Australian health‐related quality of life population norms derived from the SF‐6D

• Published in: Australian and New Zealand journal of public health Vol. 37; no. 1; pp. 17 - 23
• Main Authors: Norman, Richard, Church, Jody, van den Berg, Bernard, Goodall, Stephen
• Format: Journal Article
• Language: English
• Published: Oxford, UK Elsevier B.V 01.02.2013; Blackwell Publishing Ltd; Elsevier Limited; Elsevier
• Subjects: Adult; Age Distribution; Aged; Australia; Body Mass Index; Cost analysis; Education; Family Characteristics; Female; Gender; Health care expenditures; Health Status Indicators; Health Surveys; Households; Humans; Male; Middle Aged; Norms; Population; Population norms; Population studies; Population Surveillance - methods; Psychometrics - instrumentation; Quality of Life; Sex Distribution; SF-6D; Socioeconomic Factors; Socioeconomic status; Socioeconomics; Subgroups; Surveys and Questionnaires - standards; Young Adult; Australia; United Kingdom > UK; Canberra Australian Capital Territory Australia; PSE, New Zealand; PSE, Australia; SF‐6D; Australia; socioeconomic status; Population norms
• ISSN: 1326-0200; 1753-6405
• DOI: 10.1111/1753-6405.12005

To investigate population health‐related quality of life norms in an Australian general sample by age, gender, BMI, education and socioeconomic status. The SF‐36 was included in the 2009/10 wave of the Household, Income and Labour Dynamics in Australia (HILDA) survey (n=17,630 individuals across 7,234 households), and converted into SF‐6D utility scores. Trends across the various population subgroups were investigated employing population weights to ensure a balanced panel, and were all sub‐stratified by gender. SF‐6D scores decline with age beyond 40 years, with decreasing education and by higher levels of socioeconomic disadvantage. Scores were also lower at very low and very high BMI levels. Males reported higher SF‐6D scores than females across most analyses. This study reports Australian population utility data measured using the SF‐6D, based on a national representative sample. These results can be used in a range of policy settings such as cost‐utility analysis or exploration of health‐related inequality. In general, the patterns are similar to those reported using other multi‐attribute utility instruments and in different countries.