Cognition and Social–Physiological Factors Associated With Malnutrition in Hospitalized Older Adults in Taiwan. Issue 1 (March 2015)

• Record Type: Journal Article
• Authors: Peng, Li-Ning; Cheng, Yu; Chen, Liang-Kung; Tung, Heng-Hsin; Chu, Kuei-Hui; Liang, Shu-Yuan
• Is Part Of: Journal of nursing research. Volume 23:Issue 1(2015)
• Publication Date: 2015-03
• Subjects: malnutrition -- cognitive function -- geriatric -- Taiwan; Nursing -- Periodicals; Nursing -- Research -- Periodicals; 610.7
• DOI: 10.1097/jnr.0000000000000074
• Languages: English
• ISSNs: 1682-3141

Abstract

ABSTRACT: Background: Malnutrition is prevalent among hospitalized geriatric patients. Purpose: The aim of this study was to explore the impact of cognitive status and its associated factors on the nutritional status of hospitalized geriatric patients. Methods: A descriptive and cross-sectional study design was conducted. Two instruments, the Mini Nutritional Assessment and the Mini-Mental State Examination (MMSE), were administered to 401 geriatric participants. Linear regression was used to examine the contribution of cognitive status and its associated factors to the nutritional status of participants. Results: Participants had a mean age of 85 years, and three quarters (73.6%) were men. Participants earned a mean MMSE score of 19.1 ± 8.0 and a mean Mini Nutritional Assessment score of 20.2 ± 5.2. Two thirds (67.1%) were at risk for malnutrition, and 22.7% experienced malnutrition. One third (33.1%) had mild-to-moderate cognitive impairment, and 32.2% had severe cognitive impairment. The MMSE scores accounted for 21% of the total variability in nutritional status. In addition, the Charlson Comorbidity Index score and care status were also significant predictors of malnutrition and, together with the MMSE scores, accounted for 53% of the variability in the nutritional status of participants in the regression model. Conclusions: Findings indicate that cognitive status, concomitant comorbidities, and care status are significant predictors of malnutrition. The results of this study provide information to help clinicians identify at-risk populations for malnutrition and develop appropriate nutrition programs based on individual needs.