A Structural Equation Modeling Approach to Fatigue-related Risk Factors for Occupational Injury
A Structural Equation Modeling Approach to Fatigue-related Risk Factors for Occupational Injury
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DOI：
10.1093/aje/kws219
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发表时间：
2012-10-01
影响因子：
5
通讯作者：
Christiani, David C.
中科院分区：
文献类型：
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作者：
Arlinghaus, Anna;Lombardi, David A.;Christiani, David C.
职业伤害与许多个人和与工作有关的危险因素有关，包括工作时间长和睡眠时间短；然而，造成这种伤害的复杂机制尚未完全了解。作者使用结构方程模型(SEM)作为一种新的方法来研究与疲劳相关的职业伤害的直接和间接潜在危险因素。这项研究的样本包括89,366名来自全国健康访谈调查(6年，20042009)的在职工人，这是一项对美国人口中具有代表性的横断面样本的年度调查。每周工作时间和平时睡眠时间对职业伤害的直接和间接影响采用二元结果的扫描电子显微镜方法和复杂的抽样设计进行建模。同时考察了性别、年龄、种族/民族、职业、行业、薪酬类型、身体质量指数(BMI)和心理困扰的混淆和中介效应。工作时间长和睡眠时间短会单独增加受伤的风险。其他直接危险因素包括性别、职业、薪酬类型和BMI。同时，睡眠时间在长工作时间、高心理压力、高BMI与伤害的不良关系中起中介作用。这些发现表明，扫描电子显微镜是一种有用的方法，用来检验复杂样本中的二分结果和间接影响，并提供了一个全面的新的损伤预测模型。
Occupational injury is associated with numerous individual and work-related risk factors, including long working hours and short sleep duration; however, the complex mechanisms causing such injuries are not yet fully understood. The authors used structural equation modeling (SEM) as a novel approach to examine fatigue-related direct and indirect potential risk factors for occupational injury. The study sample contained 89,366 employed workers from the National Health Interview Survey (pooled across 6 years, 20042009), an annual survey of a representative cross-sectional sample of the US population. Direct and indirect effects of weekly hours worked and usual sleep duration on occupational injuries were modeled using SEM procedures for dichotomous outcomes and a complex sampling design. Confounding and mediating effects of gender, age, race/ethnicity, occupation, industry, type of pay, body mass index (BMI), and psychological distress were simultaneously examined. Long working hours and short sleep duration independently increased the risk of injury. Additional direct risk factors were gender, occupation, type of pay, and BMI. At the same time, sleep duration mediated the adverse relations of long working hours, high psychological distress, and high BMI with injury. These findings indicate that SEM is a useful approach with which to examine dichotomous outcomes and indirect effects in complex samples, and it offers a comprehensive new model of injury prediction.