title: Measurement of perceived health problems as a means of detecting elderly people at risk of malnutrition.
abstract: BACKGROUND
  As nutritional preventative measures are more effective in elderly people assessed as non protein-energy malnourished (non-PEM) than such interventions are in those who are malnourished, early detection of those at risk of malnutrition is important.
  
  
  OBJECTIVE
  This study tests the hypothesis that health problems measured by the Nottingham Health Profile (NHP) can predict residents at risk of malnutrition.
  
  
  METHODS
  Nutritional status was assessed in 261 residents newly admitted to municipal care using a combination of anthropometry and serum protein measurements. From this sample, 20 non-PEM residents, simultaneously assessed as moderately malnourished according to a subjective method, were consecutively included. Using a paired matched design, 20 other non-PEM residents, who were simultaneously subjectively assessed as well nourished, completed the pairs.
  
  
  RESULTS
  Univariate logistic regression analyses showed that the dimensions of emotional reactions, energy, pain, physical mobility and sleep had significant power to predict residents at risk of malnutrition. In the multiple logistic regression analysis, energy had the highest explanatory power.
  
  
  CONCLUSIONS
  Non-PEM residents, assessed as moderately malnourished according to the Subjective Global Assessment, perceived significantly greater health problems than non-PEM residents subjectively assessed as well nourished. Measurement of health problems adds important information to that used in early detection of residents at risk of malnutrition.
authors.affiliation: Department of Medicine and Care, Division of Nursing Science, Faculty of Health Sciences, Linköping University, SE-581 85 Linköping, Sweden. lennart.christensson@educ.ltjkpg.se
authors.forename: L
authors.initials: L
authors.lastname: Christensson
authors.forename: M
authors.initials: M
authors.lastname: Unossons
authors.forename: A-C
authors.initials: AC
authors.lastname: Ek
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D015577:Geriatric Assessment; D006304:Health Status; D006801:Humans; D016015:Logistic Models; D008297:Male; D044342:Malnutrition / Q000175:diagnosis*; D015596:Nutrition Assessment; D009752:Nutritional Status / Q000502:physiology; D012112:Residential Facilities; D018570:Risk Assessment; D013548:Sweden