DOI: https://doi.org/10.32776/revbiomed.v30i3.684

Comparación de métodos de estimación del gasto energético en reposo en adultos jóvenes de Yucatán, México

Juan Carlos Espadas Herrera, Juan Carlos Ávila López, Lucía González Ramírez, Reinhard Janssen Aguilar, Fernanda Molina Seguí, Rodrigo Huerta Quintanilla, Ana María Hernández Hernández, Efraín Canto Lugo, Hugo Antonio Laviada Molina

Resumen

Introducción: Extrapolar ecuaciones matemáticas para la predicción del gasto energético en reposo (GER) a poblaciones diferentes a la original donde fueron desarrolladas, puede comprometer la precisión del cálculo.

Objetivo: comparar diversas ecuaciones predictivas del GER contra la calorimetría indirecta (CI) para la determinación de la mejor ecuación como alternativa en adultos jóvenes universitarios en Yucatán.

Material y Métodos: estudio transversal con 34 mujeres y 30 hombres (20.25 ± 1.5 años) clasificados de acuerdo a su índice de masa corporal (IMC): subgrupos sin sobrepeso y con sobrepeso. La medición del GER fue a través de un calorímetro indirecto portátil. El análisis estadístico incluyó la evaluación del sesgo con intervalos de confianza del 95%, precisión, exactitud y correlación de Pearson (P=0.01).

Resultados: a pesar de la alta correlación entre las ecuaciones predictivas del GER y la CI, no fue posible identificar alguna con clara superioridad frente al resto. La ecuación de MifflinSt Jeor mostró algunas ventajas al evaluar al grupo total.

Conclusión: en la práctica clínica, las ecuaciones predictivas son un instrumento útil y económico que no debe ser descartado a pesar de sus limitaciones.

Palabras clave: Calorimetría indirecta. Índice de masa corporal. Evaluación nutricional. Impedancia eléctrica. Metabolismo basal. Metabolismo energético. 

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Referencias

Psota T, Chen KY. Measuring energy expenditure in clinical populations: rewards and challenges. Eur J Clin Nutr. 2013; 67(5): 436–442.

Frankenfiel DC, Ashcraft C. Estimating energy needs in nutrition support patients. JPEN J Parenter Enteral Nutr. 2011; 35(5): 563-570.

Parra A, Cherem L, Galindo D, Díaz M, Pérez AB, Hernández C. Comparación del gasto energético en reposo determinado mediante calorimetría indirecta y estimado mediante fórmulas predictivas en mujeres con grados de obesidad I a III. Nutr Hosp. 2013; 28(2): 357-364.

Haugen HA, Chan LN, Li F. Indirect calorimetry: a practical guide for clinicians. Nutr Clin Pract. 2007; 22(4): 377-388.

Kennedy S, Ryan L, Fraser A, Clegg ME. Comparison of the GEM and the ECAL indirect calorimeters against the Deltatrac for measures of RMR and diet-induced thermogenesis. J Nutr Sci. 2014; 3: e52.

Frankenfield DC, Ashcraft CM. Toward the development of predictive equations for resting metabolic rate in acutely ill spontaneously breathing patients. JPEN J Parenter Enteral Nutr. 2016; 41(7):1155-1161.

Frankenfield DC, Coleman A. An evaluation of a handheld indirect calorimeter against a standard calorimeter in obese and nonobese adults. JPEN J Parenter Enteral Nutr. 2013; 37(5): 652-658.

Kyle UG, Bosaeus I, De Lorenzo AD, Deurenber P, Elia M, Gómez JM, et al. Bioelectrical impedance analysis--part I: review of principles and methods. Clin Nutr. 2004; 23(5): 1226-1243.

Pinheiro AC, Esteves FC, Duarte R, Esteves EA, Bressan J. Energy expenditure: components and evaluation methods. Nutr Hosp. 2011; 26(3): 430-440.

Weir JB. New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol. 1949; 109: 1-9.

Harris JA, Benedict FG. A biometric study of human basal metabolism. Proc Natl Acad Sci USA. 1918; 4(12): 370-373.

Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990; 51(2): 241-247.

Valencia ME. Energía. In Bourges H, Casanueva E, Rosado J. Recomendaciones de ingestión de nutrimentos para la población mexicana: bases fisiológicas. México: Editorial Médica Panamericana; 2009.

Energy and protein requirements. Report of a joint FAO/WHO/UNU Expert Consultation. World Health Organ Tech Rep Ser. 1985; 724: 1-206.

Sheiner L, Beal S. Some suggestions for measuring prediction performance. J Pharmacokinet Biopharm. 1981; 9: 503-512.

Frankenfield D, Coleman A, Alam S, Cooney RN. Analysis of estimation methods for resting metabolic rate in critically ill adults. JPEN J Parenter Enteral Nutr. 2009; 33: 27-36.

Prado E, Lera F, Teixeira O, Maestá N, Burini RC. J Obes. Comparison of predictive equations for resting energy expenditure in overweight and obese adults. 2011; 2011: 534714.

Walker RN, Heuberger R. Predictive equations for energy needs for the critically ill. Respir Care. 2009; 54: 509–521.

AW F. Climate variables as predictors of basal metabolic rate: new equations. Am J Hum Biol. 2008; 20(5): 510-529.

Valencia ME, Moya SY, McNeill G, Haggarty P. Basal metabolic rate and body fatness of adult men in northern Mexico. Eur J Clin Nutr. 1994; 48(3): 205-211.

Parra A, Pérez-Lizaur A. Comparación de la estimación del gasto energético basal por cuatro ecuaciones versus calorimetría indirecta en mujeres con peso normal, sobrepeso y obesidad. 2012; 20(2): 63-66.

Frankenfield D, Roth-Yousey L, Compher C. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J Am Diet Assoc. 2005; 105(5): 775-789.

Frankenfield DC, Rowe WA, Smith JS, Cooney RN. Validation of several established equations for resting metabolic rate in obese and nonobese people. J Am Diet Assoc. 2003; 103(9): 1152-1159.

Korth O, Bosy-Westphal A, Zschoche P, Glüer CC, Heller M, Müller MJ. Influence of methods used in body composition analysis on the prediction of resting energy expenditure. Eur J Clin Nutr. 2007; 61(5): 582-589.

Rao ZY, Wu XT, Liang BM, Wang MY, Hu W. Comparison of five equations for estimating resting energy expenditure in chinese young, normal weight healthy adults. Eur J Med Res. 2012; 17: 26.

Weijs PJ. Validity of predictive equations for resting energy expenditure in US and Dutch overweight and obese class I and II adults aged 18-65 y. Am J Clin Nutr. 2008; 88(4): 959-970.

Melanson EL, Coelho LB, Tran ZV, Haugen HA, Kearney JT, Hill JO. Validation of the BodyGem hand-held calorimeter. Int J Obesity. 2004; 12: 1479-1484.

Alam DS, Hulshof PJM, Roordink D, Meltzer M, Salam MM, van Raaij J. Validity and reproducibility of resting metabolic rate measurements in rural bangladeshi women: comparison of measurements obtained by Med Gem and by Deltatrac device. Eur J Clin Nutr. 2005; 59: 651-657.

Fields DAKJT, Copeland KC. MedGem hand-held indirect calorimeter is valid for resting energy expenditure measurement in health children. Obesity. 2006; 14: 1755-1761.

Cooper JA, Watras AC, O'Brien MJ, Luke A, Dobratz JR, Earthman CP, et al. Assessing validity and reliability of resting metabolic rate in six gas analysis systems. J Am Diet Assoc. 2009; 109(1): 128-132.

Fares S, Miller MD, Masters S, Crotty M. Measuring energy expediture in community-dwelling older adults: are portable methods calid and acceptable? J Am Diet Assoc. 2008; 108: 544-548.

Compher C, Hise M, Sternber A, Kinosian BP. Comparision between MedGem and Deltatrac resting metabolic rate measurements. Eur J Clin Nutr. 2005; 59: 1136-1141.

Hlynsky J, Birmingham CL, Johnston M, Gritzner S. The agreement between the MedGem indirect calorimeter and a standard indirect calorimeter in anorexia nervosa. Eating Weight Disord. 2005; 10: e83-e87.

Nieman , DC , Trone GA, Austin MD. A new handheld device for measuring resting metabolic rate and oxygen consumption. J Am Diet Assoc. 2003; 103: 588-593.

Melanson E, Coelho LB, Tran ZV, Haugen HA, Kearney JTHJO. Validation of the BodyGem hand-held calorimeter. In J Obesity. 2004; 28: 1479-1484.

St.-Onge MP, Rubiano F, Jones A, Heymsfield SB. A new hand-held indirect calorimeter to measure post-prandial energy expediture. Obesity Res. 2004; 12: 704-709.

Stewart C, Goody CM, Branson R. Comparison of two systems of measuring energy expediture. JPEN Parent Enteral Nutr. 2005; 29: 212-217.

Rubenbauer JR, Johannsen DL, Baier SM, Litchfield R, Flakoll PJ. The use of a handheld calorimetry unit to estimate energy expenditure during different physiological conditions. JPEN J Parenter Enteral Nutr. 2006; 30: 246-250.

DOI: https://doi.org/10.32776/revbiomed.v30i3.684

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