描述工作和残疾假的长期轨迹：职业暴露、健康和个人人口统计学的作用。
Characterizing Long-Term Trajectories of Work and Disability Leave: The Role of Occupational Exposures, Health, and Personal Demographics.
机构信息
Stanford University School of Medicine, Palo Alto, California (Dr Harrati, Ms Meausoone, and Dr Cullen); Princeton University, Princeton, New Jersey (Dr Hepburn).
出版信息
J Occup Environ Med. 2019 Nov;61(11):936-943. doi: 10.1097/JOM.0000000000001705.
OBJECTIVE
This article characterizes trajectories of work and disability leave across the tenure of a cohort of 49,595 employees in a large American manufacturing firm.
METHODS
We employ sequence and cluster analysis to group workers who share similar trajectories of work and disability leave. We then use multinomial logistic regression models to describe the demographic, health, and job-specific correlates of these trajectories.
RESULTS
All workers were clustered into one of eight trajectories. Female workers (RR 1.3 to 2.1), those experiencing musculoskeletal disease (RR 1.3 to 1.5), and those whose jobs entailed exposure to high levels of air pollution (total particulate matter; RR 1.9 to 2.4) were more likely to experience at least one disability episode.
CONCLUSIONS
These trajectories and their correlates provide insight into disability processes and their relationship to demographic characteristics, health, and working conditions of employees.
目的
本文描述了一个大型美国制造公司的 49595 名员工队列的任期内工作和病假的轨迹。
方法
我们采用序列和聚类分析来对具有相似工作和病假轨迹的工人进行分组。然后，我们使用多项逻辑回归模型来描述这些轨迹的人口统计学、健康和工作特定相关因素。
结果
所有工人都被分为八种轨迹之一。女性工人（RR1.3 至 2.1）、患有肌肉骨骼疾病的工人（RR1.3 至 1.5）以及工作中接触高水平空气污染（总颗粒物；RR1.9 至 2.4）的工人更有可能经历至少一次残疾发作。
结论
这些轨迹及其相关因素提供了对残疾过程及其与员工人口统计学特征、健康和工作条件关系的深入了解。
Zotero 插件