title: Evaluation of nutritional assessment techniques in elderly people newly admitted to municipal care.
abstract: OBJECTIVE
  To evaluate the Subjective Global Assessment (SGA) and the Mini Nutritional Assessment (MNA) with regard to validity using a combination of anthropometric and serum-protein measurements as standard criteria to assess protein-energy malnutrition (PEM).
  
  
  METHODS
  Cross-sectional study with consecutive selection of residents aged >or=65 y.
  
  
  METHODS
  A municipality in the south of Sweden.
  
  
  METHODS
  During a year, starting in October 1996, 148 females and 113 males, aged >or=65-104 y of age, newly admitted to special types of housing for the elderly, were included in the study.
  
  
  RESULTS
  According to SGA, 53% were assessed as malnourished or moderately malnourished on admission. The corresponding figure from MNA was 79% malnourished or at risk of malnutrition. Both tools indicated that anthropometric values and serum proteins were significantly lower in residents classified as being malnourished (P<0.05). Sensitivity in detecting PEM was in SGA 0.93 and in MNA 0.96 and specificity was 0.61 and 0.26, respectively. Using regression analysis, weight index and serum albumin were the best objective nutritional parameters in predicting the SGA- and MNA classifications. Item 'muscle wasting' in SGA and 'self-experienced health status' in MNA showed most predictive power concerning the odds of being assessed as malnourished.
  
  
  CONCLUSIONS
  SGA was shown to be the more useful tool in detecting residents with established malnutrition and MNA in detecting residents who need preventive nutritional measures.
authors.affiliation: Department of Medicine and Care, Division of Nursing Science, Faculty of Health Sciences, Linköping University, Linköping, Sweden. lennart.christensson@educ.ltjkpg.se
authors.forename: L
authors.initials: L
authors.lastname: Christensson
authors.forename: M
authors.initials: M
authors.lastname: Unosson
authors.forename: A-C
authors.initials: AC
authors.lastname: Ek
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D000886:Anthropometry; D003430:Cross-Sectional Studies; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008297:Male; D008875:Middle Aged; D015596:Nutrition Assessment; D009752:Nutritional Status / Q000502:physiology*; D011502:Protein-Energy Malnutrition / Q000503:physiopathology*; D012044:Regression Analysis; D012112:Residential Facilities; D013548:Sweden; D014505:Urban Population