O7D.2 Health-related educational differences in duration of working life and loss of paid employment: working life expectancy in the netherlands

Objectives This study aims to provide insight into health-related educational differences in duration of working life by working life expectancy (WLE) and working years lost (WYL) through disability benefits and other non-employment states in the Netherlands. Methods Monthly information on employment status of the Dutch population (n=4,999,947) between 16 and 66 year from 2001 to 2015 was used to estimate working life courses. Across educational groups monthly transitions between paid employment and non-employment states were calculated with a Markov model with transitional probabilities. Usin... Mehr ...

Verfasser: Burdorf, Alex
Robroek, Suzan
Dokumenttyp: Artikel
Erscheinungsdatum: 2019
Reihe/Periodikum: Occupational and Environmental Medicine ; volume 76, issue Suppl 1, page A66.3-A67 ; ISSN 1351-0711 1470-7926
Verlag/Hrsg.: BMJ
Schlagwörter: Public Health / Environmental and Occupational Health
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27217799
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : http://dx.doi.org/10.1136/oem-2019-epi.179

Objectives This study aims to provide insight into health-related educational differences in duration of working life by working life expectancy (WLE) and working years lost (WYL) through disability benefits and other non-employment states in the Netherlands. Methods Monthly information on employment status of the Dutch population (n=4,999,947) between 16 and 66 year from 2001 to 2015 was used to estimate working life courses. Across educational groups monthly transitions between paid employment and non-employment states were calculated with a Markov model with transitional probabilities. Using this multistate model (R-package mstate) the WLE and WYL due to disability benefits and other non-employment states were estimated, stratified by educational groups. Results Despite starting in paid employment much earlier, low educated men and low educated women had a 4.17 (men) and 9.50 (women) years lower WLE at age 16 than high educated men and women. Among low educated men 3.59 WYL were due to disability benefit compared to 0.78 WYL among high educated men, resulting in a WYL gap 2.81 years. Low educated women had 3.47 WYL due to disability benefit compared to 1.38 WYL among high educated women introducing a WYL gap of 2.09. Educational inequalities in premature death added to this WYL gap another 0.7 years among men and 0.3 years among women. Conclusions The working life course showed large educational differences. A considerable amount of the lost working time is health-related due to disability benefits and premature death. In comparison to high educated workers, those with a low educational level lose a substantial part of their working life due to disability benefit, unemployment, and no income. The metrics of WLE and WYL provide useful insights into the life-course perspective of working careers.