Quality of Life, Socioeconomic Well-Being and Heart Rate Variability in 16-18-Year-Old Girls Living in the Russian Arctic

ORIGINAL ARTICLE
Anna V. Ukhanova, Liliya V. Poskotinova

 
For citation: Ukhanova AV, Poskotinova LV. Quality of Life, Socioeconomic Well-Being and Heart Rate Variability in 16-18-Year-Old Girls Living in the Russian Arctic. International Journal of Biomedicine. 2024;14(3):492-496. doi:10.21103/Article14(3)_OA17
 
Originally published September 6, 2024

Abstract: 

Background: 16-18-year-old girls represent the country's reproductive and employment potential, which is the basis for its future demographic and socioeconomic development. The study aimed to determine the heart rate variability (HRV) indicators that can be most interrelated with quality of life (QoL) and socioeconomic well-being in 16-18-year-old girls living in the Russian Arctic.
Methods and Results: The study involved 53 girls aged 16-18 living in Arkhangelsk. The World Health Organization Brief Quality of Life Questionnaire (WHOQOL-BREF), Family Affluence Scale (FAS II), Family Financial Satisfaction Questionnaire, and Chen Internet Addiction Scale (CIAS) were used. HRV parameters were determined at rest and during slow-paced breathing with a frequency of 6 respiratory cycles per minute (6SPB).
In girls with HR 90 bmp and below, the increase of “Psychological Health,” “Social Relationship,” and “Environmental health” scores of WHOQOL-BREF was correlated with the decrease of sympathetic activity and with the increase of vagal activity during the 6SPB test. CIAS scores were positively correlated with sympathetic activity. The number of family vacations in the last year was correlated with a decrease in sympathetic activity.
Conclusion:16-18-year-old girls with optimal resting HR living in the Russian Arctic have more significant correlations of HRV indicators with social, psychological, and environmental aspects of QoL, as well as with the risk of Internet addiction, and, to a lesser extent, with economic living conditions. The opportunity for young people in the Arctic region to spend vacations with their families several times during the year helps reduce cardiac stress.

Keywords: 
quality of life • socio-economic well-being • heart rate variability • girls • Arctic region
References: 
  1. Piotrowska E, Zechałko-Czajkowska A, Biernat J, Mikołajczak J. Ocena wybranych cech stylu zycia kształtujacych stan zdrowia 16-18 letnich dziewczat. Cz. I. Stosowanie róznych diet, aktywność fizyczna, palenie papierosów i picie alkoholu [Assessment of selected features of the lifestyle being conduicive to the state of health of 16-18 year old girls. Part I. Dieting, physical activity, smoking and drinking alcohol]. Rocz Panstw Zakl Hig. 2009;60(1):51-7. Polish. PMID: 19579770.
  2. Biswakarma R, Maslowski K, Reiss MJ, Harper JC. Parenthood intentions of 16-18-year-olds in England: a survey of school students. Hum Fertil (Camb). 2024 Dec;27(1):2310639. doi: 10.1080/14647273.2024.2310639. Epub 2024 Feb 12. PMID: 38346450.
  3. Averyanova IV. [Main indicators of physical development and cardiovascular system in young people of the north leaving and not leaving the region for a summer vacation]. Social Aspects of Population Health [serial online] 2022; 68(3):10. doi: 10.21045/2071-5021-2022-68-3-10. [In Russian].
  4. World Health Organization. Child growth standards. Available from:  https://www.who.int/tools/child-growth-standards/standards [cited May 7, 2024]
  5. World Health Organization. WHOQOL: Measuring Quality of Life. Available from: https://www.who.int/tools/whoqol/whoqol-bref (accessed on 2024 May 7)
  6. Bruno VV. [Risky sexual behavior of modern teenagers in Russia. Part I.] Sociological Science and Social Practice. 2018;4:117-129. doi: 10.19181/snsp.2018.6.4.6089. [In Russian].
  7. Rosén H, Ahlström G, Lexén A. Psychometric properties of the WHOQOL-BREF among next of kin to older persons in nursing homes. Health Qual Life Outcomes. 2020 Apr 19;18(1):103. doi: 10.1186/s12955-020-01345-9. PMID: 32306965; PMCID: PMC7168811.
  8. Currie CE, Elton RA, Todd J, Platt S. Indicators of socioeconomic status for adolescents: the WHO Health Behaviour in School-aged Children Survey. Health Educ Res. 1997 Sep;12(3):385-97. doi: 10.1093/her/12.3.385. PMID: 10174221.
  9. Boyce W, Torsheim T, Currie C, Zambon A. The Family Affluence Scale as a Measure of National Wealth: Validation of an Adolescent Self-Report Measure. Soc Indic Res. 2006; 78(3): 473–487. doi: 10.1007/s11205-005-1607-6.
  10. Chen S-H, Weng L-J, Su Y-J, Wu H-M, Yang, P-F. Development of a Chinese Internet Addiction Scale and Its Psychometric Study. Chinese Journal of Psychology. 2003; 45(3): 279–294. doi:10.1037/t44491-000
  11. Malygin VL, Feklysov KA, Iskandirova AB, Antonenko AA. [Methodological approaches to the early detection of Internet dependent behavior]. Med Psihol Ross. 2011;6:32–33. [In Russian].
  12. Rosstat. [System for accessing survey results] [cited May 2, 2024]. Available from: https://obdx.gks.ru (accessed on 2024 May 2). [In Russian].
  13. You M, Laborde S, Ackermann S, Borges U, Dosseville F, Mosley E. Influence of Respiratory Frequency of Slow-Paced Breathing on Vagally-Mediated Heart Rate Variability. Appl Psychophysiol Biofeedback. 2024 Mar;49(1):133-143. doi: 10.1007/s10484-023-09605-2. Epub 2023 Dec 8. PMID: 38063977.
  14. Baevsky R, Ivanov G, Chireykin L, Gavrilushkin A, Dovgalevsky P, Kukushkin Y, Mironova T, Prilutsky D, Semenov A, Fedorov V, et al. [Analysis of heart rate variability when using different electrocardiographic systems (part 1)].  J. Arrhythmology. 2002;24:65–86 [In Russian].
  15. Makarov LM, Komolyatova VN, Kiseleva II, Fedina II, Besportochny DA, Dmitrieva AV, Zokirov NZ. [Standard ECG parameters in children.Guidelines]. Moscow: Publishing House "MEDPRACTIKA-M"; 2018: 20 p. [In Russian]
  16. Horsten M, Ericson M, Perski A, Wamala SP, Schenck-Gustafsson K, Orth-Gomér K. Psychosocial factors and heart rate variability in healthy women. Psychosom Med. 1999 Jan-Feb;61(1):49-57. doi: 10.1097/00006842-199901000-00009. PMID: 10024067.
  17. Lischke A, Jacksteit R, Mau-Moeller A, Pahnke R, Hamm AO, Weippert M. Heart rate variability is associated with psychosocial stress in distinct social domains. J Psychosom Res. 2018 Mar;106:56-61. doi: 10.1016/j.jpsychores.2018.01.005. Epub 2018 Jan 10. PMID: 29455900.
  18. Williams DP, Cash C, Rankin C, Bernardi A, Koenig J, Thayer JF. Resting heart rate variability predicts self-reported difficulties in emotion regulation: a focus on different facets of emotion regulation. Front Psychol. 2015 Mar 10;6:261. doi: 10.3389/fpsyg.2015.00261. PMID: 25806017; PMCID: PMC4354240.
  19. Geisler FC, Kubiak T, Siewert K, Weber H. Cardiac vagal tone is associated with social engagement and self-regulation. Biol Psychol. 2013 May;93(2):279-86. doi: 10.1016/j.biopsycho.2013.02.013. Epub 2013 Mar 1. PMID: 23466587.
  20. Clark CR, Ommerborn MJ, Hickson DA, Grooms KN, Sims M, Taylor HA, Albert MA. Neighborhood disadvantage, neighborhood safety and cardiometabolic risk factors in African Americans: biosocial associations in the Jackson Heart study. PLoS One. 2013 May 14;8(5):e63254. doi: 10.1371/journal.pone.0063254. PMID: 23691005; PMCID: PMC3653956.
  21. Diez Roux AV. Residential environments and cardiovascular risk. J Urban Health. 2003 Dec;80(4):569-89. doi: 10.1093/jurban/jtg065. PMID: 14709706; PMCID: PMC3456219.
  22. Voronina LV, Grigorishchin AV, Kovrov DY, Oshomkov TA. [Institutional environment as a factor in the development of the social infrastructure of the Arctic zone of the Northern macroregion.Corporate Governance and Innovative Economic Development of the North].Bulletin of Research Center of Corporate Law, Management and Venture Investment of Syktyvkar State University. 2022;2(2):145-156. doi 10.34130/2070-4992-2022-2-2-145. [In Russian]
  23. Lyarskaya E. Women and the tundra. A gender shift in the Yamalpeninsula? Forum for Anthropology and Culture. 2010;13:3-38. [In Russian]
  24. Zamyatina NY. [Regions and cities of the Arctic: specifics of socio-economic development (foreign experience and Russian realities)]. Available from: https://teach-in.ru/file/synopsis/pdf/regions-of-the-arctic-M-31.pdf [cited May 2, 2024].  [In Russian]
  25. Lin PC, Kuo SY, Lee PH, Sheen TC, Chen SR. Effects of internet addiction on heart rate variability in school-aged children. J Cardiovasc Nurs. 2014 Nov-Dec;29(6):493-8. doi: 10.1097/JCN.0b013e3182a477d5. PMID: 24088623.
  26. Cheng YC, Huang YC, Huang WL. Can Heart Rate Variability be Viewed as a Biomarker of Problematic Internet Use? A Systematic Review and Meta-Analysis. Appl Psychophysiol Biofeedback. 2023 Mar;48(1):1-10. doi: 10.1007/s10484-022-09557-z. Epub 2022 Aug 18. PMID: 35980558.
  27. Galchenko AS, Grigoriev PE, Poskotinova LV. [Comparative analysis of the severity of internet addiction in students of educational organizations in the regions of the Russian Federation]. Scientific Notes of V.I. Vernadsky Crimean Federal University. (Sociology. Pedagogy. Psychology). 2021;7(73):109-117. doi: 10.37279/2413-1709-2021-7-3-109-117. [In Russian].
  28. Grigoriev PE, Galchenko AS, Poskotinova LV. [Differences in the structure of internet addiction among girls and boys - students of senior classes of secondary schools]. The Humanities. 2021;3(55):123-127 [In Russian].

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Received May 9, 2024.
Accepted June 17, 2024.
©2024 International Medical Research and Development Corporation.