Therapeutic Science for Rehabilitation (재활치료과학)

Korean Society of Neurological Occupational Therapy (대한신경계작업치료학회)
권호 표지
DOI QR코드

DOI QR Code

Predicting Healthy Lifestyle Patterns in Older Community Dwelling Adults: A Latent Profile Analysis

잠재프로파일 분석을 활용한 한국 노인 라이프스타일 유형화와 영향요인 분석

  • Park, Kang-Hyun (Dept. of Occupational Therapy, Kangwon National University) ;
  • Yang, Min Ah (Osan Dementia Center) ;
  • Won, Kyung-A (Incheon Metropolitan Dementia Center) ;
  • Park, Ji-Hyuk (Dept. of Occupational Therapy, College of Software Digital Healthcare Convergence, Yonsei University)
  • 박강현 (강원대학교 작업치료학과) ;
  • 양민아 (오산시 치매안심센터) ;
  • 원경아 (인천광역시 광역치매센터) ;
  • 박지혁 (연세대학교 소프트웨어디지털헬스케어융합대학 작업치료학과)
  • Received : 2021.01.13
  • Accepted : 2021.03.03
  • Published : 2021.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

Objective : The aim of this study was to identify subgroups of older adults with respect to their lifestyle patterns and examine the characteristics of each subgroup in order to provide a basic evidence for improving the health and quality of life. Methods : This cross-sectional study was conducted in South Korea. Community-dwelling older adults (n=184) above the age of 65 years were surveyed from April 2019 to May 2019. This study used latent profile analysis to examine the subgroups. Chi-squared (χ2) and multinomial logistic regression measures were then used to analyze individual characteristics and influencing factors. Results : The pattern of physical activity which is one of the lifestyle domains in elderly was categorized into three types: 'passive exercise type (31.1%)', 'low intensity exercise type (54.5%)', and 'balanced exercise type(14.5%)'. Activity participation was divided into three patterns: 'inactive type (12%)', 'self-management type (61%)', and 'balanced activity participation type (27%)'. In terms of nutrition, there were only two groups: 'overall malnutrition type (13.5%)' and 'balanced nutrition type (86.5%)'. Furthermore, as a result of the multinomial logistic regression analysis to understand the effects of lifestyle types on the health and quality of life of the elderly, it was confirmed that the health and quality of life were higher in those following an active and balanced lifestyle. In addition, gender, education level and residential area were analyzed as predictive factors. Conclusion : The health and quality of life of the elderly can be improved when they have balanced lifestyle. Therefore, an empirical and policy intervention strategy should be developed and implemented to enhance the health and quality of life of the elderly.

목적 : 본 연구는 고령자의 라이프스타일이 어떤 형태로 유형화되는지에 대해 라이프스타일 잠재 집단 유형을 분석하고 각 집단의 유형별 특성을 파악하여 고령자의 건강과 삶의 질 증진을 위한 기초자료를 마련하기 위해 수행되었다. 연구방법 : 본 연구에는 횡단연구방법이 사용되었다. 2019년 4월부터 5월까지 고령자의 라이프스타일 유형을 파악하기 위해 만 65세 이상의 국내 지역사회 거주 노인 184명을 대상으로 설문조사가 이루어 졌다. 수집된 설문자료를 활용하여 잠재프로파일분석(LPA)을 실시하였고, 도출된 각 유형별 특성과 영향요인을 확인하기 위해 χ2 검정, 다항로지스틱회귀분석 등을 활용하였다. 결과 : 연구결과, 고령자의 라이프스타일은 중 첫 번째 영역인 신체적 활동부분에서는 '소극적 운동 참여형(31.1%)', '저강도 운동 집중형(54.5%)'과 '균형적 운동 참여형(14.5%)'인 3개의 잠재집단으로 분류되었다. 활동 참여의 경우 '비활동형(12%)', '생활유지형(61%)', '활동적 노년형(27%)'인 3집단으로 분류되었으며, 마지막 식이습관에 대한 경우 '전반적 영양부족형(13.5%)'과 '균형적 영양 섭취형(86.5%)' 2집단으로 분류되었다. 또한 라이프스타일 유형이 고령자의 건강과 삶의 만족도에 미치는 영향을 파악하기 위해 다항로지스틱회귀분석을 실시한 결과, 활동적·균형적 라이프스타일에 속할수록 삶의 질과 건강 수준이 전반적으로 높은 곳으로 확인되었다. 또한 이러한 유형의 예측요인에서 성별, 교육수준, 거주지역 등이 주요하게 작용하는 것으로 나타났다. 결론 : 고령자가 보다 다양한 활동에 균형적으로 참여하고, 활동적인 일상생활을 수행할 때 건강과 삶의 만족도가 증진됨이 분석되었다. 따라서 본 연구결과를 토대로 고령자의 라이프스타일 유형에 맞춘 실증적·정책적 개입 방안을 제안하였다.

Keywords

Acknowledgement

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A3A2074904).

References

  1. Bang, Y. S., Kim, H. Y., & Heo, M. (2009). Relationships between physical activity participation depression and body function of the elderly in community. The Korea Contens Society, 9(10), 227-237. doi:10.5392/JKCA.2009.9.10.227
  2. Bartos, R. (1980). Over 49-the invisible consumer market. Harvard Business Review, 58(1), 140-148.
  3. Celeux, G., & Soromenho, G. (1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification, 13(2), 195-212. doi:10.1007/BF01246098
  4. Chung, M. J., Kwak, T. K., Kim, H. Y., & Kang, M. (2018). Development of NQ-E, Nutrition Quotient for Korean elderly: Item selection and validation of factor structure. Journal of Nutrition and Health, 51(1), 87-102. doi:10.4163/jnh.2018.51.1.87
  5. Clark, F., Jackson, J., Carlson, M., Chou, C. P., Cherry, B. J., Jordan-Marsh, M., ... Azen, S. P. (2012). Effectiveness of a lifestyle intervention in promoting the well-being of independently living older people: Results of the well elderly 2 randomised controlled trial. Journal of Epidemiology and Community Health, 66(9), 782-790. doi:10.1136/jech.2009.099754
  6. Collins, L. M., Fidler, P. L., Wugalter, S. E., & Long, J. D. (1993). Goodness-of-fit testing for latent class models. Multivariate Behavioral Research, 28(3), 375-389. doi:10.1207/s15327906mbr2803_4.
  7. Engel, J. F., Blackwell, R. D., & Kollat, D. T. (1982). Consumer behavior (4th ed.), New York: The Dryden Press.
  8. Ferrari, P., Friedenreich, C., & Matthews, C. E. (2007). The role of measurement error in estimating levels of physical activity. American Journal of Epidemiology, 166(7), 832-840. doi:10.1093/aje/kwm148
  9. Ferreira, L. K., Meireles, J. F. F., & Ferreira, M. E. C. (2015). Evaluation of lifestyle and quality of life in the elderly: A literature review. Revista Brasileira de Geriatria e Gerontologia, 21(5), 616-627. doi:10.1590/1981-22562018021.180028
  10. Godwin, M., Streight, S., Dyachuk, E., van den Hooven, E. C., Ploemacher, J., Seguin, R., & Cuthbertson, S. (2008). Testing the simple lifestyle indicator questionnaire: Initial psychometric study. Canadian Family Physician, 54(1), 76-77.
  11. Hu, F. B., Liu, Y., & Willett, W. C. (2011). Preventing chronic diseases by promoting healthy diet and lifestyle: Public policy implications for China. Obesity Reviews, 12(7), 552-559. doi:10.1111/j.1467-789X.2011.00863.x
  12. Hur, J. S. (2014). Determinants of social participation activities among the elderly persons. Journal of Welfare for the Aged, 64, 235-263. doi:10.21194/kjgsw.64.201406.235
  13. Jackson, J. M., Zemke, R., Nelson, L., & Clark, F. (1999). Lifestyle redesign: Implementing the well elderly program (1st ed.). Bethesda, MD: AOTA Inc.
  14. Jedidi, K., Ramaswamy, V., & Desarbo, W. S. (1993). A maximum likelihood method for latent class regression involving a censored dependent variable. Psychometrika, 58(3), 375-394. doi:10.1007/BF02294647
  15. Jeon, H. S. (2016). A study on the lifestyle and the quality of life of senior citizens based on literature examination. Korean Journal of Sports Science, 25(4), 135-149.
  16. Jeon, H. S. (2017). A study on the lifestyles in old age based on scale reorganization. Korean Journal of Sports Science, 26(4), 193-206. doi:10.35159/kjss.2017.08.26.4.193
  17. Ji, B. T., Seok, S. J., Sin, D. M., Jung, J. H., & Kim, J. W. (2010). Analysis on the effects of health exercise by lifestyle patterns of the elderly. Korean Journal of Health Education and Promotion, 27(2), 69-78.
  18. Kang, E. N. (2017). Current state and challenges of senior employment programs. Health and Welfare Policy Forum, 2017(9), 28-39.
  19. Kang, E. N., & Lee, M. H. (2014). An exploratory study of social network type among nursing home residents: Focusing on external relationship resources of nursing facilities. Health and Social Welfare Review, 34(2), 133-160. doi:10.15709/hswr.2014.34.2.133
  20. Kim, K. R., Hong, S. A., & Kim, M. K. (2008). Nutritional status and food insufficiency of Korean population through the life-course by education level based on 2005 National Health and Nutrition Survey. The Korean Nutrition Society, 41(7), 667-681.
  21. Kim, M. O., & Cho, A. M. (2018). Relation between career choice factors and life satisfaction of youth by latent profile analysis. Korean Journal of Youth Studies, 25(12), 85-107. doi:10.21509/KJYS.2018.12.25.12.85
  22. Kim, S. H., & Hong, K. J. (2010). A study on the welfare attitude of Seoul citizens using the latent class analysis. Social Welfare Policy, 37(2), 95-121. doi:10.15855/swp.2010.37.2.95
  23. Kim, S. S., & Song, J. A. (2012). Investigation of the factors relative to the health promotion behavior practice among Korean elders residing in a retirement community. Journal of the Korea Gerontological Society, 32(1), 51-66.
  24. Lee, H. J., & Kim, D. J. (2011). Cultural adaptation and reliability testing of Korean version of the world health organization disability assessment schedule 2.0: 12-items version. Journal of the Korean Society of Physical Medicine, 6(4), 475-488.
  25. Lee, Y. H., & Choi, M. K. (2011). Fear of falling, depression, physical fitness and physical activity among community dwelling elders. Korean Journal of Adult Nursing, 23(4), 351-362.
  26. Lo, Y., Mendell, N., & Rubin, D. (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767-778. doi:10.1093/biomet/88.3.767
  27. Magidson, J., & Vermunt, J. (2002). Latent class models for clustering: A comparison with K-means. Canadian Journal of Marketing Research, 20(1), 37-44.
  28. Ministry of Health and Welfare. (2017). Living profiles of older people survey in Korea. 2017. Retrieved from http://www.mohw.go.kr/react/jb/sjb030301vw.jsp?PAR_MENU_ID=03&MENU_ID=032901&page=1&CONT_SEQ=344953
  29. Min, S. K., Kim, K. I., Lee, C. I., Jung, Y. C., Suh, S. Y., & Kim, D. K. (2002). Development of the Korean version of WHO quality of life scale and WHOQOL-BREF. Quality of Life Research, 11(6), 593-600. doi:10.1023/a:1016351406336
  30. Mooney, S. J., Joshi, S., Cerda, M., Quinn, J. W., Beard, J. R., Kennedy, G. J., ... Rundle, A. G. (2015). Patterns of physical activity among older adults in New York city. American Journal of Preventive Medicine, 49(3), 13-22. doi:10.1016/j.amepre.2015.02.015
  31. Moon, S. M. (2014). Types of health behavior clusters and related factors among Korean adults. Journal of Digital Convergence, 12(8), 397-410. doi:10.14400/JDC.2014.12.8.397
  32. Neugarten, B. L. (1968). Middle age and aging. Chicago: University of Chicago Press.
  33. Nylund, K. L., Asparouhov, T., & Muthen, B. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14(4), 535-569. doi:10.1080/10705510701575396
  34. Ovrum, A. (2011). Socioeconomic status and lifestyle choices: Evidence from latent class analysis. Health Economics, 20(8), 971-984. doi:10.1002/hec.1662
  35. Park, K., Han, D., Park, H. Y., Ha, S. M., & Park, J. (2019). Pilot research for development of multi-faceted lifestyle profile components affecting health and quality of life: Delphi survey. Korean Journal of Occupational Therapy, 27(3), 105-120. doi:10.14519/kjot.2019.27.3.08
  36. Park, K. H., & Park, J. H. (2019). Analysis of convergent influence of functional level, environmental factors and lifestyle on health and quality of life among elderly using structural equation model. Journal of the Korea Concergence Society, 10(12), 377-386. doi:10.15207/JKCS.2019.10.12.377
  37. Park, K. H., Won, K. A., & Park, J. H. (2019). Systematic study on the multifaceted lifestyle assessment tools for community-dwelling elderly: Trend and application prospect. Therapeutic Science for Rehabilitation, 8(3), 7-29. doi:10.22683/tsnr.2019.8.3.007
  38. Richardson, M. T., Ainsworth, B. E., Jacobs, D. R., & Leon, A. S. (2001). Validation of the Stanford 7-day recall to assess habitual physical activity. Annals of Epidemiology, 11(2), 145-153. doi:10.1016/s1047-2797(00)00190-3
  39. Roley, S. S., DeLany, J. V., Barrows, C. J., Brownrigg, S., Honaker, D., Sava, D. I., ... Youngstrom, M. J. (2008). Occupational therapy practice framework: Domain & process 2nd edition. The American Journal of Occupational Therapy, 62(6), 625-683. doi:10.5014/ajot.62.6.625
  40. Roth, P. L., & Switzer, F. S. III. (1995). A Monte Carlo analysis of missing data techniques in an HRM setting. Journal of Management, 21(5), 1003-1023. doi:10.1016/0149-2063(95)90052-7
  41. Seo, Y. M., Kang, M. S., & Jeon, M. Y. (2016). Predictive factors on level of physical activity in the community dwelling elderly. Journal of the Korea Convergence Society, 7(6), 151-160. doi:10.15207/JKCS.2016.7.6.151
  42. Sodergren, M., Wang, W. C., Salmon, J., Ball, K., Crawford, D., & McNaughton, S. A. (2014). Predicting healthy lifestyle patterns among retirement age older adults in the WELL study: A latent class analysis of sex differences. Maturitas, 77(1), 41-46. doi:10.1016/j.maturitas.2013.09.010
  43. Song, M. O., Jang, A. R., Jung, M. J., Hong, M., & Jang, C. (2013). Occupational therapy students perceive research on image. Journal of The Korean Society of Integrative Medicine, 1(3), 97-109. doi:10.15268/ksim.2013.1.3.097
  44. Switzer III, F. S., Roth, P. L., & Switzer, D. M. (1998). Systematic data loss in HRM settings: A Monte Carlo analysis. Journal of Management, 24(6), 763-779. doi:10.1016/S0149-2063(99)80083-X
  45. Wang, L., Lee, J. G., & Hwang, J. H. (2019). A big-data analysis on older adult's health and safrty issues. Journal of the Korea Contents Association, 19(4), 336-344. doi:10.5392/JKCA.2019.19.04.336
  46. World Health Organization. (2000). International Classification of Functioning, Disability and Health: ICF. Geneva: World Health Organization.
  47. World Health Organization. (2015). Noncommunicable disease. 2015. Retrieved from http://www.who.int/mediacentre/factsheets/fs355/en/
  48. Zanjani, S., Tol, A., Mohebbi, B., Sadeghi, R., Jalyani, K. N., & Moradi, A. (2015). Determinants of healthy lifestyle and its related factors among elderly people. Journal of Education Health Promotion, 4, 1-5. doi:10.4103/2277-9531.171817