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Examining the Determinants of Occurrence of Accidents at the Construction Phase in Oil, Gas and Petrochemical Projects: (A Case Study of Assaloyeh)

[ Abbas Zarra Nezhad ] - General Office of Health, Safety and Environment, Ministry of Petroleum, Tehran, Iran
[ Seyed Bagher Mortazavi ] - Department of Environmental and Occupational Health, Faculty of Medicine, Tarbiat Modarres University, Tehran, Iran
[ Hassan Asilian Mahabadi، Ali Khavanin ] - Department of Environmental and Occupational Health, Faculty of Medicine, Tarbiat Modarres University, Tehran, Iran
[ Bahman Babaie Olam، and Ali Asghar Rajabi ] - General Office of Health, Safety and Environment, Ministry of Petroleum, Tehran, Iran

خلاصه مقاله:

In this study, a count-data regression is presented to estimate and analyze the effects of determinant factors affecting the accidents leading to death, through negative binomial regression. For this purpose the structure of 50 accidents that led to death and another 2700 accidents in the Construction Phase in Oil, Gas and Petrochemical Projects (a case study of Assaloyeh)1 during 2003-2005 has been studied. Along with total accidents, unsafe conditions, human errors, management faults and using nonstandard equipments, were considered as the main independent variables affecting the job accidents leading to death, as the dependent variable. By employing the method of developing abstract variables and taking values (codes) one and zero (zero for lack of quality and one for its existence), the variables were quantified. EViews software has been employed, because it provides support for the estimation of several models of count data. The findings of the study show that for each number increase in the unsafe conditions, human errors and either nonstandard equipments or management faults, the expected number of deadly accident increases by a factor of 0.2982 and 0.1137 as well as 0.0259, respectively. If the number of total accidents increases by one unit, the difference in the logs of expected counts would be expected to increase by 0.0025 unit, while holding the other variables in the model constant. Apart from such predictors, the log of the expected count for deadly accidents is 0.0023.

count data regression, negative binomial model, deadly accidents, Assaloyeh