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Predicting depressive and anxiety symptoms among Lebanese and Syrian adults in a suburb of Beirut, Lebanon, during concurrent crises: nested cross-sectional study

Por: Shamas · H. · Ragi · M.-E. · Abi Zeid · B. · DeJong · J. · McCall · S. J. · CAEP Study Group · Germani · El-Jardali · Ghattas · M Melhem · DeJong · McCall
Objective

This study aimed to develop prediction models for symptoms of poor mental health among Lebanese adults and adult Syrian refugees or migrants residing in a suburb of Beirut, Lebanon, separately.

Design

Nested cross-sectional study.

Setting

Sin-El-Fil, a suburb east of Beirut, Lebanon.

Participants

Lebanese and Syrian adults residing in low socio-economic status areas of Sin-El-Fil.

Primary and secondary outcome measures

Primary outcome was having depressive symptoms, ascertained through the Patient Health Questionnaire-9 where a total summative score of 10 or more indicated having depressive symptoms. Secondary outcome was having anxiety symptoms, ascertained through the Generalised Anxiety Disorder-7 where a total summative score of 10 or more indicated having anxiety symptoms.

Results

Of 1986 participants, 1322 (66.5%) were Lebanese adults, 664 (33.5%) were Syrian refugees or migrants. Among Lebanese adults and adult Syrian refugees or migrants, 324 (25.3%) and 289 (43.9%) had depressive symptoms, respectively. Having pain that impacts usual activity, having debt, not feeling safe at home and having none or one person to count on in difficult times were common predictors of depressive and anxiety symptoms among Lebanese adults and Syrian refugees or migrants. Not having a legal residency permit was also a predictor of depressive symptoms for Syrian refugees or migrants. Prediction models developed for depressive and anxiety symptoms among both nationalities had good performance measures.

Conclusions

The predictors of poor mental health included financial, health and social indicators for both Lebanese adults and Syrian refugees or migrants during the concurrent crisis in Lebanon. These models are most applicable in similar urban, crisis-affected and low-resource settings. Findings emphasise the need for social protection and financial support among populations with vulnerabilities.

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