Predictive equations to estimate bmrs of adults

BMR can be accurately measured by direct or indirect calorimetry, but it is simpler, in practice, to use predictive equations. By 1951, a plethora of equations to predict BMR were in existence, some easier to use than others. The predictive equations of Aub & Du Bois (1917) tended to over-estimate BMR, as the subjects measured by these authors were under thermal stress and anxious. In contrast, Robertson & Reid's equations (1952) underestimated BMR, as they were based on the lowest recorded values of metabolic rate. Finally, while Quenouille's analysis (Quenouille et al, 1951) was comprehensive, the equations were too complicated to be of routine practical use. Recently Schofield (1985), published predictive equations that were used for the FAO/WHO/UNU report (1985) and thereby became the basis for estimating energy requirements in man.

The Schofield analysis and equations, based on a database of 114 published studies of BMR, representing 7173 data points, is the largest and most comprehensive analysis of BMR to date. While the Schofield equations predict BMR accurately in many individuals from temperate climates, they seem to be less accurate in predicting BMR in populations in the tropics (Henry & Rees, 1991; Piers & Shetty, 1993) and North America (Clark & Hoffer, 1991) and appear to over-estimate BMR in many populations (Piers & Shetty, 1993; Soares, Francis & Shetty, 1993; Hayter & Henry, 1993).

Table 6 List of Italian subjects used in the database of Schofield

Study	n	Sex	Age	Subject details
Pepe & Rinaldi (1936)	217	M	6-16	None provided
	143	F	5-12	None provided
Pepe & Perrelli (1937)	257	M	5-16	None provided
	235	F	5-12	None provided
Felloni (1936)	532	M	19-25	Students of the Royal Fascist Academy
Lafralla (1937)	213	M	14-20	Students of Naples Royal Military College
Lenti (1937)	525	M	20-25	Military Servicemen
Pepe (1938)	252	M	18-24	Students of Royal Naval Academy
Occhiolo & Pepe (1939)	247	F	20-67	Various social groups
Occhiulo & Pepe (1940)	571	M	22-54	Police officers
Granall & Busca (1941-1942)	186	M	16-55	Labourers and miners
Total	3370

All references in Schofield, Schofield & James (1985).

There are several reasons to suggest that there is a need to re-analyse the worldwide data on BMR using stringent inclusion criteria in order to generate more valid equations to predict BMR in humans worldwide.

(1) Schofield collected data for his study a decade ago. Since then several laboratories have produced a large number of good quality BMR data for different age, sex and ethnic groups that also need to be included.
(2) Henry & Rees (1988) have identified over 1500 data points for Caucasian subjects in the old literature that meet all the strict criteria used by Schofield, but were not included; these values also need to be incorporated.
(3) Certain age groups (children and adults over 60) are under-represented, and these parts of the database need to be expanded in order to generate more reliable predictive equations for those age ranges.
(4) Close examination of the Schofield database (Table 6) shows that of the approximately 6000 BMR values for males between 10-60 years, over 3000 (50%) come from Italian military subjects. The validity of including such a disproportionate number of Italian military subjects may need to be queried, firstly, because the Italian group appears to have a higher BMR per kg than any other Caucasian group (Hayter & Henry, 1993), and secondly, because they may not be representative of the general Italian population. In fact Schofield (1985) noted that when Italians were isolated from the rest of the sample and compared with the derived BMR predictive equation there was a significant lack of fit. The inclusion of this disproportionately large Italian group with a higher BMR per kg may have artificially elevated the predictive equations generated by Schofield.
(5) If an analysis of the BMRs of people from the tropics and sub-tropics (Henry & Rees, 1991) points to a lower BMR than predicted by the Schofield equations, this may be due mainly to the bias imposed by the dominance of the Italian data. More recent data in fact support the view that BMRs of people in the tropics are not different from those in temperate regions (North America and Europe), provided the subjects are well nourished (Henry et al, 1987; Hayter, 1992; Soares, Francis & Shetty, 1993; Piers & Shetty, 1993).

There is thus mounting evidence to suggest that the Schofield equations may be overestimating BMR in many populations, leading to an over-estimation of their energy requirements. This has both practical and political implications. In the light of this, a critical reassessment of the worldwide data on BMR is required.

Figure 1 Linear least square regression lines of basal metabolic rates (MJ/d) on body weight of males (A) and females (B) of Indian, Chinese, North European and North American and Italian groups.

Figure 1 Linear least square regression lines of basal metabolic rates (MJ/d) on body weight of males (A) and females (B) of Indian, Chinese, North European and North American and Italian groups.