Evidence map›Paper›PMID 42295447›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2026

Measuring inequality in quality of life: further evidence that the EQ-5D-5L may underestimate it.

Admassu N Lamu, Gang Chen, Ling Jie Cheng, Jan Abel Olsen, EQ-DAPHNIE Project Team

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Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Admassu N LamuA Lamu Consulting, Bergen, Norway.ORCID http://orcid.org/0000-0001-6638-421X
Gang ChenCancer Health Services Research Unit, University of Melbourne, Melbourne, Australia.ORCID http://orcid.org/0000-0002-8385-5965
Ling Jie ChengNational Perinatal Epidemiology Unit, Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, United Kingdom. cheng.lingjie@nus.edu.sg.ORCID http://orcid.org/0000-0002-5338-578X
Jan Abel OlsenDepartment of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.ORCID http://orcid.org/0000-0001-9472-2669
EQ-DAPHNIE Project Team

Funding

EuroQol Research Foundation 1830-RA
6 · The paper itself

Abstract

purposeA previous study found that individuals with identical EQ-5D-5L profiles reported systematically higher EQ VAS scores with increasing educational attainment, which suggests a 'hidden' socioeconomic gradient not captured by the EQ-5D-5L. This study examines the robustness and generalisability of these findings using multi-country data.

methodsWe analysed data from 32,327 respondents aged 25 to 79 years across eight high-income countries: Australia, Canada, France, Germany, the Netherlands, New Zealand, the UK, and the US. The data came from the EQ-DAPHNIE study. Within ten selected EQ-5D-5L health profiles, we used linear regression models to estimate the associations between EQ VAS scores and educational attainment or subjective income status, adjusting for age, sex, and country.

resultsWe observed a consistent educational gradient in EQ VAS scores across most EQ-5D-5L profiles. Tertiary education was associated with higher scores in all ten profiles, with effects statistically significant at p < 0.10 in seven, of which four at p < 0.01. Income status showed an even stronger gradient, with significant associations in nine of the ten profiles. These patterns were evident in all eight countries.

conclusionThese multi-country findings provide robust evidence of a socioeconomic gradient in EQ VAS scores among respondents who report identical EQ-5D-5L health profiles, over and above what is reflected in the five EQ-5D-5L dimensions. This pattern has implications for the use of EQ-5D-5L values in equity-informative health technology assessment and population health monitoring.

Indexed as

Health Status DisparitiesQuality of LifeAdultAgedDeveloped CountriesEducational StatusFemaleHumansMaleMiddle AgedSocioeconomic Disparities in HealthSocioeconomic FactorsSurveys and QuestionnairesEQ-5D-5LEQ-DAPHNIEEQ VASHealth inequalityHealth-related quality of lifeSocioeconomic gradient

Identifiers

PMID42295447
PMCPMC13269496

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.