ArticlePDF Available

Relationship between body composition and vertical jump performance in young Spanish soccer players

Authors:
Pérez-López A, Sinovas MC, Álvarez-Valverde I, and Valades D. Relationship between body
composition and vertical jump performance in young Spanish soccer players.
J Sport Human Perf 2015; 3(3):1-12.
DOI: 10.12922/jshp.0063.2015
1
RELATIONSHIP BETWEEN BODY COMPOSITION
AND VERTICAL JUMP PERFORMANCE IN YOUNG
SPANISH SOCCER PLAYERS
Pérez-López A, Sinovas MC, Álvarez-Valverde I, and Valades D
Faculty of Medicine and Health Sciences, University of Alcalá, Madrid, Spain
Keywords: jump ability, body size, children and adolescents
INTRODUCTION
The development of motor skills in
pre-adolescence and adolescence is affected
by a wide variety of factors, one of which is
training (26). Jump ability is a motor skill that
depends on muscle contractile capacity,
stretch-shortening cycle (SCC), and high
power production (6, 15).
In childhood and adolescence, lower
levels of vertical jump performance have been
found to be a predictor of inactivity (14).
Thus, jump ability (both vertical and long
jumps) is a common test in schools (7), but
jump tests have also been used in sport
performance. In soccer, the vertical jump has
been used to monitor performance (30), to
ORIGINAL RESEARCH OPEN ACCESS
ABSTRACT
The aim of this study was to examine the relative contribution of body composition to vertical jump
performance in young Spanish soccer players. Seven hundred and twenty-three soccer players aged
7 to 19 years (156 ± 17 cm; 47.8 ± 15.1 kg) who had prior soccer experience (≥ 3 yrs) and had
trained for ~2 h·day-1, 4 days·week-1 were selected. Anthropometric measurements were taken and
three vertical jumps were performed: squat jump (SJ); counter-movement jump (CMJ); counter-
movement jump with arm swing (CMJa). Multiple regression equations revealed that age (SJ, =
0.635; CMJ, = 0.687, CMJa, = 0.674) and fat mass (SJ, = -0.203; CMJ, = -0.215, CMJa, =
-0.196) in children and age (SJ, = 0.431; CMJ, = 0.496; CMJa, = 0.536), appendicular lean
body mass (SJ,  0.214; CMJ,  0.160) and waist circumference (SJ,  -0.187; CMJ, 
-0.119) in adolescents were the body composition variables that better explained vertical jump
height. Thus, in addition to age and fat mass for children, we observed for the first time that
appendicular lean body mass and waist circumference in adolescents could be taken into
consideration as body composition predictors to assess and improve vertical jump performance in
young soccer players.
2
J Sport Hum Perf
ISSN: 2326-6333
compare training loads (3, 17), and to prevent
injuries (23), though for young players, it has
been mainly utilized to identify talented
athletes (35, 39). Moreover, squat jump (SJ)
and counter-movement jump (CMJ) height
have been associated with performance
success in this sport (5, 12).
Nonetheless, the interpretation of
jump ability performance during childhood
and adolescence in educational or sport
performance environments is often based
simply on a chronological age assessment.
However, maturation status should be taken
into consideration (25) by taking into account
other biological or body composition
parameters (8).
Body size has been described as a
confounding variable in vertical jump
performance (22), and several studies have
attempted to categorize those body
composition variables which better explain
jump ability during childhood and
adolescence. Markovic and Jaric (20, 21)
identified six variables as jump predictors:
maturation, age, gender, race, physical
activity level, and motor skills. Further,
several studies have attempted to identify
novel body composition variables from a
variety of young populations: Serbians, aged
12 to 17 years (25); Norwegians, aged 7 to 11
years (13); French youth, aged 11 to 16 years
(38); and English youth, aged 10 to 15 years
(37). Finally, Aouichaoui et al. (4) found a
positive correlation between total fat free
mass (FFM) and vertical jump performance in
a Tunisian population between the ages of 7
and 13 years, supporting the body size
paradigm (22).
Therefore, the aims of this study were
first to quantify the relationship between body
composition variables and vertical jump
performance. Secondly, to establish reference
values for vertical jump in young Spanish
soccer players between the ages of 7 and 19
years. We hypothesized that the
anthropometric measurement of skeletal
muscle and/or appendicular lean body mass
could be predictors of vertical jump
performance in childhood and/or adolescence.
Furthermore, these variables would serve as
non-invasive measurements to take into
consideration when assessing vertical jump
performance of young soccer players.
METHODS
Seven hundred and twenty-three
Spanish males between 7 and 19 years of age
took part in the present study. The
participants had at least 3 years of prior
soccer experience and had trained for ~2
h·day-1, 4 days·week-1 (including a weekly
competition) in Madrid, Spain. Further, they
were familiarized with vertical jump tests,
and those without previous experience or who
were unable to properly perform any of the
required tests were excluded. No participants
had any previous history of metabolic disease,
and no participants were taking any type of
medication.
Participants were divided into the
following age groups, accordingly to age
categories of the Spanish young soccer
leagues: (A) under the age of 10 (n = 130),
(B) between the ages of 10 and 12 (n = 147),
(C) between the ages of 13 and 14 (n = 205),
(D) between the ages of 15 and 16 (n = 130),
(E) between the ages of 17 and 19 (n = 111).
Before agreeing to participate in the study,
prospective participants’ guardians were fully
informed of the procedure and any possible
discomforts associated with the study. They
then gave their written informed consent. The
study was in accordance with the University
of Alcala´s Ethics Committee and the latest
version of the Declaration of Helsinki.
3
J Sport Hum Perf
ISSN: 2326-6333
Participants were tested during their
regular training schedules (between 6 and 9
PM) in the preparation period of the season.
Environmental conditions were maintained
(20 ± 1 ºC; 56 ± 5 %), and participants were
encouraged not to eat or drink for 2 hours
before the study.
Body composition assessments
Anthropometry was the method used
to measure body composition. Standing
height was measured by a stadiometer to the
nearest 0.1 cm, and body mass was measured
on a digital scale with an accuracy of 0.1 kg
(Harpenden Portable Stadiometer, Holtain
Ltd, Crosswell, Crymych, Pembs, United
Kingdom). Skinfold thicknesses on the right
side of the body were measured to the nearest
0.2 mm using a Holtain Ltd skinfold caliper
(Crosswell, UK). All materials were
calibrated, and the same ISAK accredited
specialist took all measurements. In order to
assess the reliability of each measure,
technical error of measurement (TEM%) was
calculated for all skinfolds, triceps (1.1%),
subscapular (1.6%), biceps (2.0%), iliac crest
(1.9%), supraspinale (2.2%), abdominal
(2.1%), front thigh (2.3%), medial calf
(1.2%); and circumferences taken, relaxed
arm (0.3%), waist (0.3%), hips (0.4%), gluteal
(0.3%), and calf (0.6%).
Fat mass (FM) (R2 = 0.77) (31, 32,
34), appendicular lean body mass (corrected
muscle girth model) (ALBM) (R2 = 0.93)
(28), and skeletal muscle mass (SMM) (R2 =
0.97) (27) were obtained from previously
reported formulas.
Vertical Jump Tests
After anthropometric measurements, a
warm-up routine consisted of low-intensity
aerobic exercises (3 minutes), dynamic
stretching (5 minutes), and single and
rebound jumps (2 minutes) was completed.
Then, participants performed three protocols
of vertical jump tests with proven reliability
and validity (19): squat jump (SJ), counter-
movement jump (CMJ), and Abalakov test or
counter-movement jump with arm swing
(CMJa). Based on a pilot study performed
previously, two attempts were carried out for
each type of test, allowing 1 minute of rest
between attempts of the same test and 2
minutes between different vertical jump tests
to ensure total recovery.
The SJ is composed of a concentric
phase preceded by an isometric phase with
90º knee flexion. To prevent the use of elastic
energy, participants stayed in the isometric
phase for 3 seconds. Also, they kept their
hands on their hips to avoid arm swing
impulse when they were required to perform a
maximal jump (15). No sinking or
countermovement was allowed.
The CMJ is composed of an initial
negative or eccentric phase that finishes with
the subject in the squat position with 90º knee
flexion and is followed by an immediate
concentric or positive phase to perform a
maximal jump. Participants kept their hands
on their hips.
Finally, the CMJa consists of a CMJ
in which arm swing is permitted. All
participants performed the swing by
beginning with their arms extended in the
anatomical position. Any other arm swing
was not permitted.
All trials were video recorded to
ensure proper technique. Vertical jump
performances were collected by an infrared
photocell system called Optojump (Microgate
SRL, Bolzano, Italy) which was connected to
a portable computer with the adequate
software (Optojump software, version
3.01.0001) (11).
4
J Sport Hum Perf
ISSN: 2326-6333
Statistical Analysis
The SPSS statistical software package
(version 17.0) was used, and all results
obtained were presented as mean ± SD. The
Kolmogorov-Smirnov test was used to assess
the normality of the anthropometric and
vertical jump variables (p> 0.05). One-way
ANOVA was used to analyze the
comparisons between age groups and
Bonferroni was used as post hoc test.
Intraclass correlation coefficients (ICCs) were
also calculated to confirm the concordance of
the measurements.
Pearson correlation and partial
correlation controlling for age were used to
assess association between anthropometric
and vertical jump parameters (p< 0.01; p<
0.05). Subsequently, a linear regression
between vertical jump performance variables
and body composition (SMM, ALBM, and
FFM) was performed. Finally, three multiple
regressions were calculated to obtain the body
composition variables (p< 0.05) that predict
vertical jump height performances for
children, adolescents, and both.
RESULTS
Effects of categories on Anthropometric and
Vertical Jump variables
Mean and standard deviation data
from the anthropometric and vertical jump
variables were calculated and are presented in
Table 1. Children and adolescents showed
statistically significant differences for
demographic variables (age, height, and
weight) (p< 0.05) between all categories, as
well as for SMM, ALBM, and FFM (p<
0.01). Nevertheless, the FM variable was not
statistically different between groups A, B,
and C, but significant relationships were
found between these groups and the
remaining ones (D and E; p< 0.05). Also,
waist circumference (WC) showed a
progressive and significant increase between
categories A, B, C, and D, whereas no
significant differences were found between
categories D and E.
Finally, vertical jump repeatability
(ICC; 95% CI) was calculated for all
protocols: SJ (0.995, 0.994-0.996), CMJ
(0.994; 0.993-0.995), and CMJa (0.996;
0.995-0.997), and significant differences were
also found in all vertical jump tests among all
age groups (p< 0.001) (Table 1).
Associations between Anthropometric and
Vertical Jump variables
Relationship between the
anthropometric and vertical jump variables
was calculated through a Pearson correlation
coefficient (data not presented). Given that
Pearson correlation showed strong
correlations between anthropometric and
vertical variable measurements (p< 0.01), a
partial correlation was performed controlling
for age (Table 2). In partial correlation, a
reduction in all coefficients was detected
compared to Pearson’s correlation. Also, a
significant association between heights of the
three vertical jump tests and body
composition variables of height, weight, FM,
and FFM (p< 0.01) was observed. SMM,
ALBM, and waist circumference were also
significantly related, though this relationship
was less pronounced (p< 0.05).
Linear Regression model for Vertical Jump
Height
Figure 1 showed linear contribution of
the independent body composition variables
(SMM, ALBM, and FFM) to the vertical
jump tests (SJ height, CMJ height, and CMJa
height) of the whole cohort of participants. A
moderate to strong relationship (R2 = 0.44 to
0.61) between the SMM, ALBM, and FFM
and the vertical jump tests was observed,
though the FFM has the strongest relationship
with the tests when compared to the SMM
and ALBM.
5
J Sport Hum Perf
ISSN: 2326-6333
Table 1. Mean ± SD of anthropometric and vertical jump variables compared by category.
A
B
C
D
E
Total
(N = 130)
(N = 147)
(N = 205)
(N = 130)
(N = 111)
(N = 723)
Mean±SD
Sig.
Mean±SD
Sig.
Mean±SD
Sig.
Mean±SD
Sig.
Mean±SD
Mean±SD
Age (yr)
9.1 ±0.7
BCDE**
11.1 ±0.6
CDE**
12.9 ±0.6
DE**
15.1 ±0.7
E**
17.3 ±0.9
13.3 ±3.1
Height (cm)
130 ±7
BCDE**
144 ±7
CDE**
156 ±9
DE**
169 ±7
E**
174 ±7
156 ±17
Weight (kg)
31.2 ±6.1
BCDE**
37.1 ±6.4
CDE**
45.7 ±9.2
DE**
57 ±10
E**
66.0 ±7.6
47.7 ±15
BMI
17.3 ±2.3
CDE**
17.8 ±2.2
CDE**
18.5 ±2.5
DE**
19.9 ±2.3
E**
21.7 ±2.1
19 ±2.5
WC (cm)
64.3 ±8.5
CDE**B*
68.0 ±9
CDE***
72.6 ±11
DE**
78.1 ±11
80.8 ±10
72.8 ±11
%FM
17.3 ±6.4
E**D*
18.5 ±5.9
DE**
18.4 ±6.7
DE**
15.0 ±4.5
13.9 ±4.7
16.7 ±6.1
FM (kg)
5.7 ±3.2
CDE**B*
7.1 ±3.3
E**CD*
8.7 ±4.4
8.8 ±4.3
9.3 ±4.0
8.0 ±3.9
FFM (kg)
13.9 ±4.7
BCDE**
18.6 ±5.1
CDE**
27.2 ±8.6
DE**
42.0 ±8.7
E**
52.1 ±7.0
31 ±16
SMM (kg)
15.8 ±3.1
BCDE**
19.0 ±3.4
CDE**
22.9 ±6.6
DE**
28.3 ±4.9
E**
32.9 ±3.7
24 ±7.7
ALBM (kg)
14.4 ±2.8
BCDE**
17.1 ±3.0
CDE**
20.6 ±6.7
DE**
25.2 ±4.4
E**
29.2 ±3.4
21.5 ±7
SJ Height (cm)
17.0 ±2.6
BCDE**
19.5 ±3.1
CDE**
21.6 ±3.4
DE**
25.6 ±5.1
E**
31.0 ±3.7
22.9 ±6.0
CMJ Height (cm)
19.3 ±3.0
BCDE**
22.7 ±3.8
CDE**
25.0 ±3.8
DE**
29.8 ±4.9
E**
36.2 ±4.2
26.6 ±7.0
CMJa Height (cm)
22.5 ±3.7
BCDE**
27.0 ±4.6
CDE**
29.6 ±4.9
DE**
35.9 ±5.6
E**
42.9 ±4.9
31.6 ±8.4
A, under 10 yrs; B, under 13 yrs; C, under 15 yrs; D, under 17 yrs; E, under 19 yrs.
SD, standard deviation; Sig. statistical significance ** p < 0.001; * p < 0.05.
BMI, Body Mass Index; WC, waist circumference; FM, fat mass; FFM, fat free mass; SMM, skeletal muscle
mass; ALBM, appendicular lean body mass; SJ, squat jump; CMJ, counter-movement jump; CMJa, counter-
movement jump with arm swing.
Table 2. Partial correlation coefficient controlling for age.
Height
Weight
WC
FM
FM
FFM
SMM
ALBM
(cm)
(kg)
(cm)
(%)
(kg)
(kg)
(kg)
(kg)
SJ Height (cm)
0.173**
0.091*
-0.073*
-0.347**
-0.232**
0.372**
0.076*
0.083*
CMJ Height (cm)
0.169**
0.098*
-0.081*
-0.334**
-0.214**
0.368**
0.093*
0.101*
CMJa Height (cm)
0.203**
0.099*
-0.082*
-0.359**
-0.236**
0.389**
0.092*
0.104*
Significance: ** p < 0.01; * p <0.05.
WC, waist circumference; FM, fat mass; FFM, fat free mass; SMM, skeletal muscle mass; ALBM,
appendicular lean body mass; SJ, squat jump; CMJ, counter-movement jump; CMJa, counter-movement jump
with arm swing.
6
J Sport Hum Perf
ISSN: 2326-6333
Figure 1. Single linear regression between SMM, ALBM, and FFM and (A) SJ height, (B) CMJ height, and (C) CMJa.
7
J Sport Hum Perf
ISSN: 2326-6333
Multiple Regression model for Vertical
Jump Height
Finally, the relative contribution of
each independent body composition variable
in the groups of children, adolescents, and the
two combined to vertical jump height in the
SJ, CMJ, and CMJa tests was examined
(Table 3). Multiple prediction models for
children indicated that age and fat mass were
the best variables for explaining height
changes in the three vertical jump tests, while
the models for adolescents showed that age,
ALBM, and waist circumference were the
best predictors of the SJ and CMJ height. But,
WC and ALBM was excluded from the CMJa
height model. Finally, the prediction model
from the whole cohort of players (7 to 19)
years showed that age, FM, ALBM, and waist
circumference were the variables which best
predicted SJ and CMJ height. However,
ALBM and waist circumference were
excluded from the CMJa height model.
Table 3. Multiple regression equations predicting vertical jump height variables
SJ Height
CMJ Height
CMJa Height

SEE
R2
SEE
R2
SEE
R2
Children
(7-13 yrs)
Constant
5.490*
2.922
0.360
4.495*
3.272
0.436
4.610*
4.097
0.410
Age
0.635
0.687
0.674
FM
-0.203
-0.215
-0.196
Adolescents
(13-19 yrs)
Constant
2.461*
3.495
0.266
0.223*
4.662
0.306
-0.584*
5.369
0.288
Age
0.431
0.496
0.536
ALBM
0.214
0.160
WC
-0.187
-0.119
All
(7-19 yrs)
Constant
3.761*
3.587
0.619
2.941*
3.853
0.671
0.455*
4.635
0.672
Age
0.801
0.824
0.840
FM
-0.091
-0.098
-0.094
ALBM
0.097
0.085
WC
-0.131
-0.081
SJ, squat jump; CMJ, counter-movement jump; CMJa, counter-movement jump with arm swing; SEE, Standard error of
estimate; FM, fat mass; ALBM, appendicular lean body mass; WC, waist circumference.
Function 1 (children): Vertical jump (SJ, CMJ or CMJa) = constant + (age coefficient x age) + (FM coefficient x FM).
Function 2a (adolescents): Vertical jump (SJ or CMJ) = constant + (age coefficient x age) + (ALBM coefficient x
ALBM) + (WC coefficient x WC).
Function 2b (adolescents): Vertical jump (CMJa) = constant + (age coefficient x age).
Function 3a (7-19 yrs): Vertical jump (SJ or CMJ) = constant + (age coefficient x age) + (FM coefficient x FM) +
(ALBM coefficient x ALBM) + (WC coefficient x WC).
Function 3b (7-19 yrs): Vertical jump (CMJa) = constant + (age coefficient x age) + (FM coefficient x FM).
* p<0.001
8
J Sport Hum Perf
ISSN: 2326-6333
DISCUSSION
Vertical jump is a relevant skill for
assessing motor development during
preadolescence and adolescence (14) as well
as for examining soccer performance (5, 39).
Body size has been proposed as a
confounding factor in vertical jump
performance during childhood and
adolescence (22, 25), and several variables
related to body composition have been found
to be predictors of vertical jump performance
(4, 20, 21): age, height, weight, and fat free
mass. Therefore, we hypothesized that
skeletal muscle mass and/or appendicular lean
body mass may influence and improve the
existing model for predicting vertical jump
height in young Spanish soccer players.
Puberty involves important bodily and
physiological changes in humans and could
explain the significant increase in all
anthropometric parameters that we found in
this study (29). As expected, the association
between fat mass and male pubertal onset was
nonlinear (Table 1), and the progressive
increase of the fat mass began after group C
(under 15 yrs), in accordance with the
beginning of puberty in boys (~13 years)
(36); thus, a high fat mass in this age range
could be explained as “hormonal preparation”
for puberty (1, 2). Accordingly, skeletal
muscle mass showed the largest increase (5.4
kg) between groups B (under 13 yrs) and C
(under 15 yrs), whereas appendicular lean
body mass reported a more progressive and
significant increase.
It has been suggested that between the
ages of 13 and 15 years, young soccer players
obtain their best performance in vertical jump
tests (18, 25). Thus, we expected to find
greater differences between groups C and D
(under 15 and under 17, respectively).
However, in Table 1, it can be observed that
within the progressive and statistically
significant increase in vertical jump heights of
the three tests, the greatest improvement in
performance was detected between groups D
and E (under 17 and under 19, respectively)
for all tests, even though the increase between
group C and D (under 15 and under 17,
respectively) was also considerable (5.4 vs.
4.0 cm, SJ; 6.4 vs. 4.8 cm, CMJ; 7.0 vs. 6.3
cm, CMJa; respectively).
Malina et al. (18) showed that vertical
jump performance increased concurrently
with sexual maturity. Moreover, testosterone
and androgen hormones have been marked as
the main factors responsible for the higher
performance in young male soccer players
during puberty (8), based on their anabolic
effects, including bone and muscle
development, loss of fat mass, and increased
lean body mass (9). Concretely, testosterone
levels increase significantly after Tanner
stage 2 and until stage 5, but not before (10).
Thus, those young soccer players in later
stages of puberty with higher androgen levels
had higher vertical jump performance in all
tests compared to those in early or mid-
puberty with lower androgen levels.
Nevertheless, motor unit synchronization and
recruitment must be also taken into
consideration (16).
Therefore, the assessment of some
variables related to the androgenic or anabolic
changes produced during the maturation
process would be useful in interpreting
vertical jump performance (8, 18). Thus, a
partial correlation controlling for age (Table
2) was carried out and revealed that FM and
FFM were more strongly correlated with
height variables of the SJ, CMJ, and CMJa
tests (p< 0.01), while SMM and ALBM were
less significantly correlated (p< 0.05).
Subsequently, linear regressions among
vertical jump test variables and FFM, SMM,
and ALBM were performed, and they showed
that FFM was a more accurate body
9
J Sport Hum Perf
ISSN: 2326-6333
composition variable for explaining vertical
jump height compared to ALBM and SMM.
Finally, three multiple regression
equations were calculated for children,
adolescents, and the whole cohort. Previous
data from a population of active Tunisian
children between the ages of 7 and 13 years
revealed that age, height, weight, and fat-free
mass were the body composition variables
that most accurately predicted vertical jump
performance (4). Though our previous
analysis seemed to support that idea, we did
not find this relationship. In contrast, in table
3 it can be observed that for children between
the ages of 7 and 13 years, age and FM were
the best predictors of vertical jump height.
The discrepancy in the two regression models
might reside in the population differences. In
this study, a population of seven hundred and
twenty-three children who trained ~2 h·day-1,
4 days·week-1 and had 3 years of soccer
experience was recruited. Likely, the degree
of training and soccer expertise could explain
why in this study height, weight, and FFM did
not predict vertical jump height in the
regression models performed (20, 21). On the
other hand, for the adolescent group (table 3),
age, ALBM, and waist circumference were
the most accurate variables for predicting SJ
and CMJ height, while for the CMJa, only age
was included in the function. The inclusion of
waist circumference, which has been related
to abdominal fat among children and
adolescent populations (33), suggests that
trunk fat mass may play an important role in
vertical jump prediction in pubertal soccer
players. Likewise, lean body mass has been
associated with maximal anaerobic power
during growth (24), and fat free mass has
been related to vertical jump performance in
children as well (4). Thus, the identification
of appendicular body mass as a body
composition variable that predicts vertical
jump height was not a surprise, even though it
had not been observed previously. Lastly, we
observed that age, FM, ALBM, and waist
circumference were the body composition
variables that predicted SJ and CMJ height
for a population of young soccer players aged
7 to 19 years. It is also observed that age
coefficient increased substantially  0.801
vs.  0.635 vs.  0.431) compared to
children and adolescents models in
accordance with the influence of age in
vertical jump performance (37).
PRACTICAL APPLICATIONS
Vertical jump is simple and recurrent
skill measured by physical educators and
strength and conditioning coaches during
childhood and adolescent for several
purposes. However, chronological age is the
only variable used to categorize the result
obtained in this population. According to the
present study, it should take into
consideration body composition variables
such as fat mass, appendicular lean body mass
and waist circumference in order to consider
biological individuality of each children
and/or adolescent and thus to perform a more
adequate assessment of vertical jump skill and
also improve it performance throughout the
reduction of fat mass and waist circumference
as well as the augment of appendicular lean
body mass.
CONCLUSIONS
We conclude that for a Spanish
population of children and adolescents
between the ages of 7 and 19 who had prior
soccer experience (≥ 3 yrs) and had trained
for ~2 h·day-1, 4 days·week-1, age, fat mass,
appendicular lean body mass, and waist
circumference were identified as predictors of
vertical jump height. Although. total skeletal
muscle mass measured anthropometrically
has not been identified as a predictor of
vertical jump neither in childhood or
adolescence, we found for the first time a
10
J Sport Hum Perf
ISSN: 2326-6333
relationship between appendicular lean body
mass and waist circumference in the
adolescent group (13 to 19 yrs) of young
soccer players.
Thus, in addition to age, the
anthropometric measure of fat mass in
children and appendicular lean body mass and
waist circumference in adolescents could be
taken into consideration to perform a fairly
assessment of vertical jump performance in
an educational or performance perspective of
young soccer players.
Acknowledgement
The authors have no conflicts of
interest that are directly relevant to the
content of this research and wish to thank all
participants and tutors for their invaluable
contribution to the study.
REFERENCES
1. Andersson AM, Juul A, Petersen JH,
Muller J, Groome NP, Skakkebaek NE.
Serum inhibin B in healthy pubertal and
adolescent boys: relation to age, stage of
puberty, and follicle-stimulating hormone,
luteinizing hormone, testosterone, and
estradiol levels. J Clin Endocrinol Metab,
1997; 82(12): 3976-3981. [PubMed].
2. Andersson AM, Toppari J, Haavisto AM,
Petersen JH, Simell T, Simell O,
Skakkebaek NE. Longitudinal
reproductive hormone profiles in infants:
peak of inhibin B levels in infant boys
exceeds levels in adult men. J Clin
Endocrinol Metab, 1998; 83(2): 675-681.
[PubMed].
3. Andersson H, Raastad T, Nilsson J,
Paulsen G, Garthe I, Kadi F.
Neuromuscular fatigue and recovery in
elite female soccer: effects of active
recovery. Med Sci Sports Exerc, 2008;
40(2): 372-380. doi:
10.1249/mss.0b013e31815b8497.
4. Aouichaoui C, Trabelsi Y, Bouhlel E,
Tabka Z, Dogui M, Richalet JP, Buvry
AB. The relative contributions of
anthropometric variables to vertical
jumping ability and leg power in Tunisian
children. J Strength Cond Res, 2012;
26(3): 777-788. doi:
10.1519/JSC.0b013e31822a61a2.
5. Arnason A, Sigurdsson SB, Gudmundsson
A, Holme I, Engebretsen L, Bahr R.
Physical fitness, injuries, and team
performance in soccer. Med Sci Sports
Exerc, 2004; 36(2): 278-285. [PubMed].
6. Asmussen E, Bonde-Petersen F. Apparent
efficiency and storage of elastic energy in
human muscles during exercise. Acta
Physiol Scand, 1974; 92(4): 537-545.
[PubMed].
7. Augste C, Kunzell S. Seasonal variations
in physical fitness among elementary
school children. J Sports Sci,
2014;32(5):415-23.
doi:10.1080/02640414.2013.830189.
8. Baldari C, Di Luigi L, Emerenziani GP,
Gallotta MC, Sgro P, Guidetti L. Is
explosive performance influenced by
androgen concentrations in young male
soccer players? Br J Sports Med, 2009;
43(3): 191-194. doi:
10.1136/bjsm.2007.040386.
9. Csakvary V, Erhardt E, Vargha P,
Oroszlan G, Bodecs T, Torok D, Toldy E,
Kovacs GL. Association of lean and fat
body mass, bone biomarkers and gonadal
steroids with bone mass during pre- and
midpuberty. Horm Res Paediatr, 2012;
78(4): 203-211. doi: 10.1159/000342335.
10. Ferlin A, Garolla A, Rigon F, Rasi
Caldogno L, Lenzi A, Foresta C. Changes
in serum insulin-like factor 3 during
normal male puberty. J Clin Endocrinol
11
J Sport Hum Perf
ISSN: 2326-6333
Metab, 2006; 91(9): 3426-3431. .
[PubMed].
11. Glatthorn JF, Gouge S, Nussbaumer S,
Stauffacher S, Impellizzeri FM,
Maffiuletti NA. Validity and reliability of
Optojump photoelectric cells for
estimating vertical jump height. J Strength
Cond Res, 2011; 25(2): 556-560. doi:
10.1519/JSC.0b013e3181ccb18d.
12. Helgerud J, Rodas G, Kemi OJ, Hoff J.
Strength and endurance of elite soccer
players. Int J Sports Med, 2011; 32(9):
677-682. [PubMed].
13. Holm I, Fredriksen P, Fosdahl M,
Vollestad N. A normative sample of
isotonic and isokinetic muscle strength
measurements in children 7 to 12 years of
age. Acta Paediatr, 2008; 97(5): 602-607.
doi: 10.1111/j.1651-2227.2008.00709.
14. Keiner M, Sander A, Wirth K,
Schmidtbleicher D. Is there a difference
between active and less active children
and adolescents in jump performance? J
Strength Cond Res, 2013; 27(6): 1591-
1596. doi:
10.1519/JSC.0b013e318270fc99.
15. Komi PV, Bosco C. Utilization of stored
elastic energy in leg extensor muscles by
men and women. Med Sci Sports, 1978;
10(4): 261-265. [PubMed].
16. Lambertz D, Mora I, Grosset JF, Perot C.
Evaluation of musculotendinous stiffness
in prepubertal children and adults, taking
into account muscle activity. J Appl
Physiol, 2003; 95(1): 64-72. [PubMed].
17. Maio Alves JM, Rebelo AN, Abrantes C,
Sampaio J. Short-term effects of complex
and contrast training in soccer players'
vertical jump, sprint, and agility abilities.
J Strength Cond Res, 2010; 24(4): 936-
941. doi:
10.1519/JSC.0b013e3181c7c5fd.
18. Malina RM, Eisenmann JC, Cumming SP,
Ribeiro B, Aroso J. Maturity-associated
variation in the growth and functional
capacities of youth football (soccer)
players 13-15 years. Eur J Appl Physiol,
2004; 91(5-6): 555-562. [PubMed].
19. Markovic G, Dizdar D, Jukic I, Cardinale
M. Reliability and factorial validity of
squat and countermovement jump tests. J
Strength Cond Res, 2004; 18(3): 551-555.
[PubMed].
20. Markovic G, Jaric S. Scaling of muscle
power to body size: the effect of stretch-
shortening cycle. Eur J Appl Physiol,
2005; 95(1): 11-19. [PubMed].
21. Markovic G, Jaric S. Is vertical jump
height a body size-independent measure
of muscle power? J Sports Sci, 2007;
25(12): 1355-1363. [PubMed].
22. Markovic S, Mirkov DM, Nedeljkovic A,
Jaric S. Body size and countermovement
depth confound relationship between
muscle power output and jumping
performance. Hum Mov Sci, 2014 Feb;
33:203-10; doi:
10.1016/j.humov.2013.11.004.
23. Menzel HJ, Chagas MH, Szmuchrowski
LA, Araujo SR, de Andrade AG, de Jesus
FR. Analysis of Lower Limb
Asymmetries by Isokinetic and Vertical
Jump Tests in Soccer Players. J Strength
Cond Res, 2013 May; 27(5):1370-7. doi:
10.1519/JSC.0b013e318265a3c8.
24. Mercier B, Mercier J, Granier P, Le
Gallais D, Prefaut C. Maximal anaerobic
power: relationship to anthropometric
characteristics during growth. Int J Sports
Med, 1992; 13(1): 21-26. [PubMed].
25. Nedeljkovic A, Mirkov DM, Kukolj M,
Ugarkovic D, Jaric S. Effect of maturation
on the relationship between physical
performance and body size. J Strength
12
J Sport Hum Perf
ISSN: 2326-6333
Cond Res, 2007; 21(1): 245-250.
[PubMed].
26. Paasuke M, Ereline J, Gapeyeva H. Knee
extension strength and vertical jumping
performance in nordic combined athletes.
J Sports Med Phys Fitness, 2001; 41(3):
354-361. [PubMed].
27. Poortmans JR, Boisseau N, Moraine JJ,
Moreno-Reyes R, Goldman S. Estimation
of total-body skeletal muscle mass in
children and adolescents. Med Sci Sports
Exerc, 2005; 37(2): 316-322. [PubMed].
28. Quiterio AL, Carnero EA, Silva AM,
Bright BC, Sardinha LB. Anthropometric
models to predict appendicular lean soft
tissue in adolescent athletes. Med Sci
Sports Exerc, 2009; 41(4): 828-836. doi:
10.1249/MSS.0b013e31818ffe4b.
29. Rogol AD, Clark PA, Roemmich JN.
Growth and pubertal development in
children and adolescents: effects of diet
and physical activity. Am J Clin Nutr,
2000; 72(2 Suppl): 521S-528S. [PubMed].
30. Ronnestad BR, Kvamme NH, Sunde A,
Raastad T. Short-term effects of strength
and plyometric training on sprint and
jump performance in professional soccer
players. J Strength Cond Res, 2008; 22(3):
773-780. doi:
10.1519/JSC.0b013e31816a5e86.
31. Sarria A, Garcia-Llop LA, Moreno LA,
Fleta J, Morellon MP, Bueno M. Skinfold
thickness measurements are better
predictors of body fat percentage than
body mass index in male Spanish children
and adolescents. Eur J Clin Nutr, 1998;
52(8): 573-576. [PubMed].
32. Slaughter MH, Lohman TG, Boileau RA,
Horswill CA, Stillman RJ, Van Loan MD,
Bemben DA. Skinfold equations for
estimation of body fatness in children and
youth. Hum Biol, 1988; 60(5): 709-723.
[PubMed].
33. Spolidoro JV, Pitrez Filho ML, Vargas
LT, Santana JC, Pitrez E, Hauschild JA,
Bruscato NM, Moriguchi EH, Medeiros
AK, Piva JP. Waist circumference in
children and adolescents correlate with
metabolic syndrome and fat deposits in
young adults. Clin Nutr, 2013; 32(1): 93-
97. doi: 10.1016/j.clnu.2012.05.020.
34. Steinberger J, Jacobs DR, Raatz S, Moran
A, Hong CP, Sinaiko AR. Comparison of
body fatness measurements by BMI and
skinfolds vs dual energy X-ray
absorptiometry and their relation to
cardiovascular risk factors in adolescents.
Int J Obes (Lond), 2005; 29(11): 1346-
1352. [PubMed].
35. Stolen T, Chamari K, Castagna C, Wisloff
U. Physiology of soccer: an update. Sports
Med, 2005; 35(6): 501-536. [PubMed].
36. Tanner JM, Whitehouse RH, Marshall
WA, Carter BS. Prediction of adult height
from height, bone age, and occurrence of
menarche, at ages 4 to 16 with allowance
for midparent height. Arch Dis Child,
1975; 50(1): 14-26. [PubMed].
37. Taylor MJ, Cohen D, Voss C, Sandercock
GR. Vertical jumping and leg power
normative data for English school
children aged 10-15 years. J Sports Sci,
2010; 28(8): 867-872. doi:
10.1080/02640411003770212.
38. Temfemo A, Hugues J, Chardon K,
Mandengue SH, Ahmaidi S. Relationship
between vertical jumping performance
and anthropometric characteristics during
growth in boys and girls. Eur J Pediatr,
2009; 168(4): 457-464. doi:
10.1007/s00431-008-0771-5.
39. Unnithan V, White J, Georgiou A, Iga J,
Drust B. Talent identification in youth
soccer. J Sports Sci, 2012; 30(15): 1719-
1726. doi:
10.1080/02640414.2012.731515.
... Body composition has been described as a confounding factor in vertical jump performance, and several studies have attempted to categorize those body composition variables which better explain jump ability during childhood and adolescence (9), and tried to determine the nature of the relationship between anthropometric factors and vertical jump performance (4,5,(10)(11)(12)(13)(14). ...
... The results of anthropometric measures obtained from our sample showed that the average age, BH, and BM were similar to the values obtained in similar studies (3,5,9,23). ...
... The results of this study suggest that there is no significant relationship between body mass and vertical jump performance among adolescents. Our findings are similar to those of previous studies (4,9,10), which also showed that body mass has no significant bearing on the vertical jump. This is supported by the findings of Marković and Jarić (11), who studied the relationship between vertical jump height and body mass, where the result showed that body mass is independent of vertical jump height. ...
Article
Full-text available
With the aim to investigate the relationship between the body composition of adolescents and their vertical jump performance, this research was carried out on a sample of seventh grade elementary school students (47 male students). The sample of measuring instruments for body composition assessment included: body height, body mass, sum of five skinfolds thicknesses (biceps, triceps, subscapularis, suprailiac, and calf), body fat percentage, and muscle mass percentage. The SJ and CMJ tests were used for the assessment of vertical jump performance. At the multivariate level the results showed that body composition, as a predictor system, explained 44% (p = .000) of the variance of SJ and 41% (p = .000) of the variance of CMJ. At the univariate level of it was noted that the sum of five skinfolds had a high influence on the predictor system for SJ (t = -3.77; p = .001) and also a high influence on CMJ (t = -2.98; p = .005). The sum of five skinfolds had a negative impact on SJ and CMJ tests for vertical jump performance assessment. It could be concluded that the relationship between body composition components and vertical jump performance was clearly demonstrated in adolescents. Key words: relationship, body composition, vertical jump, adolescents
... Other important factors to consider are weight and percentage of body fat due to its relation with jump performance (Pérez-López, Sinovas, Álvarez-Valverde, & Valades, 2015). In the present study, the weight values (A=78,5 kg, B = 84 kg and D = 73 kg), were lower compared to international senior category (A=89 kg, B= 92kg and D= 86 kg) (Palao et al., 2008) and U21 world championship 2017 participants (A= 82 kg, B= 92 kg and D= 86 kg) (FIVB, 2017). ...
Article
Full-text available
The aim of this work was to describe and study the relationship between anthropometric and conditional factors of under-21 high-performance beach volleyball players according to playing position. The sample consisted of 5 male teams (5 blockers and 5 defenders) belonging to Spanish men's national beach volleyball team or participants in international tournaments. Anthropometric profile was assessed following the guidelines proposed by ISAK. The tests performed to assess conditional factors were: vertical jump (SJ, CMJ and ABK), 5- and 10-m sprint (S5m and SlOm), agility test (AT) and overhead medicine ball throw in a standing position (OTSP) and on knees position (OTKP). Mann-Whitney U test was applied to compare blockers and defenders and Pearson correlation coefficient (r) was used to determine the relationships between anthropometric and conditional variables. The results showed that U21 Spanish beach volleyball players had lower values for height and body weight than international players of the same category. Regarding playing position, blockers showed higher values of height, weight, muscle mass and bone weight than defenders (p<0.05). The somatotype for blockers and defenders were classified as ecto-mesomorph. Relationships have been found between anthropometric variables (height, weight, bone, muscle and fat) and conditional factors. The conditional tests did not show significant differences between blockers and defenders except those which required to mobilize an external weight, in which case blockers showed a better performance. © 2020 Federacion Espanola de Docentes de Educacion Fisica. All rights reserved.
... El rendimiento físico se correlaciona negativamente con el grosor de los pliegues cutáneos en aquellos deportes donde el deportista debe desplazar su cuerpo repetidas veces ante dificultades interpuestas por el adversario, siendo la masa libre de grasa un factor influyente sobre la capacidad de producir fuerza en actividades de alta intensidad (29). La composición corporal tiene influencia sobre la eficiencia biomecánica, la capacidad fisiológica y la salud de los deportistas (6,10,21,(30)(31)(32), considerándose relevantes dichos aspectos para la práctica del fútbol ya que los equipos que ocuparon los mejores puestos en la clasificación mostraron valores inferiores de componente graso (33). Recientemente se ha realizado un análisis crítico de los estudios de aquellos factores que influyen en el rendimiento de los futbolistas, entre los que se encuentran los factores antropométricos (34), si bien dicha investigación se centra demasiado en las metodologías de análisis y menos en los resultados, como argumentan Carling y cols. ...
Article
Full-text available
Introduction: The requirements of physical demands in soccer have evolved in recent years, determining the need to investigate those aspects that condition athletic performance. The objective of this study was to describe the incidence of individualized training, company at meals, race, and demarcation on the anthropometric variables of professional soccer players since these four factors affect body composition, which is considered a predictor of performance and an indicator of lifestyle in these individuals. For this purpose, a retrospective study was developed in 51 professional players of the Spanish Football League Second Division B during the 2015/2016, 2016/2017, and 2017/2018 seasons. The anthropometric assessment was carried out under the technical standards of measurement recommended by the International Working Group of Kinanthropometry, adopted by the International Society for the Advancement of Kinanthropometry (ISAK). The results revealed that individualized training and company during meals were the factors that most influence exerted on the anthropometric variables that were collected. The values of fat mass and muscle mass, and the sum of fold measurements are sensitive to the effect of the intervention with these factors. The highest levels of interaction occurred between company during the meals and individualized training, and between demarcation and company during the meals. Considering body composition as an aspect to be taken into account in the development of performance, it should be considered that the application of certain training contents according to the individual characteristics and lifestyle of players are factors that may have a significant influence on professional soccer players.
Conference Paper
Full-text available
Workplace stress can be defined as the change in an individual's physical or mental state in response to workplaces that pose a challenge or threat to that employee (Colligan & Higgins, 2006). Teacher well-being has become increasingly important in understanding the contextual variables related to learners' academic, social-emotional, and behavioral growth (Von der Embse, 2021). Among teachers, physical education and sports teachers may suffer from stress due to high workloads. The purpose of the present study was to initially validate a stress measurement scale for physical education teachers in Tunisia.
Article
Full-text available
Objective: The aim of this study is to find out the relationships among body composition, Yo-Yo intermittent recovery (IR) test and vertical jump test in elite young soccer players. Material and Methods: Eighteen healthy young male soccer players (Age: 16.5±0.3 years, height: 178.0±5.9 cm, body weight: 65.9±7.9kg,) voluntarily participated in the study. Total and regional body composition parameters of the soccer players were examined through a dual-energy x-ray absorptiometry (DEXA) method. Vertical jump performance tests were squat jump (SJ) and active jump (AJ), and endurance performances were determined by the Yo-Yo intermittent recovery level 1 test (Yo-Yo IR1). Relationships among body composition, Yo-Yo intermittent recovery test and vertical jump test were analyzed with Pearson Correlation coefficient. Significance level was taken as ≤0.05. Results: A statistically significant negative correlation was found between squat jump and countermovement jump (r=-0.588, r=-0.573, p<0.05), and the leg fat rate. However, there were no statistically significant relationship among squat jump, Yo-Yo IR1 and countermovement jump and other whole/regional body composition (p>0.05). Conclusion: Changes in body composition are important issues for the physical performance level of young soccer players, as local excess body fat may cause deterioration, especially in jumping performance.
Article
Full-text available
Abstract In this paper, the influence of body composition and physical fitness in the success of some jumping have been investigated. The purpose of this paper is to establish the impact between body composition and physical fitness as a predictive system and jumping as a criterion system. The survey was conducted in a sample of 170 male entities aged 14 years ± 6 months, primary school students at “BajramShabani” and “NaimFrashëri” - Kumanovo. Nine variables were applied - 5 dimensions for evaluation of body composition and four for evaluation of physical fitness. Data were analyzed using regression analyses and multivariate analysis of the group. Variables body composition which have express the impact with tests of physical fitness have an impact level (P <0.000). As we look separately, we can see that the impact of the high jump test has reached a significance value of 20.9%, in variables arm subcutaneous fat tissue with a Beta coefficient (-.621) value of 0.000 and abdominal subcutaneous fat tissue have a Beta coefficient (.347) value of 0.004. The quintuple jump reached a 21.5% significance level, in subcutaneous fat tissue arm variable had a Beta coefficient value (-.334) and impact value of 0.024. The long jump test has a 27.7% significance level, but in subcutaneous fat tissue arm variables with Beta coefficients of -0492 are worth 0.000. From this research, we can conclude that the physical fitness in this case of jumps that express the explosive strength of the lower limbs have low BMI level and skin folds, while statistical influence in the motor variables has only the variables arm skin folds and in one case a variable abdominal skin folds, from which we can conclude that to have good results in jumps we should have as little as possible adipose (fat) tissue in the abdomen and arms and the same adipose (fat) tissue should be replaced with pure muscle mass. Keywords: Body composition, physical fitness, correlation, regression
Article
Full-text available
Vertical jump is one of the most prevalent acts performed in several sport activities. It is therefore important to ensure that the measurements of vertical jump height made as a part of research or athlete support work have adequate validity and reliability. The aim of this study was to evaluate concurrent validity and reliability of the Optojump photocell system (Microgate, Bolzano, Italy) with force plate measurements for estimating vertical jump height. Twenty subjects were asked to perform maximal squat jumps and countermovement jumps, and flight time-derived jump heights obtained by the force plate were compared with those provided by Optojump, to examine its concurrent (criterion-related) validity (study 1). Twenty other subjects completed the same jump series on 2 different occasions (separated by 1 week), and jump heights of session 1 were compared with session 2, to investigate test-retest reliability of the Optojump system (study 2). Intraclass correlation coefficients (ICCs) for validity were very high (0.997-0.998), even if a systematic difference was consistently observed between force plate and Optojump (-1.06 cm; p < 0.001). Test-retest reliability of the Optojump system was excellent, with ICCs ranging from 0.982 to 0.989, low coefficients of variation (2.7%), and low random errors (±2.81 cm). The Optojump photocell system demonstrated strong concurrent validity and excellent test-retest reliability for the estimation of vertical jump height. We propose the following equation that allows force plate and Optojump results to be used interchangeably: force plate jump height (cm) = 1.02 × Optojump jump height + 0.29. In conclusion, the use of Optojump photoelectric cells is legitimate for field-based assessments of vertical jump height.
Article
Full-text available
Abstract The purpose of this review article was firstly to evaluate the traditional approach to talent identification in youth soccer and secondly present pilot data on a more holistic method for talent identification. Research evidence exists to suggest that talent identification mechanisms that are predicated upon the physical (anthropometric) attributes of the early maturing individual only serve to identify current performance levels. Greater body mass and stature have both been related to faster ball shooting speed and vertical jump capacity respectively in elite youth soccer players. This approach, however, may prematurely exclude those late maturing individuals. Multiple physiological measures have also been used in an effort to determine key predictors of performance; with agility and sprint times, being identified as variables that could discriminate between elite and sub-elite groups of adolescent soccer players. Successful soccer performance is the product of multiple systems interacting with one another. Consequently, a more holistic approach to talent identification should be considered. Recent work, with elite youth soccer players, has considered whether multiple small-sided games could act as a talent identification tool in this population. The results demonstrated that there was a moderate agreement between the more technically gifted soccer player and success during multiple small-sided games.
Article
Full-text available
Assessment of lower extremity bilateral asymmetries in soccer players is important for both injury prevention and performance. The purpose of this investigation was to compare isokinetic knee extensor assessment of asymmetry with a more specific countermovement jump (CMJ). Forty-six male Brazilian professional soccer players participated in this study. The maximal power, maximal force and impulse were determined during CMJ as well as the total work and peak torque at 60/s, 180/s and 300/s during isokinetic leg extension, separately for each leg. Factor analysis was performed for all investigated variables, and the diagnostic concordance between different criteria was analyzed by McNemar's Chi test. The factor analysis showed that the isokinetic and CMJ tests were widely independent methods for the assessment of bilateral differences. Concordance of the diagnostic information could only be found between the maximal force during CMJ and the total work and peak torque at 180°/s and 300/s during isokinetic leg extension. Impulse and maximal power during countermovement jump on a double force platform appear to be appropriate additional variables for the identification of bilateral differences. Therefore, it might be pertinent to perform, in addition to isokinetic assessment, a vertical jump test on a force platform to assure widespread and reliable diagnostic information.
Article
Full-text available
We aimed to improve the physical capacity of a top-level elite football team during its pre-season by implementing a maximal strength and high-intensity endurance training program. 21 first league elite football players (20-31 yrs, height 171-194 cm, mass 58.8-88.1 kg) having recently participated in the UEFA Champions' League, took part in the study. Aerobic interval-training at 90-95% of maximal heart rate and half-squats strength training with maximum loads in 4 repetitions × 4 sets were performed concurrently twice a week for 8 weeks. The players were not familiar with maximal strength training as part of their regular program. Maximal oxygen uptake (VO(2max)) increased 8.6% (1.7-16.6) (p<0.001), from 60.5 (51.7-67.1) to 65.7 (58.0-74.5) mL · kg (-1) · min (-1) whereas half-squat one repetition maximum increased 51.7% (13.3-135.3) (p<0.001), from 116 (85-150) to 176 (160-210) kg. The 10-m sprint time also improved by 0.06 s (0.02-0.16) (p<0.001); while counter movement jump improved 3.0 cm (0.1-6.2) (p<0.001), following the training program. The concurrent strength and endurance training program together with regular football training resulted in considerable improvement of the players' physical capacity and so may be successfully introduced to elite football players.
Article
Abstract There is empirical evidence that children's physical activity is dependent on climatic conditions. In addition, a correlation between physical activity level and physical fitness has been identified. In this longitudinal study, we investigate whether seasons have an influence on physical fitness. A total of 145 German elementary school children were tested every six months over a two-year period. We used the German Motor Test 6-18 to assess physical fitness. Performance in the 6-min endurance run (P < 0.001), bidirectional jumping (P < 0.001), the standing long jump (P = 0.026), the 20 m sprint (P = 0.006) and the stand-and-reach task (P = 0.017) was significantly better in summer than in winter. There were no differences in the ability to balance backwards (P = 0.120); in the winter, the results for push-ups (P < 0.001) and sit-ups (P < 0.001) were better than those in the summer. We have shown that physical fitness is significantly influenced by the season. Consequently, when children's fitness tests are used (e.g. as the basis for intervention programs, for classifying health-risk groups or for recognising talent), the season in which testing occurred should be reported and accounted for in future studies.
Article
Background/aims: The association of bone mass with body composition, bone turnover markers and gonadal steroids was examined in Hungarian children during pre- and midpuberty. Methods: Two hundred and thirty-seven 7- to 16-year-old subjects (56% girls) were investigated. Bone mineral density (BMD), fat mass and total and appendicular lean mass were estimated with dual-energy X-ray absorptiometry (Lunar Prodigy). The fat mass index and appendicular lean mass index (LMI) were calculated. Serum bone markers, parathyroid hormone, estradiol and testosterone were analyzed. Associations between variables were evaluated by multiple regression analysis. Results: During prepuberty, bone biomarkers, gonadal steroids and appendicular LMI were associated with bone mass in both genders (p < 0.05). During midpuberty, girls' bone turnover markers were negatively associated with bone mass (p < 0.001). In prepuberty, appendicular LMI and β-crosslaps were predictors of bone mass in both genders. During midpuberty, appendicular LMI and gonadal steroids positively contributed to bone mass in both genders, while osteocalcin exerted a negative influence on total and L1-L4 spine BMD in girls and on L1-L4 BMD in boys (all p < 0.001). Conclusions: Predictors for bone development varied according to Tanner stage and gender. The most significant determinants of bone mass were appendicular LMI and estradiol.
Article
Training and activity level are important predictors of motor development. At present, many children and adolescents do not participate in any sport activity in their leisure time.In this investigation, we analyzed the level of performance of the stretch and shortening cycle in childhood and youth. Data of 801 participants were recorded for two separate groups, those in elite soccer associations and those who were less active in their leisure time.All participants completed the following performance tests: the squat-jump, the counter movement-jump and the drop-jump from varying heights. All participants answered a questionnaire to determine their level of activity. Comparisons of performance were made across the two groups.The data showed a significant (p<0.05) advantage for soccer players in nearly every variable involved in the performance of the stretch and shortening cycle. The analysis of the questionnaire highlights that approximately a quarter of students are inactive in their leisure time, which means they do not participate in any sport activity except for school sports.The data show that many children and adolescents do not participate in sport activities in their leisure time. Furthermore, many of these children and adolescents have a Body Mass Index greater than 25. The results of this investigation support that the inactivity is correlated with a low training level in children and youths.
Article
Background & aims: To determine the relevance of waist circumference (WC) measurement and monitoring in children and adolescents as an early indicator of overweight, metabolic syndrome (MS) and cardiovascular problems in young adults in comparison with visceral and subcutaneous adiposity. Methods: A cohort study with 159 subjects (51.6% female) started in 1999 with an average age of 13.2 years. In 1999, 2006 and 2008 weight, height, and WC were evaluated. In 2006 blood samples for laboratory diagnosis of MS were added. In 2008 abdominal computed tomography (ACT) to quantify the fat deposits were also added. Results: The WC measured in children and adolescents was strongly correlated with body mass index (BMI) measured simultaneously. A strong correlation was established between WC in 1999 with measures of WC and BMI as young adults. WC strongly correlated with fat deposits in ACT. The WC in 1999 expressed more subcutaneous fat (SAT), while the WC when young adults expressed strong correlation with both visceral fat (VAT) and SAT. The correlation of WC with fat deposits was stronger in females. WC and not BMI in 1999 was significantly higher in the group that evolved to MS. Conclusions: The WC in children and adolescents was useful in screening patients for MS. WC expressed the accumulation of abdominal fat; especially subcutaneous fat.
Article
The purpose of this study was to examine the relative contributions of anthropometric variables to vertical jumping ability and leg power and to establish reference values of vertical jumping parameters in athletic Tunisian children aged 7-13 years in both sexes. Three hundred and ninety-one athletic Tunisian children (208 boys and 183 girls) aged 7-13 years were randomly selected to participate in our study. They were asked to perform squat jumps and countermovement jumps. Jump heights and leg power were simultaneously provided by the optojump device. Full and stepwise regression models were calculated to identify which anthropometric parameters significantly contributed to performance variables. The multiple regressions showed that age, weight, standing height and fat-free mass were the predictors of jumping performance. The results may help in verifying the effectiveness of a specific training program and detecting highly talented athletes.