Volume 3, Issue 3 (Autumn 2016)                   johe 2016, 3(3): 56-63 | Back to browse issues page

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Heydari M, Gholamnia R, Khani jazani R, kavousi A, Soltanzadeh A. Study The role of latent variables in lost working days by Structural Equation Modeling Approach . johe 2016; 3 (3) :56-63
URL: http://johe.umsha.ac.ir/article-1-215-en.html
1- Shahid Beheshti University of Medical Sciences
2- Shahid Beheshti University of Medical Sciences , gholamnia@sbmu.ac.ir
3- Qom University of Medical Sciences
Abstract:   (9827 Views)

Background: Based on estimations, each year about 250 million work-related injuries and many temporary or permanent disabilities occur which most are preventable. Oil and Gas industries are among industries with high incidence of injuries in the world. The aim of this study has investigated  the role and effect of different risk management variables on lost working days (LWD) in the seismic projects.

Methods: This study was a retrospective, cross-sectional and systematic analysis, which was carried out on occupational accidents between 2008-2015(an 8 years period) in different seismic projects for oilfield exploration at Dana Energy (Iranian Seismic Company). The preliminary sample size of the study were 487accidents. A systems analysis approach were applied by using root case analysis (RCA) and structural equation modeling (SEM). Tools for the data analysis were included, SPSS23 and AMOS23  software.

Results: The mean of lost working days (LWD), was calculated 49.57, the final model of structural equation modeling showed that latent variables of, safety and health training factor(-0.33), risk assessment factor(-0.55) and risk control factor (-0.61) as direct causes significantly affected of lost working days (LWD) in the seismic industries (p< 0.05).

Conclusion: The finding of present study revealed that combination of variables affected in lost working days (LWD). Therefore,the role of these variables in accidents should be investigated and suitable programs should be considered for them.

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Type of Study: Research Article | Subject: Safety

1. Hosseini Kebria SS, Mohammadi Golafshani E, Jozi SA. Predicting the occupational accidents of Tehran Oil Refinery based on HSE using fuzzy logic model. Iran Occup Heal. 2014;11(6).
2. OGP - International Association of Oil & Gas Producers. Safety Performance Indicators - 2013 Data Report No. 2013s. 2014;(2013).
3. Mohammad Fam I, Zokaei HR, Simaei N. Epidemiological evaluation of fatal occupational accidents and estimation of related human costs in Tehran. J Zahedan Univ Med Sci Heal Serv. 2007;8(4):299-307.
4. Threadgold IM. The journey continues: sixty years of sharing incident information in the geophysical industry. In: SPE International Conference on Health, Safety, and Environment. Vol Society of Petroleum Engineers; 2014. Blunch N. Introduction to Structural Equation Modeling Using IBM SPSS Statistics and AMOS. Sage; 2012. [DOI:10.2118/168305-MS] [PMID]
5. Shahriar A, Sadiq R, Tesfamariam S. Risk analysis for oil & gas pipelines: A sustainability assessment approach using fuzzy based bow-tie analysis. J Loss Prev Process Ind. 2012;25(3):505-523. [DOI:10.1016/j.jlp.2011.12.007]
6. Lee J-Y, Chung J-H, Son B. Analysis of traffic accident size for Korean highway using structural equation models. Accid Anal Prev. 2008;40(6):1955-1963. [DOI:10.1016/j.aap.2008.08.006] [PMID]
7. Jakhar SK, Barua MK. An integrated model of supply chain performance evaluation and decision-making using structural equation modelling and fuzzy AHP. Prod Plan Control. 2014;25(11):938-957. [DOI:10.1080/09537287.2013.782616]
8. Wong DB, Lee SG. Modelling the predictors of intention in workplace safety compliance of a multi-ethnic workforce. Saf Sci. 2016;88:155-165. [DOI:10.1016/j.ssci.2016.05.003]
9. Fernández-Mu-iz B, Montes-Peón JM, Vázquez-Ordás CJ. Safety culture: Analysis of the causal relationships between its key dimensions. J Safety Res. 2007;38(6):627-641. [DOI:10.1016/j.jsr.2007.09.001] [PMID]
10. Hong C, Hui Q, Ou W, LONG R. Research on Structural Equation Model of Affecting Factors of Deliberate Violation in Coalmine Fatal Accidents in China. Syst Eng Pract. 2007;27(8):127-136. [DOI:10.1016/S1874-8651(08)60050-2]
11. Mohammadfam I, Soltanzadeh A, Mahmoudi S, Moghimbeigi A. P154 Analytical modelling of occupational accidents' size using structural equation modelling approach (SEM); a field study in big construction industries. Occup Environ Med. 2016;73(Suppl 1):A172-A172. [DOI:10.1136/oemed-2016-103951.471]
12. Mohammadfam I, Soltanzadeh A, Moghimbeigi A, Akbarzadeh M. Modeling of individual and organizational factors affecting traumatic occupational injuries based on the structural equation modeling: a case study in large construction industries. Arch trauma Res. 2016;5(3). [DOI:10.5812/atr.33595] [PMID] [PMCID]
13. Golob TF. Structural equation modeling for travel behavior research. Transp Res Part B Methodol. 2003;37(1):1-25. https://doi.org/10.1016/j.trb.2006.07.001 [DOI:10.1016/S0191-2615(01)00046-7]
14. Choi YS, Chung J-H. Multilevel and multivariate structural equation models for activity participation and travel behavior. J Korean Soc Transp. 2003;21(4):145-154.
15. Hamdar SH, Mahmassani HS, Chen RB. Aggressiveness propensity index for driving behavior at signalized intersections. Accid Anal Prev. 2008;40(1):315-326. [DOI:10.1016/j.aap.2007.06.013] [PMID]
16. Chung J-H, Lee D. Structural model of automobile demand in Korea. Transp Res Rec J Transp Res Board. 2002;(1807):87-91.
17. Leigh JP, Marcin JP, Miller TR. An estimate of the US government's undercount of nonfatal occupational injuries. J Occup Environ Med. 2004;46(1):10-18. [DOI:10.1097/01.jom.0000105909.66435.53] [PMID]
18. Azadeh A, Nouri J, Fam IM. The impacts of macroergonomics on environmental protection and human performance in power plants. 2005.
19. Azadeh A, Fam IM, Garakani MM. A total ergonomic design approach to enhance the productivity in a complicated control system. Inf Technol J. 2007;6(7):1036-1042. [DOI:10.3923/itj.2007.1036.1042]
20. Safety AI of CEC for CP. Guidelines for Chemical Process Quantitative Risk Analysis. Vol 1. Wiley-AIChE; 2000.
21. Aghilinejad M, Kouhpayezade J, Noori MK, Golabadi M. Association of age and work experience with work-related injuries in mining and mineral industries in Iran 2003–2011. Razi J Med Sci. 2013;19(104):20-28.
23. Golmohammadi R, Damyar N, Mohammadfam I, Faradmal J. Evaluation of the relation between noise exposure and occupational stress with unsafe acts and accidents in city bus drivers. Iran Occup Heal. 2014;11(1):70-78.
24. Sarshar S, Haugen S, Skjerve AB. Factors in offshore planning that affect the risk for major accidents. J Loss Prev Process Ind. 2015;33:188-199. [DOI:10.1016/j.jlp.2014.12.005]

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