title: Utility-based quality of life associated with overweight and obesity: the Australian diabetes, obesity, and lifestyle study.
abstract: OBJECTIVE
  This study aimed to estimate utility-based quality of life (UQoL) differences between healthy body weight and excess body weight categories.
  
  
  METHODS
  Cross-sectional analysis of 10,959 adults, participating in baseline data collection of the nationally representative Australian Diabetes, Obesity, and Lifestyle (AusDiab) Study was undertaken. Height and weight were measured by trained personnel. Body weight categories were assigned as healthy weight, overweight, and obesity subclasses I, II and III. UQoL was assessed using the SF-6D, which captures physical functioning, role limitation, social functioning, pain, mental health, and vitality on a score of 0.00-1.00 (worst-best). The relationship between body weight categories and UQoL was assessed using linear regression, adjusting for age, sex, education, and smoking.
  
  
  RESULTS
  Relative to the healthy weight group (mean UQoL score 0.77), mean adjusted UQoL differences (95% confidence intervals) were 0.001 (-0.008, 0.010) for overweight, -0.012 (-0.022, -0.001) for class-I obese, -0.020 (-0.041, 0.001) for class-II obese, and -0.069 (-0.099, -0.039) for class-III obese groups. Adding metabolic syndrome markers to the covariates had little impact on these differences.
  
  
  CONCLUSIONS
  Results confirmed an inverse dose-response relationship between body weight and UQoL in this study of Australian adults. This highlights the need to incorporate UQoL measures which are sensitive to the subclasses of obesity when evaluating obesity interventions.
authors.affiliation: Deakin Health Economics, Deakin University, Melbourne, Australia. catherine.keating@deakin.edu.au
authors.forename: Catherine L
authors.initials: CL
authors.lastname: Keating
authors.forename: Anna
authors.initials: A
authors.lastname: Peeters
authors.forename: Boyd A
authors.initials: BA
authors.lastname: Swinburn
authors.forename: Dianna J
authors.initials: DJ
authors.lastname: Magliano
authors.forename: Marjory L
authors.initials: ML
authors.lastname: Moodie
mesh_terms: D000328:Adult; D001315:Australia / Q000453:epidemiology; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D015992:Body Mass Index; D001835:Body Weight; D002784:Cholesterol / Q000097:blood; D003430:Cross-Sectional Studies; D005260:Female; D006304:Health Status; D006801:Humans; D008019:Life Style; D016014:Linear Models; D008297:Male; D008603:Mental Health; D008875:Middle Aged; D009043:Motor Activity; D015999:Multivariate Analysis; D009765:Obesity / Q000453:epidemiology* / Q000378:metabolism; D050177:Overweight / Q000453:epidemiology* / Q000378:metabolism; D011788:Quality of Life; D014280:Triglycerides / Q000097:blood
chemical_list: D001786:Blood Glucose; D014280:Triglycerides; D002784:Cholesterol