Thermic Effect of Low-Calorie Carbohydrate Intake on Resting Energy Expenditure
DOI:
https://doi.org/10.37482/2687-1491-Z136Keywords:
resting energy expenditure, thermic effect of food, basal metabolism, high-carbohydrate breakfast, indirect calorimetry, body composition, bioimpedance analysisAbstract
Basal metabolic rate (BMR) differs from resting energy expenditure (REE) by less than 10 %, the latter being measured under similar conditions, but after a low-calorie meal. Presently, the two terms are used interchangeably, although resting energy expenditure is the preferred one. However, the cycling to exhaustion test commonly used in assessing the physical performance of elite athletes should not follow a 12-hour fasting. Consequently, the subjects are given a standardized low-calorie highcarbohydrate breakfast before the test, which, according to the authors, does not distort the obtained REE values. Therefore, the aim of this study was to determine the thermic effect of a standardized high-carbohydrate meal on resting energy expenditure and body composition. Materials and methods. The anthropometry and body composition were analysed in healthy young men (n = 10) using the ACCUNIQ BC380 system; REE was assessed using indirect calorimetry; the thermic effect of a low-calorie high-carbohydrate breakfast was calculated as a difference between fasting REE and postprandial metabolism. Results. The research showed that a high-carbohydrate (91 %) food intake (250–300 kcal) produces no significant effect on REE. The meal’s thermic effect was 36.0 ± 5.7 kcal, which increased REE (1887.2 ± 111.7 kcal) by 2 % compared to baseline BMR (1851.2 ± 106.0 kcal). In the subjects, REE varied depending on the total amount of water in the body (p = 0.038), fat mass (p = 0.021), and an energy substrate (carbohydrate) intake (р = 0.046). Thus, in people, including athletes, it is acceptable to measure REE after a high-carbohydrate breakfast that does not exceed 300 kcal.
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References
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References
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Jagim A.R., Camic C.L., Kisiolek J., Luedke J., Erickson J., Jones M.T., Oliver J.M. Accuracy of Resting Metabolic Rate Prediction Equations in Athletes. J. Strength Cond. Res., 2018, vol. 32, no. 7, pp. 1875–1881. DOI: 10.1519/JSC.0000000000002111
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Binns A., Gray M., Di Brezzo R. Thermic Effect of Food, Exercise, and Total Energy Expenditure in Active Females. J. Sci. Med. Sport, 2015, vol. 18, no. 2, pp. 204–208. DOI: 10.1016/j.jsams.2014.01.008
Martin A., Normand S., Sothier M., Peyrat J., Louche-Pelissier C., Laville M. Is Advice for Breakfast Consumption Justified? Results from a Short-Term Dietary and Metabolic Experiment in Young Healthy Men. Br. J. Nutr., 2000, vol. 84, no. 3, pp. 337–344. DOI: 10.1017/s0007114500001616
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Bowden V.L., McMurray R.G. Effects of Training Status on the Metabolic Responses to High Carbohydrate and High Fat Meals. Int. J. Sport Nutr. Exerc. Metab., 2000, vol. 10, no. 1, pp. 16–27. DOI: 10.1123/ijsnem.10.1.16
Thyfault J.P., Richmond S.R., Carper M.J., Potteiger J.A., Hulver M.W. Postprandial Metabolism in Resistance-Trained versus Sedentary Males. Med. Sci. Sports Exerc., 2004, vol. 36, no. 4, pp. 709–716. DOI: 10.1249/01.MSS.0000121946.98885.F5
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Marra M., Di Vincenzo O., Cioffi I., Sammarco R., Morlino D., Scalfi L. Resting Energy Expenditure in Elite Athletes: Development of New Predictive Equations Based on Anthropometric Variables and Bioelectrical Impedance Analysis Derived Phase Angle. J. Int. Soc. Sports Nutr., 2021, vol. 18, no. 1. Art. no. 68. DOI: 10.1186/s12970-021-00465-x
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