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Background: The COVID-19 pandemic has created significant challenges in 2020 in the world and Iran. To help vulnerable groups such as refugees during the response and recovery phases of the COVID-19 pandemic, identifying the quality of life (QOL) and its associated factors is helpful. Considering that research in this field is limited, this study evaluated the effect of social determinants of health on the quality of life among Afghan refugees in Iran during the COVID-19 pandemic., Methods: We conducted a cross-sectional study on 300 Afghan refugees and migrants in Alborz province, Iran, from February to May 2022 using Convenience sampling. Data were completed using the socioeconomic status scale (SES), World Health Organization's quality of life -BREF (WHOQOL), Depression, Anxiety and Stress Scale-21 Items (DASS-21), and COVID-19 Post-Traumatic Stress Disorder Checklist (COVID-PTSD). In addition, path analysis was applied to evaluate the relationships among the research variables with quality of life., Results: 64.3% of the study participants were male, with a mean of 29.29 ± 9.64 years. The path analysis showed that SES had the most positive relationship (B = .266), and the number of COVID-19 cases had the most negative relationship (B = -.169) with the quality of life from both paths. The self-rated health had the most positive relationship (B = .25), and the DASS score had the most negative relationship (B = -.2) with the quality of life through only one path. Access to medical services was the only variable that indirectly had a positive causal relationship with QOL (B = .044)., Conclusion: We provided an empirical model that illustrates the relationships between quality of life and social determinants of health among Afghan refugees and migrants during the Covid19 pandemic. The negative emotional states of Depression, Anxiety, and Stress (DAS) as a mediator play an essential role in the quality of life and other variables., (© 2023. The Author(s).)

Considering the importance of long COVID-19 (LC), this study aimed to investigate the relationship between clinical/sociodemographic factors and LC symptoms (LCS). This online cross-sectional study was conducted on 308 people infected with COVID-19 in Alborz, Iran, from April 1 to June 1, 2022. Multivariable logistic regression models were applied to measure the association between the LCS with other variables. Overall, 76.6% of participants had at least one LCS. Results from the multivariate logistic regression analysis showed that females (crude odds ratio [OR] [95% confidence interval (CI)]: 2.725 [1.42, 5.22]), educated persons (3.747 [1.58, 8.84]), people with a higher number of COVID-19 reinfection (2.280 [1.30, 3.97]), having an underlying disease (1.996 [1.01, 3.93]), and COVID-19 severity (3.321 [1.037, 10.635]) had higher odds of LC than others (all p <.05). Study findings provide additional clinical/sociodemographic data on risk for LC. These data may inform future research and clinical practice for potential risk identification and early intervention. [ABSTRACT FROM AUTHOR]