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Validation of the modified MNA with its long-term mortality-predicting ability

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Academic year: 2022

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Background: Nutrition is a key element in maintaining health in the elderly whereas assessment is the key in detecting emerging nutritional problems. The Mini Nutritional Assessment (MNA) is a simple and non- invasive assessment tool and it has been modified according to population-specific anthropometric cut- points. However, these modified tools have not yet been tested with robust standards.

Objective: This study attempted to validate the two modified versions of the MNA with a more robust standard, the long-term mortality-predictive ability of the tool.

Methods: Data used in this analysis was the ?Survey of Health and Living Status of the Elderly in Taiwan, SHLSET? conducted by the Bureau of Health Promotion of Taiwan. All subjects were rated into three levels of nutritional status, malnourished, at risk of malnutrition or normal, according to either the original or two modified versions of the MNA. Kaplan-Meier survival analysis was performed to determine the differences between the two survival curves for the 4 follow-up years. Regression analysis was also performed to determine the significance of impact of nutritional status on survivability.

Results: During the 4-year follow-up period, subjects rated malnourished by the MNA had a two-fold mortality risk of those rated at risk and 6-7 folds of those rated normal. Survival analysis showed that the survival curves were significantly different from each other among the three rated nutritional groups.

Overall, the modified Taiwan version-2 had the best predictive ability whereas the modified version-1 was the next. Regression analysis showed clear significant predictive ability of the MNA.

Conclusion: Results of this study indicate that all three versions of the MNA have fairly good mortality- predicting ability. However, the two modified versions, especially Taiwan version-2, have stronger

predictive abilities. These results suggest that the modified MNA may be of value in developing into a tool for predicting the long-term care needs of the elderly.

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