Scharn Micky, van der Beek Allard J, Huisman Martijn, de Wind Astrid, Lindeboom Maarten, Elbers Chris Tm, Geuskens Goedele A, Boot Cécile Rl
VU University Medical Center, Department of Public and Occupational Health, Van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands.
Scand J Work Environ Health. 2017 Jul 1;43(4):326-336. doi: 10.5271/sjweh.3649. Epub 2017 May 30.
Objectives No study so far has combined register-based socioeconomic information with self-reported information on health, demographics, work characteristics, and the social environment. The aim of this study was to investigate whether socioeconomic, health, demographic, work characteristics and social environmental characteristics independently predict working beyond retirement. Methods Questionnaire data from the Study on Transitions in Employment, Ability and Motivation were linked to data from Statistics Netherlands. A prediction model was built consisting of the following blocks: socioeconomic, health, demographic, work characteristics and the social environment. First, univariate analyses were performed (P0<.15), followed by correlations and logistic multivariate regression analyses with backward selection per block (P0<.15). All remaining factors were combined into one final model (P0<.05). Results In the final model, only factors from the blocks health, work and social environmental characteristics remained. Better physical health, being intensively physically active for >2 days/week, higher body height, and working in healthcare predicted working beyond retirement. If respondents had a permanent contract or worked in handcraft, or had a partner that did not like them to work until the official retirement age, they were less likely to work beyond retirement. Conclusion Health, work characteristics and social environment predicted working beyond retirement, but register-based socioeconomic and demographic characteristics did not independently predict working beyond retirement. This study shows that working beyond retirement is multifactorial.
到目前为止,尚无研究将基于登记册的社会经济信息与关于健康、人口统计学、工作特征和社会环境的自我报告信息相结合。本研究的目的是调查社会经济、健康、人口统计学、工作特征和社会环境特征是否能独立预测退休后继续工作。方法:将就业、能力和动机转变研究的问卷数据与荷兰统计局的数据相链接。构建了一个由以下部分组成的预测模型:社会经济、健康、人口统计学、工作特征和社会环境。首先进行单变量分析(P<0.15),随后进行相关性分析以及各部分采用向后选择法的逻辑多元回归分析(P<0.15)。所有剩余因素被合并到一个最终模型中(P<0.05)。结果:在最终模型中,仅保留了健康、工作和社会环境特征部分的因素。身体健康状况较好、每周进行超过2天的高强度体育活动、身高较高以及从事医疗保健工作可预测退休后继续工作。如果受访者有长期合同或从事手工行业工作,或者其伴侣不希望他们工作到法定退休年龄,那么他们退休后继续工作的可能性较小。结论:健康、工作特征和社会环境可预测退休后继续工作,但基于登记册的社会经济和人口统计学特征并不能独立预测退休后继续工作。本研究表明,退休后继续工作是多因素的。