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Original Research

How Different Stressors Affect Quality of Life: An Application of Multilevel Latent Class Analysis on a Large Sample of Industrial Employees

ORCID Icon, , , & ORCID Icon
Pages 1261-1270 | Published online: 20 Aug 2020
 

Abstract

Background

Quality of life (QoL) indicates individual’s perception of the physical, psychological and social aspects of health. The association between QoL and all stressful life events‘ dimensions has not been investigated among industrial employees.

Purpose

The present study aimed to investigate the association between stressful life events and QoL in a large sample of Iranian industrial employees.

Material and Methods

In a cross-sectional study, 3063 manufacturing employees in Isfahan, Iran, were recruited. QoL was measured with the Euro-QoL five dimension questionnaire (EQ-5D). Stressful life events were assessed by an Iranian validated stressful life event questionnaire (SLE). Multilevel latent class regression was employed for classifying participants based on QoL and for determining its association with stressful life events.

Results

Two classes of employees, ie, low (comprised 20% of participants) and high QoL (80%), were identified. From 11 dimensions of stressful life events two major domains, socioeconomic and personal stressor profiles, were identified. Multilevel latent class regression results showed that the higher scores of social (OR: 1.14, 95%CI: 1.12–1.16) and personal (OR: 2.36, 95%CI: 1.87– 2.98) stressor domains were significantly associated with increased risk of being in the poor QoL class. Among personal and socioeconomic stressors, health concerns and daily life dimensions had higher significant association with poor QoL.

Conclusion

Results of our study indicated that life stressors have negative impacts on QoL of employees. Personal stressors showed higher negative impact than socioeconomic on QoL. Managing the stressors can play an effective role in improving the QoL of employees, their physical and mental health, and indirectly enhances the organizational performance and job productivity.

Acknowledgments

This current study is a part of a Biostatistics PhD thesis at the School of Health, Isfahan University of Medical Sciences, with project number 395482. It was supported financially in part by Vice Chancellery for Research and Technology of University of Medical Sciences. The authors would like to express many thanks to all employees of Esfahan Steel Company who collaborated in this research.

Disclosure

The authors report no conflicts of interest in this work.

Additional information

Funding

This study was funded partially by Isfahan University of Medical Sciences (IUMS).