Article Data

  • Views 1214
  • Dowloads 153

Original Research

Open Access

EVALUATION OF THE DIFFERENCES OF HOUSEHOLD INCOME AND PHYSICAL FITNESS VARIABLES IN ELDERLY KOREANS

  • Hyunkyun Ahn1
  • Wi-Young So2

1Assistant Professor, Sport Leisure & Studies, Art and Health Department, Myongji College, Seoul, Korea

2Associate Professor, Sports and Health Care Major, College of Humanities and Arts, Korea National University of Transportation, Chungju-si, Korea

DOI: 10.22374/1875-6859.14.3.7 Vol.14,Issue 3,June 2018 pp.41-48

Published: 07 June 2018

*Corresponding Author(s): Wi-Young So E-mail: wowso@ut.ac.kr

Abstract

Background and Objective

Physical activity and fitness are complementary to each other, but they are independent concepts with re-gard to health. Although there are some studies about the relationship between one’s physical activity and economic level, there are very few studies about the relationship between one’s fitness level and economic level. Therefore, this study aimed to investigate the fitness level of elderly Koreans according to their economic level.

Material and Methods

In 2015, 1,068 elderly Koreans (men=452, women=616) over 65 years of age participated in the Korean national fitness assessment. Their household income was collected using a self-report survey, and physical fitness variables (grip strength, sit-up, sit to stand, sit and reach, back scratch, one leg standing with eyes open, and 6-minute walk) were measured directly. Then the differences between household income and physical fitness variables were evaluated by conducting one-way analysis of variance (ANOVA) and the Tukey test (post-hoc testing).

Results

Elderly men showed significant differences in grip strength (p=0.009), sit-up (p<0.001), and sit to stand (p<0.001) according to the four household income groups (under 70,000 won group, 700,000 to under 2,030,000 won group, 2,030,000 to under 3,500,000 won group, and over 3,500,000 won group) by one-way ANOVA. Elderly women showed significant differences in grip strength (p=0.001), sit-up (p<0.001), one leg standing with eyes open (p=0.048), and 6-minute walk (p<0.001) according to the four groups by one-way ANOVA.

Conclusion

Physical fitness variables related to muscular strength and muscular endurance can be affected by household income in elderly Koreans.

Cite and Share

Hyunkyun Ahn,Wi-Young So. EVALUATION OF THE DIFFERENCES OF HOUSEHOLD INCOME AND PHYSICAL FITNESS VARIABLES IN ELDERLY KOREANS. Journal of Men's Health. 2018. 14(3);41-48.

References

1. World Health Organization. Obesity and overweight. Geneva. World Health Organization; 2017. http://www. who.int/mediacentre/factsheets/fs311/en/

2. Flegal KM, Kit BK, Orpana H, et al. Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. J Am Med Assoc 2013;309:71–82.

3. Glass TA. Social class and child health: our complex-ity complex. In: NS Landsdale, SM McHale, A Booth, eds. Families and Child Health. New York: Springer Science; 2013.

4. Dixon JB. The effect of obesity on health outcomes. Mol Cell Endocrinol 2010;316:104–108.

5. Lee BY, Bartsch SM, Mui Y, et al. A systems approach to obesity. Nutr Rev 2017;75(suppl 1):94–106.

6. Hammond RA, Levine R. The economic impact of obesity in the United States. Diabetes Metab Syndr Obes 2010;3:285–95.

7. Go AS, Mozaffarian D, Roger VL, et al. Executive summary: heart disease and stroke statistics--2013 update: a report from the American Heart Association. Circulation 2013;127(1):143–52.

8. Zamboni M, Mazzali G, Fantin F, et al. Sarcopenic obesity: a new category of obesity in the elderly. Nutr Metab Cardiovasc Dis 2008;18(5):388–95.

9. Nair KS. Aging muscle. Am J Clin Nutr 2005;81(5):953–63.

10. Thomas AW, Albert JS. Handbook of obesity treatment(3rd ed.). New York: Guilford Press. USA; 2002.

11. Wang Y, Beydoun MA. The obesity epidemic in the United States--gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and meta-regression analysis. Epidemiol Rev 2007;29:6–28.

12. Jakicic JM, Rogers RJ, Davis KK, et al. Role of physical activity and exercise in treating patients with overweight and obesity. Clin Chem 2018;64(1):99–107.

13. Matsushita M, Harada K, Arao T. Socioeconomic posi-tion and work, travel, and recreation-related physical activity in Japanese adults: a cross-sectional study. BMC Public Health 2015;15:916.

14. Kim IG, So WY. The relationship between household income and physical activity in Korea. J Phys Ther Sci 2014;26(12):1887–9.

15. Dunneram Y, Jeewon R. A scientific assessment of sociodemographic factors, physical activity level, and nutritional knowledge as determinants of dietary quality among Indo-Mauritian women. J Nutr Metab 2013;2013:572132.

16. Fokeena WB, Jeewon R. Is there an association between socioeconomic status and body mass index among adoles-cents in Mauritius? Scientif World J 2012;2012:750659.

17. Bhurosy T, Jeewon R. Overweight and obesity epidemic in developing countries: a problem with diet, physical activity, or socioeconomic status? Scientif World J 2014;2014:964236.

18. Frontera WR, Reid KF, Phillips EM, et al. Muscle fiber size and function in elderly humans: a longitudinal study. J Appl Physiol (1985) 2008;105(2):637–42.

19. Zamboni M, Mazzali G, Fantin F, et al. Sarcopenic obesity: a new category of obesity in the elderly. Nutr Metab Cardiovasc Dis 2008;18(5):388–95.

20. Stenholm S, Harris TB, Rantanen T, et al. Sarcopenic obesity: definition, cause and consequences. Curr Opin Clin Nutr Metab Care 2008;11(6):693–700.

21. Batsis JA, Mackenzie TA, Barre LK, et al. Sarcopenia, sarcopenic obesity and mortality in older adults: results from the National Health and Nutrition Examination Survey III. Eur J Clin Nutr 2014;68(9):1001–7.

22. Williams PT. Physical fitness and activity as separate heart disease risk factors: a meta-analysis. Med Sci Sports Exerc 2001;33(5):754–61.

23. Choi EJ, Yoo BW, So WY, et al. The relationship between socio-economic factors and physical fitness variables among Korean adults. J Mens Health 2017;13(1):e37–e44.

24. Heyward VH, Gibson A. Advanced fitness assessment and exercise prescription 7th edition. Champaign, IL: Human Kinetics; 2014.

25. Rikli RE, Jones CJ. Senior fitness test manual. 2nd edi-tion. Champaign, IL: Human Kinetics; 2013.

26. Cooper C, Fielding R, Visser M, et al. Tools in the assess-ment of sarcopenia. Calcif Tissue Int 2013;93(3):201–10.

27. Bouchard DR, Dionne IJ, Brochu M. Sarcopenic/obesity and physical capacity in older men and women: data from the nutrition as a determinant of successful ag-ing (NuAge) – the Quebec longitudinal study. Obesity 2009;17(11):2082–8.

28. Levine ME, Crimmins EM. The impact of insulin re-sistance and inflammation on the association between sarcopenic obesity and physical functioning. Obesity 2012;20(10):2101–6.

29. Reginster JY, Cooper C, Rizzoli R, et al. Recom-mendations for the conduct of clinical trials for drugs to treat or prevent sarcopenia. Aging Clin Exp Res 2016;28(1):47–58.

30. Stenholm S, Maggio M, Lauretani F, et al. Anabolic and catabolic biomarkers as predictors of muscle strength decline: the InCHIANTI study. Rejuvenation Res 2010;13(1):3–11.

31. Paddon-Jones D, Rasmussen BB. Dietary protein rec-ommendations and the prevention of sarcopenia. Curr Opin Clin Nutr Metab Care 2009;12(1):86–90.

32. Galobardes B, Shaw M, Lawlor DA, et al. W, Davey Smith G. Indicators of socioeconomic position (part 1). J Epidemiol Community Health 2006;60(1):7–12.

33. Meijer M, Röhl J, Bloomfield K, et al. Do neighbor-hoods affect individual mortality? A systematic review and meta-analysis of multilevel studies. Soc Sci Med 2012;74(8):1204–12.

34. Bergström G, Redfors B, Angerås O, et al. Low socioeco-nomic status of a patient’s residential area is associated with worse prognosis after acute myocardial infarction in Sweden. Int J Cardiol 2015;182:141–7.

35. Rawshani A, Svensson AM, Rosengren A, et al. Impact of socioeconomic status on cardiovascular disease and mortality in 24,947 individuals with type 1 diabetes. Diabet Care 2015;38(8):1518–27.

36. Utzinger J, Becker SL, Knopp S, et al. Neglected tropical diseases: diagnosis, clinical management, treatment and control. Swiss Med Wkly 2012;142:w13727.

37. Yap P, Wu FW, Du ZW, et al. Effect of deworming on physical fitness of school-aged children in Yunnan, China: a double-blind, randomized, placebo-controlled trial. PLoS Negl Trop Dis 2014;8(7):e2983.

38. Lindgren M, Börjesson M, Ekblom Ö, et al. Physical activity pattern, cardiorespiratory fitness, and socioeco-nomic status in the SCAPIS pilot trial - A cross-sectional study. Prev Med Rep 2016;4:44–9

39. Wang CY, Haskell WL, Farrell SW, et al. Cardiores-piratory fitness levels among US adults 20-49 years of age: findings from the 1999-2004 National Health and Nutrition Examination Survey. Am J Epidemiol 2010;171(4):426–35.

40. Milanović Z, Pantelić S, Trajković N, et al. Age-related decrease in physical activity and functional fitness among elderly men and women. Clin Interv Aging 2013;8:549–56.

41. Martin PE, Morgan DW. Biomechanical considerations for economical walking and running. Med Sci Sports Exerc 1992;24(4):467–74.

42. Caspersen CJ, Pereira MA, Curran KM. Changes in physical activity patterns in the United States, by sex and cross-sectional age. Med Sci Sports Exerc 2000;32(9):1601–9.

43. Ministry of Culture, Sports and Tourism. National Sur-vey on the Current Status of Participation of Lifetime Sport in Korea; 2017.

44. Church TS, Earnest CP, Skinner JS, Blair SN. Effects of different doses of physical activity on cardiorespi-ratory fitness among sedentary, overweight or obese postmenopausal women with elevated blood pressure: a randomized controlled trial. AMA 2007;297(19):2081–91.

Abstracted / indexed in

Science Citation Index Expanded (SciSearch) Created as SCI in 1964, Science Citation Index Expanded now indexes over 9,200 of the world’s most impactful journals across 178 scientific disciplines. More than 53 million records and 1.18 billion cited references date back from 1900 to present.

Journal Citation Reports/Science Edition Journal Citation Reports/Science Edition aims to evaluate a journal’s value from multiple perspectives including the journal impact factor, descriptive data about a journal’s open access content as well as contributing authors, and provide readers a transparent and publisher-neutral data & statistics information about the journal.

Directory of Open Access Journals (DOAJ) DOAJ is a unique and extensive index of diverse open access journals from around the world, driven by a growing community, committed to ensuring quality content is freely available online for everyone.

SCImago The SCImago Journal & Country Rank is a publicly available portal that includes the journals and country scientific indicators developed from the information contained in the Scopus® database (Elsevier B.V.)

Publication Forum - JUFO (Federation of Finnish Learned Societies) Publication Forum is a classification of publication channels created by the Finnish scientific community to support the quality assessment of academic research.

Scopus: CiteScore 0.7 (2022) Scopus is Elsevier's abstract and citation database launched in 2004. Scopus covers nearly 36,377 titles (22,794 active titles and 13,583 Inactive titles) from approximately 11,678 publishers, of which 34,346 are peer-reviewed journals in top-level subject fields: life sciences, social sciences, physical sciences and health sciences.

Norwegian Register for Scientific Journals, Series and Publishers Search for publication channels (journals, series and publishers) in the Norwegian Register for Scientific Journals, Series and Publishers to see if they are considered as scientific. (https://kanalregister.hkdir.no/publiseringskanaler/Forside).

Submission Turnaround Time

Conferences

Top