Resting Energy Expenditure in a Controlled Group of Young Arab Females: Correlations with Body Composition and Agreement with Prediction Equations


Objectives: To assess correlates of body compositions measures and resting energy expenditure (REE) in young Arab females, and to compare measured REE values with values calculated from REE predictive equations. Methods: Seventy nine healthy women, aged 18 - 30 years, were recruited for the study. All volunteers fasted for 8 hours, abstained from vigorous physical activity, smoking and caffeinated beverages for twelve hours before measuring body composition and REE. Resting energy expenditure was measured by indirect calorimetry and body composition was measured by a bioelectrical impedance analysis. Results: Measured-REE was significantly correlated with body fat mass, fat free mass, skeletal muscle mass, and soft lean mass (R2 ranges 0.498 - 0.592; p < 0.001). Fat-free mass had the highest correlation with measured REE (0.592). Resting energy expenditure predicted by Harris-Benedict equation was significantly higher (+90.2 kcal, p < 0.001), and REE predicted by Owen equation was significantly lower (?101.9 kcal, p < 0.001) compared to measured REE. Measured REE was not significantly different from REE predicted by either Mifflin equation or WHO/FAO/UNU equation (p > 0.05). Mean measured REE varied significantly with BMI (p < 0.001), but not with age or ethnic background. Conclusion: All body composition measures were significantly correlated with REE measured. Mifflin-St. Jeor equation showed the closest estimate to the measured REE in predicting REE of participants who had a normal weight or were overweight. Harris-Benedict equation significantly overestimated REE and Owen significantly underestimated REE.

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A. Hassan, A. Mahdi, L. Hamade, A. Kerkadi and A. Yousif, "Resting Energy Expenditure in a Controlled Group of Young Arab Females: Correlations with Body Composition and Agreement with Prediction Equations," Food and Nutrition Sciences, Vol. 4 No. 4, 2013, pp. 385-391. doi: 10.4236/fns.2013.44049.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] L. K. Mahan and S. Escott-Stump, “Krause’s Food, Nu trition, and Diet Therapy,” 10th Edition, W.B. Saunders, Philadelphia, 2000.
[2] M. Johnstone, S. D. Murison, J. S. Duncan, K. A. Rance and J. R. Speakman, “Factors Influencing Variation in Basal Metabolic Rate Include Fat-Free Mass, Fat Mass, Age, and Circulating Thyroxine but Not Sex, Circulating Leptin, or Triiodothyronine,” American Journal of Clinical Nutrition, Vol. 81, No. 4, 2005, pp. 941-948.
[3] C. Compher, D. Frankenfield, N. Keim N and L. Roth Yousey, “Best Practice Methods to Apply to Measurement of Resting Metabolic Rate in Adults: A Systematic Review,” Journal of the American Dietetic Association, Vol. 106, No. 6, 2006, pp. 881-903. doi:10.1016/j.jada.2006.02.009
[4] Stanford University, “Measuring Energy Expenditure,” 2006.
[5] R. D. Lee and D. C. Nieman, “Nutritional Assessment,” 5th Edition, McGraw-Hill Incorporation, New York, 2010.
[6] J. A. Harris and F. G. Benedict, “Biometric Study of Basal Metabolism in Man,” Carnegie Institute of Washing ton, Washington DC, 1919.
[7] M. D. Mifflin, S. T. St Jeor and L. A. Hill, “A New Predictive Equation for Resting Energy Expenditure in Heal thy Individuals,” American Journal of Clinical Nutrition, Vol. 51, No. 2, 1990, pp. 241-247.
[8] World Health Organization, “Report of a Joint FAO/ WHO/UNU Expert Consultation,” Technical Report Series 724, World Health Organization, Geneva, 1985.
[9] O. E. Owen, E. Kavle and R. S. Owen, “A Reappraisal of Caloric Requirements in Healthy Women,” American Journal of Clinical Nutrition, Vol. 44, No. 1, 1986, pp. 1-19.
[10] D. C. Nieman, G. A. Trone and M. D. Austin, “A New Handheld Device for Measuring Resting Metabolic Rate and Oxygen Consumption,” Journal of the American Dietetic Association, Vol. 103, No. 5, 2003, pp. 588-593. doi:10.1053/jada.2003.50116
[11] D. C. Nieman, M. D. Austin, L. Benezra, S. Pearce, T. McInnis, J. Unick and S. T. Gross, “Validation of Cosmed’s FitMate in Measuring Oxygen Consumption and Estimating Resting Metabolic Rate,” Research in Sports Medicine, Vol. 14, No. 2, 2006, pp. 89-96. doi:10.1080/15438620600651512
[12] C. Douglas, J. Lawrence, N. Bush, R. Oster, B. Gower and B. Darnell, “Ability of the Harris-Benedict Formula to Predict Energy Requirements Differs with Weight History and Ethnicity,” Nutrition Research, Vol. 27, No. 4, 2007, pp. 194-199. doi:10.1016/j.nutres.2007.01.016
[13] C. L. De La Torre, F. A. Ramírez-Marrero, L. R. Martínez and C. Nevárez, “Predicting Resting Energy Expenditure in Healthy Puerto Rican Adults,” Journal of the American Dietetic Association, Vol. 110, No. 10, 2010, pp. 1523-1526. doi:10.1016/j.jada.2010.07.006
[14] R. Hasson, C. Howeb, B. Jones and P Freedson, “Accuracy of Four Resting Metabolic Rate Prediction Equations: Effects of Sex, Body Mass Index, Age, and Race/Ethnicity,” Journal of Science and Medicine in Sport, Vol. 14, No. 4, 2011, pp. 344-351. doi:10.1016/j.jsams.2011.02.010
[15] D. R. Taaffe, J. Thompson, G. Butterfield and R. Marcus, “Accuracy of Equations to Predict Basal Metabolic Rate in Older Women,” Journal of the American Dietetic Association, Vol. 95, No. 12, 1995, pp. 1387-1392. doi:10.1016/S0002-8223(95)00366-5
[16] P. J. Arciero, M. A. Goran, A. M. Gardner, P. A. Andes, R. S. Tyzber and E. T. Poehlman, “A Practical Equation to Predict Resting Metabolic Rate on Older Females,” Journal of the American Geriatric Society, Vol. 41, No. 4, 1993, pp. 395-398.
[17] J. J. Cunningham, “Body Composition as a Determinant of Energy Expenditure: A Synthetic Review and a Proposed General Prediction Equation,” American Journal of Clinical Nutrition, Vol. 54, No. 4, 1991, pp. 963-969.
[18] D. Frankenfield, L. Roth-Yousey and C. Compher, “Comparison of Predictive Equations for Resting Metabolic Rate in Healthy Nonobese and Obese Adults a Systematic Review,” Journal of the American Dietetic Association, Vol. 105, No. 5, 2005, pp. 775-789. doi:10.1016/j.jada.2005.02.005
[19] G. Rodriguez, L. A. Moreno, J. Fleta and M. Buena, “Resting Energy Expenditure in Children and Adolescents: Agreement between Calorimetry and Prediction Equations,” Clinical Nutrition, Vol. 21, No. 3, 2002, pp. 255-260. doi:10.1054/clnu.2001.0531
[20] D. C. Frankenfield, E. R. Muth and W. A. Rowe, “The Harris-Benedict Studies of Human Basal Metabolism: History and Limitations,” Journal of the American Dietetic Association, Vol. 98, No. 4, 1998, pp. 439-445. doi:10.1016/S0002-8223(98)00100-X
[21] S. Heshka, K. Feld, M. Yang, D. B. Allison and S. B. Heymsfield, “Resting Energy Expenditure in the Obese: A Cross-Validation and Comparison of Prediction Equations,” Journal of the American Dietetic Association, Vol. 93, No. 9, 1993, pp. 1031-1036. doi:10.1016/0002-8223(93)92043-W
[22] J. M. Daly, S. B. Heymsfield, C. A. Head, L. B. Harvey, D. W. Nixon, H. Katzeff and G. D. Grossman, “Human Energy Requirements: Overestimation by Widely Used Prediction Equation,” Journal of the American Dietetic Association, Vol. 42, No. 8, 2006, pp. 1170-1174.

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