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Relationship of body composition and speed of cognitive processing in college students : a cross-sectional study.

Relación de la composición corporal y la velocidad de procesamiento cognitivo en estudiantes universitarios : un estudio transversal.



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Relationship of body composition and speed of cognitive processing in college students : a cross-sectional study. (2021). NOVA, 19(36). https://revistas.unicolmayor.edu.co/index.php/nova/article/view/1055

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Cristian Ermides Carrillo Ramírez

    Héctor Reynaldo Triana Reina


      Cristian Ermides Carrillo Ramírez,

      Cultura Física, Deporte y Recreación, semillero del grupo de investigación GICAEDS, Universidad Santo Tomás de Aquino. Bogotá, Colombia.


      Héctor Reynaldo Triana Reina,

      Cultura Física, Deporte y Recreación. GICAEDS de la Universidad Santo Tomás de Aquino, Bogotá, Colombia.


      Introduction. There is a wide discussion about the role of body composition in the development of cognitive functions such as processing speed, especially on fat mass. Furthermore, few studies that are being developed in Colombia, South America, have explored this relationship in college students from different areas of knowledge. Objective. To determine the relationship between cognitive processing speed (CPS) and body composition in college students from Bogotá D.C., Colombia. Material and methods. Cross-sectional descriptive and correlational study in a total sample of 122 apparently healthy male students (17 to 31 years old) from different areas of knowledge (72.1% from Physical Culture and 27.9% from other careers), belonging to private universities of the Capital District. Anthropometric parameters (height, weight, waist circumference (WC)), body composition variables (bioimpedance scale) were measured; CPS was assessed using the Paced Auditory Serial Addition Test (PASAT (60) -3”). Statistical analysis was performed using the IBM SPSS V. 25 software to calculate the results. Results. With a mean of 20.9 (3.4) years, a Body Mass Index (BMI) of 40.5% was identified in overweight and 4.1% in obesity. PASAT (60) -3”) was positively related to BMI, body fat percentage (% BF) and WC, negatively to muscle mass percentage (% MM) in the group of other races. However, the decreased CPS had a higher% CG, CC and% MM lower, compared to those who had a CPS within the expected (p = <0.05). Conclusion. Fat mass seems to influence the cognitive processing speed; however, this relationship does not follow a clearly defined pattern, it seems to behave in a curved way where extreme values could negatively affect said cognitive function. Apparently, healthier body composition can be beneficial for processing speed in college students.


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      1. Alcaraz-Ortíz, M. R., Ramírez-Flores, D., Palafox-López, G. I., & Reyes-Hernández, J. U. (2015). El déficit cognitivo relacionado con el índice de masa corporal elevado. Vertientes. Revista Especializada en Ciencias de la Salud, 18(1). Recuperado de: https://www.zaragoza.unam.mx/portal/wp-content/Portal2015/publicaciones/revistas/vertientes/Volumen18/5Deficit-jul23.pdf
      2. Asaduroglu, A. V., Tablada, M., Bai, J. C., Carrillo, M., Canale, M., & Gallerano, R. (2015). Perfil corporal y función física y cognitiva según edad en mujeres mayores ambulatorias de la ciudad de Córdoba. Revista de la facultad de Ciencias Médicas, 72(2). -Recuperado de: http://revista.webs.fcm.unc.edu.ar/files/2015/07/art.orig_.2.pdf
      3. Atkinson, H. H., Rosano, C., Simonsick, E. M., Williamson, J. D., Davis, C., Ambrosius, W. T., … Kritchevsky, S. B. (2007). Cognitive Function, Gait Speed Decline, and Comorbidities: The Health, Aging and Body Composition Study. The Journals of Gerontology: Series A, 62(8), 844–850. doi:10.1093/gerona/62.8.844
      4. Becerra, C., Reigal, R., Hernández, A. y Tamayo, I. (2013). Relaciones de la condición física y la composición corporal con la autopercepción de salud. Revista internacional de ciencias del deporte, 34 (9). 305- 318.
      5. Brooks, J. B. B., Giraud, V. O., Saleh, Y. J., Rodrigues, S. J., Daia, L. A., & Fragoso, Y. D. (2011). Paced auditory serial addition test (PASAT): a very difficult test even for individuals with high intellectual capability. Arquivos de neuro-psiquiatria, 69(3), 482-484.
      6. Cotman, C. & Berchtold, N. (2002). Exercise: a behavioral intervention to enhance brain health and plasticity. Trends Neuroscience, 25, 295-301
      7. De León-Arcila, R., Milián-Suazo, F., Camacho-Calderón, N., Arévalo-Cedano, R. E., & Escartín-Chávez, M. (2009). Factores de riesgo para deterioro cognitivo y funcional en el adulto mayor. Revista Médica del Instituto Mexicano del Seguro Social, 47(3), 277-284.
      8. Deckers, K., Van Boxtel, M., Verhey, F. & Köhler, S. (2017). Obesity and cognitive decline in adults: effect of methodological choices and confounding by age in a longitudinal study. Journal of Nutrition Health and Aging, 21(5), 546-553.
      9. Domínguez-Sanchéz, M. A., Bustos-Cruz, R. H., Velasco-Orjuela, G. P., Quintero, A. P., Tordecilla-Sanders, A., Correa-Bautista, J. E., … Ramírez-Vélez, R. (2018). Acute Effects of High Intensity, Resistance, or Combined Protocol on the Increase of Level of Neurotrophic Factors in Physically Inactive Overweight Adults: The BrainFit Study. Frontiers in physiology, 9, 741. doi:10.3389/fphys.2018.00741
      10. Formoso, J., Jacubovich, S., Injoque-Ricle, I., & Barreyro, J. P. (2018). Resolution of arithmetic problems, processing speed and working memory in children. Trends in Psychology, 26(3), 1249- 1266.
      11. Gallagher, D., Heymsfield, S. B., Heo, M., Jebb, S. A., Murgatroyd, P. R., & Sakamoto, Y.. (2000). Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. The American Journal of Clinical Nutrition, 72(3), 694–701. https://doi.org/10.1093/ajcn/72.3.694
      12. Goldfield, G. S., Kenny, G. P., Prud’homme, D., Holcik, M., Alberga, A. S., Fahnestock, M., ... & Tremblay, M. S. (2018). Effects of aerobic training, resistance training, or both on brain-derived neurotrophic factor in adolescents with obesity: the HEARTY randomized controlled trial. Physiology & behavior, 191, 138-145.
      13. Gronwall, D. M. A. (1977). Paced Auditory Serial-Addition Task: A Measure of Recovery from Concussion. Perceptual and Motor Skills, 44(2), 367–373. doi:10.2466/pms.1977.44.2.367
      14. Instituto Colombiano de Bienestar Familiar (2015). Encuesta Nacional de Situación Nutricional - ENSIN 2015. https://www.icbf.gov.co/bienestar/nutricion/encuesta-nacional-situacion-nutricional
      15. International diabetes federation. The IDF consensus worldwide definition of the Metabolic Syndrome. Bruselas, 2006.
      16. ISFTAO, K. (2006). Normas Internacionales para la Valoración Antropométrica. República de Sudáfrica: International Society for the Advancement of Kinanthropometry (ISAK).
      17. Lopera, I. C. P., Lubert, C. D., Londoño, D. M. M., & Martínez, D. L. (2019). Estandarización de pruebas neuropsicológicas para la evaluación de la atención en estudiantes universitarios (standardi-zation of a protocol of neuropsychological tests for the assessment of attention in college students). CES Psicología, 12(1), 17-31.
      18. Lubrini, G. (2013). Velocidad de procesamiento de la información en esclerosis múltiple (Doctoral dissertation, Universidad Complutense de Madrid).
      19. Malo-Serrano, Miguel, Castillo M, Nancy, & Pajita D, Daniel. (2017). La obesidad en el mundo. Anales de la Facultad de Medicina, 78(2), 173-178. Recuperado de: http://www.scielo.org.pe/scielo.php?script=sci_arttext&pid=S1025-55832017000200011
      20. Martinez Secada, C. E. (2018). Deterioro cognitivo asociado a sobrepeso y obesidad en pacientes geriátricos hospitalizados del Hospital Regional Honorio Delgado Espinoza. Recuperado de: http://repositorio.unsa.edu.pe/handle/UNSA/5640
      21. Naranjo, I. C., & Moreno, J. M. R. (2008). Hipertensión arterial y función cognitiva. Medicina clínica, 130(14), 542-552. Recuperado de: https://www.sciencedirect.com/science/article/pii/S002577530871501X
      22. Noh, H., Oh, S., Song, H. J., Lee, E. Y., Jeong, J., Ryu, O., Hong, K., & Kim, D. (2017). Relationships between cognitive function and body composition among community-dwelling older adults: a cross-sectional study. BMC Geriatrics, 17(1), 259. https://doi.org/10.1186/s12877-017-0651-9
      23. Núñez, A. M., Sobrero, M., Guzmán, L., Rico, V. E., Díaz Kuaik, I., Novarese, M., & Koskimies, J. (2014). Hipertensión: perfil psicológico y detección de deterioro cognitivo con Rorschach y mini batería de eficiencia cognitiva. Anuario de investigaciones, 21(1), 277-284. Recuperado de: http://www.scielo.org.ar/scielo.php?script=sci_arttext&pid=S1851-16862014000100029
      24. Orrell, M., Aguirre, E., Spector, A., Hoare, Z., Woods, R. T., Streater, A., Donovan, H., Hoe, J., Knapp, M., Whitaker, C., & Russell, I. (2014). Maintenance cognitive stimulation therapy for dementia: single-blind, multicentre, pragmatic randomised controlled trial. British Journal of Psychiatry, 204(6), 454-461. https://doi.org/10.1192/bjp.bp.113.137414
      25. Organización de las Naciones Unidas para la Alimentación y la Agricultura (FAO) (2016). Panorama de la Seguridad Alimentaria y Nutricional en América Latina y el Caribe. Recuperado de: https://www.paho.org/col/index.php?option=com_content&view=article&id=2686:sobrepeso-afecta-a-casi-la-mitad-de-la-poblacion-de-todos-los-paises-de-america-latina-y-el-caribe-salvo-por-haiti&Itemid=562
      26. Organización Mundial de la Salud (OMS), Nota descriptiva N°311 junio de 2016. Disponible en: http://www.who.int/mediacentre/factsheets/fs311/es/
      27. Ozakbas, S., Cinar, B. P., Gurkan, M. A., Ozturk, O., Oz, D., & Kursun, B. B. (2016). Paced auditory serial addition test: National normative data. Clinical neurology and neurosurgery, 140, 97-99.
      28. Pedraza, O. L., Perilla, H. J., Cruz, A., Botero, J. A., Montalvo, M. C., Salazar, A. M., ... & Plata, S. J. (2016). Deterioro cognitivo y factores de riesgo cardiovascular y metabólico en una muestra de adultos de Bogotá. Acta Neurológica Colombiana, 32(2), 91-99. Recuperado de: https://www.researchgate.net/publication/312241531_Deterioro_cognitivo_y_factores_de_riesgo_cardiovascular_y_metabolico_en_una_muestra_de_adultos_de_Bogota
      29. Puertas, S. (2015). Diferencias en la velocidad de procesamiento, en niños con dislexia vs. controles, medidas con potenciales evocados de larga latencia (P300). Doctorado. Universidad Nacional de Colombia.
      30. Quintero, A. P., Bonilla-Vargas, K. J., Correa-Bautista, J. E., Domínguez-Sanchéz, M. A., Triana-Reina, H. R., Velasco-Orjuela, G. P., ... & Ramírez-Vélez, R. (2018). Acute effect of three different exercise training modalities on executive function in overweight inactive men: A secondary analysis of the BrainFit study. Physiology & behavior, 197, 22-28.
      31. Ramírez-Vélez, R., Correa-Bautista, J. E., Sanders-Tordecilla, A., Ojeda-Pardo, M. L., Cobo-Mejía, E. A., Castellanos-Vega, R., … González-Ruíz, K. (2017). Percentage of Body Fat and Fat Mass Index as a Screening Tool for Metabolic Syndrome Prediction in Colombian University Students. Nutrients, 9(9), 1009. doi:10.3390/nu9091009
      32. Rivas Navarro, M. (2008). Procesos cognitivos y aprendizaje significativo. Comunidad de Madrid. Consejería de Educación. Viceconsejería de Organización Educativa.
      33. Rivas, Juan Carlos, & Gaviria, Moisés. (2000). Hipertensión Arterial Y Déficit Cognitivo. Revista Colombiana de Psiquiatría, 29(2), 105-117. Recuperado de http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0034-74502000000200003&lng=en&tlng=es.
      34. Rosano, C., Simonsick, E. M., Harris, T. B., Kritchevsky, S. B., Brach, J., Visser, M., … Newman, A. B. (2004). Association between Physical and Cognitive Function in Healthy Elderly: The Health, Aging and Body Composition Study. Neuroepidemiology, 24(1-2), 8–14. doi:10.1159/000081043
      35. Rothman, S. M., & Mattson, M. P. (2009). Adverse Stress, Hippocampal Networks, and Alzheimer’s Disease. NeuroMolecular Medicine, 12(1), 56–70. doi:10.1007/s12017-009-8107-9
      36. Sillero, M. (2005). Medidas Antropométricas. Facultad deficiencias de la actividad física y del deporte (INEF)-Tema, 2, 38-39.
      37. Skinner, J., Abel, W., McCoy, K. & Wilkins, C. (2017). Exploring the «Obesity Paradox» as a correlate of cognitive and physical function in communitydwelling black and white older adults. Ethnicity & Disease, 27(4), 387-394.
      38. Strauss, E., Sherman, E. M. S., & Spreen, O. (2006). A compendium of neuropsychological tests: Administration, norms, and commentary, 3rd ed. Oxford University Press.
      39. Tikhonoff, V., Casiglia, E., Guidotti, F., Giordano, N., Martini, B., Mazza, A., Palatini, P. (2015). Body fat and the cognitive pattern: A population-based study. Obesity, 23(7), 1502–1510. doi:10.1002/ oby.21114
      40. Uribe, D. R., Guzmán, C. S., Marambio, M. M., & Harrington, M. V. (2013). Ejercicio físico y su influencia en los procesos cognitivos. Revista Motricidad y Persona, (13), 69-74.
      41. Wang, C., Liang, W., Tseng, P., Muggleton, N., Juan, C. & Tsai, C. (2015). The relation-ship between aerobic fitness and neural oscillations during visuospatial attention in young adults. Experimental Brain Research, 233(4), 1069- 1078
      42. Wirth, R., Bauer, J. M., & Sieber, C. C. (2007). Cognitive function, body weight and body composition in geriatric patients. Zeitschrift für Gerontologie und Geriatrie, 40(1), 13-20.
      43. Wirth, R., Smoliner, C., Sieber, C. C., & Volkert, D. (2011). Cognitive function is associated with body composition and nutritional risk cognitive function is associated with body composition and nutritional risk of geriatric patients. The journal of nutrition, health & aging, 15(8), 706-710.
      44. World Health Organization. (2000). Obesity: preventing and managing the global epidemic (No. 894). World Health Organization.
      45. Zea, R., León A., Botero R., Afanador, C., & Pinzón, B. (2014). Factores de riesgo cardiovascular y su relación con la composición corporal en estudiantes universitarios. Revista de Salud Pública, 16, 505-515.
      46. Zenteno-López, M. A., Pérez-Martínez, G. P., Báez-Hernández, F. J., & García-Madrid, G. (2016). Función cognitiva en el adulto mayor con y sin diabetes tipo 2. Revista Científica De La Sociedad Española De Enfermería Neurológica, 44, 3-8. https://doi.org/10.1016/j.sedene.2016.05.002
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