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Assessing the risk of sarcopenia in the elderly: The Mini Sarcopenia Risk Assessment (MSRA) questionnaire

  • Published:
The journal of nutrition, health & aging

Abstract

Objectives

to validate the MSRA questionnaire proposed as prescreening tool for sarcopenia, in a population of community-dwelling elderly subjects.

Design

observational study.

Setting

community dwelling elderly subjects.

Participants

274 community dwelling elderly subjects, 177 women and 97 men, aged 66-78 years.

Measurements

Based on EWGSOP diagnostic criteria subjects were classified as sarcopenic and nonsarcopenic. The Mini Sarcopenia Risk Assessment (MSRA) questionnaire, is composed of seven questions and investigates anamnestic and nutritional characteristics related to risk of sarcopenia onset (age, protein and dairy products consumption, number of meals per day, physical activity level, number of hospitalizations and weight loss in the last year).

Results

33.5% of the study population, were classified as sarcopenic. With the 7-item MSRA score, subjects with a score of 30 or less, had a 4-fold greater risk of being sarcopenic than subjects with a score higher than 30 (OR:4.20;95% CI:2.26–8.06); area under the ROC curve was 0.786 (95% CI:0.725-0.847). In a logistic regression, considering as dependent variable the probability of being sarcopenic, and as independent variables the 7 items of the questionnaire, two items (number of meals and milk and dairy products consumption) showed non-significant diagnostic power. A 5-item score was then derived and the area under the ROC curve was 0.789 (95% IC:0.728-0.851). Taking into account the cost of false positive and false negative costs and the prevalence of sarcopenia, the “optimal” threshold of the original MSRA score (based on 7 items) is 30, with a sensitivity of 0.804 and a specificity of 0.505, while the “optimal” threshold of the MSRA score based on 5 items, is 45, with a sensitivity of 0.804 and a specificity of 0.604.

Conclusion

this preliminary study shows that the MSRA questionnaire is predictive of sarcopenia and can be suggested as prescreening instrument to detect this condition. The use of a short form of the MSRA questionnaire improves the capacity to identify sarcopenic subjects.

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References

  1. Crutz-Jentoft AJ, Baeyens JP, Bauer JM, Boire Y, Cederholm T, Landi F, Martin FC, Michel JP, Rolland Y, Schneider SM, Topinkovà E, Vandewoude M, Zamboni M. Sarcopenia: European consensus on definition and diagnosis. Report of the European Working Group on Sarcopenia in Older People. Age and Aging. 2010;39: 412–23.

    Google Scholar 

  2. Janssen I, Shepard DS, Katzmarzyc PT, Roubenoff R. The healthcare costs of sarcopenia in the United States. J Am Geriatrc Soc 2004;52: 80–85.

    Article  Google Scholar 

  3. Rolland Y, Czerwinski S, Abellan van Kan G, Morley JE, Cesari M, Onder G, Woo J, Baumgartner R, Pillard F, Boirie Y, Chumlea WMC, Vellas B. Sarcopenia: Its assessment, etiology, pathogenesis, consequences and future perspectives. J Nutr Health Aging. 2008 Aug-Sep; 12: 433–450.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Rossi AP, Fantin F, Micciolo R, Bertocchi M, Bertassello P, Zanandrea V, Zivelonghi A, Bissoli L, Zamboni M. Identifying sarcopenia in acute care setting patients. J Am Med Dir Assoc 2014; 15: 303.e7–12.

    Article  Google Scholar 

  5. Landi F, Liperoti R, Fusco D, Mastropaolo S, Quattrociocchi D, Proia A, Russo A, Bernabei R, Onder G. Prevalence and risk factors of sarcopenia among nursing home older residents. J Gerontol A Biol Sci Med Sci. 2012;67: 48–55.

    Article  PubMed  Google Scholar 

  6. Malmstrom TK, Morley JE. SARC-F: a simple questionnaire to rapidly diagnose sarcopenia. J Am Med Dir Assoc. 2013;14: 531–2.

    Article  PubMed  Google Scholar 

  7. Woo J, Leung J, Morley JE. Validating the SARC-F: a suitable community screening tool for sarcopenia? J Am Med Dir Assoc. 2014;15: 630–4.

    Article  PubMed  Google Scholar 

  8. Zamboni M, Turcato E, Santana H, Maggi S, Harris TB, Pietrobelli A, Heymsfield SB, Micciolo R, Bosello O. The relationship between body composition and physical performance in older women. J Am Geriatr Soc 1999;47: 1403–8.

    Article  CAS  PubMed  Google Scholar 

  9. Rossi AP, Fantin F, Caliari C, Zoico E, Mazzali G, Zanardo M, Bertassello P, Zanandrea V, Micciolo R, Zamboni M. Dynapenic abdominal obesity as predictor of mortality and disability worsening in older adults: A 10-year prospective study. Clin Nutr. 2016; 35: 199–204.

    Article  PubMed  Google Scholar 

  10. Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, Garry PJ, Lindeman RD. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998;147: 755–763.

    Article  CAS  PubMed  Google Scholar 

  11. Istituto Nazionale della Nutrizione. Tabelle di composizione degli alimenti. (National Institute of Nutrition: tables of nutritional composition). Litho Delta: Milano, 1989 (in Italian)

  12. Budui SL, Rossi AP, Zamboni M. The pathogenetic bases of sarcopenia. Clin Cases Miner Bone Metab. 2015;12: 22–6.

    PubMed  PubMed Central  Google Scholar 

  13. Kortebein P, Ferrando A, Lombeida J, Wolfe R, Evans WJ. Effect of 10 days of bed rest on skeletal muscle in healthy older adults. JAMA 2007;297: 1769–1774.

    Article  Google Scholar 

  14. Evans WJ. Skeletal muscle loss: cachexia, sarcopenia, and inactivity. Am J Clin Nutr 2010, 91(suppl): 1123–75.

    Article  Google Scholar 

  15. Renoud A, Ecochard R, Marchand F, Chapulart R, Szulc P. Predictive parameters of accelerated muscle loss in men-MINOS Study. The American Journal of Medicine 2014;127: 554–61.

    Article  PubMed  Google Scholar 

  16. Alley D, Koster A, Mackey D, Cawthon P, Ferrucci L, Simonsick EM, Yu B, Hardy S, Goodpaster B, Sarkisian C, Houston DK, Kritchevsky SB, Cummings S, Lee JS, Tylavsky FA, Newman A, Harris T. Hospitalization and change in body composition and strength in a population-based cohort of older persons. J Am Geriatr Soc. 2010;58: 2085–91.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Abellan van Kan. G. Epidemiology and consequences of sarcopenia. J Nutr Health Aging 2009;13: 708–712.

    Article  CAS  PubMed  Google Scholar 

  18. Houston DK, Nicklas BJ, Ding J, Harris TB, Tylavsky FA, Newman AB, Sun Lee J, Sahyoun NR, Visser M, Kritchevsky SB. Dietary protein intake is associated with lean mass change in older, community-dwelling adults: The Health Aging and Body Composition Study. Am J Clin Nutr 2008;87: 150–5.

    CAS  PubMed  Google Scholar 

  19. Filion ME, Barbat-Artigas S, Dupontgand S, Fex A, Karelis AD, Aubertin-Leheudre M. Relationship between protein intake and dynapenia in postmenopausal women. J Nutr Health Aging 2012;16: 616–619.

    Article  CAS  PubMed  Google Scholar 

  20. Molino S, Dossena M, Buonocore D, Verri M. Sarcopenic Obesity: An Appraisal of the Current Status of Knowledge and Management in Elderly People. J Nutr Health Aging. 2016;20: 780–8.

    Article  CAS  PubMed  Google Scholar 

  21. Fawcett T. An introduction to ROC analysis. Pattern Recogn Lett. 2006, 27:861–874.

    Article  Google Scholar 

  22. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44: 837–845.

    Article  CAS  PubMed  Google Scholar 

  23. Zhou X.H, Obuchowski N.A., McClish D.K. (2011) Statistical Methods in Diagnostic Medicine. 2nd edition. John Wiley & Sons, New York.

    Book  Google Scholar 

  24. Zweig MH, Campbell G. Receiver-Operating Characteristic (ROC) Plots: A Fundamental Evaluation Tool in Clinical Medicine. Clin Chem 1993;39: 561–577.

    CAS  PubMed  Google Scholar 

  25. Mijnarends DM, Schols JMGA, Halfens RJG, Meijers JMM, Luiking, YC, Verlaane S, Evers SMAA. Burden-of-illness of Dutch community-dwelling older adults with sarcopenia: Health related outcomes and costs. Eur J Geriatr 2016;7: 276–284.

    Article  Google Scholar 

  26. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing 2014, Vienna, Austria.

  27. Robin, N. Turck, A. Hainard, N. Tiberti, F. Lisacek, J.C. Sanchez, M. Müller, pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 2011; 12:77.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Malmstrom TK, Miller DK, Simonsick EM, Ferrucci L, Morley JE. SARC-F: a symptom score to predict persons with sarcopenia at risk for poor functional outcomes. J Cachexia Muscle Wasting 2016;7: 28–36.

    Article  Google Scholar 

  29. Barbosa-Silva TG, Menezes AM Bielemann RM, Malmstrom TK, Gonzalez MC. Enhancing the SARC-F: improving sarcopenia screening in the clinical practice. J Am Med Dir Assoc 2016; S1525-8610, 30314–0.

    Google Scholar 

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Authors and Affiliations

  1. Department of Medicine, Division of Geriatrics, University of Verona, Ospedale Maggiore, Piazzale Stefani 1, 37126, Verona, Italy

    Andrea P. Rossi, S. Rubele, F. Fantin, C. Caliari, E. Zoico, G. Mazzali, E. Ferrari & M. Zamboni

  2. Department of Psycholgy and Cognitive Sciences, University of Trento, Trento, Italy

    R. Micciolo

  3. Department of Medicinal Sciences, University of Ferrara, Ferrara, Italy

    S. Volpato

Authors
  1. Andrea P. Rossi
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  2. R. Micciolo
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  3. S. Rubele
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  4. F. Fantin
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  5. C. Caliari
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  6. E. Zoico
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  7. G. Mazzali
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  8. E. Ferrari
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  9. S. Volpato
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  10. M. Zamboni
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Correspondence to Andrea P. Rossi.

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Rossi, A.P., Micciolo, R., Rubele, S. et al. Assessing the risk of sarcopenia in the elderly: The Mini Sarcopenia Risk Assessment (MSRA) questionnaire. J Nutr Health Aging 21, 743–749 (2017). https://doi.org/10.1007/s12603-017-0921-4

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  • DOI: https://doi.org/10.1007/s12603-017-0921-4

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