9% of the population is overweight, including 13.0% of the population that is obese. Of the Dutch 4- to 11-year old children, 11.9% is already overweight [7]. In order to increase levels of physical activity and reduce obesity among children, increased attention is paid to (school-based) interventions. However, the effectiveness of these interventions has been limited. Therefore, using a different approach for promoting physical activity might be useful.

A stronger focus on motor competence in primary school could be such approach. Fundamental motor skills (FMS) are the building blocks of more advanced, complex movements required to participate in sports, games or other context specific physical activity and include object control skills (i.e. throwing and catching), locomotor skills (i.e. hopping, skipping) and balance/stability skills (i.e. one-foot balance, turning) [8]. A recent review [9] of longitudinal studies concludes that there is strong evidence that overall motor competence (but not necessarily specific skills domains) influences physical activity levels. Since an increasing number of children develop motor delays somewhere during primary school [10], improving competence in motor skills of young children might be a feasible focus for improving physical activity levels and weight status.

Although the role of perceived motor competence in the interaction between motor competence and physical activity is often overlooked, a child’s perception of its motor competence is possibly even more important for physical activity levels than their actual motor competence [11, 12]. For example, while no direct association was found between motor competence and physical activity in some studies, indirect associations via perceived motor competence and physical self-concept were found [13, 14]. Stodden et al. [15] include both motor competence and perceived motor competence in their developmental model. They state that these are important factors influencing physical activity levels and that either a positive or a negative spiral can develop. In short: if motor competence develops slower than that of peers, children will be aware of that. Their perceived motor competence lowers, making them more likely to drop out of physical activities, influencing weight status, hereby completing a negative spiral. On the other hand, when children develop an adequate competence in motor skills, a positive spiral will develop.

A key aspect of the developmental model by Stodden et al. [15] is that it suggests that these relationships change according to the developmental stages of a child. At a young age, physical activity stimulates motor skill development. At this time, children cannot distinguish between actual skills and effort, leading to inflated levels of perceived competence [16]. As a result, children continue to participate despite their actual competences, leading to more opportunities to improve their motor competence. With the development of self-awareness, perceived competence starts to reflect actual motor competence more accurately [17] and this starts to influence physical activity levels. The ongoing development of physical activity and motor skills is thus influenced by perceived motor competence. As a consequence, the spiral of disengagement in physical activity begins in children with low motor competence [15]. Therefore, the timing of an intervention might be a key factor in influencing daily physical activity levels. Motor skills should be developed before perceived motor competence starts to reflect actual motor competence, then hindering physical activity participation. Motor skills should thus be improved at a very young age, especially since there might be a sensitive period for acquiring competence in motor skills [18–20].

An age-dependency of the relationship between perceived motor competence and physical activity has been supported in literature [21]. Although evidence for the mediating role of perceived motor competence in the relation between motor competence and physical activity is insufficient, based on available studies, age also seems to influence this mediating relationship [9]. Still, the question remains when this perceived motor competence starts to impact children’s physical activity behavior [22].

Several factors are thus involved in a child’s physical development. In addition to the aforementioned factors, a reciprocal role of health-related physical fitness is also included in the model [15]: at a young age physical activity and motor competence stimulate physical fitness, but as children grow older physical fitness also influences motor competence and physical activity in return [15]. So, weight status, physical activity, motor competence, perceived motor competence and physical fitness might all be interrelated.

So far, research has mainly focused on exploring the separate proposed relationships. Some cross-sectional studies have studied multiple relationships, but this was only done in specific age groups, mainly in older children [12, 23–27]. So although the developmental nature of these relationships is an important aspect of this model, research is mainly focused on separate age categories and the strengths of associations are often not reported [9, 28]. Research including all factors and various age-categories, thus the total model, is missing. Further exploration of these relationships is thus essential. Therefore, in the present cross-sectional study, we aim to further explore the relationships between weight status, physical activity, motor competence, perceived motor competence and physical fitness in Dutch primary school children. Specifically, these relationships are studied in children ranging from 4 to 13 years old, providing more insight into these relationships through developmental time.

Materials and methods

Design and setting

This study used a cross-sectional design. Six primary schools participated, varying in socioeconomic status and spread over different neighborhoods in Amsterdam (The Netherlands). An a priori sample size calculation was done using Gpower 3.1 (Windows, Düsseldorf, Germany) [29]. With a power estimate of 0.80, alpha set at 0.05 and an effect size of 0.20, this led to a required sample size of 193. Taking into account expected exclusions, we aimed at including approximately 250 children per group and therefore 6 schools. Based on postal codes, three schools were located in an area with low socioeconomic status, two in medium and one was located in an area with high socioeconomic status. Parents gave written informed consent for their children’s participation in the study. The study protocol received written approval by the Ethics Committee of Tilburg University (EC-2019.72).

Participants

All children of these schools were invited to participate in the study. Data was collected in a final sample of 2068 children (age 4–13, 50,6% boys). In these children, at least one test was performed. Descriptive statistics on the study sample can be found in Table 1. Reasons for exclusion were absence, injury and absence of informed consent.

Table 1. Descriptive statistics of the study sample.

Age Group	Sample size (N)	Sexe (n, % boys—girls)	BMI (mean (SD))	n	MVPA^a, min/wk (mean (SD))	n	Perceived motor competence (mean (SD))	n	Motor Age (mean (SD))	n
Age 4	135	74–61 (54,8–45,2%)	15,48 (1,31)	123	42,19 (51,60)	32	3,22 (0,58)	118	4,33 (0,80)	117
Age 5	266	144–122 (54,1–45,9%)	15,59 (1,48)	248	46,02 (53,62)	88	3,27 (0,53)	245	5,16 (0,85)	248
Age 6	286	142–144 (49,7–50,3%)	15,48 (1,58)	268	111,14 (92,65)	105	3,37 (0,46)	277	6,26 (1,08)	266
Age 7	268	143–125 (53,4–46,6%)	15,83 (2,07)	255	110,26 (80,47)	114	3,34 (0,41)	259	7,57 (1,26)	248
Age 8	243	119–124 (49,0–51,0%)	16,32 (2,11)	232	129,25 (105,58)	107	3,21 (0,52)	237	8,54 (1,18)	231
Age 9	251	124–127 (49,4–50,6%)	16,83 (3,05)	242	153,51 (105,84)	188	3,14 (0,58)	230	9,50 (1,13)	237
Age 10	219	110–109 (50,2–49,8%)	17,53 (2,92)	202	164,31 (155,75)	195	3,12 (0,57)	190	10,15 (1,08)	202
Age 11	222	116–106 (52,3–47,7%)	18,40 (3,85)	198	180,88 (147,00)	205	3,17 (0,56)	185	10,65 (0,97)	193
Age 12+	178	74–104 (41,6–58,4%)	19,12 (3,74)	162	138,86 (129,37)	167	3,17 (0,54)	156	10,84 (0,88)	160
Total sample	2068	1045–1022 (50,6–49,4%)	16,63 (2,83)	1930	137,09 (125,47)	1201	3,23 (0,53)	1897	8,09 (2,37)	1902

Open in a new tab

^a MVPA: moderate-to-vigorous physical activity.

Instruments

Motor skill competence

Motor skill competence was assessed using the 4-Skills Scan [30]. This test is easy to conduct in a school setting and has been found to be both reliable (ICC = 0.93 for test–retest reliability and ICC = .97 for inter-rater reliability) [31] and valid (r = 0,58) [32]. The 4-Skills Scan consists of four components: 1. Jumping force (locomotion), 2. Bouncing ball (object control), 3. Standing still (stability) and 4. Jumping coordination (coordination). The subscales contain 11 elements of increasing difficulty. Each element represents a ‘motor age’: the age based on the depicted motor skill competence. For example, 6-year old children are expected to be able to skip. If a child successfully skips (and fails at subsequent elements), they score a motor age of 6. The mean of the four components forms a total score. Comparing motor age to calendar age leads to a score for ‘motor lead’, the final score used in our analyses. A positive motor lead value indicates that a child performs better than to be expected based on calendar age, a negative motor lead value indicates that a child performs lower than to be expected.

Perceived motor competence

For different age groups, different instruments were used to measure perceived motor competence. For children between 4 and 7, the different versions of the Pictorial Scale of Perceived Competence (PSPC) were used [33]. This scale contains 24 questions in 4 subscales (school competence, physical competence, social acceptance and maternal acceptance). For this study, the six questions of the subscale physical/motor competence were used (α = 0.55) (see Appendix). For children aged 8 and older, a Dutch translation of the Self-Perception Profile for Children (SPPC) [34] was used (CBSK) [35]. This questionnaire contains 36 questions in 6 subscales. The six questions of the subscale Athletic Competence were used for this study (α = 0.70, test-retest r = 0.83) and converted into a total score by adding up the scores and dividing them by 6. Both questionnaires are constructed in a similar way, making children choose between two types of children and asking: “who do you resemble the most?” For example: “Some children are very good in sports and physical education, but some children aren’t very good in sports in physical education. Who do you resemble the most?”

Physical activity

Physical activity was measured using an adapted questionnaire based on the ENERGY-questionnaire [36]. Questions about home situation and the questions regarding energy intake, sedentary behavior and attitude towards physical activities were excluded, since they exceeded the scope of this study. The amount of minutes of participation in organized sport per week was calculated as a measure of moderate-to-vigorous physical activity (MVPA). Since children under 10 years cannot accurately estimate their physical activity levels [37], the questionnaire was sent to the parents (online) for children younger than 10 years old. This was decided in agreement with experts in Amsterdam, who have a lot of experience in administering questionnaires to children.

Health-related physical fitness

The Eurofit test [38] was used as a measure of health-related physical fitness in children from 6 year old. This test included 8 test items: 1. Standing long jump 2. Bent arm hang 3. Sit and reach 4. 10x5m shuttle run 5. Plate tapping 6. Sit-ups 7. Handgrip strength 8. Shuttle run test. A composite score for overall fitness was calculated by converting raw scores to age-specific z-scores. Calculating a composite score for physical fitness is not common practice, but has been done before [39, 40]. In 6- and 7-year old children, plate tapping and the shuttle run test were not performed.

Weight status

Height was measured using a stadiometer, weight was measured using an analog scale. Height was rounded to the nearest half cm, weight was measured in kg with one decimal. Children were measured without wearing shoes. BMI was calculated by dividing weight (kg) by the square of the height (m) and was converted to z-scores using WHO’s bmi-for-age tables [41].

Procedures

Data collection took place in the physical education (PE) classes during school hours. Class started with a general introduction by the PE-teacher. Additional explanation and demonstration was given by the test conductors at the specific test item. To minimize the emphasis on measuring and to prevent children from watching each other, children were instructed to play PE-activities. The children were individually called to perform the specific test with the test conductor. All test conductors received training to ensure protocol compliance. Also, a supervisor was always present to observe and assure measurement quality and to organize the test-setting.

To perform all measurements, three PE-classes (approximately 45 minutes per class) were necessary. The 4-Skills Scan, in combination with body height and weight measurements, was administered in one PE-class. The tests was conducted by dividing the children in four groups. Approximately every eight minutes the groups rotated to the next activity and test. For the Eurofit test, the children were divided over two groups: one group participated in an activity with the PE-teacher, one group performed eight different tests; items 1 to 7 of the Eurofit test and the physical activity questionnaire that was completed on iPads (children ≥ 10 years). Halfway during class, the two groups switched. The shuttle run test, combined with the perceived motor competence measurements, also took one PE-class. While one group executed the shuttle run test, the other group filled in the questionnaire. For the perceived motor competence questionnaires, children were taken out of the PE-class to a more quiet place. The questionnaires started with a short introduction and an example. When children understood, either the test conductor read out the real questions to the children and filled in their answer on an iPad (PSPC) or the children could read the questions and fill in the answers by themselves (CBSK). While the PSPC was administered individually, the CBSK was administered in small groups of approximately four children.

Data analyses

Data was pre-processed using R (v 4.0.3) [42]. Total scores for motor lead, perceived motor competence and physical fitness were calculated when 75% of the individual scores were available. This was done by dividing the sum of the available scores by the number of available items. Then, for every age group, a correlation analysis was carried out in MPlus 7.4 [43] using a Full Information Maximum Likelihood (FIML) estimator to account for missing values. In all models, variances of, and covariances between variables were freely estimated, thus resulting in saturated models with df = 0 and a perfect model fit. The complex procedure in Mplus was used to account for non-independence of observations due to cluster sampling (children nested within schools). Alpha level for significance was set at .05. To check for changes in the correlations over time, a Fisher’s r to z transformation was done on the correlation coefficients that were significant. Then, the test-statistic z was calculated by $z = \frac{z_{r 1} - z_{r 2}}{{s e (z}_{r 1} - z_{r 2})}$ where ${se}_{(zr 1 - zr 2)} = \sqrt (\frac{1}{n_{1} - 3} + \frac{1}{n_{2} - 3})$ . Z-values were compared for every relationship in all age groups.

Results

The results are shown in Table 2 and Fig 1. Correlation coefficients varied from low to strong [44] and were negative for the relationships with BMI.

Table 2. Summary of the correlation analysis per age group.

Relation	Age 4	Age 5	Age 6	Age 7	Age 8	Age 9	Age 10	Age 11	Age 12+
Motor competence–physical activity	0,084	0,008	0,08	0,178^*	0,274^*	0,144	0,247^*	0,261^*	0,273^*
Motor competence–perceived motor competence	0,22	0,171^*	0,134^*	0,271^*	0,047	0,123	0,303^*	0,318^*	0,255^*
Perceived motor competence–physical activity	-0,099	0,153	0,044	0,007	0,219^*	0,132	0,215	0,241^*	0,318^*
Motor competence–physical fitness	N/A	N/A	0,45^*	0,382^*	0,53^*	0,634^*	0,618^*	0,604^*	0,473^*
Physical fitness–physical activity	N/A	N/A	0,221^*	0,395^*	0,438^*	0,186	0,349^*	0,297^*	0,296^*
BMI–motor competence	-0,078	-0,008	-0,061	-0,078	-0,155	-0,318^*	-0,322^*	-0,397^*	-0,19
BMI–physical activity	0,047	0,141	-0,068	0,116	-0,237^*	-0,165	-0,147^*	-0,305^*	-0,172^*
BMI–perceived motor competence	0,03	0,054	0,007	0,022	-0,069	-0,077	-0,092	-0,244^*	-0,142^*
BMI–physical fitness	N/A	N/A	-0,164	-0,014	-0,294^*	-0,325^*	-0,317^*	-0,382^*	-0,12

Open in a new tab

*correlation coefficients significant at p < 0,05.

Fig 1 — Nonsignificant correlations do not have a marker.

The Z-statistics revealed that the correlation coefficients do not gradually change over time. Instead, there seems to be a tipping point: either an association changes from nonsignificant to significant or the strength of that association grows stronger. A summary of the results is shown in Table 3 and Fig 2. Detailed tables are presented in the Supporting Information.

Table 3. Overview of the tipping points in the associations.

Relation	Type of tipping point	Age of tipping point
Motor competence–physical activity	No association → association	6 to 7 yo.
Motor competence–perceived motor competence	Increased strength of association	6 to 7 yo.
Perceived motor competence–physical activity	No association → association	7 to 8 yo.
Motor competence–physical fitness	Increased strength of association	7 to 8 yo.
Physical fitness–physical activity	Increased strength of association	6 to 7 yo.
BMI–physical activity	No association → association	7 to 8 yo.
BMI–physical fitness	No association → association	7 to 8 yo.
BMI–motor competence	No association → association	8 to 9 yo.
BMI–perceived motor competence	No association → association	10 to 11 yo.

Open in a new tab

Fig 2 — The * indicates that the relationship increases in strength with age: at 7 for motor competence–perceived motor competence, at 8 for motor competence–fitness and at 7 for fitness–motor competence.

The data show an association between motor competence and physical activity in children from seven years old. The association between motor competence and perceived motor competence is first detected at five years old and this association seems to strengthen at the age of seven years old, although at ages eight and nine no association is found. Similarly, an association between physical activity and perceived motor competence is detected at eight years old, although at 9 and 10 years old no association is found. Physical fitness shows an association with motor competence and physical activity right from the moment we started measuring physical fitness. This association with motor competence increases in strength from the age of eight, while the association with physical activity grows stronger at the age of seven. Lastly, the data show that associations between BMI and the other four factors emerge one by one: at eight years old an association between BMI and physical activity and between BMI and physical fitness develops, at 9 years old an association between BMI and motor competence emerges and only at 11 years old an association between BMI and perceived motor competence arises. Interestingly, we also found a stable association between perceived motor competence and physical fitness right from the age where we started measuring physical fitness (6 yo.), although this relationship is not included in the model by Stodden et al. [15].

Discussion

The goal of this study was to explore the relationships between weight status, physical activity, motor competence, perceived motor competence and physical fitness through time. To our knowledge, this is the first study including all five aspects included in the model by Stodden et al. [15] as well as a large sample of children of all ages from four to thirteen years old. Our findings show that all aspects are related to each other and that a tipping point exists at which relations between aspects emerge or at which they become stronger, confirming most of what is described in the developmental model by Stodden et al. [15].

At the center of the model by Stodden et al. [15] is the relationship between motor competence and physical activity, that changes direction from early childhood to middle childhood. They propose that in early childhood, a weak relationship between motor competence and physical activity exists: physical activity stimulates the development of motor competence. We cannot confirm this proposed pathway, since we found no correlation between these two variables in 4- to 6-year old children. While Schmutz et al. [45] already found a weak relationship between motor competence and physical activity in early childhood, Nicolai Ré et al. [46] did not. In their review study, Barnett et al. [9] found no evidence of physical activity stimulating motor competence. Our results align with this conclusion, strengthening the notion that physical activity does not predict motor competence. As we have only measured time spent on physical activities, it cannot be ruled out that the quality of physical activity (i.e. amount of variation, free-play versus guided activities) does have a certain influence on the development of motor competence. Our data show that a relationship develops in middle childhood, which is in line with King-Dowling et al. [47] who also found that this relationship emerged over the study period. Since in multiple studies, including those in young kids (3 to 6 yo) [48–51], differences in physical activity were only found between high motor competence and moderate/low motor competence, it could be that a proficiency barrier exists [48] and that motor competence and physical activity will only be related in samples of children with higher average motor competence. In that case, children will only become more physically active when they have reached a certain level of proficiency in motor skills.

Perceived motor competence is described to be a mediator in the relationship between motor competence and physical activity: in early childhood perceived motor competence is on average high and stimulates both motor competence and physical activity, in middle childhood children develop the cognitive skills to accurately evaluate their own skills, at which point actual motor competence starts influencing perceived motor competence, influencing physical activity [15]. Our data show that children’s perceived motor competence is already related to actual motor competence at a young age, which is in line with other studies [52–54]. Although a recent review [55] was not able to demonstrate an age effect in the relationship between motor competence and perceived motor competence, our findings support the results of True et al. [56], showing the strengthening of the association between motor competence and perceived motor competence through developmental time. It therefore seems like motor competence of older children influence their perceived motor competence (and/or the other way around) more than in younger children demonstrate.

On the other hand, the proposed pathway from perceived motor competence to physical activity in early childhood cannot be confirmed in this study, since children up to 8 years old with higher perceived motor competence were not more physically active. This is in line with other cross-sectional studies in young children [52, 57–59]. Interestingly, both perceived and actual motor competence seem to not be related to physical activity behavior in young children. Our results show that perceived motor competence and physical activity are first related at 8 years old and that is also supported by other studies in samples of older children [26, 60, 61]. Hence, from this age on, perceived motor competence could have a mediating role as described in the developmental model [15]. This mediation could not yet be supported in a recent review [9]. While in this review study not enough studies were available to address changes with age, based on available studies age seems to be a factor, since all mediations that were found were in samples in which the children were 9 or older [9]. Therefore, it seems that whether young children feel like they are competent in performing motor skills or not, has no effect on the amount of time they spend on physical activities. When children grow older, children with higher perceived motor competence are also more physically active. This relationship is then equally strong as the direct relationship between actual motor competence and physical activity, which possibly underlines the importance of perceived motor competence and thereby the development of sufficient motor competence before perceived motor competence starts playing a role.

Although we only measured fitness from the age of six years old, our results confirm the notion that from a young age, physically fitter children are more competent in performing motor skills and are more physically active. These relationships become stronger when children grow older. While Barnett et al. [9] report insufficient evidence for a relationship between physical fitness and total motor competence and object control motor competence, they found strong evidence for reciprocal causal pathways between physical fitness and motor competence in locomotion/coordination/stability skills. Since our measure of motor competence only includes one object control skill and the other skills are in the domains of locomotion, coordination and stability, this could explain why our motor competence composite score is significantly related to physical fitness.

Finally, weight status is included as a product of all four factors [15]. We therefore included separate correlations between BMI and the other four factors in our analysis. We found no evidence that BMI was related to any of the other factors in the youngest children. Thereafter relationships appear gradually. The fact that BMI and motor competence were only related from the age of nine years old, does not concur with other studies looking at several age groups [28, 62, 63]. Although our results do align with Khodaverdi et al. [27] and Logan et al. [64], who also did not find that BMI and motor competence were related in young children, Logan et al. [64] did find a difference in motor competence between children with high BMI versus children with normal/low BMI. It could therefore still be possible that having high BMI negatively impacts motor skill development, but that within the range of low to normal BMI, differences in BMI are not related to differences in motor competence. Similarly, Khodaverdi et al. [27] also conclude that the low average BMI of their sample may have impacted their results.

Our findings also demonstrate that from the age of 11 children with higher BMI report lower perceived motor competence. Although an inverse relationship between BMI and perceived motor competence was suggested in a recent review [65] not enough studies were available to confirm this, especially not in different age categories. This might therefore be a pathway that needs more research. Our findings show that children in late childhood who have higher perceived motor competence are also more physically active, have higher physical fitness, higher motor competence and lower BMI. Although this does not prove causality, it does align with the proposed spiral of (dis)engagement as described by Stodden et al. [15]. In middle childhood this relationship with BMI is not fully developed yet. Some longitudinal studies also support the proposed spiral. While motor competence influences fitness and fatness (directly and via fitness) from a young age [66, 67] and perceived motor competence later in childhood [68], motor competence [69, 70], perceived motor competence [68], fitness [23, 69] and weight [69] all appear to influence physical activity in late childhood. Our findings therefore reinforce the idea that focusing on motor competence in early childhood might be a feasible way to ensure continued participation in physical activities throughout childhood and adolescence and thereby reducing obesity problems.

Some relationships seem to weaken around the age of 12. This is the case for the relationship between BMI and motor competence, but also for the relationships of physical fitness with BMI, motor competence, and physical activity, where some relationships even disappear. Possibly, maturation plays an important role in the dynamic relationships between all these factors and other factors start becoming more important in the maintenance of BMI, physical activity, motor competence and fitness levels. Another possible explanation is that a ceiling effect exists for the 4 Skills Test, which might explain the weakening of relations with motor competence. Because of this, children can only perform below and on their expected motor age, not above, resulting in increased density of scores at the high end of the scale.

Multiple cross-sectional relationships proposed in the developmental model [15] have been studied together before, but only in specific age groups, mainly in older children [12, 23–27]. Our results largely concur with data from these studies, confirming relationships as proposed in the Stodden et al. [15] model. Our data extend these studies in the fact that we included a large sample of children from age 4 to 13, which made it possible to dive deeper into this model, exploring the age-dependency of the proposed relationships. Two studies [23, 26] found that fitness is a more important mediator than perceived motor competence. Indeed, our study also shows stronger associations between fitness and motor competence /physical activity than between perceived motor competence with motor competence / physical activity. However, this might also be explained by an overlap in content [71] and neuromuscular constraints [72] of tests of motor competence and physical fitness. In addition, Stodden et al. [40] pointed out that perceived motor competence may also play a role in the relation between motor competence and fitness, demonstrating another indirect pathway enforcing the spiral of (dis)engagement in physical activity. Our cross-sectional data show that there is indeed also an association between perceived motor competence and physical fitness in all age categories.

Some methodological issues seem to have impacted our results. No relation was found between motor competence and perceived motor competence at age eight and nine years old. This might be due to the fact that we changed to a different instrument (while both developed by the same author) for measuring perceived motor competence at eight years old. For young children we used a pictorial scale showing specific motor skills that were sometimes comparable with the motor skills tested by the 4 Skills Test. From 8 years old, children received a textual questionnaire, describing more generic performance at physical activities. Perhaps these questions were still too abstract for 8 and 9 year-olds, which could explain why no association was found between motor competence and perceived motor competence. Similarly, a sudden drop is seen in the relations with physical activity at the age of nine. This could be due to the fact that while we established that a self-report physical activity questionnaire was only suitable from 10 years old, part of the 9 year-olds filled in the questionnaire themselves, instead of their parents. This was done in concurrence with the PE-teacher, who predicted no response from parents. This leads to the next limitation of this study, which is the lower response rate for the physical activity questionnaire that was sent to the parents. Although this was expected, it possibly led to bias in the data and led to a significantly lower sample size for the analyses that included physical activity in the younger children. Since it is also in the younger children that we found no relationships with physical activity, some caution is warranted there. In addition, assessing physical activity by use of a questionnaire often leads to an overestimation of physical activity [73]. Another limitation of this study is the cross-sectional nature of this study, preventing us from determining causal relationships. Strengths of this study are the use of the full information maximum likelihood procedure, the large sample of children between 4 and 13 years old and the inclusion of all five factors from the developmental model proposed by Stodden et al. [15]. This made it possible to look at the existence and strength of relationships in many age groups, using the same or similar instruments. However, the large scale of this study made it impossible to also look a separate aspects of the factors, which might be a necessary follow-up step. For example, it is argued that when studying the relationship between physical activity and motor competence, a distinction should be made between organized and non-organized physical activities [74]. For example, throwing and jumping skills were related to higher intensity, skill-specific physical activity after school, but not to the general level of physical activity [75]. In addition, motor competence and perceived motor competence did not predict general physical activity during the school day, but did predict playground physical activity [76]. Similarly, it has been proposed that locomotor skills may not contribute to the opportunities to participate in physical activities to the extent that ball skills do [77, 78], especially during school lunchtime and recess breaks [78]. In addition, ball skills seem to affect perceived motor competence more than locomotor skills do [16, 76]. In this study we included only time spent in organized sports activities as a measure of physical activity. Motor competence was included as a composite score of 4 skills and similarly, a composite score was calculated for health related fitness.

In conclusion, all five factors included in the developmental model by Stodden et al. [15] are related and tipping points exist after which the relations emerge or strengthen. It should be kept in mind that this is a complex system, in which many other factors might have interrelations with the factors described in this model. However, our results indicate that targeting motor competence and perceived motor competence at a young age might be a feasible way to ensure continued participation in physical activities throughout childhood and adolescence. Yet, how to effectively influence motor competence is still largely unknown: both our data and available literature suggest that only increasing physical activity will not be enough [9], while maintaining a healthy weight could be a promising starting point to kick off a positive spiral [9, 67]. Future research should thus aim to unravel how to improve motor competence. In addition, large scale longitudinal studies including all variables and all age groups are necessary to gain more insight in the directions of these relationships through developmental time, ideally while making the distinction between different aspects within each variable. Moreover, the possibility of nonlinearity of these relationships should be further investigated, since non-linear relationships between physical activity and motor skills [79] and between BMI and motor coordination [80] have been described. Lastly, addressing sex differences in these relationships might also be interesting as it has been proposed that the mediating role of perceived motor competence might be stronger for girls than for boys [26] and that reciprocal relations between motor competence, endurance and fatness are dependent on sex [67]. Since boys and girls do not go through their maturational stages simultaneously [81], exploring sex differences in the developmental nature of the studied interrelations would be a valuable direction for follow-up studies.

Supporting information

S1 Table. Z statistic values of the difference in correlation coefficients of BMI—motor competence between ages.

* 1,96 > z > -1,96 is significant. * n/a refers to a correlation coefficient being absent because measurements were net performed in that age group. The–means that one or two of the correlation coefficients were not significant. In both situations, no calculations on the significance of the difference could be performed.

(DOCX)

Click here for additional data file.^{(13.9KB, docx)}

S2 Table. Z statistic values of the difference in correlation coefficients of BMI—perceived motor competence between ages.

(DOCX)

Click here for additional data file.^{(13.6KB, docx)}

S3 Table. Z statistic values of the difference in correlation coefficients of BMI—physical activity between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S4 Table. Z statistic values of the difference in correlation coefficients of BMI—physical fitness between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S5 Table. Z statistic values of the difference in correlation coefficients of motor competence—perceived motor competence between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S6 Table. Z statistic values of the difference in correlation coefficients of motor competence—physical activity between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S7 Table. Z statistic values of the difference in correlation coefficients of motor competence—physical fitness between ages.

(DOCX)

Click here for additional data file.^{(13.8KB, docx)}

S8 Table. Z statistic values of the difference in correlation coefficients of perceived motor competence -physical activity between ages.

(DOCX)

Click here for additional data file.^{(13.8KB, docx)}

S9 Table. Z statistic values of the difference in correlation coefficients of physical activity—physical fitness between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S10 Table. Z statistic values of the difference in correlation coefficients of perceived motor competence—physical fitness between ages.

(DOCX)

Click here for additional data file.^{(13.8KB, docx)}

Acknowledgments

The authors would like to thank the schools, children and parents for their cooperation and participation in this study. The help of the test conductors in data collection is also kindly acknowledged. Special thanks goes to M.J.M.H. Delsing and R.J. den Uil for their contributions in respectively data-analyses and writing.

Data Availability

The data have been uploaded to Figshare with DOI https://doi.org/10.21943/auas.22332841.v1.

Funding Statement

This work was supported by a grant for AU from the Netherlands Organization for Scientific Research (NWO) (grant number 023.013.055). https://www.nwo.nl/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1·9 million participants. Lancet Glob Health. 2018. Oct;6(10):e1077–86. [DOI] [PubMed] [Google Scholar]
2.CBS RIVM. Gezondheidsenquête/Leefstijlmonitor. 2019. [Google Scholar]
3.World Health Organization, editor. Global health risks: mortality and burden of disease attributable to selected major risks. Geneva, Switzerland: World Health Organization; 2009. 62 p. [Google Scholar]
4.Loprinzi PD, Cardinal BJ, Loprinzi KL, Lee H. Benefits and Environmental Determinants of Physical Activity in Children and Adolescents. Obes Facts. 2012;5(4):597–610. doi: 10.1159/000342684 [DOI] [PubMed] [Google Scholar]
5.Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9·1 million participants. 2011;12. [DOI] [PubMed] [Google Scholar]
6.Wang YC, McPherson K, Marsh T, Gortmaker SL, Brown M. Health and economic burden of the projected obesity trends in the USA and the UK. The Lancet. 2011. Aug;378(9793):815–25. doi: 10.1016/S0140-6736(11)60814-3 [DOI] [PubMed] [Google Scholar]
7.CBS RIVM. Gezondheidsenquête/Leefstijlmonitor. 2018. [Google Scholar]
8.Gallahue DL, Ozmun JC, Goodway J. Understanding motor development: Infants, children, adolescents, adults. 7th ed. New York, NY: McGraw-Hill; 2012. [Google Scholar]
9.Barnett LM, Webster EK, Hulteen RM, De Meester A, Valentini NC, Lenoir M, et al. Through the Looking Glass: A Systematic Review of Longitudinal Evidence, Providing New Insight for Motor Competence and Health. Sports Med. 2022. Apr;52(4):875–920. doi: 10.1007/s40279-021-01516-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Willems WAJJ Erken IE, Johannes M, van Kernebeek WG, de Schipper A, Toussaint HM. Goed bewegen van basisschoolleerlingen is onze zorg: Samen aan de slag met de gymleraar. JGZ Tijdschr Voor Jeugdgezondheidsz. 2016. Aug;48(4):72–7. [Google Scholar]
11.De Meester A, Maes J, Stodden D, Cardon G, Goodway J, Lenoir M, et al. Identifying profiles of actual and perceived motor competence among adolescents: associations with motivation, physical activity, and sports participation. J Sports Sci. 2016. Nov;34(21):2027–37. doi: 10.1080/02640414.2016.1149608 [DOI] [PubMed] [Google Scholar]
12.Morrison KM, Cairney J, Eisenmann J, Pfeiffer K, Gould D. Associations of Body Mass Index, Motor Performance, and Perceived Athletic Competence with Physical Activity in Normal Weight and Overweight Children. J Obes. 2018;2018:1–10. doi: 10.1155/2018/3598321 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Chan CHS, Ha ASC, Ng JYY, Lubans DR. Associations between fundamental movement skill competence, physical activity and psycho-social determinants in Hong Kong Chinese children. J Sports Sci. 2019. Jan 17;37(2):229–36. doi: 10.1080/02640414.2018.1490055 [DOI] [PubMed] [Google Scholar]
14.Jekauc D, Wagner MO, Herrmann C, Hegazy K, Woll A. Does Physical Self-Concept Mediate the Relationship between Motor Abilities and Physical Activity in Adolescents and Young Adults? Zhou R, editor. PLOS ONE. 2017. Jan 3;12(1):e0168539. doi: 10.1371/journal.pone.0168539 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Stodden DF, Goodway JD, Langendorfer SJ, Roberton MA, Rudisill ME, Garcia C, et al. A Developmental Perspective on the Role of Motor Skill Competence in Physical Activity: An Emergent Relationship. Quest. 2008. May;60(2):290–306. [Google Scholar]
16.Goodway JD, Rudisill ME. Perceived Physical Competence and Actual Motor Skill Competence of African American Preschool Children. Adapt Phys Act Q. 1997. Oct;14(4):314–26. [Google Scholar]
17.Harter S. The construction of the self: a developmental perspective. Guilford Press; 1999. [Google Scholar]
18.Casey B, Tottenham N, Liston C, Durston S. Imaging the developing brain: what have we learned about cognitive development? Trends Cogn Sci. 2005. Mar;9(3):104–10. doi: 10.1016/j.tics.2005.01.011 [DOI] [PubMed] [Google Scholar]
19.Gogtay N, Giedd JN, Lusk L, Hayashi KM, Greenstein D, Vaituzis AC, et al. Dynamic mapping of human cortical development during childhood through early adulthood. Proc Natl Acad Sci. 2004. May 25;101(21):8174–9. doi: 10.1073/pnas.0402680101 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Thomas M, Knowland VC. Sensitive Periods in Brain Development–Implications for Education Policy. Eur Psychiatr Rev. 2009;2(1):17–20. [Google Scholar]
21.Babic M, Morgan P, Plotnikoff R, Lubans D, Lonsdale C, White R. Physical activity and physical self-concept in youth: Systematic review and meta-analysis. J Sci Med Sport. 2014. Dec;18:e154. doi: 10.1007/s40279-014-0229-z [DOI] [PubMed] [Google Scholar]
22.Crane JR, Naylor PJ, Cook R, Temple VA. Do Perceptions of Competence Mediate The Relationship Between Fundamental Motor Skill Proficiency and Physical Activity Levels of Children in Kindergarten? J Phys Act Health. 2015. Jul;12(7):954–61. doi: 10.1123/jpah.2013-0398 [DOI] [PubMed] [Google Scholar]
23.Britton U, Issartel J, Symonds J, Belton S. What Keeps Them Physically Active? Predicting Physical Activity, Motor Competence, Health-Related Fitness, and Perceived Competence in Irish Adolescents after the Transition from Primary to Second-Level School. Int J Environ Res Public Health. 2020. Apr 21;17(8):2874. doi: 10.3390/ijerph17082874 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Burns R, Fu Y. Testing the Motor Competence and Health-Related Variable Conceptual Model: A Path Analysis. J Funct Morphol Kinesiol. 2018. Nov 28;3(4):61. doi: 10.3390/jfmk3040061 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.dos Santos MAM, Nevill AM, Buranarugsa R, Pereira S, Gomes TNQF, Reyes A, et al. Modeling children’s development in gross motor coordination reveals key modifiable determinants. An allometric approach. Scand J Med Sci Sports. 2018. May;28(5):1594–603. doi: 10.1111/sms.13061 [DOI] [PubMed] [Google Scholar]
26.Jaakkola T, Huhtiniemi M, Salin K, Seppälä S, Lahti J, Hakonen H, et al. Motor competence, perceived physical competence, physical fitness, and physical activity within Finnish children. Scand J Med Sci Sports. 2019. Mar 19;sms.13412. doi: 10.1111/sms.13412 [DOI] [PubMed] [Google Scholar]
27.Khodaverdi Z, Bahram A, Stodden D, Kazemnejad A. The relationship between actual motor competence and physical activity in children: mediating roles of perceived motor competence and health-related physical fitness. J Sports Sci. 2016. Aug 17;34(16):1523–9. doi: 10.1080/02640414.2015.1122202 [DOI] [PubMed] [Google Scholar]
28.Robinson LE, Stodden DF, Barnett LM, Lopes VP, Logan SW, Rodrigues LP, et al. Motor Competence and its Effect on Positive Developmental Trajectories of Health. Sports Med. 2015. Sep;45(9):1273–84. doi: 10.1007/s40279-015-0351-6 [DOI] [PubMed] [Google Scholar]
29.Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behav Res Methods. 41:1149–60. doi: 10.3758/BRM.41.4.1149 [DOI] [PubMed] [Google Scholar]
30.van Gelder W, Stroes H. Leerlingvolgsysteem Bewegen en Spelen. Over observeren, registeren en extra zorg. 2nd ed. Amsterdam, The Netherlands: Elsevier; 2010. [Google Scholar]
31.van Kernebeek WG, de Schipper AW, Savelsbergh GJP, Toussaint HM. Inter-rater and test–retest (between-sessions) reliability of the 4-Skills Scan for dutch elementary school children. Meas Phys Educ Exerc Sci. 2018. Apr 3;22(2):129–37. [Google Scholar]
32.van Kernebeek WG, de Kroon MLA, Savelsbergh GJP, Toussaint HM. The validity of the 4-Skills Scan A double-validation study. Scand J Med Sci Sports. 2018. Nov;28(11):2349–57. doi: 10.1111/sms.13231 [DOI] [PubMed] [Google Scholar]
33.Harter S, Pike R. The Pictorial Scale of Perceived Competence and Social Acceptance for Young Children. Child Dev. 1984. Dec;55(6):1969. [PubMed] [Google Scholar]
34.Harter S. The Self-perception profile for children manual. In Denver: University of Denver; 1985. [Google Scholar]
35.Veerman JW, Straathof MAE, Treffers PhDA, van den Bergh BRH, ten Brink LT. Competentiebelevingsschaal voor Kinderen—handleiding. Lisse, Netherlands: Harcourt Assessment BV.; 2004. [Google Scholar]
36.Singh AS, Vik FN, Chinapaw MJ, Uijtdewilligen L, Verloigne M, Fernández-Alvira JM, et al. Test-retest reliability and construct validity of the ENERGY-child questionnaire on energy balance-related behaviours and their potential determinants: the ENERGY-project. Int J Behav Nutr Phys Act. 2011;8(1):1. doi: 10.1186/1479-5868-8-136 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Loprinzi PD, Cardinal BJ. Measuring Children’s Physical Activity and Sedentary Behaviors. J Exerc Sci Fit. 2011;9(1):15–23. [Google Scholar]
38.van Mechelen W, van Lier WH, Hlobil H, Crolla I, Kemper HCG. Eurofit, Handleiding met referentieschalen voor 12- tot en met 16-jarige jongens en meisjes in Nederland. Haarlem: Uitgeverij de Vrieseborch; 2011. [Google Scholar]
39.Borremans E, Rintala P, Kielinen M. EFFECTIVENESS OF AN EXERCISE TRAINING PROGRAM ON YOUTH WITH ASPERGER SYNDROME. Eur J Adapt Phys Act. 2009. Jul 31;2(2):14–25. [Google Scholar]
40.Stodden DF, Gao Z, Goodway JD, Langendorfer SJ. Dynamic Relationships Between Motor Skill Competence and Health-Related Fitness in Youth. Pediatr Exerc Sci. 2014. Aug;26(3):231–41. doi: 10.1123/pes.2013-0027 [DOI] [PubMed] [Google Scholar]
41.WHO. WHO BMI-for-age reference [Internet]. 2007. [cited 2021 Jul 13]. Available from: https://www.who.int/tools/growth-reference-data-for-5to19-years/indicators/bmi-for-age [Google Scholar]
42.R Core Team. R: A language and environment for statistical computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2020. Available from: https://www.R-project.org/ [Google Scholar]
43.Muthén LK, Muthén BO. Mplus user’s guide. Los Angeles, CA: Muthén & Muthén; 1998. [Google Scholar]
44.Cohen J. Statistical Power Analysis for the Behavioural Sciences. Hillsdale, NJ, USA: Lawrence Erlbaum Associates; 1988. [Google Scholar]
45.Schmutz EA, Leeger-Aschmann CS, Kakebeeke TH, Zysset AE, Messerli-Bürgy N, Stülb K, et al. Motor Competence and Physical Activity in Early Childhood: Stability and Relationship. Front Public Health. 2020. Feb 21;8:39. [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Nicolai Ré AH, Okely AD, Logan SW, da Silva MMLM, Cattuzzo MT, Stodden DF. Relationship between meeting physical activity guidelines and motor competence among low-income school youth. J Sci Med Sport. 2019. Dec;S1440244019306954. doi: 10.1016/j.jsams.2019.12.014 [DOI] [PubMed] [Google Scholar]
47.King-Dowling S, Proudfoot NA, Cairney J, Timmons BW. Motor Competence, Physical Activity, and Fitness across Early Childhood. Med Sci Sports Exerc. 2020. Nov;52(11):2342–8. doi: 10.1249/MSS.0000000000002388 [DOI] [PubMed] [Google Scholar]
48.De Meester A, Stodden D, Goodway J, True L, Brian A, Ferkel R, et al. Identifying a motor proficiency barrier for meeting physical activity guidelines in children. J Sci Med Sport. 2018. Jan;21(1):58–62. doi: 10.1016/j.jsams.2017.05.007 [DOI] [PubMed] [Google Scholar]
49.Kambas A, Michalopoulou M, Fatouros IG, Christoforidis C, Manthou E, Giannakidou D, et al. The Relationship Between Motor Proficiency and Pedometer-Determined Physical Activity in Young Children. Pediatr Exerc Sci. 2012. Feb;24(1):34–44. doi: 10.1123/pes.24.1.34 [DOI] [PubMed] [Google Scholar]
50.Williams HG, Pfeiffer KA, O’Neill JR, Dowda M, McIver KL, Brown WH, et al. Motor Skill Performance and Physical Activity in Preschool Children. Obesity. 2008. Jun;16(6):1421–6. doi: 10.1038/oby.2008.214 [DOI] [PubMed] [Google Scholar]
51.Wrotniak BH, Epstein LH, Dorn JM, Jones KE, Kondilis VA. The Relationship Between Motor Proficiency and Physical Activity in Children. Pediatrics. 2006. Dec 1;118(6):e1758–65. doi: 10.1542/peds.2006-0742 [DOI] [PubMed] [Google Scholar]
52.Barnett LM, Ridgers ND, Salmon J. Associations between young children’s perceived and actual ball skill competence and physical activity. J Sci Med Sport. 2015. Mar;18(2):167–71. doi: 10.1016/j.jsams.2014.03.001 [DOI] [PubMed] [Google Scholar]
53.LeGear M, Greyling L, Sloan E, Bell R, Williams BL, Naylor PJ, et al. A window of opportunity? Motor skills and perceptions of competence of children in Kindergarten. Int J Behav Nutr Phys Act. 2012;9:29–33. doi: 10.1186/1479-5868-9-29 [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Robinson LE. The relationship between perceived physical competence and fundamental motor skills in preschool children: Fundamental motor skills and perceived competence. Child Care Health Dev. 2011. Jul;37(4):589–96. [DOI] [PubMed] [Google Scholar]
55.De Meester A, Barnett LM, Brian A, Bowe SJ, Jiménez-Díaz J, Van Duyse F, et al. The Relationship Between Actual and Perceived Motor Competence in Children, Adolescents and Young Adults: A Systematic Review and Meta-analysis. Sports Med. 2020. Nov;50(11):2001–49. doi: 10.1007/s40279-020-01336-2 [DOI] [PubMed] [Google Scholar]
56.True L, Brian A, Goodway J, Stodden D. Relationships Between Product- and Process-Oriented Measures of Motor Competence and Perceived Competence. J Mot Learn Dev. 2017. Dec;5(2):319–35. [Google Scholar]
57.Hall C, Eyre E, Oxford S, Duncan M. Does Perception of Motor Competence Mediate Associations between Motor Competence and Physical Activity in Early Years Children? Sports. 2019. Apr 1;7(4):77. doi: 10.3390/sports7040077 [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Lopes VP, Barnett L, Rodrigues L. Is There an Association Among Actual Motor Competence, Perceived Motor Competence, Physical Activity, and Sedentary Behavior in Preschool Children? J Mot Learn Dev. 2016. Dec;4(2):129–41. [Google Scholar]
59.Slykerman S, Ridgers ND, Stevenson C, Barnett LM. How important is young children’s actual and perceived movement skill competence to their physical activity? J Sci Med Sport. 2016. Jun;19(6):488–92. doi: 10.1016/j.jsams.2015.07.002 [DOI] [PubMed] [Google Scholar]
60.De Meester A, Stodden D, Brian A, True L, Cardon G, Tallir I, et al. Associations among Elementary School Children’s Actual Motor Competence, Perceived Motor Competence, Physical Activity and BMI: A Cross-Sectional Study. Pappalardo F, editor. PLOS ONE. 2016. Oct 13;11(10):e0164600. doi: 10.1371/journal.pone.0164600 [DOI] [PMC free article] [PubMed] [Google Scholar]
61.Khodaverdi Z, Bahram A, Khalaji H. Motor Skill Competence and Perceived Motor Competence: Which Best Predicts Physical Activity among Girls? 2013;42:6. [PMC free article] [PubMed] [Google Scholar]
62.Lopes VP, Stodden DF, Bianchi MM, Maia JAR, Rodrigues LP. Correlation between BMI and motor coordination in children. J Sci Med Sport. 2012. Jan;15(1):38–43. doi: 10.1016/j.jsams.2011.07.005 [DOI] [PubMed] [Google Scholar]
63.Spessato BC, Gabbard C, Robinson L, Valentini NC. Body mass index, perceived and actual physical competence: the relationship among young children: Perceived and actual physical competence and body mass index among young children. Child Care Health Dev. 2012. Dec;n/a-n/a. [DOI] [PubMed] [Google Scholar]
64.Logan SW, Scrabis-Fletcher K, Modlesky C, Getchell N. The Relationship Between Motor Skill Proficiency and Body Mass Index in Preschool Children. Res Q Exerc Sport. 2011. Sep;82(3):442–8. doi: 10.1080/02701367.2011.10599776 [DOI] [PubMed] [Google Scholar]
65.Trecroci A, Invernizzi PL, Monacis D, Colella D. Actual and Perceived Motor Competence in Relation to Body Mass Index in Primary School-Aged Children: A Systematic Review. Sustainability. 2021. Sep 6;13(17):9994. [Google Scholar]
66.Lima RA, Pfeiffer KA, Bugge A, Møller NC, Andersen LB, Stodden DF. Motor competence and cardiorespiratory fitness have greater influence on body fatness than physical activity across time. Scand J Med Sci Sports. 2017. Dec;27(12):1638–47. doi: 10.1111/sms.12850 [DOI] [PubMed] [Google Scholar]
67.Lima RA, Bugge A, Ersbøll AK, Stodden DF, Andersen LB. The longitudinal relationship between motor competence and measures of fatness and fitness from childhood into adolescence. J Pediatr (Rio J). 2019. Jul;95(4):482–8. doi: 10.1016/j.jped.2018.02.010 [DOI] [PubMed] [Google Scholar]
68.Jekauc D, Wagner MO, Herrmann C, Hegazy K, Woll A. Does Physical Self-Concept Mediate the Relationship between Motor Abilities and Physical Activity in Adolescents and Young Adults? Zhou R, editor. PLOS ONE. 2017. Jan 3;12(1):e0168539. doi: 10.1371/journal.pone.0168539 [DOI] [PMC free article] [PubMed] [Google Scholar]
69.Jaakkola T, Yli-Piipari S, Huotari P, Watt A, Liukkonen J. Fundamental movement skills and physical fitness as predictors of physical activity: A 6-year follow-up study: Motor skills, fitness, and physical activity. Scand J Med Sci Sports. 2016. Jan;26(1):74–81. [DOI] [PubMed] [Google Scholar]
70.Elhakeem A, Hardy R, Bann D, Kuh D, Cooper R. Motor performance in early life and participation in leisure-time physical activity up to age 68 years. Paediatr Perinat Epidemiol. 2018. Jul;32(4):327–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
71.Utesch T, Bardid F, Büsch D, Strauss B. The Relationship Between Motor Competence and Physical Fitness from Early Childhood to Early Adulthood: A Meta-Analysis. Sports Med. 2019. Apr;49(4):541–51. doi: 10.1007/s40279-019-01068-y [DOI] [PubMed] [Google Scholar]
72.Cattuzzo MT, dos Santos Henrique R, Ré AHN, de Oliveira IS, Melo BM, de Sousa Moura M, et al. Motor competence and health related physical fitness in youth: A systematic review. J Sci Med Sport. 2016. Feb;19(2):123–9. doi: 10.1016/j.jsams.2014.12.004 [DOI] [PubMed] [Google Scholar]
73.Adamo KB, Prince SA, Tricco AC, Connor-Gorber S, Tremblay M. A comparison of indirect versus direct measures for assessing physical activity in the pediatric population: A systematic review. Int J Pediatr Obes. 2009;4:2–27. doi: 10.1080/17477160802315010 [DOI] [PubMed] [Google Scholar]
74.Holfelder B, Schott N. Relationship of fundamental movement skills and physical activity in children and adolescents: A systematic review. Psychol Sport Exerc. 2014. Jul;15(4):382–91. [Google Scholar]
75.Raudsepp L, Päll P. The Relationship between Fundamental Motor Skills and Outside-School Physical Activity of Elementary School Children. Pediatr Exerc Sci. 2006. Nov 1;18:426–35. [DOI] [PubMed] [Google Scholar]
76.Famelia R, Tsuda E, Bakhtiar S, Goodway JD. Relationships Among Perceived and Actual Motor Skill Competence and Physical Activity in Indonesian Preschoolers. J Mot Learn Dev. 2018. Oct 1;6(s2):S403–23. [Google Scholar]
77.Barnett LM, Morgan PJ, Van Beurden E, Ball K, Lubans DR. A Reverse Pathway? Actual and Perceived Skill Proficiency and Physical Activity: Med Sci Sports Exerc. 2011. May;43(5):898–904. [DOI] [PubMed] [Google Scholar]
78.Cohen KE, Morgan PJ, Plotnikoff RC, Callister R, Lubans DR. Fundamental movement skills and physical activity among children living in low-income communities: a cross-sectional study. Int J Behav Nutr Phys Act. 2014;11(1):49. doi: 10.1186/1479-5868-11-49 [DOI] [PMC free article] [PubMed] [Google Scholar]
79.Bezerra TA, Bandeira PFR, de Souza Filho AN, Clark CCT, Mota JAPS, Duncan MJ, et al. A Network Perspective on the Relationship Between Moderate to Vigorous Physical Activity and Fundamental Motor Skills in Early Childhood. J Phys Act Health. 2021. Jul 1;18(7):774–81. doi: 10.1123/jpah.2020-0218 [DOI] [PubMed] [Google Scholar]
80.Lopes VP, Malina RM, Maia JAR, Rodrigues LP. Body mass index and motor coordination: Non-linear relationships in children 6–10 years. Child Care Health Dev. 2018. May;44(3):443–51. doi: 10.1111/cch.12557 [DOI] [PubMed] [Google Scholar]
81.Fechner PY. The biology of puberty: New developments in sex differences. In: Gender Differences at Puberty. p. 17–28. [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0278438.r001

Decision Letter 0

Ender Senel

2 Jan 2023

PONE-D-22-31483The relationships between children’s motor competence, physical activity, perceived motor competence, physical fitness and weight status in relation to agePLOS ONE

Dear Dr. den Uil,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please see the reviewers suggestions to revise your paper.

Please submit your revised manuscript by Feb 16 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Ender Senel, PhD

Academic Editor

PLOS ONE

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.

2. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For more information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

3. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

4. We note that Figure 1 in your submission contain copyrighted images. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

a) You may seek permission from the original copyright holder of Figure(s) [#] to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

b) If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This large-scale cross-sectional study examined correlations among five variables noted in the Stodden et al., conceptual model in children from 4-13 yrs, noting changes (or lack thereof) in the strength of correlations each year. The writing is generally clear and to the point.

This is the largest study to date that addresses all aspects of the model, which is a strength of the study. Specifically addressing the notion of hypothesized changes in the strength of associations across childhood and into adolescence is important as most studies in this area have not addressed this critical aspect of the model hypotheses and have not covered this wide of an age span.

While the cross-sectional nature of the data limits the generalizability of the conclusions, the data generally support other longitudinal data from studies that have examined a limited number of variables in the model. It might be useful to address the results of these studies to corroborate or refute the results of the current study as the age ranges of the below studies are within the age range of the current study.

Jaakkola, T., Yli‐Piipari, S., Huotari, P., Watt, A., & Liukkonen, J. (2016). Fundamental movement skills and physical fitness as predictors of physical activity: A 6‐year follow‐up study. Scandinavian Journal of Medicine & Science in Sports, 26(1), 74-81.

Lima, R.A., Pfeiffer, K.A., Bugge, A., Møller, N.C., Andersen, L.B., Stodden, D.F. (2017). Motor competence and cardiorespiratory fitness have greater influence on body fatness than physical activity across time. Scand J Med Sci Sport, 1-10. https://doi.org/10.1111/sms.12850

Lima, R. A., Bugge, A., Ersbøll, A. K., Stodden, D. F., & Andersen, L. B. (2019). The longitudinal relationship between motor competence and measures of fatness and fitness from childhood into adolescence. Jornal de Pediatria, 95, 482-488.

While the individual correlations among variables at each age is important in its own right, I am left wondering if it would be possible to analyze the data at each age as a collective system (e.g., using SEM/path analyses) as it would provide understanding of whether the data collectively “fit” the Stodden et al model as a whole (i.e., as a more comprehensive system of individual factors of development). This would provide a stronger conceptual understanding (while still providing an understanding of the individual strength of correlation coefficients in the models) of the overall fit of the conceptual model across ages, which was the intent of including all the different variables that have, historically, been examined individually. If the ”fit” of the individual age models strengthen (or do not) across time, then the central research question would still be answered (in addition to examining how individual correlations changed across time). As can be seen from the suggested “tipping point” time frames in Table 3, potentially demonstrating a non-significant model fit in younger ages would still address the central research question and account for the original hypotheses of the model, which suggests correlations among variables in the model (and the overall model fit) would be weaker in early childhood. However, based on the range of sample sizes at each age, and the number of variables that would need to be entered into each model, I am not sure if this suggestion is feasible from a statistical standpoint.

Another potential limitation of the current statistical analyses is the assumption of linear relationships between variables. The authors address this idea indirectly when referencing a proficiency barrier, but it is still a potential avenue for exploration, perhaps in a subsequent paper.

While the “motor age” variable partially addresses how motor skill scores generally increase with each age group, would it be useful to provide supplementary data to see the changes in raw motor skill scores across age groups? The authors noted a potential ceiling effect for the motor skill measures; thus, it might be useful to provide the raw data to better show the how motor skill levels change across time.

One important limitation in the data is based on the measure of PA. I believe it is important to note the limitations of these data more concretely. Specifically, the overestimation of PA with questionnaires should be noted.

Lastly, addressing maturation and how that impact gender-specific differences in the relationships (specifically during the adolescent transition) also is an important notion that was not explored in the data. Controlling for gender in the correlations might be a useful endeavor from a statistical standpoint.

Reviewer #2: Review_PONE-D-22-31483

Overview

The manuscript is excellent, the subject matter is current, and it is straightforward and objective. The research covers a significant information gap about the association between motor competence, physical activity, and related factors by using a well-designed approach and a large sample. Although I provide some suggestions for the authors' consideration, I firmly recommend publication of this article.

Introduction

Update the reference [2]

Materials and Method

• Give more information about the socioeconomic status of the sample or the population from which the sample was drawn.

• Give more details of excluded participants (exclusion percentage, gender, age group)

• Give more details on how the sampling was done; explain how the sample size was estimated.

Discussion

• Lines 300-302 - “Although we cannot draw conclusions on causality, our findings do not support the proposed pathway in which physical activity stimulates motor competence in early childhood.”

This sentence, unfortunately, is poorly constructed and may lead the reader into a misunderstanding. The authors are asked to consider rewriting it, bearing in mind that the data in this article preclude any stimulus/cause-effect inference. The choice of terms here must be very careful.

It is also suggested that the authors reflect a little more on the results of physical activity and possible biases in data collection, as it is precisely at younger ages that n is the lowest for the physical activity variable.

• Line 302-305: at this point, it should be considered that the present study used indirect measures of physical activity;

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Maria Teresa Cattuzzo

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2023 Apr 14;18(4):e0278438. doi: 10.1371/journal.pone.0278438.r002

Author response to Decision Letter 0

24 Feb 2023

Dear sir/madam,

Thank you for your review. We have addressed all question and remarks in our revised Cover Letter and Response to the Reviewers and have adjusted our Manuscript. We thereby hope our revised submission meets the requirements for publishing.

Sincerely,

AR den Uil

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(69.6KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0278438.r003

Decision Letter 1

Ender Senel

21 Mar 2023

The relationships between children’s motor competence, physical activity, perceived motor competence, physical fitness and weight status in relation to age

PONE-D-22-31483R1

Dear Dr. den Uil,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Ender Senel, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

Reviewer #1: The authors have adequately addressed all my suggestions.

A suggestion for future work with these data... Cluster analyses... A different approach to address the data more from a person-centered (vs. a variable-centered) perspective.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

**********

PLoS One. doi: 10.1371/journal.pone.0278438.r004

Acceptance letter

Ender Senel

5 Apr 2023

PONE-D-22-31483R1

The relationships between children’s motor competence, physical activity, perceived motor competence, physical fitness and weight status in relation to age

Dear Dr. den Uil:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ender Senel

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Z statistic values of the difference in correlation coefficients of BMI—motor competence between ages.

(DOCX)

Click here for additional data file.^{(13.9KB, docx)}

S2 Table. Z statistic values of the difference in correlation coefficients of BMI—perceived motor competence between ages.

(DOCX)

Click here for additional data file.^{(13.6KB, docx)}

S3 Table. Z statistic values of the difference in correlation coefficients of BMI—physical activity between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S4 Table. Z statistic values of the difference in correlation coefficients of BMI—physical fitness between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S5 Table. Z statistic values of the difference in correlation coefficients of motor competence—perceived motor competence between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S6 Table. Z statistic values of the difference in correlation coefficients of motor competence—physical activity between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S7 Table. Z statistic values of the difference in correlation coefficients of motor competence—physical fitness between ages.

(DOCX)

Click here for additional data file.^{(13.8KB, docx)}

S8 Table. Z statistic values of the difference in correlation coefficients of perceived motor competence -physical activity between ages.

(DOCX)

Click here for additional data file.^{(13.8KB, docx)}

S9 Table. Z statistic values of the difference in correlation coefficients of physical activity—physical fitness between ages.

(DOCX)

Click here for additional data file.^{(13.7KB, docx)}

S10 Table. Z statistic values of the difference in correlation coefficients of perceived motor competence—physical fitness between ages.

(DOCX)

Click here for additional data file.^{(13.8KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(69.6KB, docx)}

Data Availability Statement

The data have been uploaded to Figshare with DOI https://doi.org/10.21943/auas.22332841.v1.

[pone.0278438.ref001] 1.Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1·9 million participants. Lancet Glob Health. 2018. Oct;6(10):e1077–86. [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref002] 2.CBS RIVM. Gezondheidsenquête/Leefstijlmonitor. 2019. [Google Scholar]

[pone.0278438.ref003] 3.World Health Organization, editor. Global health risks: mortality and burden of disease attributable to selected major risks. Geneva, Switzerland: World Health Organization; 2009. 62 p. [Google Scholar]

[pone.0278438.ref004] 4.Loprinzi PD, Cardinal BJ, Loprinzi KL, Lee H. Benefits and Environmental Determinants of Physical Activity in Children and Adolescents. Obes Facts. 2012;5(4):597–610. doi: 10.1159/000342684 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref005] 5.Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9·1 million participants. 2011;12. [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref006] 6.Wang YC, McPherson K, Marsh T, Gortmaker SL, Brown M. Health and economic burden of the projected obesity trends in the USA and the UK. The Lancet. 2011. Aug;378(9793):815–25. doi: 10.1016/S0140-6736(11)60814-3 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref007] 7.CBS RIVM. Gezondheidsenquête/Leefstijlmonitor. 2018. [Google Scholar]

[pone.0278438.ref008] 8.Gallahue DL, Ozmun JC, Goodway J. Understanding motor development: Infants, children, adolescents, adults. 7th ed. New York, NY: McGraw-Hill; 2012. [Google Scholar]

[pone.0278438.ref009] 9.Barnett LM, Webster EK, Hulteen RM, De Meester A, Valentini NC, Lenoir M, et al. Through the Looking Glass: A Systematic Review of Longitudinal Evidence, Providing New Insight for Motor Competence and Health. Sports Med. 2022. Apr;52(4):875–920. doi: 10.1007/s40279-021-01516-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref010] 10.Willems WAJJ Erken IE, Johannes M, van Kernebeek WG, de Schipper A, Toussaint HM. Goed bewegen van basisschoolleerlingen is onze zorg: Samen aan de slag met de gymleraar. JGZ Tijdschr Voor Jeugdgezondheidsz. 2016. Aug;48(4):72–7. [Google Scholar]

[pone.0278438.ref011] 11.De Meester A, Maes J, Stodden D, Cardon G, Goodway J, Lenoir M, et al. Identifying profiles of actual and perceived motor competence among adolescents: associations with motivation, physical activity, and sports participation. J Sports Sci. 2016. Nov;34(21):2027–37. doi: 10.1080/02640414.2016.1149608 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref012] 12.Morrison KM, Cairney J, Eisenmann J, Pfeiffer K, Gould D. Associations of Body Mass Index, Motor Performance, and Perceived Athletic Competence with Physical Activity in Normal Weight and Overweight Children. J Obes. 2018;2018:1–10. doi: 10.1155/2018/3598321 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref013] 13.Chan CHS, Ha ASC, Ng JYY, Lubans DR. Associations between fundamental movement skill competence, physical activity and psycho-social determinants in Hong Kong Chinese children. J Sports Sci. 2019. Jan 17;37(2):229–36. doi: 10.1080/02640414.2018.1490055 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref014] 14.Jekauc D, Wagner MO, Herrmann C, Hegazy K, Woll A. Does Physical Self-Concept Mediate the Relationship between Motor Abilities and Physical Activity in Adolescents and Young Adults? Zhou R, editor. PLOS ONE. 2017. Jan 3;12(1):e0168539. doi: 10.1371/journal.pone.0168539 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref015] 15.Stodden DF, Goodway JD, Langendorfer SJ, Roberton MA, Rudisill ME, Garcia C, et al. A Developmental Perspective on the Role of Motor Skill Competence in Physical Activity: An Emergent Relationship. Quest. 2008. May;60(2):290–306. [Google Scholar]

[pone.0278438.ref016] 16.Goodway JD, Rudisill ME. Perceived Physical Competence and Actual Motor Skill Competence of African American Preschool Children. Adapt Phys Act Q. 1997. Oct;14(4):314–26. [Google Scholar]

[pone.0278438.ref017] 17.Harter S. The construction of the self: a developmental perspective. Guilford Press; 1999. [Google Scholar]

[pone.0278438.ref018] 18.Casey B, Tottenham N, Liston C, Durston S. Imaging the developing brain: what have we learned about cognitive development? Trends Cogn Sci. 2005. Mar;9(3):104–10. doi: 10.1016/j.tics.2005.01.011 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref019] 19.Gogtay N, Giedd JN, Lusk L, Hayashi KM, Greenstein D, Vaituzis AC, et al. Dynamic mapping of human cortical development during childhood through early adulthood. Proc Natl Acad Sci. 2004. May 25;101(21):8174–9. doi: 10.1073/pnas.0402680101 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref020] 20.Thomas M, Knowland VC. Sensitive Periods in Brain Development–Implications for Education Policy. Eur Psychiatr Rev. 2009;2(1):17–20. [Google Scholar]

[pone.0278438.ref021] 21.Babic M, Morgan P, Plotnikoff R, Lubans D, Lonsdale C, White R. Physical activity and physical self-concept in youth: Systematic review and meta-analysis. J Sci Med Sport. 2014. Dec;18:e154. doi: 10.1007/s40279-014-0229-z [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref022] 22.Crane JR, Naylor PJ, Cook R, Temple VA. Do Perceptions of Competence Mediate The Relationship Between Fundamental Motor Skill Proficiency and Physical Activity Levels of Children in Kindergarten? J Phys Act Health. 2015. Jul;12(7):954–61. doi: 10.1123/jpah.2013-0398 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref023] 23.Britton U, Issartel J, Symonds J, Belton S. What Keeps Them Physically Active? Predicting Physical Activity, Motor Competence, Health-Related Fitness, and Perceived Competence in Irish Adolescents after the Transition from Primary to Second-Level School. Int J Environ Res Public Health. 2020. Apr 21;17(8):2874. doi: 10.3390/ijerph17082874 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref024] 24.Burns R, Fu Y. Testing the Motor Competence and Health-Related Variable Conceptual Model: A Path Analysis. J Funct Morphol Kinesiol. 2018. Nov 28;3(4):61. doi: 10.3390/jfmk3040061 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref025] 25.dos Santos MAM, Nevill AM, Buranarugsa R, Pereira S, Gomes TNQF, Reyes A, et al. Modeling children’s development in gross motor coordination reveals key modifiable determinants. An allometric approach. Scand J Med Sci Sports. 2018. May;28(5):1594–603. doi: 10.1111/sms.13061 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref026] 26.Jaakkola T, Huhtiniemi M, Salin K, Seppälä S, Lahti J, Hakonen H, et al. Motor competence, perceived physical competence, physical fitness, and physical activity within Finnish children. Scand J Med Sci Sports. 2019. Mar 19;sms.13412. doi: 10.1111/sms.13412 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref027] 27.Khodaverdi Z, Bahram A, Stodden D, Kazemnejad A. The relationship between actual motor competence and physical activity in children: mediating roles of perceived motor competence and health-related physical fitness. J Sports Sci. 2016. Aug 17;34(16):1523–9. doi: 10.1080/02640414.2015.1122202 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref028] 28.Robinson LE, Stodden DF, Barnett LM, Lopes VP, Logan SW, Rodrigues LP, et al. Motor Competence and its Effect on Positive Developmental Trajectories of Health. Sports Med. 2015. Sep;45(9):1273–84. doi: 10.1007/s40279-015-0351-6 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref029] 29.Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behav Res Methods. 41:1149–60. doi: 10.3758/BRM.41.4.1149 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref030] 30.van Gelder W, Stroes H. Leerlingvolgsysteem Bewegen en Spelen. Over observeren, registeren en extra zorg. 2nd ed. Amsterdam, The Netherlands: Elsevier; 2010. [Google Scholar]

[pone.0278438.ref031] 31.van Kernebeek WG, de Schipper AW, Savelsbergh GJP, Toussaint HM. Inter-rater and test–retest (between-sessions) reliability of the 4-Skills Scan for dutch elementary school children. Meas Phys Educ Exerc Sci. 2018. Apr 3;22(2):129–37. [Google Scholar]

[pone.0278438.ref032] 32.van Kernebeek WG, de Kroon MLA, Savelsbergh GJP, Toussaint HM. The validity of the 4-Skills Scan A double-validation study. Scand J Med Sci Sports. 2018. Nov;28(11):2349–57. doi: 10.1111/sms.13231 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref033] 33.Harter S, Pike R. The Pictorial Scale of Perceived Competence and Social Acceptance for Young Children. Child Dev. 1984. Dec;55(6):1969. [PubMed] [Google Scholar]

[pone.0278438.ref034] 34.Harter S. The Self-perception profile for children manual. In Denver: University of Denver; 1985. [Google Scholar]

[pone.0278438.ref035] 35.Veerman JW, Straathof MAE, Treffers PhDA, van den Bergh BRH, ten Brink LT. Competentiebelevingsschaal voor Kinderen—handleiding. Lisse, Netherlands: Harcourt Assessment BV.; 2004. [Google Scholar]

[pone.0278438.ref036] 36.Singh AS, Vik FN, Chinapaw MJ, Uijtdewilligen L, Verloigne M, Fernández-Alvira JM, et al. Test-retest reliability and construct validity of the ENERGY-child questionnaire on energy balance-related behaviours and their potential determinants: the ENERGY-project. Int J Behav Nutr Phys Act. 2011;8(1):1. doi: 10.1186/1479-5868-8-136 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref037] 37.Loprinzi PD, Cardinal BJ. Measuring Children’s Physical Activity and Sedentary Behaviors. J Exerc Sci Fit. 2011;9(1):15–23. [Google Scholar]

[pone.0278438.ref038] 38.van Mechelen W, van Lier WH, Hlobil H, Crolla I, Kemper HCG. Eurofit, Handleiding met referentieschalen voor 12- tot en met 16-jarige jongens en meisjes in Nederland. Haarlem: Uitgeverij de Vrieseborch; 2011. [Google Scholar]

[pone.0278438.ref039] 39.Borremans E, Rintala P, Kielinen M. EFFECTIVENESS OF AN EXERCISE TRAINING PROGRAM ON YOUTH WITH ASPERGER SYNDROME. Eur J Adapt Phys Act. 2009. Jul 31;2(2):14–25. [Google Scholar]

[pone.0278438.ref040] 40.Stodden DF, Gao Z, Goodway JD, Langendorfer SJ. Dynamic Relationships Between Motor Skill Competence and Health-Related Fitness in Youth. Pediatr Exerc Sci. 2014. Aug;26(3):231–41. doi: 10.1123/pes.2013-0027 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref041] 41.WHO. WHO BMI-for-age reference [Internet]. 2007. [cited 2021 Jul 13]. Available from: https://www.who.int/tools/growth-reference-data-for-5to19-years/indicators/bmi-for-age [Google Scholar]

[pone.0278438.ref042] 42.R Core Team. R: A language and environment for statistical computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2020. Available from: https://www.R-project.org/ [Google Scholar]

[pone.0278438.ref043] 43.Muthén LK, Muthén BO. Mplus user’s guide. Los Angeles, CA: Muthén & Muthén; 1998. [Google Scholar]

[pone.0278438.ref044] 44.Cohen J. Statistical Power Analysis for the Behavioural Sciences. Hillsdale, NJ, USA: Lawrence Erlbaum Associates; 1988. [Google Scholar]

[pone.0278438.ref045] 45.Schmutz EA, Leeger-Aschmann CS, Kakebeeke TH, Zysset AE, Messerli-Bürgy N, Stülb K, et al. Motor Competence and Physical Activity in Early Childhood: Stability and Relationship. Front Public Health. 2020. Feb 21;8:39. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref046] 46.Nicolai Ré AH, Okely AD, Logan SW, da Silva MMLM, Cattuzzo MT, Stodden DF. Relationship between meeting physical activity guidelines and motor competence among low-income school youth. J Sci Med Sport. 2019. Dec;S1440244019306954. doi: 10.1016/j.jsams.2019.12.014 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref047] 47.King-Dowling S, Proudfoot NA, Cairney J, Timmons BW. Motor Competence, Physical Activity, and Fitness across Early Childhood. Med Sci Sports Exerc. 2020. Nov;52(11):2342–8. doi: 10.1249/MSS.0000000000002388 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref048] 48.De Meester A, Stodden D, Goodway J, True L, Brian A, Ferkel R, et al. Identifying a motor proficiency barrier for meeting physical activity guidelines in children. J Sci Med Sport. 2018. Jan;21(1):58–62. doi: 10.1016/j.jsams.2017.05.007 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref049] 49.Kambas A, Michalopoulou M, Fatouros IG, Christoforidis C, Manthou E, Giannakidou D, et al. The Relationship Between Motor Proficiency and Pedometer-Determined Physical Activity in Young Children. Pediatr Exerc Sci. 2012. Feb;24(1):34–44. doi: 10.1123/pes.24.1.34 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref050] 50.Williams HG, Pfeiffer KA, O’Neill JR, Dowda M, McIver KL, Brown WH, et al. Motor Skill Performance and Physical Activity in Preschool Children. Obesity. 2008. Jun;16(6):1421–6. doi: 10.1038/oby.2008.214 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref051] 51.Wrotniak BH, Epstein LH, Dorn JM, Jones KE, Kondilis VA. The Relationship Between Motor Proficiency and Physical Activity in Children. Pediatrics. 2006. Dec 1;118(6):e1758–65. doi: 10.1542/peds.2006-0742 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref052] 52.Barnett LM, Ridgers ND, Salmon J. Associations between young children’s perceived and actual ball skill competence and physical activity. J Sci Med Sport. 2015. Mar;18(2):167–71. doi: 10.1016/j.jsams.2014.03.001 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref053] 53.LeGear M, Greyling L, Sloan E, Bell R, Williams BL, Naylor PJ, et al. A window of opportunity? Motor skills and perceptions of competence of children in Kindergarten. Int J Behav Nutr Phys Act. 2012;9:29–33. doi: 10.1186/1479-5868-9-29 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref054] 54.Robinson LE. The relationship between perceived physical competence and fundamental motor skills in preschool children: Fundamental motor skills and perceived competence. Child Care Health Dev. 2011. Jul;37(4):589–96. [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref055] 55.De Meester A, Barnett LM, Brian A, Bowe SJ, Jiménez-Díaz J, Van Duyse F, et al. The Relationship Between Actual and Perceived Motor Competence in Children, Adolescents and Young Adults: A Systematic Review and Meta-analysis. Sports Med. 2020. Nov;50(11):2001–49. doi: 10.1007/s40279-020-01336-2 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref056] 56.True L, Brian A, Goodway J, Stodden D. Relationships Between Product- and Process-Oriented Measures of Motor Competence and Perceived Competence. J Mot Learn Dev. 2017. Dec;5(2):319–35. [Google Scholar]

[pone.0278438.ref057] 57.Hall C, Eyre E, Oxford S, Duncan M. Does Perception of Motor Competence Mediate Associations between Motor Competence and Physical Activity in Early Years Children? Sports. 2019. Apr 1;7(4):77. doi: 10.3390/sports7040077 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref058] 58.Lopes VP, Barnett L, Rodrigues L. Is There an Association Among Actual Motor Competence, Perceived Motor Competence, Physical Activity, and Sedentary Behavior in Preschool Children? J Mot Learn Dev. 2016. Dec;4(2):129–41. [Google Scholar]

[pone.0278438.ref059] 59.Slykerman S, Ridgers ND, Stevenson C, Barnett LM. How important is young children’s actual and perceived movement skill competence to their physical activity? J Sci Med Sport. 2016. Jun;19(6):488–92. doi: 10.1016/j.jsams.2015.07.002 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref060] 60.De Meester A, Stodden D, Brian A, True L, Cardon G, Tallir I, et al. Associations among Elementary School Children’s Actual Motor Competence, Perceived Motor Competence, Physical Activity and BMI: A Cross-Sectional Study. Pappalardo F, editor. PLOS ONE. 2016. Oct 13;11(10):e0164600. doi: 10.1371/journal.pone.0164600 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref061] 61.Khodaverdi Z, Bahram A, Khalaji H. Motor Skill Competence and Perceived Motor Competence: Which Best Predicts Physical Activity among Girls? 2013;42:6. [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref062] 62.Lopes VP, Stodden DF, Bianchi MM, Maia JAR, Rodrigues LP. Correlation between BMI and motor coordination in children. J Sci Med Sport. 2012. Jan;15(1):38–43. doi: 10.1016/j.jsams.2011.07.005 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref063] 63.Spessato BC, Gabbard C, Robinson L, Valentini NC. Body mass index, perceived and actual physical competence: the relationship among young children: Perceived and actual physical competence and body mass index among young children. Child Care Health Dev. 2012. Dec;n/a-n/a. [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref064] 64.Logan SW, Scrabis-Fletcher K, Modlesky C, Getchell N. The Relationship Between Motor Skill Proficiency and Body Mass Index in Preschool Children. Res Q Exerc Sport. 2011. Sep;82(3):442–8. doi: 10.1080/02701367.2011.10599776 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref065] 65.Trecroci A, Invernizzi PL, Monacis D, Colella D. Actual and Perceived Motor Competence in Relation to Body Mass Index in Primary School-Aged Children: A Systematic Review. Sustainability. 2021. Sep 6;13(17):9994. [Google Scholar]

[pone.0278438.ref066] 66.Lima RA, Pfeiffer KA, Bugge A, Møller NC, Andersen LB, Stodden DF. Motor competence and cardiorespiratory fitness have greater influence on body fatness than physical activity across time. Scand J Med Sci Sports. 2017. Dec;27(12):1638–47. doi: 10.1111/sms.12850 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref067] 67.Lima RA, Bugge A, Ersbøll AK, Stodden DF, Andersen LB. The longitudinal relationship between motor competence and measures of fatness and fitness from childhood into adolescence. J Pediatr (Rio J). 2019. Jul;95(4):482–8. doi: 10.1016/j.jped.2018.02.010 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref068] 68.Jekauc D, Wagner MO, Herrmann C, Hegazy K, Woll A. Does Physical Self-Concept Mediate the Relationship between Motor Abilities and Physical Activity in Adolescents and Young Adults? Zhou R, editor. PLOS ONE. 2017. Jan 3;12(1):e0168539. doi: 10.1371/journal.pone.0168539 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref069] 69.Jaakkola T, Yli-Piipari S, Huotari P, Watt A, Liukkonen J. Fundamental movement skills and physical fitness as predictors of physical activity: A 6-year follow-up study: Motor skills, fitness, and physical activity. Scand J Med Sci Sports. 2016. Jan;26(1):74–81. [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref070] 70.Elhakeem A, Hardy R, Bann D, Kuh D, Cooper R. Motor performance in early life and participation in leisure-time physical activity up to age 68 years. Paediatr Perinat Epidemiol. 2018. Jul;32(4):327–34. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref071] 71.Utesch T, Bardid F, Büsch D, Strauss B. The Relationship Between Motor Competence and Physical Fitness from Early Childhood to Early Adulthood: A Meta-Analysis. Sports Med. 2019. Apr;49(4):541–51. doi: 10.1007/s40279-019-01068-y [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref072] 72.Cattuzzo MT, dos Santos Henrique R, Ré AHN, de Oliveira IS, Melo BM, de Sousa Moura M, et al. Motor competence and health related physical fitness in youth: A systematic review. J Sci Med Sport. 2016. Feb;19(2):123–9. doi: 10.1016/j.jsams.2014.12.004 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref073] 73.Adamo KB, Prince SA, Tricco AC, Connor-Gorber S, Tremblay M. A comparison of indirect versus direct measures for assessing physical activity in the pediatric population: A systematic review. Int J Pediatr Obes. 2009;4:2–27. doi: 10.1080/17477160802315010 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref074] 74.Holfelder B, Schott N. Relationship of fundamental movement skills and physical activity in children and adolescents: A systematic review. Psychol Sport Exerc. 2014. Jul;15(4):382–91. [Google Scholar]

[pone.0278438.ref075] 75.Raudsepp L, Päll P. The Relationship between Fundamental Motor Skills and Outside-School Physical Activity of Elementary School Children. Pediatr Exerc Sci. 2006. Nov 1;18:426–35. [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref076] 76.Famelia R, Tsuda E, Bakhtiar S, Goodway JD. Relationships Among Perceived and Actual Motor Skill Competence and Physical Activity in Indonesian Preschoolers. J Mot Learn Dev. 2018. Oct 1;6(s2):S403–23. [Google Scholar]

[pone.0278438.ref077] 77.Barnett LM, Morgan PJ, Van Beurden E, Ball K, Lubans DR. A Reverse Pathway? Actual and Perceived Skill Proficiency and Physical Activity: Med Sci Sports Exerc. 2011. May;43(5):898–904. [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref078] 78.Cohen KE, Morgan PJ, Plotnikoff RC, Callister R, Lubans DR. Fundamental movement skills and physical activity among children living in low-income communities: a cross-sectional study. Int J Behav Nutr Phys Act. 2014;11(1):49. doi: 10.1186/1479-5868-11-49 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0278438.ref079] 79.Bezerra TA, Bandeira PFR, de Souza Filho AN, Clark CCT, Mota JAPS, Duncan MJ, et al. A Network Perspective on the Relationship Between Moderate to Vigorous Physical Activity and Fundamental Motor Skills in Early Childhood. J Phys Act Health. 2021. Jul 1;18(7):774–81. doi: 10.1123/jpah.2020-0218 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref080] 80.Lopes VP, Malina RM, Maia JAR, Rodrigues LP. Body mass index and motor coordination: Non-linear relationships in children 6–10 years. Child Care Health Dev. 2018. May;44(3):443–51. doi: 10.1111/cch.12557 [DOI] [PubMed] [Google Scholar]

[pone.0278438.ref081] 81.Fechner PY. The biology of puberty: New developments in sex differences. In: Gender Differences at Puberty. p. 17–28. [Google Scholar]

PERMALINK

The relationships between children’s motor competence, physical activity, perceived motor competence, physical fitness and weight status in relation to age

Anne R den Uil

Mirka Janssen

Vincent Busch

Ilse T Kat

Ron H J Scholte

Roles

Abstract

Introduction

Materials and methods

Design and setting

Participants

Table 1. Descriptive statistics of the study sample.

Instruments

Motor skill competence

Perceived motor competence

Physical activity

Health-related physical fitness

Weight status

Procedures

Data analyses

Results

Table 2. Summary of the correlation analysis per age group.

Fig 1. Overview of the correlation coefficients of the different relationships in all age groups.

Table 3. Overview of the tipping points in the associations.

Fig 2. The summary of the investigated age-dependent interrelations in model form.

Discussion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Ender Senel

Roles

Author response to Decision Letter 0

Decision Letter 1

Ender Senel

Roles

Acceptance letter

Ender Senel

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases