title: Clinical study of mini-nutritional assessment for older Chinese inpatients.
abstract: BACKGROUND
  Malnutrition is a common problem in older patients. Early detection of malnutrition is an important task in clinical practice. The MNA has become an extensively used tool to evaluate nutritional status in European countries and the United States.
  
  
  OBJECTIVE
  We evaluated the Mini-Nutritional Assessment (MNA) test and the short-form MNA (MNA-SF) test as screening tools for malnutrition in older Chinese inpatients and focused on finding an optimal cutoff point for MNA total score and MNA-SF score.
  
  
  METHODS
  One hundred eighty-four older Chinese inpatients were enrolled in this study from July to August 2006. Nutritional assessment included MNA, anthropometric measurements, and biochemical markers.
  
  
  RESULTS
  According to the original cutoff point of the full MNA, 19.6% of those assessed were malnourished, 53.2% were at risk of malnutrition and 27.2% were well nourished. Correlations were found between MNA, MNA-SF and body mass index, triceps skinfold thickness, serum albumin, lymphocyte count, hemoglobin, lymphocyte ratio. With the most proper cutoff point lower than 19 indicating malnutrition, when using serum albumin (< 35.0 g/L) as the indicator, the sensitivity and specificity of the MNA total score were 0.6286 and 0.7466; when using BMI (< 18.5 kg/m2) as the indicator, the sensitivity and specificity were 0.8636 and 0.7469. The incidence rate of malnutrition was 32.6%. The most proper cutoff point of MNA-SF was lower than 12.
  
  
  CONCLUSIONS
  The MNA and MNA-SF were useful tools to identify older Chinese inpatients with malnutrition. However, the cutoff point of the MNA should be modulated for this population.
authors.affiliation: Tianjin Lung Cancer Center, Department of Thoracic Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, PR China.
authors.forename: Z
authors.initials: Z
authors.lastname: Lei
authors.forename: D
authors.initials: D
authors.lastname: Qingyi
authors.forename: G
authors.initials: G
authors.lastname: Feng
authors.forename: W
authors.initials: W
authors.lastname: Chen
authors.forename: R Shoshana
authors.initials: RS
authors.lastname: Hock
authors.forename: W
authors.initials: W
authors.lastname: Changli
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000886:Anthropometry; D015415:Biomarkers / Q000097:blood; D015992:Body Mass Index; D002681:China / Q000453:epidemiology; D002784:Cholesterol / Q000097:blood; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008297:Male; D044342:Malnutrition / Q000175:diagnosis* / Q000453:epidemiology; D008403:Mass Screening / Q000379:methods / Q000592:standards; D008875:Middle Aged; D015596:Nutrition Assessment; D009752:Nutritional Status; D011237:Predictive Value of Tests; D012372:ROC Curve; D012015:Reference Standards; D018570:Risk Assessment; D012709:Serum Albumin / Q000032:analysis
chemical_list: D015415:Biomarkers; D012709:Serum Albumin; D002784:Cholesterol