한국전문물리치료학회지 (Physical Therapy Korea)

  • 제28권3호
  • /
  • Pages.177-185
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  • 2021
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  • 1225-8962(pISSN)
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  • 2287-982X(eISSN)
한국전문물리치료학회 (Korean Research Society of Physical Therapy)
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Risk Factors for Sarcopenia, Sarcopenic Obesity, and Sarcopenia Without Obesity in Older Adults

  • Kim, Seo-hyun (Department of Physical Therapy, The Graduate School, Yonsei University) ;
  • Yi, Chung-hwi (Department of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University) ;
  • Lim, Jin-seok (Department of Physical Therapy, The Graduate School, Yonsei University)
  • 투고 : 2021.06.24
  • 심사 : 2021.07.08
  • 발행 : 2021.08.20
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초록

Background: Muscle undergoes change continuously with aging. Sarcopenia, in which muscle mass decrease with aging, is associated with various diseases, the risk of falling, and the deterioration of quality of life. Obesity and sarcopenia also have a synergy effect on the disease of the older adults. Objects: This study examined the risk factors for sarcopenia, sarcopenic obesity, and sarcopenia without obesity and developed prediction models. Methods: This machine-learning study used the 2008-2011 Korea National Health and Nutrition Examination Surveys in the analysis. After data curation, 5,563 older participants were selected, of whom 1,169 had sarcopenia, 538 had sarcopenic obesity, and 631 had sarcopenia without obesity; the remaining 4,394 were normal. Decision tree and random forest models were used to identify risk factors. Results: The risk factors for sarcopenia chosen by both methods were body mass index (BMI) and duration of moderate physical activity; those for sarcopenic obesity were sex, BMI, and duration of moderate physical activity; and those for sarcopenia without obesity were BMI and sex. The areas under the receiver operating characteristic curves of all prediction models exceeded 0.75. BMI could predict sarcopenia-related disease. Conclusion: Risk factors for sarcopenia-related diseases should be identified and programs for sarcopenia-related disease prevention should be developed. Data-mining research using population data should be conducted to enhance the effectiveness of early treatment for people with sarcopenia-related diseases through predictive models.

키워드

과제정보

This study was supported by the "Brain Korea 21 FOUR Project", the Korean Research Foundation for Department of Physical Therapy in the Graduate School of Yonsei University.

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