Income-Related Inequality in Health-Related Quality of Life Among Australian Adults: The Contribution of Chronic Conditions

Background: Chronic conditions are associated with poorer health-related quality of life (HRQoL) and are more common in socioeconomically disadvantaged groups. We examined income-related inequality in health-related quality of life and quantified the contribution of chronic conditions to inequality in HRQoL among Australian adults. Methods: We analysed pooled cross-sectional survey data from 4953 Australian adults recruited through a non-probability online panel. We measured HRQoL using EQ-5D-5L utility scores calculated with the Australian value set. We measured income-related inequality using the Erreygers-corrected concentration index. Multivariable ordinary least squares regression estimated adjusted associations with utility, and decomposition analysis estimated the statistical contributions of chronic-condition burden and sociodemographic characteristics. Results: Higher EQ-5D-5L utility was modestly concentrated among participants in higher-income categories (Erreygers-corrected concentration index [ECI] = 0.0328; bootstrap SE = 0.0038; 95% bootstrap percentile CI 0.0251–0.0401; p < 0.001). Compared with participants reporting no chronic condition, those with multimorbidity had an adjusted utility score that was 0.151 points lower. Multimorbidity made the largest contribution to the observed inequality (27.63%), followed by not working (26.34%) and annual income above A$65,000 (19.27%). Conclusions: EQ-5D-5L utility was modestly concentrated among participants in higher-income categories. Multimorbidity and not working were the largest measured contributors. These cross-sectional findings describe statistical associations and do not establish cause and effect.

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Journal
Health Economics and Policy
Published
2026-11-04
DOI
https://doi.org/10.3390/hep1020011
Primary Topic
Health disparities and outcomes
Type
article
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article

Income-Related Inequality in Health-Related Quality of Life Among Australian Adults: The Contribution of Chronic Conditions

Tracy Anne Comans, Syed Afroz Keramat, Vanessa Lee, Rajat Patel
Health Economics and Policy
Health disparities and outcomes
article

Income-Related Inequality in Health-Related Quality of Life Among Australian Adults: The Contribution of Chronic Conditions

Tracy Anne Comans, Syed Afroz Keramat, Vanessa Lee, Rajat Patel
article en

Abstract

Background: Chronic conditions are associated with poorer health-related quality of life (HRQoL) and are more common in socioeconomically disadvantaged groups. We examined income-related inequality in health-related quality of life and quantified the contribution of chronic conditions to inequality in HRQoL among Australian adults. Methods: We analysed pooled cross-sectional survey data from 4953 Australian adults recruited through a non-probability online panel. We measured HRQoL using EQ-5D-5L utility scores calculated with the Australian value set. We measured income-related inequality using the Erreygers-corrected concentration index. Multivariable ordinary least squares regression estimated adjusted associations with utility, and decomposition analysis estimated the statistical contributions of chronic-condition burden and sociodemographic characteristics. Results: Higher EQ-5D-5L utility was modestly concentrated among participants in higher-income categories (Erreygers-corrected concentration index [ECI] = 0.0328; bootstrap SE = 0.0038; 95% bootstrap percentile CI 0.0251–0.0401; p < 0.001). Compared with participants reporting no chronic condition, those with multimorbidity had an adjusted utility score that was 0.151 points lower. Multimorbidity made the largest contribution to the observed inequality (27.63%), followed by not working (26.34%) and annual income above A$65,000 (19.27%). Conclusions: EQ-5D-5L utility was modestly concentrated among participants in higher-income categories. Multimorbidity and not working were the largest measured contributors. These cross-sectional findings describe statistical associations and do not establish cause and effect.

Health Economics and PolicyVol. 1(2)
The University of Queensland (AU)
Openalex Percentile: Top 12%
Health disparities and outcomes
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