4.6 Article

The relevance of socio-demographic and occupational variables for the assessment of work-related stress risk

Journal

BMC PUBLIC HEALTH
Volume 13, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/1471-2458-13-1157

Keywords

Work-related stress; Risk factors; Italy; Epidemiological survey; Management standards indicator tool

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Background: Work-related stress is widely recognized as one of the major challenges to occupational health and safety. The correlation between work-related stress risk factors and physical health outcomes is widely acknowledged. This study investigated socio-demographic and occupational variables involved in perceived risk of work-related stress. Methods: The Italian version of the Health and Safety Executive Management Standards Indicator Tool was used in a large survey to examine the relationship between work-related stress risks and workers' demographic and occupational characteristics. Out of 8,527 questionnaires distributed among workers (from 75 organizations) 6,378 were returned compiled (74.8%); a set of mixed effects models were adopted to test single and combined effects of the variables on work-related stress risk. Results: Female workers reported lower scores on control and peer support and more negative perceptions of relationships and change at work than male workers, most of them with full-time contracts. Age, job seniority, and educational level appeared positively correlated with control at work, but negatively with job demands. Fixed-term workers had positive perceptions regarding job demands and relationships, but more difficulties about their role at work than permanent workers. A commuting time longer than one hour and shift work appeared to be associated with higher levels of risk factors for work-related stress (except for role), the latter having more negative effects, increasing with age. Conclusions: The findings suggest that the assessment and management of work-related stress risk should consider specific socio-demographic and occupational risk factors such as gender, age, educational level, job status, shift work, commuting time, job contracts.

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