Acuerdo entre el análisis de bioimpedancia eléctrica y las ecuaciones predictivas para evaluar la tasa metabólica en reposo en niños palestinos de 6 a 9 años
DOI:
https://doi.org/10.47197/retos.v78.118732Palabras clave:
Análisis de bioimpedancia eléctrica, niños, masa libre de grasa, tasa metabólica en reposo, PalestinaResumen
Introducción: La tasa metabólica en reposo (RMR) es el componente más grande del gasto energético diario y es esencial para mantener el equilibrio energético durante el crecimiento infantil.
Objetivo: Este estudio evaluó la concordancia entre el análisis de bioimpedancia eléctrica (BIA) y las ecuaciones predictivas comunes para estimar la RMR en niños palestinos de 6 a 9 años, y buscó desarrollar una ecuación específica para la población basada en la masa libre de grasa (FFM).
Metodología: Se seleccionaron aleatoriamente 1,100 niños de 11 gobernaciones de Cisjordania. Se realizaron mediciones antropométricas y de RMR, y se compararon las estimaciones de las ecuaciones predictivas con los valores obtenidos mediante BIA.
Resultados: La RMR media fue de 1117,65 kcal/día. La ecuación de la OMS (1985) mostró la mayor concordancia con BIA. La FFM fue un predictor independiente fuerte de la RMR, dando lugar a la ecuación:
RMR (kcal/día) = 376,015 + (34,120 × FFM) (R² = 0,88).
Discusión: Los valores de crecimiento y RMR estuvieron dentro de rangos normales, aunque las diferencias respecto a los estándares internacionales probablemente reflejan factores genéticos, nutricionales, socioeconómicos, climáticos y de actividad física.
Conclusión: La ecuación basada en FFM ofrece una herramienta práctica para monitorear el crecimiento, guiar la nutrición y diseñar programas de actividad física para prevenir la obesidad y enfermedades relacionadas en niños palestinos.
Referencias
Acar-Tek, N., Ağagündüz, D., Şahin, T. Ö., Baygut, H., Uzunlar, E. A., Küçükkaraca Zakkour, H., & Karaçallı, A. (2023). Validation of predictive equations for resting energy expenditure in children and adolescents with different body mass indexes. Nutrition Journal, 22(39). https://doi.org/10.1186/s12937-023-00868-3
Aguirre CA, GDC Salazar, DV Lopez de Romaña, JA Kain, CL Corvalán & RE Uauy.(2014). Evaluation of simple body composition methods: assessment of validity in pre-pubertal Chilean children. European Journal of Clinical Nutrition,69, 269-273. DOI: 10.1038/ejcn.2014.144
Al Alwan I, Felimban N, Altwaijri Y, Tamim H, Al Mutair A, Shoukri M, Tamimi W.(2010). Puberty onset among boys in Riyadh, Saudi Arabia. Clin Med Insights Pediatr. 8; 4:19-24. doi: 10.4137/cmped. s4610
Albertsson Wikland K, Luo ZC, Niklasson A, Karlberg J. (2002). Swedish population-based longitudinal reference values from birth to 18 years of age for height, weight and head circumference. Acta Pediatric; 91: 739–754. Stockholm. DOI: 10.1080/08035250213216
Al-Hazzaa HM. (2007). Prevalence and trend in obesity among schoolchildren in Central Saudi Arabia between 1988 and 2005. Saudi Med J. 28:1569-1574. PMID: 17914521
Anne D, Lawrence, Samia A, Yoeju M, Izzeldin H, Hamed AL O, Daniel D & Kebreab G. (2018). Physical fitness characteristics of Omani primary school children according to body mass index. The Journal of Sports Medicine and Physical Fitness, 1-24. DOI: 10.23736/S0022-4707.18.08136-7.
Arciero. P. Goran. M, Poehlman. (1993). Resting metabolic rate is lower in women compared to men, Journal of Applied Physiology, 75, 2514-2520. DOI: 10.1152/jappl.1993.75.6.2514
Bedogni, G., Bertoli, S., De Amicis, R., Foppiani, A., De Col, A., Tringali, G., Marazzi, N., De Cosmi, V., Agostoni, C., Battezzati, A., & others. (2020). External validation of equations to estimate resting energy expenditure in 2037 children and adolescents with and 389 without obesity: A cross-sectional study. Nutrients, 12(5), 1421. https://doi.org/10.3390/nu12051421
Bland, J. M., & Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet, 327(8476), 307–310. PMID: 2868172.
Charlotte J., Emma L., Samuel W. & Michael J. (2018). Relationships between Motor Competence, Physical Activity, and Obesity in British Preschool Aged-Children, J. Funct. Morphol. Kinesiol. 3, 57; https://doi.org/10.3390/jfmk3040057
Chun, D., Kim, S. J., Kim, Y. H., Suh, J., & Kim, J. (2024). The estimation of pubertal growth spurt parameters using the superimposition by translation and rotation model in Korean children and adolescents: a longitudinal cohort study. Frontiers in Pediatrics, 12, Article 1372013. https://doi.org/10.3389/fped.2024.1372013
Chun, D., Kim, S. J., Suh, J., & Kim, J. (2025). Timing, velocity, and magnitude of pubertal changes in body composition: A longitudinal study. Pediatric Research, 97, 293‑300. https://doi.org/10.1038/s41390-024-03299-w.
Dabas A, Khadgawat R, Gahlot M, Surana V, Mehan N, Ramot R, Pareek A, Sreenivas V & Marwaha RK. (2018). Height velocity in apparently healthy north Indian school children. Indian J Endocr Metab; 22:256-260. doi: 10.4103/ijem.IJEM_638_17
De Cosmi V, Mazzocchi A, Milani GP, Calderini E, Scaglioni S, Bettocchi S, et al. (2020). Prediction of resting energy expenditure in children: May artificial neural networks improve our accuracy? J Clin Med. 9(4):1026. https://doi.org/10.3390/jcm9041026
Delgadillo, Natalie A.; Wyatt, Frank; Olson, Michael W.; and Choi, Soon-Mi (2022) "The Effects of Body Composition on Resting Metabolic Rate among College Aged Students," International Journal of Exercise Science: Conference Proceedings: Vol. 2: Iss. 14, Article 94. Available at: https://digitalcommons.wku.edu/ijesab/vol2/iss14/94
Fernández-Verdejo, R., Sanchez-Delgado, G., & Ravussin, E. (2024). Energy Expenditure in Humans: Principles, Methods, and Changes Throughout the Life Course. Retrieved from https://repository.lsu.edu/ clinical_research_pubs/148. https://doi.org/10.1146/annurev-nutr-062122-031443
Fuentes-Servín, J., Avila-Nava, A., González-Salazar, L. E., Pérez-González, O. A., Servín-Rodas, M. D. C., Serralde-Zuñiga, A. E., Medina-Vera, I., & Guevara-Cruz, M. (2021). Resting energy expenditure prediction equations in the pediatric population: A systematic review. Frontiers in Pediatrics, 9, 795364. https://doi.org/10.3389/fped.2021.795364
Furqan, M &Haqua, A. (2009). Surface area in children: A simple formula. Indian Pediatrics, 46,1085-1087, https://pubmed.ncbi.nlm.nih.gov/19430073/.
García-Guzmán, A. D., Becerra-Morales, S. N., Pinzón-Navarro, B. A., Baldwin-Monroy, D. D., Sampriti-Tarres, M., Velasco-Hidalgo, L., Avila-Nava, A., Cárdenas-Cardos, R. S., Maldonado-Silva, K., Guevara-Cruz, M., & Medina-Vera, I. (2025). Development of a predictive equation for resting energy expenditure in pediatric patients with oncological diagnosis. Frontiers in Nutrition, 12, Article 1656975. https://doi.org/10.3389/fnut.2025.16569
Gitsi, E., Kokkinos, A., Konstantinidou, S. K., Livadas, S., & Argyrakopoulou, G. (2024). The Relationship between Resting Metabolic Rate and Body Composition in People Living with Overweight and Obesity. Journal of Clinical Medicine, 13(19), 5862. https://doi.org/10.3390/jcm13195862
Henry, C. J. K. (2007). Basal metabolic rate studies in humans: Measurement and development of new equations. Public Health Nutrition, 8(7A), 1133–1152. https://doi.org/10.1079/PHN2005801
Huang, L., Guo, Z., Jiang, Z., Xu, Y., & Huang, H. (2025). Resting Metabolic rate in obesity. Postgraduate Medical Journal, 101(1195), 396–410. https://doi.org/10.1093/postmj/qgae153
Iju Shrestha, Hari Sharan Makaju. (2018). Change in height of the individual among selected ethnic groups. Int J Anat Res, 6(1.3):5007-5010. DOI: 10.16965/ijar.2017.537
Institute of Medicine (IOM). (2005). Dietary reference intakes for Energy, Carbohydrate, Fiber, Fat, fatty acids, cholesterol, protein, and amino acids (macronutrients). Washington, D.C.: The National Academies Press. DOI: https://doi.org/10.17226/10490
Jagim, A. R., Jones, M. T., Askow, A. T., Luedke, J., Erickson, J. L., Fields, J. B., & Kerksick, C. M. (2023). Sex differences in resting metabolic rate among athletes and association with body composition parameters: A follow-up investigation. Journal of Functional Morphology and Kinesiology, 8(3), 109. https://doi.org/10.3390/jfmk8030109
Jésus P, Achamrah N, Grigioni S, Charles J, Rimbert A, Folope V, Petit A, Déchelotte P, Coëffier M. (2015). Validity of predictive equations for resting energy expenditure according to the body mass index in a population of 1726 patients followed in a Nutrition Unit. Clin Nutr. 34(3):529-35. DOI: 10.1016/j.clnu.2014.06.009
Kabiri LS, Hernandez DC, Mitchell K. (2015). Reliability, Validity, and Diagnostic Value of a Pediatric Bioelectrical Impedance Analysis Scale. Child Obes;11(5):650-5. DOI: 10.1089/chi.2014.0156
Kim M-H, Kim J-H, Kim E-K. (2012). Accuracy of predictive equations for resting energy expenditure (REE) in non-obese and obese Korean children and adolescents. Nutr Res Pract ;6(1):51–60. DOI: 10.4162/nrp.2012.6.1.51
Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, Heitmann BL, Kent-Smith, Melchior JC, Pirlich M, Scharfetter H, Schols AM, Pichard C; (2004). Bioelectrical impedance analysis—part I: review of principles and methods. Clin Nutr. 23(5): 1226-43.DOI: 10.1016/j.clnu.2004.06.004
Lito M Amit & Young-Woong Song. (2018). Formulae evaluation for estimating body surface area of Korean children. J UOEH, 40(1), 19-32. DOI: 10.7888/juoeh.40.19
Madanhire, T., Macdougall, A., Kasonka, L., Mabuda, H. B., Chisenga, M., Mujuru, H., Bandason, T., Dzavakwa, N. V., Simms, V., Ward, K. A., Ferrand, R. A., Mohammed, N., & Gregson, C. L. (2025). Patterns of linear growth among children and adolescents living with HIV on antiretroviral therapy in Zimbabwe and Zambia. BMC Infectious Diseases, 25, 112. DOI: 10.1186/s12879-025-10669-0
Marderfeld, L., Guz Mark, A., Biran, N., & Shamir, R. (2023). Can we rely on resting metabolic rate equations? Large variance in Crohn disease pediatric patients. Journal of Pediatric Gastroenterology & Nutrition, 77(3), 389‑392. https://doi.org/10.1097/MPG.0000000000003878
Nadia M. Gharib, Parveen Rush eed. (2009). Anthropometry and body composition of school children in Bahrain. Ann Saudi Med, 29(4), 258-269. doi: 10.4103/0256-4947.55309
Ohara, K., Nakamura, H., Kouda, K. et al. (2023). Similarities and discrepancies between commercially available bioelectrical impedance analysis system and dual-energy X-ray absorptiometry for body composition assessment in 10–14-year-old children. Sci Rep 13, 17420. https://doi.org/10.1038/s41598-023-44217-0
O'Neill JER, Corish CA, Horner K. (2023). O’Neill, J.E.R., Corish, C.A. & Horner, K. Accuracy of Resting Metabolic Rate Prediction Equations in Athletes: A Systematic Review with Meta-analysis. Sports Med 53, 2373–2398. https://doi.org/10.1007/s40279-023-01896-z
Ortiz-Marrón H, Cabañas Pujadas G, Ortiz-Pinto MA, Martín García A, Matesanz Martínez C, Antonaya Martín MDC, Cortés Rico O, Galán I. (2023). Changes in general and abdominal obesity in children at 4, 6 and 9 years of age and their association with other cardiometabolic risk factors. Eur J Pediatr ;182(3):1329-1340. doi: 10.1007/s00431-022-04802-3
Owen OE, Kavle E, Owen RS, Polansky M, Caprio S, Mozzoli MA, et al. (1986). A reappraisal of caloric requirements in healthy women. Am J Clin Nutr;44(1):1–19. DOI: 10.1093/ajcn/44.1.1
Prado-Nóvoa, O., Howard, K. R., Laskaridou, E., Reid, G. R., Zorrilla-Revilla, G., Marinik, E. L., … & Davy, K. P. (2024). Validation of predictive equations to estimate resting metabolic rate of females and males across different activity levels. American Journal of Human Biology, 36(4), e24005. https://doi.org/10.1002/ajhb.24005
Pretorius, A., Wood, P. S., Becker, P. J., & Wenhold, F. A. M. (2025). Low variability of resting metabolic rate among early, middle, and late achievers of steady state suggests a shortened indirect calorimetry protocol for young children. Nutrition, 136, 112779. https://doi.org/10.1016/j.nut.2025.112779
Rexhepi, A., & Brestovci, B. (2020). Differences in growth and development velocity between boys and girls from Kosovo, aged 6–18 years. International Journal of Medical and Surgical Sciences, 7(1), Article 472. https://doi.org/10.32457/ijmss.v7i1.472
Rogol, A.D., Roemmich, J.N. & Clark, P.A., (2002). Growth at puberty. Journal of adolescent health, 31(6),192-200.DOI: 10.1016/s1054-139x(02)00485-8
Rush EC, Scragg R, Schaaf D, Jovanovich G & Plank LD/ (2008). Indices of fatness and relationships with age, ethnicity and lipids in New Zealand European, Maori and Pacific children. European Journal of Clinical Nutrition, 63, 627-633. DOI: 10.1038/ejcn.2008.15
Sampriti Debnath, Nitish Mondal, & Jaydip Sen. (2018). Percent of body fat, fat-mass, fat-free mass and assessment of body composition among rural school-going children of Eastern-India, Anthropological Review, 81(2), 158-173. DOI:10.2478/anre-2018-0011.
Schofield WN. (1985). Predicting resting metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr. 1985; 39:5–41. PMID: 4044297.
Shin, J., Kang, I., & Lee, M. (2024). Risk factors related to resting metabolic rate-related DNAJC6 gene variation in children with overweight/obesity: 3-year panel study. Nutrients, 16(24), 4423. https://doi.org/10.3390/nu16244423
Sovio U, Bennett AJ, Millwood IY, Molitor J, O’Reilly PF, et al. (2009) Genetic determinants of height growth assessed longitudinally from infancy to adulthood in the Northern Finland birth cohort 1966. PLoS Genet, 5(3): e1000409 DOI: 10.1371/journal.pgen.1000409 .
Sparti A, DeLany JP, de la Bretonne JA, Sander GE, Bray GA. (1997). Relationship between resting metabolic rate and the composition of the fat-free mass. Metabolism.;46(10):1225-30. DOI: 10.1016/s0026-0495(97)90222-5
Speakman, J. R., & Selman, C. (2007). Physical activity and resting metabolic rate. Proceedings of the Nutrition Society, 62(3), 621–634. https://doi.org/10.1079/PNS2003282
Tanaka T, Suwa S, Yokoya S, Hibi I. (1988). Analysis of linear growth during puberty. Acta Paediatr Scand; 347:25-29. PMID: 3254033.
Tanner JM, Davies PS. (1985). Clinical longitudinal standards for height and height velocity for North American children, J Pediatr, 107:317-329. DOI: 10.1016/s0022-3476(85)80501-1 .
Thakur R and Gautam RK. (2016). Differential metabolic rates among the school going boys of a Central Indian Town (Sagar). Human Biology Review, 5 (2), 146 -160.
Tian-Shing Lee,Ting Chao, Ren-Bin Tang, Chia-Chang Hsieh, Shu-Jen Chen &Low-Tone Ho. (2004). A longitudinal study of growth patterns in school children in Taipei area I: growth curve and height velocity curve. Journal of the Chinese Medical Association. 67(2),67-72. PMID: 15146901.
Trudy MA Wijnhoven, Joop MA van Raaij, Angela Spinelli, GrIjur Starc, Maria Hassapidou, Igor Spiroski, Harry Rutter, Éva Martos, Ana I Rito, Ragnhild Hovengen, Napoleón Pérez-Farinós & Ausra Petrauskiene.(2014), WHO European Childhood Obesity Surveillance Initiative: body mass index and level of overweight among 6–9-year-old children from school year 2007/2008 to school year 2009/2010. BMC Public Health. 7;14:806. DOI:10.1186/1471-2458-14-806
UNICEF. (2025). The State of the World’s Children 2025: Child Nutrition Report. United Nations Children’s Fund. https://www.unicef.org/reports/state-of-worlds-children/2025
Vlasa IM, Pop RM, Vlasa IM, Pașcanu IM. (2026). Changes in Bioelectrical Impedance Analysis and Lipid Profile in Children Diagnosed with Short Stature Who Undergo Growth Hormone Therapy: One Single-Center Experience. Medicina (Kaunas). 20;62(1):209. https://doi.org/10.3390/medicina62010209
Wang Z, Ying Z, Bosy-Westphal A, Zhang J, Heller M, Later W, Heymsfield SB, Müller MJ. (2010). Evaluation of specific metabolic rates of major organs and tissues: comparison between men and women. Am J Hum Biol;23(3):333-8. DOI: 10.1002/ajhb.21137
WHO (World Health Organization). (1985). Energy and protein requirements: Report of a joint. FAO/WHO/UNU expert consultation. WHO Technical Report Series No. 724, 206pp. PMID: 3937340.
Descargas
Publicado
Número
Sección
Licencia
Derechos de autor 2026 Abdelnaser A. Qadumi, Sulaiman H. Amad, Qais M. Nairat, Rawand K. Qutob, Mohammad A. Qadoumi, Ali A. Qadoume, Monther A. Nasrallah

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
Los autores que publican en esta revista están de acuerdo con los siguientes términos:
- Los autores conservan los derechos de autor y garantizan a la revista el derecho de ser la primera publicación de su obra, el cuál estará simultáneamente sujeto a la licencia de reconocimiento de Creative Commons que permite a terceros compartir la obra siempre que se indique su autor y su primera publicación esta revista.
- Los autores pueden establecer por separado acuerdos adicionales para la distribución no exclusiva de la versión de la obra publicada en la revista (por ejemplo, situarlo en un repositorio institucional o publicarlo en un libro), con un reconocimiento de su publicación inicial en esta revista.
- Se permite y se anima a los autores a difundir sus trabajos electrónicamente (por ejemplo, en repositorios institucionales o en su propio sitio web) antes y durante el proceso de envío, ya que puede dar lugar a intercambios productivos, así como a una citación más temprana y mayor de los trabajos publicados (Véase The Effect of Open Access) (en inglés).
Esta revista sigue la "open access policy" de BOAI (1), apoyando los derechos de los usuarios a "leer, descargar, copiar, distribuir, imprimir, buscar o enlazar los textos completos de los artículos".
(1) http://legacy.earlham.edu/~peters/fos/boaifaq.htm#openaccess