Predictive factors for disability pension — An 11-year follow up of young persons on sick leave due to neck, shoulder, or back diagnoses

Author:

Borg Karin1,Hensing Gunnel2,Alexanderson Kristina2

Affiliation:

1. Division of Social Medicine and Public Health Science, Department of Health and Environment, Faculty of Health Sciences, S-581 85 Linköping, Sweden,

2. Division of Social Medicine and Public Health Science, Department of Health and Environment, Faculty of Health Sciences, S-581 85 Linköping, Sweden

Abstract

Aims: Although back diagnoses are recurrent and the main diagnoses behind sickness absence and disability pension surprisingly few longitudinal studies have been performed. This study identifies predictive factors for disability pension among young persons initially sick-listed with back diagnoses. Methods: An 11-year prospective cohort study was conducted, including all individuals in a Swedish city who, in 1985, were aged 25-34 and sick-listed ≥ 28 days owing to neck, shoulder, or back diagnoses (n=213). The following data was obtained: disability pension, emigration, and death for 1985-96, sickness absence for 1982-84, and demographics in 1985 regarding sex, income, occupation, marital status, diagnosis, socioeconomic group, and citizenship. Cox regression and life tables were used in the analyses. Results: In 1996, i.e. within 11 years, 22% of the individuals (27% of the women and 14% of the men) had been granted disability pension. The relative risk for disability pension was higher for women (2.4; p=0.010), persons with foreign citizenship (3.6; p=0.009), and those who had had > 14 sick-leave days per spell during the three years before inclusion, compared to those with < 7days/spell (3.1; p = 0.003). Conclusions: This cohort of young persons proved to be a high-risk group for disability pension. Some of the factors known to predict long-time sickness absence also predict disability pension in a cohort of already sick-listed persons.

Publisher

SAGE Publications

Subject

Public Health, Environmental and Occupational Health,General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3