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Influencing factors of sarcopenia in older adults based on the Newman system model: a case-control study.
Zhang, Yan; Zhang, Pan; Wang, Fenglan; Xing, Fengmei.
Afiliação
  • Zhang Y; School of Nursing and Rehabilitation, North China University of Science and Technology, No.21 Bohai Avenue, New Town, Caofeidian District, Tangshan City, 063210, Hebei Province, China.
  • Zhang P; School of Nursing and Rehabilitation, North China University of Science and Technology, No.21 Bohai Avenue, New Town, Caofeidian District, Tangshan City, 063210, Hebei Province, China.
  • Wang F; School of Nursing and Rehabilitation, North China University of Science and Technology, No.21 Bohai Avenue, New Town, Caofeidian District, Tangshan City, 063210, Hebei Province, China.
  • Xing F; Department of Clinical Medicine, North China University of Science and Technology, Tangshan, 063210, China. fengmeixing@ncst.edu.cn.
Eur Geriatr Med ; 14(5): 1049-1057, 2023 Oct.
Article em En | MEDLINE | ID: mdl-37378858
PURPOSE: Research on sarcopenia has primarily focused on single fields such as physiology or psychology. However, there is a lack of clear evidence to determine the influence of social factors on sarcopenia. Therefore, our aim was to explore the multidimensional factors that contribute to sarcopenia in older adults within the community. METHODS: In this retrospective case-control study, we applied the diagnostic criteria from The Asian Working Group on Sarcopenia (AWGS) 2019 to categorize study subjects into control and case groups. Our aim was to examine the impact of physical, psychological, and social factors on community-dwelling older adults with sarcopenia across multiple dimensions. We utilized descriptive statistics, as well as simple and multivariate logistic regression analyses, to analyze the data. We compared the odds ratios (OR) of the factors between the two groups and ranked the importance of the influencing factors using the XGBoost algorithm in Python software. RESULTS: Combined with multivariate analysis and XGBoost algorithm results, it can be seen that physical activity is the strongest predictor of sarcopenia [OR] = 0.922(95% CI 0.906-0.948), followed diabetes mellitus [OR] = 3.454(95% CI 1.007-11.854), older age [OR] = 1.112(95% CI 1.023-1.210), divorced or widowed [OR] = 19.148 (95% CI 4.233-86.607), malnutrition [OR] = 18.332(95% CI 5.500-61.099), and depressed [OR] = 7.037(95% CI 2.391-20.710). CONCLUSIONS: Factors associated with the development of sarcopenia in community-dwelling older adults cover a multiplicity of physical, psychological, and social factors, physical activity, diabetes mellitus, age, marital status, nutrition, and depression were important factors that have an impact on sarcopenia. REGISTRATION NUMBER: ChiCTR2200056297.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article