ArticleHealth and quality of life outcomes2024
Health inequity assessment in Brazil: is EQ-5D-3L sensible enough to detect differences among distinct socioeconomic groups?
Article in Health and quality of life outcomes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Understanding Global Health Inequality and Inequity: Causes, Consequences, and the Path Toward Justice in Healthcare.Public health challenges · 2025Review
- Assessing inequalities in health utility scores among cancer patients undergoing systemic and radiation therapy.Health and quality of life outcomes · 2025Article
- Examining the Association Between Equity-Related Factors and EQ-5D-3L Health Utilities of Patients with Cancer.Current oncology (Toronto, Ont.) · 2025Article
- Measuring inequality in quality of life: Why the EQ-5D may underestimate it.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025Article
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6 authors.
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Abstract
backgroundMultidimensional health-related quality of life (HRQOL) instruments, such as the EQ-5D, are increasingly used to assess inequalities in health. However, it is necessary to explore the ability of these instruments to capture differences between population groups, especially in low/middle-income countries. This study aimed to investigate whether the EQ-5D-3L instrument can detect differences in HRQOL between groups of different socioeconomic status (SES) in Brazil.
methodsData collection occurred during the Brazilian EQ-5D-3L valuation study and included respondents aged 18 to 64 years enrolled in urban areas. SES was aggregated into three categories: "higher" (A and B), "intermediate" (C) and "lower" (D and E). EQ-5D-3L index was calculated considering the Brazilian value set. A mixed-effects regression model was estimated with random effects on individuals and marginal effects on SES, sex, and educational attainment. Odds ratios for the chance of reporting problems for each EQ-5D dimension were estimated by logistic regression.
resultsA total of 9,148 respondents were included in the study. Mean age was 37.80 ± 13.13 years, 47.4% were men and the majority was ranked as classes B or C (38.4% and 50.7%, respectively). Participants in lower SES classes reported increasingly poorer health compared to individuals in higher classes. The mean EQ-5D-3L index decreased as SES deteriorates being significantly higher for classes A and B (0.874 ± 0.14) compared to class C (0.842 ± 0.15) and classes D and E (0.804 ± 0.17) (p < 0.001). The same was observed for the mean EQ-VAS scores (84.0 ± 13.8 in classes A and B, 81.0 ± 17 in class C and 78.3 ± 18.7 in class C [p < 0.001]). The multivariate analysis confirmed that SES is an independent factor that effects EQ-5D-3L index measures. Participants in intermediate and lower SES classes have a statistically significant lower EQ-5D-3L index compared to participants in classes A and B, regardless of age, sex, and educational attainment.
conclusionIn a Brazilian population sample, the EQ-5D-3L instrument was able to detect important differences between groups with distinct socioeconomic statuses (SES). The EQ-5D-3L is useful for exploring inequities in health.
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