Introduction to Human Nutrition

22 Introduction to Human Nutrition

CT scanning is expensive and, because of the rela-
tively high level of radiation, the method is limited to
subjects for whom scanning is indicated on clinical
grounds. An alternative method to CT scanning is
MRI, which has the advantage that no ionizing radia-
tion is involved.
During MRI, the signals emitted when the body is
placed in a strong magnetic fi eld are collected and, as
with CT scanning, the data are used to generate a
visual cross-sectional slice of the body in a certain
region. The determination of adipose tissue versus
nonadipose tissue is based on the shorter relaxation
time of adipose tissue than of other tissues that contain
more protons or differ in resonance frequency. MRI
has the advantage over CT scanning that the subject is
not exposed to ionizing radiation. However, the time
necessary to make an MRI image is relatively long
(minutes versus seconds using CT), which has impli-
cations for the quality of the image. Any movement of
the subject, even the movements of the intestinal tract
when making images in the abdominal region, will
decrease the quality of the image.
As with CT scanning, images can be combined to
obtain information on total body composition. Infor-
mation about organ size can be obtained with a high
accuracy. For example, MRI is used to study the con-
tribution of various organs to the resting metabolic
rate of the total body.
Both CT scanning and MRI are expensive, and
therefore their use will remain limited to a few labo-
ratories and for very specifi c situations.

2.7 Doubly indirect methods

Anthropometry

Weight/height indices
A weight/height index aims to correct body weight
for height. As a measure of body composition, for
example body fat, a weight/height index should have
a high correlation with body fat, but also a low cor-
relation with body height, otherwise in short people
body fat would be systematically overestimated or
underestimated.
In the literature, a number of weight/height indices
have been proposed. Examples are the Quetelet index
or body mass index (BMI: weight/height^2 ), the Broca
index [weight/(height – 100)], and the Benn index
(weight/heightp, in which the exponent p is popula-

tion specifi c). The Quetelet index or BMI is the most

widely used index today. Its correlation with body fat

is high (depending on the age group r = 0.6–0.8) and

the correlation with body height is generally low. The

World Health Organization (WHO) promotes the

BMI as a crude indicator for weight judgment. In

Table 2.5 the cut-off points for underweight, normal

weight, overweight, and obesity according to the

WHO are given. These cut-off values are based on the

relation of BMI with mortality and with risk factors

for disease as found in Caucasian populations. For

non-Caucasian populations other cut-off values may

apply (WHO, 2004).

The cut-off values for BMI as in Table 2.5 cannot

be used in children. In younger children, weight com-

pared with height is relatively low, and so is the BMI.

During growth, the increase in weight is larger than

the increase in height and, consequently, the BMI

increases with age during the pubertal phase of life.

There are age-related BMI cut-off values for obesity

for children.

The BMI can also be used as a predictor for the

percentage of body fat. Several studies have been pub-

lished in which a good relationship between the BMI

and the amount of body fat (either as fat mass or as

body fat percentage) was demonstrated. The relation-

ship between BMI and body fat percentage is age and

gender dependent and is different among certain

ethnic groups (Box 2.8). When using such age- and

gender-specifi c prediction equations, body fat per-

centage can be predicted with an error of 3–5%. This

error is similar to the prediction error of other doubly

indirect methods, for example skinfold thickness or

total body bioelectrical impedance measurements.

The disadvantage of these prediction formulae is that

they obviously cannot be used in certain subjects or

Table 2.5 Classifi cation of weight in adults according to body mass

index

Classifi cation Body mass index (kg/m^2 ) Risk of comorbidities

Underweight <18.5 Low

Normal range 18.5–24.9 Average

Overweight >25.0

Preobese 25.0–29.9 Increased

Obese class I 30.0–34.9 Moderate

Obese class II 35.0–39.9 Severe

Obese class III > 40 Very severe

Reproduced with permission of the World Health Organization.