The term "psychosocial work environment" appears frequently in research articles, including those published in the Scandinavian Journal of Work, Environment and Health. Recently, the first ...international handbook on the emerging field of "psychosocial epidemiology" extensively addressed the contribution of psychosocial working conditions to health and illness. There is, however, also a controversial debate pertaining to the meaning of the word "psychosocial" and whether it might enhance a focus on psychological phenomena and draw attention away from the work environment. Here, Rugulies provides some comments on this debate. He will first address the historical use of the term psychosocial work environment and then present a conceptual framework showing the relation of the psychosocial work environment to phenomena on both the societal and individual level.
Working hours, including the number and the arrangement thereof – such as shift work, night work, and quick returns – are classic topics in research on work environment and health. The struggle for ...working time reduction and the eight-hour work day is also one of the oldest fights of the labor movement, dating back to the 19th century (1). International Workers’ Day, celebrated annually on 1 May, has its origin in the Haymarket Affair, a rally in support of a strike for the eight-hour work day at the Haymarket Square in Chicago, USA, on 4 May 1886. At the rally, a riot broke out and a bomb exploded, killing several workers and police officers. In the aftermath, the State of Illinois prosecuted labor movement activists. Although the person who throw the bomb was never identified and the circumstances of the attack remained unclear, four labor movement activists, including August Spies, the editor of the German-American newspaper Arbeiter-Zeitung, were executed by hanging on 11 November 1887. A fifth activist died by suicide in prison (2). When the International Labour Organization (ILO) was established as an agency of the newly created League of Nations (the predecessor of today’s United Nations) after World War I in 1919, one of its main aims was the regulation and reduction of working time (1). The demand for the 8-hour work day and 48-hour work week was even included in the peace treaty of Versailles (Part XIII, Section II, Article 427) that was signed on 28 June 1919 following World War I (3, 4). Although working hours have been greatly reduced in many high-income countries since the 19th century, particularly in Europe, the discussion about working hours remains topical, as can be seen by the recent debate about a 4-day working week (5, 6). In South-East and East Asian countries, such as Japan, South Korea, and Taiwan, where working hours >48 hours per week are still widely prevalent, health concerns of such long working hours are an important topic of discussion (7, 8). Notably, the Japanese language has coined two terms: karōshi for death due to overwork (usually of cardiovascular causes) and karōjisatsu for death by suicide due to overwork (9). At the Scandinavian Journal of Work, Environment & Health, we regularly receive papers from researchers in Asia examining the health effects of long working hours (10–12). This issue includes a paper from a German research group on the association between night shift work and risk of cardiovascular disease (13). I use this opportunity to reflect briefly in this editorial on research on working hours and cardiovascular health. In the May issue (number 4) of the Journal, as part of our 50-year anniversary special publication series (14, 15), there will be a much more detailed account on what we have learned so far on working hours and health. Long working hours and cardiovascular disease In 2015, Kivimäki et al (16) published a seminal paper on long working hours and cardiovascular disease for the Individual Participant Data Meta-Analysis of Working Population (IPD-Work) Consortium that showed an association of long working hours with an increased risk of both ischemic heart disease and stroke (16). The association was stronger for stroke than ischemic heart disease (pooled relative risks 1.33 versus 1.13). Furthermore, for stroke, but not ischemic heart disease, the analyses suggested an exposure–response pattern. Thus, the longer the working hours, the greater the risk of stroke. From 2017 to 2021, the World Health Organization (WHO) and ILO conducted a project on the WHO/ILO Joint Estimates of the Work-Related Burden of Disease and Injury (17, 18) that included systematic reviews on the association of long working hours and risk of ischemic heart disease (19) and stroke (20). Results were similar to those reported by the IPD-Work Consortium in 2015. Long working hours, defined as ≥55 hours per week, were associated with a small increased risk of ischemic heart disease (pooled risk ratio 1.17) (19) and a larger increased risk of stroke (pooled risk ratio 1.35) (20). Based on these risk estimates and estimates on the country-specific prevalence of long working hours, the WHO and ILO estimated that, in 2016, globally 745 194 deaths were attributable to long working hours, with the largest burden in South-East Asia (17, 18, 21). A summary of the WHO/ILO joint estimates project has been published as a discussion paper in our Journal (22), together with an editorial (23). Obviously, the estimate of approximately 750 000 annual deaths due to long working hours is based on several assumptions, including that the epidemiological studies` estimates indicate a causal association between long working hours and cardiovascular outcomes and that data on the worldwide prevalence of long working hours are valid. Kivimäki and colleagues (24) expressed concerns about the interpretation that there is sufficient evidence for harmfulness of long working hours with regard to ischemic heart disease. Among other things, the authors were concerned about residual confounding (eg, by health-related behaviors, although it is debated whether they are mainly confounders, for which one should control, or mediators, for which one should not control (25)). They also presented analyses of data that suggested that socioeconomic position might be an important effect modifier and that the harmful effect of long working hours on risk of ischemic heart disease may be limited to workers of low socioeconomic position. As socioeconomic position is linked to the type of work the workers are doing, the possible effect modification by socioeconomic position could also mean that other, unmeasured working conditions may modify the association between long working hours and health. In other words, in addition to the length of the working hours, what happens during these working hours might also be important. In Denmark, Hannerz and colleagues (26, 27) attempted to replicate the analyses on long working hours and ischemic heart disease and stroke using large-scale register data. With regard to ischemic heart disease, they did not find an increased risk with long working hours rate ratio (RR) 1.07, 95% confidence interval (CI) 0.94–1.21 for >48 versus 32–40 hours (26). When stratified by socioeconomic position, long working hours were not associated with an increased risk of ischemic heart disease among workers of high, medium and unknown socioeconomic position, but there was an increased risk among workers of low socioeconomic position that worked long hours (RR 1.27, 95% CI 1.05–1.53). Although the interaction `long working hours × socioeconomic position` was not statistically significant, this increased risk among workers of low socioeconomic position is in agreement with the analyses by Kivimäki et al (24). With regard to stroke, Hannerz et al (27) did not find an increased risk for all types of stroke combined among those with long working hours, however, they reported an association between long working hours and increased risk of hemorrhagic stroke. This result was recently replicated in an analysis of the French CONSTANCES study (28) where exposure to long working hours during the past ten years was, in the adjusted model, associated with an increased risk of hemorrhagic stroke but not ischemic stroke. One can summarize that during the past ten years, several large-scale studies and meta-analyses on long working hours and cardiovascular outcomes have been published. Whereas the WHO has concluded that there is sufficient evidence for harmfulness for the association between long working hours and ischemic heart disease and stroke (19–21), other studies point to possible effect modification by socioeconomic position (24, 26) with regard to ischemic heart disease and the need to distinguish between ischemic and hemorrhagic stroke (27, 28). Shift work, night shift work and cardiovascular disease In 2018, Torquati et al (29) published a systematic review and meta-analysis that showed an increased risk of cardiovascular disease among shift workers. For those working shifts for five years, each additional five-year period of shift work was associated with a 7% increased risk of cardiovascular disease. Night shift work has been of particular interest for cancer research (30) but might also be relevant with regard to cardiovascular diseases. In their recent review and meta-analysis, Su et al (31) reported that night shift work was associated with an increased risk of cardiovascular mortality (pooled estimate 1.15, 95% CI 1.03–1.29). However, only four studies were included in this review. In 2022, a Swedish research group published two papers on night shift work from a large sample of healthcare workers in Stockholm, one on cerebrovascular disease and the other on ischemic heart disease. Bigert et al (32) reported that frequent night shifts and frequent consecutive night shifts were associated with an increased risk of cerebrovascular disease, including stroke. Kader et al (33) reported that permanent night shifts and frequent night shifts were associated with an increased risk of ischemic heart disease. In Denmark, Vestergaard et al (34)examined the association between night shift work and ischemic heart disease in a large-cohort of healthcare workers with day-to-day payroll information. The results were less clear than those of Kader et al (33): male, but not female, healthcare workers with night work had an increased risk of ischemic heart disease compared to day-time workers. The paper by Jankowiak et al (13) in the current issue of the Journal examined night shift work and risk of cardiovascular disease in a population-based cohort in the city of Mainz and Mainz-Bingen in Germany (13). The hazard ratios for low, middle, and high night shift work were 1.19, 1.32, and 1.14, respectively, compared to no night shift work, in the most-adjusted model. An important strength of the study is the comprehensive clini
We live in unprecedented modern times experiencing how an outbreak of a particular viral disease, COVID-19, caused by SARS-CoV-2, also commonly referred to as the Coronavirus, is disrupting societies ...and personal lives. The virus is likely to spread to most, if not all, countries, illustrating the interconnectedness of the world. While many national measures to contain, suppress, mitigate, or delay the spread of the virus are being taken, there is great uncertainty as to which measures are appropriate or not, varying from instructions of stringent hand hygiene; travel restrictions; social distancing; and closure of schools, restaurants, bars and shops to a complete lock down of large parts of society. Here, Burdorf et al discuss the long-lasting societal effects of this pandemic.
The Nordic countries have a long tradition of research studying the impact of the psychosocial work environment on health (1, 2). Fittingly, the Scandinavian Journal of Work, Environment and Health ...has been a key place for the presentation and discussion of studies examining the complex relations between working conditions, psychological processes, and health and illness. Chances are high that this will continue in the foreseeable future as an increasing proportion of the workforce, particularly – but not exclusively – in high-income countries, is facing potentially health-affecting psychosocial working conditions, such as working with people in need, team work, demands for high flexibility, job insecurity, international competition, or working with tight deadlines – to name just a few examples (3). Additionally, mental ill-health, which is known to be caused to a substantial extent by adverse psychosocial circumstances in life (4), is on the rise to become the leading cause of disability-adjusted life years lost in high-income countries (5). Examining whether and how psychosocial working conditions contribute to mental ill-health, and ultimately how this knowledge can be used for preventive efforts, is an important task for occupational health research (6, 7). Over the last decade, major improvements have been made in the designs of psychosocial work environment studies. Earlier research has often been hampered by an over reliance on cross-sectional data, with the immanent limitations in establishing temporality of exposure and outcome and drawing causal inference (8). Today, however, data from several large-scale cohort studies are available, not least in the Nordic countries. The number of cohort studies has grown to such an extent that a European Research Consortium recently launched a project on an “Individual-participant-data meta-analysis of working populations” (IPD-Work), aiming to synthesize the data from the numerous European psychosocial work environment cohort studies (9). Despite this progress, there are still important methodological challenges that need to be tackled. A major concern is how the psychosocial work environment can be assessed in the most precise and unbiased way. Self-administered questionnaires. By far, the most widely-used method for assessing the psychosocial work environment is the self-administered questionnaire. Several instruments with good psychometric properties have been developed, both for testing specific theoretical models (10, 11) and assessing the psychosocial work environment in all its broadness (12–14). Using self-reported data has many advantages. First, it is a convenient and cost-effective way to collect a lot of information from a large number of people, the latter being necessary when the aim is to investigate incident of disease. Second, workers are the obvious experts of their own workplaces; they are likely those who know most about their work environment. Third, questionnaires enable researchers to enquire about typical or average working conditions and are not restricted to the work environment of a specific day. These important advantages must be balanced against one major disadvantage. The response in self-administered questionnaires is in all likelihood not only driven by characteristics of the work environment (ie, the entity that is intended to be measured) but also by other factors, such as personal dispositions, mood, expectations, previous experiences, or health. This might cause both non-differential and differential misclassification, resulting in under- and overestimations of effects. For researchers mainly focused on how individual differences shape the perception and appraisal process of the person (15), the precise measurement of psychosocial working conditions might be of lesser concern. However, for researchers interested in the characteristics of the work environment that harm, protect or promote workers’ health, the most accurate and valid assessment of psychosocial working conditions is a major concern. This concern is, of course, not new. In the 1980s, scholars such as Kasl, Frese, and Zapf already warned against the naive use of self-reported exposure data in studies on psychosocial work environment and health (16, 17). Thus, the problem is not that the research community is unaware of the limitations of self-administered questionnaires; the problem is to find the right solutions. There are, for example, alternatives to self-administered questionnaires, but, not surprisingly, each alternative has its own challenges. Workplace aggregation of self-reported data. The purpose of aggregating individual responses to group levels in the workplace (eg, departments or work groups) is that the influence of individual factors can be reduced and the shared work environment can be carved out. The method has been used in some studies (18–20), but has also been discussed controversially (21). Particular challenging is the identification of the organizational level at which individuals have a sufficient amount of shared work environment. Also, whereas certain workplace characteristics (eg, organizational justice) appear well-suited for workplace aggregation, other characteristics (eg, decision authority) might be better suited for aggregation at the job title instead of at the workplace level. To complicate things further, sometimes the non-shared work environment could be the most important exposure. Imagine a workplace where a high level of social coherence is achieved by the social exclusion of some selected employees. Whereas the social cohesion score of the workplace is likely high, the score of these selected employees is likely low. This might lead investigators to conclude that the scores of these employees are biased by individual characteristics, such as negative affectivity, whereas in fact the contrast between the high social cohesion score at the group level and the low score for these selected employees is the pivotal workplace exposure in this example. Observer-based assessments. One of the most advanced methods for observer-based assessments of the psychosocial work environment is the RHIA/VERA method, which is a German acronym for “Regulationshindernisse in der Arbeitswelt/Verfahren zur Ermittlung von Regulationserfordernissen”. The method, which is based on action-regulation theory, was developed by work and organizational psychologists in Germany in the 1980s (22, 23) and has been tested in several countries (24–26). A major advantage is that the objective of interest, the working conditions, are directly observed. A major disadvantage is that the assessment is time-consuming and costly. Moreover, psychosocial exposures, such as bullying, threats, or violence at work, which are important predictors of mental ill-health (27–29), are unlikely to surface in the presence of an observer. Further, although the method avoids bias resulting from employees’ individual characteristics, bias resulting from observers’ individual characteristics is possible. Assessment by register data. Recently, Virtanen et al (30) used register data on hospital ward overcrowding as an indicator of high workload among hospital staff. The authors found a clear dose–response pattern between the level of ward overcrowding and risk of antidepressant treatment among the employees at these wards. In this issue of the Scandinavian Journal of Work Environment and Health, Ervasti and colleagues (31) present a register-linkage study that examined the effect of the psychosocial work environment in schools on risk of sickness absence of teachers. This topic is highly relevant. Sickness absence has evolved as a major research theme, in particular in the Nordic countries (32, 33). Although sickness absence is a complex phenomenon, influenced not only by health but by other factors as well (34), it is nevertheless an excellent indicator of both physical and mental ill-health (35, 36). Human service work, including teaching, and the emotional demands associated with working with people, is suspected to increase risk of mental ill-health of employees and subsequent sickness absence (37, 38). Investigating this association is, however, difficult, because pre-clinical conditions of ill-health at baseline might cause participants to overestimate quantitative and emotional demands when working conditions are assessed by self-report. Ervasti et al used register data on the proportion of pupils with special educational needs (SEN) at the schools as a measure of psychosocial working conditions. They found that risk of sickness absence increased with the percentage of SEN pupils, and that this association was stronger in schools with a high pupil–teacher ratio. Thus, the authors identified a prospective association between a specific working condition and risk of sickness absence. Their analyses also suggested a clear solution: increase teaching staff in schools with a high percentage of SEN pupils. Moreover, Ervasti et al (31) adjusted their analyses for average income level of residents in the school neighborhood, thereby addressing another important issue: the role of contextual factors in studies on psychosocial work environment and health (39). Despite its merits, the article by Ervasti et al also illustrates the limitations of register-linkage studies. As the authors themselves point out, the study does not provide insight into the specific mechanism that links the proportion of SEN pupils to risk of sickness absence. A high proportion of SEN pupils might add to the quantitative workload of teachers, it might qualitatively change the teachers’ work environment, for example by increasing social conflicts and decreasing social cohesion in the class, or it might generally cause a feeling of insufficiency among teachers who were not adequately trained to teach SEN pupils. Important effect modifiers might be the attitude and reactions of the other students and their parents toward
The Scandinavian Journal of Work, Environment & Health was launched 50 years ago. In this paper we describe how research topics have changed over time.
A complete list of all 2899 articles in the ...past 50 years was compiled. Each article was coded for type of exposure, type of health outcome, research design, first author, and country of correspondence address. Count of citations was based on the Scopus database.
Overall, the attention for chemical exposure in the first 30 years has shifted towards the psychosocial work environment, shift work, and physical work load. These shifts in exposure are mirrored by increased attention over time for mental disorders and musculoskeletal disorders. Cardiovascular disorders and cancer have been studied consistently over the past 50 years. Researchers from Scandinavian countries have been responsible for about 50% of the Journal's content, while authorship has broadened to about 30 countries in recent years.
During the past 50 years, some research topics have consistently remained highly visible in the Journal, whereas other topics have gained or lost interest. In terms of authors' contribution, the Journal has its roots in research from the Nordic countries, but has evolved over time as a truly international periodical with a well-recognized position in research on occupational health.
With this first issue of 2024, we kick off the celebration of 50 years of publishing research in the Scandinavian Journal of Work, Environment & Health. In January 1975, the inaugural issue of the ...Journal was published (read it here: www.sjweh.fi/issue/274). We are delighted that 50 years later not only are we still around, but we have retained our special position in the science publication business as an independent journal that is not owned by a commercial publishing house. We are grateful that our not-for-profit publisher, the Nordic Association of Occupational Safety and Health (NOROSH), has ensured this independence. And we are proud to belong to a community of authors, reviewers, editors, international advisory board members, and, of course, readers that is committed to research excellence and has carried this journal for now half a century. Thank you!
We want to celebrate our anniversary by looking both back and ahead. In each issue of 2024, we will include an invited 50-year-anniversary article, authored by leading researchers in the field. In this first issue, we take a look at ourselves, reflecting on work environment exposures and health outcomes that have emerged as well as those that have vanished from the pages in the Journal. And we take a look at those papers that have generated the greatest interest among our readers (1).
In the coming year, various authors will take a look at the research field, that is, they will discuss specific work environment conditions and health outcomes. This will include exposures as diverse as asbestos and the psychosocial work environment and outcomes such as musculoskeletal disorders and occupational cancers. We will in particular examine the successes and failures with regard to these exposures and outcomes. Has occupational health research made a difference? Are there success stories where our research has helped to protect and improve workers’ health and thereby contributed to a better population health? Did we provide solid evidence on health hazardous, health-protecting, and health enhancing working conditions and did this result in changes at the workplace? Or did we fail? Was our research not good enough to provide sufficient evidence for action? Or was our research good enough but action still did not happen? And what can we do in the future to improve? How can we do research better and thus make a difference in society?
We are looking forward to the answers to these questions in the anniversary-related papers, which are incidently not yet written, so we do not know what they will tell us. Our guess is, though, that there are no easy answers and a lot of work still remains ahead of us. We and others have recently argued in a Discussion Paper series on “Work and Health” in The Lancet that “major gains in population health and reductions in health disparities can be made by an increased focus on improving the work environment.” (2). However, as we also argue in the series, there is still a long way to go in realizing the potential that good work has for better population health (2–4).
Our objective with 50-year SJWEH anniversary series is that, by the end of the year, the occupational health community will have become more knowledgeable about what went well and not so well in our research field and that we feel confident where to go next. To engage the community further in this discussion, we are planning a half-day in-person and online symposium on 4 October 2024. We are still working on the exact format and content of the symposium. Please stay tuned on LinkedIn and follow the updates in our newsletter.
References 1. Burdorf A, Rugulies R. Fifty years of research in the Scandinavian Journal of Work, Environment & Health. Scand J Work Environ Health. 2024;50(1):3–10. https://doi.org/10.5271/sjweh.4135 2. Frank J, Mustard C, Smith P, Siddiqi A, Cheng Y, Burdorf A, et al. Work as a social determinant of health in high-income countries: past, present, and future. Lancet. 2023;402(10410):1357-1367. https://doi.org/10.1016/S0140-6736(23)00871-1 3. Rugulies R, Aust B, Greiner BA, Arensman E, Kawakami N, LaMontagne AD, et al. Work-related causes of mental health conditions and interventions for their improvement in workplaces. Lancet. 2023;402(10410):1368-1381. https://doi.org/10.1016/S0140-6736(23)00869-3 4. Burdorf A, Fernandes RCP, Robroek SJW. Health and inclusive labour force participation. Lancet. 2023;402(10410):1382-1392. https://doi.org/10.1016/S0140-6736(23)00868-1
At the Scandinavian Journal of Work, Environment & Health, it is our fundamental conviction that workers’ health is a value in itself. To put it simply, work must not be health-hazardous, and work ...must not make the worker neither physically nor mentally sick. In our minds, there is no need for any further rationale for healthy and safe work. That said, it would be naïve to think that, in a bottom-line world, the bottom-line would not count with regard to work and health. It does count at individual, company, and societal level. At individual level, a worker may worry about reduced payment during sickness absence. At company level, the phrase “is there a business case?” is often heard. At societal level, all economic consequences, rather than a partial interest, are considered. Therefore, there is a broad need to know the magnitude of the economic loss that comes with a health-hazardous work environment and, vice-versa, the magnitude of the economic benefit that comes with improving the work environment. For example, when the World Health Organization (WHO) published in 2022 its landmark guidelines on mental health at work using a societal perspective (1), a lot of attention was paid to the WHO`s estimation that the global economic costs of the most prevalent mental health conditions totalled USD1 trillion per year (2, 3). There is, thus, a great demand for work environment economics, for analyses that quantify the economic costs of a poor work environment and the economic benefits of a good work environment. However, this demand is yet not being met by the research community. As van Dongen & van der Beek (4) delineated in an editorial in this Journal in May 2022, there are two types of work environment economic studies: (i) observational studies that examine the economic costs of work-related ill-health among workers, the so-called `cost of illness` studies and (ii) economic evaluation studies that examine cost-effectiveness and return-on-investment of occupational health interventions. With regard to the latter, van Dongen & van der Beek point to a couple of recent promising evaluation studies (5, 6), however, they conclude that the methodological quality of economic evaluations of occupational health interventions leaves in general a lot to be desired (4). With regard to the former, observational studies on the economic costs of work-related ill-health among workers, Russo et al (5) recently published in this Journal a cost-estimation model for work-related stress that was tested in two case studies in Italy – in healthcare and public administration. Costs were estimated as loss of productivity due to sickness absence attributable to work-related stress. The authors showed that across different work organizations, the proportion of sickness absence attributable to work-related stress varied strongly, and that methodological choices influenced the cost estimations largely. In this issue of the Journal, Pedersen and colleagues (7) go a step further and present a paper that aims to estimate the effect of work-related stress on labor market costs at the societal level. Linking survey data from Denmark on indicators of self-reported work-related stress to register data on labor market affiliation, they first calculated the two-year prospective association between exposure to work stress and days of recurrent (being at work, sickness absence, unemployment, being temporarily out of the labor market for other reasons) and absorbing (retirement, disability pension, death) labor market states. Absorbing states occurred only rarely in their sample. Next, they calculated the costs incurred by the recurrent labor market states, ie, the costs associated with days lost due to all work absenteeism combined and work absenteeism stratified by sickness absence, unemployment, and being temporarily out of the labor market. Based on these calculations, the authors estimated an average annual work absenteeism loss per employee of €1903 for men and €3909 for women. For the Danish workforce, this corresponds to annual expenses of €305 million among men and €868 million among women, a total expense of €1.17 billion or 0.3% of the Danish gross domestic product in 2022. The results of this article caused a lot of interest in the Danish media and among unions and employer organizations (8, 9). We commend the authors for their bold approach to estimate the costs of an assumed work-environment-induced health condition at the societal level, taking advantage of the excellent Danish health and labor market registers and using multi-state modeling that takes recurrence of events into consideration. There are, though, also important challenges in the article, relating both to the outcome and health condition under study. Regarding the outcome, there are two major labor market costs to consider: (i) costs related to absenteeism, ie, costs due to not being at work, and (ii) costs related to loss of productivity, ie, costs due to being at work but with reduced work capacity. Pederson and colleagues limited their analyses to the former and did not analyze the latter. This is understandable, as absenteeism can be closely monitored in Danish national registers, whereas no national register is available for monitoring the productivity of workers. In terms of internal validity, it was therefore likely a wise decision by the authors to limit the analyses to an outcome where good data is available. However, as a consequence, an important part of the labor market costs of work-related stress – the loss in productivity among those who are present at work with reduced work capacity – could not be addressed in the article. Regarding the health condition under study, the authors analyzed work-related stress. On the one hand, this is laudable, stress at work is topical and a major point of public debate in many countries, including Denmark. On the other hand, the authors could hardly have chosen a more difficult health condition. Stress is on many accounts an intricate, some would say, hopeless concept in research. Since the early days of stress research by Walter B Cannon (1871–1945) and Hans Selye (1907–1982), the concept of stress has been plagued with ambiguities (10, 11). Today, there is no lack of elaborated stress models (stimulus-based models, reaction-based models, the transactional model, the allostatic load model, the cognitive-activation theory of stress, to name just a few) (12–14). However, there is no common definition of stress, and there is no agreement on basic questions, such as if stress research should focus on the environmental conditions (often called “stressors”) that may cause cognitive, emotional, behavioral, and physiological changes in the individual (often called “stress reactions”) or if the focus should be on these stress reactions of the individual and how these different types of reactions are related to each other. To make things further complicated, Pedersen and colleagues not only analyzed “stress”, but they analyzed “work-related stress”, thus, they based their analyses on the assumption that the stress condition reported by the participants were, to a considerable extent, caused by the work environment. To ensure the work-relatedness of their stress concept, Pedersen and colleagues combined three very different measures into one index. The three measures included (i) a kind of self-labeling method, where the definition of stress and the attribution to work or none-work related causes were solely at the discretion of the respondents; (ii) the measurement of a psychosocial work environment condition, job strain, that has been conceptualized as a stressor, ie, as an entity that is assumed to elicit stress reactions (15); and (iii) four items of Cohen’s Perceived Stress Scale (PSS-4), which is probably the most widely used questionnaire for assessing stress (16, 17), however, in a modified version that included references to work in three of the four items. When taking a closer look at the three stress measures, one cannot help but to wonder whether the stress index by Pedersen and colleagues is rather a measure of poor psychosocial working conditions than a measure of stress. One of the three measures, job strain, obviously, is conceptualized as a measure of psychosocial working conditions, defined by the simultaneous exposure of high job demands and low job control (15). But also the modified PSS-4 items that asked, for example, about feeling that difficulties at work were piling up or feeling confident about handling problems at work, may have captured important parts of the psychosocial work environment. Thus, it could be argued that the article is first and foremost about the labor market costs of poor psychosocial working conditions. To summarize, Pedersen and colleagues provided us with a thought-provoking paper on two hot but also very challenging topics in occupational health research, work-related stress and work environment economics. Both topics are likely strongly shaped by macro-level structural conditions that vary greatly between countries(18, 19). We look forward to further analyses and papers on these topics from other regions of the world. Conflict of interest statement Reiner Rugulies is employed at the same research institution as the authors of the article by Pedersen et al, and he collaborates closely with the last author (Ida EH Madsen). Dr Rugulies was neither involved in the design, analysis or writing of the article nor in the decision by the journal to accept the article for publication. References 1. World Health Organization. WHO guidelines on mental health at work. Geneva: World Health Organization, 2022. Available from: https://www.who.int/publications/i/item/9789240053052 (Accessed: 28 September 2022). 2. World Health Organization and International Labour Organization. Mental health at work: Policy brief. Geneva: World Health Organization and International Labour Organization, 2022. Availabl
In the past three years, we have witnessed the devastating effects of the COVID-19 pandemic, with unprecedented challenges to all aspects of human life worldwide. In the workforce, it rapidly became ...clear that workers in some jobs were more likely to suffer adverse consequences for morbidity and mortality. In our earlier editorials in the Scandinavian Journal of Work Environment and Health, we reviewed emerging evidence, suggesting that well-established socio-economic health inequalities intermingled with occupational risk factors, making it difficult to target the conditions at work that contributed to the transmission of SARS-CoV-2 in working populations (1, 2). As a first priority for the research agenda on COVID-19, we suggested the identification of occupations at higher risk for becoming infected and specific work characteristics that contribute to the risks. Such insights will be immensely valuable for preparedness to threats of future pandemics (2).
Many researchers have addressed this pertinent question with gusto in different populations with different study approaches. In an illustrative example with a population-based approach, Nafilyan and colleagues (3) constructed a register-based cohort study of all 14 million people aged 40–64 years in England for confirmed or suspected COVID-19 death in 2020 across 41 occupational categories. Occupations with the highest age-standardised mortality rates (5–6-fold) were those working as taxi and cab drivers or chauffeurs, workers in elementary occupations, and care workers and home carers. Adjustment for sociodemographic factors attenuated the elevated mortality rates, and further adjustment for living conditions resulted in a residual variance of 20–30% as the best estimate of the maximum contribution of workplace exposure to COVID-19 mortality (3). A comparable registered-based study in Sweden among 4.6 million citizens with an occupation confirmed the highest mortality risk among taxi and bus drivers (4-fold risk), and also pointed towards elevated risk among cleaners and service workers. Likewise, adjustment for socioeconomic factors, such as education and income, greatly reduced the excess risk due to occupation. In contrast, country of birth and income tertile were the strongest socioeconomic determinants of COVID-19 mortality, and these associations were only marginally attenuated by adjustment for occupational groups (4).
In countries with advanced hospital admission registers, occupational risk of COVID-19 related hospital admission can be studied. In Denmark, Bonde et al (5) reported an increased risk for hospitalization due to COVID-19 among healthcare workers, social workers, and a few occupations within transportation compared to office workers. Risk of hospital admission was also increased among spouses of workers in occupations with a high COVID-19 risk (6). The excess risk for hospital admission among healthcare workers, but not among other high-risk occupations, attenuated in the latest COVID-19 waves (7).
Do these studies point towards the conclusions that occupation will at best play only a minor role in COVID-19 mortality? From a methodological point of view, we need to consider whether adjustment for education and income in the association between occupation and COVID-19 mortality is a sound strategy. Since education partly determines working careers and, thus, occupations that people will hold, over-adjustment may be a serious risk. From an exposure point of view, we would preferably measure airborne exposure of SARS-CoV-2 across occupations, and subsequently link levels of exposure across occupations to mortality patterns. Unfortunately, measuring exposure to a coronavirus is still a farfetched dream, although newly developed methods for waste-water surveillance may hold some promise (8).
An alternative to hospitalization and mortality studies is to study SARS-CoV-2 infection rates across occupations. Early reports have shown that this is not a simple task. There are a variety of reasons why people get tested for SARS-CoV-2, such as access at work and employer requirements on testing regimes. Thus, differences in likelihood of being tested may contribute to biased comparisons across occupations (9). Recently, the test-negative design has been advocated as suitable design, eliminating bias through likelihood of being tested by comparing those with a positive test to those with a negative test, thus excluding those who have never been tested from the reference group (10).
In this issue of the Scandinavian Journal of Work Environment and Health, the study by Eekhout and colleagues illustrates its usefulness (11). Based on over 200 000 workers with serological SARS-CoV-2 test results, the test-negative design was applied to identify occupations with increased risk for infections, while simultaneously talking into account potential confounders, such as socioeconomic position and household composition. Occupations with high infection rates were quite similar to those reported in the mortality studies described above, with many elementary and manually skilled jobs showing the highest probability to a positive test. The study also applied a job exposure matrix (12) with four work-related factors that could influence the transmission of SARS-CoV-2 at the workplace. Findings showed modestly increased odds of a positive test for these risk factors, and adjustment for several covariates slightly decreased or increased the odds ratios. However, due to substantial collinearity between these work-related risk factors, it was not possible to single out the relative contribution of each factor separately to the infections rates. The magnitude of the observed odd ratios (varying between 1.1 to 1.8) and the prevalence of the work-related risk factors suggest that the proportion of SARS-CoV-2 infections in the general population that is attributable to factors at work will not exceed 30%. This is in line with results of another job-exposure matrix, applied in a French cohort, suggesting that the proportion of COVID-19 cases attributable to work was 20–40% (13).
Why are some occupations at risk and others not? Recent studies have reported in many occupations elevated risks of COVID-19 related morbidity and mortality. The occupational risk factors seem to be interrelated to well-established socioeconomic determinants of health inequalities that are also applicable to COVID-19. The few studies on associations between work-related risk factors and SARS-CoV-2 infection rates provide a rather scattered picture. This is likely partly due to uncertainty about mechanisms of transmission and appropriate mitigation measures (14). Emerging evidence clearly indicates that work plays a role, albeit limited, in the transmission of the coronaviruses and, as such, offers a point of entry for prevention strategies. We must learn from the valuable experiences in the past three years how conditions at the workplace have contributed to the rise and fall of the COVID-19 pandemic.
References 1. Burdorf A, Porru F, Rugulies R. The COVID-19 (Coronavirus) pandemic: consequences for occupational health. Scand J Work Environ Health 2020;46:22930. https://doi.org/10.5271/sjweh.3893 2. Burdorf A, Porru F, Rugulies R. The COVID-19 pandemic: one year later - an occupational perspective. Scand J Work Environ Health 2021;47:2457. https://doi.org/10.5271/sjweh.3956 3. Nafilyan V, Pawelek P, Ayoubkhani D, Rhodes S, Pembrey L, Matz et al. Occupation and COVID-19 mortality in England: a national linked data study of 14.3 million adults. Occup Environ Med 2022;79:433-41. https://doi.org/10.1136/oemed-2021-107818 4. Billingsley S, Brandén M, Aradhya S, Drefahl S, Andersson G, Mussino E. COVID-19 mortality across occupations and secondary risks for elderly individuals in the household: A population register-based study. Scand J Work Environ Health 2022;48:52-60. https://doi.org/10.5271/sjweh.3992 5. Bonde JP, Sell L, Meulengracht Flachs E, Coggon D, Albin M, Oude Hengel KM, et al. Occupational risk of COVID-19 related hospital admission in Denmark 2020-2021: a follow-up study. Scand J Work Environ Health 2023;49:84-94. https://doi.org/10.5271/sjweh.4063 6. Bonde JP, Mølenberg Begtrup L, Coggon D, Høy Jensen J, Meulengracht Flachs E, Jakobsson K, et al. COVID-19-related hospital admission in spouses of partners in at-risk occupations. Scand J Work Environ Health. 2023;49(3):193-200. https://doi.org/10.5271/sjweh.4080 7. Bonde JP, Sell L, Høy Jensen J, Mølenberg Begtrup L, Meulengracht Flachs E, Jakobsson K et al. Ocupational risk of COVID-19 across pandemic waves: a two-year national follow-up study of hospital admissions. Scand J Work Environ Health 2022;48:672-77. https://doi.org/10.5271/sjweh.4056 8. Nauta M, McManus O, Træholt Franck K, Lindberg Marving E, Dam Rasmussen E, et al. Early detection of local SARS-CoV-2 outbreaks by wastewater surveillance: a feasibility study. Epidemiol Infect 2023;151:e28. https://doi.org/10.1017/S0950268823000146 9. van Tongeren M, Rhodes S, Pearce N. Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health. 2022;48:586-57. https://doi.org/10.5271/sjweh.4052 10. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The evolving usefulness of the test-negative Design in studying risk factors for COVID-19. Epidemiology 2022;33:e7-e8. https://doi.org/10.1097/EDE.0000000000001438 11. Eekhout I, van Tongeren M, Pearce N, Oude Hengel KM. The impact of occupational exposures on infection rates during the COVID-19 pandemic: a test-negative design study with register data of 207 034 Dutch workers. Scand J Work Environ Health. 2023;49(4):259-270. https://doi.org/10.5271/sjweh.4086 12. Oude Hengel KM, Burdorf A, Pronk A, Schlünssen V, Stokholm ZA, Kolstad HA, et al. Exposure to a SARS-CoV-2 infection at work: development of an international job exposure matrix (COVID-19-J
The COVID-19 pandemic is discussed. This report points to the importance of occupation as a risk factor but also to the availability and use of appropriate personal protection to mitigate the risk of ...becoming infected. In addition, well-established socioeconomic factors of health inequalities intermingled with occupations at risk, demonstrated by the fact that most taxi drivers belonged to the same ethnic group and that taxi drivers had higher mortality rates when residing in London. These findings are mirrored in a recent preprint publication from the US state of California, reporting that relative excess mortality was particularly high among food/agriculture, transportation/logistics, facilities, and manufacturing workers.
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