1. The prevalence of protein and protein-energy malnutrition in a population of geriatric rehabilitation patients at SCO Health Service Amy Nichols, Dietetic Intern Julie Campagna, RD, Research Advisor SCO Health Service July 17th, 2008

2. Outline  Introduction  Objectives  Methodology  Results  Discussion  Conclusion

3. Introduction SCO Health Service  4 facilities in Ottawa  Élisabeth-Bruyère Health Centre Location of Geriatric Rehabilitation Program GRP: 98 beds  largest inpatient rehab site http://www.scohs.on.ca

4. Introduction Malnutrition  Inadequate nutrition  Determinants of malnutrition Body weight, body fat and protein stores, lab values  Definitions vary within literature

5. Introduction Malnutrition  Protein malnutrition: Alb <35 g/L ; BMI ≥24.0  Protein-energy malnutrition (PEM): Alb <35 g/L ; BMI <24.0 Salva et al (2004), Manual of Clinical Dietetics, Mahan et al (2004)

6. Introduction Malnutrition  Prevalence: 35 – 85% (4) Geriatric unit: 35% – 61% with 93% at risk (5,6) Hospitalized: 23% (7) Rehabilitation: 56.1% (8)

7. Introduction  Treatment: Nutritional supplementation  muscle strength,  bone loss (10)  LOS (10) Weight loss prevention (11) Malnutrition  Complications:  admission rates (9)  rates of morbidities (8)  death rates (5)

8. Objectives  To assess the overall nutritional status of the group of patients admitted to the SCO Health Service GRP during 2006  To calculate the prevalence of protein and protein-energy malnutrition within this group

9. Methodology Subjects  357 eligible GRP patients  Admitted January 1 st – December 31 st, 2006  Inclusion criteria: >65 years of age Stable medical condition Serum albumin concentration, height and weight recorded within 7 days of admission

10. Methodology Methods  Design: Retrospective chart review  Collection of pertinent information from charts: Age Gender Reason for admission to GRP Length of stay (LOS) Relevant current diagnoses

11. Methodology Methods  Kidney, liver, inflammatory disease identified as having negative impact on serum albumin concentration (5,8,12,13) Total group “Non-Acutely Ill” subgroup those who did not present with these conditions “Acutely Ill” subgroup those who presented with kidney, liver, inflammatory disease

12. Methodology Methods  Classification of protein or protein-energy malnourished patients using Alb and BMI  Calculation of prevalence in total group, “Acutely Ill” and “Non-Acutely Ill” subgroups Prevalence = # of malnourished patients x 100 total # of patients

13. Methodology Statistics  SPSS version 16.0  Frequency: Crosstabulations  Effect of illness: Chi Square Test of Independence (X 2 ) (p<0.05)  Significance: binomial test (p<0.05)

14. Results Participant characteristics  306 eligible patients  Most common reasons for admission: 50.7% following fracture(s) (n=155) 20.6% following surgery (n=63) 16.7% for deconditionning (n=51)

15. Results Participant characteristics AverageTotal Group (n=306) Acutely Ill (n=94) Non-Acutely Ill (n=212) Age (years)82.381.382.7 Sex (M:F)89:21727:6762:150 Length of Stay (d)42.742.442.8 Height (cm)162.6163.0162.4 Weight (kg)65.667.964.5 BMI (kg/m 2 )24.725.524.4 Albumin (g/L)34.934.635.1

16. Results Prevalence Total GroupAcutely IllNon-Acutely Ill Total Number30694212 Pro Malnourished Prevalence 74 24.2% 29 30.9% 45 21.2% Pro-E Malnourished Prevalence 76 24.8% 22 23.4% 54 25.8% Either Prevalence 150 49.0%* 51 54.3%** 99 46.7%*** *p=0.755; **p=0.470; ***p=0.372

17. Discussion Results  Objectives accomplished  Prevalence: 49% vs 56.1% (8) Difference likely due to varying definitions of malnutrition and data used to determine status  Effect of Illness: 30.9% vs 21.2% Consistent with expected results, though not significant

18. Discussion Limitations  Human error  Retrospective design Individual variability; limited to data already in charts  Albumin as marker of nutritional status Overlap (12), morbidities (14,15), inflammation (16), negative acute phase reactant (3)  BMI as marker of nutritional status Possible to be malnourished and have normal BMI

19. Discussion Recommendations  Prospective study  Alternative methods of identifying and confirming malnutrition Ex: Mini-Nutritional Assessment (MNA)  misdiagnosis, better identification of at risk

20. Conclusion  Malnutrition   in disease/mortality rates  Treatment: dietary therapies specific to individual populations  Objective of study to assess nutritional status of patients at Élisabeth-Bruyère Health Centre’s GRP  Despite limitations and lack of statistically significant results, substantial portion of patients found to be malnourished

21. Conclusion Implications  Need for dietary intervention identified  Justification for implementation of supplementation or food enrichment trial  Benefits able to be quantified and evaluated  Improvement of health outcome for future patients

22. Acknowledgements  Special thanks to the following people for their contribution to the development and evolution of this research project: Julie Campagna – Research Advisor Marisa Leblanc – Research Mentor Carole Ryall and Yvon Rollin – SCO Health Service Louise Gariepy – Statistician Danielle – Peer Reviewer Barbara Khouzam – Research Coordinator

23. References 1. Salva A, Corman B, Andrieu S et al. Minimum data set for nutritional intervention studies in elderly people. J Gerontol 2004:59:724-729. 2. American Dietetic Association and Dietitians of Canada. Manual of clinical dietetics 6 th edition. Nutrition assessment of adults. Illinois: Library of Congress, 2000. 3. Mahan LK, Escott-Strump S. Krause’s food, nutrition & diet therapy 11 th edition. Philadelphia: Elsevier, 2004:440. 4. Novartis Nutrition Corporation. Resource manual for long term care. Mississauga, 2006. 5. Sullivan DH, Walls RC, Bopp MM. Protein-energy undernutrition and the risk of mortality within one year of hospital discharge: a follow-up study. J Am Geriatr Soc 1995:43:507-512. 6. Rypkema G, Adang E, Dicke H et al. Cost-effectiveness of an interdisciplinary intervention in geriatric inpatients to prevent malnutrition. J Nutr Health Aging 2003:8:122-7.

24. References 7. Guigoz Y. The Mini Nutritional Assessment (MNA®) review of the literature – what does it tell us? J Nutr Health Aging 2006:10:466-487. 8. Donini LM, De Bernardini L, De Felice MR et al. Effect of nutritional status on clinical outcome in a population of geriatric rehabilitation patients. Aging Clin Exp Res 2004:16:132-138. 9. Sullivan DH. Risk factors for early hospital readmission in a select population of geriatric rehabilitation patients: the significance of nutritional status. J Am Geriatr Soc 1992:40:792-798. 10. Schürch M-A, Rizzoli R, Slosman D et al. Protein supplements increase serum insulin-like growth factor-I levels and attenuate proximal femur bone loss in patients with recent hip fracture. A randomized double-blind, placebo-controlled trial. Ann Intern Med 1998:128:801-809. 11. Gazzotti C, Arnaud-Battandier F, Parello M et al. Prevention of malnutrition in older people during and after hospitalization: results from a randomised controlled clinical trial. Age Aging 2003:32:321-325.

25. References 12. Covinsky KE, Covinsky MH, Palmer RM et al. Serum albumin concentration and clinical assessments of nutritional status in hospitalized older people: different sides of different coins? J Am Geriatr Soc 2002:50:631-637. 13. Sergi G, Coin A, Volpato S et al. Role of visceral proteins in detecting malnutrition in the elderly. Eur J Clin Nutr 2006:60:203-209. 14. Sullivan DH, Patch GA, Walls RC et al. Impact of nutritional status on morbidity and mortality in a select population of geriatric patients. Am J Clin Nutr 1990:51:749-758. 15. Sullivan DH, Walls RC. Impact of nutritional status on morbidity in a population of geriatric rehabilitation patients. J Am Geriatr Soc 1994:42:471-477. 16. Sullivan DH, Roberson PK, Johnson LE et al. Association between inflammation-associated cytokines, serum albumins, and mortality in the elderly. J Am Med Dir Assoc 2007:8:458-463.

26. Questions? Thank you!