制造业员工职业伤害影响因素探讨

Analysis on the influencing factors of occupational injuries among manufacturing workers

关键词: 制造业员工  职业伤害  影响因素

Keywords: manufacturing workers  occupational injuries  influencing factors

摘 要: 目的 探讨制造业员工职业伤害的影响因素,为制定职业伤害干预措施提供依据。方法 采用 2022 年欧盟职业安全与健康管理局开展的职业场所职业安全与健康情况调查数据中 2553 名制造业员工相关数据,以职业伤害发生数、发生率及构成比等指标对数据进行描述性分析;采用 χ² 检验对研究对象的年龄、性别、文化程度、工作情况、工种等 20 个变量进行单因素分析,采用多因素 logistic 回归模型分析制造业员工职业伤害的影响因素。结果 共 138 人在过去 1 年发生了职业伤害,发生率 5.4%(138/2553)。性别、年龄、工种、文化程度、雇佣类型、使用移动电子设备、超负荷工作、遭受暴力行为、骚扰或欺凌、组织内部沟通合作不畅、缺乏工作自主性、抑郁或焦虑、肌肉骨骼疾患及过度疲劳等 14 个变量与职业伤害的发生有关联性(P<0.05)。Logistic 回归分析显示,性别、文化程度、使用移动电子设备、遭受暴力行为、组织内部沟通合作不畅、肌肉骨骼疾患、过度疲劳等 7 个因素对职业伤害的影响有统计学意义(P<0.05)。结论 制造业企业应重点关注文化程度低、遭受暴力行为、组织内部沟通合作不畅以及存在肌肉骨骼疾患、过度疲劳感的相关人群。建议通过调整作业安排、提供心理健康咨询及相关培训等措施对员工的职业伤害进行干预。

Abstract: Objective To explore the influencing factors of occupational injuries of manufacturing workers and to provide the basis to formulate interventions of occupational injuries.Methods Data of 2553 manufacturing workers were extracted from the survey on occupational safety and health conditions conducted by the European Agency for Safety and Health at Work in 2022.Descriptive analysis was performed to describe the number,incidence rate,and proportion of occupational injuries.The chi-square test was used to perform univariate analyses of 20 variables included in this study,such as age, gender,degree of education,employment status,and type of work.Logistic regression analysis was used to analyze the influencing factors of occupational injuries of manufacturing workers.Results A total of 138 individuals experienced occupational injuries in the past year,with an incidence rate of 5.6% (138/2553).The happening of occupational injuries was found to be associated with 14 variables (P<0.05),including age,gender,type of work,degree of education,type of employment,usage of mobile electronic devices, overwork,exposure to violence,harassment or bullying,poor internal communication and cooperation,lack of job autonomy,depression or anxiety,musculoskeletal disorder and excessive fatigue.Logistic regression analysis indicated that gender,degree of education, usage of mobile electronic devices, exposure to violence,poor internal communication and cooperation,musculoskeletal disorder and excessive fatigue had statistically significant effects on occupational injuries (all P<0.05). Conclusion Manufacturing enterprises should focus on populations characterized by low degree of education,exposure to violence, poor internal communication and cooperation,musculoskeletal disorder,and excessive fatigue.Interventions including adjustments of work arrangements, providing mental health counseling and relevant training programs should be adopted to prevent occupational injury.