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OP104 Development and validation of a model predicting poor mental health amongst older Syrian refugees in Lebanon during the COVID-19 pandemic: a repeated cross-sectional analysis
  1. Stephen McCall1,
  2. Berthe Abi Zeid1,
  3. Tanya El Khoury1,
  4. Monique Chaaya2,
  5. Abla Sibai2,
  6. Sirine Anouti3,
  7. Zeinab Ramadan3,
  8. Hala Ghattas1,
  9. Sawsan Abdulrahim4,
  10. Leen Farouki5
  1. 1Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
  2. 2Department of Epidemiology and Population Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
  3. 3Norwegian Refugee Council (NRC), Beirut, Lebanon
  4. 4Department of Health Promotion and Community Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
  5. 5School of Social and Political Science, University of Edinburgh, Edinburgh, UK


Background Throughout the COVID-19 pandemic, older Syrian refugees in Lebanon faced multiple adverse socio-ecological difficulties, which may have exacerbated their mental health disorders. Identifying predictors of poor mental health provides pathways for humanitarian programming to target interventions. This study aimed to identify socio-ecological predictors of poor mental health amongst older Syrian refugees living in Lebanon during the COVID-19 pandemic.

Methods All Syrian refugee households in Lebanon with members aged 50 years or older that received assistance from a humanitarian organization were invited to participate in a multi-wave telephone survey. A repeated cross-sectional analysis was conducted for three (out of five) data collection waves of a longitudinal survey (wave 1 (September-December 2020), wave 3 (January-April 2021) and wave 5 (January-March 2022)). The main outcome, mental health, was measured using the Mental Health Inventory-5, in which a score equal to or less than 60 indicated poor mental health. All candidate predictors identified from the literature and collected in the survey were included in the model. Using wave 1 data, the model was developed through backward stepwise logistic regression. Bootstrapping was used to internally validate the model and to provide an estimate of optimism. The model’s optimism-adjusted calibration slope (C-slope) and discrimination (C-statistic) of the model were presented. Model performance was assessed in waves 3 and 5.

Results Of 3,229 participants, 47% were female, and the median age was 56 years old [IQR: 53–62]. At wave 1, 76.7% had poor mental health, increasing to 89.2% and 92.7% at wave 3 and wave 5, respectively. Predictors for poor mental health were food insecurity, water insecurity, lacking legal documentation, unemployment, and poor self-reported health. The optimised adjusted C-statistic was 0.69 (95% CI:0.67–0.72) with a C-slope of 0.93 (95% CI:0.84–1.05). The C-statistic was 0.69 (95%CI:0.66–0.72) in wave 3, and 0.73 (95%CI:0.69–0.76) in wave 5, as well as the C-slope were 1.00 (95%CI:0.83–1.17) and 1.00 (95%CI:0.84–1.16), respectively.

Discussion The mental health of older Syrian refugees in Lebanon worsened during the COVID-19 pandemic. Predictors of poor mental health were related to the basic human needs and rights of refugees, which require to be met to improve the health and well-being of this vulnerable population. This study is representative of older Syrian refugees receiving assistance and may not be generalizable to all Syrians residing in Lebanon.

  • Mental health
  • Refugee health
  • Global health

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