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Measuring inequality in quality of life: Why the EQ-5D may underestimate it
Jan Abel Olsen1, Gang Chen2, Admassu Lamu3
1Department of Community Medicine, Faculty of Health Sciences, UiT - the Arctic University of Norway, 9019, Tromsø, Norway. jan.abel.olsen@uit.no.
Objective:
The EQ-5D is increasingly being used in studies of health inequalities, providing further evidence of a social gradient in health; i.e. consistent positive associations between a socioeconomic indicator and health. However, the steepness in the social gradients in HRQoL differs depending on which of the two EQ-5D measures is used; whether based on respondents' EQ-5D-5L descriptions or by their direct valuation in EQ-VAS. This study aims to provide new knowledge as to why the two HRQoL measures suggest different degrees of health inequalities.
Methods:
Based on two large unique data sets (Tromsø Study Wave 7, N = 21,083; MIC study, N = 8022), cross-sectional analyses were conducted. We identified the most prevalent EQ-5D-5L profiles. Within each of ten EQ-5D-5L profile groups, we examine response heterogeneities in EQ-VAS scores using linear regressions, as explained by respondents' level of educational attainment, controlling for age and sex.
Results:
We showed significantly increasing EQ-VAS scores along with educational attainments. For instance, in the most prevalent health state (11121), a consistent education-health gradient was observed: compared to individuals with primary education, the EQ-VAS was 1.7 higher among those with secondary education; 2.6 higher among individuals with short tertiary education; and, 3.7 higher among individuals with long tertiary education.
Conclusions:
This paper provides new insights into the use of EQ-5D in health inequality studies by suggesting an additional underlying education gradient in HRQoL than what is revealed through the EQ-5D-5L values. Broader psychosocial domains and aspects of adaptation should be considered when monitoring health inequalities.
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