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

## TL;DR

This study examines how chronic diseases and other factors predict job loss in Lebanon during multiple crises, highlighting the need for workforce protections.

## Contribution

The study identifies specific chronic diseases and socio-demographic factors as predictors of employment attrition during overlapping crises in Lebanon.

## Key findings

- Older age, female sex, and chronic conditions like CVD and diabetes were significant predictors of employment attrition.
- The study found that musculoskeletal disorders' impact on employment attrition increases with age.
- A prediction model showed moderate discriminative ability and good calibration for employment attrition.

## 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.