International Journal of
Physical Sciences

  • Abbreviation: Int. J. Phys. Sci.
  • Language: English
  • ISSN: 1992-1950
  • DOI: 10.5897/IJPS
  • Start Year: 2006
  • Published Articles: 2569

Full Length Research Paper

Modelling morbidity related absenteeism among workers in University of Ibadan Community, Nigeria: Poisson regression

Apau, G. S., Fagbamigbe, A. F.*, Adebowale, S. A. and Bamgboye, E. A.        
Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria.
Email: [email protected]

  •  Accepted: 28 June 2011
  •  Published: 09 September 2011

Abstract

Globally, sickness absenteeism is a contemporary public health problem, particularly in developing countries. However, very few studies had addressed the theoretical and methodological aspects of health related absenteeism among University workers. A retrospective study of sickness records of 4447 employees of University of Ibadan made available at the University Staff Clinic (Jaja). The health records of each staff for the whole 12 months in 2007 were reviewed. Data analysis was performed using descriptive statistics and Poisson distribution model was used in the data modeling. The prevalence of sick-off leave at the staff clinic was 4.7%. Also, 12.4% of all the staff had been sick at least once during the study period. There was a slight differential in absent rate by sex, age, marital status and years of service. However, differential existed in absent rate among subgroup of workers by different occupational groups and staff category. Majority of the spells lasted for between one and two days. The Poisson regression model showed that staff category and occupational group are the only predictors of days sick-off. Among the dependent variables considered, only sick-off days followed Poisson distribution model. Also, Poisson regression model is adequate to describe and predict the pattern of sickness absenteeism in the study area.

 

Key words: Absenteeism, Poisson, model, morbidity.