Alan C Tsai1, Mei-Yen Lai2. 1. Department of Healthcare Administration, Asia University, 500 Liufeng Road, Wufeng, Taichung 41354, Taiwan, ROC; Department of Health Services Management, School of Public Health, China Medical University, Taichung 40402, Taiwan, ROC. Electronic address: atsai@umich.edu. 2. Department of Healthcare Administration, Asia University, 500 Liufeng Road, Wufeng, Taichung 41354, Taiwan, ROC; Nursing Department, Taichung Veterans General Hospital, Taichung, Taiwan, ROC. Electronic address: bs88877@yahoo.com.tw.
Abstract
BACKGROUND & AIMS: Falling is a major issue in geriatric health. Tools that identify individuals at risk of falling can help reduce the risk of falling. The study aimed to determine whether the full and short-form Mini Nutritional Assessment (MNAs) have the ability to predict the risk of falling in older adults. METHODS: Subjects were 3118 ≥ 53-year old Taiwanese who completed both the 1999 and 2003 "Taiwan Longitudinal Study on Aging" surveys. We rated these subjects with normalized versions of the MNA and applied the standard cut-offs to define under-nutrition (≤23.5 and ≤11 points, respectively). We used multivariate logistic regression analysis and receiver operating characteristics to evaluate the ability of these tools in predicting the risk of falling three years later. RESULTS: Older adults rated as at risk of malnutrition with the full MNA (OR = 1.87, 95% confidence interval = 1.33-2.63, p < 0.001) or the short-form (1.39, 1.07-1.80, p = 0.014) were associated with increased risk of falling three years later. Both versions significantly predicted the risk of falling and performed slightly better in ≥65-year old persons than in younger (53-64-year old) persons. The short-form performed relatively well compared to the full scale. CONCLUSIONS: Results suggest that the full and short-form MNAs, in addition to rating the risk of malnutrition, also predict the risk of falling in older adults. Although the short-form is slightly less effective than the full scale in predicting the future risk of falling, its simplicity, effectiveness and efficiency make it ideal as a multipurpose screening tool in clinical settings.
BACKGROUND & AIMS: Falling is a major issue in geriatric health. Tools that identify individuals at risk of falling can help reduce the risk of falling. The study aimed to determine whether the full and short-form Mini Nutritional Assessment (MNAs) have the ability to predict the risk of falling in older adults. METHODS: Subjects were 3118 ≥ 53-year old Taiwanese who completed both the 1999 and 2003 "Taiwan Longitudinal Study on Aging" surveys. We rated these subjects with normalized versions of the MNA and applied the standard cut-offs to define under-nutrition (≤23.5 and ≤11 points, respectively). We used multivariate logistic regression analysis and receiver operating characteristics to evaluate the ability of these tools in predicting the risk of falling three years later. RESULTS: Older adults rated as at risk of malnutrition with the full MNA (OR = 1.87, 95% confidence interval = 1.33-2.63, p < 0.001) or the short-form (1.39, 1.07-1.80, p = 0.014) were associated with increased risk of falling three years later. Both versions significantly predicted the risk of falling and performed slightly better in ≥65-year old persons than in younger (53-64-year old) persons. The short-form performed relatively well compared to the full scale. CONCLUSIONS: Results suggest that the full and short-form MNAs, in addition to rating the risk of malnutrition, also predict the risk of falling in older adults. Although the short-form is slightly less effective than the full scale in predicting the future risk of falling, its simplicity, effectiveness and efficiency make it ideal as a multipurpose screening tool in clinical settings.
Authors: Christoph Ihle; Christoph Weiß; Gunnar Blumenstock; Ulrich Stöckle; Björn Gunnar Ochs; Christian Bahrs; Andreas Nüssler; Anna Janine Schreiner Journal: BMC Musculoskelet Disord Date: 2018-03-15 Impact factor: 2.362
Authors: Pengfei Ren; Xianliang Zhang; Litao Du; Yang Pan; Si Chen; Qiang He Journal: Int J Environ Res Public Health Date: 2022-03-03 Impact factor: 3.390