Literature DB >> 29222883

The Geriatric Nutritional Risk Index predicts mortality in nonagenarians and centenarians receiving home care.

Hui Wang1,2, Shan Hai1, Yan Zhou1, Ping Liu1, Bi-Rong Dong3.   

Abstract

BACKGROUND AND OBJECTIVES: The increasing prevalence of malnutrition in old people is related to the risk of illness and death. A number of screening tools to detect malnutrition have been used in the elderly to assess nutritional status and predict prognosis. The aim of the present study was to investigate the ability of the Geriatric Nutritional Risk Index (GNRI) to assess nutritional status and predict mortality in very old home-care people by using a cross-sectional study of Chinese older people aged 90-105 years. METHODS AND STUDY
DESIGN: The present study was based on a 4-year follow-up of mortality data from a previous cross-sectional study. The study was conducted with a very elderly population with a mean age of 93.5±3.2 years (n=716; 230 men and 486 women). In 2005, trained researchers performed face-to-face interviews and physical and geriatric assessments to obtain information on sociodemographic factors, self-reported medical diseases, geriatric-specific conditions, anthropometric factors, biochemical data, and the GNRI score. In 2009, vital status were requested from the local government.
RESULTS: After 4 years of follow-up, 371 participants died (125 men and 246 women, 51.8%). The median follow-up time was significantly worse in the nutritional risk group (GNRI <=98) (30.26±15.80 vs 42.27±11.82 months, p<0.001). Activities of daily living (ADL) impairment (hazard ratio [HR]=1.414, 95% CI=1.121-1.783), and GNRI score (HR=0.92, 95% CI=0.908-0.932) were associated with all-cause mortality according to a Cox regression analysis.
CONCLUSIONS: The GNRI, a nutrition-related risk index, can predict mortality in very old Chinese home-care people.

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Year:  2018        PMID: 29222883     DOI: 10.6133/apjcn.022017.10

Source DB:  PubMed          Journal:  Asia Pac J Clin Nutr        ISSN: 0964-7058            Impact factor:   1.662


  9 in total

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