Adolescents’ Flexibility Can Affect Motor Competence: The Pathway from Health Related Physical Fitness to Motor Competence

Abstract

Motor competence has been shown to predict health-related physical fitness (HRPF) components in youth, but there is indeterminate evidence for the reverse path. Even less is known about the specific relationship between motor competence and flexibility. Our aims in this study were to analyze the relationship between flexibility and motor competence among adolescents; and, secondarily, to examine the relationships between motor competence and other HRPF components (body composition and musculoskeletal fitness). We conducted a longitudinal study (14-months follow-up) with two measurement points of 128 participants (55.5% girls; 45% boys) aged 12–13 years at baseline. We assessed HRPF components at the first time point and determined motor competence at the second time point. We assessed HRPF in terms of body composition (body fat percentage), musculoskeletal fitness (sit-up test), and flexibility (sit and reach). We determined motor competence using the Körperkoordinationstest für Kinder (KTK). We employed multivariate analyses of variance (MANOVA) to examine the effect of HRPF on motor competence through three models, in which each HRPF component was considered an independent variable. Sex, age, physical activity, and body mass index (BMI) z-scores were considered confounders. In our crude models all HRPF components significantly affected motor competence. In adjusted models, flexibility (p = .002) and body composition (p < .001) significantly affected motor competence. Overall, these results supported the assumptions that HRPF components are related to motor competence in adolescence, and that flexibility can affect motor competence in young people.

Keywords

flexibility motor skills adolescents fitness body fat

Introduction

Motor competence is a global term encompassing all forms of goal-directed tasks involving coordination and control of the human body (Cattuzzo et al., 2016; Robinson et al., 2015). Motor competence refers to the proficiency with which people perform a wide variety of motor tasks, including those in active play, physical education classes, and sport activities (Chagas & Marinho, 2021). In particular, the acquisition of adequate motor competence is considered a key factor in young people’s general development (D'Hondt et al., 2013; Gallahue et al., 2012). Also, children’s motor competence levels have been associated with health related markers (Chagas & Batista, 2017), including physical fitness.

In turn, physical fitness is a state of being that reflects a person’s ability to perform specific exercises and function (Pate et al., 2012). Physical fitness is considered a powerful health marker in childhood and adolescence (Ortega et al., 2008), because some fitness components have been related to health outcomes (Corbin et al., 2008; Ortega et al., 2008; Pate et al., 2012). For instance, cardiorespiratory and musculoskeletal fitness, as well as body composition, have been associated with cardiovascular risk profiles in youth (Ortega et al., 2008), whereas trunk flexibility has seemed to be related to lumbar health (Kemmochi et al., 2018). Therefore, health related physical fitness (HRPF) is comprised of body composition, cardiorespiratory fitness, musculoskeletal fitness and flexibility.

Body composition refers to the relative percentage of fat, muscle, bone and other tissues that comprise the body (Corbin et al., 2008). Musculoskeletal fitness is a multidimensional construct comprising the integrated function of muscle strength, muscle endurance, and muscle power (Pate et al., 2012). Flexibility refers to the amount of motion that is possible at a given joint or series of joints (Corbin et al., 2008). Of note, flexibility depends on the intrinsic property of body tissues as connective tissues and muscle elasticity, but its definition refers to the joints and not just muscles (Pate et al., 2012). Overall, emerging evidence has shown that, in addition to its association with health outcomes, HRPF is considered a correlate of motor competence in young people (Barnett et al., 2016).

Systematic reviews on associations between HRPF and motor competence in young people found evidence supporting a negative association between body fatness and motor competence (Cattuzzo et al., 2016; Lubans et al., 2010) and a positive association between motor competence and both cardiorespiratory fitness (Cattuzzo et al., 2016; Lubans et al., 2010; Utesch et al., 2019) and musculoskeletal fitness (Cattuzzo et al., 2016; Utesch et al., 2019). Prior reviews found the relationship between motor competence and flexibility uncertain (Cattuzzo et al., 2016; Lubans et al., 2010; Utesch et al., 2019). Lopes et al. (2017) argued that the rationale for the proposed relationship between flexibility and motor competence is that range of motion is important to motor competence because it permits movement with appropriate degrees of displacement. Thus, understanding how flexibility and motor competence relate over time is a pathway to understanding causal mechanisms and determining whether there is a predictive relationship between these variables in young people.

These prior reviews summarized a limited number of longitudinal studies analyzing the relationship between flexibility and motor competence in young people (Cattuzzo et al., 2016; Utesch et al., 2019), leaving largely unknown how motor competence and HRPF relate over time. In a systematic review by Barnett et al. (2021) on longitudinal and experimental evidence published from 2014, there was strong evidence of a positive effect of motor competence on HRPF, but there was indeterminate evidence for the reverse effect. For specific skill domains, there were strong positive relationships for locomotor/coordination skills in both directions. There was strong evidence that locomotor/coordination predicted muscular strength/endurance and some evidence that motor competence predicted cardiovascular endurance. When considering the pathway from fitness to motor competence, there was mixed evidence for effects of muscular strength/endurance on motor competence and strong evidence in both directions for a negative association between motor competence and weight status. Considering flexibility specifically in the path from fitness to motor competence, flexibility was assessed by the sit and reach task in two studies. Among 8-year-old Portuguese girls, flexibility predicted motor coordination for hopping, jumping sideways, and moving sideways. However, this prediction did not hold for six and 7-year old girls on the same three skill tests or on walking backwards (Antunes et al., 2016). Among Belgian children aged 8 years, flexibility did not predict motor coordination two years later (Coppens et al., 2019). In the other direction (i.e., motor competence to fitness), Fransen et al. (2014) reported that Belgian children aged 6 and 8 years old who were more coordinated were also more flexible over a 2-year period than those with lower coordination. Given that available findings regarding the associations between motor competence and flexibility are limited and inconclusive (Lopes et al., 2017), this topic warrants further investigation.

Adolescence is a critical period in which to study the relationship between flexibility and motor competence, because flexibility becomes more variable in adolescence than at earlier ages, and some individuals lose a significant degree of mobility across joints (Haywood & Getchell, 2014). To date, however, there has been no longitudinal research regarding the relationship between motor competence and flexibility in adolescents. While theory suggests that this relationship strengthens over development (Stodden et al., 2008), prior research evidence for the pathway from flexibility fitness to motor competence is mixed. In this context, we aimed to analyze this relationship in adolescents while also examining the relationships between motor competence and other HRPF components (body composition and musculoskeletal fitness).

Method

Participants

This was a 14-month follow-up study with two measurement time points. We recruited a convenience sample of 128 adolescents (71 girls, 57 boys) aged 12–13 years (M age =13.7, SD =0.6) from a middle school. All students were from seventh and eighth grades at baseline (and eighth and ninth, respectively, at follow-up). Those who met our selection criteria (i.e., no history of injury or disease that could affect motor performance) were included in the analysis. Participants were assessed at baseline (first time point) and 14 months later (second time point). All measurements were performed during the school year in the school gymnasium, by a single assessor, following standard measurement procedures for anthropometry, physical fitness and motor competence. Measurement procedures included fully explaining tasks and familiarizing participants with them. Participant attrition from baseline to follow-up was 41%, meaning that analyses were based on 53 participants. This large attrition was due to some students’ school drop-out. Descriptive statistics, including demographic characteristics at baseline, are provided in Table 1. We obtained advanced ethical approval for this research protocol from a human participants review committee, and we obtained parental consent and child assent from all participants prior to engaging them in research.

Table 1.

Participant Characteristics. Means (Standard Deviations) and Confidence Intervals of All Variables Assessed at First Time Point.

	Boys (n = 57)	Girls (n = 71)
Age (years)	13.8 (.6)	13.8 (.7)
Age (years)	CI: 13.6–13.9	CI: 13.7–14.0
Body weight (kg)	49.1 (11.8)	54.5 (15.1)
Body weight (kg)	CI: 45.0–52.3	CI: 50.9–58.1
Height (m)	1.61 (.1)	1.59 (.01)
Height (m)	CI: 1.58–1.62	CI: 1.57–1.62
BMI (z-scores)	−0.37 (.7)	0.20 (1.1)
BMI (z-scores)	CI: −.56 to −.18	CI: −.06–.46
Physical activity (PAQ-C scores)	3.0 (.1)	2.3 (.7)
Physical activity (PAQ-C scores)	CI: 2.8–3.2	CI: 2.1–2.4
Body fat (%)	16.1 (6.9)	28.0 (10.6)
Body fat (%)	CI: 14.2–17.9	CI: 25.5–30.5
Flexibility (cm)	19.8 (9.2)	24.2 (8.1)
Flexibility (cm)	CI: 17.3–22.2	CI: 22.2–26.1
MS fitness (sit-up test scores)	33.5 (8.9)	20.8 (9.6)
MS fitness (sit-up test scores)	CI: 31.1–35.9	CI: 17.8–22.3

‘CI’ is confidence interval; ‘MS’ is musculoskeletal.

Procedure

Anthropometric characteristics were assessed at the first time point and included body weight, stature and skinfold thickness. Body mass was measured to the nearest 0.1 kg using an electronic scale, with participants wearing their school uniform. Stature was measured while unshod with a stadiometer to the nearest 0.1 cm. We then calculated body mass index (BMI; kg/m²). We measured triceps and gastrocnemius skinfold thickness twice, using a skin caliper (Cescorf®), and we converted the mean values for each skinfold to a body fat percentage using the Slaughter equation (Slaughter et al., 1988).

We assessed all HRPF components at this first time point, including body composition (in terms of body fat), musculoskeletal fitness (sit-up) and flexibility (sit and reach). Body composition (body fat percentage) was assessed using anthropometric characteristics (triceps and gastrocnemius skinfold thickness) and the Slaughter equation (Slaughter et al., 1988). We applied the sit-up test in accordance with the ‘Projeto Esporte Brasil’ manual (Gaya & Gaya, 2016). Initially, the participant was in the supine position, knees at 90°, arms crossed over the chest, and feet held at the sole by the appraiser. With the verbal command to start, the chronometer was triggered and the participant flexed their trunk until they could touch the thighs with the elbows. Then the participant returned to the initial position. For each correct execution, we assigned a score of one. The movements were repeated as many times as possible within 60 seconds. Flexibility (sit and reach) was assessed using a wooden box with 30 cm for each side and an overhang of 23 cm on the superior face (Council of Europe fit, 1988). A tape measure of 53 cm was centrally placed on the testing box, with 0 cm positioned at the end of the overhang. Participants, unshod, sat on the floor with knees extended and the sole of the feet placed against the wooden box, under its overhang, with their toes coinciding with the 23th cm of the tape measure. The test consisted of trials to reach as far forward as possible on the tape measure, with one hand on top of the other and with the appraiser holding the legs of the participant to keep their knees extended. After two trials, we recorded the longest reach score.

We assessed motor competence at the second time point using a reliable and valid instrument: the Körperkoordinationstest für Kinder (KTK; Kiphard & Shilling, 2007). It consists of four tests: (a) walking backwards; (b) hopping; (c) jumping sideways; and (d) moving sideways. The item scores of each test were transformed into motor quotients using norm scores/conversion tables (Kiphard & Shilling, 2007). The first test was walking backwards on balance beams (3 m length) of decreasing width (6, 4.5, and 3 cm). Each beam was crossed three times where we allowed a maximum of eight steps per trial (72 steps overall); the sum of steps in all trials determined Motor Quotient 1. The second test involved one-legged hopping over an obstacle, formed with an increasing pile of pillows (pillow size 60 cm × 20 cm × 5 cm; the maximum was 12 pillows or a height of 60 cm). Only three trials were allowed for each obstacle and three, two, or one point(s) were/was awarded for successful performance on the first, second, or third try, respectively. Therefore, a maximum of 39 points (including a ground level trial) could be scored for each leg; the scores were summed to determine Motor Quotient 2. The third task was two-legged sideways jumping across a wooden slat (60 cm × 4 cm × 2 cm), positioned in the middle of an area (60 cm x 100 cm), for 15 seconds as quickly as possible, where participant should: land inside area, with both feet simultaneously, without touching wooden slat while jumping. The number of jumps performed correctly was summed over two trials to determine Motor Quotient 3. The final task involved moving sideways on wooden boards (25 cm × 25 cm × 5.7 cm) as many times as possible in 20s. One point was awarded for each time the plate was transferred and one more for stepping on it. The number of relocations was counted and summed over two trials to determine Motor Quotient 4.

Physical activity has been shown to be associated with motor competence (Barnett et al., 2016) and with HRPF (Júdice et al., 2017) in youth. Thus, physical activity is a potential confounder in this relationship. As such, we assessed physical activity level through a translated and cross-culturally adapted (Chagas et al., 2020) version of the Physical Activity Questionnaire for Older Children (PAQ-C; Kowalski et al., 2004) into the language of the participants. The PAQ-C has good internal consistency, Cronbach’s α = .85–.87; and good test-retest reliability, with an Intra-class Correlation Coefficient (ICC) of .90. It is a self-administered 7-days recall instrument, appropriate for middle school aged children approximately between 8–14 years old who are currently in the school system and have recess as a regular part of their school week. The summary score from the PAQ-C is the average of the sum of the nine item questions, each scored on a 5-point scale.

Statistical Analyses

We determined descriptive statistics for all measurements, considering the HRPF components (flexibility, musculoskeletal fitness and body composition) assessed at baseline as independent variables and motor competence level, assessed at follow-up, as a combined dependent variable, comprised of “walking backwards,” “hopping,” “jumping sideways,” and “moving sideways” skills. We used multivariate analysis of variance (MANOVA) to examine the relationship between HRPF and motor competence. For this, we constructed three main models in which we separately considered each HRPF component as the independent variable: flexibility (model 1), musculoskeletal fitness (model 2) and body composition (model 3). All models were analyzed without adjustments (crude models) and with adjustments for potential confounders (i.e., sex, age, physical activity and BMI z-scores). We determined eta partial squared $(η 2$ ) as measures of effect size across all models, considering the following cutoff points: .01 (small), .06 (medium) and .14 (large) (Cohen, 1988). We used independent t-tests to compare differences in flexibility, musculoskeletal fitness, body composition, physical activity levels and motor competence between boys and girls. We determined Cohen’s d measures of effect size across t-tests, considering the following cutoff points: .2 (small), .5 (medium) and .8 (large). All data analyses were executed using the Statistical Package for the Social Sciences (SPSS, version 22, IBM Corp.).

Results

Descriptive statistics for participants’ age, body weight, stature, physical activity, body fat percentage, flexibility, musculoskeletal fitness and motor competence assessed at baseline are presented in Table 1. As shown, at baseline, girls showed higher flexibility (t (126) = 2.867, p =.005), higher body fat percentage (t (126) = 7.352, p <.001), lower sit-up scores (t (126) = −8.128, p <.001) and lower physical activity levels (t (126) = −5.978, p <.001) than boys. The effect size across these comparisons was Cohen’s d= .44 (small to medium). At follow-up, girls presented lower motor competence skills (walking backwards: t (43) = −3.240, p =.002; hopping: t (43) = −4.485, p <.001; jumping sideways: t (43) = −6.741, p <.001; moving sideways: t (43)= −3.751, p =.001) than boys. The effect size across these comparisons was Cohen’s d = .76 (medium to large). Motor competence levels of boys and girls are shown in Figure 1.

Figure 1.

Performances on KTK Tasks by Sex with Boys Outperforming Girls on All Motor Tasks. Note: Walking backwards: t = 3.240, p=.002; hopping: t = 4.485, p < .001; jumping sideways: t = 6.741, p < .001; moving sideways: t = 3.751, p = .001; Cohen’s d = .76 (medium to large).

In all crude models, there was a significant effect of flexibility (Pillai’s trace = .267, F = 3.646, p < .001), musculoskeletal fitness (Pillai’s trace = .477, F = 9.121, p < .001) and body fat percentage (Pillai’s trace = .633, F = 17.284, p < .001) on motor competence. When adjusted for potential confounders (sex, age, physical activity and BMI z-scores), the MANOVA showed a positive effect of flexibility on motor competence (Pillai’s trace = .363, F = 5.130, p = .002). In Model 2, however, there was no significant effect of musculoskeletal fitness on motor competence after adjusting for potential confounders (Pillai’s trace = .174, F = 1.897, p = .132). In Model 3, the MANOVA indicated a negative effect of body fat percentage on motor competence, even after adjusting for potential confounders (Pillai’s trace = .569, F = 12.205, p < .001). The multivariate analysis with flexibility (Model 1), musculoskeletal fitness (Model 2) and body fat percentage (Model 3) as the independent variables are shown in Tables 2 to 4, respectively.

Table 2.

Model 1: Multivariate Analysis with Flexibility as the Independent Variable and Motor Competence as a Combined Dependent Variable (Encompassing “Walking Backwards,” “Hopping,” “Jumping Sideways,” and “Moving Sideways” Scores) with and without Confounder Adjustments (Age, Sex, Physical Activity and BMI Z-Scores).

	Crude Model
Dependent Variable	Parameter	B	p-value	$η 2$
Walking backwards	Intercept	94.883	<.001	.745
Walking backwards	Sit-and-reach	.214	.585	.007
Hopping	Intercept	69.123	<.001	.356
Hopping	Sit-and-reach	.945	.154	.047
Jumping sideways	Intercept	80.962	<.001	.562
Jumping sideways	Sit-and-reach	.681	.181	.041
Moving sideways	Intercept	79.415	<.001	.671
Moving sideways	Sit-and-reach	1.160	.005	.171
Adjusted model
Walking backwards	Intercept	95.449	.128	.058
	Sit-and-reach	.155	.620	.006
	Age	−.479	.919	.000
	BMI (z-scores)	−10.200	.000	.307
	Physical activity	.645	.865	.001
	Sex	9.959	.120	.061
Hopping	Intercept	.890	.992	.000
	Sit-and-reach	.992	.026	.120
	Age	4.762	.465	.014
	BMI (z-scores)	−17.248	.000	.398
	Physical activity	−4.163	.428	.016
	Sex	31.918	.001	.258
Jumping sideways	Intercept	27.552	.670	.005
	Sit-and-reach	.820	.016	.140
	Age	1.674	.734	.003
	BMI (z-scores)	−5.123	.053	.093
	Physical activity	6.039	.133	.057
	Sex	27.829	.000	.317
Moving sideways	Intercept	33.360	.566	.008
	Sit-and-reach	1.187	.000	.297
	Age	2.616	.555	.009
	BMI (z-scores)	−8.118	.001	.241
	Physical activity	1.120	.753	.003
	Sex	16.619	.007	.170

B is an unstandardized coefficient for dependent variable. $η 2$ is partial eta squared effect size.

Table 3.

Model 2: Multivariate Analysis with Musculoskeletal Fitness as the Independent Variable and Motor Competence as a Combined Dependent Variable (Encompassing “Walking Backwards,” “Hopping,” “Jumping Sideways,” and “Moving Sideways” Scores) with and without Confounder Adjustments (Age, Sex, Physical Activity and BMI Z-Scores).

	Crude Model
Dependent Variable	Parameter	B	p-value	$η 2$
Walking backwards	Intercept	82.060	<.001	.843
Walking backwards	Sit-up	.691	.001	.232
Hopping	Intercept	54.896	<.001	.476
Hopping	Sit-up	1.349	<.001	.303
Jumping sideways	Intercept	63.990	<.001	.723
Jumping sideways	Sit-up	1.241	<.001	.437
Moving sideways	Intercept	77.675	<.001	.843
Moving sideways	Sit-up	1.025	<.001	.425
Adjusted model
Walking backwards	Intercept	101.117	.105	.066
	Sit-up	.084	.734	.003
	Age	−.799	.866	.001
	BMI (z-scores)	−9.943	.001	.251
	Physical activity	.789	.834	.001
	Sex	8.334	.222	.038
Hopping	Intercept	29.606	.743	.003
	Sit-up	.081	.822	.001
	Age	3.804	.586	.008
	BMI (z-scores)	−17.999	<.001	.337
	Physical activity	−2.499	.653	.005
	Sex	26.642	.010	.157
Jumping sideways	Intercept	58.247	.382	.020
	Sit-up	.489	.071	.081
	Age	−.127	.980	>.001
	BMI (z-scores)	−3.516	.243	.035
	Physical activity	6.717	.105	.066
	Sex	18.715	.014	.146
Moving sideways	Intercept	76.106	.240	.035
	Sit-up	.606	.023	.126
	Age	.254	.959	>.001
	BMI (z-scores)	−6.330	.034	.110
	Physical activity	2.270	.566	.009
	Sex	4.575	.519	.011

B is an unstandardized coefficient for dependent variable. $η 2$ is partial eta squared effect size.

Table 4.

Model 3: Multivariate Analysis with Body Fat Percentage as the Independent Variable and Motor Competence as a Combined Dependent Variable (Encompassing “Walking Backwards,” “Hopping,” “Jumping Sideways,” and “Moving Sideways” Scores) with and without Confounder Adjustments (Age, Sex, Physical Activity and BMI Z-Scores).

	Crude Model
Dependent Variable	Parameter	B	p-value	$η 2$
Walking backwards	Intercept	122.928	<.001	.930
Walking backwards	% Body fat	−1.050	<.001	.378
Hopping	Intercept	135.793	<.001	.877
Hopping	% Body fat	−2.100	<.001	.518
Jumping sideways	Intercept	125.857	<.001	.890
Jumping sideways	% Body fat	−1.374	<.001	.377
Moving sideways	Intercept	134.124	<.001	.946
Moving sideways	% Body fat	−1.373	<.001	.537
Adjusted model
Walking backwards	Intercept	102.867	.129	.058
	% Body fat	−.059	.906	>.001
	Age	−.706	.883	.001
	BMI (z-scores)	−9.858	.059	.089
	Physical activity	.853	.823	.001
	Sex	8.978	.183	.045
Hopping	Intercept	59.261	.544	.010
	% Body fat	−.586	.425	.016
	Age	2.937	.675	.005
	BMI (z-scores)	−13.210	.081	.076
	Physical activity	−3.098	.577	.008
	Sex	24.608	.015	.143
Jumping sideways	Intercept	89.339	.228	.037
	% Body fat	−.740	.185	.045
	Age	−.299	.955	>.001
	BMI (z-scores)	.494	.930	>.001
	Physical activity	6.599	.121	.061
	Sex	20.498	.008	.169
Moving sideways	Intercept	157.019	.020	.132
	% Body fat	−1.717	.001	.244
	Age	−1.410	.763	.002
	BMI (z-scores)	5.775	.248	.034
	Physical activity	1.121	.762	.002
	Sex	2.749	.672	.005

B is an unstandardized coefficient for dependent variable. $η 2$ is partial eta squared effect size.

Discussion

Our main aim in this longitudinal study was to analyze the relationship between flexibility and motor competence in adolescents. We found that flexibility had a positive effect on motor competence, even after adjusting for potential confounders. In addition, we assessed the relationships between other HRPF components (i.e., body composition and musculoskeletal fitness and motor competence and found that, in crude models, both musculoskeletal fitness and body fat percentage significantly affected motor competence. However, only body fat remained significant after adjusting for potential confounders. Collectively, our results supported the assumption that HRPF components matter for motor competence in adolescence; and, more specifically, flexibility can affect motor competence in young people. (Table 5).

Table 5.

Correlation Matrix (Pearson’s r) with motor Competence (KTK Scores), Body Composition (% Body Fat), Flexibility (Sit and Reach) and Musculoskeletal Fitness (Sit-Up).

	1	2	3	4	5	6	7
(1) Walking backwards	—	.745 p < .001	.683 p < .001	.665 p < .001	−.615 p < .001	.084 p = .585	.482 p = .001
(2) Hopping	.745 p < .001	—	.783 p < .001	.711 p < .001	−.719 p < .001	.216 p = .154	.550 p < .001
(3) Jumping sideways	.683 p < .001	.783 p < .001	—	.808 p < .001	−.614 p < .001	.203 p = .181	.661 p < .001
(4) moving sideways	.665 p < .001	.711 p < .001	.808 p < .001	—	−.733 p < .001	.414 p = .005	.652 p < .001
(5) % body fat	−.615 p < .001	−.719 p < .001	−.614 p < .001	−.733 p < .001	—	−.015 p = .870	−.646 p < .001
(6) sit-and-reach	.084 p = .585	.216 p = .154	.203 p = .181	.414 p = .005	−.015 p = .870	—	.111 p = .213
(7) sit-up	.482 p = .001	.550 p < .001	.661 p < .001	.652 p < .001	−.646 p < .001	.111 p = .213	—

In line with these findings, in a systematic review that included cross-sectional, longitudinal, experimental and quasi-experimental studies published until 2013, Cattuzzo et al. (2016) found strong evidence for an inverse association between motor competence and weight status in children and adolescents. When considering the pathway from weight status to motor competence, Barnett et al.’s (2021) review of longitudinal and experimental evidence published from 2014 confirmed that there was strong positive evidence that weight status affected motor competence across childhood; yet longitudinal evidence of this finding among adolescents is scarce. In this regard, Chagas et al. (2021) found that motor competence and weight status were related among adolescents, but those authors examined body fat as the outcome. Therefore, our study adds to the literature by providing longitudinal evidence that body fat has a negative effect on motor competence among adolescents with a large effect size - even after adjusting for confounders. The inverse relationship between body fat and motor competence was expected because the higher the amount of body mass of individuals, the more mechanical work is required to perform motor tasks, especially those which demand weight-bearing (Chagas & Batista, 2019), like locomotor skills. Indeed, our investigation showed that body fat percentage had an inverse relationship with combined locomotor/coordination/stability skills (i.e., “walking backwards,” “hopping,” “moving sideways” and “jumping sideways”) that denoted motor competence. Overall, our longitudinal evidence for the relationship between body fat and motor competence in adolescents is consistent with the model proposed by Stodden et al. (2008), in which it is assumed that increased body fat levels will result in lower motor competence across childhood and adolescence.

With respect to musculoskeletal fitness, Barnett et al.’s (2021) review found mixed evidence for muscular strength/endurance predicting motor competence across childhood. Considering curl-up/sit-up specifically, prior longitudinal research (Antunes et al., 2016) reported that sit-ups predicted jumping sideways for boys. However, in that study, sit-ups did not predict hopping, moving sideways or walking backwards. In addition, one longitudinal study found that curl-ups did not predict motor competence in children (Dos Santos et al., 2018). On one hand, we might expect young people who are physically fit later in childhood and adolescence to be more likely to maintain physical activity for longer periods of time with an associated increase in their motor competence (Stodden et al., 2008). On the other hand, the pathway from fitness to motor competence was considered undetermined in the most recent review on this topic (Barnett et al., 2021). While 59% of associations assessed in the included studies show a positive effect from fitness to motor competence, this was previously classified as indeterminate because <60% had been the cut off for that interpretation. Barnett et al., 2021 had removed studies with large numbers of multiple comparisons from the final summary totals, as these large studies might have biased the results. Delving deeper into results from that review, there was no evidence for the pathway from fitness to locomotor/coordination/stability skills (27/97, 28%) when all studies and all analyses were considered; but, when a study with multiple comparisons was removed, there was strong positive evidence (17/25, 68%). Our findings did not corroborate such evidence, as we found no significant effect of muscular strength/endurance on motor competence after adjusting for potential confounders. Perhaps muscular strength/endurance is linked to selected motor skills, such that there is an association with those that require core stability or explosive strength, but none when considering motor competence as a combined variable encompassing different movement skills, as we did in this investigation.

With respect to flexibility, Utesch et al. (2019) found limited previous research in this area in their review. Nevertheless, cross-sectional studies (Behan et al., 2022; Lopes et al., 2017) and longitudinal studies (Fransen et al., 2014) are in line with our results, in that they found flexibility to be associated with motor competence in young people. One cross-sectional study found that young people aged 6–14 years with limited flexibility were more likely to have more gross motor coordination problems (Chaves et al., 2016). Concerning the path from fitness to motor competence, previous longitudinal findings are contradictory. Antunes et al. (2016) found that the sit and reach test at 8-years was a predictor of jumping sideways, moving sideways and hopping for 14-year-old girls, but not for boys. Coppens et al. (2019) found that flexibility in 8-year-old children did not predict motor competence two years later.

To our knowledge, ours was the first longitudinal research to analyze and affirm the significant effect of flexibility on motor competence among adolescents. Our large effect size results can be explained by the idea that individuals need adequate joint mobility to perform motor tasks with an appropriate range of motion. For instance, motor tasks involving trunk flexion like “moving sideways” in the KTK test require a certain degree of flexibility in the lower back. Thus, low levels of flexibility across the lower back structure can hamper motor performance on that task. Conversely, adequate levels of flexibility permit freedom of movement and contribute to ease and economy of muscular effort (Corbin et al., 2008). In addition, theory suggests that the association between motor competence and HRPF among young people strengthens over development (Stodden et al., 2008), although this is yet to be tested empirically. Given that we recruited adolescents into our longitudinal study, we would expect them to show a positive relationship between flexibility and motor competence over time. Future studies may wish to test the hypothesis that the strength of association will increase over development. In the aforementioned review (Barnett et al., 2021), each study had different start and end points and used different measurement constructs for fitness and motor skill competence, prohibiting the reviewers from drawing this conclusion.

Considering the undetermined evidence for an association between motor competence and flexibility indicated by previous reviews (Cattuzzo et al., 2016; Lubans et al., 2010; Utesch et al., 2019) and the paucity of follow-up studies addressing this relationship (Barnett et al., 2021), our research adds to the literature by providing longitudinal data of relevance to this topic. Understanding this relationship in young people is a necessity, especially considering the high prevalence of adolescents with low levels of flexibility. In Brazil, it is estimated that 50% of youth are in a health risk zone when considering flexibility (Pedretti et al., 2020). It is hard, though, to determine health-related criterion-referenced cut-points for muscular skeletal fitness for young people. A recent review (Fraser et al., 2021) endeavored to do this, but, due to the variation in the discriminatory ability of different musculoskeletal tests, the authors could not establish universal health-related cut-points. Handgrip strength and the standing broad jump were identified with the highest discriminatory ability, whereas only two studies examined flexibility. Nevertheless, besides the potential health-related issues, low levels of flexibility can negatively affect motor development, given that this HRPF component had an effect on motor competence in our investigation. Therefore, it seems plausible to recommend stretching exercises as part of structured programs whose aim is the development of motor competence in early adolescence. In addition, we should encourage young people to engage in physical education classes, sports and other structured and unstructured activities that can improve the levels of flexibility and other HRPF components as a strategy to develop their motor competence.

Limitations and Directions for Further Research

In short, while strengths of this study were its rare use of a longitudinal design and the focus on the adolescent developmental period, its weaknesses included our dependence on convenience sampling and significant participant attrition from initial testing to follow-up, due to some students’ school drop-out and logistic issues that interfered with follow-up assessment. Another issue is that the pubertal growth spurt begins on average at 9–10 years for girls and 11–12 years for boys (Soliman et al., 2014). Then, while 12–13 years corresponded to a mid-pubertal growth spurt in females, male adolescents of these ages were at the beginning of their growth spurt. Although there is considerable variation between individuals and populations in maturation (Soliman et al., 2014), a larger sample might have permitted us to analyze the data by sex. In addition, lack of control for maturational differences could also be considered a weakness, although maturation was not a predictor in any of the studies conducted as part of “The Michigan State University Motor Performance Study” (Barnett & Ulrich, 2021). We acknowledge that other studies have reported biological maturity to be an important consideration when studying motor and fitness performance during youth (Drenowatz & Greier, 2019). Finally, we only assessed motor competence at follow-up; and, as such, we could only assess a single path (i.e., from HRPF) to motor competence. Nevertheless, our multivariate approach provides new information on a little known area in the literature. Future researchers should address the weaknesses of this study; and, as noted, might address whether the relationship between flexibility and motor competence strengthens over development.

Conclusions

This investigation addressed the interrelationship between HRPF and motor competence across adolescence, considering motor competence as a combined variable encompassing different movement skills. Overall, our results supported the assumption that HRPF components matter for motor competence in adolescence. Besides being important health markers, body composition and flexibility can exert an effect on motor competence over time, even after adjusting for potential confounders. Therefore, the development of these HRPF components should be encouraged in adolescents with the aim to foster motor competence.

Footnotes

Acknowledgments

We would like to thank Maria Carolina Joia for her collaboration.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Approval

CAAE: 35534514.5.0000.5259

ORCID iD

Daniel das Virgens Chagas

Author Biographies

Daniel das Virgens Chagas is an Associate Professor of the Institute of Physical Education and Sports and Permanent Advisor in the Graduate Program of Physical Exercise and Sport Sciences at Rio de Janeiro State University (UERJ), Brazil. His research focuses on motor competence, behavioral and health outcomes across childhood and adolescence.

Lisa Barnett is a full Professor and senior member of the Institute for Physical Activity and Nutrition at Deakin University (Australia). She is President of the International Motor Development Research Consortium (https://www.i-mdrc.com). She is internationally recognized in the assessment of children's actual and perceived movement skill competency and for her research into how movement skills relate to health behaviours.

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