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Abstract

Background

Explanations of social inequalities in sickness absence are lacking in the literature. Our objectives were to evaluate the contribution of various occupational exposures in explaining these inequalities in a national representative sample of employees.

Methods

The study was based on the cross-sectional sample of the SUMER 2010 survey that included 46 962 employees, 26 883 men and 20 079 women. Both sickness absence spells and days within the last 12 months, as health indicators, were studied. Occupation was used as a marker of social position. The study included both psychosocial work factors (variables related to the classical job strain model, psychological demands, decision latitude, social support and understudied variables related to reward, job insecurity, job promotion, esteem, working time/hours and workplace violence) and occupational exposures of chemical, biological, physical and biomechanical nature. Weighted age-adjusted Poisson and negative binomial regression analyses were performed.

Results

Strong occupational differences were found for sickness absence spells and days and for exposure to most work factors. Psychosocial work factors contributed to explain occupational differences in sickness absence spells, and the contributing factors were: decision latitude, social support, reward, shift work and workplace violence. Physical exposure, particularly noise, and biomechanical exposure were also found to be contributing factors. Almost no work factor was found to contribute to occupational differences in sickness absence days.

Conclusion

Preventive measures at the workplace oriented towards low-skilled occupational groups and both psychosocial work factors and other occupational exposures may be beneficial to reduce sickness absence spells and occupational differences in this outcome.

Introduction

Sickness absence is considered as a crucial indicator in the occupational health field because of its human, social and economic costs.1 Sickness absence is a good marker of health status2 and the longer the duration of sickness absence, the stronger the association with health outcomes. This indicator is also an excellent predictor of future health outcomes and mortality.3,4 Specific theories and explanatory models addressing the causes of sickness absence have been presented especially in research in psychology and social science.5 Social inequalities in sickness absence have been reported, and the lower the social position, the higher the risk of sickness absence. This result is in agreement with the social epidemiology literature underlining social inequalities in various health outcomes.6 Nevertheless, the literature is sparse on the factors that may contribute to explain social inequalities in sickness absence.

The causes of sickness absence may be multifactorial and working conditions and occupational exposures may play a role in this outcome. However, only a small number of studies investigated their role in the explanation of social inequalities in sickness absence. As occupational exposures may be associated with sickness absence and are unequally distributed across the working population, they may be considered as potential explanations for social inequalities in sickness absence. Consequently, exploring this topic may be informative to reduce both the occurrence of sickness absence and social inequalities in this outcome.

Studies exploring the role of working conditions in social inequalities in sickness absence showed that physical exposures and/or psychosocial work factors were contributing factors.7–16 The literature appears weak to determine the most contributing group of exposures: some studies suggested that physical exposures had higher contributions than psychosocial work factors,7,10,11 other studies showed similar or higher contributions for psychosocial work factors13,16 and for the other studies, the results were inconclusive mainly because no physical exposure or no psychosocial work factor was studied or because no analysis was performed to evaluate the respective contribution of the various types of exposures. The conclusions may also be difficult to draw regarding the most important contributing factors precisely as the number and content of the exposures differed according to the studies. Furthermore, the studies did not systematically present the contribution of each factor separately, making impossible the identification of the most contributing factors. The available studies often explored working population samples from specific sectors, companies or areas, making the generalization of the results difficult to national working populations. Exceptions were national samples from Denmark, Finland, France and Norway.7,10,13,16 Finally, these studies did not provide the confidence intervals of the contributions of the exposures in social inequalities in sickness absence, making the interpretation of the results difficult in terms of significance of these contributions.

The objectives of the study were to describe social inequalities in sickness absence, and to identify the aspects of working conditions that may contribute to explain these inequalities. We studied both the number of spells and days of sickness absence. We used occupation as a marker of social position, and a large range of occupational exposures of psychosocial, chemical, biological, physical and biomechanical nature.

Methods

The SUMER survey is a national periodical cross-sectional survey from the French ministry of labour, based on a network of occupational physicians, who collect the data for a random sample of employees. Occupational medicine is mandatory for all employees in France. SUMER 2010, the last survey conducted in 2010, included around 50 000 employees interviewed by 2400 occupational physicians. The survey included two questionnaires: a main questionnaire and a self-administered questionnaire. Using their expert evaluation, the occupational physicians filled in the main questionnaire about physical, biological, chemical, biomechanical and organizational exposures for each employee. Employees filled in a self-administered questionnaire about psychosocial work factors and health outcomes. Ethical approval was granted by the French ethics committees. Several articles have already been published by our team using these survey data.17–22

Sickness absence was measured using two items: the number of spells of absence for health-related reasons (excluding work accident or maternity) and the total number of sickness absence days within the last 12 months. These two variables were used as two outcomes.

Psychosocial work factors included the three main dimensions of the job strain model:23 psychological demands, decision latitude, including skill discretion and decision authority, and social support from colleagues and supervisors. The combination of high psychological demands and low decision latitude is called job strain, and the combination of job strain and low social support (isolation) is called iso-strain. Job strain model dimensions were constructed using the validated French version of the questionnaire.24,25 The scores were constructed according to the recommendations by Karasek et al. and dichotomized at the median of the total sample. The dimension of reward of the effort-reward imbalance model, including three subdimensions, esteem, job promotion and job security,26 was measured using the validated French version of this questionnaire.27 Reward and its subdimensions were dichotomized at the median of the total sample. Five working time variables were studied: long working hours, night work, shift work, unsociable work days and predictability of schedules. Three factors were related to workplace violence: physical violence/sexual assault, bullying and verbal abuse, and exposure was defined by at least one situation of workplace violence for each factor. Demands for responsibility were dichotomized at the median of the total sample. More details may be found elsewhere.17–22

Physical exposure was defined by at least 20 h of exposure to noise, thermic constraints, radiations or controlled air/space within the previous week. Biomechanical exposure was defined by at least 20 h of exposure to manual materials handling, postural/articular constraints, vibrations or driving within the previous week. Biological and chemical exposures were defined by at least one biological/chemical exposure within the previous week. The questionnaires and evaluation of all occupational exposures were built using national and European guidelines and a full description may be found elsewhere.28

Occupation was coded using the French national classification of occupations that is close to the International Standard Classification of Occupation (ISCO), and included at the first level of the classification four categories of employees: professionals/managers used as the reference category, associate professionals/technicians, clerks/service workers and blue collar workers. Occupation was used as a marker of social position as it characterizes adult social position, is available for all workers, and may reflect occupational exposures better than education or other markers.29,30

All analyses were performed using weighted data to provide estimates which were nationally representative of the French working population of employees (i.e. 22 millions of employees representing 92% of the total national population of employees in France, excluding the public sector of education and some ministries).21 The differences between occupations for all variables were tested using Rao-Scott Chi-square test. The associations between occupation and sickness absence spells were studied using weighted Poisson regression analysis among the total sample. The associations between occupation and sickness absence days were studied using weighted negative binomial regression analysis among the subsample of those who had at least one absence spell. The contributions of psychosocial work factors and other occupational exposures to occupational inequalities in these two outcomes were calculated for the three occupational groups: associate professionals/technicians, clerks/service workers and blue collar workers in comparison to professionals/managers. The contribution of each work factor (or a set of work factors) to the explanation of the occupational differences was estimated by the Karlson, Holm and Breen (KHB) method.31,32 Positive contributions (%) indicated rate ratio (RR) (respectively mean ratio -MR-) reductions and negative contributions indicated RR (respectively MR) increases. A 95% confidence interval was calculated for each contribution using the Jackknife method to provide the significance of each contribution.

Several models were performed:

  • A first model included only occupation and age as independent variables (model 0).

  • Each psychosocial work factor or occupational exposure was added separately to model 0 (extended model 0).

  • All the psychosocial work factors (models 1–2) and all the occupational exposures (models 3–4) that displayed significant positive contributions for at least one gender or occupational group were added simultaneously to model 0 as independent variables.

Models 1 and 3 included the main dimensions of psychosocial work factors and occupational exposures and models 2 and 4 included their subdimensions.

Additional analyses were performed to disentangle the respective contribution of each factor in models 1–4 using the KHB decomposition method that provides unbiased decompositions in the context of nonlinear probability models.33

The results for the associations between psychosocial work factors and occupational exposures and sickness absence spells and days were derived from extended models 0.

Men and women were analysed separately. All analyses were performed using SAS and STATA.

Results

Of the 53 940 employees asked to participate to the SUMER survey in 2010, 46 962 employees, 26 883 men and 20 079 women, agreed. The response rate was 87%. Almost all psychosocial work factors displayed significant occupational gradients (Additional Supplementary table S1), with a higher prevalence of exposure among low-skilled occupational groups (clerks/service workers and/or blue collar workers). Two psychosocial work factors displayed inverse occupational gradients: high psychological demands and long working hours. Marked occupational gradients were observed for the other occupational exposures. Blue collar workers were more likely to be exposed to physical, biomechanical and chemical exposures and service workers were more likely to be exposed to biological exposures. The prevalence of one absence spell or more and the mean duration of absence days were higher among low-skilled occupations.

Table 1 showed that the prevalence of one absence spell or more was higher for women than for men, and the mean duration of absence days was higher among men than among women. Significant associations were found between occupation and sickness absence spells and days, with the highest RRs (respectively MRs) observed among clerks/service workers and/or blue collar workers.

Table 1

Distribution of sickness absence spells and days and their association with occupation

Men (N = 26 553)Women (N = 19 870)P-value for the comparison between gendersa
Number of sickness absence spells N (%)<0.0001
015786 (59.90)11377 (58.27)
18378 (31.18)5964 (29.51)
21722 (6.27)1685 (8.44)
≥3667 (2.65)844 (3.78)
Association between occupation and absence spells
RR (95% CI) (model 0)b
Associate professionals, technicians1.19 (1.09–1.30)1.14 (1.02–1.28)
Clerks, service workers1.40 (1.28–1.53)1.19 (1.07–1.32)
Blue collar workers1.37 (1.27–1.47)1.18 (1.04–1.33)
Men (N = 7728)Women (N = 6955)
Weighted mean number of sickness absence days (95% CI)17.38 (16.14–18.61)16.54 (15.49–17.60)0.046
Association between occupation and absence days
MR (95% CI) (model 0)b
Associate professionals, technicians1.61 (1.29–1.99)1.54 (1.29–1.84)
Clerks, service workers1.77 (1.37–2.27)1.82 (1.54–2.14)
Blue collar workers2.06 (1.68–2.52)2.13 (1.70–2.66)
Men (N = 26 553)Women (N = 19 870)P-value for the comparison between gendersa
Number of sickness absence spells N (%)<0.0001
015786 (59.90)11377 (58.27)
18378 (31.18)5964 (29.51)
21722 (6.27)1685 (8.44)
≥3667 (2.65)844 (3.78)
Association between occupation and absence spells
RR (95% CI) (model 0)b
Associate professionals, technicians1.19 (1.09–1.30)1.14 (1.02–1.28)
Clerks, service workers1.40 (1.28–1.53)1.19 (1.07–1.32)
Blue collar workers1.37 (1.27–1.47)1.18 (1.04–1.33)
Men (N = 7728)Women (N = 6955)
Weighted mean number of sickness absence days (95% CI)17.38 (16.14–18.61)16.54 (15.49–17.60)0.046
Association between occupation and absence days
MR (95% CI) (model 0)b
Associate professionals, technicians1.61 (1.29–1.99)1.54 (1.29–1.84)
Clerks, service workers1.77 (1.37–2.27)1.82 (1.54–2.14)
Blue collar workers2.06 (1.68–2.52)2.13 (1.70–2.66)

%: weighted %.

a

Rao-Scott chi-square test or weighted negative binomial regression analysis.

b

RR/MR adjusted for age (weighted Poisson or negative binomial regression analysis).

Professionals/managers: reference group.

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Table 1

Distribution of sickness absence spells and days and their association with occupation

Men (N = 26 553)Women (N = 19 870)P-value for the comparison between gendersa
Number of sickness absence spells N (%)<0.0001
015786 (59.90)11377 (58.27)
18378 (31.18)5964 (29.51)
21722 (6.27)1685 (8.44)
≥3667 (2.65)844 (3.78)
Association between occupation and absence spells
RR (95% CI) (model 0)b
Associate professionals, technicians1.19 (1.09–1.30)1.14 (1.02–1.28)
Clerks, service workers1.40 (1.28–1.53)1.19 (1.07–1.32)
Blue collar workers1.37 (1.27–1.47)1.18 (1.04–1.33)
Men (N = 7728)Women (N = 6955)
Weighted mean number of sickness absence days (95% CI)17.38 (16.14–18.61)16.54 (15.49–17.60)0.046
Association between occupation and absence days
MR (95% CI) (model 0)b
Associate professionals, technicians1.61 (1.29–1.99)1.54 (1.29–1.84)
Clerks, service workers1.77 (1.37–2.27)1.82 (1.54–2.14)
Blue collar workers2.06 (1.68–2.52)2.13 (1.70–2.66)
Men (N = 26 553)Women (N = 19 870)P-value for the comparison between gendersa
Number of sickness absence spells N (%)<0.0001
015786 (59.90)11377 (58.27)
18378 (31.18)5964 (29.51)
21722 (6.27)1685 (8.44)
≥3667 (2.65)844 (3.78)
Association between occupation and absence spells
RR (95% CI) (model 0)b
Associate professionals, technicians1.19 (1.09–1.30)1.14 (1.02–1.28)
Clerks, service workers1.40 (1.28–1.53)1.19 (1.07–1.32)
Blue collar workers1.37 (1.27–1.47)1.18 (1.04–1.33)
Men (N = 7728)Women (N = 6955)
Weighted mean number of sickness absence days (95% CI)17.38 (16.14–18.61)16.54 (15.49–17.60)0.046
Association between occupation and absence days
MR (95% CI) (model 0)b
Associate professionals, technicians1.61 (1.29–1.99)1.54 (1.29–1.84)
Clerks, service workers1.77 (1.37–2.27)1.82 (1.54–2.14)
Blue collar workers2.06 (1.68–2.52)2.13 (1.70–2.66)

%: weighted %.

a

Rao-Scott chi-square test or weighted negative binomial regression analysis.

b

RR/MR adjusted for age (weighted Poisson or negative binomial regression analysis).

Professionals/managers: reference group.

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Almost all psychosocial work factors were associated with sickness absence spells (table 2). Physical exposure, noise, controlled air/space and manual materials handling increased the number of absence spells for both genders. Biomechanical exposure and vibrations were also significant among women. Among the psychosocial work factors, only low decision authority, low social support from supervisors, low reward and low esteem increased the number of sickness absence days among men. None of the other occupational exposure was associated with the number of sickness absence days (not showed).

Table 2

Associations between work factors and sickness absence spells: results from weighted Poisson regression analysis

Extended models 0 (each factor separately)MenWomen
RR (95% CI)RR (95% CI)
Low decision latitude1.24 (1.17–1.32)1.26 (1.19–1.34)
Low skill discretion1.19 (1.12–1.26)1.21 (1.14–1.29)
Low decision authority1.20 (1.13–1.27)1.28 (1.19–1.36)
High psychological demands1.27 (1.20–1.35)1.33 (1.26–1.41)
Low social support1.30 (1.23–1.38)1.40 (1.32–1.49)
Low social support (from supervisors)1.32 (1.25–1.40)1.35 (1.28–1.43)
Low social support (from colleagues)1.05 (0.99–1.12)1.24 (1.17–1.32)
Job strain1.37 (1.28–1.47)1.40 (1.32–1.49)
Iso-strain1.41 (1.32–1.52)1.46 (1.37–1.56)
Low reward1.56 (1.47–1.65)1.52 (1.43–1.61)
Low esteem1.50 (1.42–1.59)1.49 (1.41–1.58)
Job insecurity1.39 (1.31–1.47)1.30 (1.23–1.38)
Low job promotion1.45 (1.37–1.53)1.41 (1.33–1.49)
Long working hours0.82 (0.74–0.91)0.88 (0.73–1.06)
Night work1.01 (0.93–1.11)0.98 (0.84–1.14)
Shift work1.13 (1.06–1.21)1.12 (1.04–1.20)
Unsociable work days0.97 (0.91–1.04)1.01 (0.94–1.09)
Low predictability0.94 (0.89–1.00)1.06 (1.00–1.13)
Physical violence1.46 (1.27–1.69)1.25 (1.05–1.50)
Bullying1.53 (1.44–1.63)1.49 (1.41–1.58)
Verbal abuse1.45 (1.37–1.55)1.44 (1.35–1.53)
Demands for responsibility1.00 (0.94–1.06)1.09 (1.03–1.16)
Biological exposure0.95 (0.87–1.03)1.03 (0.97–1.09)
Chemical exposure1.04 (0.98–1.11)1.00 (0.94–1.07)
Physical exposure1.07 (1.00–1.14)1.21 (1.14–1.29)
Noise1.15 (1.08–1.23)1.25 (1.17–1.33)
Thermic constraints0.93 (0.87–1.00)1.11 (0.99–1.24)
Radiations1.06 (0.90–1.23)0.89 (0.73–1.08)
Controlled air/space1.09 (1.01–1.16)1.11 (1.04–1.19)
Biomechanical exposure1.03 (0.97–1.09)1.10 (1.04–1.16)
Manual materials handling1.06 (1.00–1.13)1.07 (1.00–1.14)
Postural/articular constraints1.04 (0.97–1.11)1.06 (0.99–1.15)
Vibrations1.01 (0.93–1.09)1.20 (1.02–1.41)
Driving0.86 (0.81–0.91)0.95 (0.87–1.03)
Extended models 0 (each factor separately)MenWomen
RR (95% CI)RR (95% CI)
Low decision latitude1.24 (1.17–1.32)1.26 (1.19–1.34)
Low skill discretion1.19 (1.12–1.26)1.21 (1.14–1.29)
Low decision authority1.20 (1.13–1.27)1.28 (1.19–1.36)
High psychological demands1.27 (1.20–1.35)1.33 (1.26–1.41)
Low social support1.30 (1.23–1.38)1.40 (1.32–1.49)
Low social support (from supervisors)1.32 (1.25–1.40)1.35 (1.28–1.43)
Low social support (from colleagues)1.05 (0.99–1.12)1.24 (1.17–1.32)
Job strain1.37 (1.28–1.47)1.40 (1.32–1.49)
Iso-strain1.41 (1.32–1.52)1.46 (1.37–1.56)
Low reward1.56 (1.47–1.65)1.52 (1.43–1.61)
Low esteem1.50 (1.42–1.59)1.49 (1.41–1.58)
Job insecurity1.39 (1.31–1.47)1.30 (1.23–1.38)
Low job promotion1.45 (1.37–1.53)1.41 (1.33–1.49)
Long working hours0.82 (0.74–0.91)0.88 (0.73–1.06)
Night work1.01 (0.93–1.11)0.98 (0.84–1.14)
Shift work1.13 (1.06–1.21)1.12 (1.04–1.20)
Unsociable work days0.97 (0.91–1.04)1.01 (0.94–1.09)
Low predictability0.94 (0.89–1.00)1.06 (1.00–1.13)
Physical violence1.46 (1.27–1.69)1.25 (1.05–1.50)
Bullying1.53 (1.44–1.63)1.49 (1.41–1.58)
Verbal abuse1.45 (1.37–1.55)1.44 (1.35–1.53)
Demands for responsibility1.00 (0.94–1.06)1.09 (1.03–1.16)
Biological exposure0.95 (0.87–1.03)1.03 (0.97–1.09)
Chemical exposure1.04 (0.98–1.11)1.00 (0.94–1.07)
Physical exposure1.07 (1.00–1.14)1.21 (1.14–1.29)
Noise1.15 (1.08–1.23)1.25 (1.17–1.33)
Thermic constraints0.93 (0.87–1.00)1.11 (0.99–1.24)
Radiations1.06 (0.90–1.23)0.89 (0.73–1.08)
Controlled air/space1.09 (1.01–1.16)1.11 (1.04–1.19)
Biomechanical exposure1.03 (0.97–1.09)1.10 (1.04–1.16)
Manual materials handling1.06 (1.00–1.13)1.07 (1.00–1.14)
Postural/articular constraints1.04 (0.97–1.11)1.06 (0.99–1.15)
Vibrations1.01 (0.93–1.09)1.20 (1.02–1.41)
Driving0.86 (0.81–0.91)0.95 (0.87–1.03)

RR adjusted for age and occupation.

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Table 2

Associations between work factors and sickness absence spells: results from weighted Poisson regression analysis

Extended models 0 (each factor separately)MenWomen
RR (95% CI)RR (95% CI)
Low decision latitude1.24 (1.17–1.32)1.26 (1.19–1.34)
Low skill discretion1.19 (1.12–1.26)1.21 (1.14–1.29)
Low decision authority1.20 (1.13–1.27)1.28 (1.19–1.36)
High psychological demands1.27 (1.20–1.35)1.33 (1.26–1.41)
Low social support1.30 (1.23–1.38)1.40 (1.32–1.49)
Low social support (from supervisors)1.32 (1.25–1.40)1.35 (1.28–1.43)
Low social support (from colleagues)1.05 (0.99–1.12)1.24 (1.17–1.32)
Job strain1.37 (1.28–1.47)1.40 (1.32–1.49)
Iso-strain1.41 (1.32–1.52)1.46 (1.37–1.56)
Low reward1.56 (1.47–1.65)1.52 (1.43–1.61)
Low esteem1.50 (1.42–1.59)1.49 (1.41–1.58)
Job insecurity1.39 (1.31–1.47)1.30 (1.23–1.38)
Low job promotion1.45 (1.37–1.53)1.41 (1.33–1.49)
Long working hours0.82 (0.74–0.91)0.88 (0.73–1.06)
Night work1.01 (0.93–1.11)0.98 (0.84–1.14)
Shift work1.13 (1.06–1.21)1.12 (1.04–1.20)
Unsociable work days0.97 (0.91–1.04)1.01 (0.94–1.09)
Low predictability0.94 (0.89–1.00)1.06 (1.00–1.13)
Physical violence1.46 (1.27–1.69)1.25 (1.05–1.50)
Bullying1.53 (1.44–1.63)1.49 (1.41–1.58)
Verbal abuse1.45 (1.37–1.55)1.44 (1.35–1.53)
Demands for responsibility1.00 (0.94–1.06)1.09 (1.03–1.16)
Biological exposure0.95 (0.87–1.03)1.03 (0.97–1.09)
Chemical exposure1.04 (0.98–1.11)1.00 (0.94–1.07)
Physical exposure1.07 (1.00–1.14)1.21 (1.14–1.29)
Noise1.15 (1.08–1.23)1.25 (1.17–1.33)
Thermic constraints0.93 (0.87–1.00)1.11 (0.99–1.24)
Radiations1.06 (0.90–1.23)0.89 (0.73–1.08)
Controlled air/space1.09 (1.01–1.16)1.11 (1.04–1.19)
Biomechanical exposure1.03 (0.97–1.09)1.10 (1.04–1.16)
Manual materials handling1.06 (1.00–1.13)1.07 (1.00–1.14)
Postural/articular constraints1.04 (0.97–1.11)1.06 (0.99–1.15)
Vibrations1.01 (0.93–1.09)1.20 (1.02–1.41)
Driving0.86 (0.81–0.91)0.95 (0.87–1.03)
Extended models 0 (each factor separately)MenWomen
RR (95% CI)RR (95% CI)
Low decision latitude1.24 (1.17–1.32)1.26 (1.19–1.34)
Low skill discretion1.19 (1.12–1.26)1.21 (1.14–1.29)
Low decision authority1.20 (1.13–1.27)1.28 (1.19–1.36)
High psychological demands1.27 (1.20–1.35)1.33 (1.26–1.41)
Low social support1.30 (1.23–1.38)1.40 (1.32–1.49)
Low social support (from supervisors)1.32 (1.25–1.40)1.35 (1.28–1.43)
Low social support (from colleagues)1.05 (0.99–1.12)1.24 (1.17–1.32)
Job strain1.37 (1.28–1.47)1.40 (1.32–1.49)
Iso-strain1.41 (1.32–1.52)1.46 (1.37–1.56)
Low reward1.56 (1.47–1.65)1.52 (1.43–1.61)
Low esteem1.50 (1.42–1.59)1.49 (1.41–1.58)
Job insecurity1.39 (1.31–1.47)1.30 (1.23–1.38)
Low job promotion1.45 (1.37–1.53)1.41 (1.33–1.49)
Long working hours0.82 (0.74–0.91)0.88 (0.73–1.06)
Night work1.01 (0.93–1.11)0.98 (0.84–1.14)
Shift work1.13 (1.06–1.21)1.12 (1.04–1.20)
Unsociable work days0.97 (0.91–1.04)1.01 (0.94–1.09)
Low predictability0.94 (0.89–1.00)1.06 (1.00–1.13)
Physical violence1.46 (1.27–1.69)1.25 (1.05–1.50)
Bullying1.53 (1.44–1.63)1.49 (1.41–1.58)
Verbal abuse1.45 (1.37–1.55)1.44 (1.35–1.53)
Demands for responsibility1.00 (0.94–1.06)1.09 (1.03–1.16)
Biological exposure0.95 (0.87–1.03)1.03 (0.97–1.09)
Chemical exposure1.04 (0.98–1.11)1.00 (0.94–1.07)
Physical exposure1.07 (1.00–1.14)1.21 (1.14–1.29)
Noise1.15 (1.08–1.23)1.25 (1.17–1.33)
Thermic constraints0.93 (0.87–1.00)1.11 (0.99–1.24)
Radiations1.06 (0.90–1.23)0.89 (0.73–1.08)
Controlled air/space1.09 (1.01–1.16)1.11 (1.04–1.19)
Biomechanical exposure1.03 (0.97–1.09)1.10 (1.04–1.16)
Manual materials handling1.06 (1.00–1.13)1.07 (1.00–1.14)
Postural/articular constraints1.04 (0.97–1.11)1.06 (0.99–1.15)
Vibrations1.01 (0.93–1.09)1.20 (1.02–1.41)
Driving0.86 (0.81–0.91)0.95 (0.87–1.03)

RR adjusted for age and occupation.

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When each factor/exposure was studied separately (extended models 0), decision latitude and its subdimensions, social support and its subdimensions, job strain, iso-strain, reward and its subdimensions, shift work, and the three variables related to workplace violence displayed significant contributions in the explanation of the association between occupation and sickness absence spells (tables 3 and 4). Some differences were observed between genders and occupational groups. The total contribution of psychosocial work factors (models 1 and 2) was significant for both genders and all occupational groups and ranged 24–48% among men and 47–70% among women. Physical exposure and noise had significant contributions for both genders, and biomechanical exposure had also significant contributions among women only. The total contribution of physical and biomechanical exposures was significant for both genders and all occupational groups and ranged 5–22% among men and 11–48% among women. Long working hours that displayed inverse occupational gradients, protective associations with sickness absence spells (table 1) and positive contributions among men were not included in models 1–2.

Table 3

Contribution (%) of work factors to occupational inequalities in sickness absence spells: results for weighted Poisson regression analysis among men

MenAssociate professionals, techniciansClerks, service workersBlue collar workers
RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)
Model 01.19 (1.09–1.30)1.40 (1.28–1.53)1.37 (1.27–1.47)
Extended models 0 (each factor separately)
Low decision latitude1.14 (1.05–1.25)22.35 (8.75–35.95)1.27 (1.16–1.40)27.51 (16.61–38.41)1.26 (1.17–1.36)25.41 (16.00–34.81)
Low skill discretion1.16 (1.06–1.27)16.00 (4.80–27.20)1.30 (1.18–1.43)21.23 (11.50–30.96)1.29 (1.20–1.39)18.43 (10.34–26.53)
Low decision authority1.16 (1.07–1.27)13.86 (5.52–22.19)1.33 (1.21–1.46)15.43 (8.55–22.30)1.31 (1.21–1.41)15.57 (8.94–22.20)
High psychological demands1.23 (1.12–1.34)−20.87 (−33.63 to − 8.12)1.50 (1.37–1.64)−19.79 (−27.77 to − 11.81)1.47 (1.36–1.58)−22.04 (−29.80 to − 14.27)
Low social support1.17 (1.07–1.28)4.65 (−0.17 to 9.47)1.37 (1.25–1.50)5.19 (1.98–8.40)1.32 (1.22–1.42)6.60 (3.34–9.86)
Low social support (supervisors)1.18 (1.08–1.28)0.62 (−4.05 to 5.28)1.37 (1.26–1.50)2.95 (−0.04 to 5.93)1.34 (1.24–1.44)4.82 (2.07–7.57)
Low social support (colleagues)1.19 (1.09–1.30)0.65 (−0.54 to 1.84)1.40 (1.28–1.54)0.42 (−0.31 to 1.14)1.35 (1.26–1.46)0.57 (−0.36 to 1.51)
Job strain1.16 (1.07–1.27)11.59 (4.15–19.02)1.35 (1.23–1.48)10.63 (6.20–15.05)1.33 (1.24–1.43)8.42 (5.21–11.63)
Iso-strain1.16 (1.07–1.27)9.13 (2.87–15.39)1.35 (1.23–1.48)8.20 (4.54–11.86)1.32 (1.22–1.42)6.77 (3.87–9.68)
Low reward1.15 (1.05–1.25)19.13 (7.74–30.52)1.33 (1.22–1.46)13.58 (7.59–19.57)1.33 (1.24–1.43)8.45 (4.13–12.78)
Low esteem1.16 (1.06–1.27)11.66 (3.23–20.10)1.34 (1.23–1.47)10.71 (5.49–15.93)1.34 (1.24–1.44)6.47 (2.59–10.35)
Job insecurity1.17 (1.07–1.27)12.80 (5.05–20.55)1.36 (1.24–1.49)6.81 (2.91–10.72)1.34 (1.25–1.45)7.32 (4.06–10.58)
Low job promotion1.15 (1.06–1.26)16.91 (6.38–27.44)1.33 (1.21–1.46)13.88 (8.14–19.61)1.34 (1.24–1.44)6.98 (3.24–10.71)
Long working hours1.16 (1.06–1.27)17.26 (5.60–28.92)1.36 (1.24–1.49)11.20 (4.66–17.75)1.33 (1.23–1.43)12.54 (5.67–19.41)
Night work1.17 (1.08–1.28)0.17 (−1.09 to 1.43)1.40 (1.28–1.54)0.27 (−1.72 to 2.27)1.37 (1.27–1.48)0.27 (−1.67 to 2.20)
Shift work1.18 (1.08–1.30)5.94 (1.44–10.43)1.37 (1.25–1.51)7.28 (2.92–11.64)1.35 (1.25–1.45)7.69 (3.09–12.29)
Unsociable work days1.19 (1.09–1.30)−0.18 (−0.73 to 0.36)1.41 (1.28–1.54)−1.44 (−4.92 to 2.04)1.37 (1.27–1.48)−0.36 (−1.22 to 0.51)
Low predictability1.19 (1.09–1.30)0.19 (−0.78 to 1.16)1.42 (1.29–1.55)−0.68 (−1.58 to 0.22)1.38 (1.28–1.49)−0.12 (−0.61 to 0.37)
Physical violence1.17 (1.07–1.28)1.39 (−0.15 to 2.93)1.35 (1.23–1.48)5.57 (2.56–8.58)1.35 (1.26–1.46)0.55 (−0.09 to 1.20)
Bullying1.17 (1.07–1.28)7.64 (1.40–13.88)1.36 (1.24–1.49)7.31 (3.17–11.45)1.35 (1.26–1.46)3.23 (0.48–5.98)
Verbal abuse1.15 (1.05–1.25)16.07 (6.81–25.34)1.29 (1.18–1.41)21.84 (14.10–29.58)1.37 (1.27–1.47)−1.14 (−3.32 to 1.05)
Demands for responsibility1.19 (1.09–1.30)0.03 (−1.10 to 1.17)1.40 (1.28–1.53)−0.02 (−0.78 to 0.73)1.37 (1.27–1.48)0.07 (−2.32 to 2.46)
Model 11.09 (1.00–1.19)43.26 (18.00–68.53)1.19 (1.08–1.32)45.53 (28.05–63.01)1.25 (1.16–1.36)23.97 (12.58–35.36)
Model 21.10 (1.00–1.20)42.17 (17.39–66.96)1.18 (1.07–1.30)47.68 (29.06–66.30)1.25 (1.16–1.36)25.17 (13.46–36.88)
Extended models 0 (each factor separately)
Biological exposure1.19 (1.09–1.30)−2.29 (−6.33 to 1.74)1.42 (1.29–1.55)−3.45 (−9.01 to 2.12)1.38 (1.28–1.48)−1.40 (−3.65 to 0.86)
Chemical exposure1.18 (1.08–1.29)4.39 (−2.35 to 11.13)1.39 (1.27–1.52)2.42 (−1.04 to 5.87)1.34 (1.24–1.44)7.26 (−2.76 to 17.28)
Physical exposure1.17 (1.07–1.28)7.90 (−0.56 to 16.36)1.38 (1.26–1.51)4.74 (0.01–9.46)1.32 (1.21–1.43)12.19 (0.08–24.30)
Noise1.16 (1.06–1.27)13.23 (4.23–22.22)1.37 (1.25–1.50)5.96 (2.62–9.30)1.27 (1.18–1.38)22.42 (10.66–34.18)
Thermic constraints1.20 (1.10–1.31)−5.40 (−11.81 to 1.01)1.42 (1.30–1.56)−4.88 (−9.97 to 0.22)1.41 (1.30–1.52)−8.35 (−16.65 to − 0.05)
Radiations1.19 (1.09–1.30)0.56 (−1.12 to 2.24)1.40 (1.28–1.54)−0.20 (−0.79 to 0.38)1.37 (1.27–1.47)0.43 (−0.75 to 1.60)
Controlled air/space1.20 (1.10–1.31)−5.07 (−10.34 to 0.20)1.42 (1.29–1.55)−3.01 (−5.76 to − 0.25)1.39 (1.29–1.50)−5.37 (−10.18 to − 0.57)
Biomechanical exposure1.19 (1.08–1.30)1.30 (−1.84 to 4.44)1.39 (1.27–1.53)1.27 (−1.60 to 4.14)1.35 (1.26–1.46)3.72 (−4.61 to 12.04)
Manual materials handling1.17 (1.07–1.28)7.16 (-0.85 to 15.17)1.38 (1.25–1.51)4.93 (-0.31 to 10.16)1.32 (1.22–1.43)11.41 (-0.13 to 22.96)
Postural/articular constraints1.18 (1.08–1.29)2.71 (-3.04 to 8.46)1.39 (1.26–1.52)2.82 (-2.96 to 8.60)1.35 (1.25–1.46)4.53 (-4.52 to 13.59)
Vibrations1.19 (1.09–1.30)0.29 (-2.59 to 3.16)1.40 (1.28–1.53)0.13 (-1.20 to 1.46)1.37 (1.27–1.47)0.95 (-8.63 to 10.53)
Driving1.21 (1.10–1.32)−7.96 (−13.56 to − 2.37)1.40 (1.28–1.53)0.34 (−1.18 to 1.86)1.41 (1.31–1.52)−9.77 (−14.20 to − 5.34)
Model 31.17 (1.07–1.28)8.35 (−0.46 to 17.15)1.38 (1.25–1.51)5.28 (0.09–10.47)1.31 (1.21–1.42)13.87 (0.30–27.44)
Model 41.16 (1.06–1.27)13.22 (3.90–22.54)1.37 (1.25–1.50)5.95 (1.89–10.00)1.27 (1.18–1.38)22.39 (9.38–35.41)
MenAssociate professionals, techniciansClerks, service workersBlue collar workers
RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)
Model 01.19 (1.09–1.30)1.40 (1.28–1.53)1.37 (1.27–1.47)
Extended models 0 (each factor separately)
Low decision latitude1.14 (1.05–1.25)22.35 (8.75–35.95)1.27 (1.16–1.40)27.51 (16.61–38.41)1.26 (1.17–1.36)25.41 (16.00–34.81)
Low skill discretion1.16 (1.06–1.27)16.00 (4.80–27.20)1.30 (1.18–1.43)21.23 (11.50–30.96)1.29 (1.20–1.39)18.43 (10.34–26.53)
Low decision authority1.16 (1.07–1.27)13.86 (5.52–22.19)1.33 (1.21–1.46)15.43 (8.55–22.30)1.31 (1.21–1.41)15.57 (8.94–22.20)
High psychological demands1.23 (1.12–1.34)−20.87 (−33.63 to − 8.12)1.50 (1.37–1.64)−19.79 (−27.77 to − 11.81)1.47 (1.36–1.58)−22.04 (−29.80 to − 14.27)
Low social support1.17 (1.07–1.28)4.65 (−0.17 to 9.47)1.37 (1.25–1.50)5.19 (1.98–8.40)1.32 (1.22–1.42)6.60 (3.34–9.86)
Low social support (supervisors)1.18 (1.08–1.28)0.62 (−4.05 to 5.28)1.37 (1.26–1.50)2.95 (−0.04 to 5.93)1.34 (1.24–1.44)4.82 (2.07–7.57)
Low social support (colleagues)1.19 (1.09–1.30)0.65 (−0.54 to 1.84)1.40 (1.28–1.54)0.42 (−0.31 to 1.14)1.35 (1.26–1.46)0.57 (−0.36 to 1.51)
Job strain1.16 (1.07–1.27)11.59 (4.15–19.02)1.35 (1.23–1.48)10.63 (6.20–15.05)1.33 (1.24–1.43)8.42 (5.21–11.63)
Iso-strain1.16 (1.07–1.27)9.13 (2.87–15.39)1.35 (1.23–1.48)8.20 (4.54–11.86)1.32 (1.22–1.42)6.77 (3.87–9.68)
Low reward1.15 (1.05–1.25)19.13 (7.74–30.52)1.33 (1.22–1.46)13.58 (7.59–19.57)1.33 (1.24–1.43)8.45 (4.13–12.78)
Low esteem1.16 (1.06–1.27)11.66 (3.23–20.10)1.34 (1.23–1.47)10.71 (5.49–15.93)1.34 (1.24–1.44)6.47 (2.59–10.35)
Job insecurity1.17 (1.07–1.27)12.80 (5.05–20.55)1.36 (1.24–1.49)6.81 (2.91–10.72)1.34 (1.25–1.45)7.32 (4.06–10.58)
Low job promotion1.15 (1.06–1.26)16.91 (6.38–27.44)1.33 (1.21–1.46)13.88 (8.14–19.61)1.34 (1.24–1.44)6.98 (3.24–10.71)
Long working hours1.16 (1.06–1.27)17.26 (5.60–28.92)1.36 (1.24–1.49)11.20 (4.66–17.75)1.33 (1.23–1.43)12.54 (5.67–19.41)
Night work1.17 (1.08–1.28)0.17 (−1.09 to 1.43)1.40 (1.28–1.54)0.27 (−1.72 to 2.27)1.37 (1.27–1.48)0.27 (−1.67 to 2.20)
Shift work1.18 (1.08–1.30)5.94 (1.44–10.43)1.37 (1.25–1.51)7.28 (2.92–11.64)1.35 (1.25–1.45)7.69 (3.09–12.29)
Unsociable work days1.19 (1.09–1.30)−0.18 (−0.73 to 0.36)1.41 (1.28–1.54)−1.44 (−4.92 to 2.04)1.37 (1.27–1.48)−0.36 (−1.22 to 0.51)
Low predictability1.19 (1.09–1.30)0.19 (−0.78 to 1.16)1.42 (1.29–1.55)−0.68 (−1.58 to 0.22)1.38 (1.28–1.49)−0.12 (−0.61 to 0.37)
Physical violence1.17 (1.07–1.28)1.39 (−0.15 to 2.93)1.35 (1.23–1.48)5.57 (2.56–8.58)1.35 (1.26–1.46)0.55 (−0.09 to 1.20)
Bullying1.17 (1.07–1.28)7.64 (1.40–13.88)1.36 (1.24–1.49)7.31 (3.17–11.45)1.35 (1.26–1.46)3.23 (0.48–5.98)
Verbal abuse1.15 (1.05–1.25)16.07 (6.81–25.34)1.29 (1.18–1.41)21.84 (14.10–29.58)1.37 (1.27–1.47)−1.14 (−3.32 to 1.05)
Demands for responsibility1.19 (1.09–1.30)0.03 (−1.10 to 1.17)1.40 (1.28–1.53)−0.02 (−0.78 to 0.73)1.37 (1.27–1.48)0.07 (−2.32 to 2.46)
Model 11.09 (1.00–1.19)43.26 (18.00–68.53)1.19 (1.08–1.32)45.53 (28.05–63.01)1.25 (1.16–1.36)23.97 (12.58–35.36)
Model 21.10 (1.00–1.20)42.17 (17.39–66.96)1.18 (1.07–1.30)47.68 (29.06–66.30)1.25 (1.16–1.36)25.17 (13.46–36.88)
Extended models 0 (each factor separately)
Biological exposure1.19 (1.09–1.30)−2.29 (−6.33 to 1.74)1.42 (1.29–1.55)−3.45 (−9.01 to 2.12)1.38 (1.28–1.48)−1.40 (−3.65 to 0.86)
Chemical exposure1.18 (1.08–1.29)4.39 (−2.35 to 11.13)1.39 (1.27–1.52)2.42 (−1.04 to 5.87)1.34 (1.24–1.44)7.26 (−2.76 to 17.28)
Physical exposure1.17 (1.07–1.28)7.90 (−0.56 to 16.36)1.38 (1.26–1.51)4.74 (0.01–9.46)1.32 (1.21–1.43)12.19 (0.08–24.30)
Noise1.16 (1.06–1.27)13.23 (4.23–22.22)1.37 (1.25–1.50)5.96 (2.62–9.30)1.27 (1.18–1.38)22.42 (10.66–34.18)
Thermic constraints1.20 (1.10–1.31)−5.40 (−11.81 to 1.01)1.42 (1.30–1.56)−4.88 (−9.97 to 0.22)1.41 (1.30–1.52)−8.35 (−16.65 to − 0.05)
Radiations1.19 (1.09–1.30)0.56 (−1.12 to 2.24)1.40 (1.28–1.54)−0.20 (−0.79 to 0.38)1.37 (1.27–1.47)0.43 (−0.75 to 1.60)
Controlled air/space1.20 (1.10–1.31)−5.07 (−10.34 to 0.20)1.42 (1.29–1.55)−3.01 (−5.76 to − 0.25)1.39 (1.29–1.50)−5.37 (−10.18 to − 0.57)
Biomechanical exposure1.19 (1.08–1.30)1.30 (−1.84 to 4.44)1.39 (1.27–1.53)1.27 (−1.60 to 4.14)1.35 (1.26–1.46)3.72 (−4.61 to 12.04)
Manual materials handling1.17 (1.07–1.28)7.16 (-0.85 to 15.17)1.38 (1.25–1.51)4.93 (-0.31 to 10.16)1.32 (1.22–1.43)11.41 (-0.13 to 22.96)
Postural/articular constraints1.18 (1.08–1.29)2.71 (-3.04 to 8.46)1.39 (1.26–1.52)2.82 (-2.96 to 8.60)1.35 (1.25–1.46)4.53 (-4.52 to 13.59)
Vibrations1.19 (1.09–1.30)0.29 (-2.59 to 3.16)1.40 (1.28–1.53)0.13 (-1.20 to 1.46)1.37 (1.27–1.47)0.95 (-8.63 to 10.53)
Driving1.21 (1.10–1.32)−7.96 (−13.56 to − 2.37)1.40 (1.28–1.53)0.34 (−1.18 to 1.86)1.41 (1.31–1.52)−9.77 (−14.20 to − 5.34)
Model 31.17 (1.07–1.28)8.35 (−0.46 to 17.15)1.38 (1.25–1.51)5.28 (0.09–10.47)1.31 (1.21–1.42)13.87 (0.30–27.44)
Model 41.16 (1.06–1.27)13.22 (3.90–22.54)1.37 (1.25–1.50)5.95 (1.89–10.00)1.27 (1.18–1.38)22.39 (9.38–35.41)

RR adjusted for age. Professionals/managers: reference group.

Model 1: decision latitude + social support + reward + shift work + physical violence + bullying + verbal abuse.

Model 2: skill discretion + decision authority + social support (from supervisors) + social support (from colleagues) + esteem + job insecurity + job promotion + shift work + physical violence + bullying + verbal abuse.

Model 3: physical exposure + biomechanical exposure.

Model 4: noise + biomechanical exposure.

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Table 3

Contribution (%) of work factors to occupational inequalities in sickness absence spells: results for weighted Poisson regression analysis among men

MenAssociate professionals, techniciansClerks, service workersBlue collar workers
RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)
Model 01.19 (1.09–1.30)1.40 (1.28–1.53)1.37 (1.27–1.47)
Extended models 0 (each factor separately)
Low decision latitude1.14 (1.05–1.25)22.35 (8.75–35.95)1.27 (1.16–1.40)27.51 (16.61–38.41)1.26 (1.17–1.36)25.41 (16.00–34.81)
Low skill discretion1.16 (1.06–1.27)16.00 (4.80–27.20)1.30 (1.18–1.43)21.23 (11.50–30.96)1.29 (1.20–1.39)18.43 (10.34–26.53)
Low decision authority1.16 (1.07–1.27)13.86 (5.52–22.19)1.33 (1.21–1.46)15.43 (8.55–22.30)1.31 (1.21–1.41)15.57 (8.94–22.20)
High psychological demands1.23 (1.12–1.34)−20.87 (−33.63 to − 8.12)1.50 (1.37–1.64)−19.79 (−27.77 to − 11.81)1.47 (1.36–1.58)−22.04 (−29.80 to − 14.27)
Low social support1.17 (1.07–1.28)4.65 (−0.17 to 9.47)1.37 (1.25–1.50)5.19 (1.98–8.40)1.32 (1.22–1.42)6.60 (3.34–9.86)
Low social support (supervisors)1.18 (1.08–1.28)0.62 (−4.05 to 5.28)1.37 (1.26–1.50)2.95 (−0.04 to 5.93)1.34 (1.24–1.44)4.82 (2.07–7.57)
Low social support (colleagues)1.19 (1.09–1.30)0.65 (−0.54 to 1.84)1.40 (1.28–1.54)0.42 (−0.31 to 1.14)1.35 (1.26–1.46)0.57 (−0.36 to 1.51)
Job strain1.16 (1.07–1.27)11.59 (4.15–19.02)1.35 (1.23–1.48)10.63 (6.20–15.05)1.33 (1.24–1.43)8.42 (5.21–11.63)
Iso-strain1.16 (1.07–1.27)9.13 (2.87–15.39)1.35 (1.23–1.48)8.20 (4.54–11.86)1.32 (1.22–1.42)6.77 (3.87–9.68)
Low reward1.15 (1.05–1.25)19.13 (7.74–30.52)1.33 (1.22–1.46)13.58 (7.59–19.57)1.33 (1.24–1.43)8.45 (4.13–12.78)
Low esteem1.16 (1.06–1.27)11.66 (3.23–20.10)1.34 (1.23–1.47)10.71 (5.49–15.93)1.34 (1.24–1.44)6.47 (2.59–10.35)
Job insecurity1.17 (1.07–1.27)12.80 (5.05–20.55)1.36 (1.24–1.49)6.81 (2.91–10.72)1.34 (1.25–1.45)7.32 (4.06–10.58)
Low job promotion1.15 (1.06–1.26)16.91 (6.38–27.44)1.33 (1.21–1.46)13.88 (8.14–19.61)1.34 (1.24–1.44)6.98 (3.24–10.71)
Long working hours1.16 (1.06–1.27)17.26 (5.60–28.92)1.36 (1.24–1.49)11.20 (4.66–17.75)1.33 (1.23–1.43)12.54 (5.67–19.41)
Night work1.17 (1.08–1.28)0.17 (−1.09 to 1.43)1.40 (1.28–1.54)0.27 (−1.72 to 2.27)1.37 (1.27–1.48)0.27 (−1.67 to 2.20)
Shift work1.18 (1.08–1.30)5.94 (1.44–10.43)1.37 (1.25–1.51)7.28 (2.92–11.64)1.35 (1.25–1.45)7.69 (3.09–12.29)
Unsociable work days1.19 (1.09–1.30)−0.18 (−0.73 to 0.36)1.41 (1.28–1.54)−1.44 (−4.92 to 2.04)1.37 (1.27–1.48)−0.36 (−1.22 to 0.51)
Low predictability1.19 (1.09–1.30)0.19 (−0.78 to 1.16)1.42 (1.29–1.55)−0.68 (−1.58 to 0.22)1.38 (1.28–1.49)−0.12 (−0.61 to 0.37)
Physical violence1.17 (1.07–1.28)1.39 (−0.15 to 2.93)1.35 (1.23–1.48)5.57 (2.56–8.58)1.35 (1.26–1.46)0.55 (−0.09 to 1.20)
Bullying1.17 (1.07–1.28)7.64 (1.40–13.88)1.36 (1.24–1.49)7.31 (3.17–11.45)1.35 (1.26–1.46)3.23 (0.48–5.98)
Verbal abuse1.15 (1.05–1.25)16.07 (6.81–25.34)1.29 (1.18–1.41)21.84 (14.10–29.58)1.37 (1.27–1.47)−1.14 (−3.32 to 1.05)
Demands for responsibility1.19 (1.09–1.30)0.03 (−1.10 to 1.17)1.40 (1.28–1.53)−0.02 (−0.78 to 0.73)1.37 (1.27–1.48)0.07 (−2.32 to 2.46)
Model 11.09 (1.00–1.19)43.26 (18.00–68.53)1.19 (1.08–1.32)45.53 (28.05–63.01)1.25 (1.16–1.36)23.97 (12.58–35.36)
Model 21.10 (1.00–1.20)42.17 (17.39–66.96)1.18 (1.07–1.30)47.68 (29.06–66.30)1.25 (1.16–1.36)25.17 (13.46–36.88)
Extended models 0 (each factor separately)
Biological exposure1.19 (1.09–1.30)−2.29 (−6.33 to 1.74)1.42 (1.29–1.55)−3.45 (−9.01 to 2.12)1.38 (1.28–1.48)−1.40 (−3.65 to 0.86)
Chemical exposure1.18 (1.08–1.29)4.39 (−2.35 to 11.13)1.39 (1.27–1.52)2.42 (−1.04 to 5.87)1.34 (1.24–1.44)7.26 (−2.76 to 17.28)
Physical exposure1.17 (1.07–1.28)7.90 (−0.56 to 16.36)1.38 (1.26–1.51)4.74 (0.01–9.46)1.32 (1.21–1.43)12.19 (0.08–24.30)
Noise1.16 (1.06–1.27)13.23 (4.23–22.22)1.37 (1.25–1.50)5.96 (2.62–9.30)1.27 (1.18–1.38)22.42 (10.66–34.18)
Thermic constraints1.20 (1.10–1.31)−5.40 (−11.81 to 1.01)1.42 (1.30–1.56)−4.88 (−9.97 to 0.22)1.41 (1.30–1.52)−8.35 (−16.65 to − 0.05)
Radiations1.19 (1.09–1.30)0.56 (−1.12 to 2.24)1.40 (1.28–1.54)−0.20 (−0.79 to 0.38)1.37 (1.27–1.47)0.43 (−0.75 to 1.60)
Controlled air/space1.20 (1.10–1.31)−5.07 (−10.34 to 0.20)1.42 (1.29–1.55)−3.01 (−5.76 to − 0.25)1.39 (1.29–1.50)−5.37 (−10.18 to − 0.57)
Biomechanical exposure1.19 (1.08–1.30)1.30 (−1.84 to 4.44)1.39 (1.27–1.53)1.27 (−1.60 to 4.14)1.35 (1.26–1.46)3.72 (−4.61 to 12.04)
Manual materials handling1.17 (1.07–1.28)7.16 (-0.85 to 15.17)1.38 (1.25–1.51)4.93 (-0.31 to 10.16)1.32 (1.22–1.43)11.41 (-0.13 to 22.96)
Postural/articular constraints1.18 (1.08–1.29)2.71 (-3.04 to 8.46)1.39 (1.26–1.52)2.82 (-2.96 to 8.60)1.35 (1.25–1.46)4.53 (-4.52 to 13.59)
Vibrations1.19 (1.09–1.30)0.29 (-2.59 to 3.16)1.40 (1.28–1.53)0.13 (-1.20 to 1.46)1.37 (1.27–1.47)0.95 (-8.63 to 10.53)
Driving1.21 (1.10–1.32)−7.96 (−13.56 to − 2.37)1.40 (1.28–1.53)0.34 (−1.18 to 1.86)1.41 (1.31–1.52)−9.77 (−14.20 to − 5.34)
Model 31.17 (1.07–1.28)8.35 (−0.46 to 17.15)1.38 (1.25–1.51)5.28 (0.09–10.47)1.31 (1.21–1.42)13.87 (0.30–27.44)
Model 41.16 (1.06–1.27)13.22 (3.90–22.54)1.37 (1.25–1.50)5.95 (1.89–10.00)1.27 (1.18–1.38)22.39 (9.38–35.41)
MenAssociate professionals, techniciansClerks, service workersBlue collar workers
RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)
Model 01.19 (1.09–1.30)1.40 (1.28–1.53)1.37 (1.27–1.47)
Extended models 0 (each factor separately)
Low decision latitude1.14 (1.05–1.25)22.35 (8.75–35.95)1.27 (1.16–1.40)27.51 (16.61–38.41)1.26 (1.17–1.36)25.41 (16.00–34.81)
Low skill discretion1.16 (1.06–1.27)16.00 (4.80–27.20)1.30 (1.18–1.43)21.23 (11.50–30.96)1.29 (1.20–1.39)18.43 (10.34–26.53)
Low decision authority1.16 (1.07–1.27)13.86 (5.52–22.19)1.33 (1.21–1.46)15.43 (8.55–22.30)1.31 (1.21–1.41)15.57 (8.94–22.20)
High psychological demands1.23 (1.12–1.34)−20.87 (−33.63 to − 8.12)1.50 (1.37–1.64)−19.79 (−27.77 to − 11.81)1.47 (1.36–1.58)−22.04 (−29.80 to − 14.27)
Low social support1.17 (1.07–1.28)4.65 (−0.17 to 9.47)1.37 (1.25–1.50)5.19 (1.98–8.40)1.32 (1.22–1.42)6.60 (3.34–9.86)
Low social support (supervisors)1.18 (1.08–1.28)0.62 (−4.05 to 5.28)1.37 (1.26–1.50)2.95 (−0.04 to 5.93)1.34 (1.24–1.44)4.82 (2.07–7.57)
Low social support (colleagues)1.19 (1.09–1.30)0.65 (−0.54 to 1.84)1.40 (1.28–1.54)0.42 (−0.31 to 1.14)1.35 (1.26–1.46)0.57 (−0.36 to 1.51)
Job strain1.16 (1.07–1.27)11.59 (4.15–19.02)1.35 (1.23–1.48)10.63 (6.20–15.05)1.33 (1.24–1.43)8.42 (5.21–11.63)
Iso-strain1.16 (1.07–1.27)9.13 (2.87–15.39)1.35 (1.23–1.48)8.20 (4.54–11.86)1.32 (1.22–1.42)6.77 (3.87–9.68)
Low reward1.15 (1.05–1.25)19.13 (7.74–30.52)1.33 (1.22–1.46)13.58 (7.59–19.57)1.33 (1.24–1.43)8.45 (4.13–12.78)
Low esteem1.16 (1.06–1.27)11.66 (3.23–20.10)1.34 (1.23–1.47)10.71 (5.49–15.93)1.34 (1.24–1.44)6.47 (2.59–10.35)
Job insecurity1.17 (1.07–1.27)12.80 (5.05–20.55)1.36 (1.24–1.49)6.81 (2.91–10.72)1.34 (1.25–1.45)7.32 (4.06–10.58)
Low job promotion1.15 (1.06–1.26)16.91 (6.38–27.44)1.33 (1.21–1.46)13.88 (8.14–19.61)1.34 (1.24–1.44)6.98 (3.24–10.71)
Long working hours1.16 (1.06–1.27)17.26 (5.60–28.92)1.36 (1.24–1.49)11.20 (4.66–17.75)1.33 (1.23–1.43)12.54 (5.67–19.41)
Night work1.17 (1.08–1.28)0.17 (−1.09 to 1.43)1.40 (1.28–1.54)0.27 (−1.72 to 2.27)1.37 (1.27–1.48)0.27 (−1.67 to 2.20)
Shift work1.18 (1.08–1.30)5.94 (1.44–10.43)1.37 (1.25–1.51)7.28 (2.92–11.64)1.35 (1.25–1.45)7.69 (3.09–12.29)
Unsociable work days1.19 (1.09–1.30)−0.18 (−0.73 to 0.36)1.41 (1.28–1.54)−1.44 (−4.92 to 2.04)1.37 (1.27–1.48)−0.36 (−1.22 to 0.51)
Low predictability1.19 (1.09–1.30)0.19 (−0.78 to 1.16)1.42 (1.29–1.55)−0.68 (−1.58 to 0.22)1.38 (1.28–1.49)−0.12 (−0.61 to 0.37)
Physical violence1.17 (1.07–1.28)1.39 (−0.15 to 2.93)1.35 (1.23–1.48)5.57 (2.56–8.58)1.35 (1.26–1.46)0.55 (−0.09 to 1.20)
Bullying1.17 (1.07–1.28)7.64 (1.40–13.88)1.36 (1.24–1.49)7.31 (3.17–11.45)1.35 (1.26–1.46)3.23 (0.48–5.98)
Verbal abuse1.15 (1.05–1.25)16.07 (6.81–25.34)1.29 (1.18–1.41)21.84 (14.10–29.58)1.37 (1.27–1.47)−1.14 (−3.32 to 1.05)
Demands for responsibility1.19 (1.09–1.30)0.03 (−1.10 to 1.17)1.40 (1.28–1.53)−0.02 (−0.78 to 0.73)1.37 (1.27–1.48)0.07 (−2.32 to 2.46)
Model 11.09 (1.00–1.19)43.26 (18.00–68.53)1.19 (1.08–1.32)45.53 (28.05–63.01)1.25 (1.16–1.36)23.97 (12.58–35.36)
Model 21.10 (1.00–1.20)42.17 (17.39–66.96)1.18 (1.07–1.30)47.68 (29.06–66.30)1.25 (1.16–1.36)25.17 (13.46–36.88)
Extended models 0 (each factor separately)
Biological exposure1.19 (1.09–1.30)−2.29 (−6.33 to 1.74)1.42 (1.29–1.55)−3.45 (−9.01 to 2.12)1.38 (1.28–1.48)−1.40 (−3.65 to 0.86)
Chemical exposure1.18 (1.08–1.29)4.39 (−2.35 to 11.13)1.39 (1.27–1.52)2.42 (−1.04 to 5.87)1.34 (1.24–1.44)7.26 (−2.76 to 17.28)
Physical exposure1.17 (1.07–1.28)7.90 (−0.56 to 16.36)1.38 (1.26–1.51)4.74 (0.01–9.46)1.32 (1.21–1.43)12.19 (0.08–24.30)
Noise1.16 (1.06–1.27)13.23 (4.23–22.22)1.37 (1.25–1.50)5.96 (2.62–9.30)1.27 (1.18–1.38)22.42 (10.66–34.18)
Thermic constraints1.20 (1.10–1.31)−5.40 (−11.81 to 1.01)1.42 (1.30–1.56)−4.88 (−9.97 to 0.22)1.41 (1.30–1.52)−8.35 (−16.65 to − 0.05)
Radiations1.19 (1.09–1.30)0.56 (−1.12 to 2.24)1.40 (1.28–1.54)−0.20 (−0.79 to 0.38)1.37 (1.27–1.47)0.43 (−0.75 to 1.60)
Controlled air/space1.20 (1.10–1.31)−5.07 (−10.34 to 0.20)1.42 (1.29–1.55)−3.01 (−5.76 to − 0.25)1.39 (1.29–1.50)−5.37 (−10.18 to − 0.57)
Biomechanical exposure1.19 (1.08–1.30)1.30 (−1.84 to 4.44)1.39 (1.27–1.53)1.27 (−1.60 to 4.14)1.35 (1.26–1.46)3.72 (−4.61 to 12.04)
Manual materials handling1.17 (1.07–1.28)7.16 (-0.85 to 15.17)1.38 (1.25–1.51)4.93 (-0.31 to 10.16)1.32 (1.22–1.43)11.41 (-0.13 to 22.96)
Postural/articular constraints1.18 (1.08–1.29)2.71 (-3.04 to 8.46)1.39 (1.26–1.52)2.82 (-2.96 to 8.60)1.35 (1.25–1.46)4.53 (-4.52 to 13.59)
Vibrations1.19 (1.09–1.30)0.29 (-2.59 to 3.16)1.40 (1.28–1.53)0.13 (-1.20 to 1.46)1.37 (1.27–1.47)0.95 (-8.63 to 10.53)
Driving1.21 (1.10–1.32)−7.96 (−13.56 to − 2.37)1.40 (1.28–1.53)0.34 (−1.18 to 1.86)1.41 (1.31–1.52)−9.77 (−14.20 to − 5.34)
Model 31.17 (1.07–1.28)8.35 (−0.46 to 17.15)1.38 (1.25–1.51)5.28 (0.09–10.47)1.31 (1.21–1.42)13.87 (0.30–27.44)
Model 41.16 (1.06–1.27)13.22 (3.90–22.54)1.37 (1.25–1.50)5.95 (1.89–10.00)1.27 (1.18–1.38)22.39 (9.38–35.41)

RR adjusted for age. Professionals/managers: reference group.

Model 1: decision latitude + social support + reward + shift work + physical violence + bullying + verbal abuse.

Model 2: skill discretion + decision authority + social support (from supervisors) + social support (from colleagues) + esteem + job insecurity + job promotion + shift work + physical violence + bullying + verbal abuse.

Model 3: physical exposure + biomechanical exposure.

Model 4: noise + biomechanical exposure.

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Table 4

Contribution (%) of work factors to occupational inequalities in sickness absence spells: results for weighted Poisson regression analysis among women

WomenAssociate professionals, techniciansClerks, service workersBlue collar workers
RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)
Model 01.14 (1.02–1.28)1.19 (1.07–1.32)1.18 (1.04–1.33)
Extended models 0 (each factor separately)
Low decision latitude1.08 (0.97–1.21)37.70 (5.67–69.72)1.08 (0.97–1.20)56.34 (21.84–90.83)1.04 (0.92–1.18)75.72 (17.96–133.48)
Low skill discretion1.10 (0.98–1.23)28.35 (3.24–53.46)1.10 (0.99–1.22)45.32 (15.07–75.57)1.07 (0.93–1.21)60.61 (9.68–111.54)
Low decision authority1.09 (0.98–1.21)36.45 (7.16–65.74)1.11 (1.00–1.23)43.12 (17.50–68.74)1.08 (0.96–1.23)53.34 (14.23–92.45)
High psychological demands1.19 (1.07–1.33)−31.81 (−59.64 to − 3.98)1.28 (1.15–1.42)−38.25 (−62.15 to − 14.36)1.28 (1.13–1.45)−50.24 (−90.53 to − 9.96)
Low social support1.12 (1.01–1.26)8.64 (−1.51 to 18.80)1.18 (1.06–1.31)7.19 (0.55–13.83)1.14 (1.00–1.29)23.81 (4.95–42.66)
Low social support (supervisors)1.13 (1.02–1.27)8.64 (−0.54 to 17.81)1.19 (1.07–1.32)2.72 (−3.06 to 8.50)1.15 (1.02–1.31)13.78 (1.52–26.05)
Low social support (colleagues)1.13 (1.01–1.26)4.93 (−2.25 to 12.10)1.19 (1.08–1.32)3.73 (−0.92 to 8.38)1.17 (1.03–1.32)11.69 (2.33–21.06)
Job strain1.11 (0.99–1.24)21.22 (3.29–39.15)1.14 (1.03–1.27)24.05 (9.44–38.66)1.13 (1.00–1.28)27.64 (6.54–48.74)
Iso-strain1.11 (0.99–1.25)15.91 (1.33–30.48)1.16 (1.04–1.29)16.70 (5.93–27.47)1.14 (1.00–1.29)24.84 (5.01–44.66)
Low reward1.12 (1.00–1.26)15.85 (−1.97 to 33.67)1.18 (1.06–1.31)8.26 (−1.92 to 18.44)1.17 (1.03–1.33)10.00 (−3.61 to 23.60)
Low esteem1.13 (1.02–1.26)7.48 (−3.37 to 18.34)1.19 (1.08–1.32)1.29 (−6.43 to 9.01)1.17 (1.03–1.32)4.04 (−6.35 to 14.42)
Job insecurity1.13 (1.01–1.27)5.62 (−4.89 to 16.13)1.17 (1.05–1.31)4.04 (−3.37 to 11.45)1.17 (1.03–1.33)6.45 (−3.59 to 16.49)
Low job promotion1.12 (0.99–1.25)22.59 (0.21–44.97)1.17 (1.05–1.30)14.22 (1.57–26.87)1.16 (1.02–1.32)15.53 (−0.29 to 31.35)
Long working hours1.12 (1.00–1.26)9.12 (−7.42 to 25.67)1.17 (1.05–1.30)7.77 (−5.37 to 20.91)1.16 (1.02–1.32)8.12 (−6.44 to 22.68)
Night work1.14 (1.02–1.27)−0.20 (−1.88 to 1.48)1.19 (1.07–1.32)−0.18 (−1.68 to 1.32)1.19 (1.04–1.35)−0.31 (−2.94 to 2.33)
Shift work1.13 (1.01–1.26)9.53 (−0.65 to 19.70)1.17 (1.05–1.30)7.28 (0.63–13.93)1.14 (1.00–1.29)17.94 (−1.03 to 36.90)
Unsociable work days1.14 (1.02–1.28)0.42 (−3.19 to 4.03)1.19 (1.07–1.32)0.47 (−3.57 to 4.51)1.17 (1.04–1.33)0.55 (−4.20 to 5.30)
Low predictability1.14 (1.02–1.28)1.09 (−0.87 to 3.05)1.19 (1.07–1.32)2.28 (−0.61 to 5.16)1.17 (1.03–1.33)2.05 (−0.90 to 5.01)
Physical violence1.14 (1.02–1.28)4.58 (−0.34 to 9.50)1.19 (1.07–1.32)1.09 (−0.15 to 2.34)1.19 (1.04–1.35)0.16 (−0.72 to 1.04)
Bullying1.15 (1.03–1.28)−1.81 (−11.00 to 7.38)1.19 (1.08–1.32)−0.54 (−6.88 to 5.81)1.17 (1.03–1.32)3.11 (−5.58 to 11.80)
Verbal abuse1.12 (1.00–1.26)15.22 (−4.56 to 35.00)1.18 (1.06–1.32)1.94 (−7.24 to 11.13)1.24 (1.08–1.41)−26.62 (−47.21 to − 6.03)
Demands for responsibility1.14 (1.02–1.27)1.69 (−1.28 to 4.67)1.20 (1.08–1.33)−3.25 (−6.41 to − 0.09)1.18 (1.04–1.34)−1.39 (−3.91 to 1.13)
Model 11.07 (0.95–1.20)50.89 (3.44–98.34)1.09 (0.98–1.22)47.00 (13.73–80.27)1.09 (0.95–1.24)53.03 (8.36–97.71)
Model 21.04 (0.93–1.17)67.35 (6.83–127.88)1.05 (0.94–1.18)66.38 (18.93–113.84)1.05 (0.92–1.21)70.25 (10.47–130.02)
Extended models 0 (each factor separately)
Biological exposure1.14 (1.02–1.27)3.63 (−5.48 to 12.74)1.18 (1.07–1.32)3.29 (−4.66 to 11.23)1.17 (1.03–1.33)2.18 (−3.20 to 7.57)
Chemical exposure1.14 (1.02–1.28)0.33 (−6.68 to 7.33)1.19 (1.07–1.32)0.43 (−8.91 to 9.78)1.18 (1.03–1.34)0.84 (−17.29 to 18.97)
Physical exposure1.13 (1.01–1.26)8.92 (−3.01 to 20.85)1.17 (1.05–1.30)9.42 (0.08–18.77)1.10 (0.97–1.26)38.60 (2.70–74.51)
Noise1.12 (1.01–1.26)11.17 (1.06–21.28)1.17 (1.05–1.29)11.52 (3.74–19.30)1.11 (0.97–1.26)36.79 (6.17–67.42)
Thermic constraints1.14 (1.02–1.28)−0.35 (−4.03 to 3.34)1.19 (1.07–1.32)1.53 (−2.76 to 5.82)1.15 (1.01–1.32)11.26 (−7.06 to 29.58)
Radiations1.15 (1.02–1.28)−1.60 (−4.77 to 1.58)1.19 (1.07–1.32)0.20 (−0.35 to 0.74)1.18 (1.04–1.34)0.00 (−0.58 to 0.58)
Controlled air/space1.15 (1.03–1.29)−6.02 (−12.69 to 0.65)1.21 (1.09–1.34)−7.74 (−14.41 to − 1.07)1.20 (1.05–1.36)−9.06 (−18.12 to 0.01)
Biomechanical exposure1.14 (1.02–1.27)3.55 (−0.39 to 7.49)1.18 (1.06–1.30)7.85 (1.34–14.36)1.15 (1.01–1.30)14.34 (0.61–28.08)
Manual materials handling1.13 (1.01–1.26)8.10 (−2.08 to 18.29)1.17 (1.05–1.30)9.80 (−1.48 to 21.08)1.14 (1.01–1.30)16.84 (−4.46 to 38.14)
Postural/articular constraints1.14 (1.02–1.27)3.90 (−2.18 to 9.97)1.18 (1.06–1.31)7.89 (−3.23 to 19.01)1.15 (1.01–1.31)13.87 (−6.52 to 34.26)
Vibrations1.14 (1.02–1.28)0.17 (−0.49 to 0.83)1.19 (1.07–1.32)0.91 (−0.25 to 2.06)1.16 (1.02–1.32)8.64 (−2.12 to 19.40)
Driving1.14 (1.02–1.28)0.06 (−1.07 to 1.19)1.19 (1.07–1.32)2.38 (−1.70 to 6.47)1.17 (1.03–1.33)1.50 (−1.32 to 4.33)
Model 31.12 (1.00–1.26)11.33 (−1.66 to 24.32)1.16 (1.04–1.29)15.24 (3.05–27.43)1.09 (0.95–1.24)48.40 (5.64–91.16)
Model 41.12 (1.00–1.25)13.49 (1.61–25.36)1.15 (1.04–1.28)17.21 (5.79–28.63)1.09 (0.96–1.24)46.73 (8.31–85.16)
WomenAssociate professionals, techniciansClerks, service workersBlue collar workers
RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)
Model 01.14 (1.02–1.28)1.19 (1.07–1.32)1.18 (1.04–1.33)
Extended models 0 (each factor separately)
Low decision latitude1.08 (0.97–1.21)37.70 (5.67–69.72)1.08 (0.97–1.20)56.34 (21.84–90.83)1.04 (0.92–1.18)75.72 (17.96–133.48)
Low skill discretion1.10 (0.98–1.23)28.35 (3.24–53.46)1.10 (0.99–1.22)45.32 (15.07–75.57)1.07 (0.93–1.21)60.61 (9.68–111.54)
Low decision authority1.09 (0.98–1.21)36.45 (7.16–65.74)1.11 (1.00–1.23)43.12 (17.50–68.74)1.08 (0.96–1.23)53.34 (14.23–92.45)
High psychological demands1.19 (1.07–1.33)−31.81 (−59.64 to − 3.98)1.28 (1.15–1.42)−38.25 (−62.15 to − 14.36)1.28 (1.13–1.45)−50.24 (−90.53 to − 9.96)
Low social support1.12 (1.01–1.26)8.64 (−1.51 to 18.80)1.18 (1.06–1.31)7.19 (0.55–13.83)1.14 (1.00–1.29)23.81 (4.95–42.66)
Low social support (supervisors)1.13 (1.02–1.27)8.64 (−0.54 to 17.81)1.19 (1.07–1.32)2.72 (−3.06 to 8.50)1.15 (1.02–1.31)13.78 (1.52–26.05)
Low social support (colleagues)1.13 (1.01–1.26)4.93 (−2.25 to 12.10)1.19 (1.08–1.32)3.73 (−0.92 to 8.38)1.17 (1.03–1.32)11.69 (2.33–21.06)
Job strain1.11 (0.99–1.24)21.22 (3.29–39.15)1.14 (1.03–1.27)24.05 (9.44–38.66)1.13 (1.00–1.28)27.64 (6.54–48.74)
Iso-strain1.11 (0.99–1.25)15.91 (1.33–30.48)1.16 (1.04–1.29)16.70 (5.93–27.47)1.14 (1.00–1.29)24.84 (5.01–44.66)
Low reward1.12 (1.00–1.26)15.85 (−1.97 to 33.67)1.18 (1.06–1.31)8.26 (−1.92 to 18.44)1.17 (1.03–1.33)10.00 (−3.61 to 23.60)
Low esteem1.13 (1.02–1.26)7.48 (−3.37 to 18.34)1.19 (1.08–1.32)1.29 (−6.43 to 9.01)1.17 (1.03–1.32)4.04 (−6.35 to 14.42)
Job insecurity1.13 (1.01–1.27)5.62 (−4.89 to 16.13)1.17 (1.05–1.31)4.04 (−3.37 to 11.45)1.17 (1.03–1.33)6.45 (−3.59 to 16.49)
Low job promotion1.12 (0.99–1.25)22.59 (0.21–44.97)1.17 (1.05–1.30)14.22 (1.57–26.87)1.16 (1.02–1.32)15.53 (−0.29 to 31.35)
Long working hours1.12 (1.00–1.26)9.12 (−7.42 to 25.67)1.17 (1.05–1.30)7.77 (−5.37 to 20.91)1.16 (1.02–1.32)8.12 (−6.44 to 22.68)
Night work1.14 (1.02–1.27)−0.20 (−1.88 to 1.48)1.19 (1.07–1.32)−0.18 (−1.68 to 1.32)1.19 (1.04–1.35)−0.31 (−2.94 to 2.33)
Shift work1.13 (1.01–1.26)9.53 (−0.65 to 19.70)1.17 (1.05–1.30)7.28 (0.63–13.93)1.14 (1.00–1.29)17.94 (−1.03 to 36.90)
Unsociable work days1.14 (1.02–1.28)0.42 (−3.19 to 4.03)1.19 (1.07–1.32)0.47 (−3.57 to 4.51)1.17 (1.04–1.33)0.55 (−4.20 to 5.30)
Low predictability1.14 (1.02–1.28)1.09 (−0.87 to 3.05)1.19 (1.07–1.32)2.28 (−0.61 to 5.16)1.17 (1.03–1.33)2.05 (−0.90 to 5.01)
Physical violence1.14 (1.02–1.28)4.58 (−0.34 to 9.50)1.19 (1.07–1.32)1.09 (−0.15 to 2.34)1.19 (1.04–1.35)0.16 (−0.72 to 1.04)
Bullying1.15 (1.03–1.28)−1.81 (−11.00 to 7.38)1.19 (1.08–1.32)−0.54 (−6.88 to 5.81)1.17 (1.03–1.32)3.11 (−5.58 to 11.80)
Verbal abuse1.12 (1.00–1.26)15.22 (−4.56 to 35.00)1.18 (1.06–1.32)1.94 (−7.24 to 11.13)1.24 (1.08–1.41)−26.62 (−47.21 to − 6.03)
Demands for responsibility1.14 (1.02–1.27)1.69 (−1.28 to 4.67)1.20 (1.08–1.33)−3.25 (−6.41 to − 0.09)1.18 (1.04–1.34)−1.39 (−3.91 to 1.13)
Model 11.07 (0.95–1.20)50.89 (3.44–98.34)1.09 (0.98–1.22)47.00 (13.73–80.27)1.09 (0.95–1.24)53.03 (8.36–97.71)
Model 21.04 (0.93–1.17)67.35 (6.83–127.88)1.05 (0.94–1.18)66.38 (18.93–113.84)1.05 (0.92–1.21)70.25 (10.47–130.02)
Extended models 0 (each factor separately)
Biological exposure1.14 (1.02–1.27)3.63 (−5.48 to 12.74)1.18 (1.07–1.32)3.29 (−4.66 to 11.23)1.17 (1.03–1.33)2.18 (−3.20 to 7.57)
Chemical exposure1.14 (1.02–1.28)0.33 (−6.68 to 7.33)1.19 (1.07–1.32)0.43 (−8.91 to 9.78)1.18 (1.03–1.34)0.84 (−17.29 to 18.97)
Physical exposure1.13 (1.01–1.26)8.92 (−3.01 to 20.85)1.17 (1.05–1.30)9.42 (0.08–18.77)1.10 (0.97–1.26)38.60 (2.70–74.51)
Noise1.12 (1.01–1.26)11.17 (1.06–21.28)1.17 (1.05–1.29)11.52 (3.74–19.30)1.11 (0.97–1.26)36.79 (6.17–67.42)
Thermic constraints1.14 (1.02–1.28)−0.35 (−4.03 to 3.34)1.19 (1.07–1.32)1.53 (−2.76 to 5.82)1.15 (1.01–1.32)11.26 (−7.06 to 29.58)
Radiations1.15 (1.02–1.28)−1.60 (−4.77 to 1.58)1.19 (1.07–1.32)0.20 (−0.35 to 0.74)1.18 (1.04–1.34)0.00 (−0.58 to 0.58)
Controlled air/space1.15 (1.03–1.29)−6.02 (−12.69 to 0.65)1.21 (1.09–1.34)−7.74 (−14.41 to − 1.07)1.20 (1.05–1.36)−9.06 (−18.12 to 0.01)
Biomechanical exposure1.14 (1.02–1.27)3.55 (−0.39 to 7.49)1.18 (1.06–1.30)7.85 (1.34–14.36)1.15 (1.01–1.30)14.34 (0.61–28.08)
Manual materials handling1.13 (1.01–1.26)8.10 (−2.08 to 18.29)1.17 (1.05–1.30)9.80 (−1.48 to 21.08)1.14 (1.01–1.30)16.84 (−4.46 to 38.14)
Postural/articular constraints1.14 (1.02–1.27)3.90 (−2.18 to 9.97)1.18 (1.06–1.31)7.89 (−3.23 to 19.01)1.15 (1.01–1.31)13.87 (−6.52 to 34.26)
Vibrations1.14 (1.02–1.28)0.17 (−0.49 to 0.83)1.19 (1.07–1.32)0.91 (−0.25 to 2.06)1.16 (1.02–1.32)8.64 (−2.12 to 19.40)
Driving1.14 (1.02–1.28)0.06 (−1.07 to 1.19)1.19 (1.07–1.32)2.38 (−1.70 to 6.47)1.17 (1.03–1.33)1.50 (−1.32 to 4.33)
Model 31.12 (1.00–1.26)11.33 (−1.66 to 24.32)1.16 (1.04–1.29)15.24 (3.05–27.43)1.09 (0.95–1.24)48.40 (5.64–91.16)
Model 41.12 (1.00–1.25)13.49 (1.61–25.36)1.15 (1.04–1.28)17.21 (5.79–28.63)1.09 (0.96–1.24)46.73 (8.31–85.16)

RR adjusted for age. Professionals/managers: reference group.

Model 1: decision latitude + social support + reward + shift work + physical violence + bullying + verbal abuse.

Model 2: skill discretion + decision authority + social support (from supervisors) + social support (from colleagues) + esteem + job insecurity + job promotion + shift work + physical violence + bullying + verbal abuse.

Model 3: physical exposure + biomechanical exposure.

Model 4: noise + biomechanical exposure.

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Table 4

Contribution (%) of work factors to occupational inequalities in sickness absence spells: results for weighted Poisson regression analysis among women

WomenAssociate professionals, techniciansClerks, service workersBlue collar workers
RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)
Model 01.14 (1.02–1.28)1.19 (1.07–1.32)1.18 (1.04–1.33)
Extended models 0 (each factor separately)
Low decision latitude1.08 (0.97–1.21)37.70 (5.67–69.72)1.08 (0.97–1.20)56.34 (21.84–90.83)1.04 (0.92–1.18)75.72 (17.96–133.48)
Low skill discretion1.10 (0.98–1.23)28.35 (3.24–53.46)1.10 (0.99–1.22)45.32 (15.07–75.57)1.07 (0.93–1.21)60.61 (9.68–111.54)
Low decision authority1.09 (0.98–1.21)36.45 (7.16–65.74)1.11 (1.00–1.23)43.12 (17.50–68.74)1.08 (0.96–1.23)53.34 (14.23–92.45)
High psychological demands1.19 (1.07–1.33)−31.81 (−59.64 to − 3.98)1.28 (1.15–1.42)−38.25 (−62.15 to − 14.36)1.28 (1.13–1.45)−50.24 (−90.53 to − 9.96)
Low social support1.12 (1.01–1.26)8.64 (−1.51 to 18.80)1.18 (1.06–1.31)7.19 (0.55–13.83)1.14 (1.00–1.29)23.81 (4.95–42.66)
Low social support (supervisors)1.13 (1.02–1.27)8.64 (−0.54 to 17.81)1.19 (1.07–1.32)2.72 (−3.06 to 8.50)1.15 (1.02–1.31)13.78 (1.52–26.05)
Low social support (colleagues)1.13 (1.01–1.26)4.93 (−2.25 to 12.10)1.19 (1.08–1.32)3.73 (−0.92 to 8.38)1.17 (1.03–1.32)11.69 (2.33–21.06)
Job strain1.11 (0.99–1.24)21.22 (3.29–39.15)1.14 (1.03–1.27)24.05 (9.44–38.66)1.13 (1.00–1.28)27.64 (6.54–48.74)
Iso-strain1.11 (0.99–1.25)15.91 (1.33–30.48)1.16 (1.04–1.29)16.70 (5.93–27.47)1.14 (1.00–1.29)24.84 (5.01–44.66)
Low reward1.12 (1.00–1.26)15.85 (−1.97 to 33.67)1.18 (1.06–1.31)8.26 (−1.92 to 18.44)1.17 (1.03–1.33)10.00 (−3.61 to 23.60)
Low esteem1.13 (1.02–1.26)7.48 (−3.37 to 18.34)1.19 (1.08–1.32)1.29 (−6.43 to 9.01)1.17 (1.03–1.32)4.04 (−6.35 to 14.42)
Job insecurity1.13 (1.01–1.27)5.62 (−4.89 to 16.13)1.17 (1.05–1.31)4.04 (−3.37 to 11.45)1.17 (1.03–1.33)6.45 (−3.59 to 16.49)
Low job promotion1.12 (0.99–1.25)22.59 (0.21–44.97)1.17 (1.05–1.30)14.22 (1.57–26.87)1.16 (1.02–1.32)15.53 (−0.29 to 31.35)
Long working hours1.12 (1.00–1.26)9.12 (−7.42 to 25.67)1.17 (1.05–1.30)7.77 (−5.37 to 20.91)1.16 (1.02–1.32)8.12 (−6.44 to 22.68)
Night work1.14 (1.02–1.27)−0.20 (−1.88 to 1.48)1.19 (1.07–1.32)−0.18 (−1.68 to 1.32)1.19 (1.04–1.35)−0.31 (−2.94 to 2.33)
Shift work1.13 (1.01–1.26)9.53 (−0.65 to 19.70)1.17 (1.05–1.30)7.28 (0.63–13.93)1.14 (1.00–1.29)17.94 (−1.03 to 36.90)
Unsociable work days1.14 (1.02–1.28)0.42 (−3.19 to 4.03)1.19 (1.07–1.32)0.47 (−3.57 to 4.51)1.17 (1.04–1.33)0.55 (−4.20 to 5.30)
Low predictability1.14 (1.02–1.28)1.09 (−0.87 to 3.05)1.19 (1.07–1.32)2.28 (−0.61 to 5.16)1.17 (1.03–1.33)2.05 (−0.90 to 5.01)
Physical violence1.14 (1.02–1.28)4.58 (−0.34 to 9.50)1.19 (1.07–1.32)1.09 (−0.15 to 2.34)1.19 (1.04–1.35)0.16 (−0.72 to 1.04)
Bullying1.15 (1.03–1.28)−1.81 (−11.00 to 7.38)1.19 (1.08–1.32)−0.54 (−6.88 to 5.81)1.17 (1.03–1.32)3.11 (−5.58 to 11.80)
Verbal abuse1.12 (1.00–1.26)15.22 (−4.56 to 35.00)1.18 (1.06–1.32)1.94 (−7.24 to 11.13)1.24 (1.08–1.41)−26.62 (−47.21 to − 6.03)
Demands for responsibility1.14 (1.02–1.27)1.69 (−1.28 to 4.67)1.20 (1.08–1.33)−3.25 (−6.41 to − 0.09)1.18 (1.04–1.34)−1.39 (−3.91 to 1.13)
Model 11.07 (0.95–1.20)50.89 (3.44–98.34)1.09 (0.98–1.22)47.00 (13.73–80.27)1.09 (0.95–1.24)53.03 (8.36–97.71)
Model 21.04 (0.93–1.17)67.35 (6.83–127.88)1.05 (0.94–1.18)66.38 (18.93–113.84)1.05 (0.92–1.21)70.25 (10.47–130.02)
Extended models 0 (each factor separately)
Biological exposure1.14 (1.02–1.27)3.63 (−5.48 to 12.74)1.18 (1.07–1.32)3.29 (−4.66 to 11.23)1.17 (1.03–1.33)2.18 (−3.20 to 7.57)
Chemical exposure1.14 (1.02–1.28)0.33 (−6.68 to 7.33)1.19 (1.07–1.32)0.43 (−8.91 to 9.78)1.18 (1.03–1.34)0.84 (−17.29 to 18.97)
Physical exposure1.13 (1.01–1.26)8.92 (−3.01 to 20.85)1.17 (1.05–1.30)9.42 (0.08–18.77)1.10 (0.97–1.26)38.60 (2.70–74.51)
Noise1.12 (1.01–1.26)11.17 (1.06–21.28)1.17 (1.05–1.29)11.52 (3.74–19.30)1.11 (0.97–1.26)36.79 (6.17–67.42)
Thermic constraints1.14 (1.02–1.28)−0.35 (−4.03 to 3.34)1.19 (1.07–1.32)1.53 (−2.76 to 5.82)1.15 (1.01–1.32)11.26 (−7.06 to 29.58)
Radiations1.15 (1.02–1.28)−1.60 (−4.77 to 1.58)1.19 (1.07–1.32)0.20 (−0.35 to 0.74)1.18 (1.04–1.34)0.00 (−0.58 to 0.58)
Controlled air/space1.15 (1.03–1.29)−6.02 (−12.69 to 0.65)1.21 (1.09–1.34)−7.74 (−14.41 to − 1.07)1.20 (1.05–1.36)−9.06 (−18.12 to 0.01)
Biomechanical exposure1.14 (1.02–1.27)3.55 (−0.39 to 7.49)1.18 (1.06–1.30)7.85 (1.34–14.36)1.15 (1.01–1.30)14.34 (0.61–28.08)
Manual materials handling1.13 (1.01–1.26)8.10 (−2.08 to 18.29)1.17 (1.05–1.30)9.80 (−1.48 to 21.08)1.14 (1.01–1.30)16.84 (−4.46 to 38.14)
Postural/articular constraints1.14 (1.02–1.27)3.90 (−2.18 to 9.97)1.18 (1.06–1.31)7.89 (−3.23 to 19.01)1.15 (1.01–1.31)13.87 (−6.52 to 34.26)
Vibrations1.14 (1.02–1.28)0.17 (−0.49 to 0.83)1.19 (1.07–1.32)0.91 (−0.25 to 2.06)1.16 (1.02–1.32)8.64 (−2.12 to 19.40)
Driving1.14 (1.02–1.28)0.06 (−1.07 to 1.19)1.19 (1.07–1.32)2.38 (−1.70 to 6.47)1.17 (1.03–1.33)1.50 (−1.32 to 4.33)
Model 31.12 (1.00–1.26)11.33 (−1.66 to 24.32)1.16 (1.04–1.29)15.24 (3.05–27.43)1.09 (0.95–1.24)48.40 (5.64–91.16)
Model 41.12 (1.00–1.25)13.49 (1.61–25.36)1.15 (1.04–1.28)17.21 (5.79–28.63)1.09 (0.96–1.24)46.73 (8.31–85.16)
WomenAssociate professionals, techniciansClerks, service workersBlue collar workers
RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)RR (95% CI)% (95% CI)
Model 01.14 (1.02–1.28)1.19 (1.07–1.32)1.18 (1.04–1.33)
Extended models 0 (each factor separately)
Low decision latitude1.08 (0.97–1.21)37.70 (5.67–69.72)1.08 (0.97–1.20)56.34 (21.84–90.83)1.04 (0.92–1.18)75.72 (17.96–133.48)
Low skill discretion1.10 (0.98–1.23)28.35 (3.24–53.46)1.10 (0.99–1.22)45.32 (15.07–75.57)1.07 (0.93–1.21)60.61 (9.68–111.54)
Low decision authority1.09 (0.98–1.21)36.45 (7.16–65.74)1.11 (1.00–1.23)43.12 (17.50–68.74)1.08 (0.96–1.23)53.34 (14.23–92.45)
High psychological demands1.19 (1.07–1.33)−31.81 (−59.64 to − 3.98)1.28 (1.15–1.42)−38.25 (−62.15 to − 14.36)1.28 (1.13–1.45)−50.24 (−90.53 to − 9.96)
Low social support1.12 (1.01–1.26)8.64 (−1.51 to 18.80)1.18 (1.06–1.31)7.19 (0.55–13.83)1.14 (1.00–1.29)23.81 (4.95–42.66)
Low social support (supervisors)1.13 (1.02–1.27)8.64 (−0.54 to 17.81)1.19 (1.07–1.32)2.72 (−3.06 to 8.50)1.15 (1.02–1.31)13.78 (1.52–26.05)
Low social support (colleagues)1.13 (1.01–1.26)4.93 (−2.25 to 12.10)1.19 (1.08–1.32)3.73 (−0.92 to 8.38)1.17 (1.03–1.32)11.69 (2.33–21.06)
Job strain1.11 (0.99–1.24)21.22 (3.29–39.15)1.14 (1.03–1.27)24.05 (9.44–38.66)1.13 (1.00–1.28)27.64 (6.54–48.74)
Iso-strain1.11 (0.99–1.25)15.91 (1.33–30.48)1.16 (1.04–1.29)16.70 (5.93–27.47)1.14 (1.00–1.29)24.84 (5.01–44.66)
Low reward1.12 (1.00–1.26)15.85 (−1.97 to 33.67)1.18 (1.06–1.31)8.26 (−1.92 to 18.44)1.17 (1.03–1.33)10.00 (−3.61 to 23.60)
Low esteem1.13 (1.02–1.26)7.48 (−3.37 to 18.34)1.19 (1.08–1.32)1.29 (−6.43 to 9.01)1.17 (1.03–1.32)4.04 (−6.35 to 14.42)
Job insecurity1.13 (1.01–1.27)5.62 (−4.89 to 16.13)1.17 (1.05–1.31)4.04 (−3.37 to 11.45)1.17 (1.03–1.33)6.45 (−3.59 to 16.49)
Low job promotion1.12 (0.99–1.25)22.59 (0.21–44.97)1.17 (1.05–1.30)14.22 (1.57–26.87)1.16 (1.02–1.32)15.53 (−0.29 to 31.35)
Long working hours1.12 (1.00–1.26)9.12 (−7.42 to 25.67)1.17 (1.05–1.30)7.77 (−5.37 to 20.91)1.16 (1.02–1.32)8.12 (−6.44 to 22.68)
Night work1.14 (1.02–1.27)−0.20 (−1.88 to 1.48)1.19 (1.07–1.32)−0.18 (−1.68 to 1.32)1.19 (1.04–1.35)−0.31 (−2.94 to 2.33)
Shift work1.13 (1.01–1.26)9.53 (−0.65 to 19.70)1.17 (1.05–1.30)7.28 (0.63–13.93)1.14 (1.00–1.29)17.94 (−1.03 to 36.90)
Unsociable work days1.14 (1.02–1.28)0.42 (−3.19 to 4.03)1.19 (1.07–1.32)0.47 (−3.57 to 4.51)1.17 (1.04–1.33)0.55 (−4.20 to 5.30)
Low predictability1.14 (1.02–1.28)1.09 (−0.87 to 3.05)1.19 (1.07–1.32)2.28 (−0.61 to 5.16)1.17 (1.03–1.33)2.05 (−0.90 to 5.01)
Physical violence1.14 (1.02–1.28)4.58 (−0.34 to 9.50)1.19 (1.07–1.32)1.09 (−0.15 to 2.34)1.19 (1.04–1.35)0.16 (−0.72 to 1.04)
Bullying1.15 (1.03–1.28)−1.81 (−11.00 to 7.38)1.19 (1.08–1.32)−0.54 (−6.88 to 5.81)1.17 (1.03–1.32)3.11 (−5.58 to 11.80)
Verbal abuse1.12 (1.00–1.26)15.22 (−4.56 to 35.00)1.18 (1.06–1.32)1.94 (−7.24 to 11.13)1.24 (1.08–1.41)−26.62 (−47.21 to − 6.03)
Demands for responsibility1.14 (1.02–1.27)1.69 (−1.28 to 4.67)1.20 (1.08–1.33)−3.25 (−6.41 to − 0.09)1.18 (1.04–1.34)−1.39 (−3.91 to 1.13)
Model 11.07 (0.95–1.20)50.89 (3.44–98.34)1.09 (0.98–1.22)47.00 (13.73–80.27)1.09 (0.95–1.24)53.03 (8.36–97.71)
Model 21.04 (0.93–1.17)67.35 (6.83–127.88)1.05 (0.94–1.18)66.38 (18.93–113.84)1.05 (0.92–1.21)70.25 (10.47–130.02)
Extended models 0 (each factor separately)
Biological exposure1.14 (1.02–1.27)3.63 (−5.48 to 12.74)1.18 (1.07–1.32)3.29 (−4.66 to 11.23)1.17 (1.03–1.33)2.18 (−3.20 to 7.57)
Chemical exposure1.14 (1.02–1.28)0.33 (−6.68 to 7.33)1.19 (1.07–1.32)0.43 (−8.91 to 9.78)1.18 (1.03–1.34)0.84 (−17.29 to 18.97)
Physical exposure1.13 (1.01–1.26)8.92 (−3.01 to 20.85)1.17 (1.05–1.30)9.42 (0.08–18.77)1.10 (0.97–1.26)38.60 (2.70–74.51)
Noise1.12 (1.01–1.26)11.17 (1.06–21.28)1.17 (1.05–1.29)11.52 (3.74–19.30)1.11 (0.97–1.26)36.79 (6.17–67.42)
Thermic constraints1.14 (1.02–1.28)−0.35 (−4.03 to 3.34)1.19 (1.07–1.32)1.53 (−2.76 to 5.82)1.15 (1.01–1.32)11.26 (−7.06 to 29.58)
Radiations1.15 (1.02–1.28)−1.60 (−4.77 to 1.58)1.19 (1.07–1.32)0.20 (−0.35 to 0.74)1.18 (1.04–1.34)0.00 (−0.58 to 0.58)
Controlled air/space1.15 (1.03–1.29)−6.02 (−12.69 to 0.65)1.21 (1.09–1.34)−7.74 (−14.41 to − 1.07)1.20 (1.05–1.36)−9.06 (−18.12 to 0.01)
Biomechanical exposure1.14 (1.02–1.27)3.55 (−0.39 to 7.49)1.18 (1.06–1.30)7.85 (1.34–14.36)1.15 (1.01–1.30)14.34 (0.61–28.08)
Manual materials handling1.13 (1.01–1.26)8.10 (−2.08 to 18.29)1.17 (1.05–1.30)9.80 (−1.48 to 21.08)1.14 (1.01–1.30)16.84 (−4.46 to 38.14)
Postural/articular constraints1.14 (1.02–1.27)3.90 (−2.18 to 9.97)1.18 (1.06–1.31)7.89 (−3.23 to 19.01)1.15 (1.01–1.31)13.87 (−6.52 to 34.26)
Vibrations1.14 (1.02–1.28)0.17 (−0.49 to 0.83)1.19 (1.07–1.32)0.91 (−0.25 to 2.06)1.16 (1.02–1.32)8.64 (−2.12 to 19.40)
Driving1.14 (1.02–1.28)0.06 (−1.07 to 1.19)1.19 (1.07–1.32)2.38 (−1.70 to 6.47)1.17 (1.03–1.33)1.50 (−1.32 to 4.33)
Model 31.12 (1.00–1.26)11.33 (−1.66 to 24.32)1.16 (1.04–1.29)15.24 (3.05–27.43)1.09 (0.95–1.24)48.40 (5.64–91.16)
Model 41.12 (1.00–1.25)13.49 (1.61–25.36)1.15 (1.04–1.28)17.21 (5.79–28.63)1.09 (0.96–1.24)46.73 (8.31–85.16)

RR adjusted for age. Professionals/managers: reference group.

Model 1: decision latitude + social support + reward + shift work + physical violence + bullying + verbal abuse.

Model 2: skill discretion + decision authority + social support (from supervisors) + social support (from colleagues) + esteem + job insecurity + job promotion + shift work + physical violence + bullying + verbal abuse.

Model 3: physical exposure + biomechanical exposure.

Model 4: noise + biomechanical exposure.

Open in new tab

Two psychosocial work factors contributed to the explanation of occupational differences in sickness absence days: decision authority (contribution of 5.23%, P < 0.05) and esteem (contribution of 2.67%, P < 0.05) among male blue collar workers (not showed).

The results from the KHB decomposition method showed that the following factors played a significant role in the global contribution of the factors in models 1–4 (not showed): decision latitude, decision authority, verbal abuse and noise (for both genders), reward, esteem, job promotion, physical violence and bullying (among men), and biomechanical exposure (among women), confirming the results from extended models 0.

Discussion

Main results

Strong occupational differences were observed for both the number of spells and days of sickness absence, low-skilled occupations having an increased rate ratio of spells of absence of 20–40% and a 2-fold rate of absence days compared with managers/professionals. Strong occupational differences were also found for most work factors. Psychosocial work factors contributed substantially to explain occupational differences in sickness absence spells, and occupational exposures of physical and biomechanical nature also provided significant contributions but to a lesser extent. Almost no work factor was found to contribute to the explanation of occupational differences in sickness absence days.

Limitations and strengths of the study

The study used a large representative sample of the national French working population of employees, with weighted data and a good response rate, facilitating generalization of the findings. The weighted and unweighted results were very similar, although it can be noticed that the unweighted analyses provided more significant results than the weighted results. Presenting the weighted results is thus a cautious approach. All the analyses were stratified according to gender, which is important in occupational epidemiology.34 We were also able to provide results for each occupational group in comparison with managers/professionals used as a reference group. Occupational inequalities in sickness absence spells and days were both studied. A large range of work factors and exposures was examined to provide a complete picture of working conditions. Given the wide coverage of our study regarding work exposures, our study may also bring useful information about the relative importance of the different types of work exposures, something that was lacking in the literature to date. Well-established instruments were used to measure psychosocial work factors, facilitating comparisons with other studies. Emergent factors, understudied in the literature in this topic, were also studied. The study also included other occupational exposures that were measured by occupational physicians using their expert evaluation. We studied the contribution of each work factor in the explanation of occupational differences in sickness absence. Models were also performed including all factors that displayed significant contributions. Additional analyses were also performed to disentangle the respective contribution of each factor in models 1–4. Nevertheless, these additional results may be considered conservative given the complex interrelations between factors, especially regarding psychosocial work factors. We used sophisticated statistical analyses to include weights, and to calculate the confidence intervals and significance of the contributions, that helped to select the factors in the final models.

A few limitations deserve to be mentioned. The study had a cross-sectional design, and the conclusions about statistical associations may not be causal. A reverse causality between sickness absence and occupation may be possible and may be explained by a selection effect called social selection. Indeed, employees with health-related problems might have been selected in low-skilled occupations. However, social selection has been suggested to play a small role only in explaining social inequalities in other health outcomes.35 A healthy worker effect may also be suspected in our study if low-skilled workers are more likely to have sickness absence, because of their working conditions, that leads to exit from the labour market or change jobs. This healthy worker effect may underestimate the association between occupation and sickness absence, as well as the contribution of work factors in the explanation of occupational differences in sickness absence. Psychosocial work factors were not all measured using validated questionnaires, and some factors may have been neglected. In addition, no information was available regarding duration of exposure, something that may lead to an underestimation of the contribution of work factors in social inequalities in health.36 Sickness absence was self-reported and might not be as reliable as information received from registers.37

Comparison with the literature

Strong occupational differences in sickness absence spells and days were observed in our study, in agreement with other previous studies.7–16 Strong occupational differences were found for most work factors in our study, in agreement with the literature7,12,13,15 and the two major exceptions have already been reported in previous studies, i.e. the inverse occupational gradients for psychological demands and/or long working hours.12,13,15

We found that both psychosocial work factors and other occupational exposures were contributing factors to occupational differences in sickness absence spells, but almost no work factor was found to contribute to the explanation of occupational differences in sickness absence days/duration. In this topic, the literature focused mainly on the presence of long sickness absence (i.e. sickness absence exceeding a certain number of days/weeks),7–9,11,13,14,16 and the studies exploring the number of days of sickness absence have been very seldom.10

Although both psychosocial work factors and the other occupational exposures contributed to explain the occupational differences in sickness absence spells, our results suggest that the contribution of psychosocial work factors may be higher than the contribution of the other occupational exposures of physical and biomechanical nature. The literature does not appear consistent on this point. Some studies suggested that physical exposures had higher contributions than psychosocial work factors,7,10,11 and other studies showed similar or higher contributions for psychosocial work factors.13,16 Nevertheless, the comparison with the literature may be tricky as the number and content of work factors may differ between studies. Furthermore, most studies did not provide the contribution of each work factor separately, but rather a global contribution of a group of factors. It is thus difficult to conclude that a given factor had a contribution per se. Finally, as the previous studies did not provide the significance of the contributions of work factors, it is also difficult to conclude that these contributions were significant or not. With these remarks, our comparison with the literature below may be imprecise.

We found that decision latitude, social support, job strain and iso-train were contributing factors to occupational inequalities in sickness absence spells, confirming previous results.7,9–16 Reward and its three subdimensions, esteem, job security and job promotion, contributed to explain these inequalities among men, and job promotion was also a contributing factor among women. Job insecurity was found to be a contributing factor in one previous study.10 Shift work contributed to explain occupational differences in sickness absence spells for both genders, in agreement with two previous studies.11,13 Workplace violence factors displayed significant contributions among men. Some other studies reported similar results.10,11,13,16

Our study showed that physical exposure and particularly noise were contributing factors to occupational inequalities in sickness absence spells. The literature is seldom on these exposures and only two previous studies reported that physical exposure and/or noise contributed to these inequalities.10,13 Biomechanical exposure was also found to be a contributing factor among women in our study, confirming previous results.7,10–13,15,16

Our results suggest that the contribution of work factors may differ according to gender and occupational group. A higher number of contributing psychosocial work factors were found among men than among women, and some work factors contributed for one gender and not for the other. Differences were also found according to occupational group. Among men, the contribution of psychosocial work factors might be higher for clerks/service workers and associate professionals/technicians than for blue collar workers. For both genders, our results also suggest that the contribution of physical and biomechanical exposures might be higher for blue collar workers than for the other occupational groups.

Conclusion

Working conditions and occupational exposures contributed to explain occupational inequalities in sickness absence spells in our study. Psychosocial work factors played a major role in explaining these inequalities. Both the classical psychosocial work factors from the job strain model but also other understudied factors were contributing factors. Physical exposure, particularly noise and biomechanical exposure were the other important contributing factors to these inequalities. Preventive measures should target low-skilled occupational groups and both psychosocial work factors and other occupational exposures. Our study suggests that comprehensive prevention policies at the workplace may be beneficial to reduce both the occurrence of sickness absence spells and social inequalities in this outcome.

Supplementary data

Supplementary data are available at EURPUB online.

Acknowledgements

The authors thank the members of the DARES (French ministry of labour), all the occupational physicians and ‘médecins inspecteurs régionaux du travail’, and all the employees who participated to the SUMER survey and made this study possible.

Funding

This study was funded by the French ministry of labour (DARES, Grant No. 2200684049).

Conflicts of interest: None declared.

Key points

  • Working conditions contributed to explain occupational inequalities in sickness absence spells.

  • Psychosocial work factors played a major role in explaining these inequalities.

  • Physical and biomechanical exposures were the other important contributing factors to these inequalities.

  • Comprehensive prevention policies at the workplace may be beneficial to reduce both the occurrence of sickness absence spells and social inequalities in this outcome.

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© The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
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