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What Are the Risk Factors for Malnutrition in Older-Aged Institutionalized Adults?
Malnutrition is common in older adults and is associated with functional impairment, reduced quality of life, and increased morbidity and mortality. The aim of this study was to explore the association between health (including depression), physical functioning, disability and cognitive decline, and...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7551464/ https://www.ncbi.nlm.nih.gov/pubmed/32961917 http://dx.doi.org/10.3390/nu12092857 |
Sumario: | Malnutrition is common in older adults and is associated with functional impairment, reduced quality of life, and increased morbidity and mortality. The aim of this study was to explore the association between health (including depression), physical functioning, disability and cognitive decline, and risk of malnutrition. Participants were recruited from nursing homes in Italy and completed a detailed multidimensional geriatric evaluation. All the data analyses were completed using Stata Version 15.1. The study included 246 participants with an age range of 50 to 102 (80.4 ± 10.5). The sample was characterised by a high degree of cognitive and functional impairment, disability, and poor health and nutritional status (according to Mini Nutritional Assessment (MNA), 38.2% were at risk for malnutrition and 19.5% were malnourished). Using a stepwise linear regression model, age (B = −0.043, SE = 0.016, p = 0.010), depression (B = −0.133, SE = 0.052, p = 0.011), disability (B = 0.517, SE = 0.068, p < 0.001), and physical performance (B = −0.191, SE = 0.095, p = 0.045) remained significantly associated with the malnutrition risk in the final model (adjusted R-squared = 0.298). The logistic regression model incorporating age, depression, disability, and physical performance was found to have high discriminative accuracy (AUC = 0.747; 95%CI: 0.686 to 0.808) for predicting the risk of malnutrition. The results of the study confirm the need to assess nutritional status and to investigate the presence of risk factors associated with malnutrition in order to achieve effective prevention and plan a better intervention strategy. |
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