张建江, 王少颖, 陈思萍, 刘建铃. 重型载货运营卡车司机的疲劳状况及影响因素分析[J]. 环境与职业医学. DOI: 10.11836/JEOM23440
引用本文: 张建江, 王少颖, 陈思萍, 刘建铃. 重型载货运营卡车司机的疲劳状况及影响因素分析[J]. 环境与职业医学. DOI: 10.11836/JEOM23440
ZHANG Jianjiang, WANG Shaoying, CHEN Siping, LIU Jianling. Fatigue status and influencing factors of heavy-duty commercial truck drivers[J]. Journal of Environmental and Occupational Medicine. DOI: 10.11836/JEOM23440
Citation: ZHANG Jianjiang, WANG Shaoying, CHEN Siping, LIU Jianling. Fatigue status and influencing factors of heavy-duty commercial truck drivers[J]. Journal of Environmental and Occupational Medicine. DOI: 10.11836/JEOM23440

重型载货运营卡车司机的疲劳状况及影响因素分析

Fatigue status and influencing factors of heavy-duty commercial truck drivers

  • 摘要: 背景

    疲劳驾驶是现代社会公路交通事故的重要诱因,重型载货运营卡车司机疲劳状况引起广泛关注。目前,我国对重型载货运营卡车司机的疲劳状况及其影响因素的研究比较薄弱。

    目的

    分析重型载货运营卡车司机的疲劳状况以及工作时间、失眠和职业倦怠等因素对其疲劳状况的影响。

    方法

    采用整群抽样的方法,于2023年7—8月选取新疆维吾尔自治区W市3个行政区的长途货运物流市场(站)的重型载货运营卡车司机为调查对象进行横断面研究。使用自行设计的问卷调查重型载货运营卡车司机的人口信息学特征和职业特征,并采用中文版《疲劳量表-14》、《阿森斯失眠量表》和《职业倦怠量表》对其疲劳、失眠和职业倦怠状况进行测量。采用Mann-Whitney U检验和Kruskal-Wallis H检验比较组间差异,Spearman相关系数分析各变量之间的相关性,以疲劳状况为应变量进行分层回归,研究各自变量对疲劳状况的影响。

    结果

    有效问卷311份,有效率88.86%(311/350)。调查对象的身体疲劳、脑力疲劳和疲劳总分的中位数和第25、75百分位数MP25P75)分别为3.00(2.00,4.00)、2.00(1.00,3.00)和5.00(4.00,6.00)分。分组比较结果显示,除是否吸烟外,不同年龄、婚姻状况、子女数量、文化程度、从事货运时间、日均工作时间和平均月收入组疲劳总分差异均有统计学意义(P<0.05);无睡眠障碍、可疑失眠和失眠组疲劳总分的差异有统计学意义(P<0.001);无、中度和重度职业倦怠组疲劳总分的差异亦有统计学意义(P<0.001)。失眠状况得分与身体疲劳(rs=0.507)、脑力疲劳(rs=0.547)和疲劳总分(rs=0.618)间均呈正相关(P<0.001)。分层回归分析结果提示,子女数量增加、日均工作时间延长、失眠问题和个人成就感降低维度得分的增加与重型载货运营卡车司机疲劳状况呈正向关联(P<0.05),所建立的重型载货运营卡车司机疲劳状况的多元回归方程为:疲劳总分=7.579+0.581×子女数量+0.916×日均工作时间+0.434×失眠状况得分+0.754×个人成就感降低维度得分。

    结论

    重型载货运营卡车司机的疲劳状况不容乐观,子女数量增加、日均工作时间延长、失眠症状严重和个人成就感降低维度得分增加可能对其疲劳状况具有负面影响。

     

    Abstract: Background

    Fatigue driving is an important cause of road traffic accidents in modern society, and the fatigue condition of heavy-duty commercial truck drivers has attracted widespread attention. Research on the fatigue status and influencing factors of heavy-duty commercial truck drivers in China is relatively rare at present.

    Objective

    To analyze the main characteristics of fatigue among heavy-duty commercial truck drivers and the impacts of factors such as working hours, insomnia, and occupational burnout on their fatigue status.

    Methods

    Using cluster sampling method, a cross-sectional study was conducted from July to August 2023, enrolling heavy-duty commercial truck drivers in long-distance freight logistics markets (stations) located in three administrative regions of W City, Xinjiang Uygur Autonomous Region. A self-designed questionnaire was used to collect demographic and occupational characteristics of heavy-duty commercial truck drivers, and the Chinese versions of Fatigue Scale-14 (FS-14), Athens Insomnia Scale (AIS), and Maslach Burnout Inventory General Survey (MBI-GS) were used to evaluate their fatigue, insomnia, and occupational burnout status, respectively. Mann-Whitney U test and Kruskal-Walls H test were used to compare intergroup differences, and Spearman correlation coefficient was used to analyze the correlation between variables. Hierarchical regression models were used to study the impacts of selected variables on fatigue status.

    Results

    This study obtained 311 valid questionnaires, with a valid recovery rate of 88.86% (311/350). The physical fatigue, mental fatigue, and total fatigue scores of the survey subjects in M (P25, P75) were 3.00 (2.00, 4.00), 2.00 (1.00, 3.00), and 5.00 (4.00, 6.00), respectively. The comparison results showed that, except for smoking, there were statistically significant differences in total fatigue scores between different groups of age, marital status, number of children, educational level, service length of freight transportation, average daily working time, and average monthly income (P<0.05). The difference in total fatigue score among the groups without sleep disorders, with suspected insomnia, and with insomnia was statistically significant (P<0.001). The difference in total fatigue score among the groups without occupational burnout, with moderate occupational burnout, and with severe occupational burnout was also statistically significant (P<0.001). Positive correlations were found between insomnia score and scores of physical fatigue (rs=0.507), mental fatigue (rs=0.547), and total fatigue (rs=0.618) (P<0.001). Hierarchical regression models revealed that having more children, extended daily working hours, insomnia, and increased scores of decreased personal accomplishment were negative factors affecting the fatigue status of heavy-duty commercial truck drivers (P<0.05), and the final regression equation was: total fatigue score=7.579+0.581×number of children+0.916×average daily working time+0.434×score of AIS+0.754×score of reduced personal accomplishment.

    Conclusion

    The fatigue status of heavy-duty commercial truck drivers is not optimistic. An increase in the number of children, extended daily working hours, severe insomnia symptoms, and increased scores of decreased personal accomplishment associate with their worse fatigue status.

     

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