Results

The mean (SD, range) age of the study population was 50.8 (10.4, 18–65) for men and 50.8 (9.4, 19–65) for women. There were more single men than single women. Compared with women, more men had attained a higher managerial status or were engaged in blue collar occupations, worked longer hours, and listed higher educational levels. Men smoked and consumed alcohol much more than women. The physical activity level was also higher for men than women (all p<0.01).

The job characteristics scores, according to sex and selected variables, are shown in table 1. Men had higher job demands and job control scores than women. Because of a substantial difference in the level of job control, the job strain level (the ratio of demands to control) was significantly higher for women than men. The younger men and women had higher job demand scores than the similarly placed older workers. The job control score was higher for younger than older men, thus both groups yielded the same level of strain. Younger women workers had higher strain scores than the older women. In both sexes, similar trends were found within the same occupational strata and level of educational attainment. With the exception of job demands for women, workers in managerial jobs and employment as white collar workers had higher demands and control scores than their respective counterparts. Better educated workers had higher control scores. The level of strain was significantly higher for the subordinates, blue collar workers, and those who were less educated.

According to the hypertension criterion, its prevalence in our sample was 25.1% (n=790) for men and 18.6% (n=631) for women. When compared with a representative population in Japan, the sample used here seemed to have lower blood pressure levels.27

Table 2 shows the prevalence of hypertension and normotension for the respective groups with selected variables. The prevalence of hypertension rose with increasing age for both sexes. In men, the age adjusted prevalence of hypertension was higher for those employed as white collar workers, those who were unmarried, had a family history of hypertension, were ex-smokers, consumed more alcohol, were physically more inactive, and were heavier than their respective counterparts. Similar associations were found in women for family history of hypertension, physical activity, and body mass index. However, hypertension in women was more common in less well educated women and in smokers. Marital status or alcohol intake was not associated with the prevalence of hypertension among women.

For men, the prevalence of hypertension increased as the level of job control decreased and the levels of psychological demands and job strain increased. Only the association between job strain and the prevalence of hypertension was significant, whereas neither job control nor demands was significantly related to the prevalence of hypertension. In women, the associations between job characteristics and the prevalence of hypertension were inconsistent.

Table 3 shows the results of multiple logistic analyses. For men, age, marital status, family history of hypertension, alcohol intake, physical activity index, and body mass index were significantly and independently associated with the prevalence of hypertension. Job strain had a significant association with hypertension after adjusting for associated variables. Even after adjusting for all the possible confounders, including working conditions and education, the association remained significant (odds ratio (OR) 1.17; 95% confidence interval (95% CI) 1.04 to 1.32). In women, age, lower educational status, family history of hypertension, and body mass index were significantly associated with hypertension; however, the association between job strain and hypertension was not significant.

Table 4 shows the results of multiple logistic analyses based on four sociodemographic strata: manager or subordinate; white collar or blue collar worker; lower or higher than compulsory education level; and younger or older(<55 or 56–65) workers (all separated by sex). For men, each stratified category consistently showed an increased relative risk of job strain; but a significant excess risk of job strain was found for the categories of: subordinate, blue collar, lower educational attainment, and older age. Particularly, the differences between jobs (manager or subordinate) and employment (white or blue collar) were substantial. For women, no association between job strain and hypertension could be detected by the stratified analysis.

Although adjustment for occupation may lead to an overadjustment for the effect of job strain on health outcomes,14 28adjustments were made for occupation in the final model. The magnitude of the association was slightly lower but remained significant (OR 1.14; 95% CI 1.01 to 1.28).

The analyses were performed for each occupation. Relatively high ORs were found for male and female construction workers and male transport workers. For male construction workers, a significant OR was found despite the few cells (see appendices 1 and 2 for the job characteristics scores and the results of multiple logistic regression analyses for each occupation).

Multiple regression analyses were conducted to see the linear effect of the job strain index on mean systolic and diastolic pressures. In these analyses, adjustment was made for the use of antihypertensive medication as well as the other confounders noted. No significant associations were found.

Discussion

Job strain was positively associated with the prevalence of hypertension in Japanese men over a wide range of occupations. The excess prevalence amounted to 18% after adjustments for age, employment, marital status, family history of hypertension, smoking habits, alcohol intake, physical activity, and body mass index. With a crude assumption of the worst tertile job strain score defined as exposed, the aetiological fraction (population attributable risk) of the study population with hypertension was estimated to be 5.6%, which, from a public health point of view, would not be negligible.1 As in other studies, only a combination of high demands and low control was related to the prevalence of hypertension.4 5 20 29 The magnitude of the association seemed to be strongest for the lower social classes, where the level of job strain was higher than for their respective counterparts, and less so in the older age group. For the women in this sample, job strain was not associated with hypertension.

This sample seemed to underrepresent hypertension, perhaps because the invitation to participate in the study did not insist that those who were receiving care in hospitals and clinics for cardiovascular diseases should sign up with the others. However, this in itself is unlikely to produce a selective bias that would lead a normotensive worker who perceived his or her job as psychologically less demanding or one where the control was high to participate in the study. Observed associations between hypertension and behavioural variables other than job characteristics were similar to those reported in earlier epidemiological studies.30-33 Although the studied sample was not truly representative of the Japanese working population, these findings may reflect a profile of hypertension among Japanese workers.

One of the debates about the research methodology of the job strain model is: has the study population been selected from a few well chosen occupations or from a wide range of occupations?1It is thought that a few well chosen occupations may be suitable for scrutinising specific job characteristics that affect workers' health in the selected occupations. Homogeneous samples may make it possible to illuminate the pure job strain effect on health outcome. However, the job demand-control questionnaire is often criticised as being too simple a tool to provide an adequate description of the psychosocial work environment. This low level of sophistication may not be powerful enough to produce a contrast in the exposure to stress within the small variance of a homogeneous sample. Occupation specific measures of job strain would be necessary to study a specific occupation in depth.34 Alternatively, in a diverse population such as this sample, a relatively wide variability of the stress level within the occupations is expected, which may increase the power to establish associations. Another advantage is the possibility of testing the job strain effect in several strata that the heterogeneity provides. Although only a weak association was found in our total sample, the stratified analyses showed some clear associations.

The finding of a job strain effect in male blue collar workers was similar to those obtained in recent studies, in which it was proved that the demand-control model is a more powerful predictor of cardiovascular disease in male blue collar workers than in their white collar counterparts.7 35 36 The consistent finding about job and education may provide support for the notion that work related psychosocial factors explain the reported health disadvantage of populations from the lower social classes.37 38 The findings that even in Japan where the general belief is that there is relatively high homogeneity of wealth and health, show the importance of the social class issue in any analysis of job strain.

The association between job strain and hypertension seemed to be stronger in the older than in the younger age group. Because the study population was recruited from relatively rural communities, and changing occupation is unlikely (particularly in the older age group), this finding might indicate a cumulative effect of job strain on hypertension.6 However, because the oldest male category (56–65, 57.1% of the hypertensive men) accounted for most of the relation between job strain and hypertension, a definitive conclusion must await further studies.

Men and women may be affected differently by job characteristics. The sex differences found were unlikely to emerge from the difference in their stress related coping patterns—such as alcohol drinking5 39—because many lifestyle variables were adjusted for in the analysis. However, a sex difference may exist in the effectiveness of coping.40 The following, which might explain the sex differences, were not considered here: full time versus part time work, work preferences, and concepts about the value of work.41 42 It should be noted that, according to the findings of this study, single male workers had a higher prevalence of hypertension than those who were married, which suggests that factors outside of work may affect the workers' health. Sex differences in the regulation of the sympathetic nervous system is another possible explanation.43

The magnitude of the association found was very weak: the linear analyses did not produce any significant associations. One of the reasons may be due to a methodological weakness—the use of casual blood pressure measurements for the outcome instead of ambulatory blood pressure monitoring. Previous studies indicate that ambulatory blood pressure monitoring is more sensitive for detecting an association.5 19 20 29 In our study, blood pressure was measured at the person's health examination, not at his or her work site. Because a fully automated sphygmomanometer was used to measure blood pressure, observer errors in measurement were unlikely. The self reported history of hypertension and actual blood pressure levels were highly correlated. Thus substantial misclassification of the subjects was unlikely. However, particularly in occupational stress research, introducing ambulatory blood pressure monitoring in several situations (including at work) may make the association more precise,19 20 29 which is difficult to do in large scale epidemiological studies.

The manner in which the psychological job characteristics are measured should be considered. The reliability and validity of the questionnaire on job characteristics were confirmed in other Japanese settings.23 24 In this sample, too, the questionnaire was found to be internally consistent. Interrelations among the job characteristic scores, sex, and occupation were in concordance with previous studies.35 41 44 However, the bias associated with self reporting is often criticised in job strain research. For example, those who are aware that their blood pressure is increased may let their health be affected by external work conditions.45 Because 50%–70% of our cohort members have undergone yearly medical examinations, most of the participants were presumably aware of their blood pressure levels. This may account for some bias. It should be noted that participants were asked questions about their job characteristics, not their feelings about stress. The demand-control model may relate more to objective measures of stressor than other questionnaires.46 Still, cultural differences may exist in reporting patterns for psychosocial measures.47 To confirm this, more objective measures, such as an average measure of job characteristics and measures by outside expert observers are needed.1 28 Although changing occupation is considered to be unlikely in the rural settings used here, the cumulative effects of job strain should be considered to confirm the results by using such a measure as the job exposure matrix.48

Our findings provide limited support for the hypothesis that job strain is related to high blood pressure among Japanese male workers, which is independent of possible confounding factors. Male workers in the lower social classes and who are older seem to be more susceptible to the effect of job strain on hypertension. These populations may be target groups for further analyses or intervention.