Bayesian network prediction study on the impact of occupational health psychological factors on insomnia among thermal power generation workers
10.3760/cma.j.cn121094-20231114-00114
- VernacularTitle:火力发电职工职业健康心理因素对失眠影响的贝叶斯网络预测研究
- Author:
Fangfang CUI
1
;
Peijia SHENG
;
Jingxuan MA
;
Ting SHI
;
Yongwei WANG
Author Information
1. 四川大学华西公共卫生学院（华西第四医院）职业危害评价科，四川省职业卫生应急（甲级）重点实验室，四川大学华西-协和陈志潜卫生健康研究院卫生应急管理研究中心，成都 610041
- Keywords:
Insomnia;
Sleep disorders;
Occupational health risks;
Bayesian networks;
Thermal power generation
- From:
Chinese Journal of Industrial Hygiene and Occupational Diseases
2024;42(6):447-452
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the risk factors of insomnia among employees in the thermal power generation industry and the network relationships between their interactions, and to provide scientific basis for personalized interventions for high-risk groups with insomnia.Methods:In November 2022, 860 employees of a typical thermal power generation enterprise were selected as the research subjects by cluster sampling. On-site occupational health field surveys and questionnaire surveys were used to collect basic information, occupational characteristics, anxiety, depression, stress, occupational stress, and insomnia. The interaction between insomnia and occupational health psychological factors was evaluated by using structural equation model analysis and Bayesian network construction.Results:The detection rates of anxiety, depression and stress were 34.0% (292/860), 32.1% (276/860) and 18.0% (155/860), respectively. The total score of occupational stress was (445.3±49.9) points, and 160 workers (18.6%) were suspected of insomnia, and 578 workers (67.2%) had insomnia. Structural equation model analysis showed that occupational stress had a significant effect on the occurrence of insomnia in thermal power generation workers (standardized load coefficient was 0.644), and occupational health psychology had a low effect on insomnia (standardized load coefficient was 0.065). However, the Bayesian network model further analysis found that anxiety and stress were the two parent nodes of insomnia, with direct causal relationships, the arc strength was-8.607 and -15.665, respectively. The model prediction results showed that the probability of insomnia occurring was predicted to be 0 in the cases of no stress and anxiety, low stress without anxiety, and no stress with low anxiety. When high stress with low anxiety and low stress with high anxiety occurred, the predicted probability of insomnia occurring were 0.38 and 0.47, respectively. When both high stress and high anxiety occurred simultaneously, the predicted probability of insomnia occurring was 0.51.Conclusion:Bayesian network risk assessment can intuitively reveal and predict the insomnia risk of thermal power generation workers and the network interaction relationship between the risks. Anxiety and stress are the direct causal risks of insomnia, and stress is the main risk of individual insomnia of thermal power generation workers. The occurrence of insomnia can be reduced based on scientific intervention of stress conditions.
