Abstract
[Background]As a pillar industry in China,the manufacturing sector has a high incidence of non-fatal occupational injuries.The factors influencing non-fatal occupational injuries in this industry are closely related at various levels,including individual,equipment,environment,and management,making the analysis of these influ-encing factors complex.
[Objective]To identify influencing factors of non-fatal occupational injuries among manufacturing workers,providing a basis for targeted interventions and surveillance.
[Methods]A total of 2243 frontline workers from cable and shipbuilding enterprises were selected as study subjects to investigate the incidence of non-fatal occupational injuries and collect information at four levels:individual,equipment,management,and environment in past 12 months.Data balancing was performed using resampling,and LASSO regression was used to select factors of non-fatal occupa-tional injuries.The influence degree and type of variables were judged based on the magnitude of the estimated coefficients of each variable,where variables with estimated coefficients＞0 are risk factors,and those＜0 are protective factors.The area under the receiver operating characteristic(ROC)curve(AUC)was used to test the performance of the model,with an AUC value＞0.7 indicating good model performance.
[Results]Among the 2243 frontline workers,males accounted for 77.7%(1742 out of 2243),with the main age range being 40-49 years old,representing 29.5%(661 out of 2243),82.7%of the workers(1854 out of 2243)were married,and 55.6%(1248 out of 2243)had a junior middle school education level.The average monthly income for 51.0%(1144 out of 2243)of the workers was between 5000 and 6999 Chinese Yuan.The incidence of non-fatal occupational injuries among the manufacturing workers was 8.4%(189/2243)in the past 12 months.Among the 22 factors associated with the occurrence of non-fatal occupational injuries(P＜0.05),10 were individual-level fac-tors,including gender,smoking,alcohol consumption,colleague relationships,average exercise duration,job burnout,work fatigue,musculoskeletal disorders,cardiovascular diseases,and neurological and sensory organ diseases;3 were equipment-level factors,including equipment operability,hazardous workpieces,and safety hazards;5 were environmental-level factors,including low temperatures,special operations,noise,workspace size,and dirty and disorderly environment;and 4 were management-level factors,including daily working hours,weekly working days,overtime,and pre-job technical training.The AUC value of the LASSO regression model was 0.704 and the final model retained a total of 10 variables.Among them,there were 7 risk factors for non-fatal occupational injuries(coefficient＞0),including safety hazards,musculoskeletal disorders,dangerous workpieces,job burnout,dirty and disorderly environment,smoking,and male gender;and 3 protective factors(coefficient＜0),including pre-job technical training,good colleague relationship,and long working days per week.
[Conclusion]Manufacturing enterprises need to focus on the incidence of non-fatal occupational injuries and conduct targeted interven-tions for non-fatal occupational injuries by controlling potential safety hazards,providing pre-job technical training,reducing dangerous workpieces,rectifying working environment,and reasonably arranging working hours.关键词
非致命性职业伤害/影响因素/LASSO回归/机器学习/制造业Key words
non-fatal occupational injury/influencing factor/LASSO regression/machine learning/manufacture分类
医药卫生
