Analysis of factors affecting mental health of automobile manufacturing workers based on structural equation modeling

Abstract

Background

Due to the unique nature of their work, automotive manufacturing workers are prone to mental health issues. However, in China, few studies have explored the interactive mechanisms among factors affecting their mental health.

Objective

This study analyzes the mental health status of workers in the automotive manufacturing industry in Chongqing, China, aiming to provide assistance in improving their mental well-being.

Methods

Using the stratified cluster sampling method, 1296 survey subjects were randomly selected. Data were collected through a questionnaire survey and analyzed using structural equation modeling.

Results

The prevalence of mental health problems was 20.91%. The results of univariate analysis showed that gender, age, marital status, average weekly working hours, and the need to work night shifts had varying degrees of effect on workers’ mental health (P < 0.05). Structural equation modeling showed that occupational health literacy, work-related musculoskeletal disorders (WMSDs), and working time arrangement all had an effect on mental health, with total effects of −0.153, 0.269, and 0.204, respectively, with occupational health literacy having an indirect effect of −0.034 on mental health through WMSDs.

Conclusions

The detection rate of mental health problems among automobile manufacturing workers in Chongqing is high, and the level of occupational health literacy, the occurrence status of WMSDs, and the schedule of working hours are related to the occurrence of mental health problems, with WMSDs having the greatest impact on the mental health of manufacturing workers.