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 Table of Contents  
REVIEW ARTICLE
Year : 2022  |  Volume : 6  |  Issue : 4  |  Page : 211-218

Psychosocial stressors in psychosomatic cardiology: A narrative review


Department of International Health, Karolinska Institutet; Department of Psychology, Stress Research Institute, University of Stockholm, Stockholm, Sweden

Date of Submission11-Aug-2022
Date of Acceptance26-Aug-2022
Date of Web Publication16-Sep-2022

Correspondence Address:
Prof. Töres Theorell
Department of International Health, Karolinska Institutet, Stockholm, Sweden, Department of Psychology, Stress Research Institute, University of Stockholm, Karlbergsvägen 72B, Stockholm 11335
Sweden
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/hm.hm_26_22

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  Abstract 

The definition of a psychosocial stressor and reactions to it is discussed in relation to individual and environmental factors. The relation of this model to psychophysiological stress reactions and regeneration, as well as its significance for cardiovascular diseases, is described. Three classes of psychosocial stressors (life changes, work conditions, and family conflicts) are then described in relation to cardiovascular illness and risk factors. Particular emphasis is on longitudinal studies of patients. Heart contractility and urinary adrenaline excretion are discussed in detail. Epidemiological data on psychosocial stressors and cardiovascular disease outcomes (mainly myocardial infarction) are also discussed.

Keywords: Ballistocardiography, family conflict, job stress, life change, psychosocial, stressor, urinary adrenaline excretion


How to cite this article:
Theorell T. Psychosocial stressors in psychosomatic cardiology: A narrative review. Heart Mind 2022;6:211-8

How to cite this URL:
Theorell T. Psychosocial stressors in psychosomatic cardiology: A narrative review. Heart Mind [serial online] 2022 [cited 2023 Jan 31];6:211-8. Available from: http://www.heartmindjournal.org/text.asp?2022/6/4/211/356218


  Introduction Top


Stressors in a biological context

A stressor is an external environmental condition which induces a stress reaction. In cardiological stress research, defining and assessing stressors are important themes. This presentation will be limited to psychosocial stressors.

According to a simplified epidemiological model, an environmental “objective” stressor may induce endocrinological, immunological, and cardiovascular reactions that accelerate or induce a cardiovascular disorder. However, as is generally accepted, the human body does not interact with the environment in such a simple way. The complexity of the interplay between stressors of the body is illustrated in [Figure 1].[1] There are objectively definable conditions that could act as stressors (inducing stress) and also anti-stressors in the environment that prevent stress reactions.
Figure 1: Schematic presentation of the interplay between stressors or anti-stressors in the environment (left) and individual coping (middle) in catabolic or anabolic responses (right)

Click here to view


The externally defined stressors and anti-stressors exert their influence through the individual's coping strategies, which are displayed in the center of the diagram. The coping patterns are a product of genes as well as of the individual's previous experiences. When the individual has processed the influence of the stressors, physiological and psychological reactions arise, which could give rise to “stress,” i.e., mobilization of energy such as stimulation of the sympathoadrenomedullary (SA) and hypothalamo-pituitary-adreno-cortisol (HPA) systems. The final stage of this energy mobilization is catabolism. If on the contrary, the anti-stressor component dominates in the environment, there will be recuperation and regeneration, corresponding to stimulation of the hypothalamo-pituitary-gonadal (HPG) system. The final stage of the latter reaction is anabolism, i.e., a healing process. Our bodies are constantly balancing these two systems – we need to be able to mobilize energy in demanding situations, but we have to safeguard our periods of rest and recuperation in order for us to sustain health. It should also be emphasized that an environmental condition that demands energy mobilization may shift importance for an individual so that the same condition becomes a condition stimulating anabolism. Finally, our genes interact with this complex system. Studies in epigenetics have shown, for instance, that genes related to stress reactions (such as those important for noradrenaline or serotonin excretion) can change their sensitivity to the environment. This means that “stress genes” will show increased sensitivity to stressors when an individual is living in a dangerous environment. Conversely, the gene sensitivity can decrease in a supportive environment. For a detailed discussion of these concepts, see Theorell's research.[1]

Most of the arrows in the graph are bidirectional. This means that the individual's coping is influenced by previous experiences in similar situations but also that the same coping may affect (sensitize or desensitize) the activity in stress-regulating genes (epigenetics). Finally, the individual's coping may change the environment, dangerous factors may be removed and anti-stressors added.

The bidirectional arrows in the stress reactions complicate the interpretation of associations that we observe between stressors and the development of disorders. Another problem in stressor research is that an objective situation could be interpreted differently by different individuals. In epidemiological research, efforts are made to find the true environmental part of the observed stressor, as the reader will see in later in this presentation. For instance, among critical life events, death of a close relative and loss of employment are objectively definable events, although the individual's role in the precipitation of these events shows substantial variation. Small events that we are exposed to frequently are often more difficult to define in objective terms, and the individual's role could be substantial.

Stressors discussed in this presentation are as follows:

  • Critical life changes
  • Stressors in working life
  • Family conflicts.


I will start by presenting the details of empirical research. This will be followed by a critical discussion of the potential clinical importance of the findings in the field.

Critical life changes

There is conflicting evidence whether life changes are associated with subsequent myocardial infarction (MI). A more detailed discussion regarding the assessment of critical life changes can be found in Theorell's research.[2],[3] In this presentation, I shall start discussing physiological correlates of week-to-week life events and then bring in longer perspectives – what is the likelihood that critical life changes or an accumulation of life events trigger a MI?

How do everyday life changes that are recorded on a week-to-week basis influence our SA system? Most of these self-reported life changes are small events which have been labeled “daily hassles and uplifts.”[4]

A detailed longitudinal study of weekly life changes and week-to-week variations in catecholamine excretion was performed on a group of patients who had recently suffered a MI.[5] They were interviewed systematically each week about life changes that they had experienced during the previous 7-day period. The interview followed a standard list of life changes, and every reported change was translated to a score based on ratings from the general population of the “amount of adaptation required.” If there were several changes, the scores for that week were summed. On the day of the life change interview, they also collected urine for the assessment of adrenaline and noradrenaline excretion during working hours. The results showed that on a group level, there was a significant association between the reported life change points during the past week and the urinary excretion of adrenaline during working hours on the last day of the past 7-day period. After within-participant standardization of both life change scores per week and urinary adrenaline excretion per minute during working hours, with individual means as anchor points and percent deviation from the individual mean in each observation, it was possible to summarize the average “effect” of a given percentage change in life change score during a given week on the percentage change in adrenaline excretion. As expected, the correlation was of moderate size; the amount of life change/week explained 10% of the variance at the group level. On average, a doubled life change score corresponded to a 30% increase in adrenaline excretion. This is close to the adrenaline excretion effect observed in most stress experiments in the laboratory. The individual covariation between life change and adrenaline excretion varied markedly, however, between participants. In about one-third of participants, the amount of life change had a strong relationship with adrenaline excretion, whereas among another one-third of participants, the relationship was moderate, and in the remaining participants, there was no such association. In one case, important life changes correlated with angina pectoris attacks. The week-to-week variations in catecholamine excretion were, in some cases, pronounced. They exceeded by far the variations observed in clinical laboratory stress experiments.

This study indicated that there were pronounced differences between individuals in their sensitivity to (mostly minor) life changes. A clinical observation was that our attention to ongoing life problems was appreciated emotionally by the patients. Our experiences from this study indicate that life changes should receive greater attention in taking patient histories. They are not so easy to study systematically,[3] mainly because the meaning of a specific life change could vary between individuals. In addition, some life changes are purely environmental, whereas others could be partly or completely self-induced. The highly significant life changes are relatively rare, whereas trivial events are common.

In the initial development of life change research in cardiology, using the Holmes-Rahe life change assessment methodology,[6] the first step was to systematically interview patients who were hospitalized – because of an acute MI – about life changes that had occurred during each one of the 23-month periods in the 3 years preceding the MI as well as in matched comparison groups. The findings showed that in patients without preceding symptoms of coronary heart disease, there was a gradual increase in self-reported life change scores not observed in the comparison group or in the MI group with premonitory symptoms.[7] Later reports criticized the use of life change score data. In a large prospective study, we were unable to confirm our findings from early studies[2],[3] of an accumulation of critical life changes during the months preceding the onset of MI, but we did show[8],[9] that the experience of specific life changes (such as increased responsibility at work) during one year had value in predicting increased risk of developing a MI during the subsequent 2-year period. Möller et al.[10] made similar findings in a large case–control study of patients with MI and a control group. A sum of life change scores for the year preceding the onset did not differentiate patients from control subjects, but specific life changes related to important changes in the work situation such as increased responsibility did so, for both men and women – with increased responsibility at work (perceived as important) being reported more often in the year preceding MI onset than in the control group. In the same study, a special interview technique was also used for the exploration of the possible significance of acute triggering events during the week preceding the onset. Events related to acutely increased pressure at work were reported significantly more often in the days preceding the infarction than during the days preceding that period.[10]

The confusion regarding the possible role of an accumulation of life changes (high life change score) in the triggering of MI could be explained using a dynamic perspective. With regard to the total load of life changes during a given period, the dynamics are probably of crucial importance: an increase to a level greater than the individual's habitual level of life problems may be decisive. That was not in focus, neither in the prospective nor in the case–control study in which single assessments were made for the whole year preceding the onset. This could be part of the explanation of the discrepancy between the prospective and initial retrospective findings (in which participants retrospectively reported life changes for the 3 past years, year-quarter after year-quarter). Retrospective “search for meaning” in a patient who has recently had a MI, as well as biased memory artifacts (emphasizing some but forgetting others), could also have contributed to the discrepancy.

Next, the findings from a longitudinal study of life changes reported continuously during 6-month periods in patients with coronary heart disease will be discussed. In this study, repeated data were also collected regarding cardiac contractile patterns – which enabled us to connect life change patterns to heart function. The contractile patterns were studied by means of ballistocardiography.

Ballistocardiographic recordings reflect recoils created in the human body by the heartbeat. The most frequent principle has been to record movements – ultra-low-frequency acceleration – in the sagittal dimension. The patient is placed on a horizontal bed, and movements are recorded by an accelerometer mounted in the bed. This method was introduced by the physiologist Isaac Starr in 1946.[11] Ballistocardiographic measures are always combined with other beat-to-beat measures of heart function. A very recent application has been to use ballistocardiographic/seismographic cardiac measurements included in a smart dress for cosmonauts in extraterrestrial stations and it has also been used as part of polygraphic recordings in intensive care of newborn babies where electrodes cannot be used.[12]

In our studies, we had access to systematic clinical protocols, including ballistocardiograms from 73 patients with ischemic heart disease and 50 matched control subjects. These subjects were followed bimonthly during periods from 2 to 7 years. The ballistocardiograms were classified qualitatively according to a scheme introduced by Starr. The analysis indicated that the ballistocardiographic recordings among patients with a poor prognosis were classified as worse than those among other subjects.[13] Findings from a period of 2 years preceding cardiac death and matched periods in survivors with heart disease and control subjects showed that it was also possible to identify quantitative relevant measures from the ballistocardiograms. Accordingly, IJ amplitude that reflects cardiac force was significantly lower among patients destined to die during the follow-up. During the last 6 months preceding death, however, cardiac force (proxy measured by the IJ amplitude) from a stable mean level of 2 cm, during the periods 24–18, 18–12, and 12–6 months, both in those who later died and in those who survived, to 2.4 cm in the group who died but with no change during that period in the surviving group. Thus, there was on average a 20% increase in cardiac force during the ½-year preceding death but not in the other group. A similar pattern was observed for cardiac force (heart rate times IJ amplitude). An increased incidence of arrhythmias also occurred in the death group.[14] This change in cardiac function was preceded by an accumulation of critical life changes during the period 6–12 months before death, with an increase of 45 in mean life change sum score (amount of adaptation required, with score for each kind of event possible from 0 to 100) per ½ year during that period.[15] Life change items that generate this level of score according to population-based tables are for instance dismissal from work and marital reconciliation. Another observation was that the ballistocardiographic measure of contractility (“IJ velocity,” IJ amplitude divided by IJ duration) was highly significantly associated with the urinary excretion of vanillylmandelic acid, an integrated measure of the 24-h excretion of catecholamines, which was analyzed in a subgroup of patients. In addition, stress interviews showed that the contractility was sensitive to discussions inducing arousal.[16]

In summary, these findings showed that measures from the ballistocardiogram used repeatedly in individuals over long periods of time could be related to sympathomedullary activity (24-h catecholamine excretion), arousal (during interviews), and cardiac prognosis (death). Analyses of contractile patterns are of value in the identification of patients needing extra psychosocial care.

Our findings in the longitudinal ballistocardiographic studies show that it is possible that accumulation of critical life change may have resulted in increased load on the heart via sympathoadrenomedullary and HPA axis mechanisms and then in a delayed coronary death.

From a clinical perspective, it is useful because it means that a cardiologist who monitors the patient's critical life changes may get insight into psychosocial prevention for the patient. I noticed in my own work on life changes that patients appreciate a discussion about their own ongoing life changes.

Increased responsibility at work should be regarded as an objectively definable life change, and it was shown to have predictive value in relation to increased risk of developing MI in prospective[8],[9] and case-controlled studies.[10] Other more infrequent but critical life changes that have been related to increased MI risk are unemployment,[17] divorce,[18] and bereavement.[19]

Psychosocial stressors in working life

In the scientific literature on the role of psychosocial working conditions in the pathogenesis of ischemic heart disease, a number of theoretical models have been proposed starting in the 1980s.

The first proposed model was the person–environment fit (PEF) which was introduced at the Institute for Social Research in Ann Arbor, Michigan. It became possible to relate psychosocial factors to a formal theory accepted by several researchers, for instance, lack of PEF[20] and dissatisfaction with work.[21] Other researchers felt that the use of such models would lead to an underestimation of the importance of work organization and the possibility that improved work organization could have in health promotion. That approach was also stimulated when Karasek introduced his demand control (DC) model in 1979.[22]

The DC model with the addition of social support at work demand-control-support (DCS)[22],[23],[24] was introduced to cardiovascular epidemiology 35 years ago. The DCS theory postulates that combinations of excessive psychological demands and poor possibility for the employee to exert control over (decision latitude) and to obtain social support at work give rise to increased health risks for employees. A work situation is particularly psychologically demanding when the tempo is constantly high, and at the same time, the tasks are difficult and require constant attention. Control (decision latitude) has two components. In the terminology introduced by Karasek, decision latitude is used to describe the possibility that the work organization gives the employee to exert control over his/her situation. There are two components, namely decision authority, which is the possibility for the worker to exert control over the work process, and skill discretion, the possibility to develop skills in order to be able to exert control in unexpected situations. Finally, social support has several components, such as support from superiors and support from colleagues as well as emotional and instrumental support.

The effect of high demands and low decision latitude on the risk of developing acute manifestations of ischemic heart disease (mostly MI) has been examined in many studies, and there is growing consensus that there is a significant relationship.[25],[26]

The operation of the DC model in working subjects has been illuminated in several studies of the associations between job strain and physiological measures. An early longitudinal study was performed by our group.[27] Men in six different occupations representing both blue-collar and white-collar occupations were followed for 1 working day once every quarter of the year. They continued their participation throughout the year (to avoid seasonal group effects on assessments). On every occasion, psychological demands and decision latitude were assessed by means of the Swedish short version of the DC questionnaire. In addition, the participants were instructed to measure their own blood pressure once every hour from wake-up in the morning to bedtime. A morning blood sample was taken. For every individual, the job strain measures (demand divided by decision latitude) from the 4 assessment days were rated from highest to lowest. The results showed that during working hours, the day with the worst job strain had the highest average systolic blood pressure. There were no significant findings for plasma cortisol using the same analytical framework.[28] The participants also reported more impaired sleep that day, and in the participating white-collar workers, the plasma testosterone levels were 14% lower on the 2 days with the worst job strain than on other days,[29] probably reflecting a lower activity in the regenerative “anabolic” HPG axis mentioned above.[30] The overarching interpretation of this longitudinal study is that increasing job strain may generate long-lasting reactions related to energy mobilization and reduced body regeneration. Another observation was that subjects who reported a moderate number of emotions related to blood pressure peaks during working hours had the least rise in systolic blood pressure (mean rise 1 mmHg) during their 2 peak days of job strain,[31] while those who reported no emotions at all (mean rise 6 mmHg) or very many emotions (5 adjectives corresponding to 5 mmHg and 6 adjectives corresponding to 9 mmHg elevation of systolic blood pressure) at the same time during job strain days had a more pronounced job-strain-related blood pressure rise. Accordingly, our data indicated a U-shaped association between awareness of one's own assessment of the importance of emotions to systolic blood pressure elevation during days with job strain. No awareness at all and awareness of the influence of many different emotions were associated with a pronounced response to days with a high degree of job strain. A later large longitudinal study (the Whitehall II cohort) showed that both extremely high and extremely low levels of negative emotions are associated with high blood pressure levels.[32] The common denominator between the extremes may be the inability to handle emotions in stressful situations.

There has been extensive research on the relationship between job strain and cortisol levels and no simple relationship seems to exist. Whether elevation or lowering of morning cortisol takes place during job strain periods seems to depend on the duration of job strain exposure and a number of intermediary variables such as age.[33] It could be speculated that long-lasting exposure to job strain will lead to physiological exhaustion with a flattened diurnal rhythm – which means low morning cortisol. Similarly, several longitudinal studies of variations in job strain in relation to variations in blood pressure have been published.[34] Tobe et al.[35] observed that, at least in women, lack of cohesion in the workplace (social support at work) amplified the effect of job strain on blood pressure elevation. It should be emphasized that the findings of an association between job strain and blood pressure elevation (mostly systolic) are consistently observed when ambulatory assessments are made and less frequently when blood pressure has been measured in a conventional way in the doctor's office.

Job strain is presently the work organization model that has been most extensively studied in cardiovascular epidemiology. A new development in job strain research is the study of mortality related to exposure to job strain in vulnerable subjects with cardiometabolic disease, for instance, subjects with manifest coronary heart disease or diabetes. In this group, there are particularly strong effects – increased mortality after exposure to job strain.[36]

All these results point to the bad effect of long-term exposure to job strain, but a new interesting development[37] is research on other aspects of the DC model showing that long-term exposure to the combination of high psychological demands and high control (so-called active work) seems to protect against cognitive decline in old age, even when adjustments have been made for education level and age.

Apart from job strain,[38] several other work-related psychosocial stressors have been established in relation to cardiovascular outcomes or cardiometabolic risk. Long working hours,[39] job insecurity,[40] shift and night work,[41],[42] and organizational downsizing[43],[44] have been studied in relation to several disease outcomes such as coronary heart disease, stroke, diabetes 2, and atrial fibrillation[45] as well as psychiatric depression.[46] In the majority of studies, there are positive findings although the relative risks are relatively low, mostly ranging between 1.2 and 1.8. It should be pointed out that these illness outcomes only partly overlap. There is a total effect on morbidity, not just, for instance, cardiovascular disease. Therefore, when a more general illness outcome approach is used[47] – with an analysis of lost healthy years because of any illness – it becomes obvious that long-lasting exposure to job strain shortens a healthy life and increases the risk of long-lasting sick leave.[48]

Ideally, in epidemiology, a stressor should be defined objectively. This is often not possible although efforts are made to stimulate participants in self-report studies to rate what the work situation implies per se Questionnaires for the assessment of psychological demands and decision latitude have been constructed in that way. Still, there is always a subjective component in self-reports, and an alternative, more objective method builds upon job exposure matrices that are based on average ratings of subjects who work in different occupations. This is more likely for decision latitude than for psychological demands.[49]

During later years, alternatives to the DC and DCS have been utilized. The effort–reward (ER) imbalance (ERI) model, according to Siegrist, is the most frequent alternative.[50] It postulates that when there is an imbalance between the effort that an employee is making and the reward that is given to him/her adverse health risks arise. Although the concepts of demand and effort are partly overlapping, they reflect different aspects of the work situation. While the construction of the questions regarding psychological demands in the DCS model aims at demands from the organization on the individual, the effort concept addresses the individual's perception of the effort that he/she is making for the organization. Similarly, the reward concept addresses the rewards that the individual feels that he/she gets from the organization. The ER model sometimes also includes the “overcommitment” dimension, which is treated more as an individual trait determining part of the variance. Three kinds of rewards are addressed, namely material (salary), social (promotion and esteem), and psychological (feedback). Like the DC and DCS models, the ERI has been successful in predicting several kinds of disease outcomes, such as depression[51] and incident coronary heart disease.[52] It seems that the two models DCS and ERI can supplement one another in predictions since they overlap only partially. In particular, the combination of poor ERI and low decision latitude seems to be of importance in predicting an increased risk of developing depression[53] and MI.[54]

The ERI model has also been examined in relation to physiological parameters. Such reviews conclude that for changes in heart rate variability, altered blood lipids, and risk of developing metabolic syndrome, there are robust results, whereas findings for cortisol release, inflammation, and blood coagulation are less consistent.[55] A meta-analysis of 56 studies showed that there is a significant relationship between poor effort–reward imbalance and HPA activity and that the overcommitment dimension seems to predict some of the changes in physiological parameters.[56]

A third model is the demand resource (DR) model, which postulates that high demands have adverse health effects only when resources are small for the individual worker. Resources are broadly defined and are related both to individual and organizational resources. A more flexible assessment philosophy is used, allowing for variations in assessment depending on the organizational context.[57]

An important discussion relates to the degree of individual traits contributing to the interpretation and effects of work stressors. Burr et al.[58] have discussed this problem. The more pronounced the subjective component of the reported stressor is, the higher the predictive value in relation to illness outcome. On the other hand, it is problematic from a work organization's point of view if the individual interpretation component is pronounced. Then, it may not be possible to translate the information into recipes for an improved work organization. In the collection of data from employees, the subjective input is more pronounced for the effort–reward and DR models than it is for the DC model.

A critique against the use of self-reported working conditions has been that self-reports may influence the individual's description of his/her psychological health and the working conditions. A study based on the Swedish Twin Registry[59] showed that while there is a genetic contribution to self-reports of demands, decision authority, and skill discretion, it is highly unlikely that this influence can explain associations between those three work characteristics on the one hand and self-reports of depressive symptoms on the other hand.

Family conflicts

An established anti-stressor is social support, both in life in general and at work.[60],[61] Our focus in this review is on “negative” stressors, although increasing attention is being paid both to marital and work–family conflicts which have been studied mainly in women. A prospective study of women with coronary heart disease showed that the risk of new heart disease episodes during a 5-year follow-up after the first episode was more pronounced in women with both marital conflicts and job strain[62] than in other participants. In addition, in the same study, quantitative coronary angiography was performed at disease onset and 3 years later.[63] In the group with neither job strain nor family conflict, the coronary atherosclerosis decreased (mean artery lumen mean increased by 0.2 mm), whereas in the group with both job strain and marital conflict, the coronary atherosclerosis became worsened (mean artery lumen decreased by 0.2 mm). During later years, there has been increasing attention on work–family conflict which is related to the development of cardiometabolic risk in women.[64] Accordingly, the combination of problems both at work and in private life and direct conflicts between work and family life are important stressors, particularly for women.

Importance of psychosocial stressors to ischemic heart disease and its risk factors

The referred studies do not cover the whole research field. The author has rather tried to illuminate some research areas that need to be “revisited.” In all the referred studies, there have been efforts to quantify the effects of psychosocial stressors on outcomes – ischemic heart disease or physiological responses to such stressors. The findings indicate the following:

  1. An accumulation of life events is mirrored in a moderate increase in urinary excretion of adrenaline in patients with ischemic heart disease – a doubled life change score from 1 week to the next was on average associated with a 30% increase in urinary adrenaline excretion. This association explained a moderate amount of variation (10%). There were pronounced individual differences in sensitivity to life change accumulation. The study was specifically focused on catecholamine excretion (adrenaline and noradrenaline) and thus the participants had standardized diet during 2 days preceding the urine collection and there was strict advice regarding smoking and alcohol consumption. No corresponding associations were observed for noradrenaline
  2. As a single measure assessed during a whole year, a high total life change score is not predictive of increased risk of developing a MI during the subsequent year. However, in patients with ischemic heart disease that are followed longitudinally, a buildup of a high life change score during 6 months could lead to increased heart load and increased risk of cardiac death with a delay of several months. This is, however, based on one solitary study and needs to be replicated in other studies
  3. Several independent epidemiological prospective studies have shown that particularly important life events such as divorce, loss of spouse, job loss, and markedly increased job responsibility are associated with increased risk of developing a MI. The increases in risk ratio are small to moderate but statistically significant
  4. Several psychosocial work stressors have been identified and there are also competing theoretical models. The most frequently used models in cardiological epidemiology are the DCS and the ER models. In work psychology, the DR model is frequently used. The DCS is constructed as mainly a stressor model whereas the ER and DR models include more of the worker's individual interpretation. Estimates from case–control and prospective studies point at relative risks for developing ischemic heart disease associated with the combination of high demands and low control at work (job strain) between 1.2 and 1.8 with a conservative mean of 1.3. Using the most frequent operationalization of job strain, this corresponds to an attributable fraction of 0.05 which means that 5% of ischemic heart disease could theoretically be prevented if job strain could be eliminated. Such calculations are adjusted for other accepted risk factors. Corresponding estimates for ER are similar and the two models only partly overlap. Therefore, the joint use of both models could improve predictions. If the stressors shift/night work, precarious employment status, extreme overtime work and lack of justice at work are also included the potential importance of the work environment increases in predictions. Similarly, if other disease endpoints are included such as depression, stroke, and onset of diabetes, the importance of the work stressors turns out to be even more important from a societal point of view
  5. Variations in job strain are mirrored in blood pressure variations, and the magnitude of these changes is partly determined by the individual's handling of emotions. Sleep quality and activity in regenerative hormones are also influenced by variations in job strain
  6. Stressors outside working life have not been explored to the same extent as work stressors. Studies on women have shown, however, that family conflicts and work stressors may both contribute to cardiovascular risk and that joint exposure may be of special importance to development of coronary atherosclerosis and cardiovascular disease risk among women who suffer from ischemic heart disease. Similar findings have been made for women using ambulatory blood pressure as endpoint.


Concluding remarks

The psychosocial stressors that have been discussed are established and have a role in the development of ischemic heart disease. Since the patients react with their cardiovascular system to these stressors, it is important for clinicians to pay due respect to these factors in clinical work. Several of the studies that have been referred to in this text need to be replicated.

Ethical statement

The Ethical Statement is not applicable for this article.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Theorell T. Anabolism and Regeneration – the Good Perspective. In: Theorell T, editoer. Handbook of Socioeconomic Determinants of Occupational Health. Ch. 30. London: Springer Books; 2020. p. 611-24.  Back to cited text no. 1
    
2.
Theorell TG. Review of research on life events and cardiovascular illness. Adv Cardiol 1982;29:140-9.  Back to cited text no. 2
    
3.
Theorell T. Evaluating life events and chronic stressors in relation to health: Stressors and health in clinical work. Adv Psychosom Med 2012;32:58-71.  Back to cited text no. 3
    
4.
Kanner AD, Coyne JC, Schaefer C, Lazarus RS. Comparison of two modes of stress measurement: Daily hassles and uplifts versus major life events. J Behav Med 1981;4:1-39.  Back to cited text no. 4
    
5.
Theorell T, Lind E, Fröberg J, Karlsson CG, Levi L. A longitudinal study of 21 subjects with coronary heart disease: Life changes, catecholamine excretion and related biochemical reactions. Psychosom Med 1972;34:505-16.  Back to cited text no. 5
    
6.
Holmes TH, Rahe RH. The social readjustment rating scale. J Psychosom Res 1967;11:213-8.  Back to cited text no. 6
    
7.
Theorell T, Rahe RH. Psychosocial factors and myocardial infarction. I. An inpatient study in Sweden. J Psychosom Res 1971;15:25-31.  Back to cited text no. 7
    
8.
Theorell T, Lind E, Flodérus B. The relationship of disturbing life-changes and emotions to the early development of myocardial infarction and other serious illnesses. Int J Epidemiol 1975;4:281-93.  Back to cited text no. 8
    
9.
Theorell T, Floderus-Myrhed B. 'Workload' and risk of myocardial infarction – A prospective psychosocial analysis. Int J Epidemiol 1977;6:17-21.  Back to cited text no. 9
    
10.
Möller J, Theorell T, de Faire U, Ahlbom A, Hallqvist J. Work related stressful life events and the risk of myocardial infarction. Case-control and case-crossover analyses within the Stockholm heart epidemiology programme (SHEEP). J Epidemiol Community Health 2005;59:23-30.  Back to cited text no. 10
    
11.
Starr I. Abnormal forms of the ballistocardiogram. Fed Proc 1946;5:100.  Back to cited text no. 11
    
12.
Erkinjuntti M, Kero P, Halonen JP, Mikola H, Sainio K. SCSB method compared to EEG-based polygraphy in sleep state scoring of newborn infants. Acta Paediatr Scand 1990;79:274-9.  Back to cited text no. 12
    
13.
Lynn TN, Wolf S. The prognostic significance of the ballistocardiogram in ischemic heart disease. Am Heart J 1974;88:277-80.  Back to cited text no. 13
    
14.
Theorell T, Blunk D, Wolf S. Ballistocardiographic indicators of prognosis in ischemic heart disease. J Lab Clin Med 1975;86:46-56.  Back to cited text no. 14
    
15.
Theorell T, Rahe CR. Life change events, ballistocardiography and coronary death. J Human Stress 1975;1:18-24.  Back to cited text no. 15
    
16.
Theorell T, Blunk D, Wolf S. Emotions and cardiac contractility as reflected in ballistocardiographic recordings. Pavlov J Biol Sci 1974;9:65-75.  Back to cited text no. 16
    
17.
Gallo WT. Evolution of research on the effect of unemployment on acute myocardial infarction risk. Arch Intern Med 2012;172:1737-8.  Back to cited text no. 17
    
18.
Dupre ME, George LK, Liu G, Peterson ED. Association between divorce and risks for acute myocardial infarction. Circ Cardiovasc Qual Outcomes 2015;8:244-51.  Back to cited text no. 18
    
19.
Mostofsky E, Maclure M, Sherwood JB, Tofler GH, Muller JE, Mittleman MA. Risk of acute myocardial infarction after the death of a significant person in one's life: The determinants of myocardial infarction onset study. Circulation 2012;125:491-6.  Back to cited text no. 19
    
20.
Kahn RL. On the meaning of work. J Occup Med 1974;16:716-9.  Back to cited text no. 20
    
21.
Sales SM, House J. Job dissatisfaction as a possible risk factor in coronary heart disease. J Chronic Dis 1971;23:861-73.  Back to cited text no. 21
    
22.
Karasek R. Job demands, job decision latitude and mental strain: Implications for job redesign. Adm Sci Q 1979;24:285-307.  Back to cited text no. 22
    
23.
Johnson JV, Hall EM. 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 1988;78:1336-42.  Back to cited text no. 23
    
24.
Karasek RA, Theorell T. Healthy Work. Basic Books. New York: 1990.  Back to cited text no. 24
    
25.
Theorell T, Jood K, Järvholm LS, Vingård E, Perk J, Östergren PO, et al. A systematic review of studies in the contributions of the work environment to ischaemic heart disease development. Eur J Public Health 2016;26:470-7.  Back to cited text no. 25
    
26.
Li J, Landsbergis P, Sembajwe G, Descatha A, Siegrist J. Comments to Moretti Anfossi et al.'s (2022) 'Work exposures and development of cardiovascular diseases: A systematic review': What Is current scientific consensus? Ann Work Expo Health 2022;66:822-4.  Back to cited text no. 26
    
27.
Theorell T, Perski A, Akerstedt T, Sigala F, Ahlberg-Hultén G, Svensson J, et al. Changes in job strain in relation to changes in physiological state. A longitudinal study. Scand J Work Environ Health 1988;14:189-96.  Back to cited text no. 27
    
28.
Kristenson M, Garvin P, Lundberg U, editors. The Role of Saliva Cortisol Measurement In Health And Disease. London: Bentham Books; 2012.  Back to cited text no. 28
    
29.
Theorell T, Karasek RA, Eneroth P. Job strain variations in relation to plasma testosterone fluctuations in working men – A longitudinal study. J Intern Med 1990;227:31-6.  Back to cited text no. 29
    
30.
Theorell T. Regeneration and anabolism. The good perspective. In: Theorell T, editor. Handbook of Socioeconomic Determinants of Occupational Health. Springer Books. Handbook Series in Occupational Health Sciences. Springer, London; 2020.  Back to cited text no. 30
    
31.
Shimomitsu T, Theorell T. Intraindividual relationships between blood pressure level and emotional state. Psychother Psychosom 1996;65:137-44.  Back to cited text no. 31
    
32.
Dich N, Rod NH, Doan SN. Both high and low levels of negative emotions are associated with higher blood pressure: Evidence from Whitehall II cohort study. Int J Behav Med 2020;27:170-8.  Back to cited text no. 32
    
33.
Rudolph KE, Sánchez BN, Stuart EA, Greenberg B, Fujishiro K, Wand GS, et al. Job strain and the cortisol diurnal cycle in MESA: Accounting for between- and within-day variability. Am J Epidemiol 2016;183:497-506.  Back to cited text no. 33
    
34.
Landsbergis PA, Dobson M, Koutsouras G, Schnall P. Job strain and ambulatory blood pressure: A meta-analysis and systematic review. Am J Public Health 2013;103:e61-71.  Back to cited text no. 34
    
35.
Tobe SW, Kiss A, Sainsbury S, Jesin M, Geerts R, Baker B. The impact of job strain and marital cohesion on ambulatory blood pressure during 1 year: The double exposure study. Am J Hypertens 2007;20:148-53.  Back to cited text no. 35
    
36.
Kivimäki M, Pentti J, Ferrie JE, Batty GD, Nyberg ST, Jokela M, et al. Work stress and risk of death in men and women with and without cardiometabolic disease: A multicohort study. Lancet Diabetes Endocrinol 2018;6:705-13.  Back to cited text no. 36
    
37.
Pan KY, Xu W, Mangialasche F, Dekhtyar S, Fratiglioni L, Wang HX. Working life psychosocial conditions in relation to late-life cognitive decline: A population-based cohort study. J Alzheimers Dis 2019;67:315-25.  Back to cited text no. 37
    
38.
Kivimäki M, Nyberg ST, Batty GD, Fransson EI, Heikkilä K, Alfredsson L, et al. Job strain as a risk factor for coronary heart disease: A collaborative meta-analysis of individual participant data. Lancet 2012;380:1491-7.  Back to cited text no. 38
    
39.
Kivimäki M, Jokela M, Nyberg ST, Singh-Manoux A, Fransson EI, Alfredsson L, et al. Long working hours and risk of coronary heart disease and stroke: A systematic review and meta-analysis of published and unpublished data for 603,838 individuals. Lancet 2015;386:1739-46.  Back to cited text no. 39
    
40.
Ferrie JE, Virtanen M, Jokela M, Madsen IE, Heikkilä K, Alfredsson L, et al. Job insecurity and risk of diabetes: A meta-analysis of individual participant data. CMAJ 2016;188:E447-55.  Back to cited text no. 40
    
41.
Knutsson A, Bøggild H. Shiftwork and cardiovascular disease: Review of disease mechanisms. Rev Environ Health 2000;15:359-72.  Back to cited text no. 41
    
42.
Knutsson A, Kempe A. Shift work and diabetes – A systematic review. Chronobiol Int 2014;31:1146-51.  Back to cited text no. 42
    
43.
Andreeva E, Magnusson Hanson LL, Westerlund H, Theorell T, Brenner MH. Depressive symptoms as a cause and effect of job loss in men and women: Evidence in the context of organisational downsizing from the Swedish longitudinal occupational survey of health. BMC Public Health 2015;15:1045.  Back to cited text no. 43
    
44.
Brenner MH, Andreeva E, Theorell T, Goldberg M, Westerlund H, Leineweber C, et al. Organizational downsizing and depressive symptoms in the European recession: The experience of workers in France, Hungary, Sweden and the United kingdom. PLoS One 2014;9:e97063.  Back to cited text no. 44
    
45.
Kivimäki M, Nyberg ST, Batty GD, Kawachi I, Jokela M, Alfredsson L, et al. Long working hours as a risk factor for atrial fibrillation: A multi-cohort study. Eur Heart J 2017;38:2621-8.  Back to cited text no. 45
    
46.
Theorell T, Hammarström A, Aronsson G, Träskman Bendz L, Grape T, Hogstedt C, et al. A systematic review including meta-analysis of work environment and depressive symptoms. BMC Public Health 2015;15:738.  Back to cited text no. 46
    
47.
Magnusson Hanson LL, Westerlund H, Chungkham HS, Vahtera J, Rod NH, Alexanderson K, et al. Job strain and loss of healthy life years between ages 50 and 75 by sex and occupational position: Analyses of 64 934 individuals from four prospective cohort studies. Occup Environ Med 2018;75:486-93.  Back to cited text no. 47
    
48.
Mutambudzi M, Theorell T, Li J. Job strain and long-term sickness absence from work: A ten-year prospective study in German working population. J Occup Environ Med 2019;61:278-84.  Back to cited text no. 48
    
49.
Theorell T, Tsutsumi A, Hallquist J, Reuterwall C, Hogstedt C, Fredlund P, et al. Decision latitude, job strain, and myocardial infarction: A study of working men in Stockholm. The SHEEP study group. Stockholm heart epidemiology program. Am J Public Health 1998;88:382-8.  Back to cited text no. 49
    
50.
Siegrist J. Adverse health effects of high-effort/low-reward conditions. J Occup Health Psychol 1996;1:27-41.  Back to cited text no. 50
    
51.
Siegrist J, Wege N. Adverse psychosocial work environments and depression-A narrative review of selected theoretical models. Front Psychiatry 2020;11:66.  Back to cited text no. 51
    
52.
Dragano N, Siegrist J, Nyberg ST, Lunau T, Fransson EI, Alfredsson L, et al. Effort-reward imbalance at work and incident coronary heart disease: A multicohort study of 90,164 individuals. Epidemiology 2017;28:619-26.  Back to cited text no. 52
    
53.
Dragano N, He Y, Moebus S, Jöckel KH, Erbel R, Siegrist J, et al. Two models of job stress and depressive symptoms. Results from a population-based study. Soc Psychiatry Psychiatr Epidemiol 2008;43:72-8.  Back to cited text no. 53
    
54.
Peter R, Siegrist J, Hallqvist J, Reuterwall C, Theorell T, SHEEP Study Group. Psychosocial work environment and myocardial infarction: Improving risk estimation by combining two complementary job stress models in the SHEEP study. J Epidemiol Community Health 2002;56:294-300.  Back to cited text no. 54
    
55.
Siegrist J, Li J. Work Stress and altered biomarkers: A synthesis of findings based on the effort-reward imbalance model. Int J Environ Res Public Health 2017;14:1373.  Back to cited text no. 55
    
56.
Eddy P, Wertheim EH, Hale MW, Wright BJ. A systematic review and meta-analysis of the effort-reward imbalance model of workplace stress and hypothalamic-pituitary-adrenal axis measures of stress. Psychosom Med 2018;80:103-13.  Back to cited text no. 56
    
57.
Demerouti E, Bakker AB, Nachreiner F, Schaufeli WB. The job demands-resources model of burnout. J Appl Psychol 2001;86:499-512.  Back to cited text no. 57
    
58.
Burr H, Formazin M, Pohrt A. Methodological and conceptual issues regarding occupational psychosocial coronary heart disease epidemiology. Scand J Work Environ Health 2016;42:251-5.  Back to cited text no. 58
    
59.
Theorell T, De Manzano Ö, Lennartsson AK, Pedersen NL, Ullén F. Self-reported psychological demands, skill discretion and decision authority at work: A twin study. Scand J Public Health 2016;44:354-60.  Back to cited text no. 59
    
60.
Berkman LF, Syme SL. Social networks, host resistance, and mortality: A nine-year follow-up study of Alameda County residents. Am J Epidemiol 1979;109:186-204.  Back to cited text no. 60
    
61.
Berkman LF. Assessing the physical health effects of social networks and social support. Annu Rev Public Health 1984;5:413-32.  Back to cited text no. 61
    
62.
Orth-Gomér K, Leineweber C. Multiple stressors and coronary disease in women. The Stockholm female coronary risk study. Biol Psychol 2005;69:57-66.  Back to cited text no. 62
    
63.
Wang HX, Leineweber C, Kirkeeide R, Svane B, Schenck-Gustafsson K, Theorell T, et al. Psychosocial stress and atherosclerosis: Family and work stress accelerate progression of coronary disease in women. The Stockholm female coronary angiography study. J Intern Med 2007;261:245-54.  Back to cited text no. 63
    
64.
Berkman LF, Liu SY, Hammer L, Moen P, Klein LC, Kelly E, et al. Work-family conflict, cardiometabolic risk, and sleep duration in nursing employees. J Occup Health Psychol 2015;20:420-33.  Back to cited text no. 64
    


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