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Diagnosis-specific sick leave as a long-term predictor of disability pension: a 13-year follow-up of the GAZEL cohort study.

Identifieur interne : 001272 ( Main/Exploration ); précédent : 001271; suivant : 001273

Diagnosis-specific sick leave as a long-term predictor of disability pension: a 13-year follow-up of the GAZEL cohort study.

Auteurs : Kristina Alexanderson [Suède] ; Mika Kivim Ki [Royaume-Uni] ; Jane Ferrie [Royaume-Uni] ; Hugo Westerlund [Suède] ; Jussi Vahtera [Finlande] ; Archana Singh-Manoux [Royaume-Uni] ; Maria Melchior [France] ; Marie Zins [France] ; Marcel Goldberg [France] ; Jenny Head [Royaume-Uni]

Source :

RBID : Hal:inserm-01155239

Abstract

Factors that increase the risk of labour market exclusion are poorly understood. In this study, we examined the extent to which all-cause and diagnosis-specific sick leave predict subsequent disability pension (DP). Prospective cohort study of 20 434 persons employed by the French national gas and electric company (the GAZEL study). New sick-leave spells >7 days in 1990-1992 were obtained from company records. Follow-up for DP was from 1994 to 2007. The HR, adjusted for age and occupational position, for DP was 3.5 (95% CI 2.7 to 4.5) in men and 2.6 (95% CI 1.9 to 3.5) in women with one or more sick-leave spells >7 days compared with those with no sick leave. The strongest predictor of DP was sick leave with a psychiatric diagnosis, HR 7.6 (95% CI 5.2 to 10.9) for men and 4.1 (95% CI 2.9 to 5.9) for women. Corresponding HRs for sick leave due to circulatory diagnoses in men and women were 5.6 (95% CI 3.7 to 8.6) and 3.1 (95% CI 1.8 to 5.3), for respiratory diagnoses 3.9 (95% CI 2.6 to 5.8) and 2.6 (95% CI 1.7 to 4.0), and musculoskeletal diagnoses 4.6 (95% CI 3.4 to 6.4) and 3.3 (95% CI 2.2 to 4.8), respectively. Sick leave with a psychiatric diagnosis is a major risk factor for subsequent DP, especially among men. Sick leave due to musculoskeletal or circulatory disorders was also a strong predictor of DP. Diagnosis-specific sick leave should be recognised as an early risk marker for future exclusion from the labour market.


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<name sortKey="Melchior, Maria" sort="Melchior, Maria" uniqKey="Melchior M" first="Maria" last="Melchior">Maria Melchior</name>
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<address>
<country key="FR"></country>
</address>
</desc>
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<orgName>Hôpital Paul Brousse</orgName>
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</address>
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<country>France</country>
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<name sortKey="Zins, Marie" sort="Zins, Marie" uniqKey="Zins M" first="Marie" last="Zins">Marie Zins</name>
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<country key="FR"></country>
</address>
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<orgName>Hôpital Paul Brousse</orgName>
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</address>
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<addrLine>101, rue de Tolbiac, 75013 Paris </addrLine>
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<country>France</country>
<placeName>
<settlement type="city">Versailles</settlement>
<region type="region" nuts="2">Île-de-France</region>
</placeName>
<orgName type="university">Université de Versailles-Saint-Quentin-en-Yvelines</orgName>
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<author>
<name sortKey="Goldberg, Marcel" sort="Goldberg, Marcel" uniqKey="Goldberg M" first="Marcel" last="Goldberg">Marcel Goldberg</name>
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<country key="FR"></country>
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<orgName>Hôpital Paul Brousse</orgName>
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<country>France</country>
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<settlement type="city">Versailles</settlement>
<region type="region" nuts="2">Île-de-France</region>
</placeName>
<orgName type="university">Université de Versailles-Saint-Quentin-en-Yvelines</orgName>
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<author>
<name sortKey="Head, Jenny" sort="Head, Jenny" uniqKey="Head J" first="Jenny" last="Head">Jenny Head</name>
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<orgName>Department of Epidemiology and Public Health</orgName>
<desc>
<address>
<addrLine>1-19 Torrington Place London WC1E 6BT</addrLine>
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<orgName>University College of London [London]</orgName>
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<addrLine>Gower Street, London WC1E 6BT </addrLine>
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<country>Royaume-Uni</country>
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<series>
<title level="j">Journal of Epidemiology and Community Health</title>
<idno type="ISSN">0143-005X</idno>
<imprint>
<date type="datePub">2012-01-31</date>
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<front>
<div type="abstract" xml:lang="en">
<p>Factors that increase the risk of labour market exclusion are poorly understood. In this study, we examined the extent to which all-cause and diagnosis-specific sick leave predict subsequent disability pension (DP). Prospective cohort study of 20 434 persons employed by the French national gas and electric company (the GAZEL study). New sick-leave spells >7 days in 1990-1992 were obtained from company records. Follow-up for DP was from 1994 to 2007. The HR, adjusted for age and occupational position, for DP was 3.5 (95% CI 2.7 to 4.5) in men and 2.6 (95% CI 1.9 to 3.5) in women with one or more sick-leave spells >7 days compared with those with no sick leave. The strongest predictor of DP was sick leave with a psychiatric diagnosis, HR 7.6 (95% CI 5.2 to 10.9) for men and 4.1 (95% CI 2.9 to 5.9) for women. Corresponding HRs for sick leave due to circulatory diagnoses in men and women were 5.6 (95% CI 3.7 to 8.6) and 3.1 (95% CI 1.8 to 5.3), for respiratory diagnoses 3.9 (95% CI 2.6 to 5.8) and 2.6 (95% CI 1.7 to 4.0), and musculoskeletal diagnoses 4.6 (95% CI 3.4 to 6.4) and 3.3 (95% CI 2.2 to 4.8), respectively. Sick leave with a psychiatric diagnosis is a major risk factor for subsequent DP, especially among men. Sick leave due to musculoskeletal or circulatory disorders was also a strong predictor of DP. Diagnosis-specific sick leave should be recognised as an early risk marker for future exclusion from the labour market.</p>
</div>
</front>
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<li>Finlande</li>
<li>France</li>
<li>Royaume-Uni</li>
<li>Suède</li>
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<li>Uusimaa</li>
<li>Île-de-France</li>
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<li>Helsinki</li>
<li>Versailles</li>
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<name sortKey="Melchior, Maria" sort="Melchior, Maria" uniqKey="Melchior M" first="Maria" last="Melchior">Maria Melchior</name>
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<name sortKey="Zins, Marie" sort="Zins, Marie" uniqKey="Zins M" first="Marie" last="Zins">Marie Zins</name>
</country>
</tree>
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