ArticleBMJ global health2024
Predicting poor mental health among older Syrian refugees in Lebanon during the COVID-19 pandemic: a nested cross-sectional study.
Article in BMJ global health, 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.
- Observational
- Mental well-being among Syrian refugee workers in Lebanon: a multidimensional approach.Journal of global health · 2026Article
- Predicting COVID-19 infection among older Syrian refugees in Lebanon: A multi-wave survey.PloS one · 2026Article
- Psychosocial well-being and mental health of low- and middle-income countries' internally displaced persons and refugees during COVID-19: a systematic literature review.Global mental health (Cambridge, England) · 2024Review
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10 authors.
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Abstract
introductionThe COVID-19 pandemic has worsened pre-existing vulnerabilities among older Syrian refugees in Lebanon, potentially impacting their mental health. The study aims to describe the evolution of poor mental health over time and to develop and internally validate a prediction model for poor mental health among older Syrian refugees in Lebanon.
methodsThis prognostic study used cross-sectional data from a multiwave telephone survey in Lebanon. It was conducted among all Syrian refugees aged 50 years or older from households that received assistance from a humanitarian organisation. Data were collected between 22 September 2020 and 20 January 2021. Poor mental health was defined as a Mental Health Inventory-5 score of 60 or less. The predictors were identified using backwards stepwise logistic regression. The model was internally validated using bootstrapping. The calibration of the model was presented using the calibration slope (C-slope), and the discrimination was presented using the optimised adjusted C-statistic.
resultsThere were 3229 participants (median age=56 years (IQR=53-62)) and 47.5% were female. The prevalence of poor mental health was 76.7%. Predictors for poor mental health were younger age, food insecurity, water insecurity, lack of legal residency documentation, irregular employment, higher intensity of bodily pain, having debt and having chronic illnesses. The final model demonstrated good discriminative ability (C-statistic: 0.69 (95% CI 0.67 to 0.72)) and calibration (C-slope 0.93 (95%CI 0.82 to 1.07)).
conclusionMental health predictors were related to basic needs, rights and financial barriers. These allow humanitarian organisations to identify high-risk individuals, organise interventions and address root causes to boost resilience and well-being among older Syrian refugees in Lebanon.
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