Univ Lyon, Université Claude Bernard Lyon1, Ifsttar, UMRESTTE, UMR T_9405, F- 69373, Lyon, France.
Univ Lyon, Université Claude Bernard Lyon1, Ifsttar, UMRESTTE, UMR T_9405, F- 69373, Lyon, France.
Accid Anal Prev. 2019 Oct;131:254-267. doi: 10.1016/j.aap.2019.07.001. Epub 2019 Jul 20.
Several studies of the working conditions of drivers, and in particular on their pace of work, have enabled a better understanding of the risk factors for road accidents that occur during work. However, few studies are available on the risk exposure and working conditions of employees whose occupations involve driving. The purpose of this paper is to identify the different groups of employees occupationally exposed to road risk and to classify them according to working conditions.
A Multiple Correspondence Analysis (MCA) was implemented on the 41,727 individuals from the SUMER 2010 survey (Medical Monitoring of Occupational Risk Exposure: SUrveillance Médicale des Expositions aux Risques professionnels) and for 45 variables about working conditions. The analysis used 5 categories of weekly driving exposure as a supplementary variable (variable which is not used to perform the MCA): Non-exposure; Exposed <2 h; Exposed 2-10 hours; Exposed 10-20 hours; and Exposed >20 h. The results of the MCA were used to construct an ascending hierarchical classification.
The first factorial axis differentiates between conventional and unconventional work schedules. Axis 2 differentiates modalities corresponding to the working hours of the most recent working week. The third axis chiefly contrasts persons who have rules to follow with those who have none. An ascending hierarchical classification distinguishes 10 clusters of individuals according to working conditions. Four clusters of employees were excessively exposed to occupational driving. Clusters also have distinct demographic, occupational and psychosocial characteristics.
Analysis of data from the SUMER survey confirms that employees exposed to road risk are particularly affected by atypical work time characteristics, but can be found in all activity sectors and in all types of job.
多项针对驾驶员工作条件的研究,特别是对其工作节奏的研究,使人们更好地理解了工作期间发生道路事故的风险因素。然而,针对职业驾驶员的风险暴露和工作条件的研究较少。本文的目的是确定职业道路风险暴露的员工的不同群体,并根据工作条件对其进行分类。
对 2010 年 SUMER 调查(职业风险暴露医疗监测:SUrveillance Médicale des Expositions aux Risques professionnels)中的 41727 名个体和 45 个工作条件变量进行了多元对应分析(MCA)。分析使用每周驾驶暴露的 5 个类别作为补充变量(未用于执行 MCA 的变量):非暴露;<2 小时暴露;2-10 小时暴露;10-20 小时暴露;>20 小时暴露。MCA 的结果用于构建升序层次分类。
第一个因子轴区分了常规和非常规工作时间表。轴 2 区分了对应于最近工作周工作时间的模式。第三个轴主要对比了有规则遵循的人和没有规则遵循的人。升序层次分类根据工作条件区分了 10 个人群簇。有四个员工群体职业驾驶暴露过度。群体也具有不同的人口统计学、职业和心理社会特征。
SUMER 调查数据分析证实,职业道路风险暴露的员工特别受到非典型工作时间特征的影响,但可以在所有活动部门和各种类型的工作中找到。