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1000 Titel
  • Association of pre-migration socioeconomic status and post-migration mental health in Syrian refugees in Lebanon: a descriptive sex-stratified cross-sectional analysis
1000 Autor/in
  1. Lange, Saskia |
  2. Glatz, Toivo |
  3. Eiset, Andreas Halgreen |
1000 Verlag
  • BioMed Central
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-03-04
1000 Erschienen in
1000 Quellenangabe
  • 9(1):9
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s41256-024-00347-0 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10910804/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>Refugee populations present with high levels of psychological distress, which may vary among sociodemographic characteristics. Understanding the distribution across these characteristics is crucial to subsequently provide more tailored support to the most affected according to their specific healthcare needs. This study therefore seeks to investigate the association between pre-migration socioeconomic status (SES) and post-migration mental health separately for male and female Syrian refugees in Lebanon.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>In a cross-sectional study, a cluster randomized sample of 599 refugees from Syria were recruited between 2016 and 2019 within 12 months after they fled to Lebanon. Logistic regression was used to determine the association between self-reported pre-migration SES and levels of anxiety and depressive symptoms assessed on the Hopkins Symptoms Checklist-25 (HSCL-25) scale, both for the entire sample and stratified by sex. To assess the informative value of self-reported SES, its correlation with education variables was tested. All analyses were conducted in R version 4.3.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>Using complete cases, 457 participants (322 female, 135 male) were included in the analyses. Females showed on average more symptoms of anxiety (Median: 2.5) and depression (Median: 2.4) than males (Median: 2.10 and 2.07, respectively). Below average SES was associated with significantly higher odds for mental illness compared to average SES (anxiety: OR 4.28, 95% CI [2.16, 9.49]; depression: OR 1.85, 95% CI [1.06, 3.36]). For anxiety, differences between SES strata were larger for males than females. The self-reported SES measure showed only a weak positive correlation with education.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>This study adds additional descriptive data highlighting mental health differences in Syrian refugees in Lebanon, whereby below average SES is associated with worse mental health outcomes compared to average SES. These findings demand further research into the underlying mechanisms. Improving our understanding of the observed differences will provide valuable insights that can contribute to the future development of targeted measures.</jats:p> </jats:sec>
1000 Sacherschließung
lokal Cricetinae [MeSH]
lokal Female [MeSH]
lokal Social determinants
lokal Humans [MeSH]
lokal Refugees [MeSH]
lokal Mental Health [MeSH]
lokal Syria [MeSH]
lokal Cross-Sectional Studies [MeSH]
lokal Gender
lokal Animals [MeSH]
lokal Lebanon/epidemiology [MeSH]
lokal SES
lokal Mental health
lokal Migration
lokal Depression
lokal Anxiety
lokal Male [MeSH]
lokal Sex
lokal Research
lokal Mesocricetus [MeSH]
lokal Refugees
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-0673-5468|https://orcid.org/0000-0002-8994-7860|https://orcid.org/0000-0002-5487-8359
1000 Hinweis
  • DeepGreen-ID: 8fcbd04526a34cdd8aee2693e7bb83e0 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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  1. Charité – Universitätsmedizin Berlin |
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    1000 Förderer Charité – Universitätsmedizin Berlin |
    1000 Förderprogramm -
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1000 Erstellt am 2025-02-05T13:06:26.841+0100
1000 Erstellt von 322
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1000 Zuletzt bearbeitet 2025-07-30T08:37:34.949+0200
1000 Objekt bearb. Wed Jul 30 08:37:34 CEST 2025
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