Measures based on height and weight

Body “fatness”, estimated using calculations with height and weight, can be used as a proxy indicator of body composition. These calculations have the advantage that height and weight can be easily measured without any particularly sophisticated or expensive equipment. Weight-for-height is a standard that is generally used for children of between 2 and 5 years of age (with weight-for-length being used for infants younger than 2 years old).

Tables and charts of z-scores and percentiles for boys and girls separately are available from the World Health Organisation [23]. Poustie et al (2000) found weight-for-height to be an unreliable measure of nutritional status in children because of inter- and intra-examiner variation in measurement [24], while Mei et al found no difference between weight-for-height and other mea-sures of body composition [25].

Body Mass Index (BMI) (also referred to as Quetelet’s Index [26, 27]) is widely used in a variety of scenarios, from individuals “watching their weight”

to clinical settings. BMI requires no complicated measurements, simply weight and height, and is calculated from the following equations:

For metric measurements:

For imperial measurements:

Overweight and obesity in adults can be determined objectively from BMI using generally-agreed guidelines. These guidelines do vary slightly from source to source. Guidelines established by the World Health Organisation (WHO) in 1997 and published in 2000 [28] are shown in Table 1.1.

BMI Classification

< 18.5 underweight 18.5 to 24.9 healthy weight

25.0 to 29.9 overweight (or “pre-obese”) 30.0 to 34.9 class I obesity

35.0 to 39.9 class II obesity

> 40.0 class III obesity

Table 1.1: WHO criteria for overweight and obesity in adults

Although BMI is relatively simple to calculate and use, its reliability is ques-tionable because BMI doesn’t take into account proportions of FM and FFM in the body. For any given volume, FFM is heavier than FM and, as a result, people can be misclassified. For example, an athlete may be classified as over-weight due to having a higher proportion of FFM than, and therefore being heavier than, the general population. Additionally, there exist differences in body composition as a result of age, gender and possibly race that are not currently considered when interpreting BMI [27]. For example, a World Health Organisation expert consultation on appropriate BMI for Asian pop-ulations suggested that the acceptable range be narrowed to 18.5_m^kg2 - 23_m^kg2

[29].

Determining the risk of overweight and obesity from BMI is not as straight-forward for children as for adults. The BMI calculations are the same, as shown above (equations (1.2) and (1.3)), but further calculations must be carried out. One common method currently, in keeping with WHO guide-lines, is to use BMI to calculate percentile rankings from gender-specific BMI-for-age growth charts (for 2 - 20 years of age, available from the World Health Organisation (WHO) ) [28]. These percentiles are then categorised as follows:

Percentile Category

< 5th percentile Underweight

80th to < 95th percentile Overweight (“pre-obese”)

≥ 95th percentile Obese

Table 1.2: WHO criteria for overweight and obesity from gender-specific BMI-for-age growth charts for children and adolescents

As an alternative to the WHO percentiles, BMI standard deviation scores (SDS) for UK children can be relatively easily calculated using the LMS method developed by Tim Cole in 1990 [30]. This method, described in de-tail in section 2.2, adjusts BMI for height, sex and age, and allows BMI to be expressed as an exact centile or age-and-sex specific SD score relative to a reference population. It can also be used to calculate a standardised measure of the difference between an individual’s BMI SD Score at two ages, using a model published by Cole in 1997 [31].

It appears that using BMI as a simple proxy or surrogate measure of body composition presents fewer problems with children and adolescents than with adults. The Centers for Disease Control and Prevention website tells us that

“BMI is a reliable indicator of body fatness for most children and teens” [32].

Additionally, Dietz and Bellizzi state that “the body mass index (BMI; in kg/m²) offered a reasonable measure with which to assess fatness in children and adolescents” [33]. Many researchers, however, disagree with these ideas, and conclude that BMI is not the most effective method of determining body composition [34]. While the issue of increased lean mass may not be such a problem during the early stages of life, covariates such as age, gender and race should be taken into consideration when interpreting BMI as a measure of obesity-related health risk in children [26].

There do exist some alternatives to BMI, such as the Rohrer Index (RI):

RI = weight(kg)

height(m)³ (1.4)

As with BMI, the Rohrer Index is classified for children using RI-for-age charts (although these do not appear to be publicly available). However, while BMI is widely used in practice, RI does not appear to be. Mei et al (2002) found that, of weight-for-height, BMI and RI, the latter was the least reliable [25].

Other widely used proxy indicators of adiposity in both adults and children are measures based on circumference. These measures include the waist-to-hip ratio, waist circumference, and the conicity index [35].

The waist-to-hip ratio (WHR) is calculated as

circumference of the waist

circumference of the hips (1.5)

For adults, it is generally accepted that a ratio of below 0.8 is healthy for women, and below 1.0 is healthy for men [36]. A ratio higher than these may indicate that the individual concerned is at an increased risk of cardio-vascular illness. Taylor et al (1998) found that WHR is not as effective at assessing body composition as BMI [37], while some other researchers and medical professionals consider WHR to be very useful in adults for determin-ing risk of cardiovascular illness resultdetermin-ing from excess abdominal adiposity [38]. Alternative (though not as widely used) ratios are waist-to-height and waist-to-arm. WHR and other such ratios are not widely used to determine adiposity in children.

Calculating waist circumference (WC) alone generally seems to be more ef-fective as a gauge of truncal adiposity than WHR in adults [34] and has also been accepted for use with children [35]. Chan et al [34] consider WC to be a more effective measure of abdominal fat than both WHR and BMI - with neither adding any significance to predictions abdominal fat from WC.

Current guidelines for WC in adult men are increased risk at 94cm and sub-stantially increased risk at 104cm. For women, increased risk is considered to be 80cm with 88cm indicating substantially increased risk. However, it seems unlikely that a man of height 200cm with a waist circumference of 94cm would be at the same level of risk as a man of height 165cm with the same waist measurement. For children, risk determined by waist circumference, as with BMI, is determined using age-and-sex specific population percentiles.

In an editor’s note to a 2004 paper by Fernández et al [39], it is stated that those children with WCs above the 90th percentile (adjusted for age, sex and ethnicity) could be considered at significant risk for obesity-related co-morbidities. However, there does not appear to be a widely accepted cut-off point.

Developed by Dr. Margaret Ashwell, the Ashwell chart (suitable for both male and female adults) [40, 41] adjusts waist circumference for height in order to assess health risk from abdominal adiposity. Some research has been carried out assessing the potential for similar charts for children and adolescents [42] but these do not appear to be widely used in medical practice.

The conicity index [35, 43] uses waist circumference adjusted for height and weight to determine body composition from the formula shown in equation (1.6).

Findings published by Taylor et al in 2000 show that the conicity index, too, is not as effective as WC alone at highlighting the potential problems and risks of overweight or obesity. [35]

The surrogate measures of body composition presented so far are relatively straightforward to obtain and can be used by either skilled professionals in a clinical setting or people at home (though individuals should be trained to be able to get accurate height and weight measurements). However, the interpretation on the individual level in terms of actual body composition - that is, proportions of fat and fat-free mass in the body - is extremely vague. While they provide some idea of whether or not an individual may be relatively underweight or overweight, or at particular risk of cardiovascular illness, they don’t give a precise measure of actual body fatness. It would perhaps be sensible to make use of a combination of measures such as BMI and WC where actual measures (to be discussed) of the distribution of body fat itself are not available.