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

• Published in: Risk management and healthcare policy Vol. 13; pp. 1261 - 1270
• Main Authors: Parsaei, Roqayeh, Roohafza, Hamidreza, Feizi, Awat, Sadeghi, Masoumeh, Sarrafzadegan, Nizal
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis Ltd 01.01.2020; Dove; Dove Medical Press
• Subjects: Employees; Latent class analysis; Mental depression; Metabolism; multilevel latent class analysis; Occupational stress; Original Research; Quality of life; Questionnaires; Sample size; Statistical analysis; Stress; stressful life events; Variables; Workforce; multilevel latent class analysis; quality of life; stressful life events
• ISSN: 1179-1594; 1179-1594
• DOI: 10.2147/RMHP.S256800

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