Evidence map›Paper›PMID 41880362›Full record

ArticlePloS one2026

Predictors of employment attrition in Lebanon during multifaceted crises: The role of chronic diseases - a national cross-sectional study.

Myriam Dagher, Ali Abboud, Ghada E Saad, Rita Itani, Rindala Fayyad, WOMENA Study Group, Hala Ghattas, Stephen J McCall

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Myriam DagherCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.ORCID https://orcid.org/0009-0006-7587-6949
Ali AbboudDepartment of Economics, Faculty of Arts and Sciences, American University of Beirut, Beirut, Lebanon.
Ghada E SaadCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
Rita ItaniCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.ORCID https://orcid.org/0009-0009-0669-1838
Rindala FayyadCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
WOMENA Study Group
Hala GhattasCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.ORCID https://orcid.org/0000-0001-8864-3374
Stephen J McCallCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.ORCID https://orcid.org/0000-0003-0078-7010

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic and Lebanon's ongoing economic crisis exacerbated existing workforce and health disparities. This study explored the predictors of employment attrition during Lebanon's concurrent crises and examined the association between chronic conditions and employment attrition. This cross-sectional study recruited adults aged 19-64 years residing in Lebanon through random digit dialing (January - July 2024). Data collected included socio-demographics, household characteristics, employment history and characteristics, and self-reported chronic conditions. The outcome was loss of paid employment (employment attrition) during the crises. Predictors were identified through a Least Absolute Shrinkage and Selection Operator (LASSO) regression, and model discrimination and calibration were assessed. Logistic regression models, adjusted for covariates identified through a directed acyclic graph, estimated the associations between the presence and types of chronic conditions and employment attrition. The effect modification by age on the association between chronic conditions and employment attrition was also assessed. Of 2103 participants employed prior to the onset of the concurrent crises (pre-2020), 72.7% were males, 70.1% were Lebanese, and 14.7% became unemployed during the crises. Predictors of employment attrition were: older age, female sex, non-Lebanese nationality, being married, having no formal education, having at least one of either CVD, diabetes, or musculoskeletal disorders, working in a private business or non-governmental institution, and having an oral agreement with employer. The prediction model had a moderate discriminative ability and good calibration. Pre-existing cardiovascular disease (adjusted odds ratio (aOR): 2.15; 95% confidence intervals (CI), 1.27 to 3.64) and diabetes (aOR: 2.52; 95% CI, 1.43 to 4.45) were independently associated with employment attrition. The ORs of employment attrition comparing those with to those without musculoskeletal disorders significantly increased with age. This study underscores the importance to address life-course disparities that contribute to employment attrition and to consider proactive job protections to mitigate workforce disruptions during times of crises, particularly in contexts where social safety nets are absent.

Indexed as

EmploymentAdultChronic DiseaseCross-Sectional StudiesFemaleHumansLebanonMaleMiddle AgedYoung Adult

Identifiers

PMID41880362
PMCPMC13016281

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.