Using A Reclassification Method To Evaluate The Improvement Of Mini Nutritional Assessment-Taiwan Version In Predicting The Mortality Of Older Taiwanese

碩士 === 亞洲大學 === 健康產業管理學系健康管理組 === 100 === Background: Malnutrition is a common problem in geriatric health. The Mini Nutritional Assessment (MNA) has been widely applied in gerontological care. To normalize the MNA for Taiwan population, the MNA-Taiwan version 1 (MNA-T1) and version 2 (MNA-T2) have...

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Main Authors: Chen,YaHui, 陳雅惠
Other Authors: Wang, JiunYi
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/01304741951976334876
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spelling ndltd-TW-100THMU07430042015-10-13T21:07:18Z http://ndltd.ncl.edu.tw/handle/01304741951976334876 Using A Reclassification Method To Evaluate The Improvement Of Mini Nutritional Assessment-Taiwan Version In Predicting The Mortality Of Older Taiwanese 以重分類方法評估台灣修訂版簡易營養評估量表預測台灣中老年人死亡風險的改進能力 Chen,YaHui 陳雅惠 碩士 亞洲大學 健康產業管理學系健康管理組 100 Background: Malnutrition is a common problem in geriatric health. The Mini Nutritional Assessment (MNA) has been widely applied in gerontological care. To normalize the MNA for Taiwan population, the MNA-Taiwan version 1 (MNA-T1) and version 2 (MNA-T2) have been developed. The validity of the two versions requires further investigation. Objectives: The study aimed to determine the improvement of the two versions in predicting the mortality risk of older Taiwanese. Methods: We analyzed the 1999 and 2003 data of the “Survey of Health and Living Status of the Elderly in Taiwan (SHLSET)”. A sample of 4,261 subjects with 53 years old or older was recruited. The Net Reclassification Improvement (NRI) and the Cox regression with Akaike's information criterion (AIC) were used to evaluate the improvement of the MNA-T1 and MNA-T2 in predicting the 4-years follow-up mortality risk. Results: The NRI were 0.004 (p = 0.726) and −0.010 (p = 0.454) if the MNA in the predictive model was replaced by the MNA-T1 and MNA-T2, respectively. The NRI was −0.012 (p = 0.052) if the MNA-T1 in the model was replaced by the MNA-T2. The model fitting index AIC were 8,987.3, 8,204.4, 8,218.1 and 8,214.2 for the Cox regression models with CV (control variables) only, CV + MNA, CV + MNA-T1 and CV + MNA-T2, respectively. It implied that the fitting of the model gets much better if any of the three MNA versions was included in the model. However, there were only small differences among the three versions. Conclusions: The result shows that the mortality-predictive ability of the MNA-T1 and the MNA-T2 did not significantly superior to the original MNA. Beacuse there is no “gold standard” for identifying subjects with malnutrition, we just take mortality as an external reference in this study. More studies may be required to confirm the validity of the modified versions. Wang, JiunYi Tsai, AlanC 王俊毅 蔡仲弘 2012 學位論文 ; thesis 57 zh-TW
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language zh-TW
format Others
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description 碩士 === 亞洲大學 === 健康產業管理學系健康管理組 === 100 === Background: Malnutrition is a common problem in geriatric health. The Mini Nutritional Assessment (MNA) has been widely applied in gerontological care. To normalize the MNA for Taiwan population, the MNA-Taiwan version 1 (MNA-T1) and version 2 (MNA-T2) have been developed. The validity of the two versions requires further investigation. Objectives: The study aimed to determine the improvement of the two versions in predicting the mortality risk of older Taiwanese. Methods: We analyzed the 1999 and 2003 data of the “Survey of Health and Living Status of the Elderly in Taiwan (SHLSET)”. A sample of 4,261 subjects with 53 years old or older was recruited. The Net Reclassification Improvement (NRI) and the Cox regression with Akaike's information criterion (AIC) were used to evaluate the improvement of the MNA-T1 and MNA-T2 in predicting the 4-years follow-up mortality risk. Results: The NRI were 0.004 (p = 0.726) and −0.010 (p = 0.454) if the MNA in the predictive model was replaced by the MNA-T1 and MNA-T2, respectively. The NRI was −0.012 (p = 0.052) if the MNA-T1 in the model was replaced by the MNA-T2. The model fitting index AIC were 8,987.3, 8,204.4, 8,218.1 and 8,214.2 for the Cox regression models with CV (control variables) only, CV + MNA, CV + MNA-T1 and CV + MNA-T2, respectively. It implied that the fitting of the model gets much better if any of the three MNA versions was included in the model. However, there were only small differences among the three versions. Conclusions: The result shows that the mortality-predictive ability of the MNA-T1 and the MNA-T2 did not significantly superior to the original MNA. Beacuse there is no “gold standard” for identifying subjects with malnutrition, we just take mortality as an external reference in this study. More studies may be required to confirm the validity of the modified versions.
author2 Wang, JiunYi
author_facet Wang, JiunYi
Chen,YaHui
陳雅惠
author Chen,YaHui
陳雅惠
spellingShingle Chen,YaHui
陳雅惠
Using A Reclassification Method To Evaluate The Improvement Of Mini Nutritional Assessment-Taiwan Version In Predicting The Mortality Of Older Taiwanese
author_sort Chen,YaHui
title Using A Reclassification Method To Evaluate The Improvement Of Mini Nutritional Assessment-Taiwan Version In Predicting The Mortality Of Older Taiwanese
title_short Using A Reclassification Method To Evaluate The Improvement Of Mini Nutritional Assessment-Taiwan Version In Predicting The Mortality Of Older Taiwanese
title_full Using A Reclassification Method To Evaluate The Improvement Of Mini Nutritional Assessment-Taiwan Version In Predicting The Mortality Of Older Taiwanese
title_fullStr Using A Reclassification Method To Evaluate The Improvement Of Mini Nutritional Assessment-Taiwan Version In Predicting The Mortality Of Older Taiwanese
title_full_unstemmed Using A Reclassification Method To Evaluate The Improvement Of Mini Nutritional Assessment-Taiwan Version In Predicting The Mortality Of Older Taiwanese
title_sort using a reclassification method to evaluate the improvement of mini nutritional assessment-taiwan version in predicting the mortality of older taiwanese
publishDate 2012
url http://ndltd.ncl.edu.tw/handle/01304741951976334876
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