Health as predictor of unemployment. A population based study in Belgium

Abstract Background Health and employment are interrelated, but this can be both the result of social causation and health selection. Insights in the association between health and employment should be explored in different settings and countries because contextual factors may differ. In this study we investigate if at the Belgian population level, ill health leads to a higher risk of unemployment. Methods We used data from the Belgian health interview survey 2018 linked with administrative data from the compulsory health insurance including information on employment status in 2018 and 2019. The sample for this study consisted of people with a paid job, aged 18-64 year, with no record of having being unemployed in 2018 (n = 3769). Multivariate logistic regression was used to assess if the risk of becoming unemployed in 2019 varied in function of the health status assessed in the 2018 survey. Results After adjustment for age, sex, education and social support, the risk of becoming unemployed was significantly higher for people with moderate to very bad self-rated health compared to those in good health (OR 2.76; 95% CI 1.34-5.67). Similarly, unemployment in the year following participation in the survey was significantly higher among people with activity limitations because of health problems (OR 2.32; 95% CI 1.14-4.72). The higher the number of chronic diseases and conditions, the higher the risk of unemployment (OR 1.37; 95% CI 1.13-1.53). Specific predictors of unemployment were a history of serious depression in the past 12 months (OR 4.47; 95% CI 1.85-10.80) and hypertension (OR 2.54; 95% CI 1.08-6.00). Conclusions In Belgium, health problems are a risk factor of getting unemployed. Especially people with a history of serious depression in the past year have a higher risk to lose their job. The findings confirm the health selection of unemployment and the need for the labour market to invest in interventions to support people with health problems to keep or find a job. Key messages • As employment is a fundamental right, also for people with health problems, further efforts are needed to create an inclusive labour market, with also job opportunities for more vulnerable people. • To be able to understand better the link between health and unemployment at population level, longitudinal population data are needed including both dimensions.

Authors

Institutions

Publication Details

Journal
European Journal of Public Health
Published
2024-10-28
DOI
https://doi.org/10.1093/eurpub/ckae144.1103
Primary Topic
Employment and Welfare Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Health as predictor of unemployment. A population based study in Belgium

Johan Van der Heyden, Helena Bruggeman, Pierre Smith
European Journal of Public Health
Employment and Welfare Studies
article

Health as predictor of unemployment. A population based study in Belgium

Johan Van der Heyden, Helena Bruggeman, Pierre Smith
article en

Abstract

Abstract Background Health and employment are interrelated, but this can be both the result of social causation and health selection. Insights in the association between health and employment should be explored in different settings and countries because contextual factors may differ. In this study we investigate if at the Belgian population level, ill health leads to a higher risk of unemployment. Methods We used data from the Belgian health interview survey 2018 linked with administrative data from the compulsory health insurance including information on employment status in 2018 and 2019. The sample for this study consisted of people with a paid job, aged 18-64 year, with no record of having being unemployed in 2018 (n = 3769). Multivariate logistic regression was used to assess if the risk of becoming unemployed in 2019 varied in function of the health status assessed in the 2018 survey. Results After adjustment for age, sex, education and social support, the risk of becoming unemployed was significantly higher for people with moderate to very bad self-rated health compared to those in good health (OR 2.76; 95% CI 1.34-5.67). Similarly, unemployment in the year following participation in the survey was significantly higher among people with activity limitations because of health problems (OR 2.32; 95% CI 1.14-4.72). The higher the number of chronic diseases and conditions, the higher the risk of unemployment (OR 1.37; 95% CI 1.13-1.53). Specific predictors of unemployment were a history of serious depression in the past 12 months (OR 4.47; 95% CI 1.85-10.80) and hypertension (OR 2.54; 95% CI 1.08-6.00). Conclusions In Belgium, health problems are a risk factor of getting unemployed. Especially people with a history of serious depression in the past year have a higher risk to lose their job. The findings confirm the health selection of unemployment and the need for the labour market to invest in interventions to support people with health problems to keep or find a job. Key messages • As employment is a fundamental right, also for people with health problems, further efforts are needed to create an inclusive labour market, with also job opportunities for more vulnerable people. • To be able to understand better the link between health and unemployment at population level, longitudinal population data are needed including both dimensions.

European Journal of Public HealthVol. 34(Supplement_3)
Sciensano (Belgium) (BE), UCLouvain (BE)
Decent work and economic growth
Openalex Percentile: Top 67%
Employment and Welfare Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.