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4
Health-Related Fitness Measures
for Youth: Body Composition
KEY MESSAGES
Body composition is a physiologic characteristic that affects an indi-
vidual's ability to carry out daily tasks with vigor. Although body com-
position is not a demonstrative action like other health-related fitness
components, the committee has operationally defined it as a component
of fitness, a health marker, and a modifier of fitness for the purposes
of this report. Both body weight (mass) and body fat (absolute fatness
and relative fat distribution) are elements of body composition that have
implications for health and fitness. It is important to measure weight and
height in national youth fitness surveys to derive body mass index (BMI),
an indicator of weight-for-height; waist circumference, an indicator of
abdominal adiposity; and skinfolds, an indicator of subcutaneous adipose
tissue. These three recommended field indicators of body composition
for a national youth fitness survey uniquely measure different elements,
and each can be linked to health markers and outcomes in both youth
and adults. For example,
· A high BMI is related to the risk of type 2 diabetes and hypertension.
· Waist circumference is linked to risk factors for cardiovascular dis-
ease, type 2 diabetes, and all-cause mortality.
· Elevated skinfold thicknesses and proportionally more subcutaneous
fat on the trunk are associated with an elevated risk for cardiovascu-
lar disease and metabolic syndrome.
79
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80 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
Only standing height and weight should be measured in school and
other educational settings to calculate BMI given such concerns as
measurement errors and privacy.
Two approaches to interpreting the results of the above three mea-
sures are recommended to determine whether individuals or popula-
tions are at risk of poor health outcomes. For BMI, the cut-points (cutoff
scores) based on the 2000 Centers for Disease Control and Prevention
(CDC) growth charts and percentiles should be applied for underweight,
overweight, and obesity evaluations. Interim cut-points for waist circum-
ference and skinfold measures should be set at levels analogous to
those currently being applied by the CDC for BMI. This approach should
be used until evidence becomes available to support establishing waist
circumference and skinfold cut-points by associating those measures
with cardiometabolic risk factors.
B
ody weight (mass) and body fat distribution are elements of body
composition that have implications for health and fitness. No element
on its own adequately and comprehensively describes an individual's
body composition, and each element has been linked with various health
markers and outcomes in youth.
Measures of body composition have been used in the past as a compo-
nent of fitness test batteries (see Table 2-6 in Chapter 2). The background
paper for the Second International Consensus Symposium on Physical
Activity, Fitness and Health in 1992 offered an outline of "components and
factors of health-related fitness" (Bouchard and Shephard, 1994; Bouchard
et al., 2007) in which body composition was included as a morphological
component of health-related fitness. In a review of existing fitness tests, 10
of 15 physical fitness test batteries for children and adolescents included
body composition as a component of health-related fitness (Artero et al.,
2011; Castro-Piñero et al., 2010), but the supporting evidence for their
inclusion was quite variable.
Body composition differs from the other fitness components reviewed
in this report at various levels. First, there are different perspectives on
whether body composition should be considered a component of fitness.
The committee considered body composition to be a physiologic character-
istic that affects an individual's ability to carry out daily tasks with vigor
and to be influenced by physical activity behavior. Second, body composi-
tion influences performance on many fitness tests and itself is also an indica-
tor of health. The committee thus defined body composition operationally
as a component of fitness, a marker of health, and a modifier of fitness,
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BODY COMPOSITION 81
for the purposes of this report. Finally, the relationships between body
composition, in particular percent body fat, and health outcomes are well
established in both youth and adults. Thus, the committee did not collect
evidence on the relationship between any body composition field measures
and health outcomes. The committee identified appropriate measures of
body composition by selecting field-based items that were valid, reliable,
and feasible for implementation in either a national survey or a school or
other educational setting.
This chapter provides an overview of the existing measures of body
composition and presents the committee's conclusions about the best mea-
sures of body composition based on their relationship to health in youth,
as well as their integrity and feasibility. The committee's full recommenda-
tions for measuring body composition in a national fitness survey and in
schools and other educational settings can be found in Chapters 8 and 9,
respectively.
MEASUREMENT OF BODY COMPOSITION
Body weight is a gross measure of the mass of the body. The partition-
ing and quantification of mass into its basic elements has been a major focus
of study historically and has accelerated with the refinement of models
(Wang et al., 1992, 2005) and the development of technology (Ackland et
al., 2012; Heymsfield et al., 2005; Roche et al., 1996). A variety of models
and methods--developed largely in adults--have been used to partition
body mass into several elements: fat-free mass, fat mass, total body water,
fat-free dry mass, and bone mineral. As assessment techniques have become
refined, models have evolved from those including the traditional two ele-
ments (body mass = fat-free mass + fat mass) to those including three, four,
or five elements (Wang et al., 1992, 2005), with fat mass--or adipose tissue
as it is labeled in anatomical models--being basic to all models.
Body composition can be approached at several levels: atomic, molecu-
lar, cellular, tissue, and whole body (Wang et al., 1992, 1995). The technol-
ogy for measuring specific elements of body mass at each level and factors
influencing body composition have been summarized (Heymsfield et al.,
2005; Roche et al., 1996). While no single criterion measure of body com-
position is universally accepted as the gold standard (Ackland et al., 2012),
laboratory measures (e.g., underwater weight, body potassium, total body
water, and dual-energy X-ray absorptiometry [DXA]) are considered the
most accurate techniques. DXA provides measures of bone mineral and
of fat and lean tissues. The other three laboratory measures have major
limitations. Underwater weighing is used to estimate body density, which
is then converted to percentage body fat; total body potassium and total
body water provide measures of fat-free mass. Quite often, the laboratory
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82 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
measures are used together (especially underwater weighing, total body
water, and a measure of bone mineral) to provide an estimate of body
composition, depending on the model selected (see, e.g., Gutin et al., 1996).
Several additional laboratory techniques, as well as field measurements
available for estimating body composition in youth in various settings (e.g.,
research, education/practice, clinical), have been reviewed extensively by
others (Heymsfield et al., 2005; Roche et al., 1996).
Critical evaluation of body composition methodology at each level
of analysis (Wang et al., 1992, 1995) is beyond the scope of this report.
Further, while laboratory methods--such as DXA, hydrostatic weighing,
ultrasound, densitometry, and air displacement plethysmography (e.g., Bod
Pod®)--have many advantages (such as more specific measurements and
reduced measurement variation, measurement of the whole body, minimal
subject burden, and relative ease of administration), they typically require
highly specific training and special and expensive equipment. Some of the
equipment also lacks the mobility that may be necessary to access large
samples of youth.
Overall, the measurement of body composition is dependent on the
question being addressed, the information necessary, and the applica-
tion of the assessment protocols (Ackland et al., 2012). For example,
techniques used for collecting data to track the health status of a given
population epidemiologically will likely differ from those used to collect
data to achieve advances in sports performance. Also, many laboratory
methods are not feasible for use in the field because of limitations cited
earlier. Direct evaluation of body composition (i.e., DXA measure of
adiposity) is not the same as indirect and associated proximity measures
of body composition. Body mass index (BMI) is used for classification of
weight status (underweight, normal, overweight, obese), although it does
not accurately predict percent body fat (Moreno et al., 2006). Accordingly,
the selection of body composition measures depends on what element is
of interest, which in turn depends on the question(s) being asked. Given
the desirability of a comprehensive understanding of an individual's body
composition, as well as considerations of feasibility in practice settings
such as schools, the committee focused its review on low-cost field-based
measures of body composition.
Laboratory measures, such as DXA, may be appropriate for some
national surveys, like the National Health and Nutrition Examination
Survey (NHANES), for which the equipment is transported in a trailer
and only a small sample of youth is studied. For large national surveys in
which youth are tested nationwide in a school setting, however, field-based
measures are more suitable than laboratory measures. Field-based measures
include anthropometry (skinfolds, weight, height [weight-for-height in the
form of BMI], waist circumference) and bioelectric impedance analysis
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BODY COMPOSITION 83
(BIA). These measures were selected based on their relationship to health
markers, their integrity and reliability, and their previous use.
· Skinfolds provide an indication of subcutaneous fat at specifically
defined measurement sites. Skinfolds can also be used to predict
percent body fat. They can be expressed as a sum of skinfolds
(overall subcutaneous fat) and as a ratio of trunk to extremity
skinfolds (relative subcutaneous fat distribution).
· BMI (kg/m2) is an indicator of weight-for-height. It is used inter-
nationally in public health and nutrition surveys to monitor weight
status, specifically overweight and obesity. At the extremes of
heaviness, BMI is probably a reasonable indicator of fatness in the
general population.
· Waist circumference increasingly is used as an indicator of central
or abdominal adiposity rather than percent body fat, which can
vary greatly among individuals with a similar BMI. Located in the
abdominal region, abdominal fat is composed of three elements:
visceral, retroperitoneal, and subcutaneous.
· BIA provides a measure of resistance or impedance; some BIA
systems are calibrated directly to fat-free mass (or fat). Some other
systems provide a measure of total body water that is then trans-
formed to an estimate of fat-free mass. The equation for converting
resistance to total body weight usually includes height. Algorithms
used in estimating body composition with BIA with commercially
available units are considered proprietary information, which is
a major shortcoming. Moreover, it has been suggested that equa-
tions provided by manufacturers may not be suitable for estimating
body composition in youth of different racial/ethnic backgrounds
(Haroun et al., 2010). Given its shortcomings and the abundant
evidence on the effectiveness of other field-based measures, the
committee did not explore BIA further. However, if shortcomings
due to proprietary equations were resolved and the algorithms
accounted for changes in the composition of fat-free mass dur-
ing childhood and adolescence, for sex differences, and for racial/
ethnic variations in body composition, BIA might be considered a
useful measure of body composition in youth, particularly given its
ease of administration.
LITERATURE REVIEW PROCESS
As noted earlier, the fact that body composition is a measure of health
is well established. Also well established is that percent body fat is related
to health outcomes and that there are various tests with which to measure
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84 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
percent body fat, subcutaneous fat, or abdominal adiposity. Therefore, the
Centers for Disease Control and Prevention's (CDC's) literature review,
described in Chapter 3, did not include body composition as a fitness com-
ponent; the CDC review, however, included articles in which body compo-
sition appeared as a modifier of fitness or as a health marker or both. For
this reason, the committee considered each such article for inclusion in its
review, and this chapter includes findings from selected studies from the
CDC review, as well as others, in which body composition was considered
as a fitness component, a health marker, or a modifier of physical fitness. A
body of literature from obesogenic intervention research was also reviewed.
In addition, the committee reviewed validity and reliability data specific
to field tests that measure various aspects of body composition. Further,
articles on specific topics related to body composition (e.g., growth and
maturation, race/ethnicity, and body composition and health) were identi-
fied and chosen for inclusion in this chapter.
BODY COMPOSITION IN YOUTH
In addition to age, energy intake, and other factors, individual differ-
ences in biological maturation, gender, and race/ethnicity affect elements
of body composition such as fat mass and fat-free mass, subcutaneous fat,
and fat distribution. The following discussion is based on trends described
in Malina (1996, 2005) and Malina et al. (2004).
Variation in Body Composition with Age, Gender, and Maturation Status
Fat-free mass, fatness, and relative fat distribution in late childhood
and adolescence (approximate school ages) vary with age, between genders,
and among individuals of contrasting maturation status. Age- and gender-
related changes are discussed in the subsections that follow. Variation
associated with maturation status is then briefly considered.
Fat-Free Mass
The principles underlying several methods for estimating body compo-
sition warrant special consideration when applied to growing and matur-
ing youth. It is important to determine when mature (adult) levels of the
primary elements of fat-free mass are reached. This relates to the concept
of chemical maturity, defined by Moulton (1923, p. 80): "The point at
which the concentration of water, proteins, and salts [minerals] becomes
comparatively constant in the fat-free cell is named the point of chemical
maturity of the cell." Chemical maturity of fat-free mass is not attained
until after the adolescent growth spurt, probably about ages 16-18 in girls
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BODY COMPOSITION 85
and 18-20 in boys (Lohman, 1981, 1986; Malina, 2005; Wells et al., 2010).
When adult values of its primary components are reached, fat-free mass is
chemically mature.
On average, fat-free mass has a growth pattern like that of stature
and body mass. Differences over time until chemical maturity is reached
reflect a larger fat-free mass, specifically bone mineral content and skeletal
muscle mass in males. That is, the relative contribution of water to body
mass decreases while the relative contributions of solids--protein, mineral,
and fat--increase during approximately the first two decades of life, which
are dominated by the biological activities of growth and maturation. Sex
differences are apparent during the adolescent growth spurt. On average,
fat-free mass in males contains relatively less water and more protein and
mineral compared with that in females from childhood into young adult-
hood (Malina et al., 2004). Density of fat-free mass is also greater in males,
which reflects primarily sex differences in skeletal muscle mass and bone
mineral. These are only average trends, and it should be noted that there
are variations among individuals and with biological maturation (status
and timing).
Although efforts continue to derive more accurate estimates of the
chemical composition of fat-free mass, three points should be noted: (1)
the composition of fat-free mass changes during growth and maturation,
(2) variation among individuals is considerable, and (3) chemical maturity
is not attained until late adolescence or young adulthood. Ideally, equa-
tions and constants used to estimate body composition should be adjusted
for the chemical immaturity of the fat-free mass in growing and maturing
individuals.
Fat Mass
Fat mass increases more rapidly in girls than in boys during childhood
and continues to increase through adolescence in girls (Malina, 2000). Fat
mass appears to reach a plateau, or to change only slightly, near the time
of the adolescent spurt in boys (around age 13-15) (Malina, 2000). Fat
mass as a percentage of body mass (percent body fat) increases gradually
during childhood, and sex differences are small. Percent body fat increases
through adolescence in girls; it increases into early adolescence in boys and
then declines. The decline during male adolescence is a function of the ado-
lescent spurt in fat-free mass, more specifically muscle mass. Sex differences
in body composition are negligible in childhood, and are established dur-
ing the adolescent spurt and sexual maturation (Malina, 2000). Although
estimated fat mass is similar in male and female adolescents, females have
greater percent body fat.
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86 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
Weight-for-Height
BMI, as a measure of weight-for-height, declines from infancy through
early childhood and reaches its lowest point at about age 5-6. It then
increases linearly with age through childhood and adolescence and into
adulthood. Sex differences in BMI are small during childhood, rise dur-
ing adolescence, and persist into adulthood (Malina et al., 2004). The rise
in BMI after it reaches a nadir at age 5-6 has been labeled the "adiposity
rebound" (Rolland-Cachera et al., 1984). It has been suggested that indi-
viduals who have an early adiposity rebound have an increased probability
of being overweight in late adolescence and young adulthood (Rolland-
Cachera et al., 1984). The concept of adiposity rebound needs further
study. In the context of body composition, there is a need to document
specific changes in body composition during the rebound. Does it reflect an
increase in fat mass or an increase in fat-free mass? Some evidence suggests
the latter (Katzmarzyk et al., 2012).
Subcutaneous Fat
A skinfold thickness is a double fold of skin and underlying soft tis-
sues, primarily adipose tissue. Two commonly used skinfolds are the triceps
and subscapular. The former increases with age from childhood through
adolescence in females, whereas it decreases during the adolescent spurt in
males (Malina, 2000). On the other hand, the latter increases from child-
hood through adolescence in both sexes. As a result, the adolescent sex
difference in the triceps skinfold is marked compared with the relatively
small difference in the subscapular skinfold.
Any number of skinfolds can be and have been measured. Changes in
individual skinfolds are variable during growth and specifically relative to
the timing of peak height velocity, more so in boys than in girls (Malina et
al., 1999). Such variation may influence age-associated trends.
Relative Fat Distribution
Fat distribution refers to regional variation in the accumulation of
adipose tissue in the body. With advances in technology (computed tomog-
raphy [CT] scans, magnetic resonance imaging [MRI]), attention shifted
to abdominal fatness, specifically visceral versus subcutaneous. With wide-
spread availability of DXA, trunk and extremity distribution of adipose
tissue also has received more attention (Malina, 1996, 2005). Ratios of
skinfolds measured on the trunk to those measured on the extremities are
commonly used to estimate relative subcutaneous fat distribution. Ratios
of trunk to extremity skinfold thicknesses increase gradually through child-
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BODY COMPOSITION 87
hood in both sexes, and there is no sex difference in the ratios. Subse-
quently, ratios tend to be rather stable in females but to increase in males
through adolescence. Males accumulate proportionally more subcutaneous
fat on the trunk than the extremities, while females accumulate relatively
similar amounts on both the trunk and extremities (Malina, 1996; Malina
and Bouchard, 1988). Ratios of trunk to extremity adiposity based on
DXA show similar trends (He et al., 2004; Taylor et al., 2010). Ratios of
abdominal visceral and subcutaneous adiposity show small differences with
age and sex from childhood into early adolescence in normal-weight youth,
but males have proportionally more visceral adiposity in later adolescence.
A similar trend associated with age and sex is not clearly apparent in over-
weight/obese youth (Katzmarzyk et al., 2012).
Maturity-Associated Variation
Children and adolescents advanced in maturity status compared with
their chronological-age peers tend to be fatter and to have proportionally
more subcutaneous fat on the trunk (Malina and Bouchard, 1988; Malina
et al., 2004). The maturity-associated trend also continues into young
adulthood (Beunen et al., 1994a; Kindblom et al., 2006; Labayen et al.,
2009; Sandhu et al., 2006). Samples in studies using DXA, CT scans, and
MRI generally involve several age groups, so that it is difficult to clearly
specify maturity differences in each gender. Stage of puberty (clinically
and/or self-assessed) is often described, but not systematically analyzed.
When it is described, youth typically are grouped by pubertal stage or
stages so that several ages are represented within a group (Katzmarzyk
et al., 2012).
Variation in Body Composition with Race/Ethnicity
The pattern of gender- and maturity-related differences is similar in all
racial/ethnic groups. African Americans have greater total bone mineral
content during childhood, adolescence, and adulthood than whites. Com-
parisons between Mexican Americans and whites show small differences in
fat-free mass and bone mineral content, although Mexican Americans tend
to have greater adiposity. Data for skinfolds indicate proportionally more
subcutaneous adipose tissue on the trunk in African Americans, Mexican
Americans, and Asian Americans compared with whites. In contrast, data
on the distribution of visceral and subcutaneous adiposity overlap among
ethnic groups. Unfortunately, the available data often combine multiple age
groups and in some instances combine males and females and/or youth of
different ethnic groups (Katzmarzyk et al., 2012; Malina, 2005).
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88 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
BODY COMPOSITION, FITNESS, AND HEALTH IN YOUTH
This section considers body composition as both a modifier of physical
fitness and a health marker.
Body Composition as a Modifier of Physical Fitness
Body composition is one of many factors that influence performance
on laboratory- and field-based tests of physical fitness. Fat-free mass and
its major tissue component, skeletal muscle mass (force-generating tissue of
the body), obviously are important to performance on many tests. Absolute
fat-free mass is significant in tests requiring the projection of objects (e.g.,
overhead medicine ball throw) and a variety of strength tests. Fat-free mass
also is highly correlated with height in children and adolescents. Fat mass
and percent body fat are more variable, but excess fatness (absolute and
relative) tends to exert a negative influence on performances on fitness tests
that require movement or projection of the body through space (i.e., runs
and jumps) as opposed to projection of objects, as well as on endurance
tests on cycle ergometers (Boileau and Lohman, 1977; Houtkooper and
Going, 1994; Malina, 1975, 1992).
Two studies of national samples of Belgian youth considered relation-
ships between the sum of skinfolds (four in boys, five in girls) and a variety
of fitness tests (Beunen et al., 1983; Malina et al., 1995). Among males aged
12-20, partial correlations (controlling for height and body mass) and sev-
eral relevant fitness test items (static arm pull strength, sit-and-reach, vertical
jump, left lifts, flexed arm hang, agility) were negative and low to moderate,
0.13 to 0.40. Corresponding partial correlations in girls aged 7-17 ranged
from 0.08 to 0.42 (Physical Working Capacity-170 [PWC-170], step test
recovery, arm pull strength, sit-and-reach, sit-ups, leg lifts, flexed arm hang,
standing long jump, vertical jump agility). Comparison of the fattest and
leanest 5 percent of participants highlighted the negative influence of exces-
sive subcutaneous fatness for all fitness test items except sit-and-reach, arm
pull strength, and PWC-170. Differences in flexibility were negligible. The
fattest were absolutely stronger (boys and girls) and generated more watts
(girls only), reflecting their larger body size. The fattest youth of both sexes
also were advanced in skeletal maturation compared with their leanest peers
of the same age groups (Beunen et al., 1982, 1994b).
Trends were generally similar in more recent samples of normal-weight
and obese youth. For example, sum of skinfolds was inversely related to
schoolchildren's performance on the progressive aerobic cardiovascular
endurance run (PACER), push-up, and curl-up tests (r = 0.30 to 0.49)
(Lloyd et al., 2003). Low levels of cardiorespiratory endurance were asso-
ciated with percent body fat in African American and white adolescents
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BODY COMPOSITION 89
(Gutin et al., 2005); with visceral and subcutaneous abdominal fat and
waist circumference in African American and white youth aged 8-17, con-
trolling for age, sex, pubertal status, and BMI (Lee and Arslanian, 2007);
with percent body fat, percent abdominal fat, and waist circumference in
8-year-old boys and girls (Stigman et al., 2009); and with BMI, skinfolds,
and predicted percent body fat in obese children of both sexes aged 6-13
(Nassis et al., 2005).
Studies evaluating the relationship between BMI and fitness tests gener-
ally have focused on the negative influence of obesity (Chatrath et al., 2002;
Deforche et al., 2003; Kim et al., 2005; Mota et al., 2006; Stratton et al.,
2007) or BMI as a covariate of aerobic fitness (Beets and Pitetti, 2004; Beets
et al., 2005). Youth aged 5-14 classified as "underfit" (based on pass-fail
scores on five fitness tests) were at greater risk of obesity (Kim et al., 2005).
Correlations between BMI and indicators of fitness tended to be linear in
well- and undernourished children aged 6-14 (Malina et al., 1998), but
were curvilinear in youth aged 12-15 (Bovet et al., 2007) and young adults
(Sekulic et al., 2005; Welon et al., 1988). A recent study with a representa-
tive sample of Brazilian youth showed that, after adjusting for potential
confounding factors, weight and BMI were negatively correlated with per-
formance on the long jump, curl-up, pull-up, 9-minute run, 20-meter run,
and 4-meter shuttle run (Dumith et al., 2012).
Data on variations in fitness across the broad spectrum of BMI within
relatively narrow age groups are limited. Relationships between BMI and
fitness varied among fitness test items in four age groups--9-10, 11-12,
13-15, and 16-18--in a national sample of Taiwanese youth (Huang and
Malina, 2010). Correlations were low to moderate and did not vary among
age groups or between sexes. They were highest for a distance run/walk
(800/1,600 meters, 0.17 to 0.34) and lowest for the sit-and-reach (0.04 to
0.12). For sit-ups and the standing long jump, however, correlations were
higher for boys than for girls (r = 0.15 to 0.23 versus 0.10 to 0.14 and 0.22
to 0.27 versus 0.12 to 0.17, respectively). In a national sample of Taiwanese
youth (Huang and Malina, 2010), sex-specific regressions of fitness items
on BMI, using a nonlinear quadratic model, indicated differential effects
for individual tests, which varied with age and sex. Relationships for the
sit-and-reach were similar and slightly curvilinear in girls aged 9-10 and
boys aged 9-12, but were parabolic among girls aged 11-18 and boys
aged 13-18. Peaks of the parabola were sharper in adolescent boys than
in adolescent girls. Youth of both sexes aged 1318 with either higher or
especially lower BMIs had the poorest flexibility. Relationships for sit-ups
were similar in girls and boys aged 9-12. Above ~20 kg/m2 in girls and
~18 kg/m2 in boys, sit-ups declined with increasing BMI. The decline was
initially slight but accelerated with increasing BMI, more so in girls. The
relationship between BMI and performance on sit-ups was parabolic in
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100 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
weight for the derivation of BMI, (2) waist circumference, and (3) triceps
and subscapular skinfold thicknesses. Height also serves as an indicator of
linear growth status. (See Annex 4-1 for common examples of measurement
techniques.)
The committee concluded that the above three measures of body com-
position are important to collect in a national youth fitness survey for sev-
eral reasons. First, each measure is a proximal estimation of body fat and
has increased standard of error of over laboratory measures. Also, there is
consensus that the measurement of body composition is multidimensional
(Bouchard et al., 1994). Second, no single measure is considered the gold
standard and representative of all body composition tenets for children
of all morphologies: BMI is a marker of obesity, waist circumference is a
marker of abdominal adiposity, and skinfold thicknesses are a measure of
subcutaneous fat. The measures recommended have acceptable validity and
reliability.
To interpret the findings of body composition testing and determine
whether individuals or populations are at risk of negative health out-
comes, the committee recommends employing two approaches. For BMI,
the CDC's current established cut-points for underweight, overweight, and
obesity should be applied. Interim cut-points for the waist circumference
and skinfold measures should be set at levels that are analogous to those
currently being applied by the CDC for BMI. This approach should be
used until the necessary evidence becomes available to support establishing
waist circumference and skinfold cut-points by associating those measures
with cardiometabolic risk factors. The committee's full recommendation for
including body composition in a national youth fitness survey is presented
in Chapter 8.
When body composition is measured in schools and other educational
settings, important concerns arise related to the measurement of waist cir-
cumference and skinfolds. Therefore, the committee recommends that only
BMI be used in these settings. A full description of considerations and the
committee's recommendation for schools and other educational settings is
included in Chapter 9.
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BODY COMPOSITION 101
ANNEX 4-1
MEASUREMENT OF BODY COMPOSITION
QUALITY CONTROL AND TECHNIQUES
Body composition measurements should be taken by trained individuals
using established techniques. Error--the discrepancy between a measured
value and its true quantity--is inherent in anthropometry. It can be ran-
dom3 or systematic.4
Replicate measurements of the same subject are used to estimate vari-
ability or error. Replicates on the same individual are taken independently
by the same technician after a period of time has elapsed (intraobserver)
or are taken on the same individual by two different technicians (interob-
server). Replicate measurements provide an estimate of imprecision. The
technical error of measurement is a widely used measure of replicability
(Malina et al., 1973; Mueller and Martorell, 1988). Technical errors are
reported in the units of the specific measurement. Intra- and interobserver
technical errors for a variety of dimensions in national surveys and several
more local studies are summarized by Malina (1995).
Accuracy is another aspect of the measurement process. It refers to
how closely measurements taken by one or several technicians approximate
the "true" measurement. Accuracy ordinarily is assessed by comparing
measurements taken by technicians with those obtained by a well-trained
or "criterion" anthropometrist (the reference). Note, however, that well-
trained, expert anthropometrists do make errors.
The height, weight, waist circumference, and triceps and subscapular
skinfold measurement techniques described below are provided as examples
from the commonly used NHANES Anthropometry Procedures Manual.5
Stature and Weight
Stature, or standing height, is the linear distance from the floor or
standing surface to the top (vertex) of the skull. It is measured to the near-
est millimeter with the subject in standard erect posture, without shoes.
3Random error is associated with variation within and among individuals in measure-
ment technique, problems with the measuring instruments (e.g., variation in or even lack of
calibration or random variation in manufacture), and errors in recording. Random error is
nondirectional, i.e., above or below the true dimension. Random errors tend to cancel each
other out in large-scale surveys and ordinarily are not a major concern.
4Systematic error results from the tendency of a technician or a measuring instrument to
consistently under- or overmeasure a dimension. Such error is directional and introduces
bias. Measurement variability also is associated with the individual (e.g., normal variation in
physiology, temperament, cooperativeness, and stranger anxiety).
5Available at http://www.cdc.gov/nchs/data/nhanes/nhanes_07_08/manual_an.pdf (accessed
May 10, 2012).
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102 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
Body weight is a measure of body mass. It is measured to the nearest 100
grams (depending on the type of scale) with the individual attired in ordi-
nary, light, indoor clothing without shoes (e.g., gym shorts and a t-shirt). It
assumed that the scales would be calibrated regularly for a national survey.
Height and weight are used to derive body mass index (BMI) (kg/m2).
Waist Circumference
The protocol for waist circumference calls for measuring just above the
uppermost lateral border of the right illium after normal expiration. The
level should be marked on the skin. When the tape is applied, it should
make contact with the skin without indenting it. The measurement should
not be made over clothing. Two individuals may be needed, especially for
some overweight and obese individuals.
Skinfolds
A skinfold thickness is a double fold of skin and underlying soft tissue
at a specific site. Skinfolds are measured to the nearest 0.5 mm (some cali-
pers measure to the nearest millimeter, while others measure to the nearest
0.2 mm). Three measurements usually are taken for each skinfold (some
protocols recommend two).
Triceps skinfold is measured on the back of the arm (over the triceps
muscle) at the level midway between the lateral border of the acromial
process of the scapula (acromion) and the inferior border of the olecranon
process of the ulna. With the arm flexed to 90 degrees at the elbow, the
acromion is marked. A measuring tape is placed on the acromion (zero
marker) and run down the lateral side of the upper arm. The distance mid-
way between the acromion and the olecranon is marked and extended to
the back of the arm. The skinfold is measured with the arm hanging relaxed
(loosely) at the side by grasping a vertical fold about 1 cm above the mark,
with the caliper being placed at the level of the mark.
Subscapular skinfold is measured 1 cm below the tip (inferior angle)
of the scapula. The measurement site should be marked on the skin. The
skinfold should follow the natural anatomical (cleavage) lines of the skin.
It is not a vertical fold like that taken over the triceps.
REFERENCES
Ackland, T. R., T. G. Lohman, J. Sundgot-Borgen, R. J. Maughan, N. L. Meyer, A. D. Stewart,
and W. Muller. 2012. Current status of body composition assessment in sport review and
position statement on behalf of the ad hoc research working group on body composition
health and performance, under the auspices of the I.O.C. Medical Commission. Sports
Medicine 42(3):227-249.
OCR for page 103
BODY COMPOSITION 103
Addo, O. Y., and J. H. Himes. 2010. Reference curves for triceps and subscapular skinfold
thicknesses in US children and adolescents. American Journal of Clinical Nutrition
91(3):635-642.
Andersen, L. B., L. B. Sardinha, K. Froberg, C. J. Riddoch, A. S. Page, and S. A. Anderssen.
2008. Fitness, fatness and clustering of cardiovascular risk factors in children from Den-
mark, Estonia and Portugal: The European Youth Heart Study. International Journal of
Pediatric Obesity 3(Suppl. 1):58-66.
Artero, E. G., V. España-Romero, J. Castro-Piñero, F. B. Ortega, J. Suni, M. J. Castillo-Garzon,
and J. R. Ruiz. 2011. Reliability of field-based fitness tests in youth. International Journal
of Sports Medicine 32(3):159-169.
Barlow, S. E., and W. H. Dietz. 1998. Obesity evaluation and treatment: Expert Commit-
tee recommendations. The Maternal and Child Health Bureau, Health Resources and
Services Administration and the Department of Health and Human Services. Pediatrics
102(3):E29.
Barlow, S. E., and Expert Committee. 2007. Expert Committee recommendations regarding
the prevention, assessment, and treatment of child and adolescent overweight and obe-
sity: Summary report. Pediatrics 120(Suppl. 4):S164-S192.
Bassali, R., J. L. Waller, B. Gower, J. Allison, and C. L. Davis. 2010. Utility of waist circumfer-
ence percentile for risk evaluation in obese children. International Journal of Pediatric
Obesity 5(1):97-101.
Beets, M. W., and K. H. Pitetti. 2004. One-mile run/walk and body mass index of an ethni-
cally diverse sample of youth. Medicine and Science in Sports and Exercise 36(10):
1796-1803.
Beets, M. W., K. H. Pitetti, and B. J. Cardinal. 2005. Progressive aerobic cardiovascular endur-
ance run and body mass index among an ethnically diverse sample of 10-15-year-olds.
Research Quarterly for Exercise and Sport 76(4):389-397.
Beunen, G., R. M. Malina, M. Ostyn, R. Renson, J. Simons, and D. Van Gerven. 1982. Fatness
and skeletal maturity of Belgian boys 12 through 17 years of age. American Journal of
Physical Anthropology 59(4):387-392.
Beunen, G., R. M. Malina, M. Ostyn, R. Renson, J. Simons, and D. Van Gerven. 1983. Fat-
ness, growth and motor fitness of Belgian boys 12 through 20 years of age. Human
Biology 55(3):599-613.
Beunen, G., R. M. Malina, J. Lefevre, A. L. Claessens, R. Renson, J. Simons, H. Maes, B.
Vanreusel, and R. Lysens. 1994a. Size, fatness and relative fat distribution of males of
contrasting maturity status during adolescence and as adults. International Journal of
Obesity and Related Metabolic Disorders 18(10):670-678.
Beunen, G. P., R. M. Malina, J. A. Lefevre, A. L. Claessens, R. Renson, and B. Vanreusel.
1994b. Adiposity and biological maturity in girls 6-16 years of age. International Journal
of Obesity and Related Metabolic Disorders 18(8):542-546.
Boileau, R. A., and T. G. Lohman. 1977. Measurement of human physique and its effect on
physical performance. Orthopedic Clinics of North America 8(3):563-581.
Boileau, R. A., T. G. Lohman, M. H. Slaughter, T. E. Ball, S. B. Going, and M. K. Hendrix.
1984. Hydration of the fat-free body in children during maturation. Human Biology
56(4):651-666.
Bouchard, C., and R. J. Shephard. 1994. Physical activity, fitness and health: The model and
key concepts. In Physical activity, fitness and health: International proceedings and con-
sensus statement, edited by C. Bouchard, R. J. Shephard, and T. Stephens. Champaign,
IL: Human Kinetics Publishers. Pp. 11-22.
Bouchard, C., S. N. Blair, and W. L. Haskell. 2007. Why study physical activity and health?
In Physical activity and health, edited by C. Bouchard, S. N. Blair, and W. L. Haskell.
Champaign, IL: Human Kinetics Publishers. Pp. 3-19.
OCR for page 104
104 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
Bovet, P., R. Auguste, and H. Burdette. 2007. Strong inverse association between physical
fitness and overweight in adolescents: A large school-based survey. International Journal
of Behavioral Nutrition and Physical Activity 4:24-31.
Carnethon, M. R., M. Gulati, and P. Greenland. 2005. Prevalence and cardiovascular disease
correlates of low cardiorespiratory fitness in adolescents and adults. Journal of the Ameri-
can Medical Association 294(23):2981-2988.
Castro-Piñero, J., E. G. Artero, V. España-Romero, F. B. Ortega, M. Sjostrom, J. Suni, and
J. R. Ruiz. 2010. Criterion-related validity of field-based fitness tests in youth: A system-
atic review. British Journal of Sports Medicine 44(13):934-943.
Chang, C., W. Liu, X. Zhao, S. Li, and C. Yu. 2008. Effect of supervised exercise intervention
on metabolic risk factors and physical fitness in Chinese obese children in early puberty.
Obesity Reviews 9(Suppl. 1):135-141.
Chatrath, R., R. Shenoy, M. Serratto, and D. G. Thoele. 2002. Physical fitness of urban
American children. Pediatric Cardiology 23(6):608-612.
Cole, T. J., M. C. Bellizzi, K. M. Flegal, and W. H. Dietz. 2000. Establishing a standard defini-
tion for child overweight and obesity worldwide: International survey. British Medical
Journal 320(7244):1240-1243.
Daniels, S. R., P. R. Khoury, and J. A. Morrison. 1997. The utility of body mass index as a
measure of body fatness in children and adolescents: Differences by race and gender.
Pediatrics 99(6):804-807.
Daniels, S. R., J. A. Morrison, D. L. Sprecher, P. Khoury, and T. R. Kimball. 1999. Associa-
tion of body fat distribution and cardiovascular risk factors in children and adolescents.
Circulation 99(4):541-545.
Deforche, B., J. Lefevre, I. De Bourdeaudhuij, A. P. Hills, W. Duquet, and J. Bouckaert. 2003.
Physical fitness and physical activity in obese and nonobese Flemish youth. Obesity
Research 11(3):434-441.
Despres, J. P., A. Nadeau, A. Tremblay, M. Ferland, S. Moorjani, P. J. Lupien, G. Theriault, S.
Pinault, and C. Bouchard. 1989. Role of deep abdominal fat in the association between
regional adipose tissue distribution and glucose tolerance in obese women. Diabetes
38(3):304-309.
Dumith, S. C., D. Van Dusen, and H. W. Kohl. 2012. Physical fitness measures among children
and adolescents: Are they all necessary? Journal of Sports Medicine and Physical Fitness
52(2):181-189.
Freedman, D. S., W. H. Dietz, S. R. Srinivasan, and G. S. Berenson. 1999a. The relation of
overweight to cardiovascular risk factors among children and adolescents: The Bogalusa
Heart Study. Pediatrics 103(6):1175-1182.
Freedman, D. S., M. K. Serdula, S. R. Srinivasan, and G. S. Berenson. 1999b. Relation of
circumferences and skinfold thicknesses to lipid and insulin concentrations in children
and adolescents: The Bogalusa Heart Study. American Journal of Clinical Nutrition
69(2):308-317.
Freedman, D. S., L. K. Khan, W. H. Dietz, S. R. Srinivasan, and G. S. Berenson. 2001. Rela-
tionship of childhood obesity to coronary heart disease risk factors in adulthood: The
Bogalusa Heart Study. Pediatrics 108(3):712-718.
Freedman, D. S., W. H. Dietz, S. R. Srinivasan, and G. S. Berenson. 2009. Risk factors and
adult body mass index among overweight children: The Bogalusa Heart Study. Pediatrics
123(3):750-757.
Freedman, D. S., A. Goodman, O. A. Contreras, P. DasMahapatra, S. R. Srinivasan, and
G. S. Berenson. 2012. Secular trends in BMI and blood pressure among children and
adolescents: The Bogalusa Heart Study. Pediatrics 130(1):e159-e166.
Going, S. B., T. G. Lohman, E. C. Cussler, D. P. Williams, J. A. Morrison, and P. S. Horn.
2011. Percent body fat and chronic disease risk factors in U.S. children and youth.
American Journal of Preventive Medicine 41(4, Suppl. 2):S77-S86.
OCR for page 105
BODY COMPOSITION 105
Goran, M. I., and B. A. Gower. 1998. Abdominal obesity and cardiovascular risk in children.
Coronary Artery Disease 9(8):483-487.
Goran, M. I., D. B. Allison, and E. T. Poehlman. 1995. Issues relating to normalization of
body-fat content in men and women. International Journal of Obesity 19(9):638-643.
Guo, S. S., W. Wu, W. C. Chumlea, and A. F. Roche. 2002. Predicting overweight and obesity
in adulthood from body mass index values in childhood and adolescence. American
Journal of Clinical Nutrition 76(3):653-658.
Gutin, B., M. Litaker, S. Islam, T. Manos, C. Smith, and F. Treiber. 1996. Body-composition
measurement in 9-11-y-old children by dual-energy x-ray absorptiometry, skinfold-
thickness measurements, and bioimpedance analysis. American Journal of Clinical
Nutrition 63(3):287-292.
Gutin, B., Z. O. Yin, M. C. Humphries, and P. Barbeau. 2005. Relations of moderate and
vigorous physical activity to fitness and fatness in adolescents. American Journal of Clini-
cal Nutrition 81(4):746-750.
Haroun, D., S. J. C. Taylor, R. M. Viner, R. S. Hayward, T. S. Darch, S. Eaton, T. J. Cole, and
J. C. K. Wells. 2010. Validation of bioelectrical impedance analysis in adolescents across
different ethnic groups. Obesity 18(6):1252-1259.
Harrison, G. G., E. R. Buskirk, J. E. Lindsay Carter, F. E. Johnston, T. G. Lohman, M. L.
Pollock, A. F. Roche, and J. Wilmore. 1988. Skinfold thicknesses and measurement tech-
nique. In Anthropometric standardization reference manual. Vol. 55-70, edited by T. G.
Lohman, A. F. Roche, and R. Martorell. Champaign, IL: Human Kinetics Publishers.
He, Q., M. Horlick, J. Thornton, J. Wang, R. N. Pierson, S. Y. Heshka, and D. Gallagher.
2004. Sex-specific fat distribution is not linear across pubertal groups in a multiethnic
study. Obesity Research 12(4):725-733.
Herman, K. M., C. L. Craig, L. Gauvin, and P. T. Katzmarzyk. 2009. Tracking of obesity and
physical activity from childhood to adulthood: The Physical Activity Longitudinal Study.
International Journal of Pediatric Obesity 4(4):281-288.
Heymsfield, S. B., T. G. Lohman, Z. M. Wang, and S. B. Going, eds. 2005. Human body
composition. 2nd ed. Champaign, IL: Human Kinetics Publishers.
Himes, J. H., and W. H. Dietz. 1994. Guidelines for overweight in adolescent preventive
services: Recommendations from an expert committee. The Expert Committee on Clini-
cal Guidelines for Overweight in Adolescent Preventive Services. American Journal of
Clinical Nutrition 59(2):307-316.
Houtkooper, L. B., and S. B. Going. 1994. Body composition: How should it be measured?
Does it affect sports performance? Sports Science Exchange #52, Gatorade Sports Sci-
ence Institute 7(5):9.
Huang, Y. C., and R. M. Malina. 2010. Body mass index and individual physical fitness
tests in Taiwanese youth aged 9-18 years. International Journal of Pediatric Obesity
5(5):404-411.
Huxley, R., S. Mendis, E. Zheleznyakov, S. Reddy, and J. Chan. 2010. Body mass index, waist
circumference and waist: Hip ratio as predictors of cardiovascular risk: A review of the
literature. European Journal of Clinical Nutrition 64(1):16-22.
Jekal, Y., E. S. Kim, J. A. Im, J. H. Park, M. K. Lee, S. H. Lee, S. H. Suh, S. H. Chu, E. S.
Kang, H. C. Lee, and J. Y. Jeon. 2009. Interaction between fatness and fitness on CVD
risk factors in Asian youth. International Journal of Sports Medicine 30(10):733-740.
Katzmarzyk, P. T., S. R. Srinivasan, W. Chen, R. M. Malina, C. Bouchard, and G. S. Berenson.
2004. Body mass index, waist circumference, and clustering of cardiovascular disease
risk factors in a biracial sample of children and adolescents. Pediatrics 114(2):198-205.
Katzmarzyk, P. T., W. Shen, A. Baxter-Jones, J. D. Bell, N. F. Butte, E. W. Demerath, V. Gilsanz,
M. I. Goran, V. Hirschler, H. H. Hu, C. Maffeis, R. M. Malina, M. J. Müller, A. Pietrobelli,
and J. C. K. Wells. 2012. Adiposity in children and adolescents: Correlates and clinical
consequences of fat stored in specific body depots. Pediatric Obesity [Epub ahead of print].
OCR for page 106
106 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
Kim, J., A. Must, G. M. Fitzmaurice, M. W. Gillman, V. Chomitz, E. Kramer, R. McGowan,
and K. E. Peterson. 2005. Relationship of physical fitness to prevalence and incidence of
overweight among schoolchildren. Obesity Research 13(7):1246-1254.
Kindblom, J. M., M. Lorentzon, E. Norjavaara, L. Lonn, J. Brandberg, J. E. Angelhed, A.
Hellqvist, S. Nilsson, and C. Ohlsson. 2006. Pubertal timing is an independent predictor
of central adiposity in young adult males: The Gothenburg Osteoporosis and Obesity
Determinants Study. Diabetes 55(11):3047-3052.
Kuczmarski, R. J., C. L. Ogden, L. M. Grummer-Strawn, K. M. Flegal, S. S. Guo, R. Wei, Z.
Mei, L. R. Curtin, A. F. Roche, and C. L. Johnson. 2000. CDC growth charts: United
States. Advance Data (314):1-27.
Kuczmarski, R. J., C. L. Ogden, S. S. Guo, L. Grummer-Strawn, K. M. Flegal, Z. Mei,
R. Wei, L. R. Curtin, A. F. Roche, and C. L. Johnson. 2002. 2000 CDC growth charts
for the United States: Methods and development. Vital and Health Statistics 11(246):
1-190.
Labayen, I., F. B. Ortega, L. A. Moreno, C. Redondo-Figuero, G. Bueno, S. Gomez-Martinez,
and M. Bueno. 2009. The effect of early menarche on later body composition and fat
distribution in female adolescents: Role of birth weight. Annals of Nutrition and Me-
tabolism 54(4):313-320.
Larsson, B., K. Svardsudd, L. Welin, L. Wilhelmsen, P. Bjorntorp, and G. Tibblin. 1984.
Abdominal adipose tissue distribution, obesity, and risk of cardiovascular disease and
death: 13 year follow up of participants in the study of men born in 1913. British Medical
Journal (Clinical Research Edition) 288(6428):1401-1404.
Lauer, R. M., and W. R. Clarke. 1989. Childhood risk-factors for high adult-blood pressure:
The Muscatine Study. Pediatrics 84(4):633-641.
Lee, S. J., and S. A. Arslanian. 2007. Cardiorespiratory fitness and abdominal adiposity in
youth. European Journal of Clinical Nutrition 61(4):561-565.
Lee, S., J. L. Kuk, Y. Kim, and S. A. Arslanian. 2011. Measurement site of visceral adipose
tissue and prediction of metabolic syndrome in youth. Pediatric Diabetes 12(3, Pt. 2):
250-257.
Li, C., E. S. Ford, G. Zhao, and A. H. Mokdad. 2009. Prevalence of pre-diabetes and its asso-
ciation with clustering of cardiometabolic risk factors and hyperinsulinemia among U.S.
adolescents: National Health and Nutrition Examination Survey 2005-2006. Diabetes
Care 32(2):342-347.
Liu, A., A. P. Hills, X. Hu, Y. Li, L. Du, Y. Xu, N. M. Byrne, and G. Ma. 2010. Waist cir-
cumference cut-off values for the prediction of cardiovascular risk factors clustering in
Chinese school-aged children: A cross-sectional study. BMC Public Health 10:82.
Lloyd, L. K., P. A. Bishop, J. L. Walker, K. R. Sharp, and M. T. Richardson. 2003. The influ-
ence of body size and composition on Fitnessgram® test performance and the adjustment
of Fitnessgram® test scores for skinfold thickness in youth. Measurement in Physical
Education and Exercise Science 7(4):205-226.
Lloyd, L. J., S. C. Langley-Evans, and S. McMullen. 2012. Childhood obesity and risk of the
adult metabolic syndrome: A systematic review. International Journal of Obesity 36(1):
1-11.
Lobelo, F., R. R. Pate, M. Dowda, A. D. Liese, and S. R. Daniels. 2010. Cardiorespiratory
fitness and clustered cardiovascular disease risk in U.S. adolescents. Journal of Adolescent
Health 47(4):352-359.
Lohman, T. G. 1981. Skinfolds and body density and their relation to body fatness: A review.
Human Biology 53(2):181-225.
Lohman, T. G. 1986. Applicability of body composition techniques and constants for children
and youths. Exercise and Sport Sciences Reviews 14:325-357.
Malina, R. M. 1975. Anthropometric correlates of strength end motor performance. Exercise
and Sport Sciences Reviews 3(1):249-274.
OCR for page 107
BODY COMPOSITION 107
Malina, R. M. 1992. Physique and body composition: Effects on performance and effects on
training, semistarvation, and overtraining In Eating, body weight, and performance in
athletes, edited by K. D. Brownell, J. Rodin, and J. H. Wilmore. Philadelphia, PA: Lea
& Febiger. Pp. 94-114.
Malina, R. M. 1995. Anthropometry. In Physiological assessment of human fitness, edited
by P. J. Maud and C. Foster. Champaign, IL: Human Kinetics Publishers. Pp. 205-219.
Malina, R. M. 1996. Regional body composition: Age, sex, and ethnic variation. In Human
body composition, edited by A.F. Roche, S. B. Heymsfield, and T. G. Lohman. Cham-
paign, IL: Human Kinetics Publishers. Pp. 217-256.
Malina, R. M. 2000. Growth, maturation, and performance. In Exercise and sport science,
edited by W. E. Garrett and D. T. Kirkendall. Philadelphia, PA: Lippincott Williams &
Wilkins. Pp. 425-445.
Malina, R. M. 2005. Variation in body composition associated with sex and ethnicity. In Hu-
man body composition. 2nd ed., edited by S. B. Heymsfield, T. G. Lohman, Z. M. Wang
and S. B. Going. Champaign, IL: Human Kinetics Publishers. Pp. 271-298, 473-476.
Malina, R. M., and C. Bouchard. 1988. Subcutaneous fat distribution during growth. In Fat
distribution during growth and later health outcomes, edited by C. Bouchard and F. E.
Johnston. New York: Alan R. Liss, Inc. Pp. 63-84.
Malina, R. M., and P. T. Katzmarzyk. 1999. Validity of the body mass index as an indica-
tor of the risk and presence of overweight in adolescents. American Journal of Clinical
Nutrition 70(1):131S-136S.
Malina, R. M., P. V. V. Hamill, and S. Lemeshow. 1973. Selected body measurements of chil-
dren 6-11 years. Vital and Health Statistics, Series 11, No. 123. Washington, DC: U.S.
Government Printing Office.
Malina, R. M., G. P. Beunen, A. L. Claessens, J. Lefevre, B. Vandeneynde, R. Renson, B.
Vanreusel, and J. Simons. 1995. Fatness and physical-fitness of girls 7 to 17 years. Obe-
sity Research 3(3):221-231.
Malina, R. M., P. T. Katzmarzyk, and S. R. Siegel. 1998. Overnutrition, undernutrition and
the body mass index: Implications for strength and motor fitness. Medicine and Sport
Science 43:13-26.
Malina, R. M., S. Koziel, and T. Bielicki. 1999. Variation in subcutaneous adipose tissue dis-
tribution associated with age, sex, and maturation. American Journal of Human Biology
11(2):189-200.
Malina, R., C. Bouchard, and O. Bar-Or. 2004. Growth, maturation, and physical activity.
2nd ed. Champaign, IL: Human Kinetics Publishers.
May, A. L., E. V. Kuklina, and P. W. Yoon. 2012. Prevalence of cardiovascular disease risk
factors among US adolescents, 1999-2008. Pediatrics 129(6):1035-1041.
Maynard, L. M., W. Wisemandle, A. F. Roche, W. C. Chumlea, S. S. Guo, and R. M. Sier-
vogel. 2001. Childhood body composition in relation to body mass index. Pediatrics
107(2):344-350.
McCarthy, H. D., K. V. Jarrett, and H. F. Crawley. 2001. The development of waist circum-
ference percentiles in British children aged 5.0-16.9 y. European Journal of Clinical
Nutrition 55(10):902-907.
McDowell, M. A., C. D. Fryar, R. Hirsch, and C. L. Ogden. 2005. Anthropometric reference
data for children and adults: U.S. population, 1999-2002. Advance Data (361):1-5.
McDowell, M. A., C. D. Fryar, C. L. Ogden, and K. M. Flegal. 2008. Anthropometric refer-
ence data for children and adults: United States, 2003-2006. National Health Statistics
Report 10.
Mei, Z., L. M. Grummer-Strawn, A. Pietrobelli, A. Goulding, M. I. Goran, and W. H. Dietz.
2002. Validity of body mass index compared with other body-composition screening
indexes for the assessment of body fatness in children and adolescents. American Journal
of Clinical Nutrition 75(6):978-985.
OCR for page 108
108 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
Moreno, L. A., M. G. Blay, G. Rodríguez, V. A. Blay, M. I. Mesana, J. L. Olivares, J. Fleta,
A. Sarría, M. Bueno, and A.-Z. S. Group. 2006. Screening performances of the Interna-
tional Obesity Task Force body mass index cut-off values in adolescents. Journal of the
American College of Nutrition 25(5):403-408.
Mota, J., L. Flores, L. Flores, J. C. Ribeiro, and M. P. Santos. 2006. Relationship of single
measures of cardiorespiratory fitness and obesity in young schoolchildren. American
Journal of Human Biology 18(3):335-341.
Moulton, C. R. 1923. Age and chemical development in mammals. Journal of Biological
Chemistry 57:79-97.
Mueller, W. H., and R. M. Malina. 1987. Relative reliability of circumferences and skin-
folds as measures of body fat distribution. American Journal of Physical Anthropology
72(4):437-439.
Mueller, W. H., and R. Martorell. 1988. Reliability and accuracy of measurement. In Anthro-
pometric standardization reference manual, edited by T. G. Lohman, A. F. Roche, and
R. Martorell. Champaign, IL: Human Kinetics Publishers. Pp. 83-86.
Nassis, G. P., G. Psarra, and L. S. Sidossis. 2005. Central and total adiposity are lower in
overweight and obese children with high cardiorespiratory fitness. European Journal of
Clinical Nutrition 59(1):137-141.
Nguyen, Q. M., S. R. Srinivasan, J. H. Xu, W. Chen, and G. S. Berenson. 2008. Changes in
risk variables of metabolic syndrome since childhood in pre-diabetic and type 2 diabetic
subjects: The Bogalusa Heart Study. Diabetes Care 31(10):2044-2049.
ODPHP (Office of Disease Prevention and Health Promotion). 1985. Summary of findings
from National Children and Youth Fitness Study. Washington, DC: U.S. Department of
Health and Human Services.
ODPHP. 1987. Summary of findings from National Children and Youth Fitness Study II.
Washington, DC: U.S. Department of Health and Human Services.
Pietrobelli, A., M. S. Faith, D. B. Allison, D. Gallagher, G. Chiumello, and S. B. Heymsfield.
1998. Body mass index as a measure of adiposity among children and adolescents: A
validation study. Journal of Pediatrics 132(2):204-210.
Pollock, N. K., P. J. Bernard, K. Wenger, S. Misra, B. A. Gower, J. D. Allison, H. Zhu, and
C. L. Davis. 2010. Lower bone mass in prepubertal overweight children with prediabetes.
Journal of Bone and Mineral Research 25(12):2760-2769.
Reed, K. E., D. E. R. Warburton, H. M. Macdonald, P. J. Naylor, and H. A. McKay. 2008.
Action Schools! BC: A school-based physical activity intervention designed to decrease
cardiovascular disease risk factors in children. Preventive Medicine 46(6):525-531.
Reilly, J. J., A. R. Dorosty, N. M. Ghomizadeh, A. Sherriff, J. C. Wells, and A. R. Ness. 2010.
Comparison of waist circumference percentiles versus body mass index percentiles for
diagnosis of obesity in a large cohort of children. International Journal of Pediatric
Obesity 5(2):151-156.
Ribeiro, J. C., S. Guerra, J. Oliveira, L. B. Andersen, J. A. Duarte, and J. Mota. 2004. Body
fatness and clustering of cardiovascular disease risk factors in Portuguese children and
adolescents. American Journal of Human Biology 16(5):556-562.
Rizzo, N. S., J. R. Ruiz, A. Hurtig-Wennlof, F. B. Ortega, and M. Sjostrom. 2007. Relation-
ship of physical activity, fitness, and fatness with clustered metabolic risk in children and
adolescents: The European Youth Heart Study. Journal of Pediatrics 150(4):388-394.
Roche, A. F., S. B. Heymsfield, and T. G. Lohman. 1996. Human body composition. Cham-
paign, IL: Human Kinetics Publishers.
Rolland-Cachera, M. F., M. Deheeger, F. Bellisle, M. Sempé, M. Guilloud-Bataille, and E.
Patois. 1984. Adiposity rebound in children: A simple indicator for predicting obesity.
American Journal of Clinical Nutrition 39(1):129-135.
OCR for page 109
BODY COMPOSITION 109
Ross, R., T. Berentzen, A. J. Bradshaw, I. Janssen, H. S. Kahn, P. T. Katzmarzyk, J. L. Kuk,
J. C. Seidell, M. B. Snijder, T. I. A. Sorensen, and J. P. Despres. 2008. Diagnostic in obe-
sity comorbidities: Does the relationship between waist circumference, morbidity and
mortality depend on measurement protocol for waist circumference? Obesity Reviews
9(4):312-325.
Ryan, A. S., A. F. Roche, and R. J. Kuczmarski. 1999. Weight, stature, and body mass index
data for Mexican Americans from the third National Health and Nutrition Examination
Survey (NHANES III, 1988-1994). American Journal of Human Biology 11(5):673-686.
Safrit, M. J. 1990. The validity and reliability of fitness tests for children: A review. Pediatric
Exercise Science 2:9-28.
Sandhu, J., Y. Ben-Shlomo, T. J. Cole, J. Holly, and G. D. Smith. 2006. The impact of child-
hood body mass index on timing of puberty, adult stature and obesity: A follow-up
study based on adolescent anthropometry recorded at Christ's Hospital (1936-1964).
International Journal of Obesity 30(1):14-22.
Savva, S. C., M. Tornaritis, M. E. Savva, Y. Kourides, A. Panagi, N. Silikiotou, C. Georgiou,
and A. Kafatos. 2000. Waist circumference and waist-to-height ratio are better predictors
of cardiovascular disease risk factors in children than body mass index. International
Journal of Obesity 24(11):1453-1458.
Sekulic, D., N. Zenic, and G. Markovic. 2005. Non linear relationships between anthropomet-
ric and motor-endurance variables. Collegium Antropologicum 29(2):723-730.
Stigman, S., P. Rintala, K. Kukkonen-Harjula, U. Kujala, M. Rinne, and M. Fogelholm.
2009. Eight-year-old children with high cardiorespiratory fitness have lower overall and
abdominal fatness. International Journal of Pediatric Obesity 4(2):98-105.
Stratton, G., D. Canoy, L. M. Boddy, S. R. Taylor, A. F. Hackett, and I. E. Buchan. 2007.
Cardiorespiratory fitness and body mass index of 9-11-year-old English children: A se-
rial cross-sectional study from 1998 to 2004. International Journal of Obesity 31(7):
1172-1178.
Strong, W. B., R. M. Malina, C. J. R. Blimkie, S. R. Daniels, R. K. Dishman, B. Gutin,
A. C. Hergenroeder, A. Must, P. A. Nixon, J. M. Pivarnik, T. Rowland, S. Trost, and F.
Trudeau. 2005. Evidence based physical activity for school-age youth. Journal of Pedi-
atrics 146(6):732-737.
Taylor, R. W., I. E. Jones, S. M. Williams, and A. Goulding. 2000. Evaluation of waist cir-
cumference, waist-to-hip ratio, and the conicity index as screening tools for high trunk
fat mass, as measured by dual-energy x-ray absorptiometry, in children aged 3-19 y.
American Journal of Clinical Nutrition 72(2):490-495.
Taylor, R. W., A. M. Grant, S. M. Williams, and A. Goulding. 2010. Sex differences in regional
body fat distribution from pre- to postpuberty. Obesity 18(7):1410-1416.
Tjonna, A. E., T. O. Stolen, A. Bye, M. Volden, S. A. Slordahl, R. Odegard, E. Skogvoll, and
U. Wisloff. 2009. Aerobic interval training reduces cardiovascular risk factors more
than a multitreatment approach in overweight adolescents. Clinical Science 116(3-4):
317-326.
Toprak, D., A. Toprak, W. Chen, J. H. Xu, S. Srinivasan, and G. S. Berenson. 2011. Adiposity
in childhood is related to c-reactive protein and adiponectin in young adulthood: From
the Bogalusa Heart Study. Obesity (Silver Spring) 19(1):185-190.
Wang, J., J. C. Thornton, S. Bari, B. Williamson, D. Gallagher, S. B. Heymsfield, M. Horlick,
D. Kotler, B. Laferrere, L. Mayer, F. X. Pi-Sunyer, and R. N. Pierson. 2003. Comparisons
of waist circumferences measured at 4 sites. American Journal of Clinical Nutrition
77(2):379-384.
Wang, Z. M., R. N. Pierson, Jr., and S. B. Heymsfield. 1992. The five-level model: A new ap-
proach to organizing body-composition research. American Journal of Clinical Nutrition
56(1):19-28.
OCR for page 110
110 FITNESS MEASURES AND HEALTH OUTCOMES IN YOUTH
Wang, Z. M., S. Heshka, R. N. Pierson, Jr., and S. B. Heymsfield. 1995. Systematic organiza-
tion of body-composition methodology: An overview with emphasis on component-based
methods. American Journal of Clinical Nutrition 61(3):457-465.
Wang, Z. M., W. Shen, R. T. Withers, and S. B. Heymsfield. 2005. Multicomponent molecular-
level models of body composition analysis. In Human body composition, edited by S.
B. Heymsfield, T. G. Lohman, Z. M. Wang, and S. B. Going. Champaign, IL: Human
Kinetics Publishers. Pp. 163-176.
Wells, J. C. K., J. E. Williams, S. Chomtho, T. Darch, C. Grijalva-Eternod, K. Kennedy, D.
Haroun, C. Wilson, T. J. Cole, and M. S. Fewtrell. 2010. Pediatric reference data for
lean tissue properties: Density and hydration from age 5 to 20 y. American Journal of
Clinical Nutrition 91(3):610-618.
´
Welon, Z., R. Jurynec, and W. Sliwak. 1988. Optimal body weight in men (ci ez ar nalezny
m ez czyzn) in polish. Materialy i Prace Antropologiczny 109:53-71.
WHO (World Health Organization). 1995. Physical status: The use and interpretation of
anthropometry. Report of a WHO expert committee. Technical Report Series, No. 854.
Geneva, Switzerland: WHO.
WHO. 2008. WHO stepwise approach to surveillance (steps). Geneva, Switzerland: WHO.
WHO. 2011. Waist circumference and waist-hip ratio: Report of a WHO expert consultation,
Geneva, 811 December 2008. Geneva, Switzerland: WHO.
Williams, D. P., S. B. Going, T. G. Lohman, D. W. Harsha, S. R. Srinivasan, L. S. Webber, and
G. S. Berenson. 1992. Body fatness and risk for elevated blood-pressure, total cholesterol,
and serum-lipoprotein ratios in children and adolescents. American Journal of Public
Health 82(3):358-363.
