DOI 10.1007/s11136-025-04089-5
EQ-5D-5L Iranian population norms derived from the local value set during the COVID-19 pandemic.
Аннотация
PURPOSE: To derive the first population norms from the EQ-5D-5L in Iran during the COVID-19 pandemic.
METHODS
Data were obtained from a study conducted in Iran during the COVID-19 pandemic in 2021. Face-to-face, computer-assisted interviews were conducted in a single visit, involving respondents from diverse sociodemographic backgrounds and providing a balanced representation of age and gender groups. Normative data for the EQ-5D-5L dimensions, EQ-5D-5L index values, and EuroQol visual analogue scale (EQ-VAS) scores were summarized by dimensions and disaggregated by age groups and gender. Multivariable logistic and Tobit regression models were used to investigate the associations between participants' sociodemographic characteristics and their self-reported health, as measured by the EQ-5D-5L instrument, including responses on the five dimensions, EQ-5D-5L index values, and EQ-VAS scores.
RESULTS
Among 1,004 participants, the mean index value and EQ-VAS score were 0.832 and 78.27, respectively. Full health was reported in 37.65% (EQ-5D-5L) and 6.18% EQ-VAS of participants. Anxiety/depression (AD) was the most frequently reported problem (47%), followed by pain/discomfort (36%). EQ-5D-5L index values and EQ-VAS scores decreased with age and increased with education, while women reported slightly worse health states than men. Multivariable logistic regressions showed that men had higher odds of reporting problems in most dimensions except in AD. Students had the lowest odds of reporting problems, whereas divorced individuals had the highest. Age, education, marital status, employment, and chronic illness were significantly associated with EQ-5D-5L index values and EQ-VAS scores (P < 0.001).
CONCLUSION
EQ-5D-5L index values and EQ-VAS scores were associated with age, educational level, marital status, employment status, and the presence of chronic illness. These norms provide valuable insights to support health funders and policymakers in making informed decisions about resource allocation.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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