Identifying Malnutrition Risk in the Elderly: A Single- and Multi-Parameter Approach
Karolina Kujawowicz1, Iwona Mirończuk-Chodakowska1, Monika Cyuńczyk1
1Department of Food Biotechnology, Medical University of Białystok, 15-089 Białystok, Poland.
Nutrients
|August 10, 2024
Summary
Assessing malnutrition in older adults requires more than single measures. A multi-parameter model combining factors like muscle mass and depression offers superior accuracy for identifying malnutrition risk.
Area of Science:
- Geriatric Medicine
- Nutritional Science
- Biostatistics
Background:
- Malnutrition is a prevalent issue in the elderly population, often requiring intricate assessment methods.
- Current single-parameter tools may not fully capture the complexity of malnutrition risk in older adults.
Purpose of the Study:
- To compare the effectiveness of single-parameter versus multi-parameter approaches in assessing malnutrition risk among the elderly.
- To identify key factors contributing to accurate malnutrition risk assessment in geriatric populations.
Main Methods:
- A cross-sectional study involving 154 elderly individuals undergoing a comprehensive geriatric assessment (CGA).
- Malnutrition risk assessed using the Mini Nutritional Assessment (MNA), with additional data on sarcopenia, polypharmacy, depression (Geriatric Depression Scale - GDS), appetite, handgrip strength, gait speed, and body composition via bioelectrical impedance analysis (BIA), including phase angle (PA).
- Logistic regression analysis was employed to develop a predictive model for malnutrition risk.
Main Results:
- The MNA identified malnutrition risk in 36.8% of participants.
- The GDS (AUC=0.69) and PA (AUC=0.62) showed moderate predictive ability for malnutrition risk.
- A multi-parameter logistic regression model incorporating handgrip strength, skeletal muscle mass, sarcopenia, osteoporosis, depression, antidepressant use, mobility, appetite, and smoking achieved a significantly higher AUC of 0.84 (95% CI: 0.77-0.91).
Conclusions:
- Single-parameter assessments like MNA, GDS, and PA have limitations in fully capturing malnutrition risk in the elderly.
- A composite model integrating multiple clinical, functional, and body composition parameters provides a more accurate and comprehensive assessment of malnutrition risk in older adults.
- This integrated approach can aid in earlier and more effective interventions for malnutrition in the geriatric population.
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