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Value Health ; 27(5): 633-641, 2024 May.
Article in English | MEDLINE | ID: mdl-38423209

ABSTRACT

OBJECTIVES: Over half of Australia's disease burden is due to morbidity, predominantly chronic conditions. Health-related quality of life instruments provide measures of morbidity and health status across different dimensions with EQ-5D being one of the most widely used. This study reports EQ-5D-5L general population norms for Queensland, Australia using the recently published Australian value set. METHODS: Population survey results from cross-sectional computer-assisted telephone interviews for Queensland adults in 2022 and 2023 were analyzed. EQ-5D-5L, as well as modifiable risk factors and sociodemographic data were collected. Using the recently published final Australian EQ-5D-5L value set, mean utility scores were calculated for Queensland, as well as by sociodemographic characteristics, including remoteness and socioeconomic area-based measures, and modifiable risk factors, such as smoking and body mass index. Results were combined with life tables to estimate quality-adjusted life expectancy (QALE) for subgroups with different lifestyles. RESULTS: The EQ-5D utility score for the Queensland adult population was 0.916. Smoking daily, being obese or older in age, or living in the most disadvantaged socioeconomic area were associated with lower mean scores. QALE was 6.1 and 7.9 years shorter than the life expectancy for Queensland males and females, respectively, but generally, those who reported having healthier lifestyles had higher mean utility scores and thus longer QALE. CONCLUSIONS: In addition to reporting Queensland EQ-5D-5L general population norms, these results demonstrate potential QALE gains in people following healthier lifestyles. The results support investment in prevention and may motivate further studies in this important area.


Subject(s)
Quality of Life , Quality-Adjusted Life Years , Humans , Adult , Male , Queensland/epidemiology , Female , Middle Aged , Cross-Sectional Studies , Risk Factors , Aged , Young Adult , Sociodemographic Factors , Adolescent , Socioeconomic Factors , Health Status , Life Expectancy
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