A new predictive equation for resting energy expenditure in healthy individuals

Abstract

A predictive equation for resting energy expenditure (REE) was derived from data from 498 healthy subjects, including females (n = 247) and males (n = 251), aged 19-78 y (45 +/- 14 y, mean +/- SD). Normal-weight (n = 264) and obese (n = 234) individuals were studied and REE was measured by indirect calorimetry. Multiple-regression analyses were employed to drive relationships between REE and weight, height, and age for both men and women (R2 = 0.71): REE = 9.99 x weight + 6.25 x height - 4.92 x age + 166 x sex (males, 1; females, 0) - 161. Simplification of this formula and separation by sex did not affect its predictive value: REE (males) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) + 5; REE (females) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) - 161. The inclusion of relative body weight and body-weight distribution did not significantly improve the predictive value of these equations. The Harris-Benedict Equations derived in 1919 overestimated measured REE by 5% (p less than 0.01). Fat-free mass (FFM) was the best single predictor of REE (R2 = 0.64): REE = 19.7 x FFM + 413. Weight also was closely correlated with REE (R2 = 0.56): REE = 15.1 x weight + 371.

Variation in the application of methods used for predicting energy requirements in acutely ill adult patients: a survey of practice

“…This result is similar to other studies, which have compared this prediction method with measured BMR, showing that predictions underestimated true requirements (Hunter et al, 1988;Ahmad et al, 1999). Studies comparing measured BMR to BMR predicted by the Harris-Benedict equations in healthy adults have indicated that the equations consistently overestimate requirements, ranging from 104.8 to 113.5% (Daly et al, 1985;Owen et al, 1986Owen et al, , 1987Foster et al, 1988;Mifflin et al, 1990;Case et al, 1997). Few studies have compared the use of the Schofield equations in healthy adults.…”

“…The importance of estimating energy requirements has been well documented and many researchers have attempted to develop prediction equations for use when direct measurement is not possible (Harris & Benedict, 1919;Schofield, 1985;Owen et al, 1986Owen et al, , 1987Mifflin et al, 1990;Vinken et al, 1999). This study aimed to determine current methods used by Australian dietitians for estimating energy requirements of patients and the variability of the outcomes of the calculations.…”

“…Measurement of energy expenditure is the most accurate method for determining energy requirements (Jequier & Schutz, 1983;Soares et al, 1989;Coss-Bu et al, 1998;Flancbaum et al, 1999). These methods, however, are difficult in the clinical setting as they are expensive, have long measurement times, require trained personnel to perform them and are impractical (Mifflin et al, 1990;Flancbaum et al, 1999). Instead, energy requirements are generally estimated by predicting basal metabolic rate (BMR) from equations derived for healthy populations and adjusting for illness by including an injury factor and additional energy for activity.…”

“…Prediction equations are commonly used by dietitians to estimate patients' energy requirements (Schofield, 1985;Owen et al, 1986Owen et al, , 1987Mifflin et al, 1990;Vinken et al, 1999). Although practical and easy to use, the accuracy of these equations is questionable.…”

Mechanisms of changes in basal metabolism during ageing

“…Figure 2 shows the scatter diagrams redrawn from the publication A Biometric Study of Basal Metabolism in Man (1919). Despite the limited number of subjects older than 50 y, the simplicity of the Harris ± Benedict equation made it a popular equation widely used even today by many clinicians in North America (Daly et al, 1985;Roza & Shizgal, 1984;Mif¯in et al, 1990). Harris and Benedict (1919) …”