The Association of Job Strain and Health Behaviours in Men and Women

International Journal of Epidemiology International Epidemiological Association 1997 Vol. 26, No. 3 Printed in Great Britain The Association of Job Strain and Health Behaviours in Men and Women WENDY L HELLERSTEDT* AND ROBERT W JEFFERY Hellerstedt W L (Maternal and Child Health Program, Division of Health Management and Policy, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA) and Jeffery R W. The association of job strain and health behaviours in men and women. International Journal of Epidemiology 1997; 26: 575 583. Background. This study examined whether self-reported job strain, defined by the Karasek model, was associated with some early, potentially modifiable cardiovascular (CVD)-related health characteristics. Methods. Data were gathered in a 1989 cross-sectional survey of 3843 randomly selected men and women employees of 32 worksites in Minnesota. Sex-stratified crude and multivariate analyses examined the independent association of job psychological demands, latitude, and the combination of these two job domains (i.e. strain), to body mass index (BMI), smoking, exercise, and dietary fat intake. Results. Job demands was positively associated with smoking, smoking intensity, and high fat intake in men and with BMI and smoking intensity in women. Job latitude was positively associated with exercise in men and women. High-strain men smokers smoked more than other workers and high-strain women had higher BMI than other women. Conclusions. Overall, self-reported job demands, latitude, and job strain were associated with some CVD-related health characteristics, but the effects were not similar in magnitude or direction for all characteristics and they varied by sex. Keywords: job strain, body mass index, smoking, dietary fat, physical activity Studies with various methodologies have reported that job pressures and job strain are positively associated with cardiovascular disease (CVD) morbidity and mortality, 1 13 although some have found weak or no relationships. 14 16 While job strain appears to be associated with hypertension, other mechanisms may link strain to CVD risk. 17 There may be positive and/or negative work spillover 18 20 to non-work life. If job strain affects social functioning, mental or emotional health, 21,22 job strain could influence the willingness or the ability of workers to engage in health-enhancing behaviours, thus influencing CVD risk. Studies of job pressures or strain and smoking, 15,16,23 29 physical activity 16,24 and body weight 16,23,27,30 have been inconclusive. To our knowledge there have been no studies on diet and job strain. Further, few studies of CVD-related health characteristics and job strain have included women. 1,6,23,24,27,31 The Karasek model 20,32 describes two dimensions of working life that influence job strain: the psychological * Maternal and Child Health Program, Division of Health Management and Policy, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. Reprint requests to: Wendy L Hellerstedt, Maternal and Child Health Program, Division of Health Management and Policy, School of Public Health, Box 97, Rm#D355 Mayo Building, University of Minnesota, Minneapolis, MN 55455, USA. demands of the job and the worker s ability to use skills or authority to address those demands (i.e. latitude). The demand-latitude model describes four job types. When job demands and latitude are high, the model describes the job as active : the worker s skills and control are adequate for the job. Karasek 20 postulated that active workers are stimulated and motivated to develop new behaviours both on and off the job. Passive workers have low demands and low latitude. Such workers may experience a decline, over time, in activity and general problem-solving skills. Low-strain workers have low demands, but high latitude. The jobs that are hypothesized by Karasek to have the most negative effects on health are high-strain jobs, where demands are high but the worker s ability to use skill or authority to address these demands is low. 20 This study examined the proximal, and potentially intervenable, health behaviours and characteristics that may link job demands, latitude, and strain, as defined by the Karasek model, to CVD risk in a sample of 3843 workers. Because reported job strain varies between men and women, 1,6,8,23,24,31,33 analyses were stratified by sex. METHODS Study Sample Data were collected from the 32 worksites in the Minneapolis St Paul area of Minnesota, USA, that 575

576 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY participated in the Healthy Worker Project, an intervention study for the control of smoking and obesity. 34 Worksites were randomly selected from a comprehensive list of all sites in the area with 300 900 employees. Recruitment of eligible sites was 28%. Participating sites included 12 public and 20 private institutions; eight were manufacturing sites. In 1989, 200 men and women workers at each site were randomly selected for a crosssectional, self-administered health behaviour survey which also assessed socio-demographic and job-related characteristics, including perception of job strain. The average completion rate for the on-site survey was 77%, ranging from 50% to 93% by site. Of the workers who completed on-site surveys, 7% were excluded from analyses because they were part-time or shift workers. Height and weight were measured and an additional 555 survey respondents were excluded because they did not attend the measurement clinic. Finally, 66 workers were excluded because there were missing data on one or more of the job-strain questions. Thus, from a sampling frame of 6400 workers, losses due to subject nonresponse and other exclusions reduced the number of subjects for analyses to 3843 (60%). Study subjects and the group of 968 non-respondents/exclusions for whom some data were available were compared for differences on socio-demographic and job characteristics. Study subjects were significantly (P 0.05) more likely than non-subjects to be men, married, better educated, white, professional class, have annual salaries $35,000, work more hours per week, and work in jobs that did not demand vigorous physical activity. Job Characteristics Questions about job strain were based on Karasek s Job Content Instrument. 35 Decision latitude was assessed by eight questions about the worker s ability to use and develop skills (i.e. job involves learning new things, non-repetitive work, creativity, a high level of skill, and variety) and exert authority (i.e. freedom to decide how to perform work, ability to make decisions on one s own, and having a lot of say about what happens on the job). Five questions addressed the psychological demands of the job: i.e. working very fast, working very hard, having enough time to get the work done, freedom from conflicting demands, and requests to do an excessive amount of work. Subjects had four possible responses to each of the 13 questions: strongly disagree, disagree, agree, or strongly agree. Responses were weighted and summed to define the two work dimensions. 35 Job latitude scores ranged from 12 to 48, with higher scores indicating more worker skill discretion and authority. Scores for job demands ranged from 14 to 48, with higher scores indicating jobs more demanding in pace and intensity. Cronbach s alpha for the decision latitude scale was 0.74 for men and 0.71 for women and 0.73 for men and 0.75 for women for the job demands scale. Job latitude and demands scores were divided into quartiles for analyses. Quartiles for job latitude were scores of 12 32, 33 36, 37 40, and 41 48. Quartiles for job demands were scores of 14 29, 30 32, 33 36, and 37 48. To create a variable for job strain, high and low latitude and demands were defined by median cutpoints on the latitude and demands scales (37 and 33, respectively). These cutpoints were derived for the combined sample of men and women and were similar to those described by others. 11,19,21 Outcome Measures Five health characteristics were examined: (1) Body mass index (BMI), (kg/m 2 ); (2) daily cigarette smoking (yes/no); (3) smoking intensity, defined as self-reported average number of cigarettes smoked daily; (4) exercise sessions, measured by summing the responses to 12 questions about the weekly frequency of specific physical activities; 36 and (5) dietary fat intake, measured by an 18-item food frequency questionnaire constructed specifically for this study. The 18 food items were derived from the National Health and Nutrition Examination Survey II data 37 and included the major 15 food contributors to national total fat and calorie intakes. The food items were collapsed into nine food groups. 38 One group was chosen as a dependent variable: the estimated number of daily calories derived from high-fat foods (i.e. meat, milk, cheese, fats, sweets, eggs, and fried potatoes). Potential Confounders To assess the independent effects of job demands, latitude and strain, multivariate analyses included the following objective job variables: continuous variables for the number of months employed with the company and the average number of hours worked per week; dummy variables for job category (blue collar and clerical versus professional) and salary tertiles ($10 001 $20 000 versus $20 000 $35 000, and $35 000/year); and dichotomous (yes/no) variables for self-reported exposure to environmental chemical or physical hazards and physical exertion (i.e. 3 days per week of heavy job-related moving, hauling, or lifting). Continuous variables for years of education and age, and dichotomous variables for being married and white race, were also included in multivariate analyses. Statistical Analyses Sex-stratified univariate and multivariate analyses, using the MIXED model for the continuous dependent

JOB STRAIN AND HEALTH BEHAVIOURS 577 variables and the LOGIST procedure for smoking prevalence, were conducted. 39 The associations of health characteristics with quartiles of job demands and with quartiles of job latitude were assessed in separate analyses. In the MIXED models, the mean of the dependent variable for each quartile of demands or latitude was compared with the means of each of the other three quartiles. Planned comparisons also included comparing the means of the low-latitude group with those of all other workers and the means of the high-demands group with those of all other workers. Job strain was assessed in the MIXED analyses through a four-way strain variable that identified four job types: low demands low latitude (passive); low demands high latitude (lowstrain); high demands high latitude (active); and high demands low latitude (high-strain). The means of each job strain type were compared with the means of each of the other three job types. Planned comparisons included comparing the combined mean of all other workers against the individual means of high-strain, passive, and active workers. Three separate logistic models for smoking prevalence produced the crude and adjusted odds ratios (OR) and 95% confidence intervals (CI) for (1) active, passive and low-strain workers compared with high-strain workers; (2) workers in each of the first three quartiles of demands versus highdemands workers; and (3) workers in each of the last three quartiles of latitude compared with low-latitude workers. No corrections were made for multiple comparisons. RESULTS There were sex differences in job classification, job strain, and other job and health characteristics central to this study (Table 1). Men were better educated, better paid, and much more likely to be professionals than women. Mean latitude and demands scores were significantly (P 0.0001) higher for professionals compared with blue collar or clerical workers (data not shown). Some sex differences existed within job categories. Professional women reported higher job demands (P 0.0001) and less latitude (P 0.0001) than professional men, and clerical women reported higher job demands than clerical men (P = 0.01). Among men, job demands and latitude were associated with some health characteristics. Men in the highest demands quartile consumed more calories from fat (P = 0.03) and, among smokers, smoked more cigarettes daily (P = 0.04) than men in lower demands quartiles, in adjusted analyses (Table 2). Men in the lowest latitude quartile reported less exercise than other men (P = 0.02). In crude analysis, latitude was negatively TABLE 1 Characteristics of 3843 men and women in the Healthy Worker Project Characteristic Men Women n = 1872 n = 1971 Personal characteristics: Age a *** 39.0 (0.2) 37.7 (0.2) % married** 76.3 59.5 Years education a *** 15.0 (0.1) 13.6 (0.1) % white 95.4 94.9 Job characteristics: % job classification:** Blue collar 16.6 9.1 Clerical 12.3 54.4 Professional 71.2 36.4 % vigorous work activity** 12.7 7.7 % yearly salary:** $10 25 000 18.6 59.0 $25 35 000 25.5 24.5 $35 000 55.9 16.5 Hours worked/week a *** 43.7 (0.1) 41.5 (0.1) Components of job strain: Job latitude a *** 37.1 (0.1) 34.7 (0.1) Psychological demands a *** 32.4 (0.1) 33.3 (0.1) % job strain categories:** Active 27.7 23.4 Passive 27.8 35.4 Low strain 26.7 14.0 High strain 17.8 27.2 Health characteristics: BMI a *** 26.5 (0.1) 25.1 (0.1) Total exercise sessions/week a *** 9.4 (0.1) 8.5 (0.1) Calories high-fat foods/day a *** 672.8 (7.2) 521.3 (7.0) % daily smokers* 14.3 17.1 Among smokers, cigarettes/day a *** 21.0 (0.6) 17.6 (0.5) a Mean (standard error). * P 0.05; ** P 0.001; *** P 0.0001. associated with smoking intensity, but the significance disappeared in adjusted analysis where exposure to hazards (P = 0.02), physical exertion on the job (P = 0.0001), age (P = 0.0001) and months of current employment (P = 0.003) were positively associated and education (P = 0.01) was negatively associated with the number of cigarettes smoked daily. Job demands was positively associated with BMI and smoking intensity among women (Table 3). Adjusted analyses showed that women in the low-demands quartile had a smaller mean BMI than other women combined (P = 0.03) and the mean BMI of women in the highest demands quartile was greater than that of others combined (P = 0.04). Also, in adjusted analyses, women in the highest demands quartile smoked more than

578 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY TABLE 2 Mean (standard error) risk factors by quartiles of job demands and latitude for 1872 men in the Healthy Worker Project Unadjusted model Quartiles Adjusted model Quartiles (1) (2) (3) (4) (1) (2) (3) (4) Low High Low High Psychological demands Body mass index (kg/m 2 ) 26.6 26.4 26.5 26.5 26.6 26.5 26.5 26.6 (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) Exercise sessions/week 9.2 9.2 9.5 9.7 9.2 9.3 9.5 9.5 (0.2) (0.3) (0.2) (0.3) (0.2) (0.3) (0.2) (0.3) Calories high-fat foods/day 661 661 677 699 649 663 681 710 (14) (17) (16) (17) (14) (16) (16) (18) Cigarettes/day 20.9 19.3 20.9 22.7 19.7 19.5 21.6 23.6, (1.1) (1.5) (1.4) (1.4) (1.1) (1.5) (1.3) (1.4) Job latitude Body mass index (kg/m 2 ) 26.5 26.5 26.6 26.6 26.4 26.5 26.6 26.6 (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) Exercise sessions/week 9.1 9.3 9.6 9.4 8.7, 9.4 9.6 9.6 (0.3) (0.2) (0.3) (0.2) (0.3) (0.2) (0.2) (0.2) Calories high-fat foods/day 695 691 657 654 658 690 667 672 (18) (15) (16) (14) (20) (15) (16) (15) Cigarettes/day 23.2 20.4 21.1 18.9 22.4 20.5 21.7 19.3 (1.2) (1.2) (1.5) (1.4) (1.3) (1.2) (1.5) (1.4) * Adjusted for age, marital status, years of education, white race, job classification, presence of vigorous job, salary, hours worked/week, presence of hazardous work, and time with company. Mean significantly (P 0.05) different than quartile 1. Mean significantly (P 0.05) different than quartile 2. Mean significantly (P 0.05) different than quartile 3. Mean significantly (P 0.05) different than quartile 4. women in quartile 1 (P = 0.01), quartile 2 (P = 0.04), and all other women combined (P = 0.02). The total number of exercise sessions was positively associated with increased demands in crude analysis, but the significance disappeared in the adjusted model in which education (P = 0.05), physical exertion on the job (P = 0.0001), and white race (P = 0.01) were positively associated and blue collar status (P = 0.03) and age (P = 0.0001) were negatively associated with exercise. Among women, latitude showed a weaker relationship than demands to health characteristics, especially in adjusted analyses. Higher BMI appeared to be associated with low latitude, but the significance disappeared with adjustment for age (P = 0.0001), which was positively associated with BMI, and education (P = 0.006), which was negatively associated. Women in the lowest latitude quartile reported significantly less exercise than women in quartile 3 (P = 0.05) and quartile 4 (P = 0.05) and all other women (P = 0.02) in adjusted analyses. Job strain was associated with exercise, calories from high-fat foods, and smoking intensity in men (Table 4). Men in passive jobs reported significantly less weekly exercise than other men combined (P = 0.005). Lowstrain men reported fewer calories from high-fat foods than men in high-strain and active jobs, consistent with the finding that high demands was related to fat consumption. High-strain men reported smoking more cigarettes per day than other male smokers combined (P = 0.05). Job strain was associated with BMI, exercise, and smoking intensity in women. High-strain women had a higher mean BMI than other women combined (P = 0.01), although calories from high-fat foods and exercise did not vary between high-strain women and others. Active women were significantly more likely to report more exercise than other women combined (P = 0.0006) and women smokers in passive jobs reported smoking fewer cigarettes per day than other smokers (P = 0.003). Analyses were conducted to determine whether job latitude, demands, and strain were associated with

JOB STRAIN AND HEALTH BEHAVIOURS 579 TABLE 3 Mean (standard error) risk factors by quartiles of job demands and latitude for 1971 women in the Healthy Worker Project Unadjusted model Quartiles Adjusted model Quartiles (1) (2) (3) (4) (1) (2) (3) (4) Low High Low High Psychological demands Body mass index (kg/m 2 ) 24.9 25.0 25.1 25.3 24.7 24.9 25.1 25.5 (0.2) (0.3) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) Exercise sessions/week 7.9, 8.2 8.7 9.0, 8.2 8.2 8.7 8.7 (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) Calories high-fat foods/day 526 520 527 511 523 516 528 519 (12) (13) (13) (13) (13) (13) (13) (13) Cigarettes/day 17.2 17.0 17.7 18.8 16.3 17.1 17.8 19.6, (0.9) (0.8) (1.0) (0.9) (0.9) (0.9) (1.0) (0.9) Job latitude Body mass index (kg/m 2 ) 25.6, 25.0 24.6 24.7 25.2 25.1 24.8 25.0 (0.2) (0.2) (0.3) (0.3) (0.2) (0.2) (0.3) (0.3) Exercise sessions/week 8.0, 8.6 8.7 8.9 8.1, 8.5 8.7 8.8 (0.2) (0.2) (0.3) (0.3) (0.2) (0.2) (0.3) (0.3) Calories high-fat foods/day 533 527 505 508 523 524 511 526 (11) (12) (14) (15) (11) (12) (14) (16) Cigarettes/day 17.7 16.7 18.3 18.8 17.5 16.6 18.7 19.2 (0.7) (0.9) (1.1) (1.2) (0.7) (0.9) (1.1) (1.3) * Adjusted for age, marital status, years of education, white race, job classification, presence of vigorous job, salary, hours worked/week, presence of hazardous work, and time with company. Mean significantly (P 0.05) different than quartile 1. Mean significantly (P 0.05) different than quartile 2. Mean significantly (P 0.05) different than quartile 3. Mean significantly (P 0.05) different than quartile 4. cigarette smoking prevalence (not shown). There were no associations for women, but demands was positively associated with current smoking for men. In a multivariate logistic model, compared with men in the highest demands quartile, the OR for smoking for men in quartile 3 was 0.67 (95% CI : 0.47 0.97; P = 0.03); 0.61 (95% CI : 0.41 0.87; P = 0.008) for men in quartile 2; and 0.63 (95% CI : 0.43 0.88; P = 0.007) for men in the lowest demands quartile. In crude analysis, compared with high-strain men, the OR for current smoking was 0.58 (95% CI : 0.41 0.82; P = 0.002) for low-strain and 0.63 (95% CI : 0.44 0.89; P = 0.008) for active men, but significance disappeared with the adjustment for exposure to hazards at work (P = 0.07), education (P = 0.0001), and marital status (P = 0.01). DISCUSSION Smoking, obesity, dietary fat intake, and inactivity are early and modifiable CVD risk factors. This study offers some evidence that self-reported job demands, and, to a lesser degree, latitude and strain, are associated with these factors. For the most part, the observed effects were in the anticipated direction, even after adjustment for sociodemographic and other job characteristics. Associations were not similar in magnitude and they varied by sex. The lack of consistency of effect across the components of job strain, behaviours, and sex in this study is also reflected in the body of research with the Karasek model. This suggests that further work is needed to conceptualize job strain and identify salient moderating variables with consideration of sex and, perhaps, class differences. Men who reported fewer demands were significantly less likely to smoke than men who reported high demands. Other studies of men with imputed job-strain scores 9,15 and different measures of job demands 13,23 have reported inconsistent results. In this study, high demands was also associated with smoking intensity for men and women, in contrast to reports of no association

580 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY TABLE 4 Unadjusted and adjusted mean (standard error) risk factors by job strain categories for 3843 men and women in the Healthy Worker Project Unadjusted model Strain categories Adjusted model Strain categories High Low Active Passive High Low Active Passive Men Body mass index (kg/m 2 ) 26.6 26.7 26.5 26.4 26.6 26.7 26.5 26.4 (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2) Exercise sessions/week 9.7 9.4 9.5 8.9 9.6 9.6 9.5 8.8, (0.3) (0.2) (0.2) (0.2) (0.3) (0.2) (0.2) (0.2) Calories high-fat foods/day 704 636, 676 686 694 645, 692 667 (19) (15) (15) (15) (19) (16) (16) (16) Cigarettes/day 22.9 19.1 20.6 21.0 23.4 19.5 21.7 19.8 (1.3) (1.5) (1.4) (1.1) (1.3) (1.5) (1.4) (1.1) Women Body mass index (kg/m 2 ) 25.6, 24.6 24.7 25.1 25.6 24.9 24.9 24.8 (0.2) (0.3) (0.3) (0.2) (0.2) (0.3) (0.3) (0.2) Exercise sessions/week 8.5 8.0 9.3,. 8.0 8.3 8.0 9.2,, 8.3 (0.2) (0.3) (0.2) (0.2) (0.2) (0.3) (0.3) (0.2) Calories high-fat foods/day 528 500 509 532 523 506 524 525 (12) (17) (13) (11) (12) (17) (14) (11) Cigarettes/day 18.3 18.7 18.4 16.7 18.6 19.0 19.1 16.1, (0.9) (1.3) (1.1) (0.7) (0.9) (1.3) (1.1) (0.7) * Adjusted for age, marital status, years of education, white race, job classification, presence of vigorous job, salary, hours worked/week, presence of hazardous work, and time with company. Mean significantly (P 0.05) different than high strain. Mean significantly (P 0.05) different than low strain. Mean significantly (P 0.05) different than active. Mean significantly (P 0.05) different than passive. in two large studies which used imputed scores. 15,16 Among women, high demands was associated with higher BMI, but also, non-significantly, with higher exercise levels. Other studies, using different measures of job pressures, have suggested negative associations between job status and obesity 23 and between job demands and exercise 24 for women. Latitude seemed to be less strongly related to health characteristics than demands, although both men and women in the lowest latitude quartile were significantly less likely to report exercise sessions than other workers. Latitude is theoretically a measure of skill discretion and autonomy, but it is plausible that high latitude also reflects responsibility and worksite pressure, which could negatively affect the health behaviours of some individuals and thus explain inconsistent findings in other studies. 3,4,7,9,16 The main thrust of Karasek s model is that the imbalance of job responsibilities and control can result in deleterious health effects. The present study does not support the hypothesis that high-strain workers have uniformly worse health behaviours than other workers. Among men, the only behaviour for which high-strain workers were clearly at higher risk was smoking intensity, in contrast to two large studies of men, 15,16 but consistent with a study of 389 male workers in a chemical plant 26 and two studies using other measures of job pressures. 25,28 High strain was not associated with BMI for men, consistent with studies using imputed Karasek job-strain scores 16 and different measures of job pressures. 23,27 High strain did not deter physical activity, although men in passive jobs were less likely than other workers to engage in leisure-time activity, contrary to the lack of association reported for Japanese-American men. 16 Women in high-strain jobs were heavier than other workers. However, behaviours generally thought to mediate overweight, fat intake and exercise, were not associated with high-strain work. Women in active positions were more likely to report leisure-time activity than

JOB STRAIN AND HEALTH BEHAVIOURS 581 other workers, which is consistent with a Swedish study that found that physical activity in women workers was independently and positively associated with workrelated learning opportunities and psychological demands. 24 However, women smokers in active positions also reported higher smoking intensity than other women smokers. It is possible that active jobs are stressful for women and that smoking and physical activity are both used as stress modifiers. The current study had several strengths: a large, diverse sample representing 32 worksites and a variety of workers; self-reported, rather than imputed, jobstrain measures; measured height and weight; and the ability to control for several job and personal characteristics. It is also one of the few studies to assess health characteristics and job strain in men and women using Karasek s model. However, limitations in study design and possibly in the job-strain measure must be considered in interpreting the results. The crosssectional design makes it impossible to discern the direction of the relationships. These analyses assumed the dependent variables were immediate responses to strain, but that assumption may not be tenable. All of the behaviours and characteristics may have preceded the initiation of the worker s current job. Job classification of workers may have also influenced outcomes. The majority of men in this study were professionals and the majority of women were clerical workers. Undersampling at the extremes of job classification (e.g. factory workers, artists, self-employed workers), and thus potentially undersampling extremes of job strain, could have weakened our ability to find an association. Further, the generalizability of our findings may be qualified because the worksites approached for inclusion in this study were not representative of all worksites in the study s geographical area. Karasek et al. have provided a rich base of data in their attempts to delineate the aspects of job content and design that are relevant to physical and mental health. 2 4,6 9,15 17,20 22,32 However, considering the results of this and other studies using the Karasek model, further work may be needed to clarify the health-promoting or health-compromising aspects of employment, identify potentially modifying influences of job strain, and specify how the measurement of job strain could vary by sex and, possibly, social class. Regarding measurement, the Karasek model assumes an interactive relationship, based on some definition of high and low demands and latitude, although a consistent method for identifying cutpoints is not available. Misclassification error may be introduced since the model weights demands and latitude equally, although demands may be more prone to measurement error. 4,32 Further, while demands and latitude may be related to employee well-being and health behaviours, the relationships may not be linear: 40 some optimal levels of both domains may exist or extreme job demands or latitude may be health-compromising. If the relationships are not linear, misclassification could have contributed to the weak results. The perception of job demands and latitude may also depend on time or context. While Karasek argues that chronic exposures to stressors influence CVD risk, the job-strain questions did not measure the frequency or duration of job demands, decisionmaking authority, or skill discretion, thus no assessment of the chronicity of the worker s situation could be made. Further, this cross-sectional study did not measure the stability of the workers reports of job demands and latitude over time. Inherent in the job-strain model is the assumption that work characteristics, such as conflicting demands, time pressure, working hard, etc., are universally demanding to all workers. However, individuals differ in their response to the same events and in methods for coping with work-related stress. 41,42 Jobrelated coping mechanisms have not been completely identified, but there are many possible candidates for modifiers of worksite stress. For example, because older workers tend to report less strain, 7 it is possible that habituation to highly-demanding or low-latitude situations occurs and thus strain may vary according to exposure time. The study data were adjusted for age of the worker and months worked for the company, but data related to time worked at the current job were not collected. Social support, which was not measured in this study, may also modify job strain. 6,8 This study showed the association of reported strain and health characteristics differed between men and women. There were also sex differences in objective measures of job and class and in subjective reports of latitude and demands. Because most studies of job strain have not included women, there remains a need to determine whether there exists sex-specific salient aspects of job content that contribute to job strain. It is unknown whether there are sex differences in the perceptions of job strain, or whether there exists sexspecific confounders, modifiers, or reporting biases. Multiple-role conflict among women workers has received recent and deserved attention 18,33 and such work should be expanded upon. A particularly useful approach would be the prospective measurement of job strain in men and women of varying classes at several points in time 43 to determine whether, and how, health behaviours and characteristics change with changes in perceived demands and latitude.

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