Background
Work injury represents a major burden for the society and companies because of their substantial costs and related absenteeism and disability [
1,
2]. Studies reported that low-skilled and manual workers were more likely to have work injury [
3‐
6]. These findings are in line with the results provided by social epidemiology studies that underlined social inequalities in various health outcomes [
5], including injury in general [
6]. Nevertheless, the literature appears sparse on the topic of social inequalities in work injury specifically and still more seldom on the factors that may contribute to explain these inequalities.
Working conditions play an important role in the occurrence of work injury. However, the contribution of working conditions and occupational exposures to social inequalities in work injury has been studied very rarely to date. One exception may be one of our previous studies that explored work injury among other health-related outcomes and was not focused on work injury exclusively [
7]. It is thus difficult to evaluate the role of working conditions and occupational exposures in the explanation of social inequalities of work injury.
According to Eurostat, a large part of nonfatal work injuries result from physical and biomechanical exposures at the workplace [
2]. Etiological studies identified a number of occupational exposures that increase the risk of work injury, such as for example physical demands [
8,
9], noise [
10,
11], heat [
12], shift/night work and long working hours [
13]. Psychosocial work factors may also play a role in work injury. These factors have been defined using theoretical models, the most used being the job strain model [
14] composed of three main dimensions: psychological demands, decision latitude, including both skill discretion and decision authority, and social support from colleagues and supervisors. The combination of high psychological demands and low decision latitude (job strain) may have adverse effects on health, and these effects may be increased by low social support (iso-strain). Another model, the effort-reward imbalance model, defines the imbalance between high effort spent at work and low reward received (in terms of esteem, job promotion and job security) [
15]. Other psychosocial work factors have emerged more recently in the literature: workplace violence such as physical violence, sexual harassment, verbal abuse and bullying, predictability as well as demands for responsibility. Studies showed that high psychological demands, low decision latitude, low social support and/or job strain were associated with work injury [
16‐
22]. A few studies found significant associations between low reward [
19], workplace violence/conflicts [
16,
19,
21‐
23] and work injury.
As poor working conditions and occupational exposures were found to be associated with work injury and as these conditions and exposures may be more prevalent among low-skilled and manual workers [
7,
24], they may be considered as pertinent explanations of social inequalities in work injury. Work injury is an avoidable outcome, consequently information on this topic may be crucial to prevent work injury and reduce social inequalities in this outcome.
This study aimed at exploring occupational differences in work injury and at evaluating the contribution of a large number of occupational exposures of psychosocial, chemical, biological, physical and biomechanical nature in the explanation of these differences.
Methods
Study population
The SUMER survey is a periodic national cross-sectional survey from two departments of the French ministry of labour conducted every seven years. Its objective is to evaluate occupational exposures among the national working population of employees, in order to define preventive strategies and research priorities in France. The SUMER survey is based on a network of voluntary occupational physicians, in charge of compulsory medical examinations of employees, who collect the data for a random sample of their employees. Each occupational physician selected 30 employees of the population of employees seen during the period of collection using a random method (one employee of 10 or 20 for example). Occupational medicine is mandatory for all employees in France; consequently, every employee has a medical examination with an occupational physician periodically. SUMER 2010, the last survey conducted in 2010, included around 50,000 employees interviewed about their physical, biological, chemical, biomechanical, organizational and psychosocial exposures by 2400 occupational physicians. The survey included two questionnaires: a main questionnaire and a self-administered questionnaire. The occupational physicians filled in the main questionnaire mainly about physical, biological, chemical, biomechanical and organizational exposures for each employee. Employees filled in a self-administered questionnaire in which their responses were collected about psychosocial work factors and health outcomes. Several articles have already been published by our team using these survey data [
19,
25‐
29].
Work injury
The information about work injury was collected in the self-administered questionnaire. Work injury was measured by the number of injuries (0, 1, 2, 3 or more), which required a medical treatment and at least one day of absence within the last 12 months. We used the number of work injuries within the last 12 months as the outcome of our study.
Psychosocial work factors
Psychosocial work factors were constructed using the data collected in the self-administered questionnaire.
Job strain model dimensions were constructed using the validated French version of the questionnaire [
30,
31]: decision latitude (9 items, Cronbach alpha = 0.78, including 6 items for skill discretion and 3 items for decision authority), psychological demands (9 items, Cronbach alpha = 0.80) and social support (8 items, Cronbach alpha = 0.82, including 4 items for social support from colleagues and 4 items for social support from supervisors). The scores were constructed according to the recommendations by Karasek and dichotomized at the median of the total sample. Job strain was defined by the combination of high demands and low latitude, and isostrain by the combination of job strain and low support.
Reward (11 items, Cronbach alpha = 0.85, including 5 items for esteem, 2 items for job security and 4 items for job promotion) from the effort-reward imbalance model was measured using the validated French version of this questionnaire [
32]. Reward and its sub-dimensions were dichotomized at the median of the total sample.
Five working time variables were studied: long working hours (1 item, ≥48 h/week following the European directive on working time), night work (1 item, working between 12 and 5 am ≥1 night/week), shift work (1 item, either permanent or alternating/rotating shifts), unsociable work days (1 item, working on Sunday or Saturday ≥1 day/week), and predictability of schedules (4 items: information about time schedules for the next day, week, month and the next three months).
Three factors were related to workplace violence: physical violence or sexual assault (2 items), bullying (9 items) and verbal abuse (2 items). Exposure was defined by at least one situation of workplace violence for each factor.
Demands for responsibility (4 items: a mistake in work may lead to serious consequences for product/service quality, to serious financial losses for the company, to dangerous consequences for the safety of people or oneself, and to wage/work/job sanctions for oneself) was dichotomized at the median of the total sample.
Other occupational exposures
Other occupational exposures (physical, biomechanical, biological and chemical exposures) were measured by the occupational physicians using their expert evaluation and collected in the main questionnaire.
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 exposure was defined by at least one biological exposure within the previous week.
Chemical exposure was defined by at least one chemical exposure within the previous week.
The questionnaires and the evaluation of all occupational exposures were built using national and European guidelines and a full description may be found elsewhere [
21].
Occupation
Occupation was coded using the French national classification of occupations (PCS by INSEE) that is close to the International Standard Classification of Occupation (ISCO), and was used as a measure of social position 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 [
33,
34].
Statistical methods
The data were weighted 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). The method for the calculation of weights performed by the DARES of the French ministry of labour had different objectives: to control for the potential bias related to volunteering of occupational physicians by taking into account their characteristics in comparison with the characteristics of the national population of occupational physicians, to control for the potential bias related to the differential periodicity of medical examinations (highly exposed employees have more frequent medical examinations), to control for the potential bias related to non-response to the survey, and finally to provide final weights using a calibration on margins to take the characteristics of the national French population of employees into account. These final weights were calculated using the following calibration variables: gender, age, nationality, working time (full or part time), occupation, company size, and economic activity. All analyses were performed using weighted data.
Major differences in work injury are usually observed between gender and age groups, the prevalence of work injury is lower among women than among men, and may decrease with age [
2]. Men and women were analyzed separately and age was taken into account in all models.
The statistical analysis included three steps:
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 that displayed significant positive contributions for at least one gender or occupational group were added simultaneously to model 0 as independent variables in model 1 and model 2.
-
Similarly, all the occupational exposures that displayed significant positive contributions for at least one gender or occupational group were added simultaneously to model 0 as independent variables in model 3 and model 4.
-
Finally, all work factors that displayed significant positive contributions for at least one gender or occupational group were added simultaneously to model 0 as independent variables in model 5 and model 6.
Models 1, 3 and 5 included the main dimensions of psychosocial work factors and occupational exposures and models 2, 4 and 6 included their sub-dimensions.
Additional analyses were performed to disentangle the respective contribution of each factor in models 1–6 using the KHB decomposition method that provides unbiased decompositions in the context of nonlinear probability models [
37].
-
Thirdly, the associations between occupational exposures and work injury were explored. The results for the associations between psychosocial work factors and work injury were presented in a previous paper and showed that high psychological demands, low social support (especially from supervisors), low reward and its sub-dimensions, low predictability, physical violence, bullying and verbal abuse were associated with work injury [
19]. The associations between the other occupational exposures and work injury were derived from the models above and presented in the present study.
All statistical 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%. The description of the sample among men and women may be found elsewhere [
19,
25‐
29]. Almost all psychosocial work factors displayed significant occupational gradients (Table
1), with a higher prevalence of exposure among low-skilled occupational groups (clerks/service workers and/or blue-collar workers): low decision latitude, low social support, job strain, isostrain, low reward (for men only), night work, shift work, unsociable work days, low predictability, the different forms of workplace violence and demands for responsibility (these two last factors especially for men). Two psychosocial work factors displayed inverse occupational gradients; high psychological demands and long working hours were more prevalent among professionals/managers. 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 Rao-Scott Chi-Square values showed that the magnitude of the occupational differences may be stronger for these exposures than for psychosocial work factors. There was a strong occupational gradient in the prevalence of work injury; blue-collar workers were more likely to have work injury, and the differences between occupations were particularly marked among men.
Table 1
Prevalence of psychosocial work factors, other occupational exposures and work injury according to occupational groups
Men (N) | 5082 | 6408 | 3574 | 11,819 | |
Prevalence (%) |
Low decision latitude | 20.3 | 38.0 | 62.1 | 56.8 | 929*** |
Low skill discretion | 21.9 | 38.1 | 63.6 | 55.7 | 797*** |
Low decision authority | 41.2 | 54.7 | 70.0 | 69.0 | 517*** |
High psychological demands | 65.6 | 50.5 | 37.7 | 36.7 | 515*** |
Low social support | 38.6 | 40.7 | 43.4 | 44.2 | 19*** |
Low social support (from supervisors) | 40.5 | 40.1 | 42.7 | 44.1 | 13** |
Low social support (from colleagues) | 64.8 | 66.2 | 65.8 | 66.3 | 1 |
Job strain | 13.6 | 19.9 | 24.8 | 22.0 | 83*** |
Isostrain | 9.1 | 13.2 | 16.5 | 14.5 | 47*** |
Low reward | 44.9 | 51.4 | 53.4 | 48.8 | 29*** |
Low esteem | 42.8 | 46.9 | 50.1 | 46.0 | 19*** |
Job insecurity | 44.7 | 44.0 | 41.6 | 44.4 | 4 |
Low job promotion | 36.7 | 46.4 | 48.4 | 43.0 | 59*** |
Long working hours | 25.2 | 9.0 | 5.1 | 4.1 | 798*** |
Night work | 1.2 | 3.4 | 8.8 | 8.0 | 205*** |
Shift work | 3.5 | 12.0 | 23.7 | 23.0 | 489*** |
Unsociable work days | 13.5 | 14.7 | 32.1 | 17.8 | 304*** |
Low predictability | 31.3 | 31.4 | 36.4 | 33.3 | 14** |
Physical violence | 0.8 | 1.4 | 5.6 | 1.3 | 166*** |
Bullying | 19.8 | 22.6 | 25.1 | 21.7 | 16** |
Verbal abuse | 16.1 | 22.9 | 34.5 | 14.4 | 378*** |
Demands for responsibility | 49.2 | 52.3 | 45.0 | 61.4 | 173*** |
Biological exposure | 6.7 | 14.2 | 28.7 | 15.2 | 345*** |
Chemical exposure | 6.9 | 24.9 | 26.5 | 60.6 | 2321*** |
Physical exposure | 21.1 | 41.6 | 45.4 | 78.3 | 2144*** |
Noise | 14.8 | 31.4 | 29.9 | 65.4 | 1913*** |
Thermic constraints | 6.1 | 19.7 | 30.2 | 44.5 | 1040*** |
Radiations | 3.1 | 5.0 | 2.1 | 5.7 | 48*** |
Controlled air/space | 30.3 | 19.7 | 18.5 | 10.0 | 428*** |
Biomechanical exposure | 27.1 | 36.4 | 44.7 | 74.0 | 1727*** |
Manual materials handling | 8.0 | 29.1 | 36.7 | 68.6 | 2556*** |
Postural/articular constraints | 49.6 | 63.1 | 77.0 | 90.3 | 1169*** |
Vibrations | 1.3 | 8.1 | 8.0 | 39.6 | 2020*** |
Driving | 37.6 | 46.2 | 35.6 | 56.7 | 324*** |
Work injury | | | | | 195*** |
0 | 99.0 | 96.2 | 92.6 | 89.0 | |
1 | 1.0 | 3.1 | 6.7 | 9.7 | |
2 | 0.0 | 0.7 | 0.6 | 1.1 | |
> =3 | 0.0 | 0.0 | 0.1 | 0.2 | |
Women (N) | 2811 | 5666 | 9311 | 2291 | |
Prevalence (%) |
Low decision latitude | 24.6 | 46.0 | 66.9 | 79.3 | 1095*** |
Low skill discretion | 27.3 | 47.1 | 68.7 | 78.3 | 944*** |
Low decision authority | 42.4 | 62.8 | 74.1 | 80.3 | 497*** |
High psychological demands | 65.7 | 50.4 | 41.5 | 36.6 | 255*** |
Low social support | 37.6 | 39.9 | 40.0 | 49.4 | 33*** |
Low social support (from supervisors) | 38.8 | 41.9 | 39.3 | 46.4 | 19*** |
Low social support (from colleagues) | 61.6 | 63.7 | 63.4 | 70.6 | 19*** |
Job strain | 16.7 | 24.7 | 28.7 | 30.0 | 84*** |
Isostrain | 10.6 | 15.6 | 17.7 | 21.7 | 57*** |
Low reward | 46.6 | 51.1 | 49.1 | 50.4 | 6 |
Low esteem | 43.2 | 45.2 | 42.9 | 44.8 | 4 |
Job insecurity | 42.1 | 42.8 | 37.0 | 44.9 | 33*** |
Low job promotion | 39.1 | 46.9 | 47.3 | 44.2 | 22*** |
Long working hours | 11.8 | 2.5 | 1.6 | 1.7 | 265*** |
Night work | 0.6 | 2.1 | 2.3 | 3.5 | 30*** |
Shift work | 3.1 | 14.7 | 14.8 | 27.6 | 265*** |
Unsociable work days | 8.3 | 15.9 | 19.2 | 19.0 | 83*** |
Low predictability | 24.4 | 28.5 | 33.6 | 30.4 | 43*** |
Physical violence | 0.7 | 3.6 | 1.7 | 0.9 | 45*** |
Bullying | 22.7 | 22.1 | 22.5 | 23.7 | 1 |
Verbal abuse | 25.7 | 31.0 | 26.2 | 13.3 | 94*** |
Demands for responsibility | 35.1 | 38.1 | 29.2 | 32.3 | 62*** |
Biological exposure | 12.1 | 30.6 | 34.5 | 25.7 | 228*** |
Chemical exposure | 5.6 | 20.1 | 31.3 | 52.0 | 744*** |
Physical exposure | 16.6 | 23.2 | 25.6 | 48.6 | 221*** |
Noise | 10.8 | 17.7 | 20.0 | 37.0 | 276*** |
Thermic constraints | 4.7 | 4.7 | 7.8 | 22.2 | 101*** |
Radiations | 1.4 | 3.2 | 1.1 | 1.3 | 65*** |
Controlled air/space | 28.7 | 21.4 | 16.0 | 14.4 | 135*** |
Biomechanical exposure | 27.1 | 32.6 | 42.6 | 51.8 | 214*** |
Manual materials handling | 5.8 | 22.6 | 32.8 | 47.4 | 605*** |
Postural/articular constraints | 55.3 | 64.3 | 78.6 | 92.7 | 474*** |
Vibrations | 0.4 | 0.6 | 1.3 | 8.0 | 319*** |
Driving | 20.1 | 19.7 | 11.9 | 15.2 | 104*** |
Work injury | | | | | 52*** |
0 | 98.8 | 97.3 | 95.6 | 93.9 | |
1 | 1.2 | 2.5 | 3.9 | 5.7 | |
2 | 0.0 | 0.2 | 0.4 | 0.4 | |
> =3 | 0.0 | 0.0 | 0.1 | 0.0 | |
Table
2 presents the association between occupation and work injury (after adjustment for age). Significant associations were found between occupation and work injury with strong occupational gradients. The RR of work injury associated with the occupation of blue-collar workers was 10 for men and 5 for women compared to professionals/managers. The stronger association between occupation and work injury among men than among women was confirmed by a significant interaction test among the whole sample (interaction test comparing blue-collar workers to professionals/managers between men and women significant at
p = 0.024).
Table 2
Association between occupation and work injury
RR (95% CI) (model 0) |
Associate professionals, technicians | 4.0 *** (2.5; 6.5) | 2.4 *** (1.5; 3.8) |
Clerks, service workers | 6.9 *** (4.6; 10.4) | 3.9 *** (2.5; 6.1) |
Blue-collar workers | 10.5 *** (7.2; 15.4) | 5.2 *** (3.2; 8.3) |
Table
3 presents the associations between the occupational exposures of chemical, biological, physical and biomechanical nature and work injury. When each exposure was studied separately (extended models 0), all exposures increased the risk of work injury except radiations and controlled air/space for both genders, vibrations for women and driving for men. When all occupational exposures were studied simultaneously (models 3 and 4), biological, physical and biomechanical exposures were significantly associated with work injury. Among the sub-dimensions of physical and biomechanical exposures, the associations of noise and manual materials handling with work injury were significant for both genders, and the associations of thermic constraints and vibrations were significant for men.
Table 3
Associations between occupational exposures and work injury: results from weighted Poisson regression analysis
Extended models 0 (each factor separately) |
Biological exposure | 1.4 ** (1.1; 1.8) | 2.0 *** (1.6; 2.4) |
Chemical exposure | 1.2 * (1.0; 1.4) | 1.7 *** (1.4; 2.1) |
Physical exposure | 1.8 *** (1.5; 2.3) | 1.8 *** (1.5; 2.3) |
Noise | 1.6 *** (1.3; 2.0) | 1.7 *** (1.3; 2.1) |
Thermic constraints | 1.6 *** (1.3; 1.9) | 1.9 *** (1.4; 2.5) |
Radiations | 1.1 (0.7; 1.6) | 1.2 (0.6; 2.3) |
Controlled air/space | 0.8 * (0.6; 0.9) | 0.9 (0.7; 1.2) |
Biomechanical exposure | 1.4 *** (1.2; 1.7) | 1.6 *** (1.3; 1.9) |
Manual materials handling | 1.7 *** (1.4; 2.1) | 2.3 *** (1.8; 2.9) |
Postural/articular constraints | 1.7 *** (1.3; 2.3) | 1.5 ** (1.1; 2.1) |
Vibrations | 1.6 *** (1.3; 1.9) | 1.4 (0.8; 2.3) |
Driving | 1.2 (1.0; 1.4) | 1.3 * (1.0; 1.7) |
Models 3 |
Biological exposure | 1.3 * (1.0; 1.7) | 1.6 *** (1.3; 2.1) |
Chemical exposure | 1.0 (0.8; 1.2) | 1.2 (0.9; 1.6) |
Physical exposure | 1.7 *** (1.4; 2.1) | 1.6 *** (1.2; 2.0) |
Biomechanical exposure | 1.3 ** (1.1; 1.6) | 1.4 ** (1.1; 1.7) |
Models 4 |
Biological exposure | 1.3 * (1.0. 1.6) | 1.5 ** (1.2; 1.9) |
Chemical exposure | 0.9 (0.7; 1.1) | 1.1 (0.8; 1.5) |
Noise | 1.3 ** (1.1; 1.6) | 1.4 ** (1.1; 1.8) |
Thermic constraints | 1.3 *** (1.1; 1.6) | 1.4 (1.0; 1.9) |
Manual materials handling | 1.5 *** (1.2; 1.7) | 1.8 *** (1.4; 2.3) |
Postural/articular constraints | 1.3 (1.0; 1.7) | 1.0 (0.7; 1.4) |
Vibrations | 1.3 ** (1.1; 1.5) | 0.9 (0.6; 1.6) |
Tables
4 and
5 present the change in the RRs for each occupational group after inclusion of each factor/exposure (extended models 0). The following factors displayed significant contributions in the explanation of occupational differences in work injury: low reward, low esteem, low job promotion, workplace violence factors, and demands for responsibility among men, low decision latitude, low decision authority, low job promotion, shift work, unsociable work days, low predictability and physical violence among women, and low social support, low support from supervisors, job strain and isostrain for both genders. High psychological demands had significant but negative contributions and contributed to increase occupational differences in work injury. When psychosocial work factors with significant and positive contributions were considered simultaneously in models 1 and 2, significant contributions were found for models 1 among women (11–19%), and for models 2 for both genders (4–5% for men and 10–20% for women). These contributions were significant for clerks/service workers and technicians/associate professionals among both genders and for blue collar workers among women. In the models including each exposure separately (extended models 0), chemical, biological, physical and biomechanical exposures had significant contributions to the explanation of occupational differences in work injury. Noise, thermic constraints, manual materials handling and postural/articular constraints for both genders, and vibrations for men contributed to explain these differences. Controlled air/space had significant contributions among men, but this variable displayed significant protective associations with work injury (Table
3), and was not included in the final models. When the exposures with significant contributions were included simultaneously in models 3 and 4, their contribution was significant for all three occupational groups and for men (11–26%) and women (18–31%). When finally all factors and exposures with significant contributions were included in models 5 and 6, the contributions were significant for men (11–26%) and women (27–43%) and all three occupational groups.
Table 4
Contribution (%) of work factors to occupational inequalities in work injury: results for weighted Poisson regression analysis among men
Extended models 0 (each factor separately) |
Low decision latitude | 4.0 *** | 0.3 | 6.8 *** | 0.5 | 10.4 *** | 0.4 |
Low skill discretion | 4.0 *** | 0.2 | 6.9 *** | 0.3 | 10.4 *** | 0.2 |
Low decision authority | 4.0 *** | 1.2 | 6.7 *** | 1.9 | 10.2 *** | 1.5 |
High psychological demands | 4.2 *** | −4.1 ** | 7.5 *** | −5.5 ** | 11.7 *** | −4.7 *** |
Low social support | 3.9 *** | 0.7 | 6.5 *** | 1.1 * | 9.9 *** | 1.1 ** |
Low social support (from supervisors) | 4.0 *** | 0.0 | 6.6 *** | 0.7 | 10.2 *** | 0.8 ** |
Low social support (from colleagues) | 3.9 *** | 0.1 | 6.9 *** | 0.1 | 10.2 *** | 0.1 |
Job strain | 4.0 *** | 1.3 * | 6.6 *** | 1.6 ** | 10.2 *** | 1.0 ** |
Isostrain | 3.9 *** | 0.8 | 6.6 *** | 1.0 * | 10.0 *** | 0.6 * |
Low reward | 3.9 *** | 2.4 ** | 6.5 *** | 2.4 ** | 10.2 *** | 1.1 ** |
Low esteem | 3.9 *** | 1.6 ** | 6.6 *** | 2.1 ** | 10.3 *** | 0.9 ** |
Job insecurity | 4.0 *** | 0.0 | 6.8 *** | −0.3 | 10.5 *** | 0.2 |
Low job promotion | 4.0 *** | 2.6 ** | 6.8 *** | 2.4 ** | 10.7 *** | 1.2 ** |
Long working hours | 4.1 *** | −1.8 | 7.0 *** | −1.6 | 10.7 *** | −1.4 |
Night work | 3.5 *** | −0.4 | 7.1 *** | −0.9 | 10.8 *** | −0.6 |
Shift work | 4.2 *** | −0.6 | 7.2 *** | −1.1 | 11.1 *** | −0.9 |
Unsociable work days | 4.0 *** | 0.0 | 6.8 *** | 0.2 | 10.5 *** | 0.0 |
Low predictability | 4.0 *** | −0.1 | 6.8 *** | 0.5 | 10.4 *** | 0.0 |
Physical violence | 4.0 *** | 0.3 | 6.4 *** | 1.7 ** | 10.4 *** | 0.1 |
Bullying | 4.0 *** | 0.9 * | 6.7 *** | 1.2 ** | 10.4 *** | 0.4 |
Verbal abuse | 3.8 *** | 2.8 ** | 6.1 *** | 5.4 *** | 10.5 *** | −0.3 |
Demands for responsibility | 4.0 *** | 0.6 | 6.9 *** | −0.5 | 10.2 *** | 1.2 * |
Model 1 | 3.8 *** | 1.8 | 6.4 *** | 1.9 | 10.6 *** | −1.3 |
Model 2 | 3.8 *** | 3.5 * | 6.0 *** | 4.7 * | 10.4 *** | 0.8 |
Extended models 0 (each factor separately) |
Biological exposure | 3.9 *** | 1.9 ** | 6.3 *** | 4.0 ** | 10.1 *** | 1.2 ** |
Chemical exposure | 3.9 *** | 2.4 | 6.6 *** | 1.8 * | 9.5 *** | 4.2 * |
Physical exposure | 3.5 *** | 8.9 *** | 5.9 *** | 7.3 *** | 7.5 *** | 14.5 *** |
Noise | 3.7 *** | 5.7 ** | 6.4 *** | 3.6 *** | 8.2 *** | 10.3 *** |
Thermic constraints | 3.7 *** | 4.6 *** | 6.1 *** | 5.8 *** | 8.6 *** | 7.6 *** |
Radiations | 4.0 *** | 0.1 | 6.9 *** | 0.0 | 10.5 *** | 0.1 |
Controlled air/space | 3.9 *** | 2.0 * | 6.7 *** | 1.7 * | 10.0 *** | 2.3 * |
Biomechanical exposure | 3.9 *** | 2.3 * | 6.5 *** | 3.1 ** | 8.9 *** | 6.9 ** |
Manual materials handling | 3.5 *** | 8.3 *** | 5.8 *** | 8.0 *** | 7.4 *** | 14.1 *** |
Postural/articular constraints | 3.8 *** | 5.1 ** | 6.0 *** | 7.5 ** | 8.7 *** | 9.2 ** |
Vibrations | 3.9 *** | 2.0 ** | 6.7 *** | 1.2 ** | 8.7 *** | 7.1 *** |
Driving | 4.0 *** | 1.0 | 6.9 *** | 0.0 | 10.2 *** | 1.3 |
Model 3 | 3.4 *** | 10.7 *** | 5.4 *** | 11.9 *** | 6.8 *** | 18.5 *** |
Model 4 | 3.1 *** | 15.1 *** | 4.8 *** | 16.8 *** | 5.5 *** | 26.3 *** |
Model 5 | 3.3 *** | 10.9 *** | 5.2 *** | 12.4 *** | 7.3 *** | 14.9 *** |
Model 6 | 3.0 *** | 17.5 *** | 4.2 *** | 21.7 *** | 5.6 *** | 25.6 *** |
Table 5
Contribution (%) of work factors to occupational inequalities in work injury: results for weighted Poisson regression analysis among women
Extended models 0 (each factor separately) |
Low decision latitude | 2.3 *** | 5.5 | 3.6 *** | 6.9 * | 4.6 *** | 7.5 * |
Low skill discretion | 2.3 *** | 3.2 | 3.7 *** | 4.3 | 4.8 *** | 4.5 |
Low decision authority | 2.2 *** | 6.9 * | 3.6 *** | 6.9 * | 4.7 *** | 6.8 * |
High psychological demands | 2.6 *** | −11.1 *** | 4.6 *** | − 11.1 *** | 6.3 *** | − 11.3 *** |
Low social support | 2.3 *** | 1.4 | 3.9 *** | 1.0 | 5.0 *** | 2.6 * |
Low social support (from supervisors) | 2.3 *** | 1.7 | 3.9 *** | 0.4 | 5.1 *** | 1.7 * |
Low social support (from colleagues) | 2.3 *** | 0.9 | 3.9 *** | 0.6 | 5.1 *** | 1.4 |
Job strain | 2.3 *** | 5.8 ** | 3.6 *** | 5.5 *** | 4.8 *** | 5.2 ** |
Isostrain | 2.2 ** | 3.8 * | 3.7 *** | 3.4 ** | 4.9 *** | 4.2 ** |
Low reward | 2.2 *** | 3.1 | 3.8 *** | 1.3 | 5.1 *** | 1.2 |
Low esteem | 2.3 *** | 1.5 | 4.0 *** | 0.2 | 5.2 *** | 0.5 |
Job insecurity | 2.4 *** | 0.7 | 3.9 *** | −1.2 | 4.8 *** | 0.8 |
Low job promotion | 2.2 *** | 3.0 | 3.8 *** | 2.0 * | 5.1 *** | 1.0 |
Long working hours | 2.6 *** | −5.6 | 4.3 *** | −4.0 | 5.7 *** | −3.3 |
Night work | 2.4 *** | 0.1 | 3.9 *** | 0.1 | 5.2 *** | 0.1 |
Shift work | 2.2 ** | 8.4 ** | 3.6 *** | 5.3 ** | 4.3 *** | 9.8 ** |
Unsociable work days | 2.3 *** | 3.6 * | 3.7 *** | 3.3 ** | 4.9 *** | 3.0 ** |
Low predictability | 2.4 *** | 1.9 | 3.7 *** | 3.2 ** | 5.0 *** | 2.2 * |
Physical violence | 2.2 ** | 3.7 * | 3.7 *** | 0.7 * | 5.2 *** | 0.1 |
Bullying | 2.4 *** | −0.5 | 3.9 *** | −0.1 | 5.1 *** | 0.4 |
Verbal abuse | 2.3 *** | 4.4 * | 3.8 *** | 0.5 | 5.6 *** | −5.0 ** |
Demands for responsibility | 2.4 *** | 0.8 | 4.0 *** | −1.2 | 5.2 *** | −0.3 |
Model 1 | 1.8 * | 18.6 * | 3.1 *** | 11.3 * | 4.2 *** | 9.3 |
Model 2 | 1.8 * | 19.7 * | 3.1 *** | 12.0 ** | 4.2 *** | 9.5 * |
Extended models 0 (each factor separately) |
Biological exposure | 2.1 ** | 14.5 ** | 3.3 *** | 10.9 *** | 4.7 *** | 5.6 ** |
Chemical exposure | 2.2 ** | 9.1 ** | 3.4 *** | 10.1 *** | 4.0 *** | 15.2 *** |
Physical exposure | 2.3 *** | 4.3 * | 3.7 *** | 3.7 ** | 4.2 *** | 11.9 ** |
Noise | 2.3 *** | 4.1 * | 3.7 *** | 3.4 ** | 4.4 *** | 8.5 ** |
Thermic constraints | 2.4 *** | −0.3 | 3.9 *** | 1.1 | 4.5 *** | 6.9 ** |
Radiations | 2.4 *** | 0.4 | 3.9 *** | 0.0 | 5.2 *** | 0.0 |
Controlled air/space | 2.4 *** | 1.1 | 3.9 *** | 1.2 | 5.1 *** | 1.1 |
Biomechanical exposure | 2.3 *** | 2.7 * | 3.7 *** | 4.9 ** | 4.6 *** | 6.8 ** |
Manual materials handling | 2.0 ** | 16.6 ** | 3.0 *** | 16.7 *** | 3.4 *** | 21.9 *** |
Postural/articular constraints | 2.3 *** | 4.3 | 3.6 *** | 7.2 * | 4.5 *** | 9.8 * |
Vibrations | 2.4 *** | 0.0 | 3.9 *** | 0.2 | 5.0 *** | 1.5 |
Driving | 2.4 *** | 0.0 | 4.0 *** | −1.6 | 5.3 *** | −0.7 |
Model 3 | 1.9 ** | 19.8 ** | 3.0 *** | 18.3 *** | 3.4 *** | 23.5 *** |
Model 4 | 1.8 * | 25.5 ** | 2.7 *** | 23.4 *** | 3.0 *** | 30.8 *** |
Model 5 | 1.5 | 39.1 * | 2.4 *** | 28.1 *** | 3.1 *** | 27.2 *** |
Model 6 | 1.5 | 42.9 * | 2.3 ** | 30.3 *** | 2.9 *** | 30.7 *** |
The results from the KHB decomposition method showed that some factors played a significant role in the global contribution of the factors in models 1–6 (not showed): reward, esteem, physical violence, thermic constraints, and vibrations among men, predictability, and postural/articular constraints among women, and shift work, verbal abuse, biological exposure, physical exposure, noise, biomechanical exposure and manual materials handling for both genders, confirming the results from extended models 0.
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.