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Occupational injuries in Italy: risk factors and long term trend (1951–98)
  1. B Fabiano,
  2. F Currò,
  3. R Pastorino
  1. Chemical and Process Engineering Department “G B Bonino”, University of Genoa, Via Opera Pia 15, 16145 Genoa, Italy
  1. Dr B Fabiano email: brown{at}


OBJECTIVES Trends in the rates of total injuries and fatal accidents in the different sectors of Italian industries were explored during the period 1951–98. Causes and dynamics of injury were also studied for setting priorities for improving safety standards.

METHODS Data on occupational injuries from the National Organisation for Labour Injury Insurance were combined with data from the State Statistics Institute to highlight the interaction between the injury frequency index trend and the production cycle—that is, the evolution of industrial production throughout the years. Multiple regression with log transformed rates was adopted to model the trends of occupational fatalities for each industrial group.

RESULTS The ratios between the linked indices of injury frequency and industrial production showed a good correlation over the whole period. A general decline in injuries was found across all sectors, with values ranging from 79.86% in the energy group to 23.32% in the textile group. In analysing fatalities, the trend seemed to be more clearly decreasing than the trend of total injuries, including temporary and permanent disabilities; the fatalities showed an exponential decrease according to multiple regression, with an annual decline equal to 4.42%.

CONCLUSIONS The overall probability of industrial fatal accidents in Italy tended to decrease exponentially by year. The most effective actions in preventing injuries were directed towards fatal accidents. By analysing the rates of fatal accident in the different sectors, appropriate targets and priorities for increased strategies to prevent injuries can be suggested. The analysis of the dynamics and the material causes of injuries showed that still more consideration should be given to human and organisational factors.

  • labour injuries
  • severity
  • regression model

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