Industrial Health
Online ISSN : 1880-8026
Print ISSN : 0019-8366
ISSN-L : 0019-8366
Original Articles
Job Dissatisfaction as a Contributor to Stress-related Mental Health Problems among Japanese Civil Servants
Takashi TATSUSEMichikazu SEKINE
Author information
JOURNAL FREE ACCESS FULL-TEXT HTML

2013 Volume 51 Issue 3 Pages 307-318

Details
Abstract

Although studies on the association of job dissatisfaction with mental health have been conducted in the past, few studies have dealt with the complicated links connecting job stress, job dissatisfaction, and stress-related illness. This study seeks to determine how job dissatisfaction is linked to common mental health issues. This study surveyed 3,172 civil servants (2,233 men and 939 women) in 1998, taking poor mental functioning, fatigue, and sleep disturbance as stress-related mental health problems. We examine how psychosocial risk factors at work and job dissatisfaction are associated independently with poor mental functioning, fatigue, and sleep disturbance after adjustment for other known risk factors, and how job dissatisfaction contributes to change in the degree of association between psychosocial risk factors at work and mental health problems. In general, psychosocial risk factors were independently associated with mental health problems. When adjusted for job dissatisfaction, not only was job satisfaction independently associated with mental health problems but it was also found that the association of psychosocial risk factors with mental health problems declined. Our results suggest that, although longitudinal research is necessary, attitudes toward satisfaction at work can potentially decrease the negative effects of psychosocial risk factors at work on mental health.

Introduction

That high levels of psychosocial risk at work are widespread in working populations is well known. When we look at changes occurring in the work environment from a global economic perspective, work conditions have worsened, especially in developed countries; the negative changes include, but are not limited to, organizational restructuring, the 24-h economy, and adoption of, and adaptation to, mechanisation and automation1, 2). These changes in general also expose workers to unfavourable working environments that may impact workers’ health, increasing psychosocial risk factors. Furthermore, trends such as a faster work pace or the demand for higher skills have contributed to an increase in stress-related mental health problems among workers3).

Psychosocial work factors can be associated with the incidence of many health problems, as described by Karasek and Theorell, whose model of psychosocial work characteristics is the most influential and successful in assessing such issues. According to Karasek, stressful conditions stem from demand and control conditions4, 5). This original model was later modified to include support at work as a third criterion6). As findings in past studies demonstrated, the condition of low control, low support, and high demand at work relate to many health problems; health risk behaviours7), metabolic syndrome8), coronary heart disease9), depression and other mental health problems, and health-related quality of life in general10,11,12). While the two-dimension model (the combination of job control and job demand) used in previous studies addresses mental diseases such as depression and poor mental functioning, factors such as low control, high demand, and low support at work have also been shown to independently impact mental functioning. Moreover, job control contributed more strongly and independently to the SES (Socio Economic Status) health gradient with regard to depression and mental functioning13,14,15).

On the other hand, since many people spend a considerable proportion of their waking hours at work, job dissatisfaction is another important factor associated with organizational health. Meta-analysis revealed an association with poor health and job dissatisfaction, especially in terms of mental health problems such as, burnout, anxiety, and depression16, 17). Job dissatisfaction is also considered to be one of predictors for absenteeism, turnover rates, occurrences of the common cold, absences due to illness, and early retirement18,19,20), as well as coronary heart disease (CHD) and mortality from CHD21, 22). In the NIOSH job stress and health model, job dissatisfaction, along with depression, is treated as one of the acute reactions caused by job stressors. It is considered to be one of the factors causing work-related disabilities, including unexplained physical symptoms23); past research has proven the validity of this argument18). Thus, the management of satisfied versus dissatisfied on the job is a crucial factor for occupational health.

Previous studies have also revealed an association between job dissatisfaction and job stress factors5, 18, 24). Still, the results of interactions among work characteristics including job dissatisfaction have not been consistent because, for example, psychosocial risk measured according to the demand/control combination model may have been an oversimplification25). Additionally, while meta-analysis reveals that job dissatisfaction is an important factor influencing the health of workers16), we are not so far able to identify the factors that contribute to the reduction of risk for psychosocial influences at work in the context of health problems, except for cases of health behaviours and work-family conflicts14, 26).

Furthermore, as for the relations between job dissatisfaction and health, very few previous studies examine other possible ‘stress-related problems’, including unexplained physical symptoms27), while many studies examined depression and burnout as mental problem outcomes1828,29,30). Few studies have dealt with evaluating job dissatisfaction in relation to minor symptoms (fatigue, sleep disorder, etc.) that have a strong association with stress-related illnesses3, 18), in the context of these symptoms and psychosocial risk factors at work. To counter these health issues, the proper approach would be to evaluate stress factors at work (e.g. long working hour, difference in job type, and psychosocial risk factors) and job dissatisfaction separately, and explore to what extent association between stress factors at work and health problems declines when filtered through a framework that posits ‘job satisfaction and job dissatisfaction’, the definition of which is based on Weiss’s “(job satisfaction) is a positive or negative evaluative judgment one makes about one’s job or job situation”17, 31, 32).

Taking into account the fact that previous studies have not pursued the complicated links among psychosocial factors at work, job dissatisfaction, and stress-related illness, our objective is therefore to examine 1) the different psychosocial risk factors at work as related to each of mental health problems (with respect to different symptoms such as, poor mental function, fatigue, or sleep disturbance), 2) the association of job dissatisfaction with these health problems after adjustment for known risk factors, and 3) how job dissatisfaction contributes to changes in the degree of association between psychosocial risk factors at work and mental health problems.

Subjects and Methods

Participants

Data in support of this paper came from the Japanese Civil Servants (the JACS) study, which was conducted in collaboration with the British civil servant study (the Whitehall II Study), with Phase 1 of the JACS study being conducted between 1998 and 1999. The JACS study subjects were local government civil servants working in western Japan, consisting mainly of administrative workers, professional workers (technicians, teachers, and hospital workers), clerical workers, and office support staff. Subjects were aged 18–69 yr at the time of the survey, which was administered via a questionnaire delivered to the participants by the local government human resources departments, and returned in sealed envelopes. The questionnaire was sent to 6,090 subjects, 4,933 of which responded (81.0% response rate). Questionnaires in which subjects failed to answer one or more questions about age, sex, marital status, long standing illness, job type, work characteristics, job satisfaction, or health outcomes were excluded from the analysis, resulting in data from 3,172 subjects (2,233 men and 939 women) being used for the final analysis. The mean ages of the subjects were 42.3 yr (SD: 9.8) for men and 39.8 (SD: 10.5) for women.

This study was conducted as a part of annual health checks mandated by the Japanese Industrial Safety and Health Law. An ad hoc committee of the civil service, which included a member of the Safety and Health Committee, as well as labour and personnel representatives, approved the contents and ethical aspects of this study. Informed consents were obtained from all participants, who all took part in the study voluntarily.

Questionnaire

The questionnaire items, which were chosen from the Whitehall II study, were first translated into Japanese, and then checked for accuracy by being translated back into English by an individual with no knowledge of the original Whitehall II Study. Questions relating to job types were surveyed according to the major groups of occupations of the census in Japan, grouped into 4 categories; administrative (the number of valid response, 152), professional (1,672), clerical (1,076) and office support workers (272). With administrative, professional, and clerical workers corresponding to the census classification, with a separate job category ‘office support’ for the local civil servants population, representing full-time ‘security’, ‘transport and machine operation’ and ‘non-classify-able’ workers of the census.

To assess overall job satisfaction, the questionnaire also asked about “jobs as a whole taking everything into consideration.” Participants rated their satisfaction according to one of four response categories, consisting of “very satisfied”, “satisfied”, “dissatisfied”, “very dissatisfied”. According to theoretical definition of Weiss32), the job satisfaction item was dichotomized into “satisfied” or “dissatisfied” for analysis. Also, a previous report showed that the reliability of single-item measure of job satisfaction is 0.6833).

In this study, the work characteristics of the subjects were measured by psychosocial risk factors at work, work hours, and job types. Psychosocial risk factors at work were evaluated using three job stress (job control-demand-support) variables, relative to 25 self-reported at work items, which included 15 control items, 4 demand items, and 6 at-work social support items9), with response categories ranging from 0 (often) to 3 (never). All items were calculated by summing the item scores as a stress score respectively. The reliability coefficient (Cronback’s alpha was 0.77 for control, 0.70 for demand, and 0.81 for support) in this study implied that the questionnaire had sufficient internal consistency. In general, low control, high demand, and low support are associated with poor health7,8,9, 12, 13, 26, 34). Therefore stress scores of control, demand, and support were grouped into tertiles, which were rated as high, medium, and low34). With respect to working hours, the subjects were asked to answer how many hours a day they had worked in the past month.

Health outcomes were measured using 3 stress-related mental health symptoms: poor mental health, subjective fatigue, and disturbed sleep.

The civil servants’ mental health functioning was measured using Japanese version of Short Form 36 (SF-36), which consists of 36 items and generates 8 subscales35). Aggregate mental component summary SF36 (MCS) scores were obtained by multiplying each z-score by its mental factor score coefficient and adding the eight products. Finally, each aggregate component score was transformed to a norm-based score with a Japanese population mean of 50 and standard deviation of 1036). A Japanese version of the SF-36 has been validated, and widely used in Japan. The higher scores represent better health. Poor mental functioning was defined as having a MCS score below the 25th percentile.

As for fatigue and sleep disturbance, the self-administered questionnaire was used to detect whether the subjects had health problems. To measure subjective fatigue symptoms, we asked “have you had any symptoms of unexplained fatigue during the last two weeks?” to ascertain the subjects’ perceived aspects of general fatigue37). To measure sleep disturbance symptoms, we asked ”have you had any symptoms of sleep disturbance during the last two weeks?” This item inquired as to the type of sleep disturbance, which is independent from other “not rested”, or “difficulties awaking”38).

We also used age, gender, marital status and longstanding illness variables as a confounder associated between psychosocial factors at work and mental health except work characteristics according to previous civil servant studies26, 34).

Statistics

To evaluate possible non response biases in this study, a comparison was made between the subjects studied and those excluded with regard to differences in age, sex, and health outcomes (e.g., prevalence of poor mental functioning, feelings of fatigue, and experiencing sleep disturbance). There were no significant differences in health outcomes between included and excluded subjects, although the excluded subjects tended to be older and women.

The age-adjusted percentage of job dissatisfaction by the levels of job stress was calculated using 10 yr age groups of the lowest levels of each job stress as the standard population. χ2-tests were used to evaluate the existence of gender and job stress differences at work in job satisfaction.

Logistic regression analysis was performed to examine 1) whether there were different psychosocial risk factors at work related to stress-related illness (e.g., poor mental functioning, feelings of fatigue and having sleep disturbance), and 2) whether job dissatisfaction was associated with stress- related illness after being adjusted for other known risk factors, and 3) how job dissatisfaction contributed to change in the degree of association between psychosocial risk factors at work and stress-related illness.

The odds ratios (ORs) and 95% confidence intervals (95%CI) were calculated. Statistical analyses were performed using SPSS (20.0.J). A two-tailed p value of less than 0.05 was considered to be significant.

Results

Table 1 lists all subject characteristics by gender. Women were found to be relatively younger than men, and women were less likely to be married by a significant margin. While there was no significant gender difference in the level of social support at work, women outnumbered men in low control, while there were more men than women in high demand. The majority of women were professional workers, while very few women were administrative and office support workers. Men were more likely to work longer hours (>9 h). More than 60% of both men and women reported being satisfied with their jobs. Less than 30% of subjects had any longstanding illness. The MCS mean score was 46.6 (standard deviation: 6.31) for men and 47.5 (7.11) for women (p<0.001). The number of subjects reporting poor mental functioning was 22.7% for men and 30.0% in women. 11.6% for men and 18.3% for women (p<0.001) reported fatigue, and those experiencing sleep disturbances were 8.8% of the men and 12.9% of the women.

Table 1. Characteristics of the participants by gender
Men (n=2,233) (%) Women (n=939) (%) χ2-testp-value
Age –24 2.4 9.7
25–34 25.3 26.2
35–44 28.0 29.2
45–54 34.2 26.7
55– 10.1 8.2 <0.001
Married Yes 81.1 69.2
No 18.9 30.8 <0.001
Control at work Low 34.1 41.2
Intermediate 33.5 36.3
High 32.4 22.5 <0.001
Demand at work Low 42.1 30.5
Intermediate 29.9 30.5
High 28.0 39.1 <0.001
Support at work Low 37.8 38.8
Intermediate 31.2 29.5
High 31.0 31.7 0.633
Job types Administrative 6.6 0.5
Professional 47.5 65.1
Clerical 35.2 30.9
Office support 10.7 3.5 <0.001
Work hours ≤8 h 55.9 52.5
8–9 h 21.0 29.5
9–11 h 19.0 16.8
11 h< 4.0 1.2 <0.001
Job satisfaction being satisfied 66.1 61.7
being dissatisfied 33.9 38.3 0.017
Longstanding illness Yes 27.9 26.6
No 72.1 73.4 0.463

Pearson’s χ2 tests were used to examine whether there were differences in the proportions between men and women.

Table 2 illustrates age-adjusted percentage of those with job dissatisfaction by different levels of job stress factors at work. In both men and women, all stress variables related significantly to job dissatisfaction, while higher control and support at work were likely to lower the number of those reporting dissatisfaction with their jobs. Approximately one third of all subjects having intermediate control and support were dissatisfied with their job, though dissatisfaction was slightly higher among those having low control and support. The demand levels of work was associated strongly with job dissatisfaction and showed a dose-response relationship in men and women.

Table 2. Age-adjusted percentages of job dissatisfaction by different levels of psychosocial risk at work
Psychosocial risks at work age-adjusted χ2-test
Low (%) Intermediate (%) High (%) p-value
Men Job dissatisfaction % (33.9%: prevalence among men)
Control at work 30.5 31.1 17.0 <0.001
Demand at work 16.7 29.8 47.3 <0.001
Support at work 26.9 31.4 18.9 <0.001
Women Job dissatisfaction % (38.3%: prevalence among women)
Control at work 35.4 37.5 26.5 0.024
Demand at work 23.4 33.9 49.3 <0.001
Support at work 32.4 35.4 24.8 0.017

Pearson’s χ2 test for age-standardized values by the direct method using 10-yr age groups of each gender with low levels of psychosocial risk at work as the standard population.

Table 3 notes job stress differences in poor mental functioning before and after adjusted for job dissatisfaction. In multivariate Model 1, age- and sex-adjusted ORs in low control, intermediate and high demand, and low support were significantly associated with mental functioning (ORs were 1.87, 1.52, 2.27 and 1.41 respectively). When adjusted for occupation and work hours in model 2, the adjusted OR in low control at work was attenuated slightly in comparison with that of high control, although job types and work hours did not associate with mental health problems. When further adjustments were made for job dissatisfaction, the adjusted ORs of job stress at work in poor mental functioning were attenuated in all variables. At that point low support at work was no longer significantly associated with poor mental functioning, while job dissatisfaction was strongly related to poor mental functioning (OR=2.06). The association of both job stress difference and job dissatisfaction with poor mental functioning changed little after applying adjustments for marital status and longstanding illness. Furthermore, the statistical significance of sex and age remained the same in all models.

Table 3. The association with job characteristics in poor mental functioning before and after adjustment for job dissatisfaction
Prevalence of poor mental functioning % Model 1 Model 2 Model 3 Model 4
OR (95%CI) OR (95%CI) OR (95%CI) OR (95%CI)
Sex
Men 22.7 1.00 1.00 1.00 1.00
Women 30.0 1.25 (1.04–1.49) 1.28 (1.06–1.54) 1.31 (1.08–1.58) 1.30 (1.08–1.57)
Age
55– 13.9 1.00 1.00 1.00 1.00
45–54 22.1 1.64 (1.14–2.36) 1.57 (1.08–2.27) 1.55 (1.06–2.25) 1.61 (1.11–2.35)
35–44 28.9 2.18 (1.51–3.13) 2.06 (1.41–3.00) 1.95 (1.33–2.85) 2.11 (1.43–3.10)
25–34 27.2 2.17 (1.50–3.15) 2.00 (1.36–2.95) 1.86 (1.26–2.76) 1.97 (1.31–2.97)
–24 29.7 2.38 (1.44–3.94) 2.24 (1.33–3.75) 2.20 (1.30–3.70) 2.23 (1.27–3.91)
Control at work
High 18.4 1.00 1.00 1.00 1.00
Intermediate 22.9 1.19 (0.95–1.49) 1.15 (0.92–1.44) 1.04 (0.83–1.31) 1.04 (0.82–1.31)
Low 32.1 1.87 (1.50–2.32) 1.75 (1.39–2.20) 1.43 (1.13–1.81) 1.42 (1.12–1.80)
Demand at work
Low 18.3 1.00 1.00 1.00 1.00
Intermediate 24.3 1.52 (1.23–1.89) 1.53 (1.23–1.90) 1.45 (1.16–1.81) 1.44 (1.15–1.78)
High 33.6 2.27 (1.86–2.78) 2.27 (1.81–2.85) 1.96 (1.56–2.47) 1.95 (1.55–2.45)
Support at work
High 21.9 1.00 1.00 1.00 1.00
Intermediate 23.4 1.10 (0.89–1.38) 1.10 (0.89–1.37) 0.99 (0.80–1.24) 1.00 (0.80–1.24)
Low 28.6 1.41 (1.14–1.75) 1.45 (1.17–1.79) 1.21 (0.98–1.51) 1.21 (0.97–1.51)
Job types
Administrative 13.8 1.00 1.00 1.00
Professional 24.1 1.06 (0.64–1.75) 0.99 (0.60–1.65) 0.99 (0.60–1.64)
Clerical 29.3 1.38 (0.83–2.30) 1.33 (0.80–2.23) 1.33 (0.79–2.23)
Office support 18.8 0.88 (0.49–1.57) 0.86 (0.48–1.54) 0.89 (0.50–1.61)
Work hours
≤8 h 22.7 1.00 1.00 1.00
8–9 h 24 0.90 (0.72–1.11) 0.87 (0.70–1.09) 0.88 (0.71–1.10)
9–11 h 31 1.03 (0.81–1.30) 1.03 (0.81–1.30) 1.04 (0.82–1.32)
>11 h 33.7 1.14 (0.72–1.81) 1.11 (0.70–1.77) 1.12 (0.70–1.78)
Job satisfaction
Yes 18.3 1.00 1.00
No 37.1 2.06 (1.72–2.47) 2.04 (1.70–2.44)
Married
Yes 23.6 1.00
No 29.4 1.15 (0.91–1.46)
Longstanding illness
No 23.7 1.00
Yes 27.9 1.37 (1.13–1.66)

Correlations evaluated simultaneously using multiple logistic regressions and expressed as odds ratios with 95% confidence intervals. Abbreviations: OR, odds ratio; 95%CI, 95% confidence interval. Statistically significant odds ratios are shown in bold. Model 1 is adjusted for psychosocial risk factors at work (control, demand and support), sex and age. Model 2 is adjusted for model 1 plus job types and work hours. Model 3 is adjusted for model 2 plus job dissatisfaction. Model 4 is adjusted for model 3 plus marital status and longstanding illness.

Table 4 shows job stress differences in fatigue before and after being adjusted for job dissatisfaction. When adjusted for sex, age, and job stress, high demand and low support were significantly associated with fatigue (ORs=1.96 and 1.48 respectively). Although fatigue was not related to control at work in Model 1, the increase in adjusted OR in low control was significantly associated with outcome after adjusted for job types and work hours (OR=1.33). When further adjusted for job dissatisfaction, the adjusted ORs of job stress in fatigue were attenuated in all variables. At that point, low control and support at work were no longer significantly associated with fatigue, while job dissatisfaction was strongly related to variables in fatigue (OR=1.81). The association of both job stress differences and job dissatisfaction with feeling fatigue changed little after being adjusted for marital status and long standing illness. Furthermore, the statistical significance of sex and age remained the same in all models.

Table 4. The association with job characteristics in fatigue before and after adjustment for job dissatisfaction
Prevalence of fatigue % Model 1 Model 2 Model 3 Model 4
OR (95%CI) OR (95%CI) OR (95%CI) OR (95%CI)
Sex
Men 11.6 1.00 1.00 1.00 1.00
Women 18.3 1.56 (1.26–1.94) 1.59 (1.24–1.95) 1.59 (1.27–1.99) 1.58 (1.26–1.98)
Age
55– 8.90 1.00 1.00 1.00 1.00
45–54 15.1 1.75 (1.13–2.70) 1.76 (1.13–2.75) 1.74 (1.27–1.99) 1.85 (1.18–2.90)
35–44 15.0 1.63 (1.05–2.55) 1.68 (1.06–2.65) 1.59 (1.01–2.53) 1.79 (1.12–2.86)
25–34 11.7 1.32 (0.83–2.10) 1.35 (0.84–2.18) 1.26 (0.78–2.05) 1.40 (0.84–2.32)
–24 15.2 1.64 (0.88–3.06) 1.67 (0.88–3.16) 1.63 (0.86–3.10) 1.73 (0.87–3.46)
Control at work
High 11.6 1.00 1.00 1.00 1.00
Intermediate 12.8 1.05 (0.80–1.39) 1.07 (0.81–1.41) 0.99 (0.74–1.31) 0.98 (0.74–1.30)
Low 16.1 1.31 (1.00–1.71) 1.33 (1.00–1.76) 1.13 (0.84–1.51) 1.12 (0.83–1.50)
Demand at work
Low 10.2 1.00 1.00 1.00 1.00
Intermediate 12.6 1.29 (0.99–1.69) 1.28 (0.97–1.68) 1.22 (0.92–1.61) 1.21 (0.91–1.60)
High 18.8 1.96 (1.53–2.51) 1.94 (1.47–2.56) 1.71 (1.28–2.27) 1.68 (1.27–2.24)
Support at work
High 11.4 1.00 1.00 1.00 1.00
Intermediate 12.2 1.08 (0.82–1.43) 1.08 (0.82–1.43) 1.00 (0.75–1.32) 1.00 (0.75–1.32)
Low 16.6 1.48 (1.14–1.93) 1.50 (1.15–1.96) 1.31 (1.00–1.61) 1.30 (0.99–1.71)
Job types
Administrative 12.5 1.00 1.00 1.00
Professional 14.1 0.74 (0.43–1.27) 0.70 (0.41–1.20) 0.70 (0.41–1.20)
Clerical 13.9 0.80 (0.46–1.38) 0.77 (0.44–1.38) 0.77 (0.44–1.34)
Office support 10.3 0.61 (0.32–1.18) 0.60 (0.31–1.16) 0.64 (0.33–1.23)
Work hours
≤8 h 12.5 1.00 1.00 1.00
8–9 h 14.6 1.03 (0.79–1.33) 1.01 (0.77–1.31) 1.03 (0.79–1.34)
9–11 h 16.1 1.07 (0.80–1.43) 1.06 (0.79–1.43) 1.08 (0.80–1.45)
>11 h 10.9 0.73 (0.37–1.43) 0.70 (0.36–1.38) 0.72 (0.37–1.41)
Job satisfaction
Yes 10.3 1.00 1.00
No 19.7 1.81 (1.44–2.26) 1.78 (1.42–2.23)
Married
Yes 13.4 1.00
No 14.5 1.17 (0.87–1.59)
Longstanding illness
No 12.0 1.00
Yes 18.0 1.60 (1.24–2.01)

Correlations evaluated simultaneously using multiple logistic regressions and expressed as odds ratios with 95% confidence intervals. Abbreviations: OR, odds ratio; 95%CI, 95% confidence interval. Statistically significant odds ratios are shown in bold. Model 1 is adjusted for psychosocial risk factors at work (control, demand and support), sex and age. Model 2 is adjusted for model 1 plus job types and work hours. Model 3 is adjusted for model 2 plus job dissatisfaction. Model 4 is adjusted for model 3 plus marital status and longstanding illness.

Table 5 shows job stress differences in sleep disturbance before and after being adjusted for job dissatisfaction. When adjusted for sex, age, and job stress, high demand and low support were significantly associated with sleep disturbance (ORs=1.86 and 1.59 respectively). When variables of job types and work hours were added to Model 1, the adjusted OR in high demand decreased (OR=1.59) and that of low support increased (OR=1.62), although both ORs were significantly associated with sleep disturbance. When further adjusted for job dissatisfaction, the adjusted ORs of job stress in sleep disturbance were attenuated in all variables. At that point high demand and low support at work were significantly associated with sleep disturbance, while job dissatisfaction was significantly related to sleep disturbance (OR=1.62) independently. Although longstanding illness was significantly associated with sleep disturbance, the association of both job stress differences and job dissatisfaction with sleep disturbance changed little after being adjusted for marital status and longstanding illness. Furthermore, the statistical significance of sex and age remained the same in all models except for those aged 45–54.

Table 5. The association with job characteristics in sleep disturbance before and after adjustment for job dissatisfaction
Prevalence of sleep disturbance % Model 1 Model 2 Model 3 Model 4
OR (95%CI) OR (95%CI) OR (95%CI) OR (95%CI)
Sex
Men 8.8 1.00 1.00 1.00 1.00
Women 12.9 1.39 (1.09–1.79) 1.32 (1.02–1.71) 1.34 (1.03–1.73) 1.32 (1.02–1.72)
Age
55– 12.9 1.00 1.00 1.00 1.00
45–54 10.1 0.71 (0.48–1.06) 0.67 (0.44–1.00) 0.65 (0.43–0.99) 0.70 (0.46–1.06)
35–44 11.3 0.77 (0.52–1.16) 0.71 (0.46–1.08) 0.67 (0.44–1.02) 0.78 (0.51–1.20)
25–34 7.0 0.49 (0.32–0.77) 0.44 (0.28–0.70) 0.41 (0.26–0.66) 0.49 (0.30–0.81)
–24 12.4 0.89 (0.48–1.66) 0.77 (0.41–1.47) 0.75 (0.39–1.43) 0.89 (0.44–1.82)
Control at work
High 8.6 1.00 1.00 1.00 1.00
Intermediate 10.4 1.22 (0.90–1.67) 1.26 (0.92–1.72) 1.18 (0.86–1.62) 1.18 (0.86–1.62)
Low 10.9 1.22 (0.89–1.66) 1.32 (0.96–1.83) 1.15 (0.82–1.61) 1.14 (0.82–1.60)
Demand at work
Low 7.8 1.00 1.00 1.00 1.00
Intermediate 9.3 1.25 (0.92–1.67) 1.13 (0.83–1.55) 1.09 (0.79–1.50) 1.08 (0.79–1.49)
High 13.5 1.86 (1.40–2.47) 1.59 (1.16–2.18) 1.42 (1.03–1.96) 1.41 (1.02–1.94)
Support at work
High 7.6 1.00 1.00 1.00 1.00
Intermediate 10.0 1.33 (0.97–1.84) 1.34 (0.97–1.85) 1.26 (0.91–1.74) 1.26 (0.91–1.75)
Low 12.1 1.59 (1.16–2.16) 1.62 (1.19–2.20) 1.44 (1.05–1.98) 1.43 (1.04–1.96)
Job types
Administrative 7.9 1.00 1.00 1.00
Professional 11.4 1.40 (0.73–2.66) 1.36 (0.71–2.60) 1.36 (0.71–2.59)
Clerical 8.8 1.13 (0.58–2.21) 1.12 (0.57–2.19) 1.11 (0.57–2.18)
Office support 7.4 0.89 (0.41–1.93) 0.89 (0.41–1.93) 0.95 (0.44–2.08)
Work hours
≤8 h 8.8 1.00 1.00 1.00
8–9 h 11.6 1.25 (0.93–1.68) 1.24 (0.92–1.66) 1.29 (0.96–1.73)
9–11 h 11.7 1.24 (0.88–1.73) 1.24 (0.88–1.74) 1.26 (0.90–1.77)
>11 h 8.9 1.02 (0.49–2.14) 0.99 (0.47–2.08) 1.03 (0.49–2.15)
Job satisfaction
Yes 7.9 1.00 1.00
No 13.9 1.62 (1.25–2.09) 1.59 (1.23–2.05)
Married
Yes 10.1 1.00
No 9.8 1.10 (0.77–1.57)
Longstanding illness
No 8.1 1.00 (1.47–2.43)
Yes 15.0 1.89 (1.47–2.43)

Correlations evaluated simultaneously using multiple logistic regressions and expressed as odds ratios with 95% confidence intervals. Abbreviations: OR, odds ratio; 95%CI, 95% confidence interval. Statistically significant odds ratios are shown in bold. Model 1 is adjusted for psychosocial risk factors at work (control, demand and support), sex and age. Model 2 is adjusted for model 1 plus job types and work hours. Model 3 is adjusted for model 2 plus job dissatisfaction. Model 4 is adjusted for model 3 plus marital status and longstanding illness.

Discussion

This paper set out to examine the role of being satisfied-dissatisfied on the job as a relative factor in stress-related mental health problems and as a contributor to change in the strength of the association between psychosocial risks at work and these health problems. In mental functioning, the associations with psychosocial risks at work declined significantly after being adjusted for job dissatisfaction, especially with low job control and low job support. In relation to subjective fatigue symptoms, association with psychosocial risks at work was attenuated significantly in subjects experiencing low job control. In sleep disturbance, the associations with psychosocial risks at work were attenuated in high demand and low support at work, though not significantly. Additionally, job dissatisfaction was independently and strongly associated with stress-related mental health problems, and contributed a substantial degree to the change of association between psychosocial risks at work and stress-related mental health problems.

This study also found that psychosocial risk factors at work, in which job control, demand, and support were measured, has association with poor mental functioning, feelings of unexplained fatigue, and sleep disturbance. In the Japanese cohort, the same result was obtained; psychosocial risk factors at work were associated with poor health in our previous study of Japanese civil servants12, 26, 34). In addition, unlike the results found in other health outcome models, the oldest age group, 55 and older, generated poor results in the sleep model, which may be an age effect of that category. This result was also consistent with previous studies26, 37,38,39). Additionally, job dissatisfaction was associated with each health outcome independently. This result is also consistent with various other studies including meta-analysis, which measured the association between job dissatisfaction factors and stress-related health problems16, 28). Most importantly, the differences in the ‘job satisfied − job dissatisfied’ subjective category was the strongest contributor to attenuate the association between stress-related problems and psychosocial risks at work (e. g. control, demand and support at work).

The strength of associations of psychosocial risk factors (especially, control and support at work) with mental health problems attenuated significantly when adjusted for job satisfaction in this study. Among all work characteristics (e.g. job type, work hours, psychosocial risk factors, and job dissatisfaction) that we examined in connection with mental health problems, we found that job dissatisfaction affected the associations between psychosocial risk factors and mental health problems more than other work characteristics, such as work hours or job types. This result may reflect a specific range of psychosocial risk factors at work, that is, whether they are low, intermediate, or high, they may serve as a suppresser to interest and motivation at work, which can be inferred from Table 225, 29); previous studies revealed no significant ‘satisfied’ or ‘not satisfied’ state at work based on job types and work hours40). In these cases, “job dissatisfaction” may be estimated to not only be an independently relevant factor to stress-related health, but may serve as a contributor to decrease the risk of psychosocial factors at work as well16, 23, 28).

It is worth noting that the odds ratio of job dissatisfaction was high in mental functioning, fatigue, and sleep disturbance in descending order, and the contribution to decline association between psychosocial risk factors at work and the health outcomes weakened in the same order. These differences in relation to the three health outcomes may be indicative to the differences in the impact of “physical” and “psychological” symptoms on job (dis) satisfaction factors. According to related reports, the measures of mental health that had a stronger association with job satisfaction factors than did the measures of physical health16, 18). In this study, the association of psychosocial risks at work and job satisfaction with the health outcomes showed almost no change after being adjusted for longstanding illnesses. This may suggest that the health outcomes used in this study (i.e., mental function, fatigue, and sleep disturbance), were associated more with mental health problems than with physical problems37, 39). Yet, the fact that job dissatisfaction contributed to poor mental functioning, fatigue, and sleep disturbance in descending order may indicate that job dissatisfaction has a stronger association with particular poor health problems that are vulnerable to the dynamics of psychological mechanisms23, 41).

Interestingly, after adjusted for being satisfied-dissatisfied on the job, even though the adjustment did not affect the level of association between age and gender differences and health outcomes, the strength of the association of psychosocial risk factors at work (e.g. control, demand, and support in this study) alone with each outcome was specifically attenuated. This may be considered reasonable given that being satisfied at work generally works as a buffer against negative impact of job stressors, while elements of “job satisfaction” in work characteristics is an independently relevant factor in mental health problems1828). Sekine et al. suggests that differences between men and women in the association with mental functioning can be explained by “work-family conflict”34). In our results, however, although gender differences were relevant to mental health problems, there was no difference between men and women in the association of job satisfaction with psychosocial work characteristics.

It should be mentioned that there are several limitations that may affect the interpretation of the results of this study. First, there were issues with the concept and measurement of job satisfaction per se. Theoretically an individual may be satisfied with many facets of their job but still be dissatisfied with the job overall. Previous studies examined how different facets of job satisfaction contributed to overall job satisfaction, demonstrating that overall job satisfaction was strongly associated with facets of job satisfaction, especially with intrinsic factors40). Also in this study, measurement using single items alone revealed that overall job satisfaction was associated strongly with each different stress-related outcome. This result therefore delivers an important finding in which we relied on index dichotomized for an overall “being satisfied or dissatisfied” rating using a single variable that provided a more manageable measurement32, 33)

Second, we used 4 job types, Administrative, Professional, Clerical, and Office Support following the major groups of Japan’s census. Each job type may include a variety of occupations; Professional, for example, includes technicians, teachers and hospital workers. While, our study set a frame based on the four job types of the census, we found that difference that existed among the four job types in association with mental health problems disappears when adjust for age and psychosocial risk factors at work. This result was consistent with previous studies26), which led us to conclude that the difference in association that existed among the four job types and mental health problems is explained rather by differences in psychosocial risks at work. If we examine job types in medium or minor groups, we may find a particular job has more association with mental health problem. Though this is not the framework of present study, we would assume a more detailed study specifically focused on certain occupations would reveal more specific mental health associations.28).

Third, the present study is a cross-sectional study, which makes it hard to determine the causality of the associations of job satisfaction or psychosocial work characteristics with stress-related symptoms, though this study did reveal a weak relationship between job dissatisfaction and job stress factors. However, previous studies found little evidence of a factor that positively changes association between job stress and mental health26, 34). Since job dissatisfaction, job stress, and mental health are intertwined in their relations in a complex way, longitudinal research is necessary to clarify the causal nature of these associations.

Forth, since the subjects of this study are all civil servants, it may be difficult to generalize the results. For example, compared to private sector workers, civil servants tend to work under uniform conditions in some aspects of work: these conditions include high education levels, stable wages, and guaranteed job stability with no threat of unemployment until the age of retirement42, 43). In addition, although the civil service does include manual workers such as office support workers, drivers, protective service workers, and other blue-collar occupations, civil servants tend to include more white-collar workers than the general occupational population. This result showed that being satisfied on the job may play a role in contributing to not only the level of job control and support but also the level of demand to which non-manual workers were more exposed when compared to white collar workers with regard to mental health problems44). Therefore this result may have applicability to general work population.

Conclusion

Job dissatisfaction was independently associated with different stress-related mental health problems (i.e., poor mental functioning, fatigue, and sleep disturbance) among Japanese civil servants. In addition, being satisfied on the job tended to attenuate the association of psychosocial risk factors at work with mental health problems singularly. Although longitudinal research is necessary, the factor of satisfaction at work may play an important role for the maintenance and the improvement of employees’ mental health under stressful work conditions.

Acknowledgements

We are indebted to the members of the personnel section of the local government who took part and cooperated in this study and all the civil servants in that the local government level who participated in this study. This study was in part funded by the Ministry of Health, Labour and Welfare, Japanese Society for the Promotion of Science, Occupational Health Promotion Foundation, Universe Foundation (98.04.017), Daiwa Anglo-Japanese Foundation (03/2059), Great Britain Sasakawa Foundation (2551). Funding organizations were not involved in the design, conduct, interpretation, and analysis of the study, nor in the review or approval of the manuscript.

References
  • 1)  Expert forecast on emerging psychosocial risks related to occupational safety and health. In: European agency for safety and health 2007. European Community, Luxembourg. http://osha.europa.eu/en/publications/reports. Accessed April 27, 2012.
  • 2)  Cooper CL, Locke EA (2000) Industrial and organizational psychology: linking theory with practice. Blackwell, Oxford.
  • 3)  Nieuwenhuijsen K, Bruinvels D, Frings-Dresen M (2010) Psychosocial work environment and stress-related disorders: a systematic review. Occup Med 60, 277–86.
  • 4)  Karasek RA (1979) Job demands, job decision latitude and mental strain: implications for job design. Adm Sci Q 24, 285–308.
  • 5)  Karasek RA, Theorell TT (1990) Healthy Work: Stress, Productivity, and the Reconstruction of Working Life. Basic Books, New York.
  • 6)  Johnson JV, Hall EM (1988) Job strain, work place social support, and cardiovascular disease: a cross-sectional study of a random sample of the Swedish working population. Am J Public Health 78, 1336–42.
  • 7)  Lallukka T, Lahelma E, Rahkonen O, Roos E, Laaksonen E, Martikainen P, Head J, Brunner E, Mosdol A, Marmot M, Sekine M, Nasermoaddeli A, Kagamimori S (2008) Associations of job strain and working overtime with adverse health behaviors and obesity: evidence from the Whitehall II Study, Helsinki Health Study, and the Japanese Civil Servants Study. Soc Sci Med 66, 1681–98.
  • 8)  Chandola T, Brunner E, Marmot M (2006) Chronic stress at work and the metabolic syndrome: prospective study. BMJ 332, 521–5.
  • 9)  Bosma H, Marmot MG, Hemingway H, Nicholson AC, Brunner E, Stansfeld SA (1997) Low job control and risk of coronary heart disease in Whitehall II (prospective cohort) study. BMJ 314, 558–65.
  • 10)  Paterniti S, Niedhammer I, Lang T, Consoli SM (2002) Psychosocial factors at work, personality traits and depressive symptoms: longitudinal results from the GAZEL Study. Br J Psychiatry 181, 111–7.
  • 11)  Martikainen P, Lahelma E, Marmot M, Sekine M, Nishi N, Kagamimori S (2004) A comparison of socioeconomic differences in physical functioning and perceived health among male and female employees in Britain, Finland and Japan. Soc Sci Med 59, 1287–95.
  • 12)  Sekine M, Chandola T, Martikainen P, Marmot M, Kagamimori S (2009) Socioeconomic inequalities in physical and mental functioning of British, Finnish and Japanese civil servants: role of job demand, control and work hours. Soc Sci Med 69, 1417–25.
  • 13)  Stansfeld SA, Head J, Marmot M (1998) Explaining social class differences in depression and well-being. Soc Psychiatry Psychiatr Epidemiol 33, 1–9.
  • 14)  Martikainen P, Stansfeld SA, Hemingway H, Marmot M (1999) Determinant of socioeconomic differences in change in physical and mental functioning. Soc Sci Med 49, 499–507.
  • 15)  Adler NE, Snibbe AC (2003) The role of psychosocial processes in explaining the gradient between socioeconomic status and health. Curr Dir Psychol Sci 12, 119–23.
  • 16)  Faragher EB, Cross M, Cooper CL (2005) The relationship between job satisfaction and health: a meta-analysis. Occup Environ Med 62, 105–12.
  • 17)  Tokuda Y, Hayano K, Ozaki M, Bito S, Yanai H, Koizumi S (2009) The interrelationships between working conditions, job satisfaction, burnout and mental health among hospital pcysicians in Japan: a path analysis. Ind Health 47, 166–72.
  • 18)  Spector PE (2010) Job satisfaction: application, assessment, causes, and consequences. Sage, Thousand Oaks.
  • 19)  Nakata A, Takahashi M, Irie M, Ray T, Swanson NG (2011) Job satisfaction, common cold, and sickness absence among white-collar employees: a cross-sectional survey. Ind Health 49, 116–21.
  • 20)  Mein G, Martikainen P, Stansfeld SA, Brunner E, Fuhrer R, Marmot M (2000) Predictors of early retirement in British civil servants. Age Ageing 29, 529–36.
  • 21)  Hemingway H, Marmot M (1999) Evidence based cardiology: psychosocial factors in the aetiology and prognosis of coronary heart disease: systematic review of prospective cohort studies. BMJ 318, 1460–7.
  • 22)  Sales SM, House J (1971) Job dissatisfaction as a possible risk factor in coronary heart disease. J Chronic Dis 23, 861–73.
  • 23)  Hurrell JJ Jr, McLaney MA (1988) Exposure to job stress: a new psychometric instrument. Scand J Work Environ Health 14 (suppl 1): 27–8.
  • 24)  de Croon EM, Blonk RWB, de Zwart BCH, Frings Dresen MHW, Broersen JPJ (2002) Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers. Occup Environ Med 59, 356–61.
  • 25)  Rydstedt LW, Ferrie J, Head J (2006) Is there support for curvilinear relationships between psychosocial work characteristics and mental well-being? Cross-sectional and long-term data from the Whitehall II study. Work Stress 20, 6–20.
  • 26)  Sekine M, Chandola T, Martikainen P, Marmot M, Kagamimori S (2006) Socioeconomic inequalities in physical and mental functioning of Japanese civil servants: explanation from work and family characteristics. Soc Sci Med 63, 430–45.
  • 27)  Hotopf M, Wessely S (1997) Stress in the workplace: unfinished business. J Psychosom Res 43, 1–6.
  • 28)  Ramirez AJ, Graham J, Richards MA, Cull A, Gregory WM (1996) Mental health of hospital consultants: the effects of stress and satisfaction at work. Lancet 347, 724–8.
  • 29)  Evans S, Huxley P, Gately C, Webber M, Mears A, Pajak S, Medina J, Kendall T, Katona C (2006) Mental health, burnout and job satisfaction among mental health social workers in Engaland and Wales. Br J Psychiatry 188, 75–80.
  • 30)  Tennant C (2001) Work-related stress and depressive disorders. J Psychosom Res 51, 697–704.
  • 31)  Stansfeld SA, Bosma H, Hemingway H, Marmot M (1998) Psychosocial work characteristics and social support as predictors of SF-36 health functioning: the Whitehall II study. Psychosom Med 60, 247–55.
  • 32)  Weiss HM (2002) Deconstructing job satisfaction: separating evaluations, beliefs and affective experiences. Hum Resour Manage Rev 12, 173–94.
  • 33)  Wanous JP, Reichers AE, Hudy MJ (1997) Overall job satisfaction: how good are single-item measures? J Appl Psychol 82, 247–52.
  • 34)  Sekine M, Chandola T, Martikainen P, Marmot M, Kagamimori S (2010) Sex differences in physical and mental functioning of Japanese civil servants: explanations from work and family characteristics. Soc Sci Med 71, 2091–9.
  • 35)  Ware JE (1993) SF-36 health survey manual & interpretation guide. The Health Institute, New England Medical Center, Boston.
  • 36)  Fukuhara S, Ware JE, Kosinski M, Wada S, Gandek B (1998) Psychometric and clinical tests of validity of the Japanese SF-36 health survey. J Clin Epidemiol 51, 1045–53.
  • 37)  Åkerstedt T, Fredlund P, Gillgerg M, Jansson B (2002) Work load and work hours in relation to disturbed sleep and fatigue in a large representative sample. J Psychosom Res 53, 585–8.
  • 38)  Åkerstedt T, Knutsson A, Westerholm P, Theorell T, Alfredsson L, Kecklund G (2002) Sleep disturbances, work stress and work hours: a cross-sectional study. J Psychosom Res 53, 741–8.
  • 39)  Åkerstedt T, Knutsson A, Westerholm P, Theorell T, Alfredsson L, Kecklund G (2004) Mental fatigue, work and sleep. J Psychosom Res 57, 427–33.
  • 40)  Tatsuse T, Sekine M (2011) Explaining global job satisfaction by facets of job satisfaction: the Japanese civil servants study. Environ Health Prev Med 16, 133–7.
  • 41)  Stansfeld S, Candy B (2006) Psychosocial work environment and mental health: a meta-analytic review. Scand J Work Environ Health 32, 443–62.
  • 42)  Moncada S (1999) Working conditions and social inequalities in health. J Epidemiol Community Health 53, 390–1.
  • 43)  Kawasaki K, Nagashima S (2007) What effects do the high salaries for local public employment have on the regional economy in Japan? Gov Auditing Rev 36, 107–23.
  • 44)  Johnson JV, Hall EM (1995) Class, work, and health. In: Society and health, Amick BC, Levine S, Tarlov AR, Walch DC (Eds.), 247–71,Oxford University Press, New York.
 
© 2013 by National Institute of Occupational Safety and Health
feedback
Top