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Employee and job attributes as predictors of absenteeism in a national sample of workers: The importance of health and dangerous working conditions.
Soc Sci Med 1991 Jan; 33(2):127-137
An evaluation was provided which examined the results of research investigations on employee and job characteristics which correlate with absenteeism. The sample of workers was comprised of 1308 employees who worked for at least 20 hours per week. The dependent variable was the number of self reported absences during the past 14 days. Thirty seven independent variables were considered. To assess the statistical and practical significance of possible covariates, Ordinary Least Squares, two limit Tobits, and two part models were used. The results indicated that the variable for mothers with small children ranked as the most important predictor among workers' personal characteristics. Among the health variables, insomnia, being overweight, and hazardous working conditions appeared to be the most important. Inflexible hours were apparently the most important job related variable. A number of frequently discussed predictors including race, unionization, wages and job satisfaction did not prove to be statistically significant. Health variables and hazardous conditions at the job appeared to be among the most important, yet least researched predictors of absenteeism. The author states that single equations, Tobit regressions, and two part models are complimentary research techniques in analyses of absenteeism.
NIOSH-Publication; NIOSH-Grant; Grants-other; Coping-behavior; Attitude; Task-performance; Work-capacity; Industrial-hazards; Worker-health; Workplace-studies; Mental-stress; Job-stress
Economics San Jose State Univ Foundation One Washington Square San Jose, CA 95192-0114
Issue of Publication
Other Occupational Concerns; Grants-other
Social Science and Medicine
San Jose State University, San Jose, California
Page last reviewed: May 5, 2020
Content source: National Institute for Occupational Safety and Health Education and Information Division