contadores web
Skip to main navigation menu Skip to main content Skip to site footer
##common.pageHeaderLogo.altText##

Short article

Vol. 23 No. 3 (2021)

Heart rate variability and anthropometric indices in university males of Santiago de Chile

DOI
https://doi.org/10.22267/rus.212303.242
Submitted
October 3, 2019
Published
2021-09-01

Abstract

Introduction: Low heart rate variability (HRV) has been associated with autonomic imbalances and cardiovascular risk in various populations. Objective: To relate HRV and anthropometric indices in young, physically active university male students with low cardiometabolic risk. Materials and methods: A descriptive cross-sectional study, which included 10 men aged 23.15 ± 2.91 years, with a Body Mass Index (BMI) of 25.48 ± 2.19 kg / m2, and a Waist-Hip Ratio (WHR) of 0.81 ± 0.02. Resting heart rate variability was measured over a 5 minute period. A correlational analysis was performed between BMI and WHR with the low frequency / high frequency ratio (LF / HF), standard deviation of the instantaneous variation of RR intervals (SD1), and complexity of the RR intervals (α-1). In addition, statistical power (1- β) and effect size (Cohen's "d") were determined. Results: LF / HF is only significantly related to WHR (r = 0.638; p = 0.047; d = 0.80), while SD1 and α-1 did not show any association with BMI and WHR. Conclusions: There is a parasympathetic predominance that suggests a protective mechanism on intra-abdominal adipose tissue related to WHR. Further studies are required to explain all the modulating variables of the heart rate variability.

References

  1. Veloza L, Jiménez C, Quiñones D, Polanía F, Pachón-Valero LC, Rodríguez-Triviño CY. Heart rate variability as a predictive factor of cardiovascular diseases. Rev Colomb Cardiol. 2019;26(4):205–10. DOI: 10.1016/j.rccar.2019.01.006.
  2. Gilgen-Ammann R, Schweizer T, Wyss T. RR interval signal quality of a heart rate monitor and an ECG Holter at rest and during exercise. Eur J Appl Physiol. 2019;119(7):1525-32. DOI: 10.1007/s00421-019-04142-5.
  3. Fuentes-Barria H, González-Wong C, Urbano Cerda S, Vera Aguirre V, Aguilera Eguía R. Actividad física como medida de control autonómico en pacientes con síndrome metabólico. Revisión narrativa. Rev Podium. 2020;15(3):694-704. Disponible en: https://podium.upr.edu.cu/index.php/podium/article/view/907
  4. Billman GE, Huikuri HV, Sacha J, Trimmel K. An introduction to heart ate variability: methodological considerations and clinical applications. Front Physiol. 2015;6:55. DOI: 10.3389/fphys.2015.00055.
  5. Yadav RL, Yadav PK, Yadav LK, Agrawal K, Sah SK, Islam MN. Association between obesity and heart rate variability indices: an intuition toward cardiac autonomic alteration - a risk of CVD. Diabetes Metab Syndr Obes. 2017;10:57-64. DOI: 10.2147/DMSO.S123935.
  6. Benichou T, Pereira B, Mermillod M, Tauveron I, Pfabigan D, Maqdasy S, et al. Heart rate variability in type 2 diabetes mellitus: A systematic review and meta-analysis. PLoS One. 2018;13(4):e0195166. DOI: 10.1371/journal.pone.0195166.
  7. Rosales-Soto G, Corsini-Pino R, Monsálves-Álvarez M, Yáñez-Sepúlveda R. Response of the sympathetic-parasympathetic balance of the Heart Rate Variability during a week of aerobic training in road cyclists. Rev Andal Med Deport. 2016;9(4):143–7. DOI: 10.1016/j.ramd.2015.07.002.
  8. Penzel T, Kantelhardt JW, Grote L, Peter JH, Bunde A. Comparison of detrended fluctuation analysis and spectral analysis for heart rate variability in sleep and sleep apnea. IEEE Trans Biomed Eng. 2003;50(10):1143-51. DOI: 10.1109/TBME.2003.817636.
  9. Nunan D, Sandercock GR, Brodie DA. A quantitative systematic review of normal values for short-term heart rate variability in healthy adults. Pacing Clin Electrophysiol. 2010;33(11):1407-17. DOI: 10.1111/j.1540-8159.2010.02841.x.
  10. Perrotta AS, Jeklin AT, Hives BA, Meanwell LE, Warburton DER. Validity of the Elite HRV Smartphone Application for Examining Heart Rate Variability in a Field-Based Setting. J Strength Cond Res. 2017;31(8):2296-302. DOI: 10.1519/JSC.0000000000001841.
  11. Altini M, Van Hoof C, Amft O. Relation between estimated cardiorespiratory fitness and running performance in free-living: An analysis of HRV4Training data. 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI). 2017;249-52. DOI: 10.1109/BHI.2017.7897252.
  12. Koch-Villegas G, Cancino-López J, Roco Videla Á, Jorquera-Aguilera C, Aguilera-Eguia R, Hernández-Orellana M. Control del ritmo cardiaco, ingesta energética y calidad del sueño en bailarines de danza clásica. Rev. Finlay. 2018;8(4):284-90. Disponible en: http://www.revfinlay.sld.cu/index.php/finlay/article/view/559
  13. Castro-Sepúlveda M, Cerda-Kohler H, Pérez-Luco C, Monsalves M, Andrade DC, Zbinden-Foncea H, et al. El estado de hidratación después del ejercicio afecta la tasa metabólica basal y la variabilidad de la frecuencia cardiaca. Nutr Hosp. 2015;31(3):1273–7. DOI: 10.3305/nh.2015.31.3.8523.
  14. Córdoba-Ávila A, Cobos JC, Salas JA, Camacho JE, González-Medina SC. Variabilidad de la frecuencia cardiaca en estudiantes de medicina que presentan una privación crónica del sueño. Iatreia. 2018:31(Suppl 1):S57. Disponible en: https://revistas.udea.edu.co/index.php/iatreia/article/view/329871
  15. Zamorano VG, Peinado AB, Benito PJ, Calderón FJ. Respuesta de la frecuencia cardiaca de anticipación y recuperación en función del nivel de entrenamiento aeróbico. Arch. med. Deporte. 2013;30(4):202-7. Disponible en: http://oa.upm.es/26446/
  16. Caicedo-Ochoa EY, Urrutia Gómez JA. Relación entre el control autonómico cardíaco e índices antropométricos normales en hombres jóvenes. Tunja, Boyacá, Colombia, 2014. Medicas UIS. 2015;28(3):301–8. DOI: 10.18273/revmed.v28n3-2015004.
  17. Serón P, Muñoz S, Lanas F. Nivel de actividad física medida a través de Cuestionario Internacional de Actividad Física en población chilena. Rev Med Chile. 2010;138(10):1232-9. DOI: 10.4067/S0034-98872010001100004.
  18. Durán-Agüero S, Fernández-Godoy E, Fehrmann-Rosas P, Delgado-Sánchez C, Quintana-Muñoz C, Yunge-Hidalgo W, et al. Fewer hours of sleep associated with increased body weight in Chilean University nutrition students. Rev Peru Med Exp Salud Publica. 2016;33(2):264–8. DOI: 10.17843/rpmesp.2016.332.2100.
  19. Lillo Santander C, Jorquera Aguilera C, Roco Videla A, Íñiguez Carillo B, Aguilera Eguía R, Rojas Pérez M. Morphological Profile of Female Professional Soccer Players in Chile. Medisur. 2018;16(2):248-58. Disponible en: https://pesquisa.bvsalud.org/portal/resource/pt/biblio-894817
  20. Schuindt da Silva V, Soares Vieira MF. International society for the advancement of kinanthropometry (Isak) global: International accreditation scheme of the competent anthropometrist. Rev Bras Cineantropometria e Desempenho Hum. 2020;22:e70517. DOI: 10.1590/1980-0037.2020v22e70517.
  21. Muñoz Cofre R, del Sol M, Medina González P, Escobar Inostroza J, Lizana PA, et al. Relación de los índices de masa corporal y cintura-cadera con la capacidad residual funcional pulmonar en niños chilenos obesos versus normopeso: un estudio transversal. Arch Argent Pediatr. 2019;117(4).230-6. DOI: 10.5546/aap.2019.230.
  22. Shaffer F, Ginsberg JP. An Overview of Heart Rate Variability Metrics and Norms. Front Public Heal. 2017;5:258. DOI: 10.3389/fpubh.2017.00258.
  23. Tarvainen MP, Niskanen JP, Lipponen JA, Ranta-aho PO, Karjalainen PA. Kubios HRV - Heart rate variability analysis software. Comput Methods Programs Biomed. 2014;113(1):210–20. DOI: 10.1016/j.cmpb.2013.07.024.
  24. IBM SPSS Statistics 26 [Internet]. [cited 2021 Jun 14]. Available from: https://www.ibm.com/support/pages/downloading-ibm-spss-statistics-26
  25. Faul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149-60. DOI: 10.3758/BRM.41.4.1149.
  26. World Medical Association. World Medical Association declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191–4. DOI: 10.1001/jama.2013.281053.
  27. Aune D, Sen A, Norat T, Janszky I, Romundstad P, Tonstad S, et al. Body mass index, abdominal fatness, and heart failure incidence and mortality: A systematic review and dose-response meta-analysis of prospective studies. Circulation. 2016;133(7):639–49. DOI: 10.1161/CIRCULATIONAHA.115.016801.
  28. López Sánchez GF, López Sánchez L, Díaz Suárez A. Composición corporal y variabilidad de la frecuencia cardiaca: relaciones con edad, sexo, obesidad y actividad física. Sport TK. 2015;4(2):33-40. DOI: 10.6018/242921.
  29. Rahman S, Habel M, Contrada RJ. Poincaré plot indices as measures of sympathetic cardiac regulation: Responses to psychological stress and associations with pre-ejection period. Int J Psychophysiol. 2018;133:79-90. DOI: 10.1016/j.ijpsycho.2018.08.005.
  30. Castaldo R, Melillo P, Bracale U, Caserta M, Triassi M, Pecchia L. Acute mental stress assessment via short term HRV analysis in healthy adults: A systematic review with meta-analysis. Biomed Signal Process Control. 2015;18:370–7. DOI: 10.1016/j.bspc.2015.02.012.
  31. Cancino J. Variabilidad del ritmo cardíaco ¿Por qué el caos puede ser saludable? Pensar en movimiento. 2011;9(1):22-32. DOI: 10.15517/PENSARMOV.V9I1.389.
  32. Task Force of the European Society of Cardiology, The North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation. 1996;93(5):1043-65. Disponible en: https://pubmed.ncbi.nlm.nih.gov/8598068/
  33. Gronwald T, Rogers B, Hoos O. Fractal Correlation Properties of Heart Rate Variability: A New Biomarker for Intensity Distribution in Endurance Exercise and Training Prescription? Front. Physiol. 2020;11:1152. DOI: 10.3389/fphys.2020.550572.
  34. Gronwald T, Berk S, Altini M, Mourot L, Hoos O, Rogers B. Real-Time Estimation of Aerobic Threshold and Exercise Intensity Distribution Using Fractal Correlation Properties of Heart Rate Variability: A Single-Case Field Application in a Former Olympic Triathlete. Front Sports Act Living. 2021;3:668812. DOI: 10.3389/fspor.2021.668812.
  35. Wu PS, Jordan SW, Hodson T, Chao AH. Waist-to-hip ratio is a better predictor than body mass index for morbidity in abdominally based breast reconstruction. Microsurgery. 2018;38(7):731-7. DOI: 10.1002/micr.30346.

Downloads

Download data is not yet available.

Most read articles by the same author(s)