The Indian Journal of Nutrition and Dietetics

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Resting Metabolic Rate of Junior National Weightlifters in India:Development and Validation of Prediction Models


Affiliations
1 Department of Work Physiology and Sports Nutrition, Indian Council of Medical Research, Ministry of Health and Family Welfare, Government of India, Jamai-Osmania, Hyderabad, Telangana-500 007, India
2 Biostatistics Division, National Institute of Nutrition, Indian Council of Medical Research, Ministry of Health and Family Welfare, Government of India, Jamai-Osmania, Hyderabad, Telangana-500 007, India
     

   Subscribe/Renew Journal


Weightlifters involve in intense strength and resistance training, thus calorie adequacy is a nutritional concern for them. Determining Resting Metabolic rate (RMR) is important to assess energy needs and there is limited scientific evidence in this area. Thus, this study aims to document physical characteristics and RMR of Indian junior weightlifters. It also attempts to identify suitable RMR prediction equations by developing new equations and comparing measured with predicted RMR from seven equations already existing world-wide. In this cross-sectional observation study, twenty one Indian junior weightlifters (Boys = 9; Girls = 12) were assessed for body composition (skinfold technique) and RMR using indirect calorimetry. Regression models for RMR were developed and measured RMR was compared with predicted RMR using paired samples t-test. The 24-hour RMR showed significant (P<0.01) gender differences (Boys = 1675 ± 111.7; Girls = 1425 ± 93.4), whereas, RMR per unit fat-free mass and body mass were similar across gender. The simple equation developed using body mass (RMR = 1206 + 13 × Body Mass (Kg) – 227.7 × Gender; R2 = 0.872; SEE = 60.604) showed good agreement with measured RMR. Out of seven existing RMR models, the equation of ten Haaf and Weijs (2014) showed better predictability. In conclusion, fat-free mass caused a major variation in RMR. Considering the limited scientific evidence, prediction equations newly developed and RMR equation of ten Haaf and Weijs (2014) can be used for periodical monitoring of RMR.

Keywords

Basal Metabolic Rate, Energy Expenditure, Body Composition, Indirect Calorimetry, Strength Athletes.
User
Notifications

  • Wong, J.E., Poh, B.K., Nik Shanita, S., Izham, M.M., Chan, K.Q., Tai, M.D. et al. Predicting basal metabolic rates in Malaysian adult elite athletes. Singapore Med. J., 2012, 53(11), 744.

  • Bass, S. and Inge, K. Nutrition for Special populations: Children and Young Athletes. Clinical Sports Nutrition; Burke, L.M., Deakin, V., Eds. 2006, 589-632.

  • Meyer, F., O’Connor, H. and Shirreffs, S.M. Nutrition for the young athlete. J. Sports Sci. 2007, 25 (S1), S73-S82.

  • Shetty, P. Energy requirements of adults: an update on basal metabolic rates (BMRs) and physical activity levels (PALs). Eur. J. Clin. Nutr. 1996, 50(1), S11-S23.

  • Cunningham, J.J. A reanalysis of the factors influencing basal metabolic rate in normal adults. Am. J. Clin. Nutr. 1980, 33(11), 2372-4.

  • Manore, M. and Thompson, J. Energy requirements of the athlete: assessment and evidence of energy efficiency. Clin. Sports Nutr. 2006, 3, 113-134.

  • Ribeyre, J., Fellmann, N., Montaurier, C., Delaître, M., Vernet, J. and Coudert, J. et al. Daily energy expenditure and its main components as measured by whole-body indirect calorimetry in athletic and non-athletic adolescents. Br. J. Nutr. 20008, 3(4), 355-362.

  • Burke, L., Read, R. and Gollan, R. Australian Rules football: an anthropometric study of participants. Br. J. Sports Med., 1985, 19(2), 100-102.

  • Ramana, Y.V. Energy requirements of Indian athletes in various sports. Br. J. Sports Med., 2010, 44(Suppl 1), i40-i.

  • Slater, G. and Phillips, S.M. Nutrition guidelines for strength sports: sprinting, weightlifting, throwing events, and bodybuilding. J. Sports Sci., 2011, 29(sup1), S67-S77.

  • Burke, L.M., Slater, G., Broad, E.M., Haukka, J., Modulon, S. and Hopkins, W.G. Eating patterns and meal frequency of elite Australian athletes. Int. J. Sport Nutr. Exerc. Metab., 2003, 13(4), 521-538.

  • Heymsfield, S.B., Chirachariyavej, T., Rhyu, I.J., Roongpisuthipong, C., Heo, M. and Pietrobelli, A. Differences between brain mass and body weight scaling to height: potential mechanism of reduced mass-specific resting energy expenditure of taller adults. J. Appl. Physiol., 2009, 106(1), 40-48.

  • Henry, C. Basal metabolic rate studies in humans: measurement and development of new equations. Public Health Nutr. 2005, 8(7a), 1133-1152.

  • Schofield, W. Predicting basal metabolic rate, new standards and review of previous work. Human nutrition Clinical nutrition. 1985, 39, 5-41.

  • Rao, B.N. Nutrient requirement and safe dietary intake for Indians. Bull.Nutr. Found.Ind., 2010, 31(1).

  • De Lorenzo, A., Bertini, I., Candeloro, N. and Piccinelli, R. A new predictive equation to calculate resting metabolic rate in athletes. J. Sports Med. Phys. Fitness., 1999, 39(3), 213.

  • ten Haaf, T. and Weijs, P.J. Resting energy expenditure prediction in recreational athletes of 18–35 years: confirmation of Cunningham equation and an improved weight-based alternative. PloS one. 2014, 9(10), e108460.

  • Durnin, J. and Rahaman, M.M. The assessment of the amount of fat in the human body from measurements of skinfold thickness. Br. J. Nutr., 1967, 21(03), 681-689.

  • Siri, W.E. The gross composition of the body. Adv. Biol. Med. Phys., 1956, 4(239-279), 513.

  • Cherian, K.S., Shahkar, F., Sainoji, A., Balakrishna, N. and Yagnambhatt, V.R. Resting metabolic rate of Indian Junior Soccer players: Testing agreement between measured versus selected predictive equations. Am. J. Hum. Biol., 2017.

  • Storey, A. and Smith, H.K. Unique aspects of competitive weightlifting. Sports Med. 2012, 42(9), 769-790.

  • Fry, A.C., Ciroslan, D., Fry, M.D. and LeRoux, C.D. Anthropometric and performance variables discriminating elite American junior men weightlifters. J. Strength Cond. Res., 2006, 20(4), 861.

  • Aristizabal, J., Freidenreich, D., Volk, B., Kupchak, B., Saenz, C. and Maresh, C. et al. Effect of resistance training on resting metabolic rate and its estimation by a dual-energy X-ray absorptiometry metabolic map. Eur. J. Clin. Nutr., 2015, 69(7), 831.

  • Brechue, W.F. and Abe, T. The role of FFM accumulation and skeletal muscle architecture in powerlifting performance. Eur. J. Appl. Physiol., 2002, 86(4), 327-336.

  • Broeder, C.E., Burrhus, K.A., Svanevik, L.S. and Wilmore, J.H. The effects of either high-intensity resistance or endurance training on resting metabolic rate. Am. J. Clin. Nutr., 1992, 55(4), 802-810.

  • Lemmer, J.T., Ivey, F.M., Ryan, A.S., Martel, G.F., Hurlbut, D.E. and Metter, J.E. et al. Effect of strength training on resting metabolic rate and physical activity: age and gender comparisons. Med. Sci. Sports Exerc., 2001, 3(4), 532-541.

  • Koshimizu, T., Matsushima, Y., Yokota, Y., Yanagisawa, K., Nagai, S. and Okamura, K. et al. Basal metabolic rate and body composition of elite Japanese male athletes. J. Med. Invest., 2012, 59(3.4), 253-260.

  • De Lorenzo, A., Bertini, I., Puijia, A., Testolin, G. and Testolin, C. Comparison between measured and predicted resting metabolic rate in moderately active adolescents. Acta Diabetol. 1999, 36(3), 141-145.

  • Carlsohn, A., Scharhag-Rosenberger, F., Cassel, M. and Mayer, F. Resting metabolic rate in elite rowers and canoeists: difference between indirect calorimetry and prediction. Ann. Nutr. Metab., 2011, 58(3), 239-244.

  • Loureiro, L.L., Junior, S.F., dos Passos, R.B., Porto, C.P.M. and Pierucci, A.P.T.R. Basal metabolic rate of adolescent modern pentathlon athletes: agreement between indirect calorimetry and predictive equations and the correlation with body parameters. PloS one. 2015, 10(11), e0142859.

  • Soares, M., Francis, D. and Shetty, P.S. Predictive equations for basal metabolic rates of Indian males. Eur. J. Clin. Nutr., 1993, 47(6), 389-394.

  • Ismail, M.N., Wannudri, W. and Zawiah, H. Energy expenditure studies to predict requirements of selected national athletes. Malays. J. Nutr., 1997, 3(1), 71-81.


Abstract Views: 393

PDF Views: 1




  • Resting Metabolic Rate of Junior National Weightlifters in India:Development and Validation of Prediction Models

Abstract Views: 393  |  PDF Views: 1

Authors

Keren Susan Cherian
Department of Work Physiology and Sports Nutrition, Indian Council of Medical Research, Ministry of Health and Family Welfare, Government of India, Jamai-Osmania, Hyderabad, Telangana-500 007, India
Ashok Sainoji
Department of Work Physiology and Sports Nutrition, Indian Council of Medical Research, Ministry of Health and Family Welfare, Government of India, Jamai-Osmania, Hyderabad, Telangana-500 007, India
Prem Raj Dundigalla
Department of Work Physiology and Sports Nutrition, Indian Council of Medical Research, Ministry of Health and Family Welfare, Government of India, Jamai-Osmania, Hyderabad, Telangana-500 007, India
Balakrishna Nagalla
Biostatistics Division, National Institute of Nutrition, Indian Council of Medical Research, Ministry of Health and Family Welfare, Government of India, Jamai-Osmania, Hyderabad, Telangana-500 007, India
Venkata Ramana Yagnambhatt
Department of Work Physiology and Sports Nutrition, Indian Council of Medical Research, Ministry of Health and Family Welfare, Government of India, Jamai-Osmania, Hyderabad, Telangana-500 007, India

Abstract


Weightlifters involve in intense strength and resistance training, thus calorie adequacy is a nutritional concern for them. Determining Resting Metabolic rate (RMR) is important to assess energy needs and there is limited scientific evidence in this area. Thus, this study aims to document physical characteristics and RMR of Indian junior weightlifters. It also attempts to identify suitable RMR prediction equations by developing new equations and comparing measured with predicted RMR from seven equations already existing world-wide. In this cross-sectional observation study, twenty one Indian junior weightlifters (Boys = 9; Girls = 12) were assessed for body composition (skinfold technique) and RMR using indirect calorimetry. Regression models for RMR were developed and measured RMR was compared with predicted RMR using paired samples t-test. The 24-hour RMR showed significant (P<0.01) gender differences (Boys = 1675 ± 111.7; Girls = 1425 ± 93.4), whereas, RMR per unit fat-free mass and body mass were similar across gender. The simple equation developed using body mass (RMR = 1206 + 13 × Body Mass (Kg) – 227.7 × Gender; R2 = 0.872; SEE = 60.604) showed good agreement with measured RMR. Out of seven existing RMR models, the equation of ten Haaf and Weijs (2014) showed better predictability. In conclusion, fat-free mass caused a major variation in RMR. Considering the limited scientific evidence, prediction equations newly developed and RMR equation of ten Haaf and Weijs (2014) can be used for periodical monitoring of RMR.

Keywords


Basal Metabolic Rate, Energy Expenditure, Body Composition, Indirect Calorimetry, Strength Athletes.

References