2005; Mackenbach et al. 2008). For productivity loss at work, these factors did not change the associations between educational levels and productivity loss at work. However, the association between sick leave and educational level decreased after adjustment for work-related and lifestyle-related factors. The relation between a poorer general health, on one hand, and productivity loss at work or sick leave, on the other hand, was consistent over the educational groups. Adjusting for health status between educational AZD2014 price groups did not
lead to a reduction in the strength of the association between educational level and productivity loss at work or sick leave. This implies that the higher prevalence of health problems among lower educated
workers is not a major factor in the pathway between educational level and sick leave. In accordance with the study of Laaksonen et al. (2010a), work-related factors and overweight/obesity had the biggest influence on the Selleckchem ARRY-438162 relation between educational level and sick leave. However, in the study of Laaksonen et al. (2010a), VS-4718 nmr strenuous physical work conditions instead of psychosocial work conditions provided the strongest explanation for socioeconomic differences in sickness absence. In contrast with other studies (Alavinia et al. 2009b; Laaksonen et al. 2010b; Lund et al. 2006), we did not find an association between having a physically demanding job and sick leave, nor between lifting heavy loads and sick leave. A possible explanation might be that the proportion of workers with exposure to mechanical load was low in our study population. Although 9 % was exposed to lifting heavy loads in our study, only 3 % answered ‘a lot’ on the question how often they have to lift heavy loads. This ID-8 might indicate that those workers who were classified as having
strenuous work conditions in our study are not that highly exposed to the specific physical work conditions. The evidence from literature indicates that both psychosocial and physical work-related factors may play a role in explaining educational differences in sick leave (Laaksonen et al. 2010a; Melchior et al. 2005; Niedhammer et al. 2008). Therefore, interventions aimed at improving work conditions, especially at postures, job control, and skill discretion, among lower educated employees might reduce educational differences in sick leave. However, a large proportion of the educational differences in sick leave could not be explained by these factors. Other factors, like coping strategy, social support, and motivation to work, were not measured in our study and may be relevant in explaining educational differences in sick leave, but also in productivity loss at work (Rael et al. 1995; Smith et al. 2008). In addition, factors like organizational problems, machine breakdown, or personal issues might particularly influence productivity loss at work.