Evidence map›Paper›PMID 42323880›Full record

ArticleEuropean journal of public health2026

Determinants of disability pension following sickness absence in French private-sector employees.

Mohamed Ali Ben Halima, Karim Aït Bouziad, Narimene Louati, Marie-Anne Cousin-Renié, William Dab

Abstract read
In one paragraph

Article in European journal of public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mohamed Ali Ben HalimaCEET, Conservatoire National des Arts et Métiers, Paris, France.ORCID 0000-0002-1496-0921
Karim Aït BouziadMESuRS, Conservatoire National des Arts et Métiers, Paris, France.
Narimene LouatiMESuRS, Conservatoire National des Arts et Métiers, Paris, France.
Marie-Anne Cousin-ReniéMalakoff Humanis, Paris, France.
William DabMESuRS, Conservatoire National des Arts et Métiers, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disability pension represents a major public health challenge in France, with 843 000 beneficiaries and €8.5 billion expenditure in 2022. The transition from sickness absence to disability pension remains insufficiently documented in the French context. This study identifies risk factors for disability pension among French private-sector employees to inform targeted prevention strategies. We conducted a retrospective cohort study of 228 514 employees from a complementary health insurer (2018-23), encompassing 364 762 sickness absence episodes. Risk factors for transition to disability pension were analyzed using Kaplan-Meier survival and Cox proportional hazards models stratified by absence duration, adjusting for sociodemographic, employment, organizational, and health-related factors. Of all episodes, 6404 (1.8%) progressed to disability pension. Risk was particularly high among individuals aged ≥50 years and among those in higher-risk socio-professional groups, notably executives and individuals belonging to the "Other" category (including farmers, merchants, and business owners), compared with employees. Increased risk was also observed among workers in the lowest income quartile and among employees in large companies. Long-term sickness absence (>180 days) was associated with a higher risk of disability pension. Therapeutic part-time work reduced risk only for short absences. Most risk factors lost predictive power beyond 12 months, with declining effect sizes over time. This study identifies a critical 12-month intervention window. Early interventions should prioritize therapeutic part-time work and strengthen targeted support for older workers, executives, and large company employees to reduce disability pension transitions and curb rising costs.

Indexed as

AbsenteeismPensionsPersons with DisabilitiesPrivate SectorSick LeaveAdultFemaleFranceHumansMaleMiddle AgedRetrospective StudiesRisk FactorsSocioeconomic Factorsdisability pensionoccupational health policypreventionrisk factorssickness absence

Identifiers

PMID42323880
PMCPMC13283447

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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 OpenQuestion graph.