Job characteristics, physical and psychological symptoms, and social support as antecedents of sickness absence among men and women in the private industrial sector

Most longitudinal studies on the relationship between psychosocial health resources and risks, and the employees' subsequent sickness absences have been conducted in the public sector. The purpose of this study was to find out psychosocial antecedents of sickness absenteeism in the private industrial sector. The effects of job characteristics (job autonomy and job complexity), physical and psychological symptoms, and social support (from coworkers and supervisors) on sickness absenteeism were investigated. The number of long (4-21 days) and very long (> 21 days) sickness absence episodes of 3895 persons (76% men and 24% women, mean age 44 years) was obtained from the health registers of a multinational forest industry corporation in 1995-1998. A questionnaire survey on the working conditions and health of the workers was carried out in 1996. The follow-up time of the sickness absences was 1-year 9-month. Job autonomy was found to be associated with long and very long episodes in men (rate ratio (RR) in the lowest autonomy group approximately 2 times higher than the highest autonomy group), and with very long episodes of absence in women (2-3 times higher RR between the low vs. the high category). Low job complexity predicted men's very long absences (RR 1.4). Long and very long episodes were associated with physical and psychological symptoms (RR 1.2-1.7) among men and women. Lack of coworkers' support increased the frequency of very long sickness absence among men (RR 1.4), and lack of supervisor's support among women (RR 1.6). Also, some interaction effects of social support variables were observed among both genders. We conclude that the studied psychosocial factors are associated with subsequent sickness absence, and that the associations are partly gender-specific. The results showing which variables are related to employees' sickness absenteeism in the private industrial sector can be applied in human resource management and health service planning. (C) 2003 Elsevier Science Ltd. All rights reserved.