Body fat and adipose tissue are considered to have bene®cial effects when they promote or protect the present and future function. These effects do not occur at absolute amounts or percentages of the body weight but rather they are context speci®c. Body fat stores are the major energy stores of the body and are important determinants of survival in starvation or undernutrition. Reproduction features highly as a biological function. Humans are alone in having major sex-speci®c fat stores and patterns of fat distribution 1 and these have been linked with the onset and maintenance of menstruation, with mate selection and sexual signalling, and with favourable pregnancy and lactation outcomes. To survive and reproduce good physical and psychological health are advantageous attributes. Work metabolism, bone health and, possibly immune function and energy balance itself, are related in functionally bene®cial ways to fat content and distribution.

The effect of overfeeding on the body weight, body fat, water content, energy expenditure, and digestibility of energy and nitrogen was investigated over 42 days in six young men. The metabolic rates in standard situations of work and rest were determined. Energy intakes were apparently increased by 6.2 MJ/day and energy expenditure fell slightly by 0.3 MG/day during overfeeding. Fecal and urinary losses of energy were a similar proportion of the gross energy intake in control and overfeeding periods (8%). Metabolizable energy intakes calculated from food tables agreed well with values derived from digestibility measurements in the control period (mean difference = +2%) but not in the overfeeding period (+8%). The implications of this are discussed. Mean body weight gain was 6.0 kg, 10% of initial weight; mean fat gain was 3.7 kg and water gain 1.8 liter. There were considerable interindividual differences in the weight and fat gain for a given excess energy intake. Metabolic rates in standard tasks were 10% higher at the end of overfeeding but expressed as kilojoules per kilogram per minute were similar to control values. Mean energy gain (144 MJ = fat gain X 39 kJ/g) was less than excess energy intake even allowing for overestimation of intakes using food tables and increases in metabolic rate. Such a discrepancy is unlikely to be due to unmeasured increases in metabolic rate but could have arisen from errors in the calculation of the variables involved. In this study where moderate weight gains were achieved by overfeeding mainly fat, increases in metabolic rate appear to be associated with increased body size and tissue gain rather than a luxuskonsumption mechanism.

Objective: This background paper was prepared in response to a request to review the concepts related to measurement of body composition, to discuss laboratory and field methods of assessing body composition and to discuss the practical applications of the methods -how they might be used singly or in combination to provide data for a selected population. Design: The common laboratory and field methods are described and discussed, with particular attention to the assumptions involved and the applicability of the methods to the different population groups. Most measurements of body composition are made in the field, at the bedside or clinic as opposed to in the laboratory. The laboratory methods have a role to play in their own right, in research into new concepts, models and methods. However, they are particularly important in establishing the accuracy of the field methods. Setting: Field, bedside and laboratory studies. Subjects: Children, adults, the elderly, ethnic groups. Results: Laboratory estimates of body compositions are best performed by multicomponent methods or by 2-component methods adjusted for to the populations under investigation. There is a scarcity of data for most of the populations in the world. Conclusions: Energy requirements based on body weight are an approximation since they do not take into account differences in body composition, which will better determine the true requirements. The measurement of body composition occurs in many branches of biology and medicine. It is used in the assessment of nutritional and growth status and in disease states and their treatment. Energy stores, skeletal muscle and protein content can be determined and changes monitored. In human energetics, body composition is widely used for the standardisation of other variables, such as basal metabolic rate (BMR), in the assessments of ethnic and environmental differences and of variability and adaptation to different levels of nutrition. Choosing a method is very problematic. Users want simple, inexpensive, rapid, safe accurate methods to measure body composition but speed and simplicity come at the expense of accuracy. Recommendations are made for age, sex, and in some cases, fatness and ethnic specific methods. Keywords Body compositionAnthropometry Children Adults Elderly Ethnicity Models and concepts in body composition'Any student of body composition must master terminology and the concepts of validation scales for assessing the effectiveness of new methods, new methods to assess regional as well as total body composition, and the need for population specific equations. Lack of understanding these concepts has hindered the development of the field.' 1 It is true to say that how we have viewed the body has been determined by the methods that have been available. If we can measure one component of body composition such as fat mass (FM), we can describe the body in terms of a 2-component model (2-C model) of FM and fat free mass (FFM). This was the earliest attempt at describing in vivo body compositio...

The body mass index (BMI) is being used widely as an index of overweight and undernutrition. The effects of variations of shape as evinced by relative sitting height (sitting height/stature, SH/S) on BMI were determined using mean data from 95 samples of men and 63 samples of women of non-European origin, representing 18,000 individuals. The linear regression coefficients of BMI on SH/S (b +/- standard error) were 0.78 +/- 0.16 (t = 4.8) in men and 1.19 +/- 0.22 (t = 5.3) in women. Correlations coefficients were 0.45 and 0.56, respectively. These regression coefficients compare with a predicted change of 0.9 kg/m2 per 0.01 difference in SH/S using a modelling approach. The wide variation within and between populations precludes a simple adjustment for SH/S, and in the interpretation of BMI additional anthropometric measurements may be necessary.

Low body mass index (BMI, kg/m2) has been proposed as a practical measure of energy undernutrition although it has some well-known limitations. Some reports have suggested that those Australian Aborigines living a largely traditional way of life have low BMI without compromised health status and may have paradoxically high levels of subcutaneous adipose tissue. The evidence for low BMI in Australian Aborigines is reviewed from the mean data of 1,174 individuals in 26 groups of adults and from the individual data of 349 of these individuals, collected before 1970. Three of the nine groups of women had mean BMI less than 18.5 kg/m2 and 4% of the individual men and 14% of the individual women had values less than 16 kg/m2, a value regarded as indicating severe chronic energy deficiency. Skinfold thicknesses were greater than expected from the BMI, suggesting paradoxically high subcutaneous fatness. The contribution of long-leggedness to low BMI was estimated from the regression of BMI on the sitting height to stature ratio (SH/S). For the 26 groups, this was estimated to be 2 kg/m2, r2 = 31%. The relationship was weaker with the individual data, r2 = 15%. Body shape as evinced by low SH/S does contribute to low BMI in these Australian Aborigines. Single cut-offs of BMI are not applicable to all population groups and allowance may have to be made for body form when using BMI to assess nutritional status.