Effort-Reward Model

All references are from the article: Schnall PL, Landsbergis PA. Job Strain and Cardiovascular Disease. Ann. Rev. Public Health1994, 15:381-411.

Another broader model of work stress is Johannes Siegrist’s “effort-reward” model. The model defines threatening job conditions as a “mismatch between high workload (high demand) and low control over long-term rewards” (103, p. 1128). Siegrist emphasizes personal control over long-term reward since “distressing experiences often result from basic threats to the continuity of a crucial social role”, among adults, often the occupational role. This is clearly the case “with job termination or job instability. However, related conditions of low reward and low security may also be identified, such as forced occupational change, downward mobility, lack of promotion prospects, jobs held with inconsistent educational background (status inconsistency)” (103, p. 1128). Components of workload in Siegrist’s research includes piecework, shiftwork, noise, work pressure, and increase in workload.

In addition, a psychological component (the coping pattern or “need for control”) is added to the model. Two relevant coping variables were identified from factor analysis — “vigor”, a state of active efforts with a high probability of positive feedback, and “immersion” a state of exhaustive coping reflecting frustrated, but continued efforts and associated negative feelings. “Immersion” is considered to increase an individual’s vulnerability to experiences of high demand and low status control.

In a prospective study of German factory workers, status inconsistency (OR=4.4), job insecurity (OR=3.4), work pressure (OR=3.4), and immersion (OR=4.5) independently predict CHD incidence after adjusting for other behavioral and somatic risk factors (103). A combined “low reward/high effort” variable is also a significant predictor (OR=3.4) in a separate analysis.

While the “need for control” components (“vigor” and “immersion”) are considered to be “rather stable person characteristics” in this model, it remains to be determined to what extent they are influenced by levels of work control. Several other studies provide some evidence for this process of adult socialization. For example, in a U.S. study, the substantive complexity of work (analogous to decision latitude) predicted increased intellectual flexibility, non-authoritarianism, and intellectually demanding leisure time 10 years later (66). In Sweden, workers whose jobs became more “passive” (low demand-low latitude) over six years reported less participation in political and leisure activities. In contrast, workers in jobs which became more “active”, participated more in these activities (58, p. 53).

An advantage of Siegrist’s model is that it expands the concept of control typically used in research on Karasek’s job demands-control model to include job security and upward mobility (promotion prospects). However, a limitation of Siegrist’s model is that it only predicts effects of job conditions on CHD. It does not explicitly hypothesize effects of job conditions on psychological functioning, motivation, activity, learning and coping patterns.

Appendix II a – short version ERI 

The following items refer to your present  occupation. For each of the following statements, please indicate to what degree it reflects your situation. Thank you for answering all statements.

I have constant time pressure due to a heavy work load.

1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

I have many interruptions and disturbances while performing my job.

1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

Over the past few years, my job has become more and more demanding.

1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

I receive the respect I deserve from my superiors. 

Not applicable (no superiors) continue with S-ERI5

1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

My job promotion prospects are poor. (S-ER15)

1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

I have experienced or I expect to experience an undesirable change in my work situation.

 1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

My employment security is poor.

 1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

Considering all my efforts and achievements, I receive the respect and prestige I deserve at work.

 1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

Considering all my efforts and achievements, my job promotion prospects are adequate.

1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

Considering all my efforts and achievements, my salary / income is adequate.

1. Disagree

2. Agree, but I am not at all distressed

3. Agree, and I am somewhat distressed

4. Agree, and I am distressed

5. Agree, and I am very distressed

Findings: Effort Distress

Marianne Frankenhauser’s effort-distress model has been tested in a number of studies (26, 27). Lundberg and Frankenhauser (1980) reported on a laboratory study in which healthy adults performed two tasks.

Exploring Occupational and Behavioral Risk Factors for Obesity in Firefighters

Abstract submitted to the 2011 APA NIOSH Meeting

BongKyoo Choi (1), Peter Schnall (1), Marnie Dobson (1), Leslie Israel (1), Paul Landsbergis (2), Pietro Galassetti (3), Andria Pontello (4), Stacey Kojaku (1), Dean Baker (1)

(1) Center for Occupational and Environmental Health, University of California Irvine, USA.
(2) Department of Environmental and Occupational Health Science, State University of New York Downstate Medical Center, USA.
(3) Department of Pediatrics and Department of Pharmacology, University of California Irvine, USA.
(4) Institute for Clinical and Translational Science, University of California Irvine, USA.

Abstract

Background: Obesity has been a serious public health issue in the general population and among workers in the United States (US) since at least the 1980s. Among 41 male-dominated occupations, firefighters have the third highest prevalence rate of obesity. Despite the high obesity prevalence rate among firefighters, epidemiological studies on firefighters and obesity have focused on the correlations between obesity (defined by body mass index (BMI)) and physiological covariates (e.g., blood pressures and lipid profiles). Few studies have examined the roles of working conditions and health behaviors of firefighters in obesity. The working 
conditions of firefighters are generally characterized by high mental and physical job demands, unpredictable fire fighting, relatively long calm periods of time between alarms, shift work (i.e., 24-hr shift), and frequent overtime work. These factors may increase the risk of obesity in firefighters directly or indirectly through promoting unhealthy behaviors (e.g., overeating and 
physical inactivity both at work and during leisure time). In addition, few validated instruments – a methodological prerequisite for obesity studies in firefighters – are available that specifically assess the unique working conditions and health behaviors of firefighters who work on a 24 hrshift system. Many firefighter wellness fitness (WEFIT) programs have focused on fitness training and periodic medical examinations. The WEFIT programs have never been intended to examine occupational or behavioral determinants of obesity and biological CVD risk factors.Furthermore, no study has explored differential relationships between BMI and skinfoldbased % fat by age and ethnicity (e.g., Latinos vs. Whites) and differential relationships of BMI and skinfold-based body fat % with other CVD risk factors (e.g., hypertension and blood lipid profiles) in firefighters.

Objectives: The main aims of this study are a) to develop and validate a firefighter-relevant work and health questionnaire using qualitative and quantitative methods in firefighters, b) to use this questionnaire in an epidemiological study to explore whether adverse working conditions and health behaviors are risk factors for obesity in firefighters, and c) to explore the interrelations between working conditions and health behaviors as they relate to obesity. A supplementary objective is to evaluate the strengths and weaknesses of BMI as a measurement (commonly used as a surveillance measure of obesity in many (WEFIT) programs for 
firefighters) in comparison with skinfold-based body fat %.

Methods: This study will be conducted in collaboration with a fire authority covering a county of Southern California. In order to facilitate and oversight the study, a research advisory committee will be created with members from the fire authority management, International Association of Fire Fighters (IAFF) local union, WEFIT coordinators, and researchers at a university. This study involves the following steps in chronological order: a) focus groups of firefighters by rank (captains vs. firefighters/engineers) will review and revise the domains and items in a questionnaire about working conditions and heath behaviors (dietary quality, eating behaviors, and physical activity) of firefighters; b) a final version of the questionnaire will be introduced to firefighters (n ≥ 357) who will visit an occupational health clinic as part of a firefighter WEFIT program on a regular basis. For analyses, the questionnaire information will be linked to the records of the WEFIT medical and fitness exams (BMI, body fat %, VO2 max, blood pressures, and blood lipid profiles) of the survey participants; c) a sub-sample (n ≥ 80) of the survey participants will be recruited to test the validity of the self-reported questionnaire information on working conditions and health behaviors. They will be asked to wear a waist physical activity monitor for 72 hrs (24 hrs at a work day and 48 hrs at non-work days), to complete a 3-day food 
diary, and to fill out the questionnaire again in one week after completing the survey for a 1-week test-retest reliability, and d) focus groups of firefighters will assess and evaluate study findings in order to develop recommendations for reducing weight and obesity in firefighters.

Results: This study is a 2-year project, funded by the Center for Disease Control and Prevention (CDC)/National Institute for Occupational and Environmental Health (NIOSH) from 2010 to 2012 (Grant #: 1R21OH009911-01). From a study design perspective, the overall study plan will be presented at the APA/NIOSH 2011 conference. In addition, the findings from the 
focus groups of firefighters for developing a firefighter-relevant work and health questionnaire (to be completed before the conference) will be presented in detail with focus on firefighters’ insights and contributions.

Brief Summary: Identify occupational and behavioral risk factors for obesity in firefighters is an essential first step for establishing effective intervention programs for obesity in almost 1.1 million professional and voluntary firefighters in the US.

For correspondence: BongKyoo Choi, Center for Occupational and Environmental Health, 
University of California Irvine, 5210 California Avenue, Suite 100, Irvine, CA, 92617. Tel. 1-949-
824-8641, Fax 1-949-824-2345, E-mail: b.choi@uci.edu

The Effort-Distress Model

Marianne Frankenhauser and her colleagues in Sweden have confirmed the involvement of two neuroendocrine systems in the stress response

Findings: Person-Environment Fit

The Person-Environment (P-E) Fit model, developed in the early 1970s by researchers at the University of Michigan, states that strain develops when there is a discrepancy between the motives of the person and the supplies of the environment (job), or between the demands of the job and the abilities of the person to meet those demands.

Person-Environment (P-E) Fit Model

The “job strain” model was not designed to replace the earlier more complex person-environment model of occupational stress originating from the University of Michigan (16, 42) or the recent refinement of the Michigan model by the National Institute for Occupational Safety and Health (NIOSH) (44)

Occupational Stress Index

Permission to use any of the OSI instruments should be obtained from Dr. Karen Belkic: Center for social Epidemiology

Investigation of Work History

Investigation of Work History – To Measure Cumulative Exposure

In most research studies, “job strain” was only measured at one point in time (Schnall, Landsbergis & Baker, 1994). Yet, it is believed that cumulative exposure to “job strain” increases risk of hypertension or CHD. Most likely it is the chronic biological arousal due to sustained “job strain” that contributes to the development of essential hypertension (Schnall, Landsbergis & Baker, 1994). If duration of exposure to “job strain” is not measured, then we cannot determine whether the stressful work environment has existed for the person for only the previous month, or for the previous 40 years. Use of current exposure as a surrogate for lifetime exposure is inaccurate, in part, since people often gain skills with time and age, may be promoted, may select out of “high strain” jobs, or their job characteristics may change even within the same job title. For example, in the Cornell study, 22% of the study participants changed “job strain” status over the course of 3 years (Landsbergis et al., 1995). Many study participants with a lengthy history of “job strain” might thus be currently classified as “non-strain” because of recent promotions or other job changes. Use of inaccurate measures of exposure to “job strain” (i.e., non-differential misclassification) can bias results towards the null hypothesis, leading to the conclusion that the effect of “job strain” on blood pressure is weaker than it truly is.

A work history interview, developed by Paul Landsbergis for the Cornell ambulatory blood pressure study, included two questions each on job demands, decision latitude and social support. These questions were asked of the study participant for each past job held. Interviews of 284 cohort study participants (who reported a total of 1,366 jobs), were completed as of 1/1/95. All subjects participating in the third round of data collection agreed to the interviews. Eligible interview subjects included 212 men enrolled in the cohort study at Time 1, 6 men enrolled at Time 2, 21 women enrolled at Time 1 and 45 women enrolled at Time 2. In addition, 100 nurses and aides, newly enrolled in the study at time 3, have completed a questionnaire version of the work history interview.

For the 284 completed interviews, internal consistency of the three two-item scales was acceptable (workload demands, a=.81; job decision latitude, a=.62; workplace social support, a=.63). In order to increase the reliability of the critical job decision latitude scale, two items were added to the questionnaire: “the freedom to decide how you do your work” was added to the decision-making authority subscale; “the chance to be creative” was added to the skill utilization subscale. Thus, the decision latitude of each past job is now measured by four items. Among the 155 subjects who have answered all 4 latitude items, scale reliability has increased to a=.83.

Work History Questionnaire

Listed below are questionnaire items used to define job demands, job decision latitude and workplace social support for each past job in the Work History Questionnaire used in the Cornell study. “On that job, did you have….

A) Psychological Job Demands

1) To work very hard
2) An excessive amount of work

B) Job Decision Latitude

Decision Authority
1) The freedom to decide how you do your work
2) A lot of say about what happens on the job
Skill Utilization
3) The chance to be creative
4) A high level of skill

C) Workplace Social Support

Coworker Support
1) Helpful coworkers
Supervisor Support
2) A helpful supervisor

Data Analysis

Measures of cumulative exposure to be analyzed are based on recent research by Jeffrey Johnson and colleagues (Johnson et al., 1991; Johnson & Stewart, 1993). They used Swedish national data bases to compute average job demands, control (latitude) and support scores for each year of a person’s work history, based upon their job title, age, gender and years of employment. In order to determine the effects of total work history exposure, as well as the time course of exposure (whether earlier or later exposure affects outcome), they constructed both discrete and cumulative 5-year exposure windows. Thus, mean job characteristics scores in each of the following time periods were analyzed for association with future CVD:

1. Discrete: 1-5 years prior to outcome, 6-10 years, 11-15 years, 16-20 years, 21-25 years, 26+ years.
2. Cumulative: 1-10 years prior to outcome, 1-15 years, 1-20 years, 1-25 years, total work history.
   In addition, to further assess patterns of occupational movement (career trajectory), Johnson et al. (1991) and Johnson & Stewart (1993) analyzed the following exposure measure for association with future CVD:
3. Direction of change: Whether job characteristics significantly increase, decrease or remain stable over the working life.

In the Swedish study, exposure among men to low control jobs, within the previous 25 years, was prospectively associated with CVD mortality (Johnson et al., 1991). Higher risk was observed among blue-collar men.

References

Johnson JV, Hall EM, Stewart W, Fredlund P, Theorell T. Combined exposure to adverse work organization factors and cardiovascular disease: Towards a life-course perspective. In Fechter L, ed. Proceedings of the Fourth International Conference on the Combined Effects of Environmental Factors, Baltimore: Johns Hopkins University, 1991:117-121 .

Johnson JV, Stewart W. Measuring work organization exposure over the life course with a job-exposure matrix. Scand J Work Environ Health 1993;19:21-28.

Landsbergis PA, Schnall PL, Schwartz JE, Warren K, Pickering TG. Job strain, hypertension and cardiovascular disease. In Organizational Risk Factors for Job Stress, eds. SL Sauter, LR Murphy. Washington, DC: American Psychological Association 1995:97-112.

Schnall PL, Landsbergis PA, Baker D. Job strain and cardiovascular disease. Ann Rev Public Health 1994;15:381-411.

Studies Using the Imputation Method

(All reference numbers are from Schnall PL, Landsbergis PA, Baker D. Job strain and cardiovascular disease. Annual Review of Public Health 1994;15:381-411.)

Self report bias is a potential problem in many “job strain” studies, since exposure has often been assessed through questionnaires completed by study participants. Self-reports may be inaccurate descriptions of job characteristics or may be biased by personality traits such as “negative affectivity”. Concerns have also been raised about the need for more objective measures of “job strain” in intervention studies.

Therefore, in 13 “job strain” studies, researchers employed an analytic technique to overcom self-report bias and obtain more objective measures of job characteristics – the imputation of average scores for a particular job title to individuals in that job title. The average job-title score, free of the individual’s subjective assessment, then predicts outcome for the individual. However, while this strategy is often presented as desirable, it developed in the U.S.A.. because of a lack of databases containing both job characteristics data and health data – a weakness of past research. Large within variance exists in job characteristics (55% of reliable variance for latitude, and 93% for demands), since job titles such as nurse, machinist, secretary or teacher are somewhat heterogenous in skill levels, autonomy, or demands (102). As a result, in the U.S. studies, mean scores of job characteristics are adjusted for demographic covariates (e.g., age, race, education, marital status, region, urban vs. rural, and self-employment status) in the HANES 1 (59) when imputed to an individual participant (102). Despite this adjustment, the imputation strategy introduces (non-differential) misclassification and a bias towards the null. Thus, positive findings using the imputation method (4, 5, 36, 59, 68, 81, 109) provide strong support for the model, while negative studies may result, in part, from loss of power. However, individual level job data and health data clearly need to be obtained in future research.

Job Strain and Cardiovascular Disease Risk Factors other than High Blood Pressure

Summary of 6 studies from:

Schnall PL, Landsbergis PA, Baker D.
Annual Review of Public Health, 15, 1994, 381-411.

+ 1 newly published study (1994), non-confirmatory
+ 1 older study (1991), confirmatory
(abstracts from 1995 Copenhagen conference not included)

LIST OF STUDIES

Confirm

81. Mensch, B. S., Kandel, D. B. 1988. Do job conditions influence the use of drugs. J Health Soc Behav 29:169-84.

32. Green, K. L., Johnson, J. V. 1990. The effects of psychosocial work organization on patterns of cigarette smoking among male chemical plant employees. Am J Public Health 80:1368-71.

new. Johansson G, Johnson JV, Hall EM. Smoking and sedentary behavior as related to work organization. Soc Sci Med 1991;32:837-846.

Non-confirm

37. Haratani, T., Kawakami, N., Araki, S. 1992. Job stress and cardiovascular risk factors in a Japanese working population. Presented at the 9th International Symposium on Epidemiology in Occupational Health, Cincinnati, OH.

86. Netterstrom, B., Kristensen, T. S., Damsgaard, M. T., Olsen, O., Sjol, A. 1991. Job strain and cardiovascular risk factors: A cross sectional study of employed Danish men and women. Brit J Ind Med 48:684-89.

90. Pieper, C., LaCroix, A. Z., Karasek, R. A. 1989. The relation of psychosocial dimensions of work with coronary heart disease risk factors: A meta-analysis of five United States data bases. Am J Epidemiol 129:483-94.

new. Alterman T, Shekelle RB, Vernon SW, Burau KD. Decision latitude, psychologic demand, job strain and coronary heart disease in the Western Electric Study. American Journal of Epidemiology 1994;139:620-7. (see note at end)

Non-confirm

37. Haratani, T., Kawakami, N., Araki, S. 1992. Job stress and cardiovascular risk factors in a Japanese working population. Presented at the 9th International Symposium on Epidemiology in Occupational Health, Cincinnati, OH.

86. Netterstrom, B., Kristensen, T. S., Damsgaard, M. T., Olsen, O., Sjol, A. 1991. Job strain and cardiovascular risk factors: A cross sectional study of employed Danish men and women. Brit J Ind Med 48:684-89.

90. Pieper, C., LaCroix, A. Z., Karasek, R. A. 1989. The relation of psychosocial dimensions of work with coronary heart disease risk factors: A meta-analysis of five United States data bases. Am J Epidemiol 129:483-94.

new. Alterman T, Shekelle RB, Vernon SW, Burau KD. Decision latitude, psychologic demand, job strain and coronary heart disease in the Western Electric Study. American Journal of Epidemiology 1994;139:620-7. (see note at end)

Confirm

new. Johansson G, Johnson JV, Hall EM. Smoking and sedentary behavior as related to work organization. Soc Sci Med 1991;32:837-846.

Confirm

30. Georges, E., Wear, M. L., Mueller, W. H. 1992. Body fat distribution and job stress in Mexican-American men of the Hispanic Health and Nutrition Examination Survey. Am J Human Biol 4:657-67.

Note: In Alterman et al. (1994), while “job strain” was not associated with smoking, smoking was associated with lower demands (p=.058, crude) and lower decision latitude (p<.001, crude). they also used national job title averages (occupational linkage method) rather than self-reported scores.