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

  • Vânia Ap. Leandro-Merhi
  • J. L. Braga De Aquino
JNHA: Nutrition

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

Elderly mini nutritional assessment nutritional indicators predictive factors 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Guigoz Y, Vellas B, Garry PJ. Mini nutritional assessment: A practical assessment tool for grading the nutritional state of elderly patients. Facts and Research in Gerontology 1994; Supplement(2):15–59.Google Scholar
  2. 2.
    Bauer JM, Sieber CC. Significance and diagnosis of malnutrition in the elderly. Z Arztl Fortbild Qualitatssich 2007; 101(9):605–609.PubMedGoogle Scholar
  3. 3.
    Cuyac Lantigua M, Santana Porbén S. The Mini Nutritional Assessment of the elderly in the practice of a hospital geriatrics service: inception, validation and operational characteristics. Arch Latinoam Nutr 2007; 54(3):255–265.Google Scholar
  4. 4.
    Ferreira LS, Nascimento LF, Marucci MF. Use of the mini nutritional assessment tool in elderly people from long-term institutions of southeast of Brazil. J Nutr Health & Aging 2008; 12(3):213–217.CrossRefGoogle Scholar
  5. 5.
    González Hernández A, Cuyá Lantigua M, González Escudero H, Sánchez Gutiérrez R, Cortina Martínez R, Barreto Penié J, Santana Porbén S, Rojas Pérez A. Nutritional status of Cuban elders in three different geriatric scenarios: community, geriatrics service, nursery home. Arch Latinoam Nutr 2007; 57(3):266–272.PubMedGoogle Scholar
  6. 6.
    Tsai AC, Ho CS, Chang MC. Assessing the Prevalence of Malnutrition with the Mini Nutritional Assessment (MNA) in a Nationally Representative Sample of Elderly Taiwanese. J Nutr Health & Aging 2008; 12(4):239–243.CrossRefGoogle Scholar
  7. 7.
    Lei Z, Qingyi D, Feng G, Chen W, Shoshana Hock R, Changli W. Clinical study of mini-nutritional assessment for older chinese inpatients. J Nutr Health & Aging 2009; 13(10):871–875.CrossRefGoogle Scholar
  8. 8.
    Izawa S, Kuzuya M, Okada K, Enoki H, Koike T, Kanda S, Iguchi A. The nutritional status of frail elderly with care needs according to the mini-nutritional assessment. Clinical Nutrition 2006; 25(6):962–967.PubMedCrossRefGoogle Scholar
  9. 9.
    Jones JM: The methodology of nutritional screening and assessment tools. J Hum Nutr Diet 2002; 15(1):59–71.PubMedCrossRefGoogle Scholar
  10. 10.
    Martins CP, Correia JR, do Amaral TF: Undernutrition risk screening and length of stay of hospitalized elderly. J Nutr Elder 2005, 25(2):5–21.PubMedCrossRefGoogle Scholar
  11. 11.
    Rauen MS, Moreira EAM, Calvo MCM, Lobo AS. Avaliação do estado nutricional de idosos institucionalizados. Rev Nutr 2008; 21(3):303–310.CrossRefGoogle Scholar
  12. 12.
    Gaino NM, Leandro-Merhi VA, Oliveira MRM. Idosos hospitalizados: estado nutricional, dieta, doença e tempo de internação. Rev Bras Nutr Clin 2007; 22(4):273–279.Google Scholar
  13. 13.
    BRASIL: Lei no. 8.842, de 4 de janeiro de 1994. Dispõe sobre a política nacional do idoso, cria o Conselho Nacional do Idoso e dá outras providências. [http://www.planalto.gov.br/ccivil_03/leis/L8842.htm].
  14. 14.
    World Health Organization. Physical status: the use and interpretation of anthropometry. Geneva: World Health Organization; 1995. WHO technical report series 854.Google Scholar
  15. 15.
    Frisancho AR. New norms of upper limb fat and muscle areas for assessment of nutritional status. Am J Clin Nutr 1981; 34:2540–2545.PubMedGoogle Scholar
  16. 16.
    Burr ML, Phillips MK. Anthropometric norms in the elderly. Br J Nutr 1984; 51:165–169.PubMedCrossRefGoogle Scholar
  17. 17.
    Lipschitz DA. Screening for nutritional status in the elderly. Prim Care 1994; 22(1): 55–67.Google Scholar
  18. 18.
    Universidade Federal de São Paulo. Escola Paulista de Medicina. Programa de Apoio a Nutrição (NUTWIN) — programa de computador, versão 1.5. São Paulo: UNIFESP/EPM; 2002.Google Scholar
  19. 19.
    Harris J, Benedict F. A biometric study of basal metabolism in man. Washington D.C. Carnegie Institute of Washington. 1919.Google Scholar
  20. 20.
    Conover WJ. (1971). Practical Nonparametric Statistics. John Wiley & Sons Inc. Nova Iorque.Google Scholar
  21. 21.
    Tabachnick BG, Fidell LS. (2001). Using Multivariate Statistics. 4a ed. Allyn&Bacon. Needham Heights. MA. USA.Google Scholar
  22. 22.
    SAS System for Windows (Statistical Analysis System), versão 9.1.3 Service Pack 3. SAS Institute Inc, 2002–2003, Cary, NC, USA.Google Scholar
  23. 23.
    Cereda E, Valzolgher L, Pedrolli C: Mini nutritional assessment is a good predictor of functional status in institutionalised elderly at risk of malnutrition. Clin Nutr 2008; 27(5):700–705.PubMedCrossRefGoogle Scholar
  24. 24.
    Kondrup J, Allison SP, Elia M, Vellas B, Plauth M; Educational and Clinical Practice Committee, European Society of Parenteral and Enteral Nutrition (ESPEN). ESPEN guidelines for nutrition screening 2002. Clin Nutr 2003; 22(4):415–421.PubMedCrossRefGoogle Scholar
  25. 25.
    Bo M, Massaia M, Raspo S; Bosco F, Cena P; Molaschi M, Fabris F: Preventive factors of in-hospital mortality in older patients admitted to a medical intensive care unit. J Am Geriatr Soc 2003; 51:529–533.PubMedCrossRefGoogle Scholar
  26. 26.
    Guigoz Y: The Mini Nutritional Assessment (MNA) review of the literature-What does it tell us? J Nutr Health & Aging 2006; 10(6):466–485.Google Scholar
  27. 27.
    Kaiser MJ, Bauer JM, Ramsch C, Uter W, Guigoz Y, Cederholm T, Thomas DR, Anthony P, Charlton KE, Maggio M, Tsai AC, Grathwohl D, Vellas B, Sieber CC. Validation of the mini nutritional assessment short-form (MNA ®-SF): a practical tool for identification of nutritional status. J Nutr Health & Aging 2009; 13(9):782–788.CrossRefGoogle Scholar
  28. 28.
    Venzin RM, Kamber N, Keller WCF, Suter PM, Reinhart WH. How important is malnutrition? A prospective study in internal medicine. Eur J Clin Nutr 2009; 63(3):430–436.PubMedCrossRefGoogle Scholar
  29. 29.
    Beghetto MG, Luft VC, Mello ED, Polanczyk CA. Accuracy of nutritional assessment tools for predicting adverse hospital outcomes. Nutr Hosp 2009; 24(1):56–62.PubMedGoogle Scholar
  30. 30.
    Pereira Borges N, Alegria Silva BD, Cohen C, Portari Filho PE, Medeiros FJ. Comparison of the nutritional diagnosis, obtained through different methods and indicators, in patients with cancer. Nutr Hosp 2009; 24(1):51–55.PubMedGoogle Scholar
  31. 31.
    Correia IMTD, Waitzberg DL. The impact of malnutrition on morbidity, mortality, length of hospital stay and costs evaluated through a multivariate model analysis. Clin Nutr 2003; 22(3): 235–239.PubMedCrossRefGoogle Scholar
  32. 32.
    Cuervo M, Ansorena D, Garcia A, González Martínez MA, Astiasarán I, Martínez JA. Valoración de la circunferencia de la pantorrilla como indicador de riesgo de desnutrición en personas mayores. Nutr Hosp 2009; 24(1):63–67.PubMedGoogle Scholar
  33. 33.
    Mclellan KCP, Staudt C, Silva FRF, Bernardi JLD, Frenhani PB, Leandro-Merhi VA. The use of calf circumference measurement as an anthropometric tool to monitor nutritional status in elderly inpatients. J Nutr Health & Aging 2010; 14(4):266–270. DOI 10.1007/s 12603-010-0059-0.CrossRefGoogle Scholar

Copyright information

© Serdi and Springer Verlag France 2011

Authors and Affiliations

  • Vânia Ap. Leandro-Merhi
    • 2
    • 1
    • 4
  • J. L. Braga De Aquino
    • 3
    • 1
  1. 1.Institution: School of Nutrition and MedicinePuc-Campinas-SPBrazil
  2. 2.School of NutritionPuc-Campinas-SPBrazil
  3. 3.School of MedicinePuc-Campinas-SPBrazil
  4. 4.Bairro: Jardim Madalena, Residencial Vila VerdeCampinas-SPBrazil

Personalised recommendations