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Development and validation of a risk prediction model for work disability: multicohort study

Airaksinen, J; Jokela, M; Virtanen, M; Oksanen, T; Pentti, J; Vahtera, J; Koskenvuo, M; ... Kivimäki, M; + view all (2017) Development and validation of a risk prediction model for work disability: multicohort study. Scientific Reports , 7 (1) , Article 13578. 10.1038/s41598-017-13892-1. Green open access

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Abstract

Work disability affects quality of life, earnings, and opportunities to contribute to society. Work characteristics, lifestyle and sociodemographic factors have been associated with the risk of work disability, but few multifactorial algorithms exist to identify individuals at risk of future work disability. We developed and validated a parsimonious multifactorial score for the prediction of work disability using individual-level data from 65,775 public-sector employees (development cohort) and 13,527 employed adults from a general population sample (validation cohort), both linked to records of work disability. Candidate predictors for work disability included sociodemographic (3 items), health status and lifestyle (38 items), and work-related (43 items) variables. A parsimonious model, explaining > 99% of the variance of the full model, comprised 8 predictors: age, self-rated health, number of sickness absences in previous year, socioeconomic position, chronic illnesses, sleep problems, body mass index, and smoking. Discriminative ability of a score including these predictors was high: C-index 0.84 in the development and 0.83 in the validation cohort. The corresponding C-indices for a score constructed from work-related predictors (age, sex, socioeconomic position, job strain) were 0.79 and 0.78, respectively. It is possible to identify reliably individuals at high risk of work disability by using a rapidly-administered prediction score.

Type: Article
Title: Development and validation of a risk prediction model for work disability: multicohort study
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41598-017-13892-1
Publisher version: http://dx.doi.org/10.1038/s41598-017-13892-1
Language: English
Additional information: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Epidemiology and Health > Epidemiology and Public Health
URI: http://discovery.ucl.ac.uk/id/eprint/10032642
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