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Points of uncertainty requiring further research

1. Re-analysis of BMR

The critical importance of BMR to the estimation of energy requirements and the fact that the present equations may be less than ideal and do not include the significant addition to the literature from studies in recent years in developing countries, make it desirable that the whole literature on BMR should be critically reexamined. The reassessment should also consider the emphasis (or lack of emphasis) which can be placed on relatively small differences in energy requirements in the light of the degree of variability between individuals. Indeed, the whole interpretation which can be put on population differences in calculated energy requirements needs to be re-examined.

2. Maintenance requirement

Deciding on the precise value to be attached to the 'maintenance' requirement is a topic with some potential for confused discussion; i.e. whether multiplying BMR by 1.2, 1.3, 1.4 or even more, might be interpreted as signifying unacceptably low energy requirements.

A 'realistic' maintenance factor is one which makes a reasonable allowance for the various essentials in a normal life-style, but does not include anything more than a minimum amount of physical activity. 'Activity' would be restricted to the purchase of food, cooking, washing-up, and keeping the household in moderate order, washing and dressing. The speculative value for this level of activity is 1.4 × BMR. A lower level than this 'maintenance', which has teen termed as 'survival' value, involves only minimal movement about the house for very limited periods of time, with the suggested value of 1.2 × BMR; it is incompatible with long-term cardiovascular fitness.

If these values accurately reflect a certain type of lifestyle, the practical implications, translated into the possible duration and type of physical activity, are illustrated in the following two tables relevant to a housewife with a body mass of 50 kg.

An average woman of 50 kg will have a BMR of 1260 kcal (5.27 MJ) (Table 2) per day. If BMR × 1.4 is taken as representing the energy requirement, this gives a value of 1764 kcal (7.38 MJ), i.e. 1260 × 1.4 kcal. Diet induced thermogenesis (DIT) of about 10% will represent 176 kJ. The energy available for physical activity is thus 1764 (total energy requirement) minus 1260 (BMR) minus DIT (176 kcal), leaving a total of 328 kcal (1.3 MJ).

If it is hypothesized that a minimum amount of physical activity might require, say, (1) 3.5 h of 'standing' and (2) 2 h of 'housework', 'preparing food and cooking', 'looking after the children', etc. this would cost, in energy terms,

210 (i.e. 3.5 h) × 0.5 kcal = 105 kcal (440 kJ)a (1)
120 (2 h) × 1.5 kcal = 180 kcal (756 kJ)b (2)

where: a the value for 'standing' has been taken as 0.5 kcal/min above BMR; b the value for housework, etc. has been taken as 1.5 kcal/min above BMR.

Table 2 'Activity' of an individual whose energy expenditure is equivalent to BMR × 1.4

BMR for 50 kg woman = 1260 kcal/d (5.27 MJ)
Therefore BMR × 1.4 = 1764 kcal/d (7.38 MJ)
DIT at 10% of intake = 176 kcal/d (736 kJ)

Total energy intake (1764) - BMR (1260) - DIT = 328 kcal, i.e. 328 kcal/d (1.3 MJ) for all other activities


210 min [approx 3.5 h] standing:
at 0.5 kcal/min over BMR = 105 kcal (440 kJ)

2 h housework:
at 1.5 kcal/min over BMR = 180 kcal (756 kJ)
remainder is 43 kcal (180 kJ), as 15 min walking

i.e. average day's activity:
2 h housework
15 min walking
3.5 h quiet standing
slightly more than 18 h Iying down or sitting quietly

The energy left over for physical activity is therefore 1764-1260-176-105-180=43 kcal (180 kJ).

This quantity of energy would allow about 15 min of slowish walking. The average day for such a woman would consist therefore of 2 h housework, 3.5 h of quiet standing, 15 min walking, and 18 h of lying down or sitting quietly: there is not even any allowance for work outside the home.

The pattern certainly looks anything but typical for a 50 kg woman on an energy intake of 1.4 × BMR; yet that level of energy intake would not be unusual as far as published data are concerned.

At the lower 'survival' level of 1.2 × BMR, a similar table can be reproduced, again using a 50 kg housewife for an example (Table 3).

The BMR of an average woman of 50 kg equals 1260 kcal/d (5.27 MJ), then 1.2 × BMR equals 1512 kcal/d (6.33 MJ). The energy required for DIT is approximately 10% of the total energy intake, i.e. 10% of 1512 or 150 kcal/d (628 kJ). Therefore, the energy left over for all the physical activity of the day is the total energy intake (1512 kcal) minus BMR (1260 kcal) minus DIT (150 kcal), which comes to 102 kcal/d (427 kJ). This would be the equivalent of 204 min of an activity at an energy cost of 0.5 kcal/min over the BMR such as standing with little extraneous movement. That is, on an average day, this woman would have to remain lying down resting quietly for about 20.5 h in the day, and standing with little movement or walking around for the remaining 3.5 h. This certainly betokens a minimal existence and is not to be found in other than moribund populations (Durnin, 1990).

These illustrations of 'maintenance' and 'survival' levels of energy expenditure appear of limited applicability to normal populations. Even 1.4 × BMR which is sometimes suggested as betokening an acceptable level of energy expenditure, does not seem to be compatible with a normal healthy existence.

There seems little doubt about the comparative validity of these deductions. The BMR is a variable which, although usually calculated on the basis of a formula, is capable of being measured with a high degree of precision and reproducibility and the other values for energy expenditure - i.e. DIT, the energy of housework, standing, walking, etc.-are also reasonably valid.

It is therefore possible to estimate what the energy expenditure of an individual or a population would involve if the energy requirement were 1.4 × BMR, and we can conclude that the way of life represented by this value probably is unacceptable because of a very limited amount of physical activity.

Table 3 'Activity' of an individual whose energy expenditure is equivalent to BMR × 1.2

BMR for 50 kg woman = 1260 kcal (5.27 MJ)
Therefore BMR × 1.2 = 1512 kcal (6.83 MJ)
DIT at 10% of intake = (150 kcal), (628 kJ)

Total energy intake (1512) - BMR (1260) - DIT = 102 kcal (427 kJ)
i.e. 102 kcal available for activity

204 min × 0.5 kcal over BMR

i.e. average day's activity:
3.5 h of standing with little movement
20.5 h of lying down or sitting quietly

Since, theoretically, populations having energy requirements equivalent to 1.4 × BMR or less appear likely to be, from the examples quoted, in a state which is physiologically abnormal, investigation of this research problem is of high importance. Studies on apparently normal people whose energy intakes are low, need to be combined with measurements of energy expenditure (perhaps most usefully employing the doubly-labelled water method.) and monitoring activity patterns in order to obtain more definitive data on this enigma.

Summary of research needs

Suggestions have been made, at different places in the text of this paper, for further analyses or studies on various aspects of energy requirements. The different items are as follows:

BMR: A critical re-assessment of all the data is highly desirable. Particular attention needs to be given to the extent of intra- and inter-individual variability.

Physical activities: There is a need for further analysis and for more investigation into the energy cost of different activities. The confusing effect of uncertainty with regard to whether or not rest-pauses have been taken into account in the estimate of the energy cost of the different activities is discussed.

Doubly-labelled water: Its role is discussed briefly and a specific proposal is made in relation to its potential use in the investigation of the 'maintenance' factor, specifically applied to BMR and the activity factor in physically inactive populations.

Maintenance factors: The validity of some of these to real life situations are discussed with specific examples of practical implications of the factors 1.4 (for 'maintenance') and 1.2 (for 'survival').

Body mass and composition: It is doubtful if, within a fairly wide range of 'fatness' (but excluding the grossly obese), there is any real benefit in field situations from taking body composition into account, bearing in mind the extent of the variability of both BMR and total daily energy expenditure. In this context, because total body mass clearly has a considerable influence on energy expenditure, further studies of the effect of actual or desirable body mass are needed.

Population sample size: Because of the considerable variability in many aspects of energy metabolism, it is critical to have a sample size which has an acceptable statistical power and is reasonably representative of the particular variables being analysed. It is not scientifically admissible to make other than highly qualified deductions from data obtained on only small sample sizes. It is particularly depressing to read statements with sweeping generalizations about energy expenditure, which contradict data obtained on very large numbers of individuals by many experienced investigators, when the statements are based on findings on nine individuals (Haggarty et al, 1994).


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Since energy requirements are now preferentially derived from data on energy expenditure and expressed as multiples of BMR, most of the discussion dealt with issues related to BMR, the energy cost of physical activity, physical activity levels (PALs) and the factorial method.

Under the auspices of IDECG and with funding from the Nestle Foundation, all currently available BMR data meeting a set of stringent criteria are being reanalyzed under the supervision of Henry and Durnin. The conditions under which BMRs have to be measured were reemphasized. In some earlier studies these were as strictly observed as in more recent ones; publication date is therefore not necessarily a good screening criterion. One of the questions raised was how important it is that subjects sleep at the laboratory where their BMR is measured in the morning. Durnin cited several papers (Bullough & Melby, 1993; Soares et al, 1989; Turley et al, 1993) showing that this did not make any difference. In a group of elderly subjects, Berke et al (1992) even found a significantly higher metabolic rate when they slept in a metabolic ward, than when they slept at home before coming to the laboratory, probably because at the ward they had to sleep in an unfamiliar bed and in a foreign environment. When subjects are brought to the laboratory in the morning, the question arises as to how much resting time is required, before BMR is measured. According to Ferro-Luzzi, experiments have shown that 30 min are enough in persons who have not previously been engaged in heavy physical activity. The current analysis should provide answers to several issues discussed at the meeting and considered in need of further analysis and clarification. In particular it should enable to decide whether predictive equations can remain general or should be population-specific (taking into account ethnicity, geographic regions/climate or body composition), linear or non-linear (depending on which results in the smaller residual values), etc. The importance of taking height into consideration in predictive equations was briefly discussed. Apparently Schofield tested whether including height would make a difference in the prediction of group BMRs and found that it did not.

Even though large numbers of BMR data can be found in the literature, there are age and population groups for which an adequate data base does not yet seem to exist. Underrepresented groups are infants, children, the elderly and almost any age group from developing countries. For the establishment of predictive equations the overrepresentation of individuals with specific characteristics also needs to be avoided.

In his paper, Durnin cited several papers leading to the conclusion that the intra-individual variability of BMR in adults was in the order of 3%. Henry agreed with this figure for men, but argued that in women the menstrual cycle can increase this variability to 8-10%.

In his paper, Durnin expressed the view that, on a population basis and up to a moderate level of fatness (BMI < 30), there was nothing to be gained by expressing BMR per kg lean body mass rather than body weight. In the discussion, reference was made to Garby's work suggesting that most of the inter individual variability in BMR is probably attributable to differences in body composition and that the relative size of organs, which have a high metabolic rate can make a difference, notably in chronically undernourished individuals.

The question was raised, if there are ethnic or geographic differences in BMR. Butte et al studied BMRs of white and black adolescent girls in Houston. In absolute terms, black girls had lower BMRs, but the difference disappeared when the data were corrected for body composition. Sexual maturation is likely to affect body mass, body composition and BMR and may result in differences between adolescent girls going through menarche at different ages.

Shetty et al (1986) found that the Schofield equations overestimated BMRs in Indian subjects. Henry's equations made better predictions of BMRs of populations in tropical regions. In two recent papers (Soares et al, 1993; Piers & Shetty, 1993), Shetty's group documented that BMRs of well-nourished Indian subjects, normalized for body weight, do not differ from BMRs of American subjects, but they seem to differ from Schofield equations and BMRs of certain European populations. He imputed differences, reported in the literature, to differences in ambient temperature which may not have been taken sufficiently into account in earlier studies. Torun suggested that differences in body composition could also provide a partial explanation. On average, BMRs measured in tropical regions are 4-5% lower than BMRs measured in temperate zones.

Differences have also been observed in the same subjects, measured in temperate and tropical regions. Henry suggested that such differences could be due to weight loss or disease. Shetty referred to a study by Mason (1944) who found changes in BMR, even when the latter was normalized for body weight.

A research assistant, under the supervision of Shetty and Durnin, is re-analyzing the information that is currently available on the energy cost of various activities.

The issue as to whether and how much of an energy allowance ought to be made for discretionary activities was discussed at some length. To maintain physical fitness and promote cardiovascular health, the 1985 FAO/WHO/UNU report recommended 20 min of vigorous exercise per day to adults with a sedentary life style and included in its recommendations the energy required for this exercise. Most of the discussants agreed with Durnin that there was only very little scientific evidence relating different levels of physical activity to health, but, for various reasons, the majority felt that these earlier recommendations should nevertheless be maintained.

Prentice collected and analyzed nearly 1000 data on total energy expenditure obtained with the doubly labeled water (DLW) method. More than half of these studies included also BMR measurements, so that PAL factors could be calculated and compared with PAL values obtained with other methods. Only few, mostly institutionalized individuals have PALs below 1.4, but, on average most PAL values obtained with DLW appear somewhat higher than expected and than contained in previous reports. UK dietary reference values, for instance, had assumed that a PAL of 1.4 was representative of light, 1.6 of moderate and 1.7 of heavy occupational activity in an otherwise non-active, non-occupational life style. Average PALs of sedentary people obtained by the DLW method correspond to values that were considered representative of a moderately active life style. Some of the highest values (2.42.6) look suspect because, according to PALs obtained from calorimetry, they presuppose that people spend a considerable amount of time at 70-80% of VO2 max which happens only rarely in real life. It has to be acknowledged (and perhaps provides a partial explanation) that the representativeness and generalizability of the DLW data obtained till now are limited.

The group recognized that injuries and various diseases can affect energy requirements, but was not prepared to deal with such special situations in detail. It recommended a compilation and analysis of information that is currently available in this area, but expressed a preference for presenting such information separately.


Berke EM, Gardener AW, Goran MI & Poehlman ET (1992): Resting metabolic rate and the influence of the pretesting environment. Am. J. Clin. Nutr. 55, 626-629.

Bullough RC & Melby CL (1993): Effect of inpatient vs outpatient measurement protocol on resting metabolic rate and respiratory exchange ratio. Ann. Nutr. Metabol. 37, 24-32.

Mason ED (1944): Daily measurements of basal metabolism, body temperature and pulse rate during a journey to the tropics. Indian. J. Med. Res. 32, 27-30.

Piers LS, Shetty, PS (1993): Basal metabolic rates of Indian women. Eur. J. Clin. Nutr. 47, 586-591.

Shetty PS, Soares MJ, Sheela ML (1986): Basal metabolic rates of South Indian males. Report to FAO, Rome.

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Turley KR, McBride PJ, Wilmore JH (1993): Resting metabolic rate measured after subjects spent the night at home us at a clinic. Am. J. Clin. Nutr. 58, 141-144.

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