| Young
Investigator Section Research article |
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THE EFFECT OF BODY BUILD AND BMI ON AEROBIC TEST PERFORMANCE
IN SCHOOL CHILDREN (10-15 YEARS)
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Department of Movement Sciences and Nutrition and Toxicology Institute Maastricht
(NUTRIM), Maastricht University, Maastricht, the Netherlands.
| Received |
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14 March 2006 |
| Accepted |
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06
September 2006 |
| Published |
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15
December 2006 |
©
Journal of Sports Science and Medicine (2006) 5, 699 - 706
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| ABSTRACT |
| Body
Mass Index (BMI) has often questionably been used to define body build.
In the present study body build was defined more specifically using
fat free mass index (FFMI = fat free mass normalised to the stature)
and fat mass index (FMI = fat mass normalised to stature). The body
build of an individual is 'solid' in individuals with a high FFMI
for their FMI and is 'slender' in individuals with a low FFMI relative
to their FMI. The aim of the present study was to investigate the
association between aerobic test performance and body build defined
as solid, average or slender in 10 to 15 year old children. Five-hundred-and-two
children (53% boys) aged 10 to 15 years of age were included in the
study. Aerobic test performance was estimated with an incremental
cycle ergometer protocol and a shuttle run test. BMI and percentage
fat (by skin folds) were determined to calculate FMI and FFMI. After
adjustment for differences in age, gender and body mass the solid
group achieved a significantly higher maximal power output (W) and
power output relative to body mass (W/kg) during the cycle test (p
< 0.05) and a higher shuttle-run score (p < 0.05) compared to
the slender group. The power output relative to FFM (W/kg FFM) was
comparable (p > 0.05) between different body build groups. This
study showed that body build is an important determinant of the aerobic
test performance. In contrast, there were no differences in aerobic
test performance per kilogramme FFM over the body build groups. This
suggests that the body build may be determined by genetic predisposition.
KEY
WORDS: Shuttle run test, cycle test, BMI, percentage fat, solid
body build, slender body build.
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| INTRODUCTION |
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Data from several recent studies indicate a progressive decrease
in physical activity and a parallel decrease in aerobic performance
in children and adolescents ( Brownson et al., 2005;
Hirasing et al., 2001;
Irving et al., 2003;
Rump et al., 2002).
Besides, the body fat content and the prevalence of obesity in children
has increased (Hirasing et al., 2001).
For this reason, the interest in studies aimed at the association
between aerobic capacity and body composition in children has increased
(Eisenmann, 2004).
Westerstahl (2003),
for example, who stated that the aerobic fitness in adolescents
was decreased in Sweden between 1974 and 1995 (Westerstahl et al.,
2003),
suggests that this change was partly due to the increased BMI. Goran
(2000)
specifies this statement by suggesting that the major influence
of body mass on VO2max is explained by the fat free mass
(FFM). Fatness and excess body mass do not necessarily imply a reduced
ability to maximally consume oxygen (Goran et al., 2000).
Hattori (1997)
also states that the amount of body fat does not influence the aerobic
capacity (Hattori, 1997).
In contrast, others suggest that body fat itself is associated with
VO2max. (Eliakim et al., 1997;
Mota et al., 2002;
Watanabe et al., 1994).
Overall, the results of these studies are inconsistent.
The methods which are generally accepted to express body composition
in both adults and children in these studies are the body-mass-
index (BMI) and the percentage fat. The BMI, however, is a crude
measure (Cole et al., 2000).
Although BMI is a general measure of body mass standardised for
stature, it fails to account for differences in the two main components
of body mass; fat mass (FM) and FFM. This implies that a high BMI
can be caused either by a high FM or by a high FFM. Besides BMI,
the percentage of fat is frequently used as an additional measure
for body composition. Hence, percentage of fat itself ignores subject
variation in FFM, thus individuals may differ in percentage fat
either by an identical fat-free mass but different FM, or by an
identical FM but different fat-free mass (Wells, 2001).
Thus, both BMI as well as percentage fat may yield a distorted representation
of body composition. To overcome this problem, the variables fat
free mass index (FFMI) and the fat mass index (FMI) have been introduced
(VanItallie et al., 1990;
Wells and Cole, 2002;
Freedman et al., 2005).
The FFMI is the FFM normalised to stature, whereas the FMI is the
FM normalised to stature (VanItallie et al., 1990).
In order to combine both measures, Hattori et al., 1997
combined FMI and FFMI in a statistical chart with the FFMI on the
x-axis and the FMI on the y-axis (Hattori, 1997).
In addition, previously we have transformed the chart in a regression
model in which the FFMI could be predicted from the FMI (Van Etten
et al., 1994).
Based on the proportion of the FFMI and FMI, the body build of the
individuals can be described as 'solid' in individuals with a high
FFMI for their FMI and 'slender' in individuals with a low FFMI
for their FMI (Van Etten et al., 1994).
The description of body build based on the combination of FFMI and
FMI is a more advanced and integrated way to describe the body build
than by only BMI and/or percentage fat. Although, there are some
more sophisticated measures to investigate body build, like Magnetic
Resonance Imaging (MRI) or Dual Energy X-ray Absorptiometry (DEXA),
it is not feasible to use these measures in large population based
studies.
Because studies on body build are lacking and because some type
of selection was introduced in most previous studies, in the present
study the impact of body build on aerobic test performance was investigated
in a representative cross sectional study population of school children.
The aim of this study was to investigate the association between
aerobic test performance measured by the maximal power output and
the shuttle-run test and body build defined as solid, average or
slender in 10 to 15 year old children. The absolute exercise capacity
and the capacity normalized for body mass and FFM were evaluated.
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| METHODS |
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Subjects
Five-hundred-and-two school children (268 boys and 234 girls) aged
between 10 and 15 years from primary and secondary schools in the
province of Limburg, the Netherlands were included in the study.
For the analyses the group was divided into six subgroups, based
on age (10-11, 12-13, 14-15) and sex. Data have been collected between
2001 and 2005. Data used for this study were collected within the
framework of the physical education classes. Within this framework
selection bias is reduced, because all children in a class participate.
All children and their parents were fully informed about the nature
and purpose of the study. They had the opportunity to inform the
investigator of relevant health problems. Both had, according to
the medical ethics committee legal procedures, the right to withdraw
from the study at any time.
Anthropometry
To calculate the BMI, stature and body mass (BM) were determined
bare footed in light clothes. Although there are more sophisticated
measures of percentage fat, the percentage fat was estimated from
the average sum of the four skin folds because this is valid in
a large sample (Weststrate and Deurenberg, 1989;
Vasudev et al., 2004).
Biceps, triceps, sub scapular and iliac crest skin fold thickness
were measured in triplicate. FM was calculated as percentage fat
x BW. FFM was calculated as '(1-fraction of FM) x BW'. FM and FFM
were normalised for stature by dividing them by squared stature,
to get FMI and the FFMI (Wells, 2001).
Plotting the FMI on the x-axis and the FFMI on the y-axis, subjects
with different body compositions could be distinguished (Freedman
et al., 2005;
Wells, 2001;
Wells and Cole, 2002).
A FFMI-FMI-chart was plotted for the six different age and sex groups,
and a regression line with one standard deviation was drawn (Figure
1), as has been shown previously by Van Etten et al (Van Etten
et al., 1994).
Subjects with a deviation of the regression line within one standard
deviation were considered to have an average body build. The subjects
beyond this prediction interval were assigned to either the slender
group (actual FFMI < predicted FFMI) or the solid group (actual
FFMI > predicted
FFMI) (Van Etten et al., 1994).
In brief, the subjects in the slender group had a relatively small
amount of FFM, whereas the solid subjects had a large amount of
FFM, compared to their FM and stature.
Aerobic
test performance
The aerobic test performance was estimated with an incremental cycle
protocol, in which the participants started with a 5 minute warm-up
at 50 W for girls and 75 W for boys (Ergoline, Ergometrics 800,
CE 0124). Heart rate was monitored by Polar heart rate monitors
(Polar S610). In primary school children the
work rate was increased by 25 W every 2.5 minute. When the heart
rate reached 180 beats per minute, the work rate was increased by
10 W every 2.5 minute, to be able to reach the maximal test performance
more precise. In secondary school children work rate was increased
by 50 W every 2.5 minute and by 25 W when heart rate reached 180
beats per minute. The pedal rate was 60-80 rpm. The result of the
cycle test is presented as the maximal achieved work load ('power
output').
Additionally, the school children participated in a maximal multistage
20-m shuttle run test (Leger et al., 1988).
Subjects were required to run back and forth on a 20-m course and
touch the 20-m line with their foot at the same time a beep was
emitted from a tape recorder. The Queen's University of Belfast
protocol was used in which the frequency of the sound signals increases
in such a way that running speed started at 8.0 km·h-1 and increased
by 0.5 km·h-1 every minute (Tomkinson et al., 2003).
The result of the test was expressed in number of stages, which
reflected the number of minutes the participants preceded the test.
In both the cycle as the shuttle run test the heart rate measurements
were used to evaluate whether the subjects performed maximally.
A peak heart rate of > 185 beats/minute considered as maximal
aerobic performance. Only the data of the subjects who performed
maximally were included in the study. During both test verbal encouragements
were used to stimulate the participants in performing maximally.
Both tests were separately completed, with at least one day in between.
Data
analysis
The results are shown as means and standard deviations. To test
differences between subjects with an average, solid or slender body
build, the total group was divided into six groups based on sex
and age categories (10-11, 12-13, 14-15 years of age). Subjects
were assigned to one of the defined groups for body build by comparison
with their own age and sex group. To test the differences in anthropometric
measures between children with a solid, average or slender body
build two-way analysis of variance (ANOVA) was used. Post hoc analyses
were executed with the Bonferoni test. To test the differences in
aerobic test performance analysis of covariance (ANCOVA) was used,
with body mass, age and gender as covariates. For statistical analysis
SPSS 11.0 was used. A p-value < 0.05 was considered statistically
significant.
|
| RESULTS |
|
In
total 502 school children participated in the study. The cycle ergometer
test was performed by 462 subjects whereas the shuttle-run test
was performed by 479 subjects. Non-participation in the exercise
tests was due to injuries or absence on the day of the test. Stature,
body mass and percentage fat were determined in all subjects.
Table 1 shows the anthropometric
data for different age groups, for boys and girls separately. An
increase in BMI (from 17.27 to 19.47 kg/m2 in boys and from 17.68
to 20.51 kg·m-2 in girls) and a decrease in percentage fat (from
17.18 to 15.59 % in boys and from 24.93 to 22.93 % in girls) has
been shown with an increase in age from 11 till 15 years of age.
Table 2 shows the results of
the cycle ergometer test and the shuttle run test for the different
age and sex categories.
The FFMI-FMI scatter plots for the six different age/sex groups
are shown in figure 1. This
figure also presents regression lines for the FFMI predicted from
the FMI and the BMI cut-off points for overweight and obesity. Based
on the deviation from the regression line the body build of the
subjects was classified as solid (n = 76), average (n = 348) or
slender (n = 78).
To evaluate the differences between the body build groups, well
known measures for body composition are depicted in Table
3 for the three groups of body build. Table
4 shows the differences in aerobic test performance in the incremental
cycle ergometer test and the shuttle run test for the different
groups of body build adjusted for age, gender and body mass.
As a result of the methods, the solid group had a higher FFM (p
< 0.05). ANCOVA controlling for age, gender and body mass also
revealed group differences (p < 0.05) in power output, power
output relative to body mass and shuttle run in favor of the solid
group. There were no significant differences between the groups
regarding the power output relative to FFM (p > 0.05).
|
| DISCUSSION |
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The
aim of the present study was to investigate the association between
aerobic test performance and body build measured by FFMI and FMI
in 11 to 15 year old school children. An important finding of this
study was that children with a solid body build, thus a high FFMI
compared to their FMI, scored significantly higher on the exercise
tests, even after controlling for age, gender and body mass. On
the contrary, the power output relative to FFM was comparable over
the groups.
Because complete school classes were examined in this study selection
bias was minimized and a valid representative cross-sectional sample
might be expected. When the BMI values found in this study were
compared to previous found Dutch data in a similar population an
increase was found (Hirasing et al., 2001).
This is, however, in line with previously posted assumptions that
the BMI in children is increasing (Gerver, 2001;
Hirasing et al., 2001).
In this study it was shown that the subjects with a solid body build,
who have a higher amount of FFM, achieved a higher aerobic test
performance as measured by a cycle ergometer test and the shuttle-run
test. The results suggest that in the solid group the FM appears
to be compensated by the amount of FFM. Although the total body
mass was also higher in the solid group compared to the slender
group, the differences in aerobic test performance can not be explained
by the differences in body mass because the analysis was corrected
for body mass. Therefore, the body build itself seem to be a predictor
for the aerobic capacity in adolescents independent of age, gender
and body mass.
In addition, the maximal achieved power output relative to FFM was
evaluated and there were no significant differences between the
groups based on body build. The total FFM can be considered as the
main functional mass which plays a key role during physical activity
(Goran et al., 2000).
The maximal power output relative to FFM is associated with the
physical exercise level. This is confirmed by a study of Nikolic
et. al. (1992)
with 15-year-old boys, where it was shown that the maximal aerobic
power expressed per kilogramme lean body mass was 20.6% higher in
the trained than in the untrained group (Nikolic and Ilic, 1992).
From the similar functional capacity of the FFM for subjects with
a solid, average or slender body build in our study, suggests a
similar physical exercise level in the groups. Previously, we have
found estimates for the level of sports participation for the different
groups of body build (unpublished data). The hypothesis of similar
physical exercise level is strengthened by the finding that the
sport participation of the solid, average and slender parts of the
previous study was comparable between the three groups. This may
indicate that the body build is independent of the physical exercise
level in this age category (11-15 years of age). When the body build
is not influenced by physical exercise, it might be determined by
genetic factors.
In this study, the generally recognized BMI cut-off points were
compared to the FFMI-FMI-charts with regression lines which distinguish
between solid, average or slender body build. Children who are overweight
based on their BMI can be classified in the solid, slender or average
group. The overweight group consisted of 56 children, in which 13
have a slender, 38 an average and 5 a solid body build. All these
children have a high BMI for their age and sex, while the solid
children have a relatively high FFM compared to their FM and stature,
whereas the slender children have a relatively low FFM (Van Etten
et al., 1994).
It is hypothesized that the slender overweight children are more
disadvantaged by their body mass in daily life compared to the solid
overweight children who have more FFM.
Unfortunately, the group of overweight adolescents was too small
to evaluate the impact of body build on aerobic test performance
in obesity children. It would be interesting to test this hypothesis
in a larger population of overweight children. Besides, an interesting
research question could also be whether health status in children
with a solid body build might even be better than the health status
in slender children.
There are some limitations in this study to be acknowledged. The
used measures have certain limitations. The percentage fat for example
could have been measured with a more laboratory based measurement
like hydro densitometry weighing, and the aerobic test performance
with direct oxygen measurements. However, considering the aim of
the study the prime aspect of the study design was to recruit a
large random sample of the population. This requires that complete
classes of the cooperating schools should be able to participate
in the study. Therefore, laboratory measurement of all interesting
physiological variables was not feasible. Another limitation is
that no information was collected about the maturation status of
the participants. Differences in the maturation status may partly
explain the differences in exercise performance between the body
build groups (Armstrong et al., 1998).
In conclusion, in this study it was shown that in the studied age
group the aerobic test performance is better in children with a
solid body build compared to children with a slender body build.
The power output relative to FFM is comparable over the three groups.
Because the capacity per FFM is associated with exercise training,
the results suggest that body build status is determined by genetics,
rather than by physical exercise at this age. In future research
it is relevant to investigate possible differences in aerobic test
performance between overweight children with a solid, average or
slender body build, and health differences between different body
build groups.
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| ACKNOWLEDGEMENT |
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We
would like to acknowledge Mirjam Jaarsma, Inge Jansen, Mandy Bruggink,
Richard Staats, and Danielle Cluijtmans for collecting the data
and the participating school children and teachers for providing
the data.
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| KEY
POINTS |
-
Children with a solid body build perform better in aerobic exercise
tests than slender children.
- The
power output relative to fat free mass was comparable in the solid,
slender and average group.
- Besides
body composition, body build should be considered related to other
performance measurements.
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| AUTHORS
BIOGRAPHY |
Jantine SLINGER
Employment: Maastricht University, Department of Movement
Sciences (NUTRIM).
Degree: MSc.
Research interests: Physical activity, physical fitness,
risk for type 2 diabetes and overweight in children and adolescents.
E-mail: jantine.slinger@bw.unimaas.nl |
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Frans
VERSTAPPEN
Employment: Maastricht University, Department of Movement
Sciences (NUTRIM).
Degree: MD, PhD.
Research interests: Effect of body build on weight training-induced
adaptations in body composition and muscular strength.
E-mail: ftj.verstappen@hetnet.nl
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Eric
Van BREDA
Employment: Registered medical physiologist. Maastricht
University, Department of Movement Sciences (NUTRIM).
Degree: PhD.
Research interests: Training, training physiology, training-
and activity programs for special groups (children, and diabetes
and cancer patients).
E-mail: eric.vanbreda@bw.unimaas.nl
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Harm
KUIPERS
Employment: Maastricht University, Department of Movement
Sciences (NUTRIM).
Degree: MD, PhD.
Research interests: Muscle use, disuse and overuse, metabolic
myopathies, endocrine aspects of exercise, ergogenic aids and
physical performance, energy metabolism and nutrition during
exercise, limits of physical performance, training and overtraining.
E-mail: Harm.kuipers@bw.unimaas.nl
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