The journal of nutrition, health & aging

, Volume 15, Issue 3, pp 181–186

Anthropometric parameters of nutritional assessment as predictive factors of the MINI nutritional assessment (MNA) of hospitalized elderly patients

Authors

    • School of Nutrition
    • Institution: School of Nutrition and Medicine
    • Bairro: Jardim Madalena, Residencial Vila Verde
  • J. L. Braga De Aquino
    • School of Medicine
    • Institution: School of Nutrition and Medicine
JNHA: Nutrition

DOI: 10.1007/s12603-010-0116-8

Cite this article as:
Leandro-Merhi, V.A. & Braga De Aquino, J.L. J Nutr Health Aging (2011) 15: 181. doi:10.1007/s12603-010-0116-8

Abstract

Objective

The objective of this study was to identify nutritional indicators that predict MNA (mini nutritional assessment) classification in hospitalized elderly patients.

Method

This cross-sectional study assessed the nutritional status of 109 elderly patients at the beginning of their hospital stay with anthropometric and laboratory indicators and the MNA. Habitual energy intake (HEI) was also determined. The assessed nutritional indicators were investigated by univariate and multivariate logistic regression analysis to verify if they can predict MNA classification. The odds ratio (OR) and its respective confidence interval (CI) of 95% were also calculated, and the significance level was set at 5% (p<0.05).

Results

The nutritional status of most patients (61.47%) was appropriate but 30.28% were at risk of malnourishment and 8.26% were malnourished. Statistical differences were found for those aged more than 70 years and for arm circumference, body mass index, calf circumference, triceps skinfold thickness and mid-arm muscle circumference. Initially, the predictive factors identified by univariate logistic regression were body mass index (BMI) (p=0.0001; OR=0.825), calf circumference (CC) (p=0.0026; OR=0.832), arm circumference (AC) (p<0.0001; OR=0.787), triceps skinfold thickness (TST) (p=0.0014; OR=0.920) and mid-arm muscle circumference (MAMC) (p=0.0003; OR=0.975); later, multiple logistic regression analyses revealed that first AC (p=0.0025; OR=0.731 (0.597–0.895)), then BMI (p=<0.0001; OR=10.909 (3.298–36.085)) and finally TST (p=0.0040; OR=0.924 (0.876–0.975)) and MAMC (p=0.0010; OR=0.976 (0.962–0.990)) were factors that predict MNA classification.

Conclusion

In the conditions of this study, first AC, then BMI and finally TST and MAMC together were capable of predicting MNA classification.

Key words

Elderlymini nutritional assessmentnutritional indicatorspredictive factors

Copyright information

© Serdi and Springer Verlag France 2011