MMMM
Part II
Diagnosis
International Textbook of Obesity. Edited by Per Bjorntorp.
Copyright © 2001 John Wiley & Sons Ltd
Print ISBNs: 0-471-988707 (Hardback); 0-470-846739 (Electronic)
4
Anthropometric Indices of Obesity
and Regional Distribution of Fat
Depots
T.S. Han and M.E.J. Lean
Wolfson College, Cambridge and Glasgow Royal Infirmary, Glasgow
INTRODUCTION AND
BACKGROUND
Body fatness and body shapes have been topics of
interest to people over the ages because of health
considerations, but scientific assessment and presentation have been complicated by changing
fashions and a range of myths. Many methods of
measuring body fatness have been developed for
epidemiological field studies or clinical use, based
on laboratory methods such as underwater weighing as a conventional ‘gold standard’. This twocompartment model estimates body composition
with the assumption that the densities of lean
(1.1 kg/L) and adipose (0.9 kg/L) tissues are constant (1). Indices of obesity have been derived to
assess body composition and health at the present,
and to predict future health. Rarely a method has
been developed specifically for self-monitoring by
lay people. One of the tantalizing features of research in body composition is the lack of any true
gold standard from which to calibrate other
methods. Direct measurement by chemical analysis,
either by macroscopic dissection or by lipid extraction, is of limited value as it cannot be related to
measurements in vivo.
International Textbook of Obesity. Edited by Per Björntorp.
© 2001 John Wiley & Sons, Ltd.
PURPOSES AND APPLICATIONS OF
ANTHROPOMETRY
Simple and cheap anthropometric methods are useful for epidemiological surveys of large numbers of
subjects across the population. For clinical use, anthropometric methods are useful tools for diagnosis
and monitoring patients. The most appropriate
methods may vary depending on whether the need
is for cross-sectional or longitudinal assessment. In
research studies, physiological characterization of
individuals is assessed by a range of anthropometric
measurements. One of the most fundamental issues
in employing anthropometric measurements to assess body fat is that the prediction equations must
be validated in a similar population to that to which
the equations are being applied.
METHODS COMMONLY USED TO
MEASURE BODY FATNESS
Laboratory Standard Methods
For small studies, total body fat is estimated by
standard methods (Table 4.1) such as underwater
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Table 4.1 Methods of measuring body fat and fat distribution
Methods
Accuracy
Practicality
Sensitivity to
change
Cheapness
Fat distribution
detection
Laboratory: ‘standard’ methods
Underwater weighing
Potassium-40 counting
Dual-energy X-ray absorptiometry
Computerized tomography
Magnetic resonance imaging
Multi-compartment models
Air displacement (BOD POD)
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Field: anthropometric methods
Skinfold thickness
Circumference
Body mass index
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Figure 4.1 Measuring total body fat by underwater weighing
weighing (Figure 4.1), potassium-40 (K) counting,
or more recently by imaging techniques such as
dual-energy X-ray absorptiometry (DEXA) (which
was itself calibrated against underwater weighing),
computerized tomography (CT) scan and magnetic
resonance imaging (MRI) (Figure 4.2). All these
methods make assumptions about composition of
‘average’ tissues, e.g. density of fat, constant K of
ANTHROPOMETRIC INDICES OF OBESITY
53
pend on the resolution of imaging, and they also fail
to detect fat within organs such as liver, muscles and
bones. Cadaver dissection, coupled with chemical
analysis, should theoretically overcome this problem, but there is a very real practical limitation
through the time required for dissection and alteration in tissue hydration.
Field Anthropometric Methods
Figure 4.2 Magnetic resonance imaging scanner used to image
body tissues
muscles, or attenuation to X-rays from fat and lean
tissues, and thus all the methods have inherent error. Overhydration and dehydration also affect the
estimation of body composition. In attempts to
overcome these problems, three- and four-compartment models to predict body composition have
been developed, which employ separate measurements of body fat, muscle mass, body water and
bones. These multi-compartment methods may improve accuracy of measurement but patients are
subjected to many tests. Time and costs will limit
the number of subjects that can be studied, and
accumulated errors from these methods also make
this model unattractive. A recently invented technique based on air displacement (BOD POD; Life
Measurements Instruments, Concord, CA) has
been introduced. This method measures rapidly
and is less intimidating; thus it is useful for measuring body composition of children and the elderly.
It is important to recognize that there is in fact no
true gold standard or reference method for body
composition analysis. Thus scanning methods de-
Using an underwater weighing method to predict
body fat is impractical for large field studies, requiring facilities and the cooperation of subjects and
expertise of the investigators. Proxy anthropometric methods (Table 4.1) have been employed including skinfolds (2), body mass index (BMI) (3), and
skinfolds combined with various body circumferences (4—6) to predict body fat estimated by underwater weighing. Body fat predicted from these equations shows high correlations with body fat
measured by underwater weighing and relatively
small errors of prediction. However, there have
been few major validations of these equations in
independent populations to test their generalizability or applicability in special population subgroups.
The most widely used field method for total fat has
been the four-skinfold methods (Figure 4.3), derived
from underwater weighing (2). Recognizing possible
errors of predicting body fat in subpopulations with
altered fat distribution, regression equations including waist circumference (Figure 4.4) appear to have
advantages in predicting total body fat by taking
some account of this variation in fat distribution (6).
Waist circumference, alone, predicts health (7) as
well as body composition and is recommended for
public health promotion (8,9).
Previously, little attention has been paid to developing an index of adiposity that could be used by
lay people. The BMI has been the traditional index
of obesity, but its concept and calculations are not
readily understood by many. Criteria for classification of overweight and obesity have been inconsistent. Conventional classification of BMI, using the
same criteria for both men and women, is based on
life insurance and epidemiological data. Waaler (10)
has shown a U-shaped relationship between BMI
and mortality rates, with exponential increases of
mortality in adult subjects with high BMI
( 30 kg/m) or low BMI ( 20 kg/m). These cri-
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Figure 4.3 Measuring subcutaneous skinfold thicknesses at the sites of biceps, triceps, subscapular and suprailiac using skinfold
calipers
teria for interpreting BMI do not apply to children,
whose BMI is normally much lower than that of
adults. The arbitrary cut-offs for overweight at BMI
25 and for obesity at BMI 30 kg/m have now been
adopted by the National Institutes of Health (8) in
America and World Health Organization (11).
These cut-offs have been used widely in Europe for
many years.
MEASURING BODY COMPOSITION
IN SPECIAL GROUPS
There are major effects of age on body composition
which mean that anthropometric methods may not
always be valid. A major pitfall is the unquestioning
use of equations to predict body fat derived from
one population group, without subsequent validation in another specific population group.
Infants and Children
For infants, the ‘reference’ methods used to determine body composition in infants include O isotope dilution (12) and DEXA (13). The ponderal
index (weight divided by height cubed) has been
used as an anthropometric method to assess body
fatness. Measuring children’s body composition is
problematic, as their tissue composition varies with
growth, the rate and timing of growth vary widely,
and physical activity influences the composition of
fat free mass (14). Several studies have used doubly
labelled water to monitor children’s growth and
estimate their total body water, and thus body composition. Reference values for body weight and
triceps skinfold thickness of British children have
been provided by Tanner and co-workers (15—17),
although the Tanner reference values for weight are
no longer appropriate in the UK. In a validation
study, Reilly et al. (18) have shown that the skinfold
method produces large errors in predicting body fat
ANTHROPOMETRIC INDICES OF OBESITY
55
Athletes
In athletes, BMI does not reflect body fat very well,
particularly in power athletes who have large
muscle mass. Inaccuracies in anthropometric prediction equations stem from the reference methods,
such as underwater weighing, from which they are
derived since the density of these subjects’ lean tissues is considerably higher than the 1.1 kg/L value
(1) used for estimating body composition in the
‘normal’ population. Muscle varies considerably as
a proportion of total lean body mass.
Illness
Figure 4.4 Measuring waist circumference midway between
iliac crest and lowest rib margin, and hip circumference at the
level of the greater trochanters
of 9-year-old children. These workers used underwater weighing as the reference method and found
it acceptable even to very young children. As a
generalization, anthropometric methods to estimate body fat are not reliable in children. BMI can
be used, but with caution in its interpretation because of variable stages of development at the same
age. There are standard BMI reference curves (Figure 4.5) developed by Cole et al. (19) for the Child
Growth Foundation.
Ageing and Elderly
Intra-abdominal fat increases with age and immobility, and thereby tends to invalidate the subcutaneous skinfold methods. In postmenopausal
women, body fat may accumulate intra-abdominally as a result of hormonal changes. Consequently, subcutaneous skinfold methods may underestimate their total body fat.
Conventional anthropometric prediction equations
break down with altered relative body composition.
For example, patients with advanced tuberculosis
and cancer or with benign oesophageal stenosis
may have similar BMIs as a result of weight loss,
but muscle loss is likely to be greater in a cachectic
inflammatory condition. Errors will therefore result
from using the same body composition prediction
equations. Illnesses that result in considerable loss
of minerals or specific tissues, e.g. muscle wasting in
patients with acquired immune deficiency syndrome (AIDS), may result in an overestimation of
body fat using conventional prediction equations.
In contrast, in patients with non-insulin-dependent
diabetes mellitus (NIDDM) (Type 2 diabetes) who
have increased intra-abdominal fat, there is underestimation of body fat using skinfold methods,
which increases with the amount of central fat deposition (20). There is a problem in measuring body
composition of amputees whose substantial absence of muscle mass gives unrealistic BMI values.
In bed- or chair-bound patients, height measurement is not available for calculation of BMI. Alternative methods including arm span and lower leg
length can be used to predict height with an accuracy within 4 cm (21).
ANTHROPOMETRIC ASSESSMENT OF
OBESITY
Predicting Total Body Fat from Skinfold
Thicknesses
Four skinfold thicknesses are conventionally meas-
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Figure 4.5 Standard body mass index curves from birth to 20 years for boys (a, above) and girls (b, opposite). Copyright © Child
Growth Foundation. Reproduced by permission. Copies of the CGF BMI charts are available from Harlow Printing, Maxwell Street,
South Shileds NE33 4PU, UK
ured (Figure 4.3), using calipers at biceps, triceps,
subscapular and suprailiac, and the sum of all four
skinfolds (equation 1), or just the triceps skinfold
(equation 2), with subjects’ age, are used in linear
multiple regression to predict total body fat. The
original equations for use in adults (2) have been
cross-validated in a separate sample and found to
be robust in adults aged 20—60 years (6), but tend to
underestimate substantially the total fat in the elderly, particularly women (6,22) (Figure 4.6).
Body fat % (men) : [30.9 ; log
skinfolds
(mm)] ; [0.271 ; Age (years)] 9 39.9
(1)
Body fat % (women) : [30.8 ; log skinfolds
(mm)] ; [0.274 ; Age (years)] 9 31.7
ANTHROPOMETRIC INDICES OF OBESITY
Body fat % (men) : (1.31 ; Triceps)
; (0.430 ; Age) 9 9.2
Body fat % (women) : (0.944 ; Triceps)
; (0.279 ; Age) ; 4.6
(2)
Predicting Total Body Fat from Waist
Circumference and Triceps Skinfold
Han and Lean (20) have observed a systematic
underestimation of body fat by equations using
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subcutaneous skinfold thicknesses (2) in subjects
with increased intra-abdominal fat mass, reflected
by a high waist circumference or waist-to-hip ratio,
including the elderly and those with type 2 diabetes.
Waist circumference (Figure 4.4) has been found to
correlate highly with both intra-abdominal and total fat masses (6,23), and was used on its own and
with skinfold thicknesses to develop new regression
equations to correct for the intra-abdominal fat
mass (6). These equations were validated in a large
Dutch sample from previous study of body fat distribution (3).
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Equations using waist circumference alone, adjusted for age (equation 3), showed good prediction
of body fat in the independent Dutch sample
(r : 78%) with similar error of prediction as other
equations. These equations are particularly good
for estimating body fat in the elderly without the
systematic underestimation of body fat that occurs
in the subcutaneous skinfold method (Figure 4.6).
Body fat % (men) : [0.567 ; Waist circumference
(cm)] ; [0.101 ; Age (years)] 9 31.8
(3)
Body fat % (women) : [0.439 ; Waist circumference (cm)] ; [0.221 ; Age (years)] 9 9.4
Equations combining waist circumference and
triceps skinfold, adjusted for age (equation 4), have
been shown to improve predictive power of body fat
estimation without systematic errors over equations employing subcutaneous skinfolds alone in
subjects with type 2 diabetes who had increased
intra-abdominal fat mass (20).
Body fat % (men) : [0.353 ; Waist
[0.756 ; Triceps (mm)] ; 0.235 ; Age
9 26.4
Body fat % (women) : [0.232 ; Waist
[0.657 ; Triceps (mm)] ; [0.215 ; Age
9 5.5
(cm)] ;
(years)]
(4)
(cm)] ;
(years)]
Calculations of Body Mass Index
(Quetelet Index), and its Use to Predict
Body Fat
Bigger people—both taller and fatter—are heavier
than small people. Body weight includes fat, muscle
and all other organs. For people of the same height,
most of the variation in weight is accounted for by
different amounts of body fat. BMI aims to describe
weight for height in a way which will relate maximally to body weight (or body fat) with minimal
relation to height (24). BMI is calculated as the ratio
of weight in kilograms divided by height squared
(m). Since BMI uses height, the height measurement needs to be very accurate. Classification of
BMI (Table 4.2) uses the same criteria for both men
and women is now adopted by both the NIH (8) and
WHO (25). A BMI of 18.5 to 24.9 kg/m is considered as in the normal range, above 25 kg/m as overweight and above 30 kg/m as obese. For some
purposes, the obese category is subclassified by the
Figure 4.6 Plots of errors of predicting body fat by underwater
weighing from equations using waist circumference (——,
Lean et al. (6) and subcutaneous skinfolds (------, Durnin and
Womersley (2) against age in men (a) and women (b) aged 18 to
83 years
WHO (25) as 30—34.9 (moderately obese), 35—39.9
(severely obese), and greater than 40 (very severely
obese) kg/m.
BMI can be used to predict body fat from underwater weight (r : 79%) with age and sex corrections (3). Our derived equations using BMI to predict body fat were validated in the independent
sample provided by Deurenberg et al. (3) and
showed similarly good prediction of body fat as
other equations currently in use (equation 5).
Body fat % (men) : [1.33 ; BMI (kg/m)] ;
[0.236 ; Age (years)] 9 20.2
(5)
Body fat % (women) : [1.21 ; BMI (kg/m)] ;
[0.262 ; Age (years)] 9 6.7
ANTHROPOMETRIC ASSESSMENT OF
BODY FAT DISTRIBUTION
People with central fat distribution in both sexes
ANTHROPOMETRIC INDICES OF OBESITY
tend to have a distinct body shape, said to resemble
that of an apple (Figure 4.7), a physical characteristic of men (termed ‘android’ by Vague) which tends
to be associated with metabolic abnormalities and
chronic diseases (26—31).
Body circumferences and their ratios are used to
indicate the distribution of body fat. The most important variations, in terms of health associations,
are between the amounts of fat in internal, mainly
intra-abdominal sites, as distinct from subcutaneous sites (Figure 4.8). The ‘gold standard’ for
measuring fat depots in these sites is scanning by
MRI (Figure 4.2). CT gives almost equal information but the small radiation exposure limits its acceptability.
Waist-to-hip Ratio
The ratio of waist-to-hip circumferences (Figure
4.4) was the first anthropometric method developed
from epidemiological research as an indicator of fat
distribution in relation to metabolic diseases.
Waist-to-hip ratio is related more closely to the
ratio of intra-abdominal fat/extra-abdominal fat
mass than the absolute amount of intra-abdominal
fat mass (32), and has been shown to relate to mortality from coronary heart disease and type 2 diabetes independent of BMI (28,29). Most of the value
in indicating body fat is derived from waist circumference, the hip circumference probably reflecting
several other body tissues such as bones and
muscles. The waist-to-hip ratio may have some particular value in reflecting diseases which involve
muscle reduction as well as fat deposition, e.g. type
2 diabetes (33).
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Table 4.2 Classification of body mass index for body fatness
adopted by the World Health Organization (25) and US
National Institutes of Health (8)
BMI (kg/m)
Classification
18.5—24.9
25—29.9
P30
Acceptable
Overweight—increased health risks
Obesity—high health risks
Conicity Index
The conicity index was formulated by Valdez (35) to
estimate abdominal fat, based on the theory that
leaner subjects have a body shape similar to a cylinder, but as fat is accumulated around the abdomen,
the body shape changes towards that of a double
cone (two cones with a common base at the waist).
With the assumption that the average human body
density is 1.05 kg/m, the equation was derived as:
Conicity index :
Waist
(0.109 ; (weight/height)
(6)
The conicity index is theorized to have a built-in
adjustment for height and weight so that abdominal
adiposity can be compared across different populations of varying heights and weights (36). The index
is related to the ratio of intra-abdominal fat/extraabdominal fat mass similarly to waist-to-hip ratio,
and may be useful when hip measurement is not
available. Valdez et al. (36) found the conicity index
to be correlated to cardiovascular risk factors similarly to that of waist-to-hip ratio in different countries. A drawback is that the index has not been
cross-validated to ensure applicability.
Sagittal Abdominal Diameter
Waist-to-thigh Ratio
In some studies waist-to-thigh ratio has been used
as an index for fat distribution to relate to metabolic
risk factors (34). This ratio is also influenced by
abdominal fat as well as fat mass, muscle mass and
bone structures of the thigh, which may be a strong
indicator of certain health conditions involving
both abdominal fat accumulation and skeletal
muscle wasting such as NIDDM.
The use of sagittal diameter of the waist has been
proposed as an index of abdominal fatness based on
a theory that fat deposition in the anteroposterior
axis is more ‘dangerous’ than lateral fat deposition.
This index has not been validated in an independent
population. Sagittal diameter can be measured using a pelviometer in the standing position, or a
more sophisticated instrument that is modified
from a sliding stadiometer in the supine position
(37). Gadgets are on sale with a back plate which is
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more complicated method is not likely to be much
different from a circumference or a single measurement of waist diameter.
Waist Circumference
Figure 4.7 Silhouette photographs showing variation in human body fat distribution
flexible, thereby introducing enormous errors. The
measurement of sagittal diameter of the waist has
not been used very widely. This method has recently
been validated by CT scanning and found to have
high reproducible results.
Abdominal Cross-sectional Area
Abdominal cross-sectional area (CSA ) has also
been proposed by van der Kooy et al. (38) as an
index of abdominal fat and is calculated from waist
sagittal (WSD) and waist transverse diameters
(WTD) as: CSA : (4 ; WSD ; WTD)/, but this
Recent proposals for the use of waist circumference
as a single measurement of body fat and fat distribution have now been adopted by several major public health promotion agencies and organizations
(8,9,21).
Waist circumference has been suggested as a
simple measurement to identify individuals with
high BMI or high waist-to-hip ratio. Waist circumference correlates significantly with BMI (both men
and women: r : 0.89; P 0.001). Lean et al. (39)
have derived the ‘action levels’ for weight management based on the waist circumference of over 2000
men and women (Table 4.3). Action level 1: Waist
circumference of P 94 cm in men or P 80 cm in
women identifies as overweight with increased
health risks, those with BMI P 25 kg/m and high
waist-to-hip ratio ( P 0.95 for men; P 0.80 for
women). These subjects are advised not to gain
further body weight and to increase physical activity. Action level 2: Waist circumference of P 102 cm
in men or P 80 cm in women identifies as overweight with high health risks, those with BMI
P 30 kg/m and high waist-to-hip ratio ( P 0.95 in
men and P 0.80 in women). Weight loss and consultation of health professionals are recommended
for these individuals. These action levels for weight
management have a sensitivity (correctly identifies
individuals who need weight management by waist
circumference above action levels) and a specificity
(correctly identifies individuals who do not need
weight management by waist circumference below
action levels) of more than 96% for identifying
overweight and obese subjects with high waist-tohip ratio. Waist circumference is not importantly
influenced by height (40) (Figure 4.9), thus it is not
necessary to divide waist by height when using
waist circumference as an index of adiposity. To
avoid problems with over-tightening during waist
measurement, a specially designed ‘Waist Watcher’
spring-loaded tape measure has been produced
with three colour bands based on cut-offs of the
waist circumference action levels (Figure 4.10).
ANTHROPOMETRIC INDICES OF OBESITY
61
Table 4.3 Action levels to identify overweight and obese men and women with increased abdominal fat
Waist circumference
Approximate equivalents
Action level
cm
Body mass
index
Waist-to-hip
ratio
Classification of health risks
Men
Action level 1
P94
P25
P0.95
Increased health risks
Action level 2
P102
P30
P0.95
High health risks
Women
Action level 1
P80
P25
P0.80
Increased health risks
Action level 2
P88
P30
P0.80
High health risks
METHODS FOR ANTHROPOMETRIC
MEASUREMENTS
Body Weight
Weight is measured by digital scales or beam balance to the nearest 100 g. For those unable to stand,
electronic chair scales (Weighcare C, Marsden Ltd,
London) are available. For field work, portable
scales are used. Equipment is calibrated regularly
by standard weights (4 ; 10 kg and 8 ; 10 kg), and
the results of test weighing recorded in a book.
Subjects are weighed in light clothing, fasting and
with an empty bladder, preferably at the same time
of day.
Height
Height is measured by stadiometer to the nearest
millimetre, which is calibrated by meter rule before
use. When possible, a wall mounted stadiometer is
preferred. For field work, a portable stadiometer
(Leicester Height Measure, Child Growth Foundation, London, UK; Holtain, Crymych, UK) is available. Subjects stand in bare feet which are kept
together and pointing forward. The head is level
with horizontal Frankfurt plane (line from lower
border of the eye orbit to the auditory meatus).
Subjects are encouraged to stretch upwards by applying gentle pressure at the mastoid processes and
height is recorded with subjects taking in a deep
breath for maximum measurement.
Weight management
Prevent further weight gain, try to get
down to below action level 1 (94 cm)
Seek advice to lose weight, aim for 5—10%
weight loss permanently
Prevent further weight gain, try to get
down to below action level 1 (80 cm)
Seek advice to lose weight, aim for 5—10%
weight loss permanently
Limb Lengths
When height measurement is not available in bedand chair-bound patients. Height can be predicted
from arm span or lower leg length (21). Arm span is
measured between finger tips with subjects standing
against the wall, and both arms fully stretch horizontally. Demi-arm span is measured as the horizontal distance from the web space between middle
and fourth fingers to the midpoint of the sternal
notch to the nearest millimetre, in the sitting position. Lower leg length is measured with subjects
sitting in a chair adjusted to about their knee height,
and the lower legs and bare feet flexed at 90°. The
lower legs, 25—30 cm apart, are adjusted to vertical
position both side and front views. A ruler standing
on its edge is placed on top of the patellae. Lower
leg length is taken to the nearest millimetre from the
midpoint of the ruler to the floor with a wooden
metre rule.
Waist Circumference
Waist circumference is measured midway between
the lower rib margin and iliac crest, with a horizontal tape at the end of gentle expiration (Figure 4.4),
with feet kept 20—30 cm apart. Subjects should be
asked not to hold in their stomach, and a constant
tension spring-loaded tape device reduces errors
from over-enthusiastic tightening during measurement. Waist circumference measurement reflects
body fat and does not include most of the bone
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Figure 4.8 Subcutaneous and intra-abdominal fat images obtained from magnetic resonance imaging. (a, above) Male; (b, opposite)
female. Light areas indicate fat
structure (only the spine) or large muscle masses,
whose variations between subjects might otherwise
introduce errors.
Hip Circumference
Maximum hip circumference is measured with a
horizontal steel tape at the widest part of the trochanters at horizontal position (Figure 4.4) with feet
kept 20—30 cm apart. It is related more closely to
subcutaneous fat than to intra-abdominal fat mass.
Hip circumference has limited value on its own in
body composition estimation. The circumference of
the hip is influenced by gluteal muscle mass and
pelvic size, which vary between subjects, as well as
by fat.
Thigh Circumference
Thigh circumference is measured at the level of
gluteal fold with the leg being measured relaxed by
placing it forward and slightly bent, with body
weight transferred to the other leg. It estimates fat
on the thigh but will also be altered by muscle mass.
Waist Diameter
Abdominal fat deposition is further classified into
medial (fat is accumulated at the middle of the
abdomen) and lateral (fat is accumulated at the
sides of the abdomen). Waist diameters are measured using a pelviometer or a more expensive device
that measures the supine sagittal abdominal diameter (37). The pelviometer is a cheaper instrument
ANTHROPOMETRIC INDICES OF OBESITY
that looks like a pair of large calipers and measures
the waist diameter at the level between the lower rib
margin and iliac crest. Waist sagittal diameter is
taken as the distance from the back to the front of
the abdomen measured with the subject standing.
Waist transverse diameter is taken as the distance
from the sides of the abdomen.
Skinfold Thickness
Skinfold thicknesses are measured on the left side of
the body with calipers (Holtain Ltd, Crymych, UK)
in triplicate, to the nearest 0.2 mm. All the sites
intended for measurements should be marked clearly on the skin after making measurements from
bony landmarks (Figure 4.3). When the subjects
relax their mucles, the subcutaneous fat layer
(commonly referred to as skinfold thickness) covering the muscles is relatively loose and can usually be
63
pinched easily by two fingers (thumb and index
finger) which hold the skinfold firmly throughout
the measurement (11). The pinch is made at about 1
to 2 cm above the ink mark so that the jaw of the
calipers can be applied at the mark. The thickness of
the skinfold is read about 2 seconds after closing the
jaw of the calipers.
Biceps and triceps skinfold thicknesses are made
at the midpoint of the upper arm, between the acromion process and the tip of the bent elbow. Subscapular skinfold thickness is picked up at the natural fold about 2—3 cm below the shoulder blade in
an oblique angle. Suprailiac skinfold is pinched at
about 2—3 cm above the iliac crest, in either a vertical or oblique angle on the lateral side and midaxillary line. The upper limit of skinfold calipers is
50 mm, which is exceeded for the subscapular site
when BMI is greater than 40 kg/m. Thus for very
overweight people, other methods are required.
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Figure 4.10 ‘‘Waist Watcher’’ tape measures with three colour
bands (green, orange and red) based on cut-off waist circumference action levels. (BGA, The Spire, Egypt Road, Nottingham
NG7 7GD, UK)
8.
9.
10.
Figure 4.9 The relationship between waist circumference and
height in 2183 men (a) and 2698 women (b) showing regression
line (solid) and the line of zero correlation (dashed)
11.
12.
REFERENCES
13.
1. Siri. WE. Body composition from fluid spaces and density
analysis of methods. IN: Brozek J, Henschel A (eds) Technique for Measuring Body Composition. Washington DC:
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