Is perception of safety climate a relevant predictor for occupational accidents? Prospective cohort study among blue-collar workers

摘要

OBJECTIVES: The capability of safety climate to predict accidents has been the target of widespread debate in occupational health and safety research. The objective of this prospective cohort study was to employ a shortened five-item safety climate survey to investigate whether safety climate reports in 2012 are predictive for accidents reported within the last 12 months in 2014. METHODS: In both 2012 and 2014, 3864 blue-collar workers answered the Danish Working Environment and Health Cohort Study. Logistic regression was used to study the association [odds ratio (OR)] of reporting a work-related accident (yes/no) with more than one day of sickness absence (outcome) within the last 12 months in 2014 with the number of safety climate problems (predictor). The analyses were cumulatively adjusted for age, gender (model 1), socioeconomic class, occupational group, lifestyle (model 2), and previous accidents in 2012 (model 3). RESULTS: Of the safety climate problems reported in 2012, 1017 (28%) participants reported one problem, 357 (10%) reported two and 614 (17%) reported three or more problems. Using the number of safety climate problems as a continuous variable, all models showed a dose–response relationship between number of safety climate problems in 2012 and at least one accident in 2014 (trend-test, P<0.001). Compared to participants with no safety climate problems, participants reporting two safety climate problems in 2012 had a higher risk for reporting an accident in 2014 [OR 1.84, 95% confidence interval (CI) 1.22–2.77], and the risk was higher for participants reporting three or more safety problems (OR 2.22, 95% CI 1.60–3.09). CONCLUSIONS: A higher number of safety climate problems progressively increased the OR for reporting at least one accident within the last 12 months at the two-year follow-up. The five-item safety climate survey is a simple and important tool that can be used as part of risk assessment in blue-collar workplaces.