710 study was done in a large array of diVerent work settings and only used the quantity question of the QQ method. A measure of productivity loss at work concerning the last workday was used, because a longer time span may be inXuenced by self-reports. A disadvantage of a time-span of 1 day is that it does not take into account the expected Xuc- tuations in productivity loss within workers across work- days. This unknown daily Xuctuation will have contributed to random measurement error and thus attenuated the observed associations. Although participants were informed that all information would be handled completely anony- mous, it also cannot be discarded that some information bias might have occurred, for example due to reluctance among participants to report reduced productivity at work due to fear of negative consequences. Thirdly, a low response may also be associated with the presence of productivity loss at work. The response for the productivity item varied from 9 to 96% across companies. Within each company, it may be possible that workers with productivity loss at work have had less interest in partici- pating in the study. The response level was lower in large companies, in commercial services companies, and among blue-collar workers. However, using a cutoV of 80% response, no signiWcant diVerences were found in produc- tivity loss at work between companies with high and low response levels, and response level was also not statistically signiWcant when included in the univariate analyses. There- fore, we think that this source of selection bias will not have inXuenced the results to a major extent. Finally, we used the RERI as a measure for interactivity on an additive scale. Therefore, we needed to make the assumption that the joint mechanism between lack of job control and decreased work ability follows an additive pat- tern and assumes that the odds ratios could be used as a fair approximation of relative risks. One of the disadvantages of this method is that it handles only two covariates, otherwise data in each stratum become too sparse. Under the assumption of a causal relation between decreased work ability and productivity loss at work, we estimated that only 10% of productivity loss at work was attributable to a decreased work ability. A previous study also reported that 7% of productivity loss at work was attributable to impaired health and that health impairments were strongly related to productivity loss at work than the number of diagnosed diseases (Alavinia et al. 2009). This is not very surprising, given the fact that the measure of pro- ductivity loss at work used in this study estimates all pro- ductivity loss at work, not necessarily health related. There are various reasons for lost productivity which may have nothing to do with health including machine breakdown, personal issues, and organisational problems. However, when workers are asked if their productivity loss is due to impaired health, the percentage of health-related productiv- 123 Int Arch Occup Environ Health (2011) 84:705–712 ity loss at work will be much higher. For instance, in a group of workers with musculoskeletal complaints, 75% of the subjects reported that productivity loss was due to their musculoskeletal disorders (Lötters et al. 2005). Associations between decreased work ability and pro- ductivity loss at work were most inXuenced by the dimen- sions ‘general work ability’, ‘work ability in relation to physical and mental demands’, and ‘self-reported prognosis of work ability’. These dimensions primarily reXect indi- vidual capacities to cope with work demands. Several aspects may explain the importance of these ‘capacity dimensions’. First of all, there are substantial diVerences in recall time among the seven work ability dimensions. For example, the Wrst two dimensions are concerned with the current situation; dimension Wve relates to the past 12 months, dimension six alludes to the coming 2 years, whereas dimension seven refers to the current situation. Second, work ability dimensions are highly interrelated (Pearson correlations ranged from 0.13 to 0.57) and as a consequence only the dimensions with the strongest inXu- ence will be retained in the multivariate analysis. The Wrst two dimensions of the work ability index seem to reXect to some extent a productivity measure. Our Wnding that productivity loss at work was associated with poor work factors corroborates previous studies (Aronsson and Gustafsson 2005; Alavinia et al. 2009; Martimo et al. 2009). A positive association between high workload and productivity loss at work was for example also reported in a Finnish study showing that regular overtime increases sickness presentism (Böckerman and Laukkanen 2010). When work tasks are perceived as highly demanding, a worker may experience problems complying with the work demands and hence perceive his productivity as below par. Perceived health limitations will only further increase the perception that required work output levels are not achieved and therefore result in increased productivity loss at work. In agreement with Alavinia et al. (2009) and Martimo et al. (2009), high physical work demands seemed less important for productivity loss at work than psychosocial work characteristics. DiVerent explanations could be a rea- son for this Wnding. First, job control and the related possi- bility to adjust work activities could act as a buVer in highly physical demanding professions in such a way that a worker with musculoskeletal complaints can eliminate the high physical demanding task for that speciWc day or period. Alternatively, questions concerning psychosocial work fac- tors could be more individual oriented, whereas physical work factors may reXect more objective working conditions. The Wnding could also be due to the cross-sectional design of the study, whereby it is not clear whether the lack of asso- ciation between high physical work demands and productiv- ity loss at work is due to a healthy worker eVect.