Jonas Holder
(2389965)
PHYSICAL ACTIVITY LEVELS OF STUDENTS IN
PHYSICAL EDUCATION
Thesis
Filing Date:
December 12th, 2011
Reviewer:
Prof. Dr. Wolfgang Schlicht
Institute of Sports- and Movement Science
University of Stuttgart
Contents
1. Introduction....................................................................................................................9
2. Review of the Literature...........................................................................................12
2.1. Definition of Key Terms............................................................................................. 12
2.1.1. Physical Activity....................................................................................................................... 12
2.1.2. METs............................................................................................................................................. 14
2.1.3. Energy Expenditure............................................................................................................... 15
2.1.4. Counts......................................................................................................................................... 16
2.2. Significance of Physical Activity.............................................................................17
2.2.1. Relationship of Physical Activity and Health..............................................................18
2.2.1.1. Obesity....................................................................................................................................................... 20
2.2.1.2. Type 2 Diabetes ..................................................................................................................................... 23
2.2.1.3. CVD.............................................................................................................................................................. 25
2.2.1.4. Cancer.......................................................................................................................................................... 28
2.2.1.5. Bonehealth................................................................................................................................................ 29
2.2.1.6. Mental Health.......................................................................................................................................... 31
2.2.1.7. Further Implications ........................................................................................................................... 32
2.2.2. Physical Activity as an important influence on child development (motoric,
emotional, psychosocial, cognitive) ............................................................................................ 32
2.3. Measuring Physical Activity.................................................................................... 33
2.3.1. Self-report methods............................................................................................................... 35
2.3.1.1. Physical activity questionnaires (PAQs)........................................................................................35
2.3.1.2. Activity Diary/Log ................................................................................................................................. 37
2.3.1.3. Recall interviews..................................................................................................................................... 37
2.3.2. Objective Methods.................................................................................................................. 37
2.3.2.1. Pedometry................................................................................................................................................ 37
2.3.2.2. Accelerometry......................................................................................................................................... 38
2.3.2.3. Heart rate monitoring.......................................................................................................................... 39
2.3.2.4. Combination (heart) sensors............................................................................................................ 40
2.3.2.5. Doubly Labeled Water (DLW)............................................................................................................ 43
2.3.2.6. Direct/indirect/room calorimetry................................................................................................... 43
2.3.2.7. More............................................................................................................................................................. 44
2.3.3. Others........................................................................................................................................... 44
2.3.3.1. Observation/Time keeping................................................................................................................. 44
2.4. Literature on Physical Activity in Children.......................................................44
2.4.1. Recommended amount of Physical Activity................................................................45
2.4.2. Actual Amount of Physical Activity................................................................................. 46
2.4.3. Consequences of low Physical Activity Levels............................................................47
2.4.4. Why Physical Education? (Legitimization)..................................................................50
2.4.5. What constitutes the quality of Physical Education?...............................................51
2.4.6. Physical Activity Levels in Physical Education – Previous studies.....................54
3. Empirical description of the study.......................................................................63
3.1. Methods........................................................................................................................... 63
3.1.1. Participants and setting....................................................................................................... 63
3.1.2. Instruments and procedures............................................................................................. 64
3.1.3. Data analysis............................................................................................................................ 65
3.2. Hypotheses..................................................................................................................... 66
4. Results.............................................................................................................................69
5. Discussion .....................................................................................................................77
6. Outlook............................................................................................................................81
Literature............................................................................................................................82
Acknowledgment.............................................................................................................93
Erklärung............................................................................................................................94
Appendices.........................................................................................................................95
I. Parental Information....................................................................................................... 95
II. Parental Declaration of Consent............................................................................... 96
III. Small Questionnaire about Personal Information...........................................97
IV. Demographic Data......................................................................................................... 98
Age............................................................................................................................................................ 98
Gender.................................................................................................................................................... 98
Grade....................................................................................................................................................... 99
V. Exemplary Visualized data of one student's lesson........................................100
List of Figures
Figure 1: The sub-categories of physical Activity
( http://www.fitness.gov/digest_mar2000.htm)..................................................14
Figure 2: Linear-inverse dose-effect-relationship between volume of
activity and risk of disease respectively risk reduction (mod. after Schlicht
& Brand, 2007, p.62 figure 6.1)...................................................................................20
Figure 3: Curvilinear-inverse dose-effect-relationship between volume of
activity and risk of disease respectively risk reduction (mod. after Schlicht
& Brand, 2007, p.62 figure 6.1)...................................................................................21
Figure 4: Multivariate relative risk of developing type 2 diabetes according
to physical activity levels in women with and without a parental history of
diabetes. (Hu et al., 1999, as printed in Hardman & Stensel, 2009, p. 107) 26
Figure 5: Relative risk of developing type 2 diabetes according to energy
expenditure (Weinstein et al., 2004, as printed in Hardman & Stensel,
2009, p. 108)......................................................................................................................26
Figure 6: Hancox: Prevalence of selected CVD risk factors at age 26 years
according to the mean hours of television viewing per weekday between
the ages 5 and 15 (Hancox et al., 2004)....................................................................29
Figure 7: Relationship of fitness to cancer deaths (Blair et al., 1998)..........30
Figure 8: The mean playing-to-non-playing arm difference in the bone
mineral content of the humeral shaft in 105 Finnish national-level female
tennis and squash players and 50 age-matched female controls.(Kannus et
al., 1995)..............................................................................................................................31
Figure 9: Measuring Physical Activity -Levels of Sophistication (Ekelund) 35
Figure 10: Comparing the AEE accuracy of the Actiheart to the Cosmed
K4b2 (Crouter et al., 2007)...........................................................................................43
Figure 11: schematic depiction of the 'children movement pyramid' (Graf et
al., 2006)..............................................................................................................................47
Figure 12: Physical activity levels of Dutch school children during PE
lessons (Slingerland et al., 2011)................................................................................58
Figure 13: Average EE of the children during the 7 lessons (n=22; lesson
time: 90 min) (Fröhlich et al., 2008).........................................................................61
Figure 14: Physiological Performance Curve - relationship between time of
day and physiological performance capability (mod. after Rothfuchs, 1995)
.................................................................................................................................................68
Figure 15: Mean MET values of all students over the course of their lessons.
.................................................................................................................................................77
Figure 16: Male twelfth grader..................................................................................102
List of Tables
Table 1: Multidimensional and hierarchical structure of physical fitness
(www.fitness.gov).............................................................................................................14
Table 2: Energy required for a variety of activities (Ministry of Agriculture,
Fisheries and Food. Manual of Nutrition. London: HMSO, 1992.)...................16
Table 3: International cut-off points for youth (Cole et al., 2000)..................21
Table 4: Risk Factors for Coronary Heart Disease (Jackson, 2004)................26
Table 5: Exercise recommendations for enhancing bone mineral accrual in
children and adolescents (Kohrt et al., 2004)........................................................31
Table 6: Measuring Physical Activity - Methods and Outcomes (Modified
after Ekelund)....................................................................................................................34
Table 7: Recommendations to the 'children movement pyramid' (mod. after
Graf et al., 2006)................................................................................................................46
Table 8: Cut points for moderate and vigorous activity, based on Stratton
(1996) (Slingerland et al., 2011)................................................................................55
Table 9: %MVPA by gender and grade (Slingerland et al., 2011)....................55
Table 10: Overview German Studies PA in PE........................................................57
Table 11: Movement times from various older studies (mod. after
Hoffmann, 2011)...............................................................................................................58
Table 12: Relative and absolute time students spent at different intensity
levels with an absolute lesson time of 51 min (n=132) (mod. after Wydra,
2009).....................................................................................................................................60
Table 13: Relative and absolute time students spent at different intensity
levels with an absolute lesson time of 76 min (n=417) (mod. after Wydra,
2010).....................................................................................................................................61
List of Abbreviations
2H
Over the course of two hours
AEE
Advanced Energy Expenditure
ALT-PE
Academic learning time in physical educational
ANOVA
Analysis of variance
BMC
Bone mineral content
BMD
Bone mineral density
BMI
Body mass index
BPM
Beats per minute
CDC
Centers for disease control and prevention
CO
Carbon dioxide
COPEC
Council for Physical Education for Children
CVD
Cardiovascular disease
DLW
Doubly Labeled Water
EE
Energy Expenditure
e.g.
exempli gratia, for example
et al.
et aliae, and others
etc.
etcetera
f
following
GPS
Global Positioning System
h
hour
HEPA
Health Enhancing Physical Activity
HR
Heart Rate
HRR
Heart Rate Reserve
IC
Indirect caloriometryi
t.e.
id est, that is
IPAQ
International Physical Activity Questionnaire
JUGS
Jugendgesundheitsstudie Stuttgart
kcal
kilocalorie
kg
kilogram
KIGGS
Kinder- und Jugendgesundheitssurvey
kJ
kilojoule
m2
square meter
MET
Metabolic Equivalent
min
minute
2
ml
millimeter
mod.
modification
MVPA
Moderate-to-vigorous physical activity
no.
Number
p.
Page
PA
Physical activity
PAL
Physical activity level
PAQ
Physical activity questionnaire
PASE
Physical activity scale for the elderly
REE
Resting energy expenditure
RMR
Resting metabolic rate
SAM
StepWatch Activity Monitor
SWA
SenseWear Armband
TEE
Total energy exppenditure
TV
television
UK
United Kingdom
US
United States
USA
United States of America
VO2max
Maximal oxygen uptake
vs.
versus
WHO
World Health Organzation
WRC
Whole room clorimeter
XXL
extraextralarge
yr
year
zyk
cyclic
9
1. Introduction
“Considering the background of an environment that offers students less and less
natural causes for physical activity, the age-appropriate facilitation of health-awareness and
fitness has an outstanding meaning” (Bildungsplan 2004 Allgemein bildendes Gymnasium).
This is part of the central theme about the contents of physical education in BadenWürrtemberg. Additionally, the physical abilities (endurance, strength, speed, flexibility) are
mentioned as specific goals for the different grades: "the physical abilities endurance,
strength, flexibility and speed [...] remain a central component of the classes [sixth grade]";
"the facilitation of the physical abilities, especially endurance and strength as basis for overall
fitness [...] remains at the center of physical education, in this grade as well [eighth grade]"
(Bildungsplan 2004 Allgemein bildendes Gymnasium).
This shows that physical activity is still at the center of physical education, even though other
goals are important as well (education through sport, education to sport).
This looks good in theory but it also raises the following questions: How much do students
really move during physical education. How high are the physical activity levels during a
typical lesson? How can the amount of physical activity be measured? What factors play a role
in the amount of physical activity? Can physical education contribute significantly to the
above-mentioned fitness of children and adolescents? And can fitness in fact be a realistic goal
with limited time and spatial resources at schools and adjacent gymnasiums?
These are some of the questions that I will try to answer throughout the course of this work.
It will be interesting to see whether any conclusions on how to improve physical education
can be deducted.
A special focus will be on the effects of physical activity on fitness and health an whether and
how physical education can contribute to this important issue.
“1. Children and youth aged 5–17 should accumulate at least 60 minutes of
moderate- to vigorous intensity physical activity daily.
2. Amounts of physical activity greater than 60 minutes provide additional health
benefits.
3. Most of the daily physical activity should be aerobic. Vigorous-intensity activities
should be incorporated, including those that strengthen muscle and bone, at least 3
times per week.” (WHO 2011)
10
This is the recommendation on how much physical activity children and adolescents should
accumulate each day, provided by the World Health Organization.
Another recommendation, written for adults, states that adults should be physically active
with moderate intensity for 30 minutes on most, if not on all days (Schlicht & Brand, 2007,
p.12). This is called the Health Enhancing Physical Activity Recommendation (HEPA). They also
express their recommendation in concrete numbers, namely 1200kcal per week, additionally
to the basal metabolic rate (Schlicht & Brand, 2007, p.60).
It is apparent, that school, namely physical education, is one of the main areas, from which this
recommended physical activity could come from, for the simple reason that nearly all children
and adolescents have to participate in it. In order to examine, whether physical education is
indeed suited to meet these requirements, moderate- to vigorous intensity physical activity
has to be defined and then measured during physical education.
Another area where physical education could be beneficial is exemplified by an abundance of
reports in the media about children's and adolescents' deteriorating motor skills, rising levels
of obesity, and general lack of fitness which seem omnipresent nowadays. Headlines where
today's children are called “fat, lazy and addicted to TV” (Laging, 2006) or “generation XXL”
(Graf, 2008) are a cause for concern. Add this to the ongoing urbanization with increasingly
few opportunities for children to move around their environment freely and safely and
physical education might be the only constant source for physical activity in many children's
lives. Can it live up to expectations or are physical activity levels that contribute significantly
to children's well-being just not possible in gymnasiums where as many as 60 students are
crammed in at the same time and that often only once a week?
In order to try and answer these many questions, the work will continue with the following
structure:
I will start by reviewing the current literature in the field of the study and begin with
explaining essential terms without whom the following would be difficult to understand. After
that, the significance of physical activity will be addressed. That means the question why
someone should bother to try and assess physical activity levels will be answered. Here, its
relationship with disease and child development will be in the foreground. The next step will
be, to take a look at different possibilities to measure physical activity and their advantages,
disadvantages and their possible fields of application. In the following, literature about
physical activity of children and adolescents in general will be examined. The last part of the
literary review will be about physical education and activity levels during physical education.
11
After that, I will state a number of hypotheses regarding the amount of physical activity in
physical education and the variables influencing it. These hypotheses will be based on findings
of previous studies (and personal experience). In the next chapter, the study will be described
on an empirical level. Following that are the results of the conducted study, the subsequent
discussion and an outlook on further possible ways of proceeding in this field of study.
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2. Review of the Literature
In this chapter, I will lay the groundwork for this study by giving an overview on the
literature in regard to physical activity, physical education and its implications. First, key
terms and concepts, that are important in order to understand the following, will be
explained. Afterward the significance of physical activity based on the relationship between
physical activity and health on the one hand, and child development on the other hand, will be
addressed. Here the focus will be on some common diseases which result from insufficient
physical activity. Furthermore, the difficult task of measuring physical activity with different
approaches will be looked at and evaluated. After that I will concentrate on the amounts of
physical activity in people's lives, with a special focus on children and adolescents, and
summarize findings regarding recommended physical activity levels and compare them with
the actual physical activity levels which were the results of numerous studies. Finally, I will
shift the focus to physical education and specifically the role of physical activity levels during
lessons.
2.1. Definition of Key Terms
The following pages are devoted to give the reader a basic understanding of some of
the key terms and concepts regarding this work. In the foreground will be the understanding
of physical activity which, due to the nature of the conducted study, features a prominent role
in this paper and, since it has proven to be a quite difficult concept, deserves further attention.
Additional concepts from the general field of physical activity will be explained.
2.1.1.Physical Activity
“Physical activity is defined as any bodily movement produced by skeletal muscles that
requires energy expenditure” (WHO, 2001) or very similar: “Bodily movement that is
produced by the contraction of skeletal muscle and that substantially increases energy
expenditure” (Adapted from USDHHS, 1996).
Another useful definition is: “Athletic,
recreational or occupational activities that require physical skills and utilize strength, power,
endurance, speed, flexibility, range of motion or agility; PA is a behavioral parameter used to
evaluate a Person's cardiovascular 'reserve'” ( Segen, 2006).
The first two definitions already give us important information about the measuring of
13
physical activity, which can specified by the amount of energy, a certain activity consumes.
Units in which physical activity can be expressed are for example METs or kilojoules which
will be more closely explained in the following passages and in chapter 2.3 Measuring Physical
Activity.
It is important to differentiate physical activity from related terms like 'exercise' and 'physical
fitness'. Physical activity has many dimensions, some of which can be seen in the following
figure:
Figure 1: The sub-categories of physical Activity
( http://www.fitness.gov/digest_mar2000.htm)
“Exercise, is a subcategory of physical activity that is planned, structured, repetitive, and
purposeful in the sense that the improvement or maintenance of one or more components of
physical fitness is the objective” (WHO, 2001).
Physical Fitness is characterized as “A set of attributes that people have or achieve relating to
their ability to perform physical activity” (U.S. Department of Health & Human Services, 1996).
Another, more specific definition is: “Physical fitness is a state of well-being with low risk of
premature health problems and energy to participate in a variety of physical activities”
(Howley & Franks, 1997). The multidimensional and hierarchical structure of physical fitness
is summed up in the following table:
14
Table 1: Multidimensional and hierarchical structure of physical
fitness (www.fitness.gov)
Following the definitions of the terms physical activity, exercise and physical fitness, the most
interesting variable concerning physical education is physical activity.
2.1.2. METs
Since the notion of physical activity has been established, the next step is to look at how
it can be illustrated in a way that it becomes comparable and possible to work with. One such
tool which describes levels of physical activity like this are 'METs' (Metabolic Equivalents). A
MET is defined as “the ratio of the work metabolic rate to the resting metabolic rate. One MET
is defined as 1 kcal/kg/hour and is roughly equivalent to the energy cost of sitting quietly. A
MET also is defined as oxygen uptake in ml/kg/min with one MET equal to the oxygen cost of
sitting quietly, equivalent to 3.5 ml/kg/min” (WHO, 2001), this means that MET is a
physiological concept, which expresses the energy cost of physical activities as Multiples of the
resting metabolic rate (RMR).
All in all, METs are a very useful tool to measure, evaluate and compare physical activity levels.
They provide a useful possibility (particularly for school lessons) to categorize physical
activity spent at certain intensity levels: Light activity is 1-2,9 MET, moderate activity is 3-5,9
MET and vigorous activity is 6 and above MET. They are, however, to be used carefully, for the
reasons stated above, and shouldn't be the only mean of estimating physical activity levels.
15
2.1.3.Energy Expenditure
As you know now, METs and energy expenditure are related because METs can be
derived from either oxygen uptake or energy expenditure. Thus a higher energy expenditure
means higher MET-levels. Energy expenditure can be measured with multiple methods, such
as accelerometry or heart rate monitoring, which will be explained in detail in chapter 2.3
Measuring Physical activity.
Humans oxidize (metabolize) carbohydrate, protein, fat (and alcohol) to produce energy. The
energy is needed to maintain body functions like breathing, for physical activity and for
growth and repair (Rowett Research Institute). In this study, especially the portion stemming
from physical activity (Advanced Energy Expenditure/AEE) is of interest.
The units for energy are either joules or calories, with one calorie being equivalent to 4,184
joules. The total energy expenditure (TEE) of a person over a period of time can be divided
into different components: the basal metabolic rate (BMR) which usually makes up for about
60-75% of TEE, the diet induced thermogenesis, about 10% and the part which results from
physical activity which will be called advanced energy expenditure (AEE) in this work and
accounts for between 15 to 30% of the TEE.
Energy expenditure during physical activity is a very useful tool when comparing physical
activity levels of multiple persons and/or activities. However, there are a couple of things that
have to be taken into account: It depends heavily on the intensity, duration, frequency of the
activity and on body mass and fitness of the person in question. That means a heavier person
who does the exact same movements as a lighter person has a significantly higher energy
expenditure. So weight has to be a part of the formula used to calculate energy expenditure.
This is the case in AEE, individual fitness levels, age and gender,however, which could also be
varying factors, are not.
Similar to the METs, activities can also be classified according to their physical intensity levels
using energy expenditure in kJ/min. Examples are provided in the following table:
16
Table 2: Energy required for a variety of
activities (Ministry of Agriculture, Fisheries
and Food. Manual of Nutrition. London:
HMSO, 1992.)
Measurement of energy expenditure can be achieved for example by indirect calorimetry or
heart rate monitoring which will be explained in detail in chapter 2.3. The amount of
recommended physical activity, recommended by the HEPA e.g. is an additional 1.200 kcal on
top of the REE to minimize the risks of physical inactivity (Schlicht & Brand, 2007, p. 60).
To sum up, the energy expenditure, AEE in particular, is a very useful tool in order to describe
and compare physical activity levels of different activities and persons. In this study it will be
featured prominently since the “Actiheart system is designed to calculate Activity Energy
Expenditure (AEE) using recorded heart rate and/or activity levels” (Camntech, p.37).
2.1.4. Counts
The abstract unit 'count' is what you get if you look at the results of accelerometry. This
means that any kind of pedometer or highly sophisticated accelerometer produces the same
unit, which, on its own is “inherently neither meaningful nor interpretable” (Troiana, 2006).
But since accelerometry is the most commonly used objective method to determine physical
activity (more than 90 studies annually in 2003 and 2004 (Troiano, 2006), there is of course a
way to transform these counts into meaningful caloric estimates of energy expenditure or the
related categorical measure of time spent in moderate- or vigorous- intensity activity, which
makes the data more useful for multiple applications (Troiano, 2006). If this is achieved ,the
accelerometer data can be used to compare individual lifestyles with recommended physical
17
activity levels and individual physical activity levels during specific activities with the data
given in the 'Compendium of Physical Activities' for example.
The general “approach to translate accelerometer counts into energy expenditure has been to
compare activity and oxygen consumption measured during performance of a series of
activities that reflect activities of daily living” (Troiano, 2006). “After the simultaneous counts
and oxygen consumption are obtained, regression methods are applied to determine the
relationship between the two measures, and an equation to predict energy expenditure from
accelerometer counts and/or a count threshold for a particular intensity of activity is
determined” (Troiano, 2006). Aside from the fact, that spiroergometry is rather expensive and
very time-consuming, there is a major disadvantage if accelerometry data is used on its own:
Depending on the place where the accelerometer is attached to the body, certain movements
usually remain undetected. The most common spot for the accelerometer is the waist but it is
well-documented that waist-worn accelerometers severely underestimate upper body
movement. Equations based on locomotive movement underestimates lifestyle activities and
the other way around. There are efforts by Crouter et al. (2007) to minimize this effect by
switching back and forth between two equations, one for rhythmic activities like running or
walking and one for arrhythmic or mixed movement activities. While this approach seems
useful, the more promising method would be to use a combination method like the one used in
this study (see chapter2.3.2.4 Combination (heart) sensors).
A closer look at the different objective methods to measure physical activities will follow in
chapter 2.3 Measuring Physical activity.
2.2. Significance of Physical Activity
Why is physical activity an important field of study? Common sense tells us, that it is
important to be physically active. But is this really the case? And what are the real reasons to
subject yourself to regular movement and exercise? This following chapter tries to shed a light
on the relationship between physical activity and health and what happens if insufficient
physical activity is implemented in one's life. In other words: The connection between physical
inactivity and common diseases. There is a plethora of scientific evidence concerning this
topic and a quick search in local libraries has produced results like: 'Current results on health
and physical activity' (Hollmann et al., 2001), ‘Physical Activity and Health. The evidence
explained’ (Hardman & Stensel, 2009), 'Physical activity and health' (Norgan, 1992), and
18
many more. I will try to give a short overview over the most common health related topics and
how they are connected to physical activity.
Aside from health, another very important aspect of physical activity is its contribution to the
development of children and adolescents who are of special interest because of the nature of
the conducted study.
2.2.1. Relationship of Physical Activity and Health
"Apart from the connection of physical inactivity with morbidity, i.e. causing
various organic diseases in the area of the heart-circulation-system, scientific
findings increasingly corroborate the biopositive effects on mortality. Statistics
prove that individuals who deliberately subject themselves to regular and
reasonably dosed physical exercise have a greater life expectancy" (Hollmannet al.,
2001)
“Approximately 3.2 million deaths and 32.1 million DALYs – representing about
2.1% of global DALYs – each year are attributable to insufficient physical activity”
(WHO, 2009 as cited in Mendis et al., 2011)
These quotes clearly illustrate the importance of physical activity in regard to overall health
and well-being, which is why in this chapter the focus will be on the relationship between
physical activity and health, with a special attention on children and adolescents. The
emphasis on children is due to the fact that children and adolescents are the subjects of
interest in this study and because a relationship between activity in childhood and health in
adulthood seems to exist. This is an important issue because most of the time disease doesn't
manifest itself until later in life. This point of interest however is difficult to research because
large longitudinal studies with long-term follow-up periods are necessary in order to come up
with valid data. A special look will be taken at typical diseases which are related to low or
insufficient physical activity levels. The aspects of health and types of diseases that will be
examined in the following chapters are obesity, type 2 diabetes, cardiovascular disease (CVD),
cancer, bone health, mental health and a quick overview of further implications.
Aside from the well-being of people, health is also an economic issue. Especially obesity and
type 2 diabetes have developed into widespread diseases which cost insurances and the the
state a lot of money and resources. This point just adds to the reasons why the factors which
influence these diseases need to be closely examined.
If we want to talk about health, a definition is indispensable:
"A state of complete physical, mental and social well-being, and not merely the absence of
19
disease" (WHO, 2001).
Figure 2: Linear-inverse dose-effectrelationship between volume of activity and
risk of disease respectively risk reduction
(mod. after Schlicht & Brand, 2007, p.62
figure 6.1)
“Physical activity is beneficial for physical health” is a statement the authors Schlicht & Brand
(2007) agree with (p. 60). However, there are different theories about the relationship
between amounts of physical activity and their immediate effects. One model, which seems to
apply to the the risk for coronary heart disease (Schlicht & Brand, 2007, p.62) is linear and
inverse (see figure: 2). That means, the more physical activity, the lower the risk for disease:
Curvilinear and inverse is the HEPA-recommendation, which means that too low and too high
physical activity levels are detrimental for one's health. This seems to be the case for strokes
(Schlicht & Brand, 2007, p.62).
20
Figure 3: Curvilinear-inverse dose-effectrelationship between volume of activity
and risk of disease respectively risk
reduction (mod. after Schlicht & Brand,
2007, p.62 figure 6.1)
It is important to realize that there is a close connection between physical activity and health.
But what this connection looks like exactly for every disease, age-group and even individual, is
difficult to say and, in some cases, still up for debate. However, the amount of physical activity,
necessary to improve health, has been the subject of various studies: Buksch and Helmert
(2004) found out that as little as less than an hour of strain per week lowers the mortality,
compared to inactive people. (For further elaborations see: Mensink et al., 1996, or Klein et al,
2001, as cited in Schlicht & Brand, p.64). Additional studies, concerned with the necessary
amount of physical activity to lower health risks, showed results ranging from 30 minutes per
week (Health Professional Follow-Up Study), over 2,5 hours per week (Manson et al., 2002) up
to 20 km of vigorous marching per week (Sesso et al., 2000). This leads to the conclusion that
the quantity of physical activity, however much it may be, in the field of health prevention is
essential. For further information on recommended and actual physical activity see chapter
2.4.
2.2.1.1. Obesity
In the media you hear reports about the so-called 'XXL-generation' and how parents
will outlive their children. This shows you that obesity is a societal issue. "Obesity is
recognized as a major health problem in western society. Maintenance of an acceptable body
21
weight is therefore an important aspect of a healthy lifestyle" (Saris, 1992). In Stuttgart alone,
17.2% of the girls and 15,4% of the boys are overweight. In terms of obesity, rates have just
about doubled since the 80s: 5,9% of the girls and 6,9% of the boys are considered overweight
(JUGS).
Since low levels of physical activity in children as well as in adults predisposes them to
become obese, the connection between physical activity and children's weight is worth taking
a look at. I will start by explaining how obesity is measured and by giving an overview of how
prevalent the problem of overweight and obesity in Germany and the rest of the world is:
The most common tool for describing whether someone is overweight or obese is the BMI. An
adult is considered overweight with a BMI of over 25 and obese with a BMI of over 30. Cole et
al. proposed a system to determine when a child is considered overweight or obese. The
following table shows the international cut off points for body mass index for overweight and
obesity by sex between 2 and 18 years, defined to pass through body mass index of 25 and 30
kg/m2 at age 18, obtained by averaging data from Brazil, Great Britain, Hong Kong,
Netherlands, Singapore, and United States:
Table 3: International cut-off points for youth (Cole et al., 2000)
22
Another approach, using the BMI, is "to use a given BMI percentile to indicate overweight and
obesity, often the 85th and 95th percentiles, respectively" (Hardmann & Stenzel, 2006,
p.210f). The main problem with the BMI is that it doesn't differentiate between different
tissue types. This means that an athletic, muscular person could be considered overweight by
just looking at the BMI. Despite this limitation, it has still been shown to be an adequate tool
for diagnosing obesity in children (Must & Anderson, 2006; Reilly, 2007). Another method
altogether in diagnosing obesity, would be the measuring of the waist circumference
(McCarthy et al. 2003).
According to the Kinder- und Jugendgesundheitssurvey (KIGGS) in Germany for the age group
3-18 years, there are 1,9 million overweight, among them 800000 obese children, which
equates to 15% total (Kurth & Schaffrath, 2007). In Europe, regionally there are estimates of
overweight rates of up to 35% among children and adolescents (Jackson-Leach & Lobstein,
2006) or that an overall of about 20% of children and adolescents are overweight or adipose
(Jackson-Leach & Lobstein, 2006). Other studies showed that in the USA obesity levels raised
from 5% in the 1960/70s to 17% in the year 2003/4 (Odgen, 2006).
In the following paragraph, I will try to highlight the connection between physical activity and
weight in children and adolescents: "From the reviewed research, it seems that exercise plays
an important role in the prevention of weight gain. Increasing physical activity seem to be an
effective way to increase the metabolic potential to maintain energy balance. Several factors
are involved that are not fully understood. Nevertheless, all available data indicates that
exercise is one of the most powerful effectors in this delicate balance between energy input
and output" (Saris, 1992, p.167) Data that supports this statement, is from multiple studies,
for example one study
“set in a large urban high school in Houston, Texas observed that physical activity
levels (assessed by ankle actigraphy)in overweight (BMI >= 95th percentile on CDC
2000 BMI charts) female adolescents were 10% lower than normal-weight (BMI
<85th percentile ) adolescents. Moreover, in those considered at risk of overweight
(BMI >= 85th percentile but >95th percentile) physical activity levels were 6%
lower than normal-weight girls (Sulamana et al. ,2006). [Another study was the]
European Youth Heart Study (Ruiz et al., 2006) [in which] vigorous-intensity (>6
METs) physical activity, but not moderate or overall physical activity, was
associated with lower body fat in 780 children aged 9-10 years, while a study
involving 2859 Spanish adolescents found that high levels of cardiorespiratory
fitness (predicted VO₂max) and low participation in sedentary activities (less that
two hours per day) were associated with lower abdominal obesity as measured by
waist circumference" (Ortega et al. 2007) (Hardman & Stenzel, 2006, p.212).
However, not all studies have detected a relationship between physical activity levels and
23
obesity: A study conducted by Ekelund et al. (2002) showed no such relationship (assessed
using doubly labeled water). Nonetheless, the total physical activity levels were lower in in
obese, than in normal-weight adolescents (assessed using accelerometry).
Longitudinal studies, examining this relationship, have also shown conflicting findings: Kimm
et al. (2002) showed that higher levels of physical activity leads to lower rates in of increase in
BMI and adiposity in girls between the age of 9-19. A very different result was presented by
Kettaneh et al. (2005), who found out that the girls with the highest physical activity rates had
the highest increase in BMI.
In the JUGS, the effects of obesity on other aspects of life were examined and the results
showed that psyche and academic performance suffered the most. Adolescents assessed their
psychic well being and their academic performance significantly lower scores in the
questionnaires.
Since most studies show an inverse association between physical activity levels and
overweight/obesity, the goal of keeping these diseases in check makes it necessary to examine
physical activity levels in different contexts.
2.2.1.2. Type 2 Diabetes
“Diabetes mellitus is a metabolic disorder, resulting in the inability to properly
metabolize carbohydrates and control blood sugar levels because the normal
insulin mechanism is ineffective” (Jackson, 2004, p.239).
The significance of this disease shall be exemplified by the following quatation:
“Diabetes may lead to kidney failure, circulation problems, gangrene and
amputation, blindness or retinal damage, heart attack or stroke. It is a major risk
factor for coronary heart disease, and is the seventh leading cause of death from
disease in the United states” (Jackson, 2004, p.239).
The cases of type 2 diabetes, which is closely related to obesity, in children and adolescents
have increased dramatically in the last 20 years. In the time before 1990, only two cases of
type 2 diabetes in children were reported in the literature, whereas between 2000 and 2003,
53 cases were reported (Pinhas-Hamiel & Zeitler, 2005). They also wrote that before in 1990,
only 2% of all children and adolescents, which were diagnosed with diabetes in America, type
2 was noted. But in 2004, 45% of all newly diagnosed diabetic children and adolescents had
type 2 diabetes. This trend seems to be worldwide as a corresponding development could be
noted in the following countries: Japan, Taiwan, Singapore, Hong Kong, Thailand, New Zealand,
Argentina, America and Canada (Pinhas-Hamiel & Zeitler, 2005).
24
The connection between type 2 diabetes and obesity can be seen in the following study,
conducted by Haines et al. (2007): Of the children diagnosed with type 2 diabetes in the UK,
95% were overweight and 83% were obese.
However drastic the rises in the rates of type 3 diabetes among children and adolescents
seem, it is still a fairly rare disease in young people, "with rates of 17,0-49,4 per 100000
person-years documented among 15.19 year-old minority groups in the United States"
(Writing Group for the SEARCH for diabetes in Youth Study Group 2007, as seen in Hardmann
& Stenzel, 2006).
Multiple studies have found a strong link between obesity and insulin-resistance, which is an
important marker for type 2 diabetes (Viner et al,. 2005; Lee et al., 2006, seen in Hardmann &
Stenzel, 2006, p.217).
"Clearly, physical activity has the potential to assist in the prevention of type 2 diabetes in
children and adolescents by virtue of its effect on body composition" (Hardman & Stenzel,
2006, p.216).
Concrete evidence of this matter is hard to come by and there are no trials which test whether
physical activity could prevent type 2 diabetes. The main reason for this is the relative rarity of
the disease in young people which is why huge numbers of subjects would be required.
However, insulin-sensitivity and resistance, respectively, give evidence, "that regular physical
activity could make a contribution to the prevention of type 2 diabetes in children and
adolescents" (Hardman & Stenzel, 2006, p.216):
"Findings from the National Health and Nutrition Examination Survey have
demonstrated that high levels of physical activity (assessed by questionnaire) and
cardiovascular fitness (predicted VO₂max) are significantly and positively
associated with insulin sensitivity in male adolescents (Imperatore et al., 2006).
Furthermore, the European Youth Heart Study found that total, moderate and
vigorous physical activity (assessed by accelerometry) was inversely correlated
with insulin resistance (assessed using homeostasis model assessment) in 613
Swedish adolescents (Rizzo et al., 2008). These findings suggest that regular
physical activity could make a contribution to the prevention in type 2 diabetes in
children and adolescents" (Hardman & Stenzel, 2006, p.216).
This fact makes it worthwhile to further examine physical activity levels of children and
adolescents and ways to improve them.
The correlation between physical activity and diabetes type 2 can be seen in the following two
tables:
25
Figure 4: Multivariate relative risk of developing
type 2 diabetes according to physical activity
levels in women with and without a parental
history of diabetes. (Hu et al., 1999, as printed in
Hardman & Stensel, 2009, p. 107)
Figure 5: Relative risk of developing type 2 diabetes according to
energy expenditure (Weinstein et al., 2004, as printed in Hardman
& Stensel, 2009, p. 108)
2.2.1.3. CVD
Cardiovascular disease and condition is a collective term for a number of distinct
diseases which are summarized under this name. These diseases include: heart attack,
atherosclerosis, angina pectoris, arrhythmias, congenital heart defects, rheumatic heart
disease, congestive heart failure, bacterial endocarditis, aneurysms, hypertension and stroke
(Jackson, p. 176).
26
According to Mendis et al.'s Global atlas on cardiovascular disease prevention and control
(Mendis et al., 2011), Cardiovascular disease (CVD) was the cause of death for 17 million
people during that year. It is one of the most frequent causes of death in the world, more
prominent than cancer. In fact, “for every person who dies of cancer in the USA, almost 2
people die of CVD” (Jackson, 2004, p.174). Not only does it inflict pain and suffering, it also
costs a lot of money. In the US, “it's estimated that cardiovascular disease cost the nation more
that $ 351 billion in treatment and lost productivity in 2003” (Jackson, 2004, p. 174).
Risk factors for coronary heart disease can be grouped into clusters of factors which you can
do something about and factors that we can't change. You can see those factors in the
following table:
Major alterable
Major unalterable
Hypertension
Age
Tobacco smoking Genetics
Cholesterol
Gender
Physical inactivity
Obesity
Diabetes
Contributing
Stress
Excessive Alcohol
Table 4: Risk Factors for Coronary Heart Disease (Jackson, 2004)
As you can see in this table, there are several alterable risk factors which are connected to
physical activity, in fact except for smoking, a case could be made for all major alterable risk
factors.
Although the disease doesn't present itself until later in life, evidence that the disease starts in
childhood can be found (McGill et al., 2000). This situation presents the important field of
study whether physical activity in childhood can slow down the development of the disease.
There are many studies, examining the relationship of physical activity in adulthood and the
prevalence of CVD. The first study of this kind was conducted in the 1950s (Morris et al.,
1953) and showed a negative correlation between work-related physical activity and the
incidence of CVD (Schuler, 2005). Subsequent studies, during which up to a couple thousand
participants were examined, confirmed those findings unequivocally (Schuler, 2005). The
most famous study is the Harvard alumni study ( Pfaffenbarger et al., 1986), which studied
16936 college alumni from Harvard University. They were questioned in regard to their
physical activity and then followed for 12-16 years. A linear, negative correlation between
energy expenditure and cardiovascular mortality was detected. Persons who expended about
1,5 ·10⁷ J (3500kcal) per week in physical activities were able to reduce their cardiovascular
risk by 50% compared to inactive participants (Schuler, 2005). However, only vigorous
27
physical activity had a significant effect, concerning cardiovascular mortality, light physical
activity affected the total but not the cardiovascular mortality (Schuler, 2005). Similar studies
which measured either the exercise capacity ( Myers et al., 2002) or the physical fitness
(Kujala et al., 1998; Manson et al., 1999; Stampfer et al., 2000) all came to similar negative
linear correlation between physical activity or capacity. Physical capacity even proved to be a
better predictor than previously know risk factors: An increase of the capacity of 1 MET lead
to a decrease of mortality of 12% (Schuler, 2005).
All in all, there are 30 publications from this field of primary prevention with a total of 249315
test-subjects (Schuler, 2005).
The most important aspect of cardiovascular prevention during adolescence is an early effort
by the parents to accustom their children to regular physical activity by encouraging outdoor
activities and active transportation. Without those encouraging influences from the parents'
side, a continuous decline of physical activity levels and an increase of the resulting risk
factors is to be expected (Kimm et al., 2002, as cited in Schuler, 2005). This may prevent the
disappointing results regarding the possibility to motivate middle-aged patients with risk
factors for CVD (Schuler, 2005).
Concerning the question whether CVD starts in childhood, studies usually examine risk
factors, such as blood pressure ( Hardmann & Stenzel, 2006, p. 216), due to the above-stated
fact that the disease doesn't manifest until later in life.
“A variety of cross-sectional studies have observed an association between low
levels of physical activity and/or physical fitness and elevations in risk factors for
CVD, including the metabolic syndrome (Steele et al., 2007). Examples include the
European Youth Heart study (Andersen et al., 2006; Ruiz et al., 2007), the National
Health and Nutrition Examination Survey (Carnethon et al. ,2005) and the Quebeq
Family Study (Eisenmann et al., 2005)” (Hardmann & Stenzel, 2006, p.217).
This supports the notion that physical activity levels during childhood and adolescence have
an influence in CVD risk in adulthood.
Another interesting study, conducted by Hancox et al. (2004), which give insight to exactly this
correlation by testing the connection between television viewing (a surrogate marker for
physical inactivity and poor diet) and CVD risk factors is summarized in the following figure:
28
Figure 6: Hancox: Prevalence of selected CVD risk factors at
age 26 years according to the mean hours of television viewing
per weekday between the ages 5 and 15 (Hancox et al., 2004)
To summarize, it has to be noted that physical activity during childhood and adolescence can
give evidence about CVD risk factors in adulthood. Furthermore, physical activity in adulthood
is closely connected to cardiovascular mortality.
The kind of sport activity people practice depends on personal preferences, whereas forms of
sport with a high portion of endurance are generally recommendable (Schuler, 2005).
2.2.1.4. Cancer
“You have cancer” might be the most feared sentence in doctor's offices around the
world. And it is in fact a very dangerous diagnosis which can be seen by the fact that it is the
number two cause of death in the United States, behind only cardiovascular disease (Jackson,
2004, p.228). In fact, the lifetime risk of developing some type of cancer is one in two for men
and one in three for women (American Cancer Society 2003, as cited in Jackson, 2004, p.228).
Cancer is understood as “a complex group of diseases characterized by the uncontrolled
growth and spread of abnormal cells” (Jackson, 2004, p. 228). There are more than 200
different types of cancer (http://www.cancerresearchuk.org/), so you can't just say that
physical activity can prevent cancer or something along those lines because there are an
abundance of reasons why cancer can occur. However, “physical activity does have benefits
both for preventing certain types of cancer and for surviving the disease.
29
“Physical activity is important in maintaining a neutral energy balance, which
lowers the risk of colon, prostate, endometrium, breast, and kidney cancers.
Physical activity may also have positive effects on hormone levels that will reduce
the risk of breast and prostate cancer. In addition, physical activity stimulates the
bowel and increases digestion time, which in turn lowers the risk of colon cancer” (
Jackson, 2004, p.238).
So even though, compared to the research on the connection of physical activity to obesity,
type 2 diabetes and cardiovascular disease, the causality between insufficient physical activity
levels and cancer aren't as conclusive, it's still of importance to be physically active in order to
reduce the risk of getting cancer.
The connection between cancer deaths and cardiovascular endurance was demonstrated by
Blair et al. (1989), as can be seen in the following figure:
Figure 7: Relationship of fitness to
cancer deaths (Blair et al., 1998)
2.2.1.5. Bonehealth
Osteoporosis is a major public health threat, as about 55% of Americans aged 50 or
above
are
affected
(http://www.nof.org/advocacy/resources/prevalencereport).
Osteoporosis is closely connected to low bone mass, bone mineral density (BMD) and bone
mineral content (BMC). There are studies which suggest, that physical activity and exercise,
especially weight bearing exercise, during childhood and puberty can effectively minimize
these risk factors. In fact, prepubertal and peripubertal years are a unique stage of growth
when a skeleton may be most responsive to exercise (Hardmann & Stenzel, 2006, p.219). An
effective way to research the difference of BMD and BMC in physically active and inactive test
subjects, is to conduct a side- to side comparison of the non-playing and the playing arm of
tennis and squash players (Kontulainen et al., 2002). It is important to notice that those side-
30
to side differences are significantly larger in persons who have started playing before puberty
(Kannus et al., 1995). “This clearly suggests that physical activity before and around the time
of puberty is particularly effective for increasing BMC (Hardmann & Stenzel, 2006, p. 221), as
can be seen in the following figure:
Figure 8: The mean playing-to-nonplaying arm difference in the bone
mineral content of the humeral shaft in
105 Finnish national-level female tennis
and squash players and 50 age-matched
female controls.(Kannus et al., 1995)
Another type of studies, namely intervention studies, arrived at similar results and confirmed
the effectiveness of exercise for increasing BMD and/or BMC in children and adolescents
(McDonald et al., 2007; McKay et al., 2005; Weeks et al., 2008; Yu et al., 2005, as cited in
Hardmann & Stenzel, 2006, p.221f)
“These studies indicate that exercise must be weight bearing, with several studies
demonstrating the particular effectiveness of jumping (McDonald et al., 2007;
McKay et al., 2005; Weeks et al., 2008). […] It should be noted, however, that one
study has reported and increased risk of fracture in children who perform vigorous
physical activity, presumably because they are more likely to fall" (Clark et al.,
2008).
To sum up, “there is compelling evidence that children and adolescents involved in regular
moderate- to high impact weight-bearing activities have higher BMD and greater bone
strength […] than those involved in non-weight-bearing sports or less active controls” (Daly,
2007).
Useful guidelines on how to improve bone structure in children and adolescents are provided
by the American College of Sports Medicine Position Stand on Physical Activity and Bone
Health (Kohrt et al., 2004 as cited in Hardmann & Stenzel, 2006, p.223):
Mode
Impact activities, such as gymnastics, plyometrics, and jumping, and moderate
intensity resistance training; participation in sports that involve running and
31
jumping (soccer, basketball) is likely to be of benefit, but scientific evidence is
lacking
Intensity
High, in terms of bone-loading forces; for safety reasons, resistance training
should be <60% of one-repetition maximum
Frequency
At least three days per week
Duration
10-20 minutes (twice per day or more may be more effective)
Table 5: Exercise recommendations for enhancing bone mineral accrual in children and
adolescents (Kohrt et al., 2004)
2.2.1.6. Mental Health
“It is increasingly apparent that exercise is not only good for one's physical health,
but that it is also good for one's mental health. It is now commonplace to read in
magazines and health newsletters that exercise can reduce symptoms of anxiety
(Gorman, 2002) and depression (Mayo Clinic Staff, 2005b) and can promote better
mental functioning across the age span (Mayo Clinic Staff, 2005a).” (Tenenbaum &
Ekelund, 2007)
If we once again consider the definition of health: "A state of complete physical, mental and
social well-being, and not merely the absence of disease" (WHO, 2001), we can see that the
mental aspect of health is not to be disregarded. The difficulty with mental health is the fact
that it is a summary construct which consists of well-being, self-worth, meaningfulness of life,
satisfaction with life, stress management competence and additional facets (Schlicht & Brand,
2007, p.69). This leads to the problem that most studies only measure one of the facets
(mostly well-being) and the others are neglected. In consequence: the multidimensionality is
disregarded (Schlicht & Brand, 2007 p.69). However, I will not focus on this methodicaltheoretical problem as I continue.
Apart from the fact that mental health is an important component of complete well-being,
there are three main reasons why this topic should be considered:
“[First:] PA may be useful in reducing psychological distress, among people in the
general population, and in the treatment of more serious problems such as clinical
depression and anxiety. Secondly, physical activity may help people cope with
stress more effectively, and reduce emotional reactions to stressful life events.
Thirdly, an understanding of the beneficial psychological consequences of physical
activity may help to enhance adherent to training programmes, and the
development of schedules that minimize dropout and foster lifelong activities.”
(Steptoe, 1992, p.207)
There are a number of studies evaluating the connections between physical activity and
32
mental health, especially self worth (Haugen et al., 2011) and the relationship between
physical activity and depressive symptoms (Ishii et al., 2011) have received special attention.
According to those studies, “increased levels of physical activity may be beneficial for global
self-worth in male and female adolescents by increasing their perceptions of physical
competence and physical appearance” Haugen et al., 2011), and “respondents not meeting the
recommendations for physical activity had higher depression scores than those meeting the
recommendations among different sociodemographic factors” (Ishii et al., 2011). For more
elaborate results, please compare Steptoe, 1992, p.207-229.
For the purpose of establishing the significance of physical activity, it is sufficient, at this point,
that there is evidence of a positive correlation between higher physical activity levels and an
improved status of mental health: “[Mental health] gets improved through physical activity"
(Schlicht & Brand, 2007 p.67)
2.2.1.7. Further Implications
Health ramifications, which have been discussed above, are a very important aspect
when we talk about the relevance of physical activity. However, there are other, related aspects
influencing the quality of one's living situation which are also allied to a deficiency of
movement experience (Graf, 2006). These include motoric unrest, clumsiness , unwillingness
to move, as well as emotional instability concentration and motivational disorders (Dordel,
2003, as cited in Graf, 2006).
2.2.2. Physical Activity as an important influence on child development
(motoric, emotional, psychosocial, cognitive)
Apart from the physiological and health side, which has now been discussed in detail,
another area where physical activity and movement is essential, is the field of pedagogy,
especially the part focusing on movement and child development. In this sense, FunkeWienecke (2004, p. 181-230) postulated four functions of human movement which have been
validated on an anthropological and psychoanalytic level (Laging, 2006):
1. Children shall skilfully and diversely practice the instrumental function of their body
through movement. This means they shall move so much that they can run and jump
over and from objects at different speeds and in different movement directions. Also
hand over hand movement and climbing, as well as the skilful handling of devices like
bicycle, roll- and slide-devices are part of a child's development. Furthermore, they
should be able to control the the instrumental use of movement to the end of being able
to throw, push and thrust objects, and roll, welter and somersault with their body.
33
2. Children shall, just as well, practice the social function of their movement, they shall
empathize with others, sympathize with their movements and help them; but also lead
others and be able to rely on others. To move much, enables the children to learn
moving with others together, to join a game, or to fight with others.
3. To move much, shall also lead to an understanding of the symbolic function of
movement and to the ability to express oneself, by taking on roles, mastering the
imitation and interpretation of motion patterns, taking part in symbol-games and being
able to imagine things.
4. To move much also and foremost leads to the construction of one's self, by experiencing
the body in movement itself. This sensitive function aims at physical experiences in the
movement to create the 'self' which, at the very beginning, is a physical 'self', This
function is therefore an an overarching one, that is contained in in all other function of
moving oneself. It addresses the fundamental unity of perceiving and moving. This
sensitive function enables, through intensive movement, a self-awareness, which, on
the one hand, realizes the body and, on the other hand, emphasizes the quality of
expression of the body (Funke-Wienecke, 2004, as cited in Laging, 2006)
These four very different functions of movement show that sufficient physical activity is
crucial for a broad spectrum of developmental steps every child has to go through. To sum up
this point, it can be noted that movement, play and sport are essential requirements for the
physical, motoric, emotional, psychosocial and cognitive development of children (Dordel,
2003, as cited in Graf, 2006).
2.3. Measuring Physical Activity
Physical activity is a complex entity which makes it difficult to be measured in an exact
and usable way. There are a number of ways in which physical activity levels (intensity,
frequency and duration) can be assessed. They can be roughly divided into self-report
methods where the subjective perception of an individual's physical activity is measured,
objective methods, measuring some kind of physiological or physical effect of movement, and
other methods, for example the subjective assessment of physical activity by an outsider.
There are studies which compare different types of physical activity measurements and show
that it is of great importance to choose a valid method in order to get good results ( Grams et
al., 2011; Cindy et al., 2010 Brooks; Fruin et al., 2004; Jakicic et al., 2004; Ewald et al., 2010).
I will now introduce the different possibilities for physical activity assessment and give a quick
overview on the advantages and disadvantages of each device, as well as possible situations
where an application might be suited. The two major variables that have to be taken into
consideration when choosing a method, are ease of assessment (feasibility) which includes
34
the consumed time, effort needed and the necessary expenses, and precision of the used
method. It is, for example, not realistic to use the doubly labeled water method in huge school
settings, where you want to describe everyday school life. A brief overview over some of the
methods and how they stack up when comparing those two variables can be seen in the
following figure:
Figure 9: Measuring Physical Activity -Levels of Sophistication (Ekelund)
Another comprehensive view of the different methods, the type of measurement and the
respective outcome is exemplified in the following table:
Method
Measurement
Outcome
Room caloriometry
CO₂ and VO₂
EE
Doubly labeled Water
CO₂ production
EE
Indirect Caloriometry
CO₂ and VO₂
EE
Accelerometry
Acceleration (i.e. body movement)
Counts
Heart Rate Monitoring
HR
EE
Self-Report
Intensity, Frequency,
Duration, (Type)
Activity Score, EE
Table 6: Measuring Physical Activity - Methods and Outcomes (Modified after Ekelund)
35
2.3.1.Self-report methods
“Self-report instruments continue to be the most widely used type of physical
activity measure. Thus, it is important to identify the strengths and limitations of
these measures[...] (Sallis & Sealens, 2000).”
“[I]t is particularly problematic when using self-report instruments with young
people (Biddle et al., 2011).”
I will show some evidence on the feasibility and validity of PAQs, activity diaries/logs and
recall interviews.
2.3.1.1. Physical activity questionnaires (PAQs)
PAQs are a very “widely used self-report instrument to asses physical activity and have
been used extensively in research. PAQs usually provide data on the frequency, duration and
intesity of physical activity in the various domains of activity i.e. house, occupation, leisure
and transport” (http://toolkit.s24.net/physical-activity-assessment/glossary-of-terms.html ).
A list of commonly used PAQs has been established by Krista & Caspersen (1997):
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Aerobic Center Longitudinal Study PAQ
Baecke PAQ
Bouchard 3-day physical activity record
CARDIA physical activity history
Framingham Physical activity index
Godin Leisure-time exercise questionnaire
HIP activity questionnaire
Historical leisure activity questionnaire
Kuopio Ischemic Heart Disease Study Q’s
Lipid research clinics questionnaire
Minnesota Leisure-time PA
Modifiable Activity Questionnaire
Paffenbarger Physical Activity Questionnaire
Seven-Day Physical Activity Recall
Stanford Usual Activity Questionnaire
Tecumseh Occupational PAQ
In order to know whether a PAQ is an adequate tool for measuring physical activity, its validity
has to be established. There are three types of validity:
1. “Criterion validity: A questionnaire is validated against an objective method. The
36
relationship is frequently reported as a correlation coefficients (Pearson, Sperman)
2. Absolute validity: The absolute outcome (i.e. EE or time spent in activity) is compared
to data from an objective instrument which provides the same outcome measure. The
association is usually reported as the degree of agreement (Bland and Altman method).
3. Concurrent validity: A questionnaire is compared to another self-report instrument
(i.e. diary or another questionnaire). Although a high correlation between two
subjective instruments suggests validity, the instruments are not of a different type and
may be subject to correlated error.” (Ekelund)
In general: The questionnaire has to be compared to other assessment methods, with
correlation or degree of agreement, respectively, in acceptable range, in order to be valid.
One example of how an often used PAQ, the “International Physical Activity Questionnaire
(IPAQ), which can be used via telephone interview or self-administration and was developed
as an instrument for cross-national monitoring of physical activity and inactivity” (Craig et al
2003) is validated by comparison to accelerometry can be seen in the study conducted by
Craig et al in 2003, where they compared results from the questionnaire in 12 countries to
results from an accelerometer in order to assess the criterion validity. Test-retest repeatability
and concurrent validity was also tested. (Craig et al., 2003). In conclusion of this study “IPAQ
has reasonable measurement properties for monitoring population levels of physical activity
among 18- to 65-yr-old adults in diverse settings” (Craig et al., 2003).
Other examples are studies by Washburen et al. (1992), Ewald et al. (2008) and Kurtze et al.,
(2008), in which the physical activity scale for the elderly (PASE) and the IPAQ (Kurtze)were
validated. They showed that, one the one hand, “the PASE is a brief, easily scored, reliable and
valid instrument for the assessment of physical activity in epidemiologic studies of older
people” (Washburn et al., 1992) but on the other hand “pedometer-derived step counts are a
more valid measurement of overall physical activity [...]than PASE score. Researchers should
use objective measures of physical activity whenever possible” Ewald et al., 2008).
To sum up, questionnaires usually show good to excellent reliability, poor to moderate
(although significant) criterion validity and questionable absolute validity (Ekelund). What
questionnaires provide, are prevalence estimates of physical activity, the possibility to
categorize respondents into activity categories. But they provide a poor measure of the
absolute time spent at different intensity levels and the associated energy expenditure.
Additionally, questionnaires should be used with caution in children (Ekelund).
37
2.3.1.2. Activity Diary/Log
Another simple way to "to assess the average daily levels of physical activity, energy
expenditure and the time and energy spent a different activities" (Bratteby et al., 1997) is an
activity diary or log.
"In both diaries and logs, the 24 hour period is typically broken down into shorter
segments (i.e. 15 minute segments) and individuals record their main activity for
each segment. In a diary individuals are instructed to record individual bouts of
activity as they occur during the day. Logs capture the time individuals spend in
broad categories of activity, i.e. inactive time, sitting time, and time in light,
moderate, vigorous and very rigorous intensity activity"
(http://toolkit.s24.net/physical-activity-assessment/glossary-of-terms.html).
An example of a validation study was the one by Bratteby et al. (1997) where they looked at
"daily total energy expenditure (TEE) and physical activity level (PAL = TEE/BMR) in"
(Bratteby et al) 50 15 year old boys and girls. The absolute validity was assessed by a
comparison between the diary and doubly labeled water and indirect calriometry during the
same time period. In conclusion of the study, they stated "that the activity diary method
provides a close estimate of TEE and PAL in population groups" (Bratteby et al., 1997).
Another study where two different types of diaries (cellphone and paper) came to a similar
result: "A cell phone-based PA diary is equivalent to a paper diary, acceptable to users, and a
relatively reliable and valid approach to self-reported physical activity" (Sternfeld et al., 2011).
However, "using diaries in young children via proxy reports has been shown to have low
reliability" (Freedson and Evenson, 1991).
One possible concern with physical activity diaries is, that they motivate people to move more,
thus influencing their habitual behaviour. Another problem is, that it involves a rather high
effort by the test subjects and it might therefore be more difficult to find enough willing
participants.
2.3.1.3. Recall interviews
This method is very similar to the physical activity questionnaires and therefore shares
the same advantages and disadvantages.
2.3.2.Objective Methods
2.3.2.1. Pedometry
Pedometers are, apart from the self-report-methods the cheapest and easiest way to
38
measure physical activity. They are technically an accelerometer but because of the frequency
of use, also in the general population, and their easy usability, I decided to treat them
separately.
They are only able to count steps, so only locomotive activities like walking or running are
taken into consideration. This is obviously a huge limitation and restricts the reasonable use
considerably. However, compared to the Physical Activity Scale for the Elderly (PASE), they
provide the more valid measurement (Ewald et al., 2010). And also in comparison to a
questionnaire, they prove to be useful (Sequeira et al., 1995). Compared to other objective
methods like triaxial accelerometry, heart rate and oxygen uptake, pedometry clearly shows
its limitations (Eston eta al., 1997).
To offer a conclusion on the field of study where
pedometers are of use, pedometry offers potential for large population studies (Eston et al),
particularly in a free-living population (Sequeira et al., 1995). They are a cheap and easy way
for objective measures which are generally to be preferred when measuring physical activity
(Ewald et al., 2010).
2.3.2.2. Accelerometry
The underlying principle of accelerometers is that “muscular forces can result in
acceleration of body mass. Both the acceleration of the body mass and the amount of body
mass
being
accelerated
are
in
theory
related
to
energy
expenditure”(http://toolkit.s24.net/physical-activityassessment/methods/accelerometery/index.html). The measurement outcome 'counts' has
been explained in detail in chapter 2.1.4.
In accelerometry, acceleration is measured by piezoelectric or seismic sensors in one
(longitudinal body axis, usually vertical), two (vertical and medio-lateral or vertical and
anterior-posterior) and three (vertical, medio-lateral and anterior-posterior) directions (Chen
et
al.,
2005
as
cited
in
http://toolkit.s24.net/physical-activity-
assessment/methods/accelerometery/index.html). Triaxial accelerometry proves to be the
best assessment of activity, not only compared to uniaxial accelerometry but also compared to
heart rate and pedometry (Eston et al., 1997).
I conclusion, “accelerometry offers a practical and low cost method of objectively monitoring
human movements, and has particular applicability to the monitoring of free-living subjects”
(Mathie et al., 2004).
However, it also has a few disadvantages: The most obvious one is that, depending on where
39
the accelerometer is attached (hip, lower back, ankle, wrist, thigh), it does not capture activity
from other body parts. An accelerometer, attached on the hip, e.g. would severely
underestimate cycling or other complex movements. So it doesn't surprise, that compared to a
combination methods (sensewear, actiheart) , pure accelerometry is the inferior method
(Grams et al., 2001; Crouter et al., 2006). Approaches with 2-segment regression models have
been considered which have been shown to improve the accuracy (Crouter et al., 2006).
However those laboratory settings ar e not 100% replicable in field studies.
Another problem, when studying children, especially in school settings, surfaced in the study
by Robertson et al. (2011), where some of the obese children refused to wear an acceleromet
in school because they were subjected to bullying.
To recapitulate, accelerometry has been extensively validated, is applicable to children and
adults, provides data on patterns of physical activity, is valid for assessing the total amount of
PA, and is applicable in relatively large studies (Ekelund).
2.3.2.3. Heart rate monitoring
Heart rate monitoring provides another easy and objective method how to assess
physical activity, by the measuring of a direct physiological response. It is usually done by
wearing a chest strap which sends the signals to a storage device, usually hidden in a watch.
Another possibility is the usage of electrodes which has the disadvantage to reduce the
feasibility. The basis of this method is the linear relationship between heart rate and energy
expenditure in steady state work loads involving large muscle groups (Strathe et al., 2000).
The primary outcome of this measurement method is heart rate, allowing an estimate of the
time spent at different intensity levels. The heart rate can then be converted into energy
expenditure using regression equations derived from individual or group calibrations (see:
Rennie et al., 2001) . Activity intensities can be distinguished using either absolute heart rate
values (Sirard & Pate, 2001) or heat rate indices (Trost et al., 2001). In order to get good valid
results of energy expenditure, individual calibration in a laboratory or collecting the sleeping
heart rate over night is required which reduces the feasibility considerably (Brage et al.,
2007).
A highly validated method to measure energy expenditure via heart rate monitoring is the
FLEX heart rate method (Spurr et al., 1988). “It assumes that above a given threshold (the
FLEX point) there is a linear relationship between heart rate and oxygen consumption; below
this threshold the relationship is variable. Energy expenditure above the threshold or FLEX
40
point is estimated by a linear prediction” (http://toolkit.s24.net/physical-activityassessment/methods/heart-rate-monitoring/index.html ).
The main issue concerning heart rate methods is the fact that it is not only dependent on
physical activity but on other external and internal factors, as well. Stress, caffeine,
nervousness and many more, are disturbances which can lead to wrong or inaccurate results.
2.3.2.4. Combination (heart) sensors
Due to limitations to both, accelerometry (e.g. bicycling, carrying good, walking uphill
etc.) and heart rate monitoring (e.g. elevated HR due to stress and environmental factors, and
the fact that those measurement errors are not positively correlated, a combination of the two
methods provides excellent accuracy, when assessing physical activity levels and energy
expenditure. One such device is the Actiheart, which I used during my study. and has proven to
be reliable and valid for youth populations (Corder et al., 2007, Barreira et al., 2009, as cited in
Slingerland & Borghouts, 2010).
It is a very small and light device which has the following attributes (Brage et al., 2005, as
cited in http://toolkit.s24.net):
•
has a main component 7mm thick with a 33mm diameter and houses a movement
sensor, a rechargeable battery, a memory chip and other electronics
•
weighs 8g
•
does not require a chest strap; instead electrodes are attached to the chest.
•
is waterproof; individuals only remove it to replace pads that have perished
•
offers a choice of epoch length-15s, 30s, 60s
•
the memory capacity allows 11-days of continuous monitoring using a 60 s epoch (or
15 s epochs in newest generation which has 4 times enhanced memory capacity)
•
allows collection of additional heart rate variability (HRV) information during freeliving which provides useful information on the quality of data
•
provides advanced analysis to estimate energy expenditure more accurately
Intra- and inter-instrument reliability and validity was initially assessed by Brage et al. (2005)
who tested the Actiheart against ECK and indirect calorimetry in a laboratory setting and
came to the following conclusion: "The Actiheart is technically reliable and valid. Walking and
running intensity may be estimated accurately but further studies are needed to assess
validity in other activities and during free-living" (Brage et al., 2005).
41
This is exactly what Crouter et al. (2007) did who "validate[d] the Actiheart prediction method
against indirect calorimetry during a wide range of activities in a field setting" (Crouter et al.,
2007). Again, they came to the conclusion that "[t]he Actiheart combined activity and HR
algorithm and HR algorithm provide similar estimates of AEE on both a group and individual
basis"(Crouter et al., 2007). Additionally, it showed clearly its superiority in comparison to
heart-rate monitors and accelerometers used on their own:
"In general, HR alone is not as useful for predicting AEE of light physical activities
compared to moderate and vigorous physical activities, which the current study
confirms. The Actiheart HR algorithm was significantly different from the Cosmed
K4b2 for sedentary activites and light physical activities; however, it was only
significantly different from one moderate to vigorous physical activity. The
accelerometer AEE estimates obtained in the current study were close to actual
AEE for walking; however, it underestimated the actual AEE of most other
activities. In general, hip-mounted accelerometers overestimate sedentary and
light physical activities, while underestimating moderate to vigorous physical
activities that involve upper body movement, walking uphill, and climbing
stairs"(Crouter et al., 2007).
A nice graphic illustration of the validity of the Actiheart combination method in comparison
to heart-rate and accelerometry alone, can be seen in figure 10: The fact that ACC+HR is more
accurate than ACC alone, was also concluded by Corder et al. (2007): "Although both ACC and
HR+ACC provide accurate predictions of overall PAEE, according to the activities in this study,
PAEE-prediction models using HR+ACC may be more accurate and widely applicable than
those based on accelerometry alone."
To sum up, the combination of heart-rate and accelerometry has proven to be a valid and
reliable method of assessment for physical activity levels. Combined with its small size and
easy handling, it provides both good accuracy and excellent feasibility which is why I have
decided to use this device in my study.
42
Figure 10: Comparing the AEE accuracy of the Actiheart to the Cosmed K4b2 (Crouter et al.,
2007)
Another combination method is the SenseWear Armband which contains multiple measuring
tools. It has an accelerometer, measures the electrical conductivity of the skin, which changes
in response to sweat and emotional stimuli, and has an integrated thermometer, which
measures skin temperature and the amount of heat dissipating from the body.
It has been validated against and compared to indirect calorimetry (IC) (Fruin et al., 2004), a
triaxial accelerometer and mobile spiroergometry (Grams et al., 2011). Results have been
mostly positive: “the SWA provided valid and reliable estimates of EE at rest and generated
similar mean estimates of EE as IC on the ergometer; however, individual error was large. The
SWA overestimated the EE of flat walking and underestimated inclined walking EE” (Fruin &
Rankin, 2004). “SW […] measures more accurately” (Grams et al., 2011), compared to a
triaxial accelerometer alone.
43
2.3.2.5. Doubly Labeled Water (DLW)
With the help of the doubly labeled water method (DLW), the total energy expenditure
of a person can be measured:
“The fundamental basis of the DLW technique is that whilst the hydrogen label is
lost only as water, the oxygen is lost as both water and carbon dioxide; transference
of oxygen between water and carbon dioxide is the consequence of rapid exchange
promoted by carbonic anhydrase. Therefore the difference between the turnover of
the two labels can be used as a measure of the production of carbon dioxide.
In practice the subject is asked to drink a known dose of water enriched in ²H and
¹⁸O. Samples of blood, saliva or urine, from which the isotopic composition of the
body water can be determined, are collected over the next 5-14 days. From the
isotope disappearance curves four parameters are deduced, the two pool sizes of
hydrogen and oxygen and the fractional rate constants of elimination for each of
these species, and these are combined to give an estimate of CO² production”
(http://toolkit.s24.net/physical-activity-assessment/methods/doubly-labelledwater/index.html).
DLW is a valid and exact measurement, in fact is is often used to validate other methods
(Schoeller et al., 1986). The massive disadvantage is of course, that it is still very expensive
and complicated to realize, which is why it is not the ideal method for a school study setting
like mine.
2.3.2.6. Direct/indirect/room calorimetry
Direct calorimetry measures a person's energy expenditure by the body’s heat
production in a calorimeter. Indirect calorimetry measures EE by examining respiratory gases
(oxygen consumption and carbon dioxide release is measured). The assessment method is
spirometry. A special form of this method is the whole room calorimeter (WRC) where the gas
exchange is measured of the entire room in which the proband is. Advantages of calorimetry
are that it is very accurate, valid and can be combined with other methods (Ferrannini, 1988).
However, similar to DLW which is also expensive and accurate (Pinheiro et al., 2011), the
feasibility is reduced, not only because of costs but also because the apparatus which is
required for these methods, its implementations are limited. This applies to whole room
calorimetry especially but it is also hard to imagine a whole school running around with
mobile spirometers. A very good area of application is professional sports or the validation of
other methods.
44
2.3.2.7. More
Another objective method is the use of GPS. A meta study by Krenn et al. (2011)
examined “the capability of GPS to collect high-quality data on the location of activities in
research on the relationship between physical activity and the environment.” Their Conclusion
is that “GPS is a promising tool for improving understanding of the spatial context of physical
activity. The current findings suggest that the choice of an appropriate device and efforts to
maximize participant adherence are key to improving data quality, especially over longer
study periods” (Krenn et al., 2011). However, this method is not suited to examine PA levels.
2.3.3.Others
2.3.3.1. Observation/Time keeping
"Direct observation of physical activity can provide detailed contextual information
on [...] physical activity, but is subjective and impractical for understanding daily
physical activity [...] Also, direct observation is inherently subjective, and coding
protocols may result in failure to capture intermittent activity, thereby limiting its
utility as a physical activity criterion." (Oliver et al., 2007).
It is a useful tool to combine with objective methods but on it's own it is insufficient in
determining physical activity levels.
Time keeping of physical activity is a much used tool in estimating the absolute times spent
actively or inactively during physical education lessons. Examples of conducted studies are
Dietrich (1964), Kretschmer (1974), Hoppe & Vogt (1979) and a replication study of Hoppe &
Vogt by Hoffmann (2011). Their results of minutes spent actively on on task active behavior
can be used for a descriptive analysis of physical education lessons, but in terms of actual
volume of physical activity, no exact statements can be made without any kind of intensity
measures.
2.4. Literature on Physical Activity in Children
In this chapter, the focus is on the discrepancy between recommended and actual
physical activity in children and adolescents. Of special interest is the question, whether
physical education can significantly contribute in this area. This will be answered in chapter 4
Results and in the discussion of this study.
45
2.4.1. Recommended amount of Physical Activity
Exactly how long and how intensive children should move in order to develop healthily,
can not be answered to date (Graf, 2006). There are however, several organizations and
groups which have given recommendations about the amounts of physical activity that
children should achieve. A consensus that children and adolescents should engage in at least
one hour of moderate-to-vigorous physical activity (MVPA) per day has been established
independently by various organizations and research groups, among them the World Health
Organization and the American Heart Association and the US Department of Health and
Human Services (Biddle et al., 1998; Kavey et al., 2003; Kemper et al., 2000; US Department of
Health and Human Services, 2008; WHO 2010).
A more complex system was introduced by Graf et al. (2005) who developed a 'movement
pyramid' (see figure 10).
Figure 11: schematic depiction of the 'children movement pyramid' (Graf
et al., 2006)
For a more detailed overview of the recommendations see table 12:
Daily (min)
Intensity
Adj. Borg scale
Examples
physical education, every
day activities. e.g. playing
with friends, inline skating,
hide-and seek
Vigorous
activities
2x15 min →
sweating or
together 30 min heavy breathing
≥6 → straining
Moderate
activities
4x15 min→
no sweating, no
together 60 min heavy breathing
3-5 → a bit
straining
Every day
activities
6x5 to 10 min
→ at least 30
min
-
-
active transport (e.g. to
school), house chores,...
Inactivity
6-12 years →
max. 1 hour
>12 → max. 2
-
-
TV, computer, playstation
46
hours
Table 7: Recommendations to the 'children movement pyramid' (mod. after Graf et al., 2006)
2.4.2. Actual Amount of Physical Activity
Public health experts complain about the increasingly sedentary lifestyle in children
and adolescents (US Department of Health and Human Services 1998) (Biddle et al., 1998, 5f;
Marcus et al., 2000, 32f; as cited in Buksch, 2007). The US-American National Health and
Nutrition Examination Surveys where, between 2001 and 2004, 2964 children at the age 4-12
were examined, categorized 37,3% as little physically active (≤ 6 times plying per week). 65%
had a high amount of 'screen time' (more than two hours of TV, etc.) and for 26,3%, both
applied (Anderson et al., 2008, as cited in Graf, 2010).
Dutch studies have produced similar results:
"youth guideline compliance is generally low across most western countries and
Dutch youth are no exception to this. Thirty-two percent of 4- to 11-year-old boys
and girls and 15% of 12- to 17-year-olds are currently meeting the physical activity
guidelines (Hildebrandt & Ooijendijk, 2008). In 6- to 11-year-old children living in
urban areas with low social-economic status, guideline compliance is low as 4% in
native Dutch youngsters and 3% in youngsters with a different ethnicity"
(Slingerland et al. 2001).
Two studies from Great Britain which used accelerometry and doubly labeled water to
measure physical activity have researched the same question. One conducted in Scotland,
found out that three-year-old children in Glasgow spend 79% of their time in sedentary
behavior and only 2% of their time in moderate-to-vigorous physical activity. For five-year-old
children the figures are 76% and 4% respectively (Reilly et al., 2004, as seen in Hardman &
Stenzel, 2006, p.206) One from the Southwest of England came to the result that 2,5% of
children (5,1% for boy, 0,4% for girls) met the internationally recognized recommendations of
one hour of MVPA per day (Riddoch et al., 2007, as seen in Hardman & Stenzel, 2006, p.206).
Data for Germany in the field of health-related physical activity confirms this low prevalence
for this group (Richter & Settertobulte, 2003, as cited in Buksch, 2007). In addition, it is clear
that girls are consistently less physically active than boys (Cale & Harris, 2006, as cited in
Buksch, 2007). According to the Kinder- und Jugendgesundheitssurvey (KIGGS), children
between the age 3 and 10 do sports on a regular basis; 75% at least once a week; 30% even
three times or more. Among adolescents (11-17 years old), only about 25% of the boys and
15% of the girls are active on most days of the week. An absolute quantity of physical activity
47
has not been established however (Lampert et al., 2007, as seen in Graf, 2010). It is estimated
that total physical activity among children and adolescents has regressed considerably since
the 70s from 3-4 hours to about 1 hour a day (Bös et al., 2001, as seen in Graf, 2010).
Movement time of up to 2 hours was reported by Kleine (2003), with differences between
weekdays and weekend-days (1,8 to 2,3-2,6 hours) (Kleine, 2003, as seen in Graf, 2010).
An interesting question is, whether and how much physical education can contribute to the
total physical activity.
2.4.3. Consequences of low Physical Activity Levels
Apart from increased mortality in adult age and an increased risk for various diseases,
which have been discussed in detail, there is also evidence for deteriorated motor skills and
low fitness levels for inactive children (Bloomfiel, 1997; Bös, 2003; Bös et al., 2004; Graf et al.,
2004; Tomkinson et al., 2003; as cited in Graf et al., 2006).
In order to fight the prevalence of inactivity, the Committee on Sports Medicine and Fitness
and Committee on School Health has suggested a couple of points:
"The following recommendations are adapted from those published by the Centers
for Disease Control and Prevention (CDC) (Centers for Disease Control and
Prevention, 1997) and the Council for Physical Education for Children (Council for
Physical Education for Children (COPEC) of the National Association for Sport and
Physical Education, 1998). School personnel and pediatricians are urged to review
these publications. School personnel are encouraged to:" (Committee on Sports
Medicine and Fitness and Committee on School Health 2000)
1. Establish policies that promote enjoyable, lifelong physical activity. These include:
•
Comprehensive, preferably daily, physical education for children in grades
kindergarten through 12;
•
Comprehensive health education for children in grades kindergarten through 12;
•
Commitment of adequate resources, including program funding, personnel, safe
equipment, and facilities;
•
The use of appropriately trained physical education specialists and appropriately
trained teachers for physical and health education classes, respectively;
•
Physical activity instruction and programs that meet the needs and interests of all
students, including those with illness, injury, and developmental disability, as well
as those with obesity, sedentary lifestyles, or a disinterest in traditional team or
48
competitive sports.
2. Provide physical and social environments that encourage and enable physical activity
in a safe setting. Adult supervision, teaching, and instruction in safe methods of
physical activity training, safe facilities, and the appropriate use of protective
equipment are all components of a safe environment for physical activity.
3. Implement physical education and health education curricula that emphasize enjoyable
participation in physical activity and that help students to develop the knowledge,
attitudes, motor skills, behavioral skills, and confidence needed to adopt and maintain
physically active lifestyles.
4. Provide extracurricular physical activity programs (those occurring outside of formal
classes) that address the needs and interests of all students.
5. Include parents and guardians in physical activity instruction and extracurricular
physical activity programs. Encourage parents and guardians to support their
children’s participation in enjoyable physical activities, as well as to recognize their
powerful influence as role models for active lifestyles.
6. Provide education to personnel from teaching, coaching, recreation, health care, and
school administration to effectively promote enjoyable, lifelong physical activity among
youths.
7. Regularly evaluate the school’s physical activity programs, including classroom
instruction, the nature and level of student activity, and the adequacy and safety of
athletic facilities.
8. Establish relationships with community recreation and youth sports programs and
agencies to coordinate and complement physical activity programs.
"Pediatricians and other health care professionals are encouraged to support schools in their
efforts to promote physical activity and fitness by:" (Committee on Sports Medicine and Fitness
and Committee on School Health, 2000)
1. Helping the school adapt programs to meet the needs of children and adolescents who
have activity limitations because of temporary or chronic illness, injury, or
developmental disability;
2. Providing schools and individuals with safe options for continuing with physical
activity even when students are affected by illness, injury, or disability;
49
3. Identifying and encouraging the appropriate use of safety equipment for sports and
physical activities in all settings;
4. Assessing activity patterns as part of routine health maintenance and providing advice
about how physical activity levels can be increased;
5. Encouraging physical activity at the family and community levels in addition to the
activity conducted in the schools or with organized sports;
6. Helping to identify and reduce barriers to regular physical activity—including doubts
about the need for more activity, the fear of injury, the availability of safe settings, and
the lure of more sedentary pursuits, and;
7. Working to ensure the availability of funding and personnel resources to permit every
child the opportunity to be physically active and to receive appropriate direction and
supervision from educated adults.
Again, an emphasis on physical education is stated which brings us to the point of examining
physical education closer: I will start by offering possible reasonings on why physical
education is important. After that I will discuss which factors determine the quality of PE. And
finally I will give an overview of previous studies on physical activity levels in physical
education.
2.4.4. Why Physical Education? (Legitimization)
"Physical education as a mandatory class has become expendable in the modern
recreational society - except maybe for the lower grades and respective special schools"
(Giesecke, 1998,
p. 283). More and more people are of this opinion, especially in the age of PISA-studies, G8discussions and the introduction of short and crammed bachelor degree courses. Increasing
demands of the working world raises the relevance of physical education among the
traditional core subjects to question. In order to clarify what PE has to offer, Lenzen (2000)
demands in a debate on the legitimization of PE, that a subject-specific justification is in need,
which must not only persuade PE teaches, sports educationalists and sports pedagogues, but
also the society because every justification is subjected to the societal zeitgeist.
There are several ways how physical education can contribute to the education and
maturation process of a child and adolescent. One is based on the fact that sports are an
important part of today's society. In order to be part of and participate in this cultural
50
phenomenon, one has to be prepared in school.
Anthropology delivers the explanation that a human consists of body and mind. Without the
experiences o the environment through the body, the mind cannot fully develop and the
wholeness of the body, where motoric, intellectual, social and emotional aspects operate
together is in danger. This integrated view of the human is, according to Bräutigam (2003, p.
29) another aspect in favor of PE.
Furthermore the human is described as a 'deficient being' which has to learn all vital skills,
movement included. In order to achieve a complete education, movement skills are essential
in young people's quest to achieve a self-determined and responsible conduct of life.
Another important anthropological category constituting education, is sociability, which
expresses a person's double aspect of being an individual and a social being at the same time.
What sounds like a contradiction at first, can be facilitated through sport if we think about
individual sports like gymnastics on the one side, and team-oriented sports like basketball on
the other side.
Additionally, physical education provides an excellent opportunity for children's and
adolescents' personal development, in terms of social skills like teamwork and the ability to
achieve something, but also to learn important skills like winning, losing or carrying
responsibility.
One of the aspects which is often brought up, in regard to positive effects of PE is its ability to
provide a contrast to the otherwise stagnant and often boring school routine. Since children
have a natural urge to move, PE provides a much-needed break and enables them to
concentrate better afterward.
Last but not least, there is the "potential [of physical education] to effectively provide all
children and adolescents with structured and regular physical activity, as virtually all children
and adolescents attend school. Thus, for many children PE is an important source of physical
activity" (Trudeau & Shephard, 2005, as cited in Slingerland et al., 2011). Studies showed that
a significant amount of total physical activity is accomplished during physical education: For
example,
"30% of 16-year-old Swedish adolescents in practical education are reported to
achieve all of their MVPA during PE (Westerstahl et al., 2003), whereas only 8% of
Chinese students participate in MVPA outside of school (Tudor-Lockeet al., 2003).
In Dutch adolescent boys, increases in total weekly physical activity of 3-25% have
been observed when increasing the number of weekly PE lessons(Kemper et al.,
1976). Therefore, it is often claimed that regular PE could make a meaningful
contribution to the daily accumulation of physical activity needed for health
51
benefits (Corbin & Pangrazi, 2003; Sallis et al., 1997). Physical activity obtained by
participating in PE is thus dependent on both the number of lessons provided and
the intensity of these lessons. The US Department of Health and Human Services
(2008) has acknowledged this potential in their Healthy People 2010 national
health objectives, by stating that schools should provide daily PE and by
recommending that at least 50% of regular PE lesson time should be spent in
MVPA" (Slingerland et al., 2011)
The significance of sufficient amount of PA has already been established and we now know
that a certain amount of PA comes from PE. However, how high exactly, will be seen in chapter
4 Results. The next question is if high physical activity levels are an indicator of good physical
education and whether it should be the task of the school to provide a certain amount of PA or
if other institutions would be better suited (sports clubs, fitness studios, etc.). The parameters
of good physical education, especially PA levels, are at the center of the next chapter.
2.4.5. What constitutes the quality of Physical Education?
The question of what constitutes good instruction, has always been a topic for
discussion in pedagogy. International studies like PISA have fueled the discussion and shed
new light on many things. Even though physical education hasn't been the primary focus, it is
still affected in a sense, that its quality and even its necessity, as already discussed, have been
called into question.
The fact that movement is at the center of physical education was already mentioned in the
introduction, where present-day curricula were examined. This definitely makes sense, since
PE is the only subject where movement and body are addressed and thus the only subject
which can offer an antipole to decreasing, urbanized movement spaces and an increasing
trend toward all-day school. So, despite the other goals of physical education that were
already mentioned, like social and emotional skills, physical development and experiences
have the highest priority. Following this line of argumentation, athletic movement (in the
broadest sense) and high physical activity levels appear to be an important characteristic of
good physical education.
Empirical educational research has made significant progress over the last years. Two authors,
who have devoted themselves to this research have each postulated ten quality criteria about
instruction in general (Meyer, 2004) and physical education in particular (Gebken, 2003). I
will start by showing the criteria about general instruction (Translation Dave Kloss, 2006):
1. Clear teaching structure (process clarity; clearly-defined roles; agreement on rules,
rituals, and what is permissible).
52
2. High Amount of Time-On-Task (intelligent time management; punctuality; reduction of
organizational work in the classroom).
3. Climate Conducive to Learning (mutual respect; rules that are adhered to; balancing of
responsibility; equality and care for one another).
4. Content Clarity (well-defined tasks; plausibility of thematic processes; clarity and
continuity of retaining that which was taught).
5. Meaningful Communication (through participatory planning; thorough discussions on
the meaning of tasks; frequent mutual feedback).
6. Variety of Instructional Methods (Multitude of teaching and learning patterns; and a
balancing of individualized and collective learning, of self-regulated and guided
learning).
7. Individual Support (through being patient with them a taking time for them; through
internal differentiation; through individual learning analyzes and individual learning
plans; particular attention to at-risk students).
8. Intelligent Exercises (by making students aware of learning strategies; precise
assignments for exercises; and concerted support).
9. Clear Description of Goals to Be Achieved (constructing learning situations fitted to the
curricula and the capabilities of the students; punctual feedback on learning progress).
10. Well-Prepared Learning Environment (well-organized, functional facilities; useable
learning tools).
Next, and rather similar, I will show the criteria on PE by Gebken:
1. Clear structure of the teach-learn-process
2. Ideal use of given time
3. Long involvement of students in motor activities (=extension of the amount of 'real'
movement time)
4. Pluralism of methods
5. Coherence of goals, contents and methods
6. Class climate (= Creation of a learning-beneficial, positive work-climate)
7. Meaningful class-conversations (=mediation between curriculum and students'
interests)
8. fostering approach (= orientation at individual learning state, encouragment to learn,
communication of learning strategies)
9. Student-feedback
53
10. Achievement expectation and control
Helmke (2009) and Hentig et al. (1980) put particular emphasis on 'real' or 'active' learning
time which is also important to Meyer (High Amount of Time-On-Task) and Gebken (Ideal use
of given time; Long involvement of students in motor activities (=extension of the amount of
'real' movement time)). Apart from a few studies (see chapter 2.4.6) the issue of time has been
neglected in German educational studies. In the USA, 'classroom management' and 'academic
learning time in physical education' (ALT-PE) have been points of particular interest: "This
[ALT-PE] temporal dimension of appropriate motor-engagement is considered a key indicator
of teaching effectiveness, because of its relationship with student achievement" (Van der Mars,
2006, p.191, as cited in Hoffmann, 2011).
An interesting point can be made if we compare PE with other classes: During regular class,
the rate of 'real' learning time lies between 65% and 85% (Hentig et al., 1980), whereas in
physical education the movement time is only between 13% an 24% (Dietrich, 1964;
Kretschmer, 1974; Hoppe & Vogt, 1979). It is, however, to be taken into consideration that
'real' learning time in PE doesn't exclusively consist of movement time, but is comprised of
other elements, as well.
If we compare German curricula of physical education with American ones we can see that
motor skills play a more important role in the USA. This might explain why they have a
generally higher movement times, as their PE has a more exercise-like character.
For more details on why a high portion of physical education lessons should be devoted to
movement see: Hoffmann, 2011, p.34-36.
By now, several aspects of good education have been identified, with amounts of 'real' or 'ontask' learning time being especially important. What is very surprising to me is that, in terms
of 'real' learning time, especially in PE with movement time, only the temporal aspect and not
quality or intensity, in particular, is in discussion. This, in my opinion, is a major design-flaw in
many of the studies, measuring amounts of physical activity in physical education, which is
why I have chosen to make exactly that the focus of my work.
2.4.6. Physical Activity Levels in Physical Education – Previous studies
I have narrowed the reviewed international literature down to studies which
explicitly concern themselves with physical activity levels during physical education. This
means that studies examining total PA of children (this has already been discussed in chapter
2.4.2), commuting back and forth to school, PA during school in general and extracurricular PA
54
will not be discussed here. This is due to the fact, that the number of conducted studies is
simply to large (PubMed has produced 12798 hits for the search entry 'physical education and
physical activity') and that it is not part of my field of research which is confined to the
boundaries of physical education class itself. In the context of this article, PE is defined as an
academic course included in the curriculum and offered within the normal school timetable.
On an international level, there are two recent review studies (Fairclough and Stratton 2005,
2006) which have summarized the findings of 84 studies/papers, most of them in the USA and
in the UK, investigating the amount of active lesson time during elementary (44 papers) and
secondary school (40 papers) PE. Results showed that, during elementary school physical
activity, students engaged in moderate-to-vigorous physical activity for an average of 37,4%
(±15,7) of lesson time. In secondary schools, the amount of time spent in MVPA during PE
lessons varied between 40% (±13,8) for heart-rate-monitoring and 27,7% (±14,9) for
observational data.
This difference between methods of assessment is important to note, as it indicates one of the
most significant problems, namely that of choosing the correct means of measurement (see
figure 9).
I will take a closer look at the study, conducted by Slingerland et al. (2011) because it is very
similar to my study, in terms of purpose ("to determine the overall intensity of Dutch
[ ...]secondary school physical education (PE) lessons and the influence of various lesson
characteristics on these intensity levels" (Slingerland et al., 2011)), methods (they used heartrate-monitors on 10 students during PE lessons), and participants who were Dutch primary
(n=461) and secondary (n=452) school students from 40 schools in the Netherlands. It is of
note, that primary school is from grade 1-6, and secondary school is from grade 7-12 in the
Netherlands. However, due to small chest sizes in grades 1-3, which resulted in large chunks of
heart-rate-date to be missed, these grades were disregarded, which made their group of
participants (grade 4-12) similar to mine (grade 5-12). Their setting looks as follows:
"Schools were randomly selected [...] in [...] The Hague, Nijmegen, Groningen,
Sittard, and Tilburg. [...]. The [...] lessons in the various domains were spread
equally over the school year. All schools, both primary and secondary, taught PE in
mixed-sex classes. Locations of the lessons varied from variously sized sport halls
to outdoor locations. Teachers were asked not to deviate from their regular PE
programme and to carry out their lessons as they had planned. None of the lessons
had a specifically planned physical activity intensity focus" (Slingerland et al.,
2011).
One lesson was looked at at every grade (4-12) and again at grades 7-10 because in secondary
55
school there are two school types, on up to 10thgrade and one to 12th grade, so each school
type was examined. In primary school, little more than half of the lessons were taught by a
specialist PE teacher and the rest by the classroom teachers, in secondary schools, all the
lessons were taught by PE teachers.
Cut-off-points to determine low, moderate and vigorous physical activity intensities (see table
13) were established.
Table 8: Cut points for moderate and vigorous activity, based on Stratton (1996) (Slingerland et
al., 2011)
Results of the study, in which data for 913 students were obtained during a total of 106 PE
lessons, concerning the amount of MVPA can be summarized in the following table:
Table 9: %MVPA by gender and grade (Slingerland et al., 2011)
56
Figure 12: Physical activity levels of Dutch school children during PE
lessons (Slingerland et al., 2011)
Statistical procedures (two-way independent ANOVA) for primary and secondary schools
showed main effects for gender and school type. More statistical analysis showed that primary
school students were more active than secondary school students and boys more than girls
(see figure 13).
For more results see: Slingerland et al., 2011.
Conclusions they drew, were to change the lesson contents in order to get the alarmingly low
PA levels of secondary school girls, which they blame on the prevalence of team-games, up,
and to increase the total number of PE lessons in order to make it possible for PE lessons to
contribute significantly to overall PA among children and adolescents (Slingerland et al. 2011).
Main differences between this study (apart from the fact that this one was conducted over a
longer period of time and examined a larger population) were the different school types and
therefore a more diverse population in this study, in terms of participants and setting. Another
main difference is the different measuring device. While Slingerland et al. chose a simple heart
rate monitor, I chose the more reliable combination of heart rate monitor and accelerometer.
Since the German school system is the one I examine during my study, previous studies in this
area are of special importance. Because of this, I will give a brief overview of the admittedly
bleak-looking current state of research on quantity of physical activity in German physical
education.
Considering the importance of physical activity levels in physical education, it is staggering to
see how few studies have been conducted in Germany, examining this phenomenon, let alone
57
studies which used reliable objective assessment methods. A number of studies have been
conducted during the sixties and seventies (Dietrich, 1964; Kretschmer, 1974; Hoppe & Vogt
1979), then there was a huge gap; in recent years a few studies have been implemented again
(Gerlach et al., 2006; Fröhlich et al., 2008; Rohn, 2008; Uhlenbrock et al., 2008; Wydra 2009;
Wydra 2010; Hoffmann, 2001). For an overview on the studies, please consult table no. 13:
Study
Method of assessment
Data outcome
Dietrich, 1964
Stopwatch/observation
Movement times
Kretschmer, 1974
Stopwatch/observation
Movement times
Hoppe & Vogt 1979
Stopwatch/observation
Movement times
Gerlach et al., 2006 (SPRINT)
Self-report scale of -3 to +3 (= Subjective estimate (unknown,
little movement to much
whether quantity or intensity)
movement)
Fröhlich et al., 2008
Heart-rate (HF-FLEX)
PA-levels
Rohn, 2008
Activity-diary
Subjective exertion
Uhlenbrock et al., 2008
Pedometer
PA-levels
Wydra 2009
Exertion-Questionnaire
(Borg-Scale) + observation +
HR
Subjective exertion + PA-levels
Wydra 2010
Heart-rate
PA-levels
Hoffmann, 2011
Stopwatch/observation
Movement times
Table 10: Overview German Studies PA in PE
As table 13 clearly illustrates, the data is limited. There are only three studies which measured
actual intensities of PA, which means that only those can give answers to many activity-related
questions, for example everything concerned with health and recommendations regarding PA,
since those are always given in time and intensity, energy expenditure or some combination
thereof.
But let's start chronologically: Andreas Hoffmann (2011) has already provided a nice graphic
summary of the older studies (see table 14):
Dietrich
(1964)
Kretschmer
(1974)
Hoppe & Vogt
(1979)
463
20
848
allocated time1
41 m 38 s
35 m 15s
34 m 30 s
movement time
(students)
10 m 50 s
5 m 43 s
6 m 34 s
examined lessons
equates to:
1 allocated time corresponds to the actual time of start and end of the lesson
58
in relation to clock time
24 %
13 %
15 %
in relation to allocated
time
26 %
16 %
19 %
Table 11: Movement times from various older studies (mod. after Hoffmann, 2011)
Those results seem disillusioning. You have to keep in mind, however, that only on-task
behavior was measured. If we take long-jump as an example, only the actual run-up and jump
would be considered movement, the walking back or jumping around while concentrating
would be disregarded. This means those movement-times weren't total movement times but
only those related to teacher instruction. Furthermore is the age of the conducted study a
factor because physical education and PE-teacher training has changed considerably since
then. The sports-concept (Sportartenkonzept) is no longer in practice, but rather fields of
movement (Bewegungsfelder) are the focus of modern-day PE. So let's take Hoffmann (2011)
in consideration which is a replication study of Hoppe & Vogt (1979). Movement times were
between 14% and 21%, so right around the results of the older studies. But let us keep in
mind that again only on-task behavior was measured.
Hoppe & Vogt reported that relative movement-times were significantly higher in single as
opposed to double lessons, a result which was also concluded by Hoffmann. Furthermore, they
said that class-size didn't have an impact, same with Hoffmann. Gym space however had a
negative impact, whenever there was too much or too little space. Here, Hoffmann's results
differed slightly, as more space meant more movement, differences were not significant,
however. Hoffmann also examined differences in movement-time in connection with teacher
gender and experience and concluded that more experienced teachers achieved more
movement from the students. Hoffmann also tagged students with a 'weak' or 'strong' label
and came to the not so surprising result that athletically better students move more during PE.
A more positive outlook is given by the SPRINT-study where students stated the experienced
exertion with 1,37 on a scale of -3 to +3 (see: Gerlach et al., 2006). What was measured exactly
(quantity, intensity,...) is unclear, and so is the validity of the self-report method.
One of the newer studies, conducted by Rohn (1998), also doesn't deliver helpful results in
regard to physical activity levels, es PA was assessed with activity diaries. Conclusions that PE
is less straining than sport in a club and that students didn't sweat much, don't give precise
indication on actual intensities.
Another study, on the basis of self-report-methods (questionnaires) was conducted by Wydra
59
(2009). In addition, observational techniques and heart-rate-monitors (n= 132) were used.
Subjectively, students found PE not very straining. Heart-rate results indicated an average HR
of 141,5 BPM, with intensity levels of 30 minutes above a HR of 140 and 38 minutes above
120, for a double lesson, which means that intensities are within a range that is beneficial for
health (Fröhlich et al, 2008, as cited in Wydra, 2009).
This leads us to the first study which is entirely based on objective assessment methods,
namely Fröhlich et al. (2008) who used the HF-Flex method to assess energy expenditure. It is
a pilot study, divided into two parts: In a first study, EE was measured in 15 children (12-14
years) and 14 adolescents (15-17 years) over the course of twelve days with and without
physical education. For a similar study, see: Graef, 2011. In a second study, EE was measured
in 22 children (11-13 years) during 7 different double lessons of PE. The second study is the
one, I will concern myself with. The average energy expenditure of the children can be seen in
the following table:
Figure 13: Average EE of the children during the 7
lessons (n=22; lesson time: 90 min) (Fröhlich et al., 2008)
The average energy expended for all lessons was 187±90kcal×90min, amounts within single
lessons differed between 82±53 and 266±92kcal×90min. Apart from big intraindividual
differences between lessons (up to factor 3), there were also huge interindividual differences
within the lessons (17 to 135kcal×90min in lesson 4).
Despite the small sample size which requires further systematic measures of PE lessons with
different contents, the potential of PE to influence the overall EE is evident (Fröhlich et al.,
2008). Unfortunately, Fröhlich et al. didn't assess the relative amounts of time spent in certain
activity intensity levels (low/moderate-to-vigorous/vigorous), which would have helped in
order to critically analyze the PE lessons.
60
Another study using objective measuring methods, was the one conducted by Uhlenbrock et
al., (2008) who used pedometers (StepWatch Activity Monitor (SAM) of the Fa. Cyma Inc.) to
determine the quantity and intensity of step activities by storing the number of steps in
minute intervals. Those devices were worn by 107 students over a period of 7 days. Resulting
data, which was analyzed as school time, leisure time, and weekend, was in step cycles per
hour (zyk/h). "One PE lesson increased physical activity during school time significantly
(p≤0,001) from 536±137 zyk/h to 741±267 zyk/h. Conclusion: PE increased the activity level
of a school morning by 38% above a school morning without PE lessons" (Uhlenbrock et al.,
2008). "Apart from the step cycles, PE also increased the MVPA rates before midday (>50
zyk/h) significantly (Uhlenbrock et al., 2008). Gender was again an influencing factor
regarding PA during physical education: On mornings with PE, boys moved 44% more than on
mornings without. The increase for girls was only 32%.
If we only look at physical education, the use of pedometers has to be brought into questions
because of its inability to adequately assess many types of complex movement. Another point
of criticism could be the relatively small sample size.
The last study I will take a look at was conducted by Wydra (2010). He examined PA levels in
PE of 208 female and 235 male students from 46 different grades (from 5-12) from different
types of schools. In addition, he collected data with various questionnaires (see: Wydra, 2009;
2010). All in all the study is very similar to his study from the previous year except for the
larger sample size. The average heart-rate of the students was at 140,7 BPM (compare 141,5
BPM (Wydra, 2009)) and the distribution of average heart rates was also similar. Compare
Tables 13 & 14 (Please note the different absolute lesson times):
Heart-rate-range (BPM)
Relative time (%)
Absolute time (min)
up to 100
7,4
4
101-120
17,2
9
121-140
24,4
12
141-160
21,2
11
161-180
15,3
8
181-200
11,1
6
higher than 200
2,0
1
Table 12: Relative and absolute time students spent at different intensity levels with an absolute
lesson time of 51 min (n=132) (mod. after Wydra, 2009)
61
Heart-rate-range (BPM)
Relative time (%)
Absolute time (min)
up to 99
6,4
5
100-119
16,3
12
120-139
26,5
20
140-159
25,1
19
160-179
16,8
13
180-199
8,2
6
more than 200
0,7
1
Table 13: Relative and absolute time students spent at different intensity levels with an absolute
lesson time of 76 min (n=417) (mod. after Wydra, 2010)
Unfortunately, Wydra, just like Fröhlich et al. didn't assess the relative amounts of time spent
in certain activity intensity levels (low/moderate-to-vigorous/vigorous), which would have
helped in order to critically analyze the PE lessons and compare them to international studies.
This is one of the major voids which I intend to close with the study that is to be described in
detail over the following pages. My other main point of criticism are the used methods of
assessment (except Fröhlich's HF-Flex that is highly validated), which all have major
weaknesses (see chapter 2.3 Measuring Physical Activity).
62
3. Empirical description of the study
3.1. Methods
3.1.1. Participants and setting
Participants in this field study were 323 German secondary school students from BurgGymnasium Schorndorf, in Baden-Wuerrtemberg. Among those were 165 girls (51,1%) and
158 boys (48,8%). Usable data could be gathered from 284 of those participants (165 girls
(58,1%) and 119 boys (41,9%)). Reasons for excluding data, were large missing chunks of
heart rate which happened when the electrodes loosened due to heavy sweating or physical
force, unrealistic values or software complications which made the data simply unreadable
with the Actiheart software. Why excluded data is exclusively restricted to male participants is
beyond me, but possible reasons could be attributed to the male physiology, e.g. excessive
sweating or chest hair. Concerns about varying chest sizes or complicated apparel in girls
which plagued me in the forefield, were luckily unsubstantiated. Small chest sizes of students
of lower grades also proved to not be a problem. From now on, the population I will be
referring
to,
An
overview
exact
are
the
of
the
284
participants
demographic
data
which
can
supplied
be
found
usable
in
data.
Appendix
4.
From each grade, at least 2 and up to 4 lessons were examined in order to receive a valid and
diverse set of data. In grades 5 & 6, physical education is taught co-educatively, so are the
classes in grade 11 & 12 who chose PE as one of their majors (Neigungs/Profilfach). The rest
of the grades are taught in separation with girls having female and boys male teachers. All the
teachers are specifically trained physical education teachers as is common in secondary
schools in Germany. The teachers taught their lessons according to the curriculum and were
told by me not to deviate from their regular PE program and to conduct their lessons as
previously planned. Locations of the lessons varied between two different-size gymnasiums
and an outdoor stadium. The smaller of the two gymnasium counts as two-thirds of the bigger
one. All examined lessons were double lessons, which is to be accounted for by the study
design. Explaining how to put on the Actihearts and putting on the devices, takes up to 10
minutes for the whole class which, in addition to the time that's lost due to getting changed
and the way to the sports site, would have made the rest of the lesson too short to be a typical
physical
education
lesson.
63
Unfortunately, because all the data was collected within one week, due to the strict regulations
of how much time this ‘admission paper’ is allowed to take until completion, the lesson
contents didn’t vary as much as I hoped and of the 22 lessons, 19 had team games as their
primary focus and only one was situated in the stadium.
3.1.2. Instruments and procedures
In each lesson, those students whose parents’ consent (and their own of course) we
had, were fitted with an Actiheart monitor. Those devices were described in detail in chapter
2.3.2.4.
Notes for the parents, where the procedures and intentions of the study were
described (see Appendix 1), were handed out to all classes, which were chosen to be
monitored, a few weeks earlier and enough parents gave their consent (see Appendix 2) so
that the study could be implemented. Students who were 18 years of age or older were
allowed to decide on their own whether they would like to participate or not. In addition, the
principal was informed of the project in a personal conversation and gave his consent.
Furthermore all the involved physical education teachers were given notice beforehand and
unanimously agreed to participate. Whether this extraordinary willingness to help is
experienced by other researchers as well, I don’t know, but it is possible that it is linked to my
personal connection to this particular school. I am a former student of this school myself and
additionally know some of the teachers through my years of voluntary work in a local sports
club.
30 Actiheart monitors with corresponding USB-chargers were provided by the Institute of
Sport- and Movement Science from the University of Stuttgart. The Actiheart devices were
charged and set up with the Actiheart computer software on each evening the day before they
were put to use. The recording intervals were set to 15 seconds for all examinations. At the
beginning of each lesson, I explained the participating students how to fit the device to their
chest with the help of a poster which showed a picture illustrating the exact location where it
should be placed on one’s chest area. During the explanation, a fellow university student of
mine, handed out the Actihearts, together with a set of electrodes and a small questionnaire to
gather personal information about gender, age, height and weight (see Appendix 3) and a pen
to fill out the questionnaire. The electrodes that were used were: Kendall ARBO* ECG
Electrodes which show strong adhesive strength and are not known for any unwanted side
effects. After they had been instructed, the students would either put on the instruments right
away in the gym (boys did this mostly) or go to the dressing room and put them on there
64
(most girls did this). As soon as everyone was ready, the lesson was started by the teacher. The
whole procedure, from explaining the device, until the start of the lesson, took between 5 and
10 minutes for all classes. At the end of each lesson, the students handed back the devices.
Complaints about the Actihearts were rare, however some of the participants complained
about slight discomfort when removing the electrodes (like removing a band-aid). The only
other complaint was that the glue of the electrodes was a little bit hard to wash off. During and
at the end of each lesson, the following variables were noted on standardized observation
sheets: scheduled and active lesson time, available PE area (e.g. 1/3 of the gymnasium), lesson
content and a protocol of the different activities throughout the lesson.
3.1.3. Data analysis
After data were collected with the Actiheart devices, it was imported into the Actiheart
software through USB-readers. There, data was checked for validity (if large chunks of heart
rate were missing, the data was discarded) and then transformed into advanced energy
expenditure (AEE) which is the amount of energy expended due to physical activity and METs,
the metabolic equivalent which expresses a person's activity at a time, through a standardized
branched model. I used a common group calibration model because of the diversity of the
group and because of the fact that individual calibration via step-test would have significantly
interfered with feasibility of the method in school. During the whole field study, it was my
desire to influence the regular education process as little as possible.
Data sheets from each student in each lesson were then exported into Microsoft Excel, or in
my case, OpenOffice Calc. In this program, the data were further processed and then entered
into SPSS 19.0 for subsequent analysis. Values were then calculated for the relative and
absolute amount of time spent at the intensity levels light, moderate, vigorous and MVPA
(moderate and vigorous). Descriptive statistics for scheduled and active lesson time were
calculated together with the total AEE and absolute and relative values in the different
intensity categories light, moderate, vigorous, and MVPA.
Prior to analysis, data were checked for acceptable values of normality with KolmogorovSmornov tests and equality (homogeneity) of variances with Levene's tests. Normal
distribution was found in all data. Where homogeneity of variances was given, I used analyses
of variance to check for significance, with AEE and %MVPA as the dependent variables.
Bonferroni post-hoc tests were performed to further examine differences in any significant
effects. Cut-off points for the different intensity levels were chosen at hand of the ones
65
established by Norton et al. (2010),
Where homogeneity of variances was not given, I used non-parametric tests (Mann-Whitney
and Kruskal-Wallis) to determine the significances between variables.
The alpha was set to 0,05 for all statistical analyses. Numbers were rounded to the second
decimal, except for statistical values (like F or p).
3.2. Hypotheses
In this chapter I will establish hypotheses which are based on previous findings,
scientific assumptions or, in one case, on personal supposition. These hypotheses lie the
groundwork for the empirical study and determine what exactly I am trying to find out. They
concern themselves with questions of overall physical activity during physical education and
the varying factors which influence it.
My first hypothesis is that physical activity during physical education has the potential to
contribute significantly to the overall amount of recommended PA for children and
adolescents (on school days). This had been suggested by Sallis et al. (1997) and I will try and
find out whether this is true for German secondary school physical education. The physical
activity guideline I will be referring to is one hour on moderate-to-vigorous PA per day which
has been suggested by various organizations (see chapter 2.4.1).
The next hypothesis I will investigate is that gender plays a significant role in the amount of PA
in PE. Findings about the total amount of physical activity suggest that girls are less active
than boys in general (Hildebrandt & Ooijendijk, 2008; Riddoch et al 2007, Cale & Harris 2006;
Richter & Settertobulte 2003). This may lead to the conclusion that the same is true for PE.
Evidence that girls are less active than boys in physical education has been found in the
studies conducted by Slingerland et al. (2011) "boys were more active than girls in secondary
school (Slingerland et al., 2011) (see figure 11) and Uhlenbrock et al. (2008) who said that on
mornings with PE, boys moved 44% more than on mornings without. The increase for girls
was only 32%. So the hypothesis states that boys are more active than girls during physical
education lessons.
My next hypothesis states that the amount of physical activity depends on the grade the
students are in. Slingerland et al. (2011) found a main effect for grade and his Post-hoc test
indicated that grade 5 students were more active than grade 6 students and grade 12 students
were more active than grad 8 and grade 10 students (Slingerland et al., 2011) (see table 10).
No clear tendency whether higher or younger grades were significantly more active could be
66
established which is why my hypothesis simply states that the amount of PA varies between
grades.
In close relation to this hypothesis stands the next one which predicates that the amount of
physical activity depends on the grade level of the students. This additional hypothesis is
included because I hope to identify an age-related tendency towards more or less physical
activity.
It's a fact that there is a relationship between physiological performance capability and the
time of the day (Hildebrandt, 1994; Hildebrandt e al., 1998, as seen in Siepmann & SalzbergLudwig, 2006). This means that the physiological performance capability is subject to a
certain biological rhythm of the day. This can be illustrated graphically as a physiological
performance curve (Siepmann & Salzberg-Ludwig, 2006) (see figure 13). This phenomenon
generally applies to all humans, there are however individual differences.
Figure 14: Physiological Performance Curve - relationship between time of day
and physiological performance capability (mod. after Rothfuchs, 1995)
The underlying question is whether this physiological performance curve influences physical
activity levels in physical education. The hypothesis which results from this is: Physical
activity levels are affected by the time of day.
An additional hypothesis which stems from personal experience is that PA in PE is higher in
the afternoon than is is in the morning.
An interesting observation has been made by Hoffmann (2011) who stated that it needs just
67
the right amount of available PE area in order to get high activity levels in students. My
resulting hypothesis is that too little or too much available PE area negatively affects physical
activity levels.
Another hypothesis stems from personal experience and states that: Children and adolescents
who are overweight or obese are less physically active than under- or normalweight children
and adolescents during physical education.
While observing all those lesson I made an interesting observation: Physical activity levels
seemed to be at their highest during the warm-up phase which I found interesting because it
is only supposed to be the warm-up phase and not the main strenuous part of the whole
physical education lesson. MY hypothesis which stems from this observation is that PA levels
are at their highest during the warm-up phase.
68
4. Results
In the following chapter I will present the results of the conducted field study. Points of
interest are absolute and relative lesson times, the expended energy due to physical activity
(AEE) and the absolute and relative amount of lesson time spent in the intensity level of
moderate-to-vigorous activity (MVPA (min), %MVPA). The various factors which influence
these variables (gender, grade, grade level (lower, middle and upper), time of the lesson, time
of day (morning, afternoon), available PE area, BMI and gender * grade level), will be shown,
compared and checked for statistical significance.
Data for 284 students from 22 different lessons were obtained. Scheduled lesson time was
always 90±0 minutes (standard double lesson) and active lesson time was 69,54±7 min (range
57-82) which corresponds to 77,26% of scheduled lesson time. The difference between
scheduled and active lesson time was 22,74% (20,46 min). These numbers are to be taken
with a grain of salt however because the active lesson time was negatively influenced by the
field study, since the handling of the Actiheart devices took between 5 and 10 minutes at the
beginning of each lesson. This means those numbers do not represent real unaffected facts
which is why I didn't investigate them further and for example compared active lesson times
between grades, gender or day time.
Average AEE was 813,37±322,31 kiloJoule with a range of 174-1944 kJ among all students.
Overall percentage of time spent in MVPA was 58,98±17,85% with a range of 7,83-98,8% for
all students. This corresponds to absolute time spent in MVPA of 42,14±13,66 min with a
range of 6-73 min. Mean values for the relative light, moderate and vigorous intensity
categories were 41,02±17,85% (range 1,19-92,17), 45,97±12,47% (range 7,83-76,14) and
13,02±13,25% (range 0-72), respectively. Those values correspond to absolute times of
29,12±12,74 min, 32,91±9,93 min and 9,23±9,18 min, respectively.
This paints a clear picture in regard to the first hypothesis: Time spent in in MVPA is on
average 42,14±13,66 min which corresponds to 70,23% of the recommended daily activity.
This number shows that the major part of recommended PA can be achieved thorough
physical education on school days with at least a double lesson of PE. This last dependent
clause however shows a clear restriction on real contribution of PE to total PA because
students usually only have 2-3 PE lessons a week. Converted to the whole week, including the
weekend, the amount of time spent in MVPA which stems from PE only accounts for about 1015% of the total recommend physical activity, assuming that single lessons have the same
69
absolute amount of time spent in MVPA. All the while one has to keep in mind that results are
slightly distorted due to the applying of the Actihearts at the beginning of each lesson.
When we look at the differences in gender we can see that boys (n=119) had a mean AEE of
799,98±358,13 kJ (range 174-1994) and girls (n=165) had 823,02±294,55 kJ (range 2591733).
Levene's test for homogeneity of variance was significant (F 1,282=6,903, p=0,009), so I used a
non-parametric test (Mann-Whitney) to determine whether the difference of AEE in relation
to gender was significant. The result (p=0,241) clearly shows that no significant difference
exists between boys and girls.
This results falsifies the hypothesis that boys are more active during physical activity when
the measure in question is the expended energy by means of physical activity.
In regard to percentage spent in MVPA the difference between boys who have a mean %MVPA
of 48,92±14,75% with a range of 7,83-81,76% and girls who have 66,24±16,33% with a range
of 25,69-98,81% was determined using a One-Way ANOVA (homogeneity of variance was
given with Levene's test: F1,282=1,605, p=0,206). The result of the analysis of variance
(F1,282=84,262, p<0,001) shows a significant effect of gender on %MVPA.
Concerning the second hypothesis that boys are more active during PE than girls, the results
again indicate that that's not the case, when using %MVPA as the measure of choice. On the
contrary, it is shown that girls spend significantly more time at the intensity level of moderateto-vigorous physical activity and are therefore more active than boys.
The next point to be investigated is grades and their influence on PA levels in PE. Grade 5
(n=37) had a mean AEE of 458,59±118,401kJ (range 259-686), grade 6 (n=44) had a mean
AEE of 596,05±176,087kJ (range 174-924), grade 7 (n=38) had a mean AEE of
789,11±266,063kJ (range 362-1733), grade 8 (n=19) had a mean AEE of 853,37±158,723kJ
(range 620-1138), grade 9 (n=36) had a mean AEE of 861,53±244,028kJ (range 434-1317),
grade 10 (n=37) had a mean AEE of 1104,57±261,646kJ (range 714-1592), grade 11 (n=35)
had a mean AEE of 1072,31±276,725kJ (range 261-1640) and grade 12 (n=38) had a mean
AEE of 847,03±365,317kJ (range 376-1944). Numbers for %MVPA were: Grade 5 (n=37) had a
mean %MVPA of 42,3073±11,653% (range 19,11-64,37), grade 6 (n=37) had a mean %MVPA
of 50,26±15,01% (range 7,83-77,62), grade 7 (n=37) had a mean %MVPA of 61,13±17,22%
(range 28,57-86,16), grade 8 (n=37) had a mean %MVPA of 61,58±10,25% (range 41,4076,45), grade 9 (n=37) had a mean %MVPA of 66,42±17,64% (range 29,47-94,95), grade 10
(n=37) had a mean %MVPA of 71,52±17,14% (range 44,51-98,47), Grade 11 (n=37) had a
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mean %MVPA of 64,02±16,24% (range 34,58-98,81) and grade 12 (n=37) had a mean %MVPA
of 57,98±16,14% (range 18,78-94,42). In order to check the hypothesis that grade has a
significant influence on PA levels during physical education, non-parametric tests had to be
used for AEE and %MVPA because tests for equality of variances were significant in both cases
(Levene's test had: F7,276=5,568, p<0,001 and F=2,506, p=0,016, respectively). Kruskal-Wallis
tests were significant in both cases (p<0,001) which means that the hypothesis "amount of PA
varies between grades" has been proven. Subsequent Mann-Whitney tests showed significant
differences in energy expenditure between the following grades: 5 and 6 (p=0,001), 5 and 7, 8,
9,10,11,12 (p<0,001); 6 and 7,8,9,10,11 (p<0,001), 6 and 12 (p=0,001); 7 and 10,11
(p<0,001); 8 and 10,11 (p=0,001); 9 and 10 (p<0,001), 9 and 11 (p=0,001); 10 and 12
(p<0,001); 11 and 12 (p=0,001) with an ascending grade order in regard to mean AEE of
5<6<7<12<8<9<11<10 (10 being the highest).
Mann-Whitney tests (Levine's test was significant again with F 7,276=2,506, p=0,016) examining
the %MVPA between each grade showed the following differences: 5 and 6 (p=0,012), 5 and
7,8,9,10,11,12 (p<0,001); 6 and 7,8 (p=0,004, 6 and 9,10 (p<0,001), 6 and 11 (p=0,001), 6 and
12 (p=0,016); 7 and 10 (p=0,009); 8 and 10 (p=0,020); 9 and 12 (p=0.037); 10 and 12
(p=0,001)
with
and
ascending
grade
order
in
regard
to
mean
%MVPA
of
5<6<12<7<8<11<9<10 (10 being the highest).
The next hypothesis I will examine is whether the grade level (lower, middle, upper) has an
effect on PA levels in PE. The study showed that the lower grade level (had a mean AEE of
614,96±235,24kJ (range 174-1733), the middle grade level (grades 8-10) (n=92) had a mean
AEE of 957,59±263,95kJ (range 434-1592) and the upper grade level (grades 11&12) (n=73)
had a mean AEE of 955,04±342,91kJ (range 261-1944). Levene's test for equality of variance
was significant again (F2,281=7,108, p=0,001) so the non-parametric Kruskal-Wallis test was
used and showed significance (p<0,001). Subsequent Mann-Whitney tests showed significant
differences between lower and middle (p<0,001) and lower and upper grade level (p<0,001).
No significant difference was detected between middle and upper grade level (p=0,907).
With %MVPA as the influencing variable, numbers were as follows: Lower grade level had
51,26±16,53% (range 7,83-86,16), the middle grade level had 67,47±16,46% (range 29,4798,47) and the upper grade level had 60,88±16,36% (range 18,78-98,81). Variances were
homogenous (Levene's was: F2,281=0,774, p=0,462), so a One-Way ANOVA was performed and
proved to be significant (F2,281=25,789, p<0,001). The post-hoc Bonferroni test revealed
significant differences in mean %MVPA between lower and middle (p<0,001), lower and
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upper (p<0,001) and middle and upper grade level (p<0,033).
The hypothesis "grade level influences physical activity levels in physical education" has been
verified. A tendency can also be recognized, as middle and upper grade levels had significantly
higher numbers than the lower grade levels with middle having the highest PA levels.
Interestingly, no interaction effect was found between gender and grade-level. A two-way
ANOVA was used to determine whether there is an interaction effect, between the two main
effects gender and grade level on &MVPA. Homogeneity of variances was given (Levene's
F5,278=1,265, p=0,281). The result of the two-way ANOVA was (F2,283=0,432, p<0,650).
Next in line is the hypothesis that physical activity levels in physical education are affected by
time of day. I have therefore had a look at the different times at which the lessons were
conducted. Double lessons starting at the first (7.40-9.10 o'clock), the third (9.30-11.00
o'clock), the fifth (11.20-12.55 o'clock), the seventh (13.00-14.35 o'clock), the eighth (13.5015.25 o'clock), the ninth (14.40-16.15 o'clock), the tenth (15.30-17.05 o'clock) and the
eleventh (16.20-17.55 o'clock) lesson, were surveyed.
With expended energy due to physical activity (AEE) as measurement method, homogeneity
of variances was given (Levene's test: F 7,276=1,322, p=0,240) and a One-Way ANOVO was
conducted which showed significance (F7,276=24,793, p<0,001). Mean results for the separate
lesson times were: First (n=52) 598,65±254,70kJ (range 174-1303), third (n=72)
656,35±212,64kJ (range 275-1138),
fifth (n=27) 1072,15±289,32kJ (range 563-1733),
seventh (n=13) 992,15±352,08kJ (range 261-1640), eighth (n=21) 657,14±169,03kJ (range
362-988), ninth (n=38) 1025,39±283kJ (range 434-1592), tenth (n=11) 1294±310,67kJ
(range 872-1944) and eleventh (n=50) 875,28±262,13kJ (range 455-1592).
The Bonferroni post-hoc test showed significant differences between double lessons, starting
at the first and fifth , seventh , ninth, tenth, eleventh (p<0,001) period, between third and fifth
(p<0,001), seventh (p=0,001), ninth, tenth, eleventh (p<0,001), between fifth and eight
(p<0,001) and fifth and eleventh (p=0,04), between seventh and eighth (p=0,007), between
eighth and 9,10 (p<0,001), eighth and eleventh (p=0,033) and between tenth and eleventh
(p<0,001). An ascending list of the respective times the lessons were conducted in regard to
AEE looks as follows: first<third<eighth<eleventh<seventh<ninth<fifth<tenth (with tenth
having the highest numbers).
In regard to %MVPA, the numbers of the lesson times look as follows: First 48,88% (range
7,83-98,81), third 52,59% (range 18,78-77,62), fifth 65,27% (range 34,58-86,16), seventh
70,91% (range 36,91-90,94), eighth 50,84% (range 28,57-78,19), ninth 71,05% (range 29,47-
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98,47), tenth 61,51% (range 51,21-71,38) and eleventh 65,89% (range 30,38-94,42). Since
homogeneity of variances was given (Levene's: F 7,276=1,852, p=0,078) an one-was ANOVA was
conducted and showed significance (F7,276=11,634, p<0,001). The Bonferroni post-hoc test
showed significant differences between first and fifth (p=0,001), seventh, ninth, eleventh
(p<0,001), between third and fifth (p=0,013), seventh (p=0,004), ninth, eleventh (p<0,001),
between seventh and eighth (p=0,011), and between eighth and ninth (p<0,001), eleventh
(p=0,009).
Ascending list: first<eighth<third<tenth<fifth<eleventh<seventh<ninth (with ninth being the
highest).
In terms of the hypothesis "physical activity levels in physical education depend on time of the
day" a cautious 'yes' can be stated. Careful because low amounts of lessons were conducted for
each period of time. This means that other factors of the involved lesson could have a bigger
influence than the time of the day.
The low sample sizes for each period are another reason for the next hypothesis which says
that PA levels in PE are higher in the the afternoon than in the morning. Here, the different
periods of time have a larger sample size, each. Morning is defined as the time from 7.4012.55 o'clock and afternoon is from 13.00-17.55 o’clock.
Mean AEE in the morning (n=151) was 710,83±295,39kJ (range 174-1733) and in the
afternoon (n=133) it was 929,78±312,87. Homogeneity of variances was given (Levene's:
F1,282=0,169, p=0,681) and a one-way ANOVA showed a significant difference between morning
and afternoon in terms of energy expenditure (F1,282=36,756, p<0,001).
Mean %MVPA is 53,58±16,80% (range 7,83-98,81) in the morning and 65,12±17,06 (range
28,57-98,47) in the afternoon. Again, homogeneity of variances was given (Levene's:
F1,282=0,146, p=0,703) and a one-way ANOVA showed a significant difference between morning
and afternoon in terms of energy time spent in the range of MVPA (F1,282=32,871, p<0,001).
In consequence, the hypothesis "physical activity levels in physical activity are higher in the
afternoon the in the morning" can be accepted.
"Too little or too much available PE area negatively affects physical activity levels", is the next
hypothesis I will turn my attention to. In order to investigate this claim, each lesson was
categorized into one of three groups which stand for a particular amount of available PE
space. All lessons, except for two were held in the same gym and had either one, two or three
thirds of the whole gym to their disposal, so those three available spaces mark my categories.
One lesson was held in a smaller gym which counts as 2/3 of the big one and one lesson was
73
held outside in a stadium which I have matched with the largest category 3/3.
For mean AEE, results were as follows: One third (n=111) 674,94±300,15kJ (range 174-1733),
two thirds (n=134) 942,19±313,17 (range 261-1944) and three thirds (n=39) 764,72±229,58
(range 376-1303). With homogeneity of variances given (Levene's F 2,281=1,903, p=0,015), a
one-way ANOVA was performed and turned out significant (F 2,281=25,015, p<0,001).
Bonferroni post-hoc analysis showed significant differences between 1/3 and 2/3 (p<0,001)
and between 2/3 and 3/3 (p=0,004).
When we take the mean amount of time spent at the intensity of moderate-to-vigorous
physical activity into consideration, one third is at 51,64±16,82% (range 7,13-86,16), two
thirds is at 64,78±16,55% (range 28,57-98,47) and three thirds is at 59,95±17,86% (range
18,78-98,81). Levene's test was significant again (F2,281=0,31, p=0,970) and a one-way ANOVA
was performed. Results were: F2,281=18,558, p<0,001, so significance is given. Bonferroni posthoc test signaled significant mean differences between 1/3 and 2/3 (p<0,001) and between
1/3 and 3/3 (p=0,025).
The hypothesis: "too little or too much available PE area negatively affects physical activity
levels" is proven since 2/3 of the gymnasium has the highest marks concerning AEE and
%MVPA and, except for 2/3 and 3/3 with %MVPA, the differences between one/three thirds
and two thirds are significant.
For the investigation of the next hypothesis, whether obese or overweight children and
adolescents move less than the rest, the population was subdivided (according to their BMI)
into 'underweight' (<18,6), 'normalweight' (18,6-25), 'overweight' (25,1-30) and 'obese'
(>30). Energy expenditure due to PA during the lessons showed the following numbers for the
groups: underweight (n=131) 654,33±232,56kJ (range 259-1310), normalweight (n=141)
917,16±305,7kJ (range 174-1733), overweight (n=10) 1237±277,35kJ (range 815-1592) and
obese (n=2) 1792±214,96kJ (range 1640-1944). Levene's test for equality of variance showed
homogeneity (F3,280=2,556, p=0,056), so a one-way ANOVA was performed which also turned
out to be significant (F3,280=38,254, p<0,001). Bonferroni post-hoc tests showed significant
differences between all groups, except overweight and obese. Numbers were: between
underweight and normalweight: p=0,001, between underweight and overweight: p=0,001,
between underweight and obese: p=0,001, between normalweight and overweight: p=0,002,
between normalweight and obese: p<0,001 and between overweight and obese: p=0,055
The percentage of the lessons at which the students move at moderate-to-vigorous intensity is
as follows for the four groups: underweight 54,6±16,81%(range 19,11-90,91), normalweight
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62,12±17,98% (range 7,83-98,81), overweight 68,49±16,08% (range 41,03-94,95) and obese
77,44±19,09 (range 63,93-90,94). Homogeneity of variances was given (Levene's
test:
F3,280=0,298, p=0,827. A one-way ANOVA was performed and deemed significant (F 3,280=6,052,
p=0,001). Bonferroni post-hoc tests showed significance for the difference of means between
the group underweight and the group normalweight.
The hypothesis that obese or overweight children and adolescents move less than the underor normalweight children has to be clearly rejected at hand of these numbers which say that
the exact opposite is true., when we look at the numbers for AEE. For %MVPA, only the
difference of means between the underweight childrean and the normalweight children is
significant so nothing much can be said in terms of the hypothesis, considering these
numbers. However, all of those results have to taken with reservation because the sample size
of overweight and obese children and adolescents is too small to be valid and to draw further
conclusions.
For my last hypothesis that the warm-up phase has a higher intensity level than the rest of the
lesson, I divided each lesson into two parts: Warm-up part and rest-of-the-lesson part, as i had
noted it on the observation sheets. I then took the mean MET value of all students for the two
parts and checked for significance with a one-way ANOVA. Mean MET for the warm-up phase
was 6,32±1,5METs (range 3,4-9,5), for the rest of the lesson it was 3,47±0,39METs (range
2,13-4,14)- Levene's test for equality of variances showed that they are homogenous
(F1,384=319,392, p<0,001). A one-way ANOVA showed that the mean difference is significant
(F1,384=872,47, p<0,001). That means that this hypothesis has been confirmed. This can also be
seen clearly in the following diagram which shows: The mean MET values of all students over
the course of their respective lesson. (The values for lesson time are to be ignored, since they
were only of use in creating this diagram).
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Figure 15: Mean MET values of all students over the course of their lessons.
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5. Discussion
I will start this discussion by taking a closer look at the results of each of the
hypotheses and compare them to similar results from other studies. After that I will discuss
possible implications these results could have, in regard to the structure and quantity of
physical education. Finally, to round this discussion up, I will discuss the methods and data I
used, with advantages and disadvantages at the center of interest.
The first hypothesis was that physical activity during physical education could play a role in
meeting physical activity guidelines for children and adolescents. In my study, students
accumulated an average of 42,14 min of moderate-to-vigorous physical activity per doublelesson. This is right on par with the findings of Slingerland et al. (2011) who had 21,44 min of
MVPA per single lesson in secondary school. If we take curricular and infrastructural
conditions into consideration, it becomes clear that PE alone has no chance of providing an
adequate relief for the existing problem of inactivity in young people. However, in combination
with other activities at school and during free-time, it has the potential to at least contribute in
a meaningful way. One double lesson covers about 2/3 of a child's daily recommended
physical activity, so one way to go, as far as providing children (especially in urbanized areas)
with an opportunity to get their MVPA, would be to simply increase the number of physical
education lessons. However, financial and political circumstances make this a long shot. The
goal of some people is to make PE lessons even more strenuous so that they get a training-like
character. This is not necessary, as the amount of %MVPA is already fairly high, and other
aspects would likely suffer from such a development. In comparison to the older German
studies who have concluded movement times of 16% (Kretschmer, 1974) to 26% (Dietrich,
1964) of allocated time, the difference seems enormous. One important point you have to keep
in mind, however, is the distinction between on-task movement time (which has been
investigated in the older studies) and general movement time (which is what I was trying to
find out). On-task movement time is, if anything, only interesting for the investigation on the
pedagogic quality and effectiveness of the lessons but not for anything further such as healthrelated questions. For more on this distinction see Wydra (2010).
The next hypothesis that girls are less physically active than boys during PE has been rejected,
since the exact opposite is true. This is a very surprising result, as literally all other studies
(Slingerland et al., 2001; Uhlenbrock, 2008, to name just a few) have come to a different result.
Age also proved to not be a significant factor in this case as no interaction effect between
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grade-level and gender could be found. I can only guess, what the reasons for this situation are
but one possible explanation could be the fact that the school where the study was conducted
has only recently hired several young female PE teachers and it is possible that the more
recent schooling of these teachers had a positive effect on the students' PA levels in PE. This
however is only a guess, as I have failed to note the age of the involved teachers with the
lessons. The more simple and therefore probably better explanation is that the general belief
that girls are less physically active is just that: a general belief. This is even more interesting if
we include the fact, that nearly all surveyed lesson had team games as their topic. The
dominance of team games in physical education has been a suggested reason for the superior
physical activity of boys (Slingerland et al., 2001). The topic of lesson content needs further
investigation in order to make definite statements about it's effect on physical activity levels.
The hypotheses which were concerned with connection between age and PA levels in PE
(variables were grade and grade level, respectively) also showed results which differed greatly
from the findings of other studies (see: Slingerland et al., 2001). In this case younger students
had significantly lower levels than the older ones. While one explanation could be the
relatively small sample size of examined lesson (n=22), another reason could be found in the
type of method and data analysis, which I will comment on later. Disregarding those possible
explanations, solutions have to found how the younger students can be motivated to be more
active. Further research is definitely necessary for this topic.
Another interesting hypothesis is whether the time at which the lesson was conducted has an
influence on the ensuing amount of physical activity. When comparing the starting times of the
different lesson, a significant effect could be measured, however, the sample sizes were too
small to provide a valid overview of the situation in reality. More promising was the result,
that lesson conducted in the afternoon showed significantly higher activity levels than the
ones in the morning. This observation could have serious ramifications for the planning of
when to best provide PE lessons. But again, due to a very limited number of gymnasiums each
school has access to, the schools don't really have a choice whether they would like their PE
lessons in the morning or in the afternoon, as they have to fill every minute of available gym
space.
The next hypothesis I checked is directly related to gym space and whether there is such a
thing as a right amount of space. Meaning that too little or too much available PE are has
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negative effects on PA levels. The results were in line with the observation Hoffmann (2011)
made that too little or too much gym space indeed has a negative impact on physical activity
levels in physical education. Reasons for this are rather straightforward: Too little space has a
negative effect because students simply do not have much room to run around and the teacher
is very limited with the choosing of his contents and methods because a large number of
activities is not possible on such small space. Nobody can imagine for example a team game
like soccer played by thirty students in just a third gymnasium. In regard to much gym space,
the reasoning gets a little trickier but the most logic explanation is that students don't feel the
need to move as much, if they aren't under constant observation by the teacher. And the
teacher's job to have an eye on everyone is definitely impeded by a larger scenery. This effect
leads to a possible instruction for teachers, namely that they shouldn't necessarily use all the
PE area available to them if they don't need it.
Another, for me, surprising result was concluded win comparing physical activity levels in
connection with the BMI. Results were that overweight and obese children and adolescents
have a higher advanced energy expenditure during lessons. Whether this is because they
actually move more, or the fact that EE is dependent in body mass is hard to tell. Furthermore
has to be said that the sample sizes for overweight (n=10) and obese (n=2) is very small, so no
valid conclusions can be made. Nevertheless is the fact that only so very few students are
battling a body weight that is seemingly too high is very pleasant. This could be related to the
type of school which was the highest secondary school type (Gymnasium) and therefore
relatively seen fewer children from uneducated families are there than in the general
population. If we disregard the possible explanations why this result is not valid, and spring
from the actual results, it is very encouraging to see that children aren't less active because
they are heavier and might in fact be doing something positive for their health.
Results for my last hypothesis didn't surprise me at all, as they matched what I had observed
during the lessons: Physical activity levels are at their highest during the warm-up phase of
physical education lessons. This results should give PE teachers pause to think and reevaluate
their teaching habits as the warm-up pause probably isn't intended to be the main source for
PA but rather to to prepare students for subsequent phases with relatively high intensity
levels. This means that either the first part of the lesson should be less intensive or, even
better, the rest of the lesson should be more intensive.
The next part is about the used methods and type of data analysis. The relatively low activity
levels for younger and lighter students, gave me pause as to why this is the case and one
79
possible reason could stem from the way the data was analyzed. Energy expenditure, as well
as METs are both have body mass as an big influencing factor and, in this case, weren't
corrected for age and gender of the participants. The group calibration setting I have used
could have possibly had the side effect that activity levels of lighter and in consequence
younger students were underestimated in comparison to other participants of the field study.
In order to avoid this problem, an individual calibration for each student would have had to
have taken place and this would have greatly interfered with my intention to hold the
disturbance of the regular school process to a minimum. Furthermore, one intention of this
study was to show that a high quality field study for such a complex matter could be
conducted without the prerequisite of much money, time or man power. Although to be fair,
the expensive equipment was provider by the Institute of Sports- and Movement Science of
the University of Stuttgart.
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6. Outlook
In order to give an adequate outlook, I will start with the missed opportunities which
unfolded as the process of this field study moved along. Too small sample sizes proved to be
one of the main hindrance points, why the effect of some of the variables (time of day, BMI)
couldn't be more accurately described. Other interesting variables, such as lesson content,
couldn't be investigated at all. The effect of certain teacher characteristics on PA levels is, for
example, of great interest. The effect of teacher gender would have been impossible to
measure because female teachers teach female classes and vice versa. Additionally, several
observed lessons were conducted by the same teachers which would have further nullified
eventual results. Teacher age or experience would have been interesting variables as well,
unfortunately though, that thought hadn't crossed my mind until the data gathering part of the
field study was completed. To my own disappointment, this is the reason for another variable
not to be included, namely the available space in student per m 2 which had enhanced the
results for the hypothesis that a certain amount of available PE space has the highest PE levels.
I didn't think of measuring the gymnasium at the time the study was conducted.
So in order to get an even better impression of the physical activity levels in physical
education and it's influencing factors, large-scale follow-up studies need to be implemented
which take the points of weakness of this study into consideration to get even better results.
The second part of this outlook states the necessity for empirical findings, like the ones
presented here, to find their way into practice. Possible implications (stated in the discussion),
have to be made publicly available to schools and people with the authority to influence
decisions made for the field of education. The level of interest among the participating
students, parents and teachers was high and results will be made available on the school
homepage, following a large array of questions.
So not only does more empirical evidence have to be generated, the possibly even more
important aspect is to overcome the barrier between theory and practice.
81
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Acknowledgment
I want to thank the Burg-Gymnasium Schorndorf, especially it's headmaster, Mr. Hohloch and
all participating teachers and students for being supportive and helping me getting this work
done. I would like to particularly underline Michael Oelschlegel's efforts. He helped a great
deal distributing the information among students and fellow teachers and therefore was a
vital part of this work. Last but not least I want to thank my girlfriend Emilia Kiefer for putting
up with me throughout this time and still being able to be supportive.
Thank You.
93
Erklärung
Hiermit versichere ich, dass die Arbeit
(Physical Activity Levels of Students in Physical Education)
von mir selbst und ohne jede unerlaubte Hilfe angefertigt wurde, dass sie noch keiner anderen Stelle
zur Prüfung vorgelegen hat. Die Stellen der Arbeit einschließlich der Tabellen und Abbildungen, die
anderen Werken dem Wortlaut oder dem Sinn nach entnommen sind, habe ich in jedem einzelnen
Fall kenntlich gemacht und die Herkunft nachgewiesen.
..............................................................................
Datum und Unterschrift
94
Appendices
I. Parental Information
Informationsbrief
Liebe Schülerin, lieber Schüler, sehr geehrte Eltern,
im Rahmen ihrer Abschlussarbeit führen Jonas Holder und Harald Graef (Institut für
Sport‐ und Bewegungswissenschaft, Universität Stuttgart) unter der Leitung von Prof. Dr. Wolfgang
Schlicht eine Studie zur Erfassung des Energieumsatzes/ der Bewegungsaktivität durch.
Mit der Teilnahme an der Studie werden die Schüler/-innen uns helfen zu verstehen,
inwieweit die Schule zu der allgemeinen körperlichen Aktivität der Kinder einen Beitrag
leistet. Die Erhebung sowie die Verarbeitung der Daten werden anonym sein. Die Studie ist keine
Prüfung, es gibt also keine falschen Antworten oder Ergebnisse. Uns interessiert einzig die körperliche
Aktivität der Kinder bei alltagsrelevanten Aufgaben und wie diese in Zukunft noch besser zu fördern
sind.
Durch die Teilnahme (oder Nichtteilname) an der Studie entstehen der Schülerin/ dem Schüler keine
Nachteile. Die Erhebung der Daten wird mittels eines Actiheart-Monitors durchgeführt
(http://www.camntech.com/cnt_actiheart.htm), einem kleinem Gerät, das dem Sensor einer
Pulsuhr ähnelt. Hierzu werden die Schülerinnen und Schüler das Gerät lediglich für die Dauer des
Sportunterrichts tragen.
Im Anschluss an die Studie werden wir den Schülerinnen und Schülern einen Einblick in die
Ergebnisse verschaffen und ihnen zeigen was daraus geworden ist. Wir erhoffen uns
hierdurch auch das Interesse und das Verständnis für Bewegung und körperliche Aktivität zu
fördern.
Für weitere Fragen können Sie sich gerne mit uns in Verbindung setzen:
Jonas Holder
0171-1955432
Harald Graef
0163-8727080
[email protected]
[email protected]
Wir bedanken uns an dieser Stelle schon einmal ganz herzlich für deine bzw. Ihre Unterstützung.
Hochachtungsvoll,
Jonas Holder und Harald Graef
95
II. Parental Declaration of Consent
Universität Stuttgart
Inspo• Allmandring 28 • 70569 Stuttgart
Formular zum Einverständnis der freiwilligen Teilnahme zur
Erfassung des Energieumsatzes/ der Bewegungsaktivität
bei Schülerinnen und Schülern
In der Eigenschaft als Erziehungsberechtigte/r (Eltern oder Sorgeberechtigte/r) des Kindes,
der an
der Studie teilnimmt, erkläre ich:
→ Ich habe einen Brief erhalten, der die Aspekte dieser Studie beschreibt.
→ Ich habe alle Informationen, die mir gegeben wurden, gelesen und verstanden.
→ Ich weiß, dass die Teilnahme freiwillig ist und mein Kind nicht verpflichtet ist, an dieser Studie
teilzunehmen.
→ Ich weiß, dass meinem Kind durch das Verweigern der Teilnahme keine Nachteile während der
Studie und auch nicht danach entstehen.
→ Ich nehme zur Kenntnis, dass alle erhobenen Daten anonym und nicht persönlich zu identifizieren
sind, so dass es nicht möglich ist, das Kind, das an den Tests teilgenommen hat, ausfindig zu
machen oder die gesammelten Daten zu einem späteren Zeitpunkt zurückzuverfolgen oder
abzuändern.
→ Ich bin damit einverstanden, dass die für die Studie gesammelten Daten anonym durch die
Universität
Stuttgart ausgewertet und analysiert werden.
Ich bin als Erziehungsberechtigte/r damit einverstanden, dass mein Kind an der Studie zur
Erfassung des Energieumsatzes/ der Bewegungsaktivität teilnimmt.
An den Ergebnissen, und daran wie so eine Studie aussieht, wäre ich auch interessiert. Bitte
schickt mir eine Zusammenfassung der Ergebnisse zu, an folgende E-Mail-Adresse:
______________________________________________
Name des Kindes:
______________________________________________
Klasse des Kindes:
__________________________________________________
Erziehungsberechtigte/r (Eltern oder Sorgeberechtigte/r) :
Ort, Datum Name, Vorname und Unterschrift
________________________________________ ______________________________________‐__________________________________
Institut für Sport- und Bewegungswissenschaft
Allmandring 28 • 70569 Stuttgart
http://www.sport.uni‐stuttgart.de
96
III. Small Questionnaire about Personal Information
Universität Stuttgart
Inspo• Allmandring 28 • 70569 Stuttgart
Actiheart-nr.:
Datum:
Unterrichtsstunde(n):
Persönliche Informationen:
Klasse:
Geschlecht:
Geburtsdatum:
Größe:
Gewicht:
Anleitung zum Anlegen:
Das Gerät wenn
möglich bitte so
aufkleben.
97
IV. Demographic Data
Age
Age
N
Valid
284
Missing
0
Age
Valid
Accumulated
Percentage
Percentage
Frequency
Percentage
9
3
1,1
1,1
1,1
10
33
11,6
11,6
12,7
11
41
14,4
14,4
27,1
12
37
13,0
13,0
40,1
13
21
7,4
7,4
47,5
14
33
11,6
11,6
59,2
15
32
11,3
11,3
70,4
16
25
8,8
8,8
79,2
17
21
7,4
7,4
86,6
18
26
9,2
9,2
95,8
19
9
3,2
3,2
98,9
20
2
,7
,7
99,6
21
1
,4
,4
100,0
284
100,0
100,0
Accumulate
d
Gender
Gender
N
Valid
Valid
Missing
284
0
98
Gender
Frequency
Valid
Percentage
Valid
Accumulated
Percentage
Percentage
male
119
41,9
41,9
41,9
female
165
58,1
58,1
100,0
Accumulate
284
100,0
100,0
d
Grade
Grade
N
Valid
284
Missing
0
Grade
Frequen
cy
Valid
Accumulated
Percentage Valid Percentage
Percentage
5
37
13,0
13,0
13,0
6
44
15,5
15,5
28,5
7
38
13,4
13,4
41,9
8
19
6,7
6,7
48,6
9
36
12,7
12,7
61,3
10
37
13,0
13,0
74,3
11
35
12,3
12,3
86,6
12
38
13,4
13,4
100,0
284
100,0
100,0
Accumulated
99
V. Exemplary Visualized data of one student's lesson
Figure 16: Male twelfth grader