EXERCISE AND QUALITY OF LIFE
Research article
Volume 3, No. 1, 2011, 1-9
UDC 796.035-053.8(495)
NUMBER OF STEPS PER DAY AND PHYSICAL
ACTIVITY LEVELS OF ADULTS IN GREECE
Maria Michalopoulou, Nikos Ageloussis, Labrini Drolapa and Stella Exarchopoulou
Department of Physical Education and Sports Science
Democritus University of Thrace
Abstract
This study compared self reported physical activity
(PA)
(MET min/week) with
pedometer determined PA (steps/day). Participants in this study were 300 adults, (25 - 56 years
of age). PA was assessed with the IPAQ long form and the number of steps was assessed with
the Yamax model SW-200. Participants wore the pedometer for 7 consecutive days. Data
(categorical score) was analyzed using cross-tabs analysis. Two-way ANOVA (gender 2 x level
of PA 3) was performed on the number of steps/day. Significant main effect was reported only
for the factor ìlevel of PAî with adults in the moderate and the high activity group performing
more steps/day than adults in the low PA group. Adults in Greece performed less steps/day than
the international recommendations PA suggest even though the majority of them were assigned
by IPAQ long form at the moderate and very high PA groups.
Keywords: physical activity recommendations, pedometer, self report
Introduction
The importance of physical activity
(PA) in maintaining improved quality of life
(USDHHS, 1996), increased longevity (Lee, & Paffenbarger, 2000; Lee, & Skerrett 2001) and a
number of health benefits is well recognized (Blair, Cheng, & Holder, 2001; Morris, Clayton,
Everitt, Semmence, & Burgess, 1990; Thune, Njolstad, Lochen & Forde, 1998).
The effects of PA on health can be mediated by changes in fitness, but the relationships
among levels of physical activity and health are complex. Lifestyle behaviors physical and social
environmental conditions, personal attributes and genetic characteristics can also determine their
interrelations (Bouchard, Blair and Haskell, 2006).
Even though the precise amount and type of PA required to achieve specific health
related outcomes remains unclear (Haskell, 1994; Freedson, & Miller, 2000), recommendations
regarding the types and amounts of physical activity /exercise needed for health and fitness
improvement have been suggested by different organizations for different population groups
Corresponding author. Democritus University of Thrace, Department of Physical Education and Sport Science,
Campus, 69100 Komotini, Greece, e-mail: michal@phyed.duth.gr
© 2010 Faculty of Sport and Physical Education, University of Novi Sad, Serbia
M. Michalopoulou et al.
(ACSM, 1975, 1978; AHA 1975; USDHHS, 1996; ACSM/AHA 2007). These recommendations
for health enhancing physical activity/exercise included information on the frequency, intensity
and duration of either exercise or physical activity for the general population and segments of it.
The American College of Sports Medicine originally in 1975 recommended to sedentary
adults exercising 3 days per week, for 15-60 min with 60-90% max heart rate and AHA
suggested exercising 3-4 times per week for 20-60 min with 70-80 % max heart rate The ACSM
and the USDHHS/CDC recommendation was later issued suggesting exercising 3-5 times per
week with 40 - 85 % Vo2max, recommending that every US adults should accumulate 30 min or
more of moderate intensity physical activity on most preferably all days of the week (Pate, Pratt,
Blair, Haskell, Macera, Bouchard, & King, 1995).
An alternative guideline traced back to Japanese walking clubs recommends the
accumulation of
10.000 steps per day for healthy adults
(Tudor-Lock, & Bassett,
2004).
Additionally indices to classify pedometer determined physical activity suggest that <5000 steps
per day is indicative of sedentary lifestyle, 5000-7499 steps/day is considered as low active since
it is typical of daily activity excluding sports/exercise, 7500 steps per day might be considered as
ìsomewhat activeî since it likely includes some volitional activities , > 10.000 steps per day
indicates ìactiveî individuals and finally individuals who take >12.000 steps per day are likely to
be characterized as ìhighly activeî.
With the greater emphasis on the relationship of PA to health, there is an emerging need
for accurate and reliable methods of estimating and assessing PA and energy expenditure, (Sallis,
& Saelens, 2000). Questionnaires (self report instruments, daily logs and diaries) have always
been a very popular approach in assessing PA in large population samples. IPAQ (Craig,
Marshall, Sjˆstrˆm, Bauman, Booth, Ainsworth, Pratt, Ekelund, Yngve, Sallis, & Oja, 2003) is a
self-reported measure of physical activity suitable for assessing population levels of physical
activity across countries. It has been used with confidence in developed countries or in urban
samples in developing countries, but with some caution in rural or low literacy samples from
developing countries. The primary target group for IPAQ was middle-aged adults and IPAQ
measurement properties in older adults or adolescents are not known (Craig et al. 2003). This
self report questionnaire provides both a continuous MET min/week score and a categorical
according to which participants are assigned to
3 levels of PA: high, moderate and low.
According to the IPAQ Research Committee the high PA level equates to approximately at least
one hour per day or more, of at least moderate intensity activity above the basal level of PA and
can be considered for as those who move at least 12,000 steps per day or the equivalent in
moderate and vigorous activities. The moderate level of PA equates to ìhalf and hour of at least
moderate intensity PA on most daysî and the low level of PA is the lowest level of PA and
individuals who do not meet the criteria for the other two categories are assigned to this
category.
Walking, is one of the most common forms of activity for US adults (Crespo, Keteyian,
Heath & Stempos, 1996) and Canadians (CFLRI, 2004) and is readily captured by a pedometer.
Public health initiatives in these countries have emphasized this activity (Pate et al. 1995;
USHHS ,1996; CFLRI, 2004) since walking has been associated with lower risk of CHD
(Manson, Nathan, Krolewski, Stampfer, Willett, & Hennekens, 1992) and coronary events (Hakim,
Curb, Pertovitch, Rodrigez, Yano, Ross, White, & Abott, 1999). Pedometers have been useful for
examining questions about walking and in particular distance covered on physical activity
questionnaires (Bassett, Cureton, & Ainsworth, 2000). Pedometers are a type of motion sensor
that are low-cost, unobtrusive, accurate (Basset et al., 1996; Crouter et al., 2003; Schneider et al.,
2003), and their output (steps or distance) is easily comprehendible and thus are becoming
increasingly popular in physical activity research and within the general population (Bassett,
Cureton, & Ainsworth, 2000). Pedometers are typically worn on the belt or waistband and
respond to vertical accelerations of the hip during gait cycles. They provide data on steps and
some models estimate distance traveled and energy expenditure. Although pedometers measure
2
Number of steps of Greek adults
ambulatory activity, they do not capture all types of physical activity (swimming, weight lifting,
bicycling, etc.).
They can also be used to distinguish between individuals whose physical activity level
varies based on steps per day, to determine whether individuals meet step recommendations, to
measure changes in physical activity with interventions, and address several other issues in
physical activity research and applications. According to recent studies pedometer determined
steps per day activity classifications have been proposed: _5000 sedentary, 5000ñ7499 inactive,
7500ñ9999 somewhat active and 10,000 active (Tudor-Locke, & Bassett, 2004).
According to the IPAQ scoring protocol ñ categorical score, the above recommendations
are met by those that are included in the levels of moderate PA and high PA and not by those in
the low PA level. It is unclear though whether these two recommendations are congruent or
whether ì10.000 total steps per dayî is more than 30 min of moderate-intensity physical activity.
It is also unclear if the individuals that are assigned to the 2 top levels of PA with the use of
IPAQ ñ long form meet the cut-point of 10.000 steps per day. The aim of the present study was
to determine the number of steps per day taken by adults in Greece assigned in the different PA
levels that have been proposed by IPAQ and possible gender effects on the participantsí level of
PA.
Method
Participants
Participants in this study were 300 adults 150 men (44.5 + 8.3 years of age) and 150
women (34.9 + 7.5 years of age). They were requited through a posted advertising campaign that
was initiated by the Municipal Center for Recreation in 3 Greek urban centers. Before taking part
in this study participants were informed about the purpose and the content of this study and
signed an informed consent form approved by the Dept of PESS, University of Thaceís review
board. Physical and demographic characteristics of the participants are presented in Table 1.
Instruments and Procedure
Questionnaire estimated physical activity
Physical activity was assessed with the use of the long self ñ administered version of the
International Physical Activity Questionnaire (Craig et al. 2003). This long version (31 items)
was designed to collect detailed information within the domains of household and yard work
activities, occupational activity, self-powered transport, and leisure-time physical activity as well
as sedentary activity. The data collected were summed in order to estimate the total time spent in
vigorous physical activity, moderate intensity physical activity and walking. The total weekly
PA was estimated as a continuous variable by weighting the reported minutes per week within
each activity category by a MET energy expenditure estimate assigned to each category of
activity. MET levels were obtained from the 2000 Compendium of physical activities to include
walking (3.3 MET), moderate-intensity activities (4 MET) and vigorous-intensity activities (8
MET). Cut points were also used in order to create a categorical variable according to which PA
can be characterized as high, moredate and low (IPAQ Scoring protocol, 2005).
Pedometer estimated physical activity
The pedometer used in this study was the Yamax model SW- 200, Yamax Corporation,
Tokyo, Japan. This brand detects steps taken acceptably under both controlled conditions
(Crouter, Schneider, Karabulut, & Bassett, 2003; Schneider, Crouter, Lukajic & Bassett, 2003; Le
3
M. Michalopoulou et al.
Masurier, & Tudor-Locke, 2003) and free-living conditions (Schneider et al. 2003). Additionally
as an electronic pedometer it has greater accuracy than old-fashioned mechanical pedometers
(Basset, Ainsworth, Leffett, Mathien, Main, Hunter, & Duncan, 1996). Participants were instructed
how to use the pedometer for the following 7 days (remove the pedometer only while bathing,
showering, or swimming) starting the morning of following day of the meeting. When 7 24-hour
days had elapsed the participants were asked to record their 7 days-end steps taken on the
provided log and also report it by phone to the researcher. On the 8th day a meeting with the
researcher was scheduled in order for the participants to complete the IPAQ ñ long form
questionnaire, return the pedometer kit and collect data related to height and weight to compute
body mass index (BMI) as kg/m2.
Analysis of data
All statistical analyses were performed using SPSS (Statistical Packege for the Social
Sciences for Windows, 14.0, 2006, SPSS Inc., Chicago IL). Descriptive data are presented as
frequencies, means and standard deviations. Cross-tabs analysis was used in order to assess the
effect of gender of the level of physical activity (categorical score). Two way analysis of
variance was used in order to determine the effect of gender (2) x level of physical activity (3) on
the dependent variable ìnumber of steps/dayî. Post hoc analysis was performed using the LSD
test. Pearson correlation coefficient was calculated for the variables of total physical activity
(MET min/week) score, moderate physical activity (MET min/week) score, walking (MET
min/week) score and steps/day. The level of significance was set at p = .05.
Results
Physical characteristics and physical activity data in MET values of the participants
according to gender and PA level are presented in Table 1.
Table 1
Physical characteristics and physical activity levels of the male and female participants
according to their level of physical activity
Low PA
Moderate PA High PA
Total
M (SD)
Women
(N)
41
38
71
150
PA ñMET score
924 (482)
2.318 (483)
6.562
(3.155)
4.830
(3.490)
Age (years)
47.9
(7.2)
45.6
(8.4)
43.9
(6.2)
45.8
BMI
22,73
22,28
22,33
22,38
Men
(N)
31
21
98
150
PA ñMET score
856 (562)
1.981(536)
9.654
(7.653)
5490 (4.313)
Age (years)
44.2
(5.1)
42.7
(3.3)
45.8
(7.5)
44.5
(8.3)
BMI
26,5 (4,6)
26,11 (3,3)
25,91 (3,2)
26,06 (3,05)
Gender effects on physical activity ñself report measure
Categorical MET Score
According to the results of cross-tabs analysis, chi-square was not statistically significant
(x2=1.30, p>.05) and physical activity level was independent to the factor gender. No differences
were reported between the number of male and female participants that were assigned to the 3
different levels of PA according to IPAQ categorical score.
4
Number of steps of Greek adults
Continuous MET Score
According to the results of the analysis of variance no significant effect for the factor
gender (F(1,298) = 1,762, p = .185), was revealed for the total MET score (Table 1). Additionally
MANOVA revealed a significant effect for the factor ìgenderî only on physical activity of high
intensity (F(1,298) = 4,793, p = .029) where men had significantly higher scores than women. No
gender effects were reported for physical activity of moderate intensity (F(2,298) = 3,064, p =
.081), and on walking (F(2,298) = 2,165, p = .142) (Table 2).
Table 2
Physical activity (MET min/week) of high moderate intensity and walking for men and women
participated in the study
High Intensity PA* Moderate Intensity Walking
Total Score
M (SD)
PA
Women
1.825
(2.418)
1.616
(1.477)
1.389
(1.314)
4.831
(4.993)
Men
2.553
(3.272)
1.315
(1.493)
1.622
(1.426)
5.491
(3.490)
*PA = physical activity
Number of steps
According the results of two- way ANOVA no significant interaction was revealed for
the factors ìgenderî and ìlevel of physical activityî (F(2,294) = ,234, p > .792) on the number of
steps/day taken. A significant main effect was reported only for the factor ìlevel of physical
activityî (F(2,294) = 53,168, p = .000) but not for the factor ìgenderî (F(1,294) = 1,801, p = .181).
Post hoc LSD test revealed significant differences between all three levels of the factor ìlevel of
physical activity (p<001), (Table 3).
Table 3
Number of steps per day according to the gender and level of physical activity (PA) set by IPAQ
for all the participants in this study
Low Physical Moderate Physical High PA
Total
Activity
Activity
Women (n)
41
38
71
150
5183 (1092)
6430 (2302)
8844 (2456)**
7783 (2692)
Men (n)
31
21
98
150
5309 (2379)
7206(2523)
9324 (3267)*,**
7906 (3339)
Total
72
59
169
300
5256 (1929)
6867 (2853)*
9061(2853)*,**
7845 (3029)
*= differences with low physical activity group
** = difference with moderate physical activity group
Additionally according to Pearson correlation
(r) the number of steps/day was
significantly correlated with total physical activity score (r = .50, p = .01) Correlations for men
and women between number of steps and total physical activity score, high intensity physical
activity, moderate intensity physical activity and walking are presented in Table 4.
5
M. Michalopoulou et al.
Table 4
Correlation of steps per day and physical activity assessed with IPAQ-long form for all the
participants in this study
Steps per day Walking PA
Moderate
Intensity Vigorous PA
PA
Walking PA
.40*
Moderate Intensity
.27*
.27*
PA
Vigorous PA
.41*
.26*
.34*
Total PA score
.50*
.59*
.66*
.87*
*p <.01
Discussion
According to the results of this study the majority of the participants
(76%) were
physically active enough since following the categorical scoring system of the IPAQ long form
they were assigned to the moderate and the high PA groups. Additionally the adult men and
women in this study, who were moderately and highly physically active again according to IPAQ
categorical scoring system, performed significantly more steps per day when compared to adults
who were assigned in the low physical level. Further more significant differences in the number
of steps/day were also recorded between adults who were moderately and those who were highly
active.
In further detail, in relation to gender, male participants who were assigned as highly
active performed significantly more steps/day than the other two male groups (low PA and
moderate PA) and the moderately active males performed more steps/day than the low activity
group. As for female participants, significant differences were reported between the low physical
activity group and the highly active women and between the moderately active group without
though reporting significant differences between women who were assigned in the low and
moderate activity group.
All the above results support the use of the IPAQ long form as a self report instrument
used by adults, in assessing PA level. By interpreting these results a rather positive conclusion
can be formed concerning the overall PA level of the participants since only 24% had a low PA
level that is likely to translate into unfavorable health outcomes whereas the converse would be
true for participants in the moderate and high level of PAî (Bouchard, et al. 2006).
This finding of health ensuring physical activity level for the majority of the Greek
adults is unfortunately being contradicted by those of recent studies performed in Greece and in
other European countries according to which a smaller percentage of Greek adults is active
enough to ensure health related benefits
(Makavelou, Michalopoulou, Makavelou, Ifantidou,
Kourtesis, & Zetou, 2005; Varo, Martinez-Gonzalez, de Irala-Estevez, Kearney, Gibner, & Martinez,
2003). According to the recently published Euro barometer Report (2010), 67% of the Greek
responders replayed ìneverî to the question ìHow often do you exercise or play sportî.
Additionally the number of daily steps that were recorded for the two groups of
participants in the high PA and the moderate PA groups that are supposed according to IPAQ
scoring protocol to meet the 30 min (-1day) recommendations for health enhancing PA, are lower
from what has been suggested by the literature (Tudor-Locke, & Bassett, 2004). In more detail if
the participantsí compliance with pedometer determined recommendations, in this study, was to
be based upon the number of steps they performed daily, the results would differ significantly
6
Number of steps of Greek adults
from the ones that became available with the use of IPAQ long form. Using the cut points in
daily step counts suggested by Tudor-Locke, & Bassett (2004), both participants in low and the
moderate PA groups would be characterized as ì inactiveî since their mean daily step counts
were within the 5000-7499 range, (5309 and 6867 steps/day respectively). Previous studies have
presented contradicting results according to which, adults in Australia who achieve current PA
guidelines also achieve 10.000 steps/day (Mc Cormak, Giles-Cort, & Milligan, 2006) and on the
other hand self report adherence estimates in a representative sample in US adults, were much
higher that those measured by accelerometer, (Troiano, Berrigan, Dodd, Masse, Tilert, & McDowell,
2008).
The use of PA recommendations may be closer to the findings of this study if we
consider that
8,000 steps day(-1) might be a more valid screening tool as a proxy for classifying
those meeting public health physical activity recommendations of 30 min.day(-1) of moderate
activity as suggested by previous studies
(Macfarlane, Chan, Chan, Ho, & Lee, 2008; Tudor-
Locke, Ainsworth, Thomson, & Matthews, 2002). Additionally, the use of IPAQ long form, a
self-report instrument that categorizes participantsí PA by level of exertion (light, moderate,
vigorous) and a direct method (pedometer), results in increased differences between the mean
percent of the higher category levels of intensity (Prince, Adamo, Hamel, Hardt, Gober, &
Trambley, 2008).
In conclusion, due to limited convergent validity between the two instruments
(Macfarlane, Lee, Ho, Chan, & Chan, 2006) these measures are measuring different levels of
habitual PA and care is needed when comparing their results in particular since both instruments
address PA recommendations that are being used in lifestyle PA interventions in different
population and in determining relationships between PA and health outcomes (Kahn, Ramsey,
Brownson, Howze, Powell, Stone, Rajab, & Corso, 2002; Prince et al. 2008).
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Submitted 3 Februar, 2011
Accepted 21 March, 2011
9
EXERCISE AND QUALITY OF LIFE
Research article
Volume 3, No. 1, 2011, 11-21
UDC 616-057.875:796.035]:004.9
AN AUTOMATED IDENTIFICATION OF INDIVIDUALS AT
HEALTH RISK BASED ON DEMOGRAPHIC
CHARACTERISTICS AND SELF-REPORTED PERCEPTIONS
Dejan Magoc
Department of Health Studies
Eastern Illinois University
Tanja Magoc, Ph.D.
Center for Bioinformatics and Computational Biology
University of Maryland
Joe Tomaka, Ph.D.
Department of Public Health
University of Texas at El Paso
Abstract
The risks of developing diabetes, high blood pressure, and cardiovascular disease could
be reduced by increasing the number of individuals receiving adequate levels of physical activity
(PA). Centers for Diseases Control and Prevention (CDC) has reported that about 30% of
Americans do not engage in any PA and about 40% engage in some levels of PA, but still not
meeting the recommended levels defined by the American College of Sports Medicine (ACSM).
Studies have shown that the greatest declines in PA occur during the transitions from high school
to college and beyond. Thus, it is important to identify students at young age that are at health
risk due to lack of PA, so that specific steps could be taken toward helping these individuals
develop a healthier lifestyle. We used data on 100 college students to develop a preliminary
computer program
(using a backpropagation multilayer neural network approach) to
automatically identify individuals at risk of being not sufficiently physically active. Besides
various types of demographic variables, data included information on the association between
studentsí self-reported levels of PA and Social Cognitive Theory (SCT) constructs (e.g., self-
efficacy, self-regulation, social support, expectations), as predictors of participation in PA. The
results of this study indicated that the backpropagation multilayer neural network identified and
classified individuals at risk of being not sufficiently physically active into right categories (at-
risk individuals or not at-risk individuals) 77% of the time. Collecting additional data points that
contain more at-risk individuals will improve the neural network's prediction of at-risk
individuals.
Keywords: automated identification, physical activity, college students
Corresponding author. Department of Health Studies, Eastern Illinois University, Lantz Charleston, IL 61920, e-
mail: dejanmagoc@yahoo.com
© 2010 Faculty of Sport and Physical Education, University of Novi Sad, Serbia
D. Magoc et al.
Introduction
Lack of physical activity (PA) in general population has become a major public health
concern (Petosa, Suminski, & Hortz, 2003). Even though a relatively large number of people
report participating in some PA, majority of population is not sufficiently physically active to
prevent diseases such as hypertension, diabetes, and cardiovascular disease. According to the
American Heart Association (AHA) and the American College of Sports Medicine (ACSM), at
least 30 minutes of moderate PA (e.g., walking) five days per week or 20 minutes of vigorous
PA (e.g., running) three days per week is required to keep a healthy living style (Haskell et al.,
2007). However, studies show that only about
30% of Americans satisfy the minimum exercise
requirements and another 30% does not exercise at all (CDC, 2005).
Research has also shown that levels of PA dramatrically decrease from high school to
college years and beyond (Rovniak, Eileen, & Winett, 2002). Thus, it is of high importance to
motivate college students to engage in regular physical activity. Unfortunately, many PA events
and promotions on college campuses, such as intramural leagues and sport-specific clubs, tend to
attract students who are already physically active. In order to attract physically inactive or not
sufficiently active students, it is important to identify these individuals quickly and efficiently.
After identifying students at health risk due to physical inactivity, such students could be
approached by targeted interventions.
Studies have shown consistently correlations between PA levels and demographic
characteristics, such as race and gender (Pratt, Macera, & Blanton, 1999; Mouton, Calmbach, &
Dhanda, 2000; Dunn & Wang, 2003). Research has also shown that other factors, such as self-
motivation
, previous physical activity engagement, perception of importance to exercise,
perception of current physical and psychological health and support from friends and family to
exercise are highly correlated to the amount of PA an individual performs (Pratt et al., 1999;
Magoc, Tomaka, & Thompson, 2010). These factors could be used to identify individuals at risk
of being physically inactive at early stage, which could prevent students from becoming
sedentary.
Although such data could be assessed relatively quickly, the review and evaluation
process for each individual would take considerable time and effort to perform. Instead of
manually examining all responses, we propose a system of computerized questionnaires with
automatic and practically instantaneous analysis and presentation of results to immediately
identify students at risk of not being insufficiently physically active to prevent negative health
outcomes.
This paper presents the preliminary results regarding the application of one such tool.
Specfically, using data collected from 100 college students about their weekly physical activities
as well as their demographic characteristics, the machine learning algorithm (see the section on
machine learning) was used to build a model that predict whether an individual is likely to be at
risk of being physically inactive. The predicted output for a particular individual was compared
to the weekly physical activity information entered by that individual to assess the accuracy of
the prediction.
Machine Learning
Machine learning (see Russell & Norvig, 2010; Tan, Steinbach, & Kumar, 2006) is a
branch of computer science that aims at developing computer programs that simulate human
reasoning and can therefore ìreplaceî humans in numerous tasks including data analysis and
12
Automated identification of individuals at health risk
decision making. A major focus of machine learning is to automatically learn to recognize
patterns and infer relationships among different variables. Based on the learned relationships,
these computer programs are able to make decisions that are equivalent to decisions that would
be made by humans in a given situation.
A machine learning algorithm consists of two phases: the training phase and the
application phase. In the training phase, the algorithm learns patterns and relationships in a given
data set, while in the application phase, a decision for a new instance (e.g., a new individual) is
made.
The training phase could be performed in a supervised or an unsupervised mode. In either
option, a data set is provided for training. A data set consists of numerous (tens to thousands)
data points. Each data point corresponds to one instance and contains a value for each variable
used to make the final decision. In the supervised learning, the final decision is also provided in
the training sample. Thus, for supervised learning, we need to know the correct decision in all
training data points. The known decisions are used to reduce the error in the machine learning
algorithm by aiding the algorithm to learn patterns and relationships that yield particular
decision. On the other hand, the unsupervised learning does not require knowledge of correct
decisions.
One of the main applications of machine learning is in classification problems. Given an
instance, a machine learning program classifies this instance in one of several possible groups.
An instance that is being classified consists of a value for each variable used to make the
decision, but the correct class is unknown. The classification is based on the patterns and
relationships previously observed in the training phase.
To test the accuracy of a machine learning algorithm, the algorithm is usually trained on
a data set and tested on a different set of data, both of which have known classes for each data
point, to avoid bias that would result in the algorithm performing well only on the data set used
for training. One common method to split available data points in the training and testing data
sets is to randomly split all data points into five groups, and perform 5-fold cross validation. This
method uses all possible combinations of four out of five created sets for training and one set for
testing. Thus, five tests are performed, one for each of five sets to be the testing set, and the
results of the five tests are combined to determine the accuracy of the algorithm.
Neural Network
A neural network (NN) is a type of a machine learning algorithm that is designed to
imitate the actions of the human neural system (see Russell & Norvig, 2010; Tan et al., 2006). A
NN is represented as a directed weighted graph where nodes simulate human neural cells
(neurons), and directed edges simulate the links between neurons (axons). The strength of the
signal transferred between neurons determines the action of a human. This signal strength is
simulated by the weights on the edges in an NN (Figure 1). The basic task of a NN is to learn
these weights in order to yield accurate results when applied to real life data.
13
D. Magoc et al.
Figure1. A simple Neural Network with Three Input Nodes (x1,x2,x3) and One Output Node (y)
The simplest NN is called the single-layer NN and consists of only input and output
layers of nodes. The inputs nodes take the values of variables used to make a decision, and the
output node contains the decision. The decision is made by combining the values of input nodes
and the weights on the edges.
Each data point from the training data set is processed by the NN, one by one, and after
each data point is processed, the error is calculated and the necessary adjustments to weights are
made. When all data points are processed, the same process is repeated over and over until a NN,
with a satisfying (i.e., very low) error in classification, is built or until a predefined number of
iterations is reached (usually several hundred iterations).
Single-layer neural networks are good classifiers in simple cases. However, more
complex multilayer networks are much more powerful than neural networks that contain only
input and output layers. Multilayer neural networks contain one or more hidden layers (Figure
2).
Figure 2. A Fully Connected Multilayer Neural Network
14
Automated identification of individuals at health risk
Similarly to a single-layer NN, a multi-layer NN takes values of variables of a data point
as inputs (i.e., the input layer), aggregates these values by calculating the weighted sum, and
applies a function, such as sign or sigmoid function, to produce the values of the next level of
nodes (i.e., the hidden layer). Furthermore, the hidden layer of nodes acts as the input layer for
the next level of nodes (i.e., a next hidden layer or the output layer) until the values of the output
nodes are calculated. In a multi-layer network, the links between nodes can go either from a
lower layer to a higher layer (input being the lowest layer and output the highest layer), which is
the case in feed-forward networks, or can be directed from a node to a node at a higher, same, or
lower level, which is the case in recurrent networks.
Similarly to a single-layer NN, a multi-layer NN learning algorithm works by minimizing
the error. The error could be contributed equally to each node or a backpropagation algorithm
could be used to more precisely determine the impact of each node to misclassification and
therefore allow different levels of weights adjustment on edges.
Neural Network to Identify Individuals at Health Risk
Currently available data obtained in numerous studies about PA and the factors that
influence the level of an individual's PA are characterized by still unknown probability
distributions, not precisely known dependencies among different data variables, and unclear
level to which each variable impacts an individual's readiness and commitment to exercise. Due
to all uncertainties about the relationships between PA and features highly correlated with the
level of PA, machine learning is well suited approach to capture important relationships among
features present in the existing data, which are then used to identify individuals at health risk
using only a few demographics and self-reported characteristics of individuals.
Method
Participants and Setting
The participants in this study were 100 part- or full-time currently enrolled male and
female students from a large southwestern university in the U.S. with a large Hispanic
enrollment. All participants were recruited through classroom settings, and all completed the
cross-sectional survey.
Measures
Demographic variables - included self-reported gender, race/ethnicity, class, height and
weight. In addition, participants self-reported perception of their current physical and
psychological health.
International Physical Activity Questionnaire (IPAQ; Booth, 2000) - a self-reporting
measurement of the level of PA the individual performed during the last seven days. It asked
participants to record the number of sessions and the average duration of an exercise session for
vigorous and moderate activities.
Self-Efficacy for Exercise Behavior Scale
(Sallis, Pinski, Grossman, Patterson, &
Nader,1988) - consisted of 12 questions measuring the individual's readiness to overcome
obstacles (e.g., tiredness, large amount of work, not accomplishing set physical activity goals) in
order to exercise. Moreover, the participants reported the importance of setting aside time for
exercise in their schedules and following the set goals.
15
D. Magoc et al.
The Family and Friend Support for Exercise Habits Scales (Sallis, Grossman, Pinski,
Patterson, & Nader, 1987) - measured the support and motivation to exercise that participants
received from family and friends, including exercising together with another individual,
receiving reminders from an individual to exercise, or having a discussion about exercising.
Procedures
Participants for this study were largely recruited through regular classroom meetings and
activities, with most receiving extra course credit for participation. All participants completed
informed consent forms prior to completing the questionnaires. It took approximately 20
minutes for participants to complete the questionnaire.
Results
Descriptive Analysis
A slightly more females (59%) participated in the study than males. The majority of
participants were Hispanics
(82%). Because of the high proportion of participants being
Hispanic, for the purpose of the study, all participants were classified either as Hispanic or non-
Hispanic, therefore, not making a distinction among non-Hispanic participants, which included
Caucasians, African Americans, Native Hawaiians, American Indians, and Asians.
Most participants recorded their major being health or sports related studies (73%). The
majority of participants self-reported their physical health to be good or fair (48% and 31%,
respectively) and only 13% self-reported their physical health to be excellent. Majority of the
participants rated their psychological health as good or excellent (54% and 23%, respectively).
Majority of participants recorded at least a medium level for readiness to overcome
obstacles in order to exercise as well as for motivation and support received from friends and
family members. In addition, 21% of the sample self-reported the low importance to exercise.
Almost half of the participants (41%) failed to meet the recommended levels of PA, with
a higher percentage of females being not sufficiently physically active than males (30% and
11%, respectively). In addition, 56% of the sample was overweight, including 26% of those
being classified as obese.
The collected information was used to build an automated predictor of students at risk of
being not sufficiently physically active by applying a machine learning algorithm.
Primary Analysis
Using the information collected from 100 students, we trained a backpropagation NN
with eight input variables, one hidden layer with 13 nodes, and the output layer with two nodes.
The input variables included the following:
Gender: this variable could take two values {male, female}.
Hispanic: this variable could take two values {yes, no} describing whether the individual
is Hispanic or not, respectively. This distinction was made since studies have shown that
Hispanic population exhibits different attitudes towards physical activities from those
exhibited by, for example, Caucasian people (Pratt, 1999). Since not enough data were
available to train the NN on different ethnicities among non-Hispanics, further distinction
among ethnicities was not included.
16
Automated identification of individuals at health risk
Major: this variable could take two values
{sport related, not sport related}. This
distinction was made because it is expected that students majoring in sport or health
related studies are more likely to be aware of PA importance and therefore exercise more
than their peers who major in other disciplines.
Physical health: this variable was a self-reported individualís perception, and could take
any of the five values {excellent, good, fair, poor, very poor}.
Psychological health: this variable was a self-reported individualís perception, and could
take any of the five values {excellent, good, fair, poor, very poor}.
Self-efficacy: this variable is a summary of an individual's answers to the 12 questions on
the self-efficacy scale assessment. Since each question allowed participants to express the
level of self-efficacy in the range 1-5 (1 meaning 'low' and 5 meaning 'high'), the values
were averaged, and the score above 4.00 was reported as îreally high'', the score between
3.00 and 4.00 as ìhigh'', etc. The self-efficacy variable could take one of five values
{very high, high, medium, low, very low}.
Importance of exercise: this variable represented how important it was for an individual
to make time for exercise in his/her schedule and to accomplish the scheduled PA goals.
The variable could take one of five values {very high, high, medium, low, very low}.
Support: this variable is a summary of the individual's answers to the exercise habits
scale assessment. It was created similarly to the self-efficacy variable and could take one
of the five values {very high, high, medium, low, very low}.
The output layer of the NN consisted of two nodes {risk, no risk}. Only one of these two
nodes is on as a result of applying the NN to data collected from a new individual. Depending on
which node is on, the person is classified to be or not to be at health risk based on the self-
reported characteristics.
A neural network was trained using free software package weka (Hall, Frank, Holmes,
Pfahringer, Reutemann, & Witten, 2009). Since all collected data was represented as non-
numeric data to weka, each variable that could take more than two values was represented by
multiple input nodes, one for each value the variable could take. For example, the variable
importance of exercise could take one of five values (very high, high, medium, low, and very
low), thus five input nodes were designed for this particular variable. However, even though
some variables could take one of five values, not all five values have shown up in the collected
data sample, and thus, less nodes were used to represent such a variable. For example, no one
reported his/her physical health to be very poor, thus the physical health variable used only four
nodes in the developed NN. Variables with multiple nodes, such as physical health and
importance of exercise, would have only one of their nodes set on in each training or testing
sample.
Furthermore, if a variable could take exactly two values, this variable was represented by
only one node. This node was either on or off, representing two different values that the variable
could take. With this representation, the input layer of the NN developed for the collected data
sample consists of 25 nodes.
The hidden layer was automatically generated by weka. By default, weka generates
(number of attributes + number of classes)/2 nodes in the hidden layer, which resulted in (25
input nodes + 2 output nodes)/2=13.5 for our data sample, so 13 nodes were generated in the
hidden layer.
A fully connected NN (i.e., a NN where each node from a previous layer is connected to
each node of the next layer (see Figure 2) was trained using a backpropagation algorithm.
17
D. Magoc et al.
The learning rate in the NN was initially set at 0.2 and decreased throughout training
cycles. Total of 500 iterations were performed to train this NN, which took 0.47 seconds for the
given data set.
To validate the accuracy of the developed NN, we performed 5-fold cross-validation with
80 data points used for training and 20 data points for testing. Combining results of all five runs
in cross-validation, the NN classified correctly 77% of test data. Table 1 shows the classification
of individuals into ìat riskî and ìnot at riskî categories. Out of 41 individuals who should have
been classified ìat riskî, 18 individuals were classified correctly. Similarly, out of 59 individuals
who should have been classified ìnot at riskî, only one individual was classified incorrectly.
Table 1
Classification of Individuals ìat riskî and ìnot at riskî Categories
Individuals classified
Individuals classified
ìat riskî
ìNOT at riskî
Individuals
18
23
ìat riskî
Individuals
1
58
ìNOT at riskî
Discussion
Even though there are two possible types for misclassification (i.e., an at-risk individual
classified as not at-risk, and a not at-risk individual classified as at-risk individual), most
misclassified data points corresponded to individuals that should have been classified as
individuals at risk, but were classified as not being at risk. This is encouraging for two reasons.
First, data in this study were collected from somewhat not traditional group of individuals (more
individuals in this group met the minimum physical activity requirements, which is usually not
the case). Thus, this particular data sample might not contain enough data points to train the NN
to correctly identify all at-risk individuals. We suspect that some training samples in the 5-fold
cross validation did not contain enough at-risk individuals to train the NN. We expect that
collecting additional data points that contain more at-risk individuals will improve the NN's
prediction of at-risk individuals.
Second, the current NN is able to identify almost perfectly the individuals not at risk.
Recall that the main reason for developing this automatic identification of at-risk individuals is
to target at-risk individuals by physical activities on college campuses. While the current NN
does not identify all at-risk individuals and will not contribute to targeting all at-risk individuals,
it will ensure that physically active individuals are not targeted and therefore, no resources will
be ìwasted'' on not at-risk individuals. Here, by resources, we consider items such as gift
certificates for participations in PA studies, individual attention by personal trainers conducting a
research, time spent on providing health and PA seminars, promotional offers through gym
memberships for inactive students, etc., which are often taken by individuals who do not clearly
satisfy the requirements of participation such studies, but rather take the advantage of
promotional offers to continue doing what they have already been doing. Thus, even though not
all inactive students would be reached by the currently developed NN, it is a starting point to
increase PA participation of students at health risk.
18
Automated identification of individuals at health risk
Expected Improvements in Neural Network Predictions
Even though the current NN predictions are acceptable and will allow college campuses
to target a large amount of students at health risk due to physical inactivity, further
improvements are possible. We are currently collecting more data from students at different
collegiate institutions. The following factors are expected to contribute towards better NN
training, and therefore an improved prediction rate.
First, a larger amount of data allows easier detection of patterns and relationships among
variables in a NN. Thus, collecting more data will allow for better training of the NN.
Second, a majority of the current data sample is of Hispanic origin. All the other
ethnicities are classified as non-Hispanics even though there are differences in PA attitudes
among, for example, Caucasian and African American individuals. However, currently these two
ethnic groups are considered as the same group. The newly collected data will add to wider
variety of demographic characteristics, which would aid predictions in the subgroups that are not
adequately represented in our current sample.
Third, we believe that students who do not major in health or sport related studies are
more likely to fall into the at-risk category than students majoring in health and sports studies.
Since majority of the current sample contained students that are not expected to be at health risk,
adding data points from students that are at risk will help train NN. The newly collected data will
contain more information from students at risk, and will allow a better training of NN in at risk
cases.
Fourth, a more objective assessment of the physical and psychological health of each
individual is preferable. The current sample relies on self-evaluation of one's health. However,
since not every person has same goals, the reported physical and psychological health might not
be consistent. For example, if a person weighted 220lbs a year ago, and currently weights 200lbs,
this person might feel good about his/her physical health even though this person might still be
overweight. While reports of this type are not expected to happen often and should not
drastically harm machine learning when a large amount of data is available, this type of report
might be harmful in our relatively small sample. A more objective assessment of the PA could be
obtained by combining facts such as the height, weight, and body mass index with the
individual's subjective perception.
Finally, a more objective evaluation of physical activities is needed in order to correctly
determine whether each person satisfies the minimum PA requirements as set by AHA and
ACSM. The current classification is obtained based on an individual's PA within the last seven
days and his/her subjective perception on the intensity of the activity (i.e., whether an exercise is
moderate or vigorous intensity). For example, while running at 6 mph might be considered as
vigorous PA by a person who does not exercise often, it would not be considered vigorous
intensity by an individual who satisfies the minimum PA requirements. Thus, collecting facts
(e.g., the length, time, and incline level of a run) along with a person's perception of the intensity
would provide a more objective evaluation of physical intensity of an activity. Moreover,
collecting the information over at least a few weeks would show the consistency of the exercise
rather than relying on how physically active a person was in only seven days since inactive
persons generally greatly fluctuate in the weekly amount of exercise.
Recommendations for Future Research
The majority of general population is prone to health diseases that could be easily
prevented by regular PA. While most people are aware that PA is important for their health,
many individuals are not aware of how much PA is necessary to keep their bodies in good
health. People live with the idea that some exercise is better than none (and are therefore
19
D. Magoc et al.
satisfied by finding time for little exercise), but only a small percent of individuals is aware that
they do not exercise enough to reduce the chance of diseases, such as heart attack and high blood
pressure.
The amount of PA drastically drops from high school to college and beyond. Therefore, it
is of high importance to target the first year college students in promoting PA and spreading
awareness of its importance. Since physically active students are the ones who usually respond to
PA promotions on collegiate campuses, it is important to identify students who are under the risk
of inactivity and target these particular individuals in PA studies and promotion programs.
With larger amount of data, we plan to enhance the classifier to allow three output classes
(sufficiently physically active, not sufficiently physically active, and not physically active at all)
rather than only two classes as presented in this study. The first class would include individuals
that are clearly physically active on regular bases and are reaching the minimum PA
requirements. The second class would include individuals that are physically active to certain
extend, but not enough to meet the minimum PA requirements, and are therefore under the health
risk. The third class would include individuals that are not physically active at all, and are
therefore under a great health risk. Even though the last two groups both contain individuals
under health risk, the risks are at very different levels, and the individuals belonging to these two
classes certainly need different care and motivation to increase their physical activities.
Once more data are collected and more diverse sample of population is reached, we will
train a final NN and develop a web-based tool to administer the questionnaire and immediately
identify individuals at risk of being not physically active enough. This program will be easily
accessible to everyone in order to improve well being of general population.
The developed method predicted accurately 77% of time. Even though the results are not
100% perfect, they show a great potential for quick identification of individuals at health risk
due to physical inactivity. Collecting a larger amount of data to use in the machine learning
approach as well as collecting data from wider variety of collegiate population will improve
already promising results of the proposed approach.
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Dunn, M. S., & Wang, M. Q. (2003). Effects of physical activity on substance use among college
students. American Journal of Health Studies, 18(2/3), 126-132.
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Heath, G. W., Thompson, P. D., & Bauman, A. (2007). Physical activity and public
health: Updated recommendations for adults from the American College of Sports
Medicine and the American Heart Association. Journal of American Heart Association,
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Magoc, D., Tomaka, J., & Thompson, S. (2010). Overweight, obesity and strong attitudes:
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population. Health Education Journal, 69(4), 427-438.
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Automated identification of individuals at health risk
Mounton, C. P., Calmbach, W. L., and Dhanda, R. (2000). Barriers and benefits to leisure-time
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Submitted 22 April, 2011
Accepted 15 June, 2011
21
EXERCISE AND QUALITY OF LIFE
Review article
Volume 3, No. 1, 2011, 23-29
UDC 575.113:612.74
CANDIDATE GENES IN THE FIELD OF EXERCISE GENOMICS
Vladimir Gali„
Department of Physiology
Medical faculty Novi Sad
Abstract
Skeletal muscle is extremely adaptable to various stresses which can be placed upon it. In
spite of importance of skeletal muscles, little is known about genetic factors which demonstrate
high influence to muscle size, function, strength and adaptation to various environmental factors.
Because endurance performance is a multifactorial trait, the list of candidate genes which could
account for human variation in related phenotypes is extensive. One of the first characterized and
most frequently studied genetic variant is a polymorphism in the angiotensin converting enzyme
I gene. The ACTN3 gene is the first structural skeletal muscle gene with a relation between its
genotype and elite sprinterí performance. Nevertheless, current genetic testing cannot provide an
extra advantage over existing testing methods in determining sports selection in young athletes.
The main challenge still remains to identify other, complex polygenetic variants and their
interactions with environmental factors which could provide benefit in the sports selection and
existing talent identification.
Keywords: exercise genomics, genetic polymorphism, muscle tissue
Introduction
Muscle tissue constitutes approximately 30% of body mass, it is metabolically very
active with high turnover of energy and is capable of efficient response to different
environmental stimuli. Skeletal muscle is extremely adaptable to various stresses which can be
placed upon it. These adaptations can be either positive, such as tissue growth, extreme athletic
performance or reparation of an injury, or negative, such as decline in mass and function over the
years of disuse or disease. Muscle strength is one of the most important determinants of oneís
functional ability and can influence some other tissues, like bone tissue by maintaining its
Corresponding author. Department of Physiology, Medical faculty Novi Sad. Hajduk Veljkova 3, 21000 Novi Sad.
E-mail: galic.ns@gmail.com
© 2010 Faculty of Sport and Physical Education, University of Novi Sad, Serbia
V. Gali
density throughout a lifetime. In spite of such importance of skeletal muscles, little is known
about genetic factors which demonstrate high influence to muscle size, function, strength and
adaptation to various environmental factors. Besides that, there is a diversity of information in
literature related to heritability of muscle characteristics. According to research of Bouchard and
his coworkers, whose main goal was to review all known genetic loci related to physical
performance or health-related fitness, there are more than 200 autosomal chromosome genes,
seven genes on the X chromosome and 18 mitochondrial genes that have been shown to
influence fitness and performance phenotypes (Bouchard et al., 2008). The physical performance
human phenotypes include cardio-respiratory endurance, muscle strength and exercise
intolerance. On the other hand, the health-related fitness phenotypes could be grouped in several
categories: exercise heart rate, blood pressure, body composition, insulin and glucose
metabolism, blood lipid and haemostatic factors (Bouchard et al., 2008). Despite all up-to-date
published information, majority of studies cannot establish a definitive relationship between
genotype and phenotype. The main reason for this uncertainty is small effect of a particular gene
on fitness or health-related traits and as a consequence, in order to achieve a significant ratio, it is
necessary to have above 1000 cases with as many controls. On the other hand, if the subjects are
examined in well-controlled laboratory conditions the sample size could be lower. However,
obtained results should be interpreted cautiously until other similar studies confirm initial
findings and assumptions.
Heritability of performance and health-related characteristics
One of the first strong evidence for a genetic influence on physical performance was
obtained from studies which compared related individuals with unrelated subjects in order to
discover heritability for several aerobic and cardiac-related characteristics (MacArthur, 2005).
Generally, genetic factors are thought to determine 20-80% of changes in a range of traits related
to elite athletic performance (MacArthur, 2007). Researchers estimate that performance related
traits have heritability values of approximately 50% for maximal oxygen uptake (VO2 max), 42-
46% for stroke volume and cardiac output during sub maximal exercise, 40-50% for muscle fiber
type proportions, and 67% for explosive muscle power (MacArthur, 2004). Considerable genetic
effects have been discovered for measures of skeletal muscle strength and performance, such as
muscle adaptation to endurance exercise
(Hamel et al.,
1986) or anaerobic capacity and
explosive power (Calvo et al., 2002). Interestingly, heredity of relative proportions of skeletal
muscle fiber types is considered to be between 40% and 50% (Simoneau & Bouchard, 1995).
These and studies similar to them will initiate more research into the area of human performance
genetics in order to discover favorable blend of genes, that are conducive to an athleteís specific
discipline (e.g. sprinting or endurance running).
Candidate genes in elite athletes (ACE I/D and ACTN3 R577X polymorphisms)
Specific allelic variants of the ACE and ACTN3 genes are known to produce favorable
traits with respect to athletic performance. These two genes were chosen, based on current
literature references, because they have opposing effects in the human body; variants of the ACE
gene are assumed to express bigger advantage in endurance activities, whereas, variants of the
ACTN3 gene are considered to present an advantage to power athletes, who require short surge
of intense strength and power.
ACE I/D polymorphism
Because endurance performance is a multifactorial trait, the list of candidate genes which
could account for human variation in related phenotypes is extensive. One of the first
characterized and most frequently studied genetic variant is a polymorphism in the angiotensin
converting enzyme I gene (ACE) (MacArthur & North, 2005). Specific allelic variants of the
ACE gene are known to produce favorable traits with respect to athletic performance. ACE is a
24
Exercise genomics
part of renin-angiotensin system which represents a hormonal cascade that regulates
cardiovascular function (Baudin, 2002). This pathway starts with the production of renin, in
kidneys, which transforms inactive angiotensinogen to angiotensin I. Second step is related to the
effect of ACE on angiotensin I and the result is generation of biologically active angiotensin II,
which is a strong vasoconstrictor and, in addition, it stimulates renal sodium reabsorption and
aldosterone production (Pescatello et al., 2006). A functional polymorphism of gene that codes
ACE is the insertion (I) and deletion (D) polymorphism which depends on the presence or
absence of a 287 amino acid base pairs on autosomal chromosome 17 (Pescatello et al., 2006).
This variation has given three ACE ID genotypes: II, ID and DD and their distributions in a
white people population are approximately 25% for II, 50% for ID and 25% for DD genotype
(Barley, Blackwood & Carter, 1994). The D allele of this polymorphism is related to higher
serum and tissue ACE activity which can result in greater production of angiotensin II and
aldosterone as well, increased sodium reabsorption and increased vascular smooth muscle
growth (Williams et al., 2005; Williams et al., 2004; Myerson et al., 1999). This allele is more
common in muscle strength and power athletes and it is associated with a superior muscle size
and strength response to exercise training (Hagberg et al., 1998; Montgomery et al., 1999). The I
allele is more present in endurance athletes, such as distance runners, rowers and mountaineers
and is associated with a prolonged cardiovascular response to endurance training. Lower ACE
activity in both serum and tissues is present in people with the I allele compared to the D allele
(Danser et al.,
1995; Rigat et al.,
1990). Several other studies have shown a significant
association between ACE genotype and elite athlete status. Montgomery et al. reported an
increased frequency of the I allele in 25 British mountaineers compared to 1906 sedentary
controls (Montgomery et al., 1998). On the other hand, higher frequency of the D allele was
found in 35 elite short-distance swimmers and such findings suggested that these two alleles of
ACE I/D polymorphism have dissimilar effects on performances of elite athletes (Woods et al.,
2001). On the contrary, Rankinen and coworkers (2000) published results of 192 males elite
endurance athletes compared with
189 sedentary controls and there was no difference in
genotype frequencies between these two groups. In addition, one more study has shown the lack
of physiological explanation for any association between the endurance-related cardiorespiratory
phenotypes and the ACE polymorphisms. In summary, data from the HERITAGE Family Study
do not support the concept that genetic variation at the ACE locus is a major contributor to the
cardiorespiratory endurance-related phenotypes in the sedentary state in healthy Caucasian
people (Rankinen et al., 2000).
Relation of genetic variants of ACE gene with athletic performance
Several mechanisms could explain how ACE expression might influence athletic
performance. Generally, cardiorespiratory function, with maximal oxygen uptake which is a
solid predictor of endurance performance, is related to the effect of ACE genotype. As
previously mentioned, a person with the I allele has reduced ACE serum and tissue levels and its
activity. This allele is thought to be a favorable mutation because lower ACE activity leads to
less vasoconstriction and thus an increased delivery of oxygenated blood to the working muscles.
Moreover, individuals with the I allele or the II (homozygote) genotype have greater advantage
in endurance activities, such as running, cycling, and swimming, where demand for oxygen is
crucial. A feasible explication for such findings comes from a study by Zhang and coworkers,
who showed that the ACE I allele is related with higher mass of type I (slow twitch) muscle
fibers in a person (Zhang et al., 2003). Slow twitch fibers acquire energy for their metabolism
from aerobic sources and they are fatigue-resistant at relatively low velocities of contraction. On
the other hand, the D allele is associated with the expression of type IIa and IIb (fast twitch)
fibers which are more efficient in power and strength performance and less fatigue resistant.
Nonetheless, there is some contradictory evidence regarding the effect of the ACE gene on
endurance and power performance. In some studies, researchers have shown that in older adults
25
V. Gali
there was no association between ACE gene and physical characteristics as yet (Rankinen et al.,
2000; Frederiksen et al., 2003).
In spite of all confusing results, the ACE gene continues to be the most extensively
studied of any gene related to athletic performance, with huge amount of articles examining the
effect of I/D polymorphism on fitness and performance features. The opposite findings amid
many studies illustrate the complexity of genetic studies of complex characteristics. Literature
results must be observed thoroughly before one can certainly conclude about the effect of ACE
variations on performance phenotypes. For a research to be successful, it is of the utmost
importance to have collaborative effort through data sharing among multicenter research
facilities.
ACTN3 R577X polymorphism
The ACTN3 gene and is nonsense R577X polymorphism has generated noticeable
interest in the past few years. This is the first structural skeletal muscle gene with a relation
between its genotype and elite sprinterí performance (MacArthur & North, 2007; Yang et al.,
2003). The alpha-actinins are a family of actin-binding proteins which play a main role in the
maintenance and regulation of the cytoskeleton inside a muscle fiber (Blanchard et al., 1989). In
mammals, there are four alpha-actinins. Skeletal muscle has highly expressed alpha-actinin-2
and alpha-actinin-3 as major structural parts of the contractile elements at the Z-line, which is an
important structure within the sarcomere and its function is to provide structural support for the
transmission of force when the muscle fibers are activated. (Virel & Backman, 2004; Dixson et
al., 2003; Beggs, Byers & Knoll, 1992). The function of alpha-actinins is to connect with actin
filaments, sustain the order of myofilaments and coordinate myofilament contraction by
stabilizing the contractile apparatus (Yang et al., 2003). Alpha-actinin-3 is expressed only in fast
glycolytic skeletal muscle fibers (Mills, Yang & Weinberger, 2001). Researchers believe that
alpha-actinin-3 may be optimized in order to decrease the damage which could be induced by
eccentric muscular contractions (Yang et. al, 2003). This is extremely important during forceful
contractions, which are abundant in fast twitch muscle fibers. Astonishingly, an estimated one
billion humans worldwide are completely deficient in alpha-actinin-3, because of homozygosity
for a common nonsense polymorphism (R577X) in the ACTN3 gene (MacArthur et al., 2007;
North et al., 1999). The absence of this protein is not related to a disease phenotype, since other
proteins can counterbalance, although not completely, its lack in fast twitch skeletal muscle
fibers. Moreover, the absence of this protein structure in skeletal muscles has been suggested to
block the performance of fast twitch fibers, which are important for rapid, powerful contractions.
A usual genetic variation in the ACTN3 gene results in the replacement of an arginine
(R) with a stop codon (X) at amino acid 577 (R577X). The R577 allele is the normal allele with
functional alpha-actinin-3, whilst the 577X allele has an amino acid sequence change which
produce nonfunctional protein alpha-actinin-3. This polymorphism results in the XX, RX and
RR genotype. Representation among healthy white subjects is 18, 52 and 30%, respectively
(Yang et al., 2003). It has been noticed that the recurrence of the ACTN3 577RR genotype was
higher among elite sprinters when comparing with endurance runners or control participants
(Niemi & Majamaa, 2005). This finding can suggest that the presence of 577RR allele might
have a beneficial effect on skeletal muscle function during powerful contractions.
According to the literature suggestions, that alpha-actinin-3 performs important functions
in fast twitch muscle fibers, it was expected to predict that there might be fine differences in
skeletal muscle function among humans with different ACTN3 R577X genotype. Two alleles of
ACTN3 gene may provide usefulness for different type of muscle performance. The R allele,
which generates a functional alpha-actinin-3 protein, appears to favor strong muscle contraction,
while on the other hand, the X allele might somehow provide advantage for slow and efficient
muscle performance.
26
Exercise genomics
Future perspectives and research activities
During last two decades, an increasing level of competition in different sports has caused
athletes to strive to sport results and success at no cost. Studies of the importance of genomic
factors in the responses and adaptations of performance and health-related traits to exercise have
increased during period of last 10 years (Bouchard et al., 2008). Unfortunately, along with recent
developments in gene manipulation, there is a growing concern that researchers and elite athletes
could be able to abuse this innovative technology in order to ìengineerî individuals who could
permanently express desirable genes for a peak athletic performance. Moreover, everyone is
worried that ìgene dopingî would become a reality one day and, as a result, sports competitions
could lose their true meaning and significance among athletes. However, successful
identification of genes, which control physical performance characteristics, could benefit
researchers to determine whether an athleteís genotype has been artificially changed in order to
express advantageous genotypes with increased endurance capabilities or muscular strength.
Furthermore, the process of supreme talent identification could be possible by the
discovery of genetic variants which has strong effect on athletic performance. A routine genetic
analysis could be added to the existing set of physiological, biochemical and psychological tests
which are the current basis for selecting skillful young athletes for further training. However,
there is still no solid evidence that any of these variants have predictive value for prospectively
identifying potential elite athletes. Only relying on large and prospective cohort studies,
researchers could be able to evaluate the true values of genetic testing. Several genetic factors,
for which positive associations have been reported in elite athlete cohorts (including the ACE
I/D and the ACTN3 R577X polymorphisms), are not sufficient to tell if someone can become an
elite athlete. However, genomic factors may influence in which sport an elite athlete can
compete successfully. In the case of ACE and ACTN3, one allele combination appears to favor
performance in sprint or power events (the ACE D and ACTN3 R allele), whereas the other
benefit the ability to strive in endurance sports (the ACE I and ACTN3 X allele). This can lead to
conclusion that some genetic factors might not be useful in predicting if a young, amateur athlete
has elite potential. On the contrary, it may help to guide the choices of young athletes and their
coaches in determining appropriate event and training which would be best suited for them.
Nevertheless, current genetic testing cannot provide an extra advantage over existing
testing methods in determining sports selection in young athletes. The main challenge still
remains to identify other, complex polygenetic variants and their interactions with environmental
factors which could provide benefit in the sports selection and existing talent identification.
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Submitted 12 April, 2011
Accepted 20 May, 2011
29
EXERCISE AND QUALITY OF LIFE
Research article
Volume 3, No. 1, 2011, 31-40
UDC 796.342-053.6:796.015.52
THE EFFECT OF STRENGTH TRAINING ON TENNIS SERVICE
PERFORMANCE OF JUNIOR TENNIS PLAYERS
Paraskevi Malliou (1), Dimitris Papadimitriou (1), Vasiliki Malliou (2), Anastasia Beneka (1),
Georgios Pafis (1), Christos Katsikas (2) Stiliani Roka (1) , and Ioannis Fatouros (1)
(1)Department of physical education and sport science
Democritus University of Thrace, Komotini, Greece
(2) Department of physical education and sports science
National and Kapodistrian University of Athens, Greece
Abstract
The purpose of the present study was to evaluate the effect of a 7-week shoulder specific
strength training program additional to tennis training sessions on the service velocity of junior
tennis players. Initially 60 junior tennis players (29 boys and 31 girls) with at least 2 years of
tennis experience and never followed a routine strength program, volunteered to participate in the
study. All the subjects followed a regular tennis training session (75 min). The subjects were
randomly assigned into three groups: i) group-A, which practiced in addition 15 min service after
the tennis session, ii) group-B which practiced a 7-week strength training program (15 min per
session, 3 times per week) after the tennis session, and iii) a group-C, control group, which did not
follow any extra programs after the tennis session. Two-way repeated measures analysis of
variance was performed to detect differences in each group before and after the experimental
period. The independent variable was the group (two experimental groups with different training
protocol and the control group with only tennis training), and the repeated factor was the ìtestî
(pre and post test, before and after the training period). Statistical significance was accepted at
p<.05. It was measured an overall significant quantitative improvement on service performance
while, the qualitative findings showed significant improvement in service technique only in group
A.
Keywords: tennis, shoulder strength program, service, service velocity
Introduction
Tennis skills are composed by complex movements.One of these skills, service
performance, is a result of the effective transfer of torque production that depends on technique,
muscle strength and flexibility (Cohen, Mont, Campbell, Vogelstein, & Loewy, 1994; Mont,
Corresponding author. Department of Physical Education and Sport Sciences, Democritus University of Thrace,
Campus 69100 Komotini, Greece, E-mail: pmalliou@phyed.duth.gr
© 2010 Faculty of Sport and Physical Education, University of Novi Sad, Serbia
P. Malliou et al.
Coen, Campbell, Gravare, & Mathur, 1994). An important factor for tennis service is the ability
to exert high muscular force and power to the racquet. Therefore, the ball speed in tennis service
is generated by the speed of the racquet immediately before the impact (Gordon, & Dapena,
2006). Gordon and Dapena (2006) measured the contributions of the motion of body segments to
the racquet head speed during the tennis service and suggested that among the main contributors
were the external shoulder rotation, wrist extension and twist rotation of the lower trunk, twist
rotation of the upper trunk relative to the lower trunk, shoulder abduction, and wrist flexion.
Also, Gordon and Dapena (2006) suggested that there was a positive contribution of shoulder
internal rotation shortly before the impact with the ball.
In addition, it has been shown that the internal rotators of the dominants shoulder in
tennis players produce greater torque than those who don't play tennis (Ng, & Kramer, 1991).
The internal rotators of the dominant shoulder are typically stronger of the non-dominant
shoulder in tennis players (Chandler, Kibler, Stracener, Ziegler, & Pace, 1992). Also, tennis
players tend to have muscle strength imbalance of internal versus external rotators (Mont et al.
1994; Chandler et al. 1992; Ellenbecker, Davies, & Rowinski, 1988). Although muscle strength
plays a key role to the overheads sports performance
(Wooden, Greenfield, Johansonm,
Litzelman, Mundrane, & Donatelli, 1992; Bartlett, Storey, & Simons, 1989; Perry, 1983) there
are only a few studies evaluating the effect of strength training on shoulder rotators muscles and
the related functional performance (Treiber, Lott, Duncan, Slavens, & Davis, 1998; Mont et al.
1994). It has been suggested that the upper and lower strength in a tennis player can be
extremely useful not only in the enhancement of athletic performance but also in the prevention
and rehabilitation of injuries (Ellenbecker, & Roetert, 2004). More specific Treiber et al. (1998)
showed that strength training for four weeks with Therabands and light weight drumbells appears
to increase service velocity of college tennis players.
The purpose of the present study was to evaluate whether an additional 7-week shoulder
specific strength training program would significantly increase service velocity of junior tennis
players compared to the group which practice only service in addition to tennis training sessions.
Method
Experimental Approach to Problem
Service in tennis is based on complex motor movement and depends on technique,
muscle strength and flexibility. The purpose of the present study was to evaluate the effect of
shoulder specific strength training program additional to tennis training sessions on the service
velocity of junior tennis players in order to define the need of strength exercise for junior tennis
players.
Subjects
Initially 60 junior tennis players (29 boys and 31 girls) from three different Greek tennis
clubs volunteered to serve as subjects. All subjects practiced tennis with a coach for at least 2
years (two to three times per week), and never followed a routine strength. All the subjects
participated in a regular tennis practice session (75 min). Each session included warm-up, drills
practicing ground strokes and volley, as well as drills practicing tactics of the games for 60 min
and 15min practicing service. The subjects were randomly assigned into three groups: i) group-
A, which practice in addition 15 min service after the tennis session, ii) group-B which practice a
7-week strength training program (15 min per session, 3 times per week) after the tennis session,
and iii) a group-C, control group, which did not follow any extra programs after the tennis
session.
32
Effects of strength training on tennis service
Four of the subjects failed to complete the study: three (two experimental and one control
subject) participated in less than 75% the sessions, and one subject could not complete the study
because of an injury. The data from these four subjects were dropped from the study.
The subjects ranged from 13 to 14 years old (group-A 13.3 ± 1, group-B 14.2 ± 0.8, and
group-C 14.4± 0.7, M±SD respectively), had an average weight for group-A 45.75 ± 7.74 kg,
group-B 38.33 ± 8.14 kg, and group-C 41.83 ± 7.16 kg, M±SD respectively and an average
height for group-A 153.25 ± 7.2 cm, and group-B 144.4 ± 9.6cm, and group-C 145.3 ± 5.8 cm,
M±SD respectively.
All players were right handed-dominant. Subjects were evaluated pre and post training
program for service performance: a) ball speed (quantitative evaluation) and b) technique of the
service (qualitative evaluation). In addition, the range of motion and the strength of the internal
and external rotation of the shoulder were evaluated.
Quantitative service evaluation
The service performance was conducted on an indoor tennis court. Each subject was
instructed to perform service from the baseline (0-40 m to the right of the center mark) with new
Wilson USA Open balls, with maximal velocity and control until a total of five balls landed in
the left service box. No limit was placed on the number of the attempts. If the player did not
succeed after 10 efforts had a rest break for 3-4 min. The average velocity of service was the
mean of the best three. Ball velocity was assessed in (km/h) with a calibrated radar gun (Jug
Company, 2000). The radar gun was positioned 5 meters behind the baseline, opposite to the
subject, at a height 2 meters (Jug Company, 2000). Before the evaluation the subjects played
tennis for 10-12 min and had 10-15 service from the baseline for warm-up.
Qualitative service performance evaluation
The subjects underwent service technique evaluation by three experienced tennis coaches.
Before the beginning of the procedure, the coaches were informed about the procedure and the
goals of the study. A pilot procedure has been followed, where the three coaches watched (2
times in 10 days) a videotape with service skills in similar conditions with the present study. The
correlation coefficients between the coaches (r = .92) and between the trials (r = .91) were high.
No player was found to have faulty technique and thus no player was excluded from the
participation in the study. There were observed six technical elements in service motion: 1) the
basic position, 2) the grip, 3) the body orientation, 4) the back swing 5) the touch with the ball,
6) the follow through (Eason, Smith, & Plaisance, 1989; Magill, 1985). When one of those
elements was missing, the score was 0, while it was 1 when it was appeared (Mcpherson, &
Thomas, 1989). Ten trials were assessed and the sum of the score for each element was recorded.
The score for the technique evaluation was computed by adding the scores for all the technical
elements for 10 trials.
Shoulder rotator strength assessment
The subjects underwent shoulder rotator strength evaluation that is usually used by
exercisers and is also accepted by many authors uses the (Brzycki, 1993; Mayhew, Ware, &
Rinster, 1993) equations. This is an indirect method of assessing maximal strength that is based
on the maximal number of repetitions that the exerciser accomplishes. The testing procedure that
was followed by Giannakopoulos, Beneka, & Malliou
(2004).
is now described. Each
participant is positioned supine holding a dumbbell with stabilization straps secured at the pelvis
and midthoracic levels. The assessed extremity is positioned on a table with stabilization straps
also secured at humeral level. The test is initiated with the arm in 90° of external rotation. To test
the internal rotation movement, the trial is initiated with the arm in 90° of external rotation.
33
P. Malliou et al.
Respectively, when the external rotation is tested, the trial is initiated with the arm in 90° of
internal rotation. The participants try to complete the maximal number of repetitions (e.g., 12
repetitions) with a dumbbell of their choice (e.g., 2.5kg). According to Brzyckiís and Mayhewís
equations, the maximal number of repetitions for a given weight corresponds to a specific
coefficient (e.g., 0.75). Dividing the dumbbellís weight (2.5kg) by that coefficient results in a
number indicating maximal strength (e.g., 2.5/0.25 = 3.33). The result, in this case 3.33, is
considered to be the maximal strength of the muscle group tested. Similarly, the maximal
strength of the other muscle group is assessed (Beneka, Malliou, Giannakopoulos, Kyrialanis, &
Godolias, 2002; Giannakopoulos et al. 2004; Kibler, Chandler, & Livingston, 1996).
Range of motion evaluation of shoulders rotator cuff
The testing position of the participant for the internal rotation was supine with the arm
abducted to
90degrees, the elbow flexed to
90degrees and the forearm pronated and
perpendicular to the table. A towel was placed under the humerus to bring the arm into the
scapula plane. The goniometer was aligned along the ulnar styloid process and perpendicular to
the table.
The testing position of the participant for the external rotation was supine, with the arm abducted
to 90deg, the elbow flexed to 90deg and the forearm pronated and perpendicular to the table. A
towel was placed under the humerus to bring the arm into the scapula plane. The goniometer was
aligned along the ulna to the ulnar styloid process and perpendicular to the table (Andrews,
Harrelson, & W. K., 2004).
Service training program (group-A)
The participants in group-A followed a service training session (15 min per session, 3
times per week) after the tennis practice. The service session included a) toss practice, and b)
serve practice with 2 targets (ìTî and diagonal) from both sides (deuce and advantage).
Shoulder strength intervention programs (group-B)
The subjects from group B participated in a strength training program, 6 exercises for
both shoulders (left and right), 15 min, 3 times per week for 7 weeks. (From 0 to the 3rd week
performed 2 sets of 10-15 repetitions with 0.5-1.0 kg free weights. After the 3rd week the
program progressed to 3 sets with the same repetitions and increase in the free weights by 0.5 kg
(Table 1). There was at least one day rest between practice days.
The subjects were instructed to breathe normally. The subjects from both groups were
given detailed written, verbal and physical instructions by the trainer for the various exercises.
Before the beginning of the intervention period each subject had to demonstrate proper technique
to the trainer.
Post assessments
Within 2 days, after the completion of the 7 ñweek intervention period, the follow up
assessment for all groups was begun (serving velocity and technique).
Statistical Analyses
Means and standard deviations were calculated for all depended variables. Two-way
repeated measures analysis of variance (ANOVA) (2X3, tests by different training protocol) was
performed on depended variables to detect differences in each group before and after the
34
Effects of strength training on tennis service
experimental period. The independent variable was the group (two experimental groups with
different training protocol and the control group with only tennis training), and the repeated
factor was the ìtestî
(pre and post test, before and after the training period). Statistical
significance was accepted at p<.05.
Results
Two-way repeated measures analysis of variance was used to test the differences in all
depended variables before and after training period for each group. The independent variable
was the group (two experimental groups and one control group), and the repeated factor was the
test
(before and after the training period). Tables 1 and 2 illustrate the means and standard
deviations for external and internal rotation range of motion values for all the groups.
Table 1
Means and standard deviations for external rotation range of motion values for all the groups
Range of motion / External Rotation
PreTest
PostTest
F
Groups
M
SD
M
SD
Control
68.92
10.6
71.83
7.71
.706
Service
61.50
15.5
86.75
17.2
52.9***
Strength/Service
73.5
14.5
79.08
13.3
2.58
F
14.17***
*p<.05, **p<.01, ***p<.001
Table 2
Means and standard deviations for internal rotation range of motion values for all the groups
Range of motion / Internal Rotation
PreTest
PostTest
F
Groups
M
SD
M
SD
Control
49.58
16.03
58.25
22.61
3.172
Service
50.75
8.27
82.75
19.25
43.242***
Strength/Service
44.25
8.92
54.83
14.11
4.730*
F
7.086**
*p<.05, **p<.01, ***p<.001
For external rotation range of motion test, the results showed (Table 1) that all the groups
improved their performance between the two tests but this improvement was significant only for
the ìService Groupî F(1,33)=43.24, p<.001
For internal rotation range of motion test, statistical analysis showed that all the groups
improved their performance between pre and post test but in a different way (F (2, 33) =7.086,
p<.05). Sidak Multiple Comparison test was performed to test the differences in performance for
35
P. Malliou et al.
each group. The results showed that there was a significant performance improvement in the
internal rotation range of motion test only for the experimental groups, and not for the control
group (Table 2).
Tables 3 and 4 illustrate the means and standard deviations for external and internal
rotation strength values for all the groups. For strength performance in external rotation
movement statistical analysis showed that all the groups improved their performance between
pre and post test but in a different way F (2, 33) =8.012, p<.05. Sidak Multiple Comparison test
was performed to test the differences in performance for each group. The results showed that
there was a significant performance improvement in the external rotation strength performance
only for the ìService Groupî F (1, 33) = 19.79 the ìStrength Service Groupî F (1, 33) =38.009
and not for the control group.
For strength performance in internal rotation movement (Table 4) statistical analysis
showed that all the groups improved their performance between pre and post test but in a
different way F(2,33)=7.98, p<.05. Sidak Multiple Comparison test was performed to test the
differences in performance for each group. The results showed that there was a significant
performance improvement in the internal rotation strength performance only for the ìStrength
Service Groupî F (1, 33) =15.96 and the ìService Groupî F (1, 33) = 4.25 and not for the others.
Table 3
Means and standard deviations for external rotation strength values for all the groups
Strength / External Rotation
PreTest
PostTest
F
Groups
M
SD
M
SD
Control
4.20
.57
4.45
.57
5.93
Service
4.47
.55
4.85
.69
19.79**
Strength/Service
3.98
.66
4.50
.65
38.009***
F
8.012*
*p<.05, **p<.01, ***p<.001
Table 4
Means and standard deviations for internal rotation strength values for all the groups
Strength / Internal Rotation
PreTest
PostTest
F
Groups
M
SD
M
SD
Control
4.90
.79
5.10
.95
2.33
Service
6.01
1.36
6.27
1.52
4.25
Strength/Service
4.54
.98
5.06
1.09
15.96***
F
7.98*
*p<.05, **p<.01, ***p<.001
36
Effects of strength training on tennis service
Tables
5 and 6 illustrate the means and standard deviations for quantitative
and
qualitative service evaluation test for all the groups.
Table 5
Means and standard deviations for quantitative service evaluation test for all the groups
Quantitative service evaluation test
PreTest
PostTest
F
Groups
M
SD
M
SD
Control
47
12.5
48.17
12.23
.943
Service
53
9.31
60.83
10.89
42.512***
Strength/Service
44.33
14.63
52.08
17.35
41.612***
F
10.137***
*p<.05, **p<.01, ***p<.001
Table 6
Means and standard deviations for qualitative service evaluation test for all the groups
Qualitative service evaluation test
PreTest
PostTest
F
Groups
M
SD
M
SD
Control
41.66
6.14
39.16
5.1
1.40
Service
48.33
4.34
55.00
3.74
10.1*
Strength/Service
45.83
7.4
49.16
5.96
2.50
F
4.848**
*p<.05, **p<.01, ***p<.001
For the Quantitative service evaluation test (Table 5), results showed that all groups
improved their performance between pre and post test but in a different way (F (2, 33) =10.137;
p<.001). Sidak Multiple Comparison test was performed to test the differences in performance
for each group. The results showed that there was a significant performance improvement in the
quantitative service evaluation test for the experimental groups between pre and post tests, but no
significant improvement was found for the control group.
However, difference in service performance was found only for experimental groups for
the qualitative evaluation test F (2, 33) =4.848, p<.05, and this improvement was significant only
for the Service Group (F (1, 33) =10.01, p<01) and not for the Strength Service Group (F (1, 33)
=2.5, p>.05) (Table 6).
37
P. Malliou et al.
Discussion
The present study evaluated the service performance in young tennis players with
quantitative and qualitative evaluations. It was concluded an overall significant quantitative
improvement on service performance while, the qualitative findings showed significant
improvement in service technique only in group A. These findings support the significant impact
of the technique in tennis performance. It is evident that for this age group with at least 2 years
tennis practice, improvement only in the technique can increase significantly the service
performance. As the player developed and the technique reached at a high level then, strength
and flexibility are more important physical abilities to be developed (Elliot, Fleisic, Nicholls, &
Escamilia, 2003).
In the present study both groups (A and B) increased average speed of service. Previous
investigations have been shown that strength training can increase athletic performance in tennis
(ITF). More specific, studies on tennis service showed low correlation between ball speed and
isokinetic strength of the upper body (Cohen et al. 1994; Ellenbecker, & Roetert, 1999). The ball
speed during service maybe a combination of several factors such as technique, coordination,
flexibility and strength. Cohen et al. (1994) found low correlation between shoulder internal
rotation and ball speed. The present study showed that although only group B had significant
increase in strength of internal rotation, both groups (A and B) increase significantly the range of
motion in the internal rotation. Furthermore, group A had greater increase in the range of internal
rotation compared to group B. This evidence suggests that strength training program may be an
important factor in reassuring shoulder stability. Consecutively, a smaller increase in range of
motion in group B may be related to less increase of ball speed compared to group A.
The present study showed that both groups (A and B) increased significantly the strength
of external rotation muscles, but only group A showed significant increase in the range of motion
of external rotation muscles. Thus, it is suggested that for the external rotators muscles, strength
training program restricted the improvement of range of motion, revealing again the important
role of strength training in keeping joint stability. Gordon, & Dapena (2006) measured the
contributions of the motion of body segments to the racquet head speed during the tennis service
and suggested that among the main contributors were the external shoulder rotation.
Both groups (A and B) improved significantly the quantitative performance of the
service. The findings from the strength intervention program in the present study are in
agreement with the study by Treiber et al. (1998), although, this study had different age group
(college tennis players) and different duration of the program (4 weeks). The improvement in the
present study ranged from 44.33±14.63 to 52.08±17.35 km/h in average service velocity. Others
studies (Mont et al. 1994; Ellenbecker et al. 1988) found also increase in service performance.
The average and peak service velocity increased 7.9 % and 6.0 % respectively (Treiber et al.
1998). These increases are less than the finding of Mont et al. (1994) study and Ellenbecker et al.
(1988) study. These discrepancies of the results may due in the different age groups and the
designs of the studies, such as the duration of the intervention program, method of training and
the intensity of the program.
Previous studies (Cohen et al. 1994; Ellenbecker, & Roetert, 1999; Pugh, Kovaleski,
Heitman, & Gilley, 2003) indicate a moderate correlation between upper body strength and ball
speed in the tennis service. This suggests that an absolute level of strength is necessary but not
sufficient for ultimate ball speed.
The present study showed that since service is complex movement and requires optimal
timing, coordination, and strength of many segments of human body, it is crucial to primary
develop the service movement skill for an efficient service performance.
38
Effects of strength training on tennis service
The findings of the present study suggest that for young athletes with at least two years
tennis practice improving technique can significantly increase tennis performance. As the athlete
is growing up and his technique reaches at a higher level, then strength and flexibility are more
important physical abilities to be developed.
The results of the present study also suggest that although only strength training can
increase the internal rotators strength; both strength training and service practice can increase
significantly the range of motion in the internal rotation. Furthermore, service practice in young
tennis players can better increase the internal rotators range of motion compared to strength
training. This evidence suggests that strength training program may be an important factor in
reassuring shoulder stability for young athletes. It is suggested also for the external rotators
muscles, strength training program restricted the improvement of range of motion, revealing
again the important role of strength training in keeping joint stability. Finally, both strength
training and service practice can efficiently improve the service ball speed.
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Submitted 25 January, 2011
Accepted 17 March, 2011
40
EXERCISE AND QUALITY OF LIFE
Research article
Volume 3, No. 1, 2011, 41-49
UDC 572.512-057.875:796.012.11
RELATIONS BETWEEN ANTHROPOMETRIC
CHARACTERISTICS AND LATENT DIMENSIONS OF
STRENGTH IN PERSONS OF ABOVE-AVERAGE MOTOR
ABILITIES
Milan Cvetkovi„, Damjan Jaköi„ and Dejan Orli„
Faculty of sport and physical education
University of Novi Sad
Abstract
Mere enrollment on the Faculty of Sport and Physical Education assumes that the
population has been selected according to several criteria. One of the most typical criteria is
motor development, hence students of sport and physical education might be treated as persons
of above-average motor abilities. Test battery of 17 anthropometrical tests and 14 strength tests
has been applied on the sample of 149 males, students of the Faculty of Sport and Physical
Education in Novi Sad. The purpose of this paper is to determine relations between
anthropometrical measures and latent dimensions of strength. Within the latent space of strength,
after Promax rotation of major components and based on KG criteria, three strength factors have
been isolated: static and repetitive strength, especially that of hands and trunk to a lesser degree,
explosive strength of legs, and explosive strength of arms. Finaly, three statistically significant
canonical correlations have been isolated. The first is that of explosive strength of arms having
negative correlation with all anthropometrical variables, the second is explosive strength of legs
which is in negative correlation with subcutaneous fat tissue of upper leg and triceps, but in
positive correlation with the measures of longitudinal dimensionality of skeleton, whereas the
third is static and repetitive strength of arms (and trunk to a lesser degree) being in negative
correlation with body height and leg length.
Key words: students/ static and repetitive strength/ explosive strength
Introduction
Anthropometric characteristics are the most obvious area within the bio-psycho-
sociological status of the human population. They are the manifestation of morphological
dimensions such as the constitution, body composition, structure or assembly as an organized
and relatively constant integrity of features relative to each other. This set is usually formed by
endogenous factors (internal) and to a lesser extent by exogenous (external, middle).
Corresponding author. Faculty of Sport and Physical Education, University of Novi Sad, Lov„enska 16, 21000
Novi Sad, Serbia. E-mail: cveksha@gmail.com
© 2010 Faculty of Sport and Physical Education, University of Novi Sad, Serbia
M. Cvetkovi et al.
Motor skills are usually defined as indicators of development level of the basic motion
dimensions of human that influence the successful realization of movement, regardless of
whether that skills are acquired through training or not. Motor ability, examined in this work -
strength, Zaciorski (1975) defines as the ability of man to overcome the external resistance, or to
confront him with straining of muscle.
The sample of respondents is comprised of persons of above average motor skills, in fact,
students of the Faculty of Sport and Physical Education. Mere enrollment on this kind of faculty
assumes that the population has been selected according to several criteria, including: the level of
biological development, the level of health development (injured or sick respondents do not even
take the entrance exam), the level of motor development and the level of intellectual and
conative development . One of the most typical criterion is exactly the motor development, and
hence it is mentioned above.
Researching of relationships between anthropometric characteristics and dimensions of
latent power in people of above average motor skills was conducted by numerous authors
starting from Kureli„, Momirovi„, Stojanovi„, äturm, Radojev„ and Viski„-ätalec (1975), and
their capital work, to the latest researches by Prûulj and Pelemiö (2010). These authors have
obtained relatively high correlation of areas mentioned.
The aim of this paper is to determine the relation between anthropometric characteristics
and latent dimensions of strength of this specific population.
Method
The sample of participants in this paper consisted of 149 male students of Faculty of
Sport and Physical Education from Novi Sad. The mean age of participants on the test day was
20.15 decimal years (± 0.83). All of the participants were clinically healthy and highly motivated
to participate, on the test day.
The battery of 17 anthropometric measures was applied on respondents, 15 measures that
are part of the International Biological Program (IBP) battery and two that are not, but the
authors felt that their use will contribute to better understanding of relations between studied
areas. Exactly as directed by IBP, measurements of anthropometric characteristics were carried
out.
According to factorial morphological model (Viski„-ätalec, 1974; Kureli„, Momirovi„,
Stojanovi„, äturm, Radojevi„, & Viski„-ätalec, 1975; Stojanovi„, Solari„, Vukosavljevi„, &
Momirovi„, 1975, etc..), the following measures were applied:
For evaluation of the longitudinal dimensionality of the skeleton: Body height, Arm
length and Leg length.
For evaluation of the transversal dimensionality of the skeleton: Diameter of the ankle,
Diameter of the knee joint and Diameter of the pelvis.
For evaluation of the body volume and weight: Body weight, Circumference of the
chest (middle), Circumference of the upper arm (stretched), Circumference of the
upper arm (during flexion and contraction), Circumference of the upper leg and
Circumference of the lower leg.
For evaluation of the subcutaneous fat tissue: Skin fold on the back (subscapular),
Forearm skin fold (triceps), Skin fold of the abdomen, Skin fold of the upper leg and
Skin fold of the lower leg.
42
Anthropometric characteristics and strength in students
For the evaluation of strength a battery of 14 motor tests was applied, which in previous
researches showed great reliability on the respondents of similar age and of similar life style.
Applied battery is part of a far more complex battery defined by Metikoö, Prot, Hoffman, Pintar
and Oreb
(1989) and based on its standardization, qualified measurers performed the
measurement.
The battery consisted of the following measuring instruments: Pull-ups, Lifting the trunk
in
30 seconds, Horizontal endurance on the back, Standing long jump, Deep squat for 30
seconds, Throwing a medicine ball while lying on the back, Endurance in a push-up,
Straightening of trunk, Standing high jump, Endurance under load in half-squat, Throwing a
medicine ball from the chest during spread leg sitting, Hanging while in pull-up position, Push-
ups and Standing triple jump.
Also, a detailed description and organizational details related to the measurement can be
found in Cvetkovi„ (2007).
As far as statistical processing, we applied the following statistical procedures:
For all variables that were used, the basic descriptive statistics were calculated. Then, the
variables which evaluated strength were factorized by rotating the initial matrix into a more
favorable OBLIVAX oblique solution (Momirovi„, 1998). In the paper by Momirovi„ (1999),
the behavior of different types of oblique factorial solutions was described, and was found that
OBLIVAX oblique rotation extracted latent dimensions with the most information and with
greatest representativeness, even compared to other oblique rotations like Orthoblique rotation
(Harris & Kaiser, 1964), Promax (Hendrickson & White, 1964) and Direct oblimin (Jenrich, &
Sampson, 1966) which were applied in the same paper. The number of statistically significant
factors was determined based on Intruder in the Dust (ITD) criterion (Momirovi„, 1998), which
is a relaxed PB criterion (ätalec and Momirovi„, 1971) and also represent a compromise between
the criteria with the hyper-factorization tendency (eg., KG (Kaiser, 1961)) and the criteria with
hypo-factorization (eg., Scree (Cattel, 1966)). Factors extracted in this way are latent dimensions
of power, and after extraction their definition followed. Relationships between the latent
dimensions of strength and anthropometric characteristics were determined by canonical
correlation analysis, while observing if the variables sets are well designed and which one was
better designed in the second set, was performed by redundant analysis.
43
M. Cvetkovi et al.
Results
Tables 1 and 2 show the basic descriptive statistics of variables.
Table 1
Basic descriptive statistics of anthropometric variables
VARIABLE
M SD
MIN
MAX
SKE
KUR
Body height (mm)
1816.26
62.996
1670
1975
.054
-.625
Arm length (mm)
798.32
36.171
717
899
.036
-.304
Leg length (mm)
1022.36
44.142
894
1134
-.068
-.010
Ankle diameter (mm)
70.99
3.895
62
85
.694
1.132
Knee joint diameter (mm)
100.22
4.324
91
113
.166
-.204
Width of the pelvis (mm)
286.68
16.600
255
345
.505
.534
Body weight (kg)
77.900
9.3314
54.6
123.8
.894
3.223
Chest circumference, middle (cm)
96.71
5.440
80
118
.399
1.762
Circumference of stretched upper arm (cm)
28.13
2.614
22
36
.677
.890
Circumference of bent upper arm (cm)
31.89
2.785
24
40
.468
.609
Upper leg circumference (cm)
56.23
4.358
45
74
.404
1.317
Lower leg circumference (cm)
36.74
2.400
32
44
.269
.099
Back skin fold (mm)
118.56
33.335
68
254
1.375
2.777
Triceps skin fold (mm)
91.02
32.100
28
190
.605
.092
Abdominal skin fold (mm)
131.31
51.240
52
300
.696
-.062
Upper leg skin fold (mm)
157.95
47.499
50
300
.195
-.289
Lower leg skin fold (mm)
96.82
39.948
40
240
1.083
1.054
Legend: M ñ mean, SD ñ standard deviation, MIN ñ minimal result, MAX ñ maximal result, SKE ñ skewness, KUR
- kurtosis
Based on the results from Table 1 it can be seen that the homogeneity of the sample is
present on all the variables, except for variables of Back skin fold and Lower leg skin fold where
some higher skewness results were observed, but nothing worrisome because it is not uncommon
that the values for subcutaneous fat are not normally distributed (eg Momirovi„, Hoöek, Prot and
Bosnar, 2003). Also, skewness is positive in all variables that assess the subcutaneous fat tissue,
which indicates that the distribution curve of results found in these variables moved to the area
of small values, which in turn implies that the students of the Faculty of Physical Education are
generally athletic type, which is expected.
44
Anthropometric characteristics and strength in students
Table 2.
Basic descriptive statistics of the strength variables
VARIABLE
M SD MIN MAX SKE KUR
Pull-ups (freq.)
10.67
5.274
0
31
1.089
1.815
Lifting the trunk (freq.)
30.28
3.257
22
38
.173
.024
Horizontal endurance (s)
52.75
23.283
12
142
.890
1.561
Standing long jump (cm)
245.87
18.461
198
299
.228
.637
Deep squat (freq.)
32.15
2.432
23
39
-.159
1.340
Throwing a medicine ball (cm)
1034.56
142.024
640
1490
.146
.305
Endurance in a push-up (s)
43.92
17.968
16
127
1.059
2.168
Straightening of trunk (freq.)
67.42
29.806
11
200
1.855
4.977
Standing high jump (cm)
52.06
6.117
37
73
.527
.776
Endurance in half-squat (s)
64.92
34.406
12
255
1.694
5.798
Throwing a medicine ball (sit) (cm)
684.63
78.297
500
910
.243
.161
Hanging while in pull-up (s)
62.25
18.357
20
106
.196
-.312
Push-ups (freq.)
15.43
8.135
2
50
1.362
2.811
Standing triple jump (cm)
685.07
53.263
530
851
.268
.300
By looking at Table 2 we can observe that the value of the skewness in the variables
Straightening of trunk, Endurance in half-squat and Pushups supports the fact that the motor
ability assessed with these measuring instruments isnít applied on a homogeneous population.
Since the strength is in question, where the difference in the quality of performance depends
from person to person, even this finding isnít worrying.
Table 3
Results of OBLIVAX rotatation according to ITD criteria
VARIABLE
H*1 A**1
H2 A2
H3 A3
Pull-ups
.816
.763
.437
.183
-.298
.029
Lifting the trunk
.613
.558
.217
-.036
-.376
-.191
Horizontal endurance
.351
.327
-.250
-.558
-.554
-.616
Standing long jump
.369
.046
.901
.862
-.362
-.073
Deep squat
.570
.558
.163
-.059
-.270
-.092
Throwing medicine ball (back)
.337
-.015
.475
.237
-.836
-.765
Endurance in a push-up
.780
.788
.255
-.015
-.266
.006
Straightening of trunk
.236
.210
-.027
-.179
-.267
-.250
Standing high jump
.299
.001
.865
.866
-.272
.003
Endurance in half-squat
.266
.203
.068
-.084
-.304
-.259
Throwing a medicine ball (sit)
.156
-.225
.439
.252
-.835
-.834
Hanging while in pull-up
.607
.683
.286
.173
.090
.385
Push-ups
.802
.761
.362
.090
-.325
-.028
Standing triple jump
.307
-.005
.870
.857
-.317
-.047
Legend:, *H ñ structure, **A ñ pattern
45
M. Cvetkovi et al.
After factorial analysis (Table 3) it was noted that three principal components were
identified. The first principal component is composed of the following manifestations:
Endurance in push-up, Pull-ups, Push-ups, Hanging while in pull-up and to a lesser degree
Lifting the trunk and Deep squat, so this factor could be interpreted as Static and repetitive
strength mainly of arms, and to a lesser degree of trunk.
The second factor was defined based on three manifestations: Standing high jump,
Standing long jump and Standing triple jump and unambiguously is defined as Explosive leg
strength.
The third factor consisted of: Throwing a medicine ball while sitting and Throwing a
medicine ball while lying on back and was defined as Explosive arm strength.
Table 4
Factors correlations
(Pearsonís correlation - the lower triangle, the statistical significance - the upper triangle)
FACTORS
1.
2.
3.
1. Static and repetitive strength
.565
.166
2. Explosive leg strength
-.048
.000
3. Explosive arm strength
.114
-.735
By observing the Table 4 we can notice that there is statistically significance at the level
of p = 0.000 between the second and third factor, Explosive leg strength and Explosive arm
strength, suggesting that this is actually the one factor that is separated in two by a topological
criterion. Also, this would mean that, in the case of continuing of factor analysis, entering the
second-order factors, probably only one major component would be extracted ñ the strength. For
this reason, factor analysis was completed in the space of first order.
46
Anthropometric characteristics and strength in students
Table 5
Results of cannonical correlation analysis
Latent variables of strength
CV1s
CV2s
CV3s
Static and repetitive strength
.399
.320
-.859
Explosive leg strength
-.126
.931
.343
Explosive arm strength
.738
-.674
-.041
Anthropometric variables
CV1a
CV2a
CV3a
Body height
-.297
.530
.664
Arm length
-.237
.621
.382
Leg length
-.212
.519
.531
Ankle diameter
-.437
.167
.208
Knee joint diameter
-.532
.166
.248
Width of the pelvis
-.290
.274
.296
Body weight
-.918
.131
.306
Chest circumference, middle
-.800
.166
-.036
Circumference of stretched upper arm
-.805
.108
-.281
Circumference of bent upper arm
-.757
.292
-.329
Upper leg circumference
-.807
-.215
.277
Lower leg circumference
-.663
-.085
.319
Back skin fold
-.660
-.326
.085
Triceps skin fold
-.520
-.492
.111
Abdominal skin fold
-.606
-.392
.184
Upper leg skin fold
-.476
-.574
.012
Lower leg skin fold
-.514
-.457
-.019
Ò
.780
.701
.473
Ò²
.609
.492
.224
F
.154
.395
.776
p
.000
.000
.003
Legend: Ò ñ variance, Ò² - common variance of two canonical factors, F ñ Wilkís lambda, p ñ significance
By using canonical correlation analysis (Table 5) three statistically significant canonical
correlations were extracted.
The first statistically significant canonical correlation from the area of strength was the
Explosive arm strength, which is negatively correlated with all anthropometric variables, and
especially with all the variables that hypothetically estimated Body volume and weight and
Subcutaneous fat tissue. Within Transversal dimension of skeleton it is negatively correlated
with the Diameter of knee joint and Ankle diameter.
Through overlapping analysis (Table 6) it can be noted that many variables of strength
affect the anthropometric variables.
47
M. Cvetkovi et al.
Table 6
Overlapping analysis
Latent variables of strength
Anthropometric set
Û²
Ó
·
Û²
Ó
·
.719
.089
-.586
6.106
.133
.888
1.423
.115
.446
2.302
.033
.601
.858
.014
-.248
1.575
.005
.388
Legend: Û² ñ variance, Ó ñ redundancy index, · ñ reliability of canonical variable (canonical factor)
The second canonical correlation of strength area incorporated Explosive leg strength,
which is negatively correlated with subcutaneous fat accumulated on the upper leg and triceps,
and positively correlated with measures of longitudinal dimensionality of the skeleton. This
correlation is better explained through the set on the right side, so there is a greater influence of
anthropometry on explosive leg strength than the other way around.
The third canonical pair from strength area are Static and repetitive strength of arm and to
a lesser degree of trunk and Body height and Leg length from the set on the right side. There is
an evident negative correlation within the set and also a greater influence of anthropometric
variables on the Static and repetitive strength than vice versa.
Discussion
By application of factor analysis in this study three latent dimensions of strength were
extracted: static and repetitive strength, mainly of arms, and to a lesser degree of trunk, explosive
leg strength and explosive arm strength. Using canonical correlation analysis the following three
statistically significant canonical correlations were extracted.
First, itís the explosive arm strength that is negatively correlated with all anthropometric
variables. Obtained results are logical because the larger volume, mass, diameters of joints, and
especially the more subcutaneous fat, limit or even significantly reduce the expression of speed,
and thus the explosiveness, of any movement.
Second itís the explosive leg strength, which is negatively correlated with subcutaneous
fat tissue on the upper leg and triceps, and positively correlated with measures of longitudinal
skeleton dimensionality. This is understandable because it is expected that longer leverages, that
is limbs, also provide longer jumps, through which this latent ability was estimated.
Third itís static and dynamic strengths of arm (and slightly less of trunk) that are
negatively correlated with body height and leg length. This obtained canonical pair is logical
because the bigger longitudinality of skeleton causes the bigger mass, which in turn makes it
difficult to maintain or repeat movement on the long run.
The results of this study suggest an optimal and effective use of motor tests and
anthropometric measures to monitor a training effects while studying in the Faculty of Sport and
Physical Education.
48
Anthropometric characteristics and strength in students
References
Cattel, R B (1966). Handbook of multivariate experimental psychology. Chicago: McNally.
Cvetkovi„, M. (2007). Effects of different aerobic programs with the students of Faculty of Sport
and Physical Education. Ph.D. thesis, Novi Sad: Faculty of Sport and Physical
Education.
Harris, C. W., & Kaiser, H. F.
(1964). Oblique factor analytic solutions by orthogonal
transformations. Psychometrika, 29, 347-362.
Hendrickson, A. E., & White, P. O. (1964). PROMAX: A quick method for rotation to oblique
simple structure. British Journal of Statistical Psychology, 17, 65-70.
Jenrich, R. I., & Sampson, P F. (1966). Rotation to simple loadings. Psychometrika, 31, 313-323.
Kaiser, H. F. (1961). A note on Guttman's lower bound for the number of common factors.
British Journal of Statistical Psychology, 14(1), 1.
Kureli„, N., Momirovi„, K., Stojanovi„, M., äturm, J., Radojevi„, D., & Viski„-ätalec, N.
(1975). The structure and development of morphological and motoric dimensions of
youth. Belgrade: Institute for Scientific Research of the Faculty of Physical Education.
Momirovi„, K. (1998). One very stupid method for oblique simple structure transformation:
Technical report. Belgrade: Institute of Criminological and Sociological Research.
Momirovi„, K. (1998). Intruder in the dust. A liberal criterion for determining the number of
significant components. Technical Report. Belgrade: Institute for Criminological and
Sociological Research.
Momirovi„, K.
(1999). A comparison of some methods for oblique simple structure
transformation. Technical report. Belgrade: Institute of Criminological and Sociological
Research.
Momirovi„, K., Hoöek, A., Prot, F, & Bosnar, K. (2003). About morphological types of young
adult males. Herald of Anthropological Society of Yugoslavia, 38, 29-45.
Prûulj, D., & Pelemiö, V.
(2010). Differences in motor abilities and morphological
characteristics of the athletes and nonathletes students. Scientific-expert Journal of Sport
and Health, 5, 31-38.
Stojanovi„, M., Momirovi„, K., Vukosavljevi„, R., & Solari„, S. (1975). The structure of
anthropometric dimensions. Kinesiology, 1-2.
ätalec J., & Momirovi„, K. (1971). The total amount of valid variance as a basis of criteria for
determining the number of significant principal components. Kinesiology, 1(1), 91-93.
Viski„-ätalec, N.
(1974). Relations between dimensions of movements regulation and
morphological and some dimensions of energy regulation. Master's thesis, Zagreb:
Faculty of Physical Education.
Zaciorski, V. M. (1975). The physical properties of an athlete. Belgrade: Partizan.
Submitted 8 April, 2011
Accepted 15 June, 2011
49
EXERCISE AND QUALITY OF LIFE
Review article
Volume 3, No. 1, 2011, 51-57
UDC 373.3(450):796.01
STUDY BETWEEN NEUROPHYSIOLOGICAL ASPECTS AND
REGULATION DOCUMENTS IN PRIMARY SCHOOL IN ITALY
Raiola Gaetano
Faculty of Education Science,
University of Salerno, Italy
Abstract
In recent years Italian primary school, as called in the past time elementary school, that
goes between 5 years old to 10, has been updated in the ministerial documents relating to the
educational activities. At the same time, recent discoveries about the brain have changed the
scientific bases on which are based educational psycho-pedagogy theories concerning movement
learning on motor control system such as closed loop, open loop and motor imagery. The
purpose of this work is to identify into the ministerial documents regarding the educational
activities such as aspects of psycho-pedagogy in the field of body and movement research that
relates to neurological and scientific discoveries on motor control and movement learning. The
method of research is mixed: theoretical-argumentative approach about scientific paradigms
regarding the motor learning in the early years of life and historical-documentary one about the
ministerial documents relating to the teaching activities. The results did not carry out particular
aspects of education and didactics that can be connected to the new neuro-scientific theories and
suggest to update them. All ministerial documents published do not provide any reference to
recent discoveries related to the theory of movement and to correlate these according to didactics
of motor activities. It may be useful to deepen further the study and deliver the results to the
governmental Experts for the necessary updates to fill up the vacuum.
Keywords: regulation documents, motor imagery, open loop, closed loop
Introduction
Recently, the neurological and scientific research has placed highlight to the need for
links among the different fields of knowledge to explain phenomena difficult to explain if
confined only to the exact sciences field. Thus begins a process that starts to break down the wall
that rigidly divides the sciences of life and human sciences. Several research methods can be
integrated to investigate on the whole about phenomena which may include fields of knowledge
completely different such as neurobiology and philosophy to investigate on the theory of mind
Corresponding author. Faculty of Education Science, University of Salerno, Italy, Via Ponte don Melillo, 84084 -
Fisciano (SA). E-mail: raiolagaetano@libero.it
© 2010 Faculty of Sport and Physical Education, University of Novi Sad, Serbia
R. Gaetano
on motor activities or, in this case, between neurophysiology and motor skills teaching. To
explain how the mind works only from the organic point of view may be restrictive, the same
may hold if you approach the subject only from the philosophical point of view. In the theories
of the movement change is big and should correspond with an adjustment in teaching to update
the educational theories that relate to the body. The occasion is the new scientific evidences on
the brain, this is the discovery of certain nerve cells that are activated when they see, hear or
perceive through touch a movement but do not produce actions and movements. These nerve
cells are defined mirror neurons for the property of reflecting in the mind the movements of
others or of imagining their own standing still. They do not contribute to the practical execution
of the movement while being structures appointed to motor nerve but they perceive it. For this
reasons it is called motor imagery. They can be seen when they activate, i.e. they discharge the
electrical potential and it is possible to highlight thanks to x-ray sophisticated instrumentation of
brain-imaging or neuro-imaging such as Positron Emission Tomography (PET), Functional
Magnetic Resonance Integrated
(fMRI) of Transcranial Magnetic Stimulation
(TMS) and
Magneto Encephalo Graphy (MEG). This phenomenon happens all the time when the subjects
see, hear, feel on the body or inside the body information concerning the movements of others
when there is interest in those activities and actions. It has been demonstrated the existence of
particular neurons (mirror neurons) that, in the absence of movement, discharge, activate and
reflect the motor activities of others around the body. Furthermore, they discharge even when we
imagine a movement but we do not run it. It is then defining a new theory of motor control called
imagery motor. This opens a new scenario on learning of motor activities for imitation and on
teaching based on simulation and demonstration. It means that action and perception occur in the
same time and help each other in all phases of movement. Thus, there is also knowledge in the
same time without the traditional sequential stages of sensitive afferent or perception,
development of the motor idea, motion planning, execution of actions and their feedback
(biofeedback). The importance of the playful-motor activities suggests a new way of doing
school, which can be carried out only acknowledging the centrality of the person. The preschool
is particularly interested in this scientific development for the consequences that may have on the
educational activity; applications may influence the mechanisms of acquisition of motor skills
and development of motor skills. There may also be learning in other fields of knowledge
different from physical education where the relationship among body, movement and learning
produces spatial, temporal, sequential, linguistic, expressive and musical learning and so
on. These ìlearningsî are the study of the educational psychology that updates its own scientific
paradigms in relation to these discoveries. Embodiment and situatedness are the center of
learning in early age, which means embodied and situated cognition is into the phenomena on
the body and movement to develop the learning way. However, it is important, to point out some
aspects in order to understand better how to take advantage of these discoveries as well as how to
avoid an inappropriate use and distorted cultural spreading
(Gallese,
2007). Finally, it is
important sense-perceptive competencies, the movement in the space and the time and, at least,
the body language meant as a communicative-expressive way. These discoveries bring into
discussion the theories of motor control that temporally distinguish the afferent perceptive phase
from the executive efferent one according to the two more shared scientific paradigms: closed-
loop motor control and open-loop motor control. The first provides that the perception is first
and then the movement and so constantly in a continuous loop called closed-loop motor control
system. Movements are those that are not present in motor memory and are executed with the
help of feedback for adjustments and corrections of errors. They are constantly updated through
the comparison between what is perceived, called perceptive trace, and what you have in mind,
called memory trace. The second is also expected that first is the perception and then the
movement but in one or different scheme called open-loop motor control system (Schmidt,
1985). It clarifies some differences about the past other model that is the movements are already
present in memory and do not adjust themselves with the comparison and they canít be corrected
when the feedback occurs below 200 milliseconds and the brain canít process them and use
52
Neurophysiological studies and school regulatives
them. This theory states that there are in memory a wide range of similar movements among
them in a sort of container or register. These patterns are already present at birth but become
active in certain circumstances already in a functional manner. The new discoveries about the
brain suggest a mixing up of perception/action in a single process where perception and
execution are set together without a sequential order and where the knowledge derived from
movement is learned in a single process. The aim of this study is to verify if the ministerial
documents of the kindergarten there are aspects of psycho-pedagogy and educational
applications of any recent neurological and scientific discoveries on mirror neurons and on motor
imagery; to help to develop an epistemological and psycho-pedagogical framework including
any related educational applications about body and movement; to make an epistemological
reflection on the theory of human movement in the educational school environment for preschool
activities in connection with the primary school.
The ministerial documents are in temporal order: 1955 Programme for the educational
activity in elementary school, 1985 Programme for the educational activity in elementary school,
2004 National Guidelines in the first cycle of the school, 2007 Curriculum Guidelines the first
cycle of the school, 2009 Revision of the educational organization regulated directions for the
first cycle of the school.
Method
Integration of different types of research into a single model with an ecological approach.
Theoretical and argumentative research that analyzes methodological and didactic patterns of
motor activities according to the main educational psychology and neurological and
physiological theories. Historical and documentary research that analyzes the methodological
and teaching contents of physical activities in preschool obtained from ministerial papers.
Comparative research that correlates the different models of study of physical activities for
children.
Results
In order to understand the results of the study is useful to give a course prior to the period
of the analysis of ministerial documents. For a certain period in Italy learning motor activities
were characterized by the instrumental use of the body to achieve goals in the military field. The
teaching model has been determined by military purposes aimed to develop the quantitative
aspects of movement (strength, endurance and speed) to improve performance and aesthetic
aspects (body building) to exalt the ego, while neglecting the education of the person through the
body and movement. The method chosen to improve performance was a demonstration of the
technical gesture and the order to reproduce it faithfully or the administration of heavy
workloads; action teaching was the same for all members of the group. The foundations of this
theoretical model are to be found in behaviourism school of thought that is the general law. It
begins with the external sensory stimulus, command the same for all, it continues with the
answer, predetermined, induced and required at all. Everything is constantly repeated in order to
consolidate the motor learning. At the same time and in contrast to this theoretical model, it was
born a scientific orientation that considers the totality of stimulation, mainly visual, according to
a comprehensive approach to its shape. The Gestalt theory or form (from German language), a
psychological current that derives its origin from historical necessity in America to meet the
limits of the behaviourist theory that unifies the individual behaviour caused by the stimulus. The
stimulation becomes total perception, developed and consists of all the sensations and the data
53
R. Gaetano
held in memory. Perception is subjective, individual and conditioned by already acquired
learning, it replaces the specific command with a request of execution of movement according to
an individual process of imitation. Specifically, the teacher demonstrates in the whole the gesture
to play and applies for many years the so-called educational "global-analytical-globalî theorem.
The cognitive orientation claims to the behaviourism the total absence of the importance of
innate aspects of the individual and the consequent ability of the subject to effect changes on
itself, cancelling the power that the environment exerts on the individual. A dynamic inside the
person is projected to the outside, to the surrounding environment to assert the primacy of the
individual; then, there was a review on neutrality on the inside and the outside and so appeared
three trends. The culture produces effects on learning as if it were a conditioning from which one
canít ignore and crystallizes the values in all knowledge (culturalism). The context within which
the dynamics is not neutral in the acquisition of knowledge, rather facilitates or inhibits the
activity of the mind (contextualism). Knowledge is built on another before and is constantly
developed starting from the initial matrix (constructivism).
The environment was thus partially re-evaluated on the actual impact on knowledge. It
turns out the absolute centrality of the individual respect to the environment and the priority of
the person in the motor activity without control but the teacher does not show but announces a
delivery with minimum requirements and does not interfere in the process and the individual
separately learns without a specific technique to achieve the objective it has set itself. The
teaching model refers to the techniques of teaching workshop (circle time, cooperative learning
and role playing). The phenomenology, the orientation of philosophical origin, has for some
time, before behaviourism, gestalt theory and cognitivism with its derivations, focused on the
function of the interaction body-environment and subject-subject in the mechanisms of learning,
as it was already aware of the actual functioning of the perceptive phenomena of specialized
nerve cells that are discovered later (mirror neurons). The interpretative key was all aimed at
enhancing the body as a receiver of signals to decode and that they contributed to the knowledge
that independently formed whatever it was the single channel, the sensory channel, but
determined by perception. The discovery of mirror neurons is confirmed by the phenomenology
of perception (Iacoboni, 2008) which binds together perception, action and knowledge in a
unique process with no beginning and ending, it defines a different scenario in his motion for
complete adherence to the phenomenology. Furthermore, the ability of brain to activate the
motor neuron cells that do not innervate muscles, they are evidence of functions of the mind
affecting the movement and they are only abstract, like any other knowledge that does not take
place with the movement.
The document 1955, Programme for the educational activity in elementary school is very
short and contains a few elements for the harmonic development about behaviourist aspects. It
has a double orientation: the first one is orientated to the harmonic development of the body and
its natural expression by the guide of the master and the second one to include the complexity of
movement to help to develop the child to grow up. There are no elements on motor control
system or didactics method to teach the movement as well as the neuro scientific research.
The document 1985, Programme for the educational activity in elementary school is
longer than the past one and, for the first time, speaks on motor education in a cognitive aspects
in several interface of physical education and sport in the developmental process between five
years old and ten. It contains a strong appeal for a didactic guided by the free doing and acting
and the provision of appropriate learning environments for a rich and extensive stimulation. The
field of knowledge is divided by areas and that of body and movement is enhanced as other
fields of knowledge. The teacher's role is slightly active tending in some cases to director of
operations. Despite this innovation, the document is incomplete about the new discoveries on
motor control system and there are no scientific elements on neuroscience applied to movement
and the learning process through the body.
54
Neurophysiological studies and school regulatives
The document 2004, Attachment A ñ National Guideline for the Programs of studies of
the first cycle of education National Guidelines for Personalized Programs of the Educational
Activities in the first cycle of education, Specific Learning Objectives, Recommendation to put
into practice the National Guidelines for Personalized Programs of the Educational Activities is
a very innovative regulation tool to teach properly to a new discoveries on individual learning
process. It takes in light the relation between the teaching and the learning in an unicum. It writes
in double column, where there is specified knowledge and ability in motor and sports science, as
a sort of a new scientific paradigm of physical education and sports in primary school. It is a
mere list of objectives to be achieved in the form of motor skills and there is no single reference
to teaching. Basically, it refers to the document above and does not refer to any element related
to the theories of motor control or to the recent neuro-scientific discoveries.
The document 2007, The Guidelines for the curriculum of the first cycle of education, as
the last one a large paper where there is written a lot of knowledge and process of motor and
sports science in a new vision for this research field. It resumes the contents of the document
Guidelines for primary school and they are contextualized in a disciplinary process that
goes from childhood to the end of the first education cycle. It widens the sense of continuity of
teaching action without indicating specific teaching methods. It does not indicate a specific item
on motor control and does not address to new neuro-scientific scenarios on movement in the
light of the discovery of mirror neurons or the other two motor control system theories. In all the
documents there is no cultural basis of theories of motor control and there are no elements of
new scientific discoveries about the brain from the motor point of view. The psycho-pedagogical
paradigms are totally based on the overall contents on learning generalizing the teaching in all
fields of knowledge.
The document 2009, Revision of the educational organization regulated directions for the
first cycle of the school does not explain the innovation in a new rules, but it postpones to a new
experimental study the final revision and does not hint nothing. It recommends to trust in two
last documents: 2007, the Guidelines for the curriculum of the first cycle of education and 2004,
National Guideline for the Programs of studies of the first cycle of education National
Guidelines for Personalized Programs of the Educational Activities in the first cycle of
education, Specific Learning Objectives, Recommendation to put into practice the National
Guidelines for Personalized Programs of the Educational Activities.
Thus ultimately, there is no trace of a scientific specificity about body and movement nor
there is a cultural content on the theories of motor control.
In conclusion, in these documents there are not elements and/or methods to establish the
application of motor control system in its three scientific ways and forms: closed loop, open loop
and motor imagery. The big vacuum is the absolute absence of psychological and pedagogical
aspects on movement that could have the theoretical aspect of new discoveries.
Discussion
Documents are lacking in cultural references about physical education and this results in
a total absence of knowledge of general and specific aspects of human movement, motor control
and psychological aspects. The unique and overall formulation of knowledge is useful for the
holistic approach to knowledge but it does not realize at all the objective of base knowledge of a
field of knowledge. What is needed is a detailed review of the psycho-pedagogical principles at
the basis of ministerial documents with the purpose to insert clear links to the theories of motor
control and human movement.
55
R. Gaetano
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Merleau-Ponty, M. (2002). Phenomenology of perception. London: Routledge
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(1936). Die Krisis der europischen Wissenscaften und Die
transzendentale Phanomenologie. Belgrado: Philosophia.
Mackenzie, B. D (1977). Behaviourism and the limits of scientific method. London: Routeledge
& Kegan Paul.
Skinner, B. F. (1969) Contigencies of reinfourcement. New York: Appleton-Century-Crofts.
Gardner, H. (2002) Frame of the mind: The theory of multiple intelligences. New York: Basic
Books.
Kohler, W. (1947). Gestalt psychology. New York: Liveright.
Latash, M. (2008) Neurophysiological basis of movement. Champaign, IL: Human Kinetics.
Schmidt, R., A., & Wrisberg, G. A. (2008). Motor Learning and Performance. Champaign, IL:
Human Kinetics.
Iacoboni, M. (2008). Mirroring people. The new science of how we connect with others. Los
Angeles, CA: Farrar Straus.
Rizzolatti, G. (2006) So quel che fai. Il cervello che agisce e i neuroni specchio. Milano:
Raffaello Cortina Editore.
Wrisberg, G. A. (2009). Sport skills for coaches. Champaign, IL: Human Kinetics.
Chapman, A., E. (2009). Biomechanical analysis of fundamental human movements. Champaign,
IL: Human Kinetics.
56
Neurophysiological studies and school regulatives
Regulations References
Decree of Republic President DPR no.
89 of
20 march
2009 Revisione dellíassetto
ordinamentale didattico organizzativo del primo ciclo di istruzione. Revision of
the educational organization regulated directions for the first cycle of the school.
Ministerial Decree D.M. 31 July
2007, Indicazioni per il Curriculo per il primo ciclio di
istruzione, The Guidelines for the curriculum of the first cycle of education.
Legislative Decree DLGS no. 59 of 19 February 2004 - Attachment A ñ National Guideline for
the Programs of studies of the first cycle of education National Guidelines for
Personalized Programs of the Educational Activities in the first cycle of education,
Specific Learning Objectives, Recommendation to put into practice the National
Guidelines for Personalized Programs of the Educational Activities.
Decree of Republic President DPR no. 104 of 12 February 1985 Programmi per la scuola
elementare Programme for the educational activity in elementary school.
Decree of Republic President DPR no. 503 of 14 June 1955 Programmi per la scuola elemntare
Programme for the educational activity in elementary school.
Submitted 17 January, 2011
Accepted 17 March, 2011
57
EXERCISE AND QUALITY OF LIFE
Research article
Volume 3, No. 1, 2011, 59-65
UDC 616.711-007.5-053.5:796.035
DIFFERENCES IN POSTURAL STATUS OF LOWER-GRADE
PUPILS WITH RESPECT TO THE LEVEL OF PHYSICAL
ACTIVITY
Gordana Tripunovic
ìJovan Jovanovi„ ñ Zmajî, Elementary School
Sremska Kamenica, Serbia
Abstract
A basic posture is thought to be inherited, but it can be modified by environmental factors
such as illness, age, physical activity, living conditions, physical environment, diet, and many
others. The purpose of this study was to determine the differences in postural status between
trained athletes and untrained children of the same age. The population sample included boys
aged 8-10 years from elementary schools in the city of Novi Sad, as well as from sport clubs in
the same area. They were assigned to either of the three groups: A) pupils participating in an
individual sport (N=50); B) pupils participating in a team sport (N=51), and C) pupils attending
physical education (PE) classes only (N=50)(control group). All measurements of postural status
were taken using the Napoleon Wolanski method. The analyses showed that the situation in the
control group is rather worrisome, where postural status is very poor. The weakest links are the
abdominal muscles, but also the head, shoulders, shoulder blades, spine, feet and legs.
Keywords: postural status, pupils, physical activity, sport
Introduction
A good posture is all about optimal relations among all segments of the human body,
which are fairly stable for the most part (Sabo, 2006; Purenovi„, 2007). The optimal posture
represents a biological value of the human kind, passed on by phylogenetic development. It can
be defined as an activity using the least amount of energy required for normal functioning of the
internal organs and maintenance of psychomotor abilities.
Principles of the basic body posture are very complex and are based on conditioned and
unconditioned reflexes. Since the former are dependent on external influences, body posture is
more subject to individual differences. Essentially, basic posture seems to be mostly genetic,
however it can also be altered by environmental factors like illness, age, level of physical
activity, living conditions, physical environment, eating habits, and many others.
Corresponding author. ÑJovan Jovanovi„ Zmajì, Elementary School. äkolska 3, 21203 Sremska Kamenica, Serbia.
E-mail:
© 2010 Faculty of Sport and Physical Education, University of Novi Sad, Serbia
G. Tripunovi
In order to maintain a normal, steady, upright standing position, both active and passive
forces of the locomotor system are engaged, specifically muscles, ligaments and bones. The
greatest of all external forces disturbing the optimal posture is gravity. Active forces are
produced by muscles, whereas the passive ones come from ligaments, bones and joints. In any
activity, all the forces affecting body posture must be in balance. Any disturbance inside this
system can cause an imbalance within the individual segments of the body. This imbalance
mostly occurs at the expense of the active portion of these forces, ie. muscles, which may
succumb due to fatigue, their poor conditioning, or disease. The consequence of this muscle
weakness is an increased strain on the passive portion of the locomotor system, which in turn
begins to deteriorate over time, adapting to a completely new role (Uli„, 1997).
A fundamental condition for establishing and maintaining a normal standing posture is a
well-balanced relationship between internal and external forces. These forces are the same in
magnitude, but act in opposite directions. When there is an imbalance, a good posture has been
compromised.
Biological development of children is characterized by certain natural laws.
Psychological and physical development is an ongoing process, both gradual and irregular, with
specific characteristics for each period. In other words, child growth and development are
normally continuing processes, although certain anatomical, physiological and psychological
segments do not develop at the same rate or end at the same time (Rowlands et al.,1999).
Individual differences are present at any point during development. Besides exogenic and
endogenic factors, there are many other factors affecting these differences (Nevill et al., 1998).
The period between 8-10 y of age is characterized by fairly steady, slowed gains in body
height (Ruiz et al.,
2006). Bone growth and calcification are ongoing, while physiological
curvatures of the spine are already being fixed. Even though the muscular system is evidently
becoming stronger, it is not fully developed. At the end of this period, soft muscle tissue
accounts for about 30% of the total body weight.
During this stage, it is necessary to assess body posture and check for potential
deformities in order to intervene and correct them in time.
The purpose of this study was to investigate and determine the differences, if any, in
postural status between young athletes and the untrained children of the same age.
Method
Participants
The sample was derived from Novi Sadís elementary schoolsí boys, as well as from those
participating in many sports clubs in the Novi Sad municipality. They were 8-10 y old (± 6
months).
Participants were assigned into one of the following three groups:
A) pupils participating in individual sports (N=50),
B) pupils participating in team sports (N=51),
C) pupils attending physical education (PE) classes only (N=50)
All participants had to be clinically healthy and free of any aberrations.
60
Pupilsí postural status and level of physical activity
Measures
In order to assess the overall postural status, the following parameters were looked at: 1)
Head posture; 2) Shoulder posture; 3) Shoulder blade posture; 4) Thorax development status; 5)
Digression of the spine in the frontal plane or Spine posture; 6) Abdomen posture; 7) Leg shape;
and 8) Foot arch.
The measurements of the postural status of children were taken according to the
Napoleon Wolanski method (Radisavljevi„, 2001). Three marks (0-2) were used: ëzeroí (0) was
given when all the parameters were in normal, expected relations. ëOneí (1) represented a certain
digression from a normal status of body posture, which could be corrected with appropriate
exercises (the active portion of the locomotor system was weakened in some way), and ëtwoí
was given in more severe cases with significant digression from the normal status of body
posture (structural changes of the locomotor system).
During examination, children were barefoot and in their underwear. The observations
were done from the distance of about 2 m, and were recorded in a set order. It was ensured that
measurement conditions were the same for all participants during the morning hours, in well-lit
and spacious rooms, at an optimal room temperature, and the same people taking the
measurements.
The results were analyzed by the frequency of appearance by categories of postural
status, and were expressed both numerically and in percentages. Differences between groups
calculated using Chi-square test.
Results
Table 1 shows the results for Head posture, Shoulder posture, Shoulder blade posture,
Thorax development status, Spine shape and posture, Abdomen posture, Leg shape, and Foot
arch.
Table 2 shows that there is a statistically significant difference among tested groups of
pupils in variables shoulder posture, abdomen posture, leg shape and foot arch at the level of
significance p ≤ 0.01. Whereas with a variables Spine shape and posture, this difference is at the
level of significance p ≤ 0.05, respectively.
By analyzing results of the frequencies in head posture, it can be noticed that the best
group, with greatest percentage in normal posture was found in group A (50%), followed by
group C (46%) and group B (37%). In addition, results of significant digression from normal
head posture were found in group C (control group) and B with frequency of 4%, whereas group
A had 2%.
The results in shoulder posture were as follows: 80% in group A and 74.5% in group B of
the boys with an optimal shoulder status. Only 46% of the boys in control group had good
shoulder posture and 4% of significant digression from optimal posture.
61
G. Tripunovi
Table 1
Postural status of 8-10 year-old pupils participating in individual sports (A), team sports (B),
and those not participating in any sports (C.
Frequency (%)
mark
A
B
C
0
25 (50%) 19 (37.3%)
23 (46%)
1
24 (48%) 30 (58.8%)
25 (50%)
Head posture
2
1 (2%)
2 (3.9%)
2 (4%)
Total 50 (100%)
51 (100%) 50 (100%)
0
40 (80%) 38 (74.5%)
23 (46%)
1
10 (20%) 13 (25.5%)
25 (50%)
Shoulder posture
2
-
-
2 (4%)
Total 50 (100%)
51 (100%) 50 (100%)
0
45 (90%) 44 (86.3%)
43 (86%)
1
5 (10%)
7 (13.7%)
5 (10%)
Thorax shape
2
-
-
2 (4%)
Total 50 (100%)
51 (100%) 50 (100%)
0
31 (62%)
25 (49%)
20 (40%)
Shoulder blade
1
17 (34%)
24 (47.1)
29 (58%)
position
2
2 (4%)
2 (3.9%)
1 (2%)
Total 50 (100%)
51 (100%) 50 (100%)
0
44 (88%) 40 (78.4%)
31 (62%)
Spine shape and
1
6 (12%) 11 (21.6%)
18 (36%)
posture
2
-
-
1 (2%)
Total 50 (100%)
51 (100%) 50 (100%)
0
17 (34%) 10 (19.6%)
3 (6%)
Abdomen
1
25 (50%) 19 (37.3%)
31 (62%)
posture
2
8 (16%) 22 (43.1%)
16 (32%)
Total 50 (100%)
51 (100%) 50 (100%)
0
44 (88%) 42 (82.4%)
26 (52%)
1
6 (12%)
9 (17.6%)
14 (28%)
Leg shape
2
-
-
10 (20%)
Total 50 (100%)
51 (100%) 50 (100%)
0
22 (44%) 31 (60.8%)
8 (16%)
1
28 (56%) 20 (39.2%)
39 (78%)
Foot arch
2
-
-
3 (6%)
Total 50 (100%)
51 (100%) 50 (100%)
A normal thorax shape and posture was found in 90% of the boys in group A, 86.3% in
group B and 86% in control group, whereas 4% of significant digression in posture was found in
control group.
The results for Shoulder-blade posture in groups shows that in all groups highest
percentage was with normal posture, but there was found within all three groups small
percentage (around 4%) of significant structural changes due to a scoliotic body posture.
62
Pupilsí postural status and level of physical activity
Table 2
Differences in postural status between groups of pupils
Body segment
Chi-square
p
(df)
Head posture
2.00 (4)
.736
Shoulder posture
17.069 (4)
.002
Thorax shape
4.514 (4)
.341
Shoulder blade
5.933 (4)
.204
position
Spine shape and
10.590 (4)
.032
posture
Abdomen posture
19.143 (4)
.001
Leg shape
28.693 (4)
.000
Foot arch
25.460 (4)
.000
A normal spine posture was had by 88% in group A, 78.4% in group B and 62% in
control group C. A significant digression with severe structural changes taking place had 2% in
control group.
Only 34% of the boys in group A had a normal abdomen posture, 50% had a slight
digression from normal abdomen posture, and even 16% had a significant digression. It appears
that the underlying cause of this finding may as well be a weakened active portion of the
locomotor apparatus or musculature, which can have result in a lordotic body posture. The
situation in groups B and C was similar, with high percentage of a significant digression from
normal abdomen posture.
The situation with leg-shape posture, in group A and B, high percentage of normal
posture were found (over 80%), while the rest of the subjects had slight alterations in posture that
could be corrected by strengthening the stabilizing muscles, especially in the knee joint and
ankle. In group C, 52% had a normal leg shape, 28% were with a slight digression, and even
20% had a significant digression from normal leg shape. This can certainly be attributed to a
poor level of physical activity and the result in weakening of the stabilizing musculature and
ligaments of the lower leg joints.
Finally, highest percentage of the participants in group A and B showed a normal foot
arch, and the remaining percentage had a slight digression from a normal postural status. None
had a significant digression. A dire situation was found in group C where only 16% of the boys
had a normal foot arch, 78% had a slight digression, and 6% (3 boys) had a significant digression
from normal foot arch. Feet are always the first to relent as a direct consequence of insufficient
physical activity, poor diet and obesity.
Discussion
From all these analyses, it can be inferred that the most sensitive areas in 8-10 year-old
boys participating in individual sports are the abdominal section, scapular area and feet. In these
regions of the body there was the greatest number of pupils with a slight digression from a
normal postural status.
63
G. Tripunovi
One can also observe that the situation with boys participating in team sports is worse
than with those involved in individual sports. There were more compromised regions, with a
poor postural status in the abdominal section, the head, scapular region, and the feet.
Very disturbing results compared to the other two groups, were found in group C with
untrained boys participating only in PE classes at school. In this group, the overall postural status
was very poor. The weakest links seem to be the abdominal region, the head, shoulders, scapular
area, spine, feet and legs. These findings suggest that further analysis looking at the root-cause of
this phenomenon is needed in order to make corrections, and, more importantly, provide
meaningful and timely prevention strategies to the problem.
This study was run on 151 boys aged 8-10 years, divided into three groups: trained ñ
individual sports, trained ñ team sports, and untrained. Eight variables were measured for the
assessment of the overall postural status, with the purpose of examining the differences between
the trained vs. the untrained pupils of the same age.
All measurements were taken by the Napoleon Wolanski method. The analyses of the
results led us to the following conclusions:
-
The most sensitive areas in 8-10 year-old boys participating in individual sports are the
abdominal section, scapular area and feet. In these regions of the body there were the most
pupils with a slight digression from a a normal postural status.
-
A worse situation was seen with boys participating in team sports than with those involved
in individual sports. There were more compromised regions, with a poor postural status
found in the abdominal section, the head, scapular region, and the feet.
-
The worst results were found in the control group, where there was a very worrying
situation. The weakest links were the abdominal region, the head, shoulders, scapular area,
spine, feet and legs.
After starting school, spontaneous movement activities in children are reduced. In addition
to a prolonged time spent in a sitting position, whether in school or at home, the musculoskeletal
system is negatively influenced by ergonomically inadequate school furniture, mental stress, and
in particular lack of overall movement (Filipova et al., 2003). The attitude of parents toward
movement activities appears to be very important for the creation of positive relationships of
children with respect to sports and exercise. Education (Van de Mheen et al., 1998; Groholt et
al.,
2003) is an important factor influencing the state of health. Educated people have better
attitudes toward healthy lifestyles, including exercise. A gradually developing muscular
imbalance initially manifests as a functional disorder with characteristic signs of changing body
profile, which is followed by structural changes, first affecting the soft tissues
(ligaments,
cartilage, and muscles) and later the bony and joint structures. The latter is known as fixed
postural abnormality. Unlike fixed abnormalities, poor posture in a functional disorder phase can
be willingly corrected by active muscle effort (Groholt et al., 2003) and may be influenced by
regular and special exercise (Filipova et al., 2005).
This work provides evidence that deficit of movement activities is associated with the
development of poor posture. Interventional measures, which should be implemented on a large-
scale basis, especially as part of school physical education. There is a lack of guidance and the
cooperation between health care professionals and educators regarding how best to implement
physical activities. The results of our study can be used as evidence with officials in the area of
prevention, to support efforts to improve the health of our school children and to reduce the risk
of postural damage to childrenís health.
64
Pupilsí postural status and level of physical activity
References
Filipov· V, KratÏnov· J, Trestrov· Z. (2005). National Program of HealthóGrant Projects for
the Support of Health 1994-2004 [in Czech]. Prague, Czech Republic: Regional Public
Health Authority and Institute of Health of the Middle Bohemian Region.
Groholt, E., Stigum, H., & Nordhagen, R. (2003). Recurrent pain in children, socio-economic
factors and accumulation in families. European Journal Epidemiology, 18, 965-975.
Nevill, A., Holder, R., Baxter-Jones, A., Round, J., & Jones, D. (1998). Modeling developmental
changes in strength and aerobic power in children. Journal of Applied Physiology, 84,
963-970.
Purenovi„, T.
(2007). Review of national and international research studies in postural
deformities: The period from 2000 to 2007. Facta Universitatis ñ Physical Education and
Sport, 5, 139-152.
Rowlands, A. V., Eston, R. G., & Ingledew, D. K. (1999). Relationship between activity levels,
aerobic fitness, and body fat in 8- to 10-yr-old children. Journal of Applied Physiology,
86(4), 1428-1435.
Ruiz, J. R., Rizzo, N. S., Hurtig-Wennlof, A., Ortega, F. B., Warnberg, J., & Sjostrom, M.
(2006). Relations of total physical activity and intensity to fitness and fatness in children:
the European Youth Heart Stady. The Amercan Journal of Clinical Nutrition, 84(2), 299-
303.
Sabo, E. (2006). Posturalni status dece predökolskog uzrasta u Novom Sadu [Postural status of
pre-school children in the city of Novi Sad]. Pedagoöka stvarnost, 7-8, 615-625.
Uli„, D. (1997). Osnove kineziterapije [The foundations of kinesitherapy]. Novi Sad: Samostalno
autorsko izdanje.
Van de Mheen, H., Stronks, K., & Kolman, C. W. (1998). Does childhood socioeconomic status
influence adult health through behavioral factors? International Journal of Epidemiology,
27(3), 431-437.
Submitted 12 April, 2011
Accepted 15 June, 2011
65
EXERCISE AND QUALITY OF LIFE
Research article
Volume 3, No. 1, 2011, 67-76
UDC 796.325-056.26:316.628
THE MOTIVES OF PLAYERS TO ENGAGE IN
THE SITTING VOLLEYBALL
Mladen Proti„
Humanitarian Organization ìPartnerî
Banja Luka, Republic of Srpska, Bosnia and Hercegovina
Igor VuËkovi„
Faculty of Physical Education and Sport,
University of Banja Luka, Republic of Srpska, Bosnia and Hercegovina
Abstract
The investigation aimed to determine if sport motivation for engagement to the sitting
volleyball differed between groups of participants, sorted by 6 criterions. 88 athletes (M: 83 and
F: 5) participated in this research, including sitting volleyball players in origin from Bosnia and
Herzegovina, Serbia, Croatia, Slovenia and Greece. The data are collected using the Sitting
Volleyball Participation Survey, which is modified version of Disability Sport Participation
Questionaire
(Wu, & Williams,
2001), designed for investigation of motives for sport
participation among persons with disability. Descriptive statistics and Non parametric Mann-
Whitney-U test within the SPSS 16.0, were used for statistical analysis. The results inicated that
motiv of Socialisation (78.8 %) is the prime factor of sitting volleyball participation. Statistically
significant differences between chosen groups of participants haven't been found, except the fact
that players who experienced injury in younger age emphasize the importance of sport
competition for their sport participation.
Keywords: sitting volleyball, motivation, physical disability
Introduction
Sitting volleyball is relatively young sport. With its simplicity presents great example of
adaptation and implementation of the major team sport for persons with physical disability.
There are no gender and age issues, because both sexes of various ages can play together, except
at the some higher level competitions. (Vute, 2008). De Haan (1986) indicates that sitting
volleyball is the sport primarlly for persons with physical disability. Technology accessibility,
Corresponding author. Humanitarian organization ìPartnerî Banja Luka, Beogradska street 8, 78 000 Banja Luka,
Republic of Srpska, Bosnia and Hercegovina. E-mail: mladenprotic@yahoo.com
M. Proti and I. VuËkovi
approachability and adaptability of the court (i.e. lower net, smaller dimensions) allow people
with various abilities to play together.
Motivation for sport and physical activity participation has been extensively examined by
many authors, but mainly among non disabled population of people (Gill et al., 1983; Kohl &
Hobbs, 1998; Ryan & Deci, 1990; Koivula, 1999; Kilpatrick et al., 2005; Ketteridge & Boshoff,
2008). Although, in the last 20 years scientists started to do research more intensively in the area
of sport motivation and participation in various physical activities among persons with physical
disability (Fung, 1992; Crocker, 1993; Skordilis et al., 2001; Tennant et al., 2001; Wu &
Williams, 2001; Ginis et al., 2004; Kosma et al., 2005; Rimmer et al., 2005; & King, 2006;),
using different approaches, groups of participants and methodes, there is still much space for
research development in this fieald. On the basis of current findings, it is very difficult to make
an universal pattern of behaviour or hierarchy of motivational factors among persons with
physical disability. In addition to that, if we consider the fact that this type of condition is a very
wide term which can originate from birth (congenital) or it can be result of some illnes or
accidents (acquired), then this task is even more chalenging.
Some people practice sports from the desire to compete, to prove them selfs and to others
or to win medals. Others want to have fun, maintain the level of fitness and health, but again
there are those who only want to socialise, make friends and go for a beer after the practice. The
reasons are different, but sport is that kind of environment which in all its forms provides
possibilities for many people to satisfy their needs.
The goal of this study was to examine motivational factors of players from Balkan
countries related to sitting volleyball participation. This geographycal area is specific because of
war condition who had influence on some countries from this study 15 ñ 20 years ago, and
because most of the players are still in difficult economical position. The study aimed at
discovering the strongest motivational factors for engagement in the sitting volleyball and
comparing those findings with previous studies results.
Beside of defining motives for sitting volleyball participation, the significance of this
paper is in providing information for greater understanding of this sport for persons with
disabilities. Although sitting volleyball is the most successful sport in Bosnia and Herzegovina,
people still have prejudices about persons with disabilities and what are they capable of.
Persons with disabilities are more liable for secondary health conditions (cardiovascular
diseases, type2dyabetes, obesity, stress, hypo kinesis, etc.) then persons without disabilities. The
Center for Disease Control and Prevention (CDC) recommends that adults accumulate at least 30
minutes of moderate intensity physical activity on most days of the week or 20 minutes of
vigorous activity 3 days per week (CDC, 2011). With engagement in physical activities and
satisfying the needs of persons with disabilities through specially designed programs, the risk for
development of aforementioned mentioned secondary conditions can be meaningfully reduced.
The relevance of this study is in finding and defining the factors important for sitting volleyball
participation ñ both in training and in competition.
Method
Participants
The sample of participant's study group was consisted of 88 sitting volleyball players
from who 71 was with physical disability and 13 was without disability. Four players havenít
answered on the question. From the whole number of physically disabled athletes 68 of them
68
Motives for engagement in sitting volleyball
was with acquired and only 3 with congenital physical disability. The research is conducted on
the sample of 5 females and 83 males with age span from 15 to 60 years of age.
Instrument
Instrument used for this research is modified version of Disability Sport Participation
Questionnaire (Wu, & Williams, 2001). Questions in modified survey were grouped under the
following headings: Personal data (gender, age, marital status, profession, data about medical
diagnosis, years of injury, why sitting volleyball, main reasons for engagement in this sport),
Data about sitting volleyball engagement (age when they found out for the sport, who introduce
with the sport, in which context they found out for the sport, did they know for the sport from
before difficulties after engagement), and Data about training (competition level of the club,
number of trainings per week, where the trainings take place, do the players have individual
trainings and data about injuries). Reasons for the sitting volleyball participation were measured
on the 4 ñ point importance rating scale with answers from ìvery importantî (1 point) to ìnot
important at allî (4 points).
The goal of this questionnaire is to use information obtained to develop a profile of the
sitting volleyball athletes and their participation patterns, so that it can produce more effective
sitting volleyball development programs and to use this information to increase the knowledge
about the sport.
Procedure
The data were mostly collected at International Tournament in Sitting Volleyball ìBanja
Luka Open 2009î in Banja Luka, Bosnia and Herzegovina, with ten participating clubs from
Bosnia and Herzegovina, Serbia, Croatia, Slovenia and Greece. In total, 120 questionnaires are
distributed at aforementioned International tournament and 48 additional questionnaires were
sent by e mail to the sitting volleyball players from other clubs in Republic of Srpska. Eighty
eight questionnaires have been returned altogether, which is 59.5 % of returning rate.
Statistical analysis
The basic matrix for data input and analysis was made in SPSS 16.0 software for
Windows. Descriptive statistics is calculated together with percentages of each motivational
factor for sitting volleyball engagement, in order to get basic characteristics of participantís
answers. With the use of Mann Whitney U test, differentiation of the players was performed by
six different criterions in relation to motivational factors: a) Between younger and older players,
b) Between players who had injury in younger age and who had injury in older age, c) between
more and less experienced players, d) between players who have individual trainings and those
who do not have it, e) between players who practice only sitting volleyball and those who are
engaged in some other sports, and f) between players in better ranked clubs and players in worse
ranked clubs.
Results
The participants had a choice to rank following motivational factors within the
questionnaire: Sport Competition, Health, Fitness, Socialisation, Rehabilitation and
Entertainment (Table 1).
69
M. Proti and I. VuËkovi
Results showed that Socialisation (78.8 %) is the leading reason among athletes for
sitting volleyball participation. Closely behind are Entertainment (76.7 %) and Health (76.7 %),
as second two reasons by importance. Fitness (74.4 %) is also ranked as important factor, and at
the end are Sport Competition (69 %) and Rehabilitation (60.5 %), as two lowest motivational
factors (Table 1).
Table 1
Survey of participants by motivational factors of sitting volleyball engagement
Sport competition Health Fitness Socialisation Rehab Fun
Very important
69 %
76.7 %
74.4 %
78.8 %
60.5 % 76.7 %
Quite important
23 %
15.1 %
15.1 %
18.8 %
18.5 % 17.4 %
Little important
6.9 %
7 %
9.3 %
1.2 %
14.8 %
4.7 %
Not importantat all
1.1 %
1.2 %
1.2 %
1.2 %
6.2 %
1.2 %
Table 2 shows that the respondents consider all offered motives as important for sitting
volleyball engagement. Arithmetic mean tends to answer 4 (very important), and this is also
corroborated by the values of skewness and kurtosis. Although all from the offered motivational
factors are important to respondents, there are still minimal differences.
Table 2
Descriptive statistics of motivational factors fro sitting volleyball engagement
Std.
N Mean
Minimum Maximum Skewness Kurtosis
Deviation
Sport
87
3.60
.673
1
4
-1.656
2.296
competition
Health
86
3.67
.659
1
4
-2.065
3.714
Fitness
85
3.62
.707
1
4
-1.799
2.333
Socialisation
85
3.75
.532
1
4
-2.591
8.389
Rehab
81
3.33
.949
1
4
-1.171
.144
Fun
86
3.70
.615
1
4
-2.200
4.865
The results from the Mann Whitney U test in Table 3 indicate that there are no
statistically significant differences between younger and oder players by any motivating factor
for engagement in the sitting volleyball.
70
Motives for engagement in sitting volleyball
Table 3
Comparison between younger and older players by motivational factors
Sport comp Health
Fitness
Socialis
Rehab
Fun
Mann-Whitney U
756.000
849.000
774.000
755.000
693.500
812.500
Wilcoxon W
1.791.000
1.839.000
1.720.000
1.535.000
1.434.000
1.632.000
Z
-1.568
-.373
-1.030
-1.375
-.967
-.846
Asymp. Sig. (2-tailed)
.117
.709
.303
.169
.333
.397
Significant differences havenít been found between the players who experienced injury at
a younger age and players who experienced injury at the older age, in most of the motives (see
Table 4). Only in the motive of Sport competition, significant difference has been recorded
between examined groups (p<.05). Therefore, players who have suffered injury at a younger age,
value sport competition more unlike their colleagues who have suffered injury at the older period
of life.
Table 4
Comparison between the players who suffered injury in younger age and players who suffered
injury in older age by motivational factors
Sport comp Health
Fitness
Socialis
Rehab
Fun
Mann-Whitney U
401.500
452.000
411.000
465.000
437.000
511.500
Wilcoxon W
929.500
980.000
907.000
961.000
933.000
1.007.500
Z
-2.021
-1.393
-1.784
-.591
-1.173
.000
Asymp. Sig. (2-tailed)
.043
.163
.074
.555
.241
1.000
According to the Table 5, there are no significan differences between the groups of more
and less experienced players by any motivating factor for sitting volleyball participation.
Table 5
Comparison between less experienced and more experienced players by motivational factors
Sport comp Health
Fitness
Socialis
Rehab
Fun
Mann-Whitney U
745.500
671.000
774.000
649.000
606.000
776.000
Wilcoxon W
1.375.500
1.301.000
1.809.000
1.684.000
1.467.000
1.406.000
Z
-.495
-1.492
-.170
-1.647
-1.100
-.153
Asymp. Sig. (2-tailed)
.620
.136
.865
.099
.271
.878
71
M. Proti and I. VuËkovi
There is a difference in the Rehabilitation motive (p<.05) between the players who have
additional individual work and players who do not have it (see Table 6). The players who have
individual trainings in Rehabilitation see greater motivation to engage in the sitting volleyball
unlike their counterparts.
Table 6
Comparison between the players who have additional individual work and players who do not
have it by motivational factors
Sport comp Health
Fitness
Socialis
Rehab
Fun
Mann-Whitney U
779.000
654.000
786.000
773.500
490.500
754.500
Wilcoxon W
1.814.000
1.644.000
1.452.000
1.439.500
1.351.500
1.789.000
Z
-.363
-1.795
-.077
-.252
-2.702
-.714
Asymp. Sig. (2-tailed)
.716
.073
.939
.801
.007
.475
Further results clearly indicates there are no significant differences between the players
who practice only sitting volleyball, as a type of their physical activity involvement, and players
who are engaged in some other sports or type of physical activity by any motivational factor (see
table 7).
Table 7
Comparison between players who practice only sitting volleyball and players who are engaged
in some other sport by motivational factors
Sport comp Health
Fitness
Socialis
Rehab
Fun
Mann-Whitney U
767.500
697.000
627.500
678.500
590.000
713.000
Wilcoxon W
1.232.500
1.132.000
1.062.500
2.056.500
915.000
1.178.000
Z
-.320
-.960
-1.821
-1.359
-.741
-1.042
Asymp. Sig. (2-tailed)
.749
.337
.069
.174
.459
.298
The same can be concluded from the Table 8, where the findings havenít showed
significan differences between the players from better ranked teams and players from worse
ranked teams in all motivational factors for engagement in the sitting volleyball (by all factors
p>.05).
72
Motives for engagement in sitting volleyball
Table 8
Comparison between players from better ranked and worse ranked teams by motivational factors
Sport comp Health
Fitness
Socialis
Rehab
Fun
Mann-Whitney U
605.500
535.000
578.000
508.000
532.500
546.000
Wilcoxon W
1.166.500
1.238.000
1.281.000
1.036.000
997.500
1.249.000
Z
-.072
-1.184
-.219
-1.446
-.109
-.791
Asymp. Sig. (2-tailed)
.942
.236
.827
.148
.913
.429
The biggest influence on the players to engage in the sitting volleyball had their friends
who practice the same sport (Table 9). Other factors havenít showed almost any influence.
Table 9
Descriptive statistics of the most influential factors for sitting volleyball participation
Frequency
Percentage
Friend/sitting volleyball
59
67.0
Friend/volleyball
7
8.0
Acquaintance
7
8.0
Doctor
2
2.3
Therapist
3
3.4
Coach
1
1.1
Someone else
6
6.8
Information from medias
3
3.4
Total
88
100.0
Discussion
Results showed that Socialisation is the highly ranked motivational factor for sitting
volleyball engagement followed by entertainment, health, fitness and sport competition, from the
most to the least respectively. Percentage differences between those factors are not too big, but
they are big enough to notice the difference in relation to some other research with persons with
physical disabilities. Some of them (Dishman et, al. 1985; Brasile, & Hedrick, 1991; Fung, 1992;
Chen at, al. 2007) showed that improvement of physical fitness is the main reason of sport
participation. On the other hand, Chen at, al. (2007) have also found that elite athletes with
73
M. Proti and I. VuËkovi
physical disabilities in Mainland China value the most the motives of Entertainment and Skill
development. Chinese governmant has invested a great deal of money to sports for the purpose
of achieving medals at the international competitions. Thus, many Chinese athletes prioritise to
improve their skills and to successfully represent their country, unlike the athletes from our
research where the sports for the persons for disabilities are obviously still undeveloped.
Vute (1992) in his study indicates that the most important factor for the sitting volleyball players
is desire for success. K‰lbli et, al. (2006) and K‰lbli (2008) have found that at the beginning of
the sport career main motive for the athletes is desire for competition and participation at the
Paralympics. Later, with age and at the end of their careers the dominating motive is desire to
maintain good health.
It can be concluded that incentives which motivate people with physical disabilities are
various, in contingent upon geographical area where they live, type of disability, gender, age,
etc. The fact that participants from our study prioritize Socialisation is not surprising, because
most of them are still on the margins of the society where they live, and in constant struggle with
the economical and social problems. Therefore, it is also not surprising that the Entertainment
and Health are almost equally important for the athletes, and Fitness and Sport competition do
not take important place in the motives hierarchy. This could be interpreted as an escape to some
other reality where they are accepted as equal members with possibility to have fun, and
competition will be saved for the real life.
On the whole, the results of this research havenít showed significant differences between
groups of participants in most of the variables. Players who have individual trainings emphasise
the motive of Rehabilitation for their sitting volleyball participation. Encouraging result from
this study is that younger participants have higher incentives for sport competitions, then their
older colleagues. It presents good precondition to upgrade those motives in purpose of technical
and tactical improvement and for the achievement of better results. It was unexpected that
doctors, therapists and other practitioners do not have higher influence in the process of
socialisation and inclusion of athletes to sports and physical activities. They are the first who
meet persons with disabilities after the injury, and because of that, practitioners should be the
most important motivators toward people with disabilities to engage in physical activities, but
this issue requires further research. Unlike of them, their friends are marked as the most frequent
animators for the sitting volleyball engagement. This is also confirmed by Wu & Williams,
(2001). The problem of insufficient media coverage of sport for persons with disabilities should
be noticed, too.
The results of this study could be considered very important from two reasons: a)
research of motivational factors for sport participation among persons with physical disabilities
is very rare, and b) because research included 5 countries from the region where this issue is also
much unexplored. There are still much space for the new research in this area and we hope that
this paper will contribute, at least partially, for the improvement of the life style and socialisation
of the persons with disabilities.
The small number of women, insufficient number of participants by countries and clubs,
as well as athletes without disabilities and athletes with congenital physical disabilities, disabled
us to make a comparison between those groups and their counterparts. This presents limitation of
this study, but in the same time recommendation for the future research.
With the clear understanding of motivation of persons with disabilities for sport and
physical activity engagement, teachers, coaches and other practitioners could efficiently create
strategies and programs with purpose of satisfying exactly of that what is necessary.
74
Motives for engagement in sitting volleyball
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Submitted 31 January, 2011
Accepted 20 May, 2011
76