Y-H Hsu1, M-Y Chou, C-S Chu, M-C Liao, Y-C Wang, Y-T Lin, L-K Chen, C-K Liang. 1. Chih-Kuang Liang, Address: Center for Geriatrics and Gerontology, Kaohsiung Veterans General Hospital, No. 386, Dazhong 1st Rd., Zuoying Dist., Kaohsiung City 81362, Taiwan (R.O.C.), Phone: 886-7-3422526, E-mail: ck.vghks@gmail.com.
Abstract
OBJECTIVES: To determine whether nutritional status can predict 3-year cognitive and functional decline, as well as 4-year all-cause mortality in older adults. DESIGN: Prospectively longitudinal cohort study. SETTING AND PARTICIPANTS: The study recruited 354 men aged 65 years and older in the veteran's retirement community. MEASURES: Baseline nutritional status was evaluated using the Mini-Nutritional Assessment-Short Form (MNA-SF). Cognitive function and Activities of Daily Living (ADL) function were determined by the Mini-Mental State Examination (MMSE) and the Barthel Index, respectively. Three-year cognitive and functional decline were respectively defined as a >3 point decrease in the MMSE scores and lower ADL scores than at baseline. Univariate and multivariable logistic regression analyses were conducted to identify nutritional status as a risk factor in poor outcome. The Kaplan-Meier method and Cox proportional regression models were used to estimate the effect of malnutrition risk on the mortality. RESULTS: According to MNS-SF, the prevalence of risk of malnutrition was 53.1% (188/354). Multivariate logistic regression found risk of malnutrition significantly associated with 3-year cognitive decline (Adjusted odds ratio [OR] 2.07, 95% Confidence Interval [CI] 1.05-4.08, P =0.036) and functional decline (Adjusted OR 1.83, 95% CI 1.01-3.34, P =0.047) compared with normal nutritional status. The hazard ratio (HR) for all-cause mortality was 1.8 times higher in residents at risk of malnutrition (Adjusted HR 1.82, 95% CI 1.19-2.79, P =0.006). CONCLUSIONS: Our results provide strong evidence that risk of malnutrition can predict not only cognitive and functional decline but also risk of all-cause mortality in older men living in a veteran retirement's community. Further longitudinal studies are needed to explore the causal relationship among nutrition, clinical outcomes, and the effect of an intervention for malnutrition.
OBJECTIVES: To determine whether nutritional status can predict 3-year cognitive and functional decline, as well as 4-year all-cause mortality in older adults. DESIGN: Prospectively longitudinal cohort study. SETTING AND PARTICIPANTS: The study recruited 354 men aged 65 years and older in the veteran's retirement community. MEASURES: Baseline nutritional status was evaluated using the Mini-Nutritional Assessment-Short Form (MNA-SF). Cognitive function and Activities of Daily Living (ADL) function were determined by the Mini-Mental State Examination (MMSE) and the Barthel Index, respectively. Three-year cognitive and functional decline were respectively defined as a >3 point decrease in the MMSE scores and lower ADL scores than at baseline. Univariate and multivariable logistic regression analyses were conducted to identify nutritional status as a risk factor in poor outcome. The Kaplan-Meier method and Cox proportional regression models were used to estimate the effect of malnutrition risk on the mortality. RESULTS: According to MNS-SF, the prevalence of risk of malnutrition was 53.1% (188/354). Multivariate logistic regression found risk of malnutrition significantly associated with 3-year cognitive decline (Adjusted odds ratio [OR] 2.07, 95% Confidence Interval [CI] 1.05-4.08, P =0.036) and functional decline (Adjusted OR 1.83, 95% CI 1.01-3.34, P =0.047) compared with normal nutritional status. The hazard ratio (HR) for all-cause mortality was 1.8 times higher in residents at risk of malnutrition (Adjusted HR 1.82, 95% CI 1.19-2.79, P =0.006). CONCLUSIONS: Our results provide strong evidence that risk of malnutrition can predict not only cognitive and functional decline but also risk of all-cause mortality in older men living in a veteran retirement's community. Further longitudinal studies are needed to explore the causal relationship among nutrition, clinical outcomes, and the effect of an intervention for malnutrition.
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Authors: Tiia Ngandu; Jenni Lehtisalo; Alina Solomon; Esko Levälahti; Satu Ahtiluoto; Riitta Antikainen; Lars Bäckman; Tuomo Hänninen; Antti Jula; Tiina Laatikainen; Jaana Lindström; Francesca Mangialasche; Teemu Paajanen; Satu Pajala; Markku Peltonen; Rainer Rauramaa; Anna Stigsdotter-Neely; Timo Strandberg; Jaakko Tuomilehto; Hilkka Soininen; Miia Kivipelto Journal: Lancet Date: 2015-03-12 Impact factor: 79.321