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Background <p>EQ-5D is widely used in economic evaluations and population health assessments. This study used a large population-based cohort with EQ-5D-3L data to describe the health-related quality of life (HRQoL) of the general population in Stockholm County and investigate potential inequalities and variations in HRQoL.</p> Methods <p>This study analysed data from 52,714 respondents aged 23–104 years from the 2021 Stockholm Public Health Cohort (SPHC). Calibration weights were used to address non-response bias and improve representativeness. Differences in mean EQ-VAS and EQ-5D-3L index values were analyzed using multivariable regressions, and modified poison regression was used to explore the likelihood of reporting problems across the EQ-5D dimensions. Splines were used to flexibly model the nonlinear relationship between age and HRQoL.</p> Results <p>A total of 169 health states were observed, with 37% of the respondents reporting “no problems” in all dimensions (“11111”). Further, 0.05% (<i>n</i> = 14) respondents reported the worst possible health state (“33333”). The HRQoL of the general population was generally good but variations across sociodemographic and risk factor groups were observed. HRQoL demonstrated a non-linear relationship with age, with relatively lower scores observed among the youngest adults, increasing through midlife, followed by a marked decline in older age, particularly among those aged 80 years and above. The mean EQ-5D-3&#xa0;L index was lower among females (0.79 [95% CI: 0.79–0.80]) than males (0.83 [95% CI: 0.83–0.84]), and a similar pattern was observed for the mean EQ-VAS scores (75.96 [95% CI: 75.59–76.33] vs. 78.3 [95% CI: 77.62–78.42], respectively). People with lower education, low disposable income as well as those born outside of the European union and UK reported relatively lower HRQoL. Adjusting for age attenuated but did not eliminate these demographic and socioeconomic differences. Persistent associations between behavioural risk factors and HRQoL were also observed. Similarly, people with chronic health conditions, particularly those with long-term illness or multiple health conditions, exhibited markedly lower HRQoL.</p> Conclusion <p>This study demonstrated substantial variations in HRQoL across sociodemographic groups, behavioural risk factors, and self-reported health conditions, providing insights that can inform healthcare planning and future investments in health and research. The results may also serve as reference values in clinical and economic evaluations, and for comparing outcomes from specific patient subgroups with the general population.</p>

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Variations in health-related quality of life across sociodemographic groups, health conditions, and modifiable risk factors: a population-based EQ-5D-3L study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月20日

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  • Mihretab Gebreslassie,
  • Stefan Fors,
  • Per Tynelius,
  • Mathieu F. Janssen,
  • Sofia Sveréus,
  • Emelie Heintz

摘要

Background

EQ-5D is widely used in economic evaluations and population health assessments. This study used a large population-based cohort with EQ-5D-3L data to describe the health-related quality of life (HRQoL) of the general population in Stockholm County and investigate potential inequalities and variations in HRQoL.

Methods

This study analysed data from 52,714 respondents aged 23–104 years from the 2021 Stockholm Public Health Cohort (SPHC). Calibration weights were used to address non-response bias and improve representativeness. Differences in mean EQ-VAS and EQ-5D-3L index values were analyzed using multivariable regressions, and modified poison regression was used to explore the likelihood of reporting problems across the EQ-5D dimensions. Splines were used to flexibly model the nonlinear relationship between age and HRQoL.

Results

A total of 169 health states were observed, with 37% of the respondents reporting “no problems” in all dimensions (“11111”). Further, 0.05% (n = 14) respondents reported the worst possible health state (“33333”). The HRQoL of the general population was generally good but variations across sociodemographic and risk factor groups were observed. HRQoL demonstrated a non-linear relationship with age, with relatively lower scores observed among the youngest adults, increasing through midlife, followed by a marked decline in older age, particularly among those aged 80 years and above. The mean EQ-5D-3 L index was lower among females (0.79 [95% CI: 0.79–0.80]) than males (0.83 [95% CI: 0.83–0.84]), and a similar pattern was observed for the mean EQ-VAS scores (75.96 [95% CI: 75.59–76.33] vs. 78.3 [95% CI: 77.62–78.42], respectively). People with lower education, low disposable income as well as those born outside of the European union and UK reported relatively lower HRQoL. Adjusting for age attenuated but did not eliminate these demographic and socioeconomic differences. Persistent associations between behavioural risk factors and HRQoL were also observed. Similarly, people with chronic health conditions, particularly those with long-term illness or multiple health conditions, exhibited markedly lower HRQoL.

Conclusion

This study demonstrated substantial variations in HRQoL across sociodemographic groups, behavioural risk factors, and self-reported health conditions, providing insights that can inform healthcare planning and future investments in health and research. The results may also serve as reference values in clinical and economic evaluations, and for comparing outcomes from specific patient subgroups with the general population.