title: Factors associated with cognitive impairment among older Italian inpatients. Gruppo Italiano di Farmacovigilanza nell'Anziano (G.I.F.A.).
abstract: OBJECTIVE
  To examine the association of cognitive impairment with educational, demographic, and nutritional variables in older hospitalized people.
  
  
  METHODS
  Survey of older patients admitted consecutively to a hospital during two 2-month periods in 1993.
  
  
  METHODS
  Patients admitted for general medical care at 35 hospitals participating in the GIFA study throughout Italy.
  
  
  METHODS
  A total of 3628 patients aged 65 or older were studied.
  
  
  METHODS
  The Hodkinson Abbreviated Mental Test (HAMT) was used as a screening method to assess the patients' basic cognitive function. Multiple logistic regression was used to examine the association between cognitive impairment and demographic, educational or nutritional variables.
  
  
  RESULTS
  Twenty-nine percent of older inpatients were classified as having cognitive impairment, with similar distribution of HAMT score found in both genders. Educational attainment has a highly significant inverse relationship with cognitive impairment (highest education: OR 0.32; 95% CI 0.20-0.52). Moreover, cognitive impairment decreased with increasing body mass index (3rd tertile: OR 0.69; 95% CI: 0.51-0.93), cholesterol serum level (highest values: OR 0.59; 95% CI 0.37-0.93), circulating lymphocytes (highest values: OR 0.55; 95% CI 0.45-0.69), and serum albumin (highest values: OR 0.60; 95% CI 0.47-0.76), with a gradient of influence for each variable.
  
  
  CONCLUSIONS
  Educational attainment affects cognitive function in older inpatients. The strong association between cognitive impairment and nutritional variables suggests that every effort to improve nutritional status is needed in approaching cognitive impairment in older patients.
authors.affiliation: Istituto di Clinica Medica, Università di Trieste, Italy.
authors.forename: L
authors.initials: L
authors.lastname: Cattin
authors.forename: P
authors.initials: P
authors.lastname: Bordin
authors.forename: M
authors.initials: M
authors.lastname: Fonda
authors.forename: C
authors.initials: C
authors.lastname: Adamo
authors.forename: F
authors.initials: F
authors.lastname: Barbone
authors.forename: M
authors.initials: M
authors.lastname: Bovenzi
authors.forename: A
authors.initials: A
authors.lastname: Manto
authors.forename: C
authors.initials: C
authors.lastname: Pedone
authors.forename: M
authors.initials: M
authors.lastname: Pahor
mesh_terms: D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D000428:Alcohol Drinking / Q000453:epidemiology; D015992:Body Mass Index; D002784:Cholesterol / Q000097:blood; D003072:Cognition Disorders / Q000175:diagnosis / Q000453:epidemiology* / Q000209:etiology / Q000503:physiopathology; D004522:Educational Status; D005260:Female; D006801:Humans; D007558:Italy / Q000453:epidemiology; D007902:Length of Stay / Q000706:statistics & numerical data; D016015:Logistic Models; D018655:Lymphocyte Count; D008297:Male; D009752:Nutritional Status; D016017:Odds Ratio; D015995:Prevalence; D012307:Risk Factors; D012709:Serum Albumin / Q000378:metabolism; D017678:Sex Distribution
chemical_list: D012709:Serum Albumin; D002784:Cholesterol