The Korean journal of sports medicine (대한스포츠의학회지)

The Korean Society of Sports Medicine (대한스포츠의학회)
권호 표지
DOI QR코드

DOI QR Code

The Difference of Body Mass Index According to Smart Phone Proficiency in Koreans over the Age of 60

장노년층 스마트폰 활용능력에 따른 체질량지수 차이

  • Kim, Joon-Sik (Department of Physical Education, Seoul National University) ;
  • Kim, Jung-Woon (Department of Physical Education, Seoul National University) ;
  • Hahn, Sowon (Department of Psychology, Seoul National University) ;
  • Kim, Yeon-Soo (Institute of Sport Science, Seoul National University)
  • 김준식 (서울대학교 체육교육과) ;
  • 김정운 (서울대학교 체육교육과) ;
  • 한소원 (서울대학교 심리학과) ;
  • 김연수 (서울대학교 스포츠과학연구소)
  • Received : 2018.05.10
  • Accepted : 2018.11.08
  • Published : 2018.12.01
⟨ Previous Next ⟩

Abstract

Purpose: The purpose of this study was to compare the difference of body mass index (BMI) to smart phone proficiency in men and women over the age of 60. Methods: Patients were divided into three groups with high (n=33), average (n=34), and low (n=33) smart phone proficiency. Fitness characteristics related to smart phone usage were evaluated by measuring cardiorespiratory endurance, grip strength, eye-hand coordination. As well, smart phone proficiency was evaluated by a self-reported questionnaire and a smart phone usability task that was composed of two categories: usage of the smartphone device itself and usage of phone applications. The differences in BMI of the subjects was analyzed by analysis of covariance adjusting for independent variables including age, smartphone usage period, eye-hand coordination, education and income. Results: There was a significant difference in BMI among the three groups after adjustment of age, eye-hand coordination, smartphone usage period, education and income. The results showed that the self-reported questionnaire showed a significant difference in BMI between high proficiency and low proficiency groups (high $24.88{\pm}2.46$, low $23.37{\pm}2.56$; p=0.037). Smart phone usability test results also showed a significant difference in BMI among the three groups (high $25.18{\pm}2.58$, low $23.15{\pm}2.6$; p=0.000 and high $25.18{\pm}2.58$, middle $23.57.7{\pm}1.69$; p=0.010). Conclusion: Our results suggest that high smart phone proficiency shows increased BMI in the elderly. This study suggests that people over the age of 60 who have high smartphone proficiency should be cautious of an increased BMI score.

Keywords

Acknowledgement

Supported by : Seoul National University

References

  1. Noh BS, Ahn SY, Ahn HS, Nam GS, Lee JW. Technology trends and forecasts based on smart content classification. Korea Inst Inf Technol Mag 2012;10:97-110.
  2. Pew Research Center. Smartphones are more common in Europe, U.S., less so in developing countries [Internet]. Washington (DC): Pew Research Center; 2016 [cited 2018 Nov 19]. Available from: http://www.pewglobal.org/2016/02/22/smartphone-ownership-and-internet-usage-continues-to-climbin-emerging-economies/technology-report-01-02b/.
  3. Kakihara M. Mobile apps in APAC: 2016 report [Internet]. Think with Google; 2016 [cited 2018 Nov 19]. Available from: http://apac.thinkwithgoogle.com/articles/mobile-apps-in-apac-2016-report.html.
  4. Boulos MN, Wheeler S, Tavares C, Jones R. How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYX. Biomed Eng Online 2011;10:24. https://doi.org/10.1186/1475-925X-10-24
  5. Ahmad RW, Gani A, Hamid SH, Xia F, Shiraz M. A review on mobile application energy profiling: taxonomy, state-ofthe-art, and open research issues. J Netw Comput Appl 2015;58:42-59. https://doi.org/10.1016/j.jnca.2015.09.002
  6. Pejovic V, Musolesi M. Anticipatory mobile computing: a survey of the state of the art and research challenges. ACM Comput Surv 2015;47:1-29.
  7. Hwang KH, Yoo YS, Cho OH. Smartphone overuse and upper extremity pain, anxiety, depression, and interpersonal relationships among college students. J Korea Contents Assoc 2012;12:365-75. https://doi.org/10.5392/JKCA.2012.12.10.365
  8. Choi D. Physical activity level, sleep quality, attention control and self-regulated learning along to smartphone addiction among college students. J Korea Acad Industr Coop Soc 2015;16:429-37. https://doi.org/10.5762/KAIS.2015.16.1.429
  9. Paek KS. A convergence study the association between addictive smart phone use, dry eye syndrome, upper extremity pain and depression among college students. J Korea Converg Soc 2017;8:61-9. https://doi.org/10.15207/JKCS.2017.8.1.061
  10. Choi DJ. Jung B. 2011 The report on the digital divide for the elderly [Internet]. Seoul (KR): National Information Society Agency; 2012 [cited 2018 Nov 19]. Available from: https://nia.or.kr/site/nia_kor/ex/bbs/View.do?cbIdx=81623&bcIdx=6724.
  11. Namu Wiki. Feature phone [Internet]. Asuncion (PY): Namu Wiki; 2018 [cited 2018 Oct 3]. Available from: https://namu.wiki/w/%ED%94%BC%EC%B2%98%ED%8F%B0.
  12. Kim JT, Son CY, GO EH, Ryu SS, Kim BS, Choi JA. 2016 The report on the digital divide [Internet]. Seoul (KR): National Information Society Agency; 2017 [cited 2018 Nov 19]. Available from: http://www.nia.or.kr/site/nia_kor/ex/bbs/View.do?cbIdx=81623&bcIdx=18397&parentSeq=18397.
  13. de Rezende LF, Rey-Lopez JP, Matsudo VK, do Carmo Luiz O. Sedentary behavior and health outcomes among older adults: a systematic review. BMC Public Health 2014;14:333. https://doi.org/10.1186/1471-2458-14-333
  14. de Rezende LF, Rodrigues Lopes M, Rey-Lopez JP, Matsudo VK, Luiz Odo C. Sedentary behavior and health outcomes: an overview of systematic reviews. PLoS One 2014;9:e105620. https://doi.org/10.1371/journal.pone.0105620
  15. Matthews CE, Chen KY, Freedson PS, et al. Amount of time spent in sedentary behaviors in the United States, 2003-2004. Am J Epidemiol 2008;167:875-81. https://doi.org/10.1093/aje/kwm390
  16. Korea Centers for Disease Control and Prevention. Korea Health Statistics 2015: Korea National Health and Nutrition Examination Survey (KNHANES VI-3). Cheongju: Korea Centers for Disease Control and Prevention; 2015.
  17. Ministry of Culture, Sports and Tourism. 2014 The report on national leisure activities [Internet]. Sejong (KR): Ministry of Culture, Sports and Tourism; 2015 [cited 2018 Nov 19]. Available from: http://www.mcst.go.kr/web/s_policy/dept/dept-View.jsp?pMenuCD=0406000000&pSeq=1562.
  18. Matthews CE, George SM, Moore SC, et al. Amount of time spent in sedentary behaviors and cause-specific mortality in US adults. Am J Clin Nutr 2012;95:437-45. https://doi.org/10.3945/ajcn.111.019620
  19. Yoon HJ. Television watching and depression symptoms in later life: an interdisciplinary approach to the leisure cultures and lives of older Korean adults. Korea Sci Art Forum 2015;21:313-23. https://doi.org/10.17548/ksaf.2015.09.21.313
  20. Owen N, Sparling PB, Healy GN, Dunstan DW, Matthews CE. Sedentary behavior: emerging evidence for a new health risk. Mayo Clin Proc 2010;85:1138-41. https://doi.org/10.4065/mcp.2010.0444
  21. Dunstan DW, Barr EL, Healy GN, et al. Television viewing time and mortality: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Circulation 2010;121:384-91. https://doi.org/10.1161/CIRCULATIONAHA.109.894824
  22. Thorp AA, Healy GN, Owen N, et al. Deleterious associations of sitting time and television viewing time with cardiometabolic risk biomarkers: Australian Diabetes, Obesity and Lifestyle (AusDiab) study 2004-2005. Diabetes Care 2010;33:327-34. https://doi.org/10.2337/dc09-0493
  23. Grontved A, Hu FB. Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: a meta-analysis. JAMA 2011;305:2448-55. https://doi.org/10.1001/jama.2011.812
  24. Jung YC. KISDI STAT report: possibility of smartphone and TV competition media [Internet]. Jincheon (KR): Korea Information Society Development Institute; 2017 [cited 2018 Nov 19]. Available from: https://www.kisdi.re.kr/kisdi/common/premium?file=1%7C14016.
  25. Lepp A, Barkley JE, Sanders GJ, Rebold M, Gates P. The relationship between cell phone use, physical and sedentary activity, and cardiorespiratory fitness in a sample of U.S. college students. Int J Behav Nutr Phys Act 2013;10:79. https://doi.org/10.1186/1479-5868-10-79
  26. Tremblay MS, Colley RC, Saunders TJ, Healy GN, Owen N. Physiological and health implications of a sedentary lifestyle. Appl Physiol Nutr Metab 2010;35:725-40. https://doi.org/10.1139/H10-079
  27. Hartley AA, Little DM. Age-related differences and similarities in dual-task interference. J Exp Psychol Gen 1999;128:416-49. https://doi.org/10.1037/0096-3445.128.4.416
  28. Crossley M, Hiscock M. Age-related differences in concurrent-task performance of normal adults: evidence for a decline in processing resources. Psychol Aging 1992;7:499-506. https://doi.org/10.1037/0882-7974.7.4.499
  29. Kim SE, Kim JW, Jee YS. Relationship between smartphone addiction and physical activity in Chinese international students in Korea. J Behav Addict 2015;4:200-5. https://doi.org/10.1556/2006.4.2015.028