The Effective Factors on the Number of Sick Leave Days on Steel Staffs: An Application of Multilevel Path Analysis Model with Poisson Response

In today's competitive environment, organizations focus on issues that affect cost and productivity, such as absenteeism due to illness (sick leave). According to the importance of this subject, this study done with the aim of study of effective factors on the number of sick leave days. This longitudinal study was conducted on workers of Esfahan’s Mobarakeh Steel Company during 2011- 2015. In this study, was used model multilevel path analysis with Poisson's response and MPLUS software was used to analyze such data. Findings: This study includes 7020 participants with the average age of 38.89 years. The results of the study showed that in within-group level variables of age, education and disease (cardiovascular disease, arthritis and osteopathy disease, indigestion, endocrine and cancer) have direct effect and variables of work experience and Framingham score have indirect effect on the number of sick leave days. In addition in between-group level the possibility of shift work and being a smoker has a direct effect on the number of the sick leave days. The results from the study shows that shift work workers are more exposed to disease that eventually results in an increase in the number of their sick leave days than day workers