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This issue of the Journal contains an article by Gynning et al (1) on the impact of work-life interference on burnout and job discontent in a sample of 1575 physicians in Sweden. The authors measured work-life interference and burnout at baseline in 2021, followed participants for one year, and then measured burnout again. Higher levels of work-life interference in 2021 were associated with an increased risk of high burnout in 2022, after adjustment for sex, occupational rank, family situation, work hours, overtime work, work with COVID-19 patients, and high burnout in 2021. The estimates for the association were substantial, with odds ratios of 3.67 [95% confidence interval (CI) 2.78-4.83] and 1.53 (95% CI 1.05-2.25) in the crude and the adjusted analysis, respectively. Work-life interference in 2021 was also associated with risk of job dissatisfaction and turnover intention in 2022. Whereas the design of the study was simple and straightforward, the researched phenomena, both the exposure − work-life interference − and the outcome − burnout − are anything but simple and straightforward. Work-life interference Work-life interference and related concepts, such as work-life balance or work-family conflict, have been viewed and understood differently, depending on historical and other contexts. In the beginning of the Industrial Revolution, the demand for a healthy balance between work and life might have been best expressed in the slogan “eight hours labor, eight hours recreation, eight hours rest”, allegedly coined by the British textile manufacturer and social reformer Robert Owen (1771–1858). Although the link between number of working hours and work-life balance persisted in the 21st century − as illustrated in a review by Albertsen et al (2) on working hours and work-life balance published in this journal in 2008 − new aspects emerged, such as the role of gender and gender disparities. Albertsen et al reported in their review that long working hours were strongly associated with a risk of lower work-life balance among women, whereas among men the association was much less clear. Today, there is a substantial literature studying and critically discussing concepts such as work-life interference and work-life balance from a feminist and post-feminist perspective (3, 4). In recent years, a generational perspective has been added to the research on work-life interference. It has been argued that workers from Generation Y (Gen Y or Millennials), comprising those born between the early 1980s and the mid-to-late 1990s, and Gen Z, those born between the mid-to-late 1990s and early 2010s, are more sensitive about the negative effects of work on life and focused on protecting themselves from work that interferes with life than previous generations (such as Gen X or Baby Boomers) (5, 6). Other researchers, though, have strongly criticized the generational perspective and argue there are little-to-no generational effects and that the apparent differences between the generations are actually due to age and period effects (7). An important period effect might be that in this day and age, the distinction between work and life is becoming less clear compared to earlier days of industrialized societies. Whether this is good or not for workers’ physical and mental health is not easy to answer. For many workers, and in particular but not limited to highly educated professionals (such as us, academic researchers), work is a major part of life and a key contributor to identity and self-esteem. The domains of work and life are often so much entangled that terms such as “interference” or “balance” may not be adequate to describe the relation between the two. The distinction between work and life may be further blurred because of technological advancements that allow a growing proportion of workers to work from home. Burnout The term burnout emerged in the 1970s from research on physical and mental exhaustion among volunteer workers in the USA (8). It gained popularity in particular due to the work by Christina Maslach, professor of psychology at the University of California at Berkeley, and the development of the Maslach Burnout Inventory (9). Maslach conceptualized burnout with three dimensions: emotional exhaustion, depersonalization (also termed cynicism), and reduced personal accomplishment (also termed reduced professional efficacy) (9). While the Maslach burnout inventory is by far the most widely-used instrument to assess burnout, it has also been criticized and controversially discussed, in particular with regard to the dimensions of depersonalization and reduced personal accomplishments (10, 11). Several other instruments, definitions, and conceptualizations of burnout have been proposed over the decades (12). A few years ago, the Network on the Coordination and Harmonisation of European Occupational Cohorts (OMEGA-NET) set up a panel of 50 researchers and healthcare professionals, with the aim of developing a consensual definition of occupational burnout. The results were published in the Journal in 2021 (12). The consensus definition was: “In a worker, occupational burnout or occupational physical AND emotional exhaustion state is an exhaustion due to prolonged exposure to work-related problems” (12). This brief consensus definition was the result of the panel`s impressive work that included reviews of the literature, critical discussions of the findings, and thoughtful deliberations. However, already in the next issue of the Journal, the consensus definition was challenged. In an editorial, Wilmar Schaufeli concluded that several questions regarding burnout still remain unsolved (13). One question is whether “exhaustion” is sufficient to define burnout, as the panel argued, or, as Schaufeli argued, that the burnout concept requires the inclusion of both the inability to spend effort at work (exhaustion) and the unwillingness to spend this effort (what Schaufeli termed “mental distancing”). Gynning et al (1) seem to have followed Schaufel`s reasoning and used in their study the Burnout Assessment Tool 12 (BAT-12) (14), a measurement that includes items both on exhaustion and mental distancing (see the supplementary material of their article for the wording of the items). Prevalence of burnout among physicians When one searches the Web of Science for the topics “work-life interference" OR "work-life balance”, remarkably, the top-five cited articles that show up are all about burnout among physicians (15–19). It is further notable that each of these five articles had more than 1000 citations even though they were relatively recently published: in 2018 (two articles), 2016, 2015, and 2012, respectively. Thus, it seems fair to conclude that the study by Gynning et al addresses an area of great contemporary interest. Is prevalence of burnout particularly high among physicians compared to other occupational groups? The seminal article by Shanafelt et al (15) reported that 45.8% of the physicians showed at least one burnout symptom on the Maslach Burnout Inventory. For comparison with a US population control sample, Shanafelt and colleagues used a 2-item burnout measure that yielded a burnout prevalence of 37.9% among physicians and 27.8% among controls. Recently, Møller et al (20, 21) presented results from a burnout study that invited all 104 active vascular surgeons (including vascular surgeons in training) employed at a department of vascular surgery in a Danish hospital. Of those 104 surgeons, 85 completed the survey, yielding an astonishing response rate of 82%. Burnout was measured with the Copenhagen Burnout Inventory, which assesses exhaustion (but not mental distancing) on three separate scales: personal burnout (exhaustion without attribution to a cause), work-related burnout (exhaustion attributed to work), and client/patient-related burnout (exhaustion attributed to work with clients or patients (10). The prevalence of moderate or severe burnout was 28%, 16% and 4% for personal, work-related, and client/patient-related burnout, respectively (20). Compared to the burnout prevalence reported by Shanafelt et al (15) and Møller et al (20), the burnout prevalence reported by Gynning et al is rather low (4.5% and 5.8% in 2021 and 2022, respectively). There might be many explanations for these huge differences in burnout prevalence across the three studies, such as different response rates and bias due to selective non-response or differences in working conditions between the USA, Denmark and Sweden. The most likely explanation, though, is probably the use of different instruments to measure burnout and thereby different definitions of burnout used in the three studies. Thus, for comparative studies, across countries, industries, or job group, a harmonization of burnout measurements is needed. Mechanisms As delineated above, work hours and overtime work are seen as crucial components of work-life interference in the literature (2). It is therefore remarkable that Gynning et al reported that the association between work-life interference and burnout remained, even after adjusting for work hours and overtime work. So, what is it in work that is interfering with life if not work hours and overtime? The five items to measure work-life interference in the study by Gynning et al are rather general: (i) feeling tired when coming home from work; (ii) private life is not as desired because of work; (iii) overlook personal problems because of demands at work; (iv) personal life suffers because of work; (v) change and adapt personal life to demands at work (see the Supplementary Material of the article for the exact wording of the items). The demands at work that are mentioned in the items could be quantitative demands, including work intensity, but also emotional demands, which tend to be high among physicians (22). It is also possible, though, that the respondents viewed “demands” more broadly and subsumed under the term interpersonal conflicts at work or poor work organization. In an invited commentary to Møller et al`s (21) study on burnout among vascular surgeons, Jonathan Meizoso, a US-American physician, discussed possible explanations for the high burnout prevalence in the study (23). He first expressed his puzzlement that so many Danish vascular surgeons reported burnout, in particular since the working conditions of the Danish physicians seem to be so much better compared to their US-American counterparts (37-hour regular work week, paid overtime work, paid sick leave, paid maternity and paternity leave, six weeks of paid vacation). But then he pointed to adverse working conditions listed in the article that sounded familiar to him as a physician practicing in the USA, such as “increasing bureaucracy, rising requirements of documentation, and an unfavorable electronic health record system”(23). On a theoretical level, these factors seem to be related to the concepts of “unnecessary and unreasonable tasks” in the “Stress as Offense to Self” framework (24). Future studies on work-life interference and burnout might want to examine these and other work organizational factors as potential determinants of work-life interference. These studies could also investigate the extent to which a possible effect of work organizational factors on the risk of burnout is due to work-life interference and the extent to which such an effect occurs via other mechanisms. References 1. Gynning BE, Christiansen F, Lidwall U, Brulin E. Impact of work-life interference on burnout and job discontent: A one-year follow-up study of physicians in Sweden. Scand J Work Environ Health 2024 Aug;4181. https://doi.org/10.5271/sjweh.4181 2. Albertsen K, Rafnsdóttir GL, Grimsmo A, Tómasson K, Kauppinen K. Workhours and worklife balance. Scand J Work Environ Health 2008; Supplement 5:14–21. 3. Rosa R. The trouble with ‘work-life balance’ in neoliberal academia: a systematic and critical review. J Gend Stud 2022;31(1):55–73. https://doi.org/10.1080/09589236.2021.1933926 4. Sørensen SØ. The performativity of choice: postfeminist perspectives on work-Life balance. Gend Work Organ 2017;24(3):297–313. https://doi.org/10.1111/gwao.12163 5. Campbell WK, Campbell SM, Siedor LE, Twenge JM. Generational differences are real and useful. Ind Organ Psychol 2015;8(3):324–31. https://doi.org/10.1017/iop.2015.43 6. Twenge JM, Campbell SM, Hoffman BJ, Lance CE. Generational differences in work values: leisure and extrinsic values increasing, social and intrinsic values decreasing. J Manage 2010;36(5):1117–42. https://doi.org/10.1177/0149206309352246 7. Schröder M. Work motivation Is not generational but depends on age and period. J Bus Psychol 2024;39(4):897–908. https://doi.org/10.1007/s10869-023-09921-8 8. Freudenberger HJ. Staff Burn-Out. J Soc Issues 1974;30(1):159–65. https://doi.org/10.1111/j.1540-4560.1974.tb00706.x 9. Maslach C, Jackson SE. The measurement of experienced burnout. J Occup Behav 1981;2(2):99–113. https://doi.org/10.1002/job.4030020205 10. Kristensen TS, Borritz M, Villadsen E, Christensen KB. The Copenhagen Burnout Inventory. A new tool for the assessment of burnout. Work Stress 2005;19(3):192–207. https://doi.org/10.1080/02678370500297720 11. Schaufeli WB, Taris TW. The conceptualization and measurement of burnout: common ground and worlds apart. Work Stress 2005;19(3):256–62. https://doi.org/10.1080/02678370500385913 12. Guseva Canu I, Marca SC, Dell’Oro F, Balázs Á, Bergamaschi E, Besse C et al. Harmonized definition of occupational burnout: A systematic review, semantic analysis, and Delphi consensus in 29 countries. Scand J Work Environ Health 2021 Mar;47(2):95–107. https://doi.org/10.5271/sjweh.3935 13. Schaufeli W. The burnout enigma solved? Scand J Work Environ Health 2021 Apr;47(3):169–70. https://doi.org/10.5271/sjweh.3950 14. Schaufeli WB, De Witte H, Hakanen JJ, Kaltiainen J, Kok R. How to assess severe burnout? Cutoff points for the Burnout Assessment Tool (BAT) based on three European samples. Scand J Work Environ Health 2023 May;49(4):293–302. https://doi.org/10.5271/sjweh.4093 15. Shanafelt TD, Boone S, Tan L, Dyrbye LN, Sotile W, Satele D et al. Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Intern Med 2012 Oct;172(18):1377–85. https://doi.org/10.1001/archinternmed.2012.3199 16. Shanafelt TD, Hasan O, Dyrbye LN, Sinsky C, Satele D, Sloan J et al. Changes in burnout and satisfaction with work-life balance in physicians and the general US working population between 2011 and 2014. Mayo Clin Proc 2015 Dec;90(12):1600–13. https://doi.org/10.1016/j.mayocp.2015.08.023 17. West CP, Dyrbye LN, Shanafelt TD. Physician burnout: contributors, consequences and solutions. J Intern Med 2018 Jun;283(6):516–29. https://doi.org/10.1111/joim.12752 18. West CP, Dyrbye LN, Erwin PJ, Shanafelt TD. Interventions to prevent and reduce physician burnout: a systematic review and meta-analysis. Lancet 2016 Nov;388(10057):2272–81. https://doi.org/10.1016/S0140-6736(16)31279-X 19. Rotenstein LS, Torre M, Ramos MA, Rosales RC, Guille C, Sen S et al. Prevalence of burnout among physicians: a systematic review. JAMA 2018 Sep;320(11):1131–50. https://doi.org/10.1001/jama.2018.12777 20. Møller CM, Clausen T, Aust B, Eiberg JP. A cross-sectional national study of burnout and psychosocial work environment in vascular surgery in Denmark. J Vasc Surg 2022 May;75(5):1750–1759.e3. https://doi.org/10.1016/j.jvs.2021.11.042 21. Møller CM, Clausen T, Aust B, Budtz-Lilly JW, Eiberg JP. Burnout and its consequences among vascular surgeons and trainees: a Danish national survey. J Am Coll Surg 2023 Dec;237(6):874–83. https://doi.org/10.1097/XCS.0000000000000853 22. Framke E, Sørensen JK, Nordentoft M, Johnsen NF, Garde AH, Pedersen J et al. Perceived and content-related emotional demands at work and risk of long-term sickness absence in the Danish workforce: a cohort study of 26 410 Danish employees. Occup Environ Med 2019 Dec;76(12):895–900. https://doi.org/10.1136/oemed-2019-106015 23. Meizoso JP. Invited Commentary: Burnout among surgeons: a pandemic in its own right. J Am Coll Surg 2023 Dec;237(6):883–4. https://doi.org/10.1097/XCS.0000000000000858 24. Semmer NK, Tschan F, Jacobshagen N, Beehr TA, Elfering A, Kälin W et al. Stress as Offense to Self: a promising approach comes of age. Occup Health Sci 2019;3(3):205–38. https://doi.org/10.1007/s41542-019-00041-5

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 clinical examination of the participants, both at baseline and follow-up. An important limitation is the very low number of cases in the exposure groups during the five-year follow-up. Unsurprisingly, the CI of all estimates were wide and included unity and, thus, were far away from being statistically significant. The uncertainty of the estimates do not allow firm conclusions on the results. However, the estimates from this study can be included in meta-analyses, which then may provide us with more insight on the role of night shift work on risk of cardiovascular disease. Important challenges for future research on working time and cardiovascular disease will include better use of electronic working time registration systems that will allow a more precise measurement of exposure to long working hours and the frequency and type of shift work and night shift work (35, 36). It will also be important to conceptually clarify whether health behaviors that are hazardous to cardiovascular health – such as certain dietary patterns, lack of leisure time physical activity, or smoking – are confounders or mediators, or both, for the association between working time and cardiovascular disease. This clarification is key to correctly handling data on these health behaviors in the statistical models. Finally, examining the relations of the different working time arrangements with the contents of work conducted during these arrangements might be fruitful for a better understanding of the contribution of work to cardiovascular disease. Conflict of interest statement Reiner Rugulies was involved in both the IPD-Work Consortium and the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury project. References 1. International Labour Organization (ILO). International Labour Standards on Working time [Website]. 2024. Available from: https://www.ilo.org/global/standards/subjects-covered-by-international-labour-standards/working-time/lang--en/index.htm. (Accessed: 26 Februar 2024). 2. Chicago Historical Society and the Trustees of Northwestern University. The dramas of Haymarket [Website]. 2000. Available from: https://www.chicagohistoryresources.org/dramas/. (Accessed: 26 February 2024). 3. Yale Law School. The Avalon Project: Documents in Law, History and Diplomay. The Versailles Treaty June 28, 1919: Part XIII [Website]. 2008. Available from: https://avalon.law.yale.edu/imt/partxiii.asp. (Accessed: 2 March 2024). 4. International Labour Office. Official Bulletin, Volume I, April 1919 - August 1920. Chapter VI: Part XIII of the Treaty of Peace of Versailles. Geneva ILO; 1923. Available from: https://www.ilo.org/wcmsp5/groups/public/---dgreports/---jur/documents/genericdocument/wcms_441862.pdf. (Accessed: 2 March 2024). 5. Ashton JR. The public health case for the four-day working week. J R Soc Med. 2019;112(2):81-82. https://doi.org/10.1177/0141076819826782 6. Spencer DA. A four-day working week: its role in a politics of work. Polit Q. 2022;93(3):401-407. https://doi.org/10.1111/1467-923X.13173 7. Tsai M-C, Nitta M, Kim S-W, Wang W. Working overtime in East Asia: convergence or divergence? J Contemp Asia. 2016;46(4):700-722. https://doi.org/10.1080/00472336.2016.1144778 8. Cheng Y, Park J, Kim Y, Kawakami N. The recognition of occupational diseases attributed to heavy workloads: experiences in Japan, Korea, and Taiwan. Int Arch Occup Environ Health. 2012;85(7):791-799. https://doi.org/10.1007/s00420-011-0722-8 9. Hiyama T, Yoshihara M. New occupational threats to Japanese physicians: karoshi (death due to overwork) and karojisatsu (suicide due to overwork). Occup Environ Med. 2008;65(6):428-429. https://doi.org/10.1136/oem.2007.037473 10. Huang Y, Xiang Y, Zhou W, Li G, Zhao C, Zhang D, et al. Long working hours and all-cause mortality in China: A 26-year follow-up study. Scand J Work Environ Health. 2023;49(8):539-548. https://doi.org/10.5271/sjweh.4115 11. Lee DW, Choi J, Kim HR, Myong JP, Kang MY. Differential impact of working hours on unmet medical needs by income level: a longitudinal study of Korean workers. Scand J Work Environ Health. 2022;48(2):109-117. https://doi.org/10.5271/sjweh.3999 12. Lee W, Kang SK, Choi WJ. Effect of long work hours and shift work on high-sensitivity C-reactive protein levels among Korean workers. Scand J Work Environ Health. 2021;47(3):200-207. https://doi.org/10.5271/sjweh.3933 13. Jankowiak S, Rossnagel K, Bauer J, Schulz A, Liebers F, Latza U, et al. Night shift work and cardiovascular diseases among employees in Germany: five-year follow-up of the Gutenberg Health Study. Scand J Work Environ Health. 2024;50(3):142–151. https://doi.org/10.5271/sjweh.4139 14. Rugulies R, Burdorf A. The achievements and challenges of occupational health research: Looking back and ahead. Scand J Work Environ Health. 2024;50(1):1-2. https://doi.org/10.5271/sjweh.4136 15. 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 16. 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(10005):1739-1746. https://doi.org/10.1016/S0140-6736(15)60295-1 17. World Health Organization and International Labour Organization (WHO/ILO). Joint estimates of the work-related burden of disease and injury, 2000-2016: global monitoring report. Geneva: WHO/ILO; 2021. Available from: https://apps.who.int/iris/rest/bitstreams/1370920/retrieve. (Accessed: 25 March 2022). 18. World Health Organization and International Labour Organization (WHO/ILO). Joint estimates of the work-related burden of disease and injury, 2000-2016: technical report with data sources and methods. Geneva: WHO/ILO; 2021. Available from: https://apps.who.int/iris/rest/bitstreams/1370904/retrieve. (Accessed: 25 March 2022). 19. Li J, Pega F, Ujita Y, Brisson C, Clays E, Descatha A, et al. The effect of exposure to long working hours on ischaemic heart disease: A systematic review and meta-analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury. Environ Int. 2020;142:105739. https://doi.org/10.1016/j.envint.2020.105739 20. Descatha A, Sembajwe G, Pega F, Ujita Y, Baer M, Boccuni F, et al. The effect of exposure to long working hours on stroke: A systematic review and meta-analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury. Environ Int. 2020;142:105746. https://doi.org/10.1016/j.envint.2020.105746 21. Pega F, Náfrádi B, Momen NC, Ujita Y, Streicher KN, Prüss-Üstün AM, et al. Global, regional, and national burdens of ischemic heart disease and stroke attributable to exposure to long working hours for 194 countries, 2000-2016: A systematic analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury. Environ Int. 2021;154:106595. https://doi.org/10.1016/j.envint.2021.106595 22. Pega F, Hamzaoui H, Nafradi B, Momen NC. Global, regional and national burden of disease attributable to 19 selected occupational risk factors for 183 countries, 2000-2016: A systematic analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury. Scand J Work Environ Health. 2022;48(2):158-168. https://doi.org/10.5271/sjweh.4001 23. Coggon D. Estimating population burdens of occupational disease. Scand J Work Environ Health. 2022;48(2):83-85. https://doi.org/10.5271/sjweh.4007 24. Kivimäki M, Virtanen M, Nyberg ST, Batty GD. The WHO/ILO report on long working hours and ischaemic heart disease - Conclusions are not supported by the evidence. Environ Int. 2020;144:106048. https://doi.org/10.1016/j.envint.2020.106048 25. Li J, Rugulies R, Morgan RL, Woodruff T, Siegrist J, WHO/ILO Working Group of Individual Experts on Long Working Hours on Ischaemic Heart Disease. Systematic review and meta-analysis on exposure to long working hours and risk of ischaemic heart disease - Conclusions are supported by the evidence. Environ Int. 2020;144:106118. https://doi.org/10.1016/j.envint.2020.106118 26. Hannerz H, Larsen AD, Garde AH. Long weekly working hours and ischaemic heart disease: a follow-up study among 145 861 randomly selected workers in Denmark. BMJ Open. 2018;8(6):e019807. https://doi.org/10.1136/bmjopen-2017-019807 27. Hannerz H, Albertsen K, Burr H, Nielsen ML, Garde AH, Larsen AD, et al. Long working hours and stroke among employees in the general workforce of Denmark. Scand J Public Health. 2018;46(3):368-374. https://doi.org/10.1177/1403494817748264 28. Fadel M, Sembajwe G, Li J, Leclerc A, Pico F, Schnitzler A, et al. Association between prolonged exposure to long working hours and stroke subtypes in the CONSTANCES cohort. Occup Environ Med. 2023;80(4):196-201. https://doi.org/10.1136/oemed-2022-108656 29. Torquati L, Mielke GI, Brown WJ, Kolbe-Alexander T. Shift work and the risk of cardiovascular disease. A systematic review and meta-analysis including dose-response relationship. Scand J Work Environ Health. 2018;44(3):229-238. https://doi.org/10.5271/sjweh.3700 30. IARC Working Group on the Identification of Carcinogenic Hazards to Humans. Night shift work. Lyon, France: IARC; 2020. Available from: https://publications.iarc.fr/_publications/media/download/6397/c965a667eda3a390d9797cbcde59765fef9dcb7a.pdf. (Accessed: 29 February 2024). 31. Su F, Huang D, Wang H, Yang Z. Associations of shift work and night work with risk of all-cause, cardiovascular and cancer mortality: a meta-analysis of cohort studies. Sleep Med. 2021;86:90-98. https://doi.org/10.1016/j.sleep.2021.08.017 32. Bigert C, Kader M, Andersson T, Selander J, Bodin T, Gustavsson P, et al. Night and shift work and incidence of cerebrovascular disease - a prospective cohort study of healthcare employees in Stockholm. Scand J Work Environ Health. 2022;48(1):31-40. https://doi.org/10.5271/sjweh.3986 33. Kader M, Selander J, Andersson T, Albin M, Bodin T, Harma M, et al. Night and shift work characteristics and incident ischemic heart disease and atrial fibrillation among healthcare employees - a prospective cohort study. Scand J Work Environ Health. 2022;48(7):520-529. https://doi.org/10.5271/sjweh.4045 34. Vestergaard JM, Dalboge A, Bonde JPE, Garde AH, Hansen J, Hansen AM, et al. Night shift work characteristics and risk of incident coronary heart disease among health care workers: national cohort study. Int J Epidemiol. 2023;52(6):1853-1861. https://doi.org/10.1093/ije/dyad126 35. Larsen AD, Nielsen HB, Kirschheiner-Rasmussen J, Hansen J, Hansen ÅM, Kolstad HA, et al. Night and evening shifts and risk of calling in sick within the next two days - a case-crossover study design based on day-to-day payroll data. Scand J Work Environ Health. 2023;49(2):117-125.https://doi.org/10.5271/sjweh.4074 36. Vestergaard JM, Haug JND, Dalbøge A, Bonde JPE, Garde AH, Hansen J, et al. Validity of self-reported night shift work among women with and without breast cancer. Scand J Work Environ Health. 2024;50(3):152–157. https://doi.org/10.5271/sjweh.4142

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. Available from: https://www.who.int/publications/i/item/9789240057944 (Accessed: 28 September 2022). 3. Ghebreyesus TA. Tackling the trillion dollar taboo [LinkedIn post]. 2022. Available from: https://www.linkedin.com/pulse/tackling-trillion-dollar-taboo-tedros-adhanom-ghebreyesus. (Accessed: 27 January 2024). 4. van Dongen JM, van der Beek AJ. Economic evaluations in occupational health: what brings the best bang for the buck? Scand J Work Environ Health. 2022;48(4):249-252. https://doi.org/10.5271/sjweh.4026 5. Russo S, Ronchetti M, Di Tecco C, Valenti A, Jain A, Mennini FS, et al. Developing a cost-estimation model for work-related stress: An absence-based estimation using data from two Italian case studies. Scand J Work Environ Health. 2021;47(4):318-327. https://doi.org/10.5271/sjweh.3948 6. Finnes A, Hoch JS, Enebrink P, Dahl J, Ghaderi A, Nager A, et al. Economic evaluation of return-to-work interventions for mental disorder-related sickness absence: two years follow-up of a randomized clinical trial. Scand J Work Environ Health. 2022;48(4):264-272. https://doi.org/10.5271/sjweh.4012 7. Pedersen J, Graversen BK, Hansen KS, Madsen IEH. The labor market costs of work-related stress: A longitudinal study of 52 763 Danish employees using multi-state modeling. Scand J Work Environ Health. 2024;50(2):61–72. https://doi.org/10.5271/sjweh.4131 8. Fagbevægelsens Hovedorganisation. FH: Underprioriteret forebyggelse af stress koster dyrt for alle [Internet Blog: Underprioritised prevention of stress is costly for everyone]. 2023. Available from: https://fho.dk/blog/2023/11/16/fh-underprioriteret-forebyggelse-af-stress-koster-dyrt-for-alle. (Accessed: 27 January 2024). 9. Dansk Industri. Stresssygemeldinger har menneskelige og økonomiske omkostninger [Internet News: Sickness absenteeisms due to stress have human and financial costs]. 2023. Available from: https://www.danskindustri.dk/vi-radgiver-dig/personale/nyhedsarkiver---personaleforhold/nyheder-om-arbejdsmiljo/2023/11/stresssygemeldinger-har-menneskelige-og-okonomiske-omkostninger. (Accessed: 27 January 2024). 10. Cannon WB. Bodily changes in pain, hunger, fear and rage. An account of recent researchers into the function of emotional excitement. New York: D. Appleton and Company; 1915. https://doi.org/10.1037/10013-000 11. Selye H. Stress: the physiology and pathology of a exposure to stress. Montreal: Acta Medica; 1950. 12. Lazarus RS, Folkman S. Stress, Appraisal, and Coping. New York: Springer; 1984. 13. McEwen BS. Stress, adaptation, and disease. Allostasis and allostatic load. Ann N Y Acad Sci. 1998;840:33-44. https://doi.org/10.1111/j.1749-6632.1998.tb09546.x 14. Ursin H, Eriksen HR. Cognitive activation theory of stress (CATS). Neurosci Biobehav Rev. 2010;34(6):877-881. https://doi.org/10.1016/j.neubiorev.2009.03.001 15. Theorell T, Karasek R. Current issues relating to psychological job strain and cardiovascular disease research. J Occup Health Psychol. 1996;1(1):9-26. https://doi.org/10.1037/1076-8998.1.1.9 16. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385-396. https://doi.org/10.2307/2136404 17. Eskildsen A, Dalgaard VL, Nielsen KJ, Andersen JH, Zachariae R, Olsen LR, et al. Cross-cultural adaptation and validation of the Danish consensus version of the 10-item Perceived Stress Scale. Scand J Work Environ Health. 2015;41(5):486-490. https://doi.org/10.5271/sjweh.3510 18. Lunau T, Siegrist J, Dragano N, Wahrendorf M. The association between education and work stress: does the policy context matter? PLoS One. 2015;10(3):e0121573. https://doi.org/10.1371/journal.pone.0121573 19. 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

Purpose To explore how employees understand work-related sexual harassment and label their experience. Methods This study is based on 13 semi-structured in-depth interviews with employees exposed to workplace sexual harassment. We analysed the data using a thematic approach drawing on frameworks of sensemaking in organizations. Results We identified four major themes. The first two themes, distinguishing between sexual harassment and unwanted sexual attention and labelling real life sexual harassment, outline the interviewees’ definitions of the two terms “sexual harassment” and “unwanted sexual harassment” and reveal the challenges of labelling sexually harassing behaviours at work. The last two themes; making the connection and negotiating boundaries and labels, explain the sensemaking process, i.e., how the interviewees come to understand and label their experience. Conclusion The analysis showed that the interviewees related sexual harassment with physical, coercive, and intentional behaviours, whereas unwanted sexual attention was seen as less severe and less intentional. The interviewees often doubted how to label their experience, and making sense of one´s experience could take years. Self-labelling is inherently a social process, and the validation and rejection of others play an important role. Finally, the #MeToo movement constituted a turning point for several interviewees’ understandings of events.

OBJECTIVE: The Scandinavian Journal of Work, Environment & Health was launched 50 years ago. In this paper we describe how research topics have changed over time. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

OBJECTIVE: This study aimed to systematically review the effectiveness of organizational-level interventions in improving the psychosocial work environment and workers’ health and retention.METHODS: We conducted an overview of systematic reviews on organizational-level interventions published between 2000 and 2020. We systematically searched academic databases, screened reference lists, and contacted experts, yielding 27 736 records. Of the 76 eligible reviews, 24 of weak quality were excluded, yielding 52 reviews of moderate (N=32) or strong (N=20) quality, covering 957 primary studies. We assessed quality of evidence based on quality of review, consistency of results, and proportion of controlled studies.RESULTS: Of the 52 reviews, 30 studied a specific intervention approach and 22 specific outcomes. Regarding intervention approaches, we found strong quality of evidence for interventions focusing on “changes in working time arrangements” and moderate quality of evidence for “influence on work tasks or work organization”, “health care approach changes”, and “improvements of the psychosocial work environment”. Regarding outcomes, we found strong quality of evidence for interventions about “burnout” and moderate quality evidence for “various health and wellbeing outcomes”. For all other types of interventions, quality of evidence was either low or inconclusive, including interventions on retention.CONCLUSIONS: This overview of reviews identified strong or moderate quality of evidence for the effectiveness of organizational-level interventions for four specific intervention approaches and two health outcomes. This suggests that the work environment and the health of employees can be improved by certain organizational-level interventions. We need more research, especially about implementation and context, to improve the evidence.

OBJECTIVE: Previous literature has established associations between psychosocial working conditions and sickness absence (SA), but only few studies have examined associations among younger employees. This study aimed to investigate associations between psychosocial working conditions and SA among employees, aged 15–30 years, who entered the labor market in Denmark between 2010 and 2018.METHOD: We followed 301 185 younger employees in registers for on average 2.6 years. Using job exposure matrices, we assessed job insecurity, quantitative demands, decision authority, job strain, emotional demands, and work-related physical violence. Adjusted rate ratios of SA spells of any length were estimated for women and men separately with Poisson models.RESULTS: Among women, employment in occupations with high quantitative demands, low decision authority, high job strain, high emotional demands, or high work-related physical violence was associated with higher rates of SA. Being employed in occupations with high versus low emotional demands showed the strongest association with SA, with a rate ratio of 1.44 [95% confidence interval (CI) 1.41–1.47]. Among men, being employed in occupations with low decision authority showed the strongest association with SA (1.34, 95% CI 1.31–1.37), whereas occupations with high quantitative demands, high job strain, and high emotional demands were associated with lower rates of SA.CONCLUSION: We found that several psychosocial working conditions were associated with SA spells of any length. Associations with SA spells of any length resemble associations with long-term SA, suggesting that results from previous studies on long-term SA may be generalizable to all lengths of SA among younger employees.

Background According to the Medical Research Council (MRC) framework, the theorisation of how multilevel, multicomponent interventions work and the understanding of their interaction with their implementation context are necessary to be able to evaluate them beyond their complexity. More research is needed to provide good examples following this approach in order to produce evidence-based information on implementation practices.Objectives This article reports on the results of the process evaluation of a complex mental health intervention in small and medium enterprises (SMEs) tested through a pilot study. The overarching aim is to contribute to the evidence base related to the recruitment, engagement and implementation strategies of applied mental health interventions in the workplace.Method The Mental Health Promotion and Intervention in Occupational Settings (MENTUPP) intervention was pilot tested in 25 SMEs in three work sectors and nine countries. The evaluation strategy of the pilot test relied on a mixed-methods approach combining qualitative and quantitative research methods. The process evaluation was inspired by the RE-AIM framework and the taxonomy of implementation outcomes suggested by Proctor and colleagues and focused on seven dimensions: reach, adoption, implementation, acceptability, appropriateness, feasibility and maintenance.Results Factors facilitating implementation included the variety of the provided materials, the support provided by the research officers (ROs) and the existence of a structured plan for implementation, among others. Main barriers to implementation were the difficulty of talking about mental health, familiarisation with technology, difficulty in fitting the intervention into the daily routine and restrictions caused by COVID-19.Conclusions The results will be used to optimise the MENTUPP intervention and the theoretical framework that we developed to evaluate the causal mechanisms underlying MENTUPP. Conducting this systematic and comprehensive process evaluation contributes to the enhancement of the evidence base related to mental health interventions in the workplace and it can be used as a guide to overcome their contextual complexity.Trial registration number ISRCTN14582090.

OBJECTIVE: Night and evening work is associated with risk of sickness absence, but little is known about the acute effects of these types of shifts on sickness absence. The aim of the current study is therefore to examine the risk of calling in sick within two days after a night or an evening shift. METHODS: By use of a case-crossover design, odds of calling in sick within two days after a night or an evening shift compared to day shifts were analyzed within the same person. Day-to-day information on shifts and sickness absence were derived from the Danish Working Hour Database on 44 767 cases. Data were analyzed using conditional logistic regression. The analyses were supplemented by extensive testing of methodological choices. RESULTS: Analyses showed higher odds of calling in sick after a night shift [odds ratio (OR) 1.22, 95% confidence intervak (CI) 1.14–1.30] and lower odds after an evening shift (OR 0.89, 95% CI 0.84–0.93) compared to day shifts within the same person. Testing of methodological choices suggested that in particular the duration of case and control periods, time between these periods along with the number of control periods affected the results. CONCLUSION: This large and unique within-person study among Danish hospital employees indicate that the risk of calling in sick is affected by the types of shifts, independently of sex, age, and time-invariant confounding. Extensive testing identified important methodological choices eg, length and number of included periods to consider when choosing the case-crossover design.

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-JEM). Scand J Work Environ Health 2022;48:61-70. https://doi.org/10.5271/sjweh.3998 13. Fadel M, Gilbert F, Legeay C, Dubée V, Esquirol Y, Verdun-Esquer C, et al. Association between COVID-19 infection and work exposure assessed by the Mat-O-Covid job exposure matrix in the CONSTANCES cohort. Occup Environ Med 2022;79:782-89. https://doi.org/10.1136/oemed-2022-108436 14. Chu DK, Akl EA, Duda S, Solo K, Yaacoub S, Schüneman HJ, et al. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. Lancet 2020; 395: 1973-87. https://doi.org/10.1016/j.jvs.2020.07.040

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

OBJECTIVES: Workplace bullying has been suggested to increase symptoms of anxiety. A reverse relationship has also been proposed. However, so far only few earlier studies have investigated this topic and the reported associations might partly be explained by unmeasured individual characteristics. In this study, we aim to examine the temporality and directionality between workplace bullying and anxiety symptoms, taking time-invariant characteristics into account. Furthermore, we aim to examine whether leadership quality modifies these associations. METHODS: We included 13 491 individuals from two nationwide cohort studies in Sweden and Denmark. Using cross-lagged structural equation models (SEM) and dynamic panel models with fixed effects, we examined contemporaneous and lagged associations between self-reported workplace bullying and anxiety. Cohort-specific results were estimated and combined using fixed-effect meta-analysis. RESULTS: The cross-lagged SEM models supported contemporaneous and lagged relationships in both directions (from workplace bullying to symptoms of anxiety and vice versa). In contrast, only contemporaneous relationships remained statistically significant and of considerable magnitude in the dynamic panel models with fixed effects. Specifically, exposure to workplace bullying was related to a concurrent increase in anxiety symptoms (b=0.61, 95% confidence interval 0.32–0.90). No support of interaction with leadership quality was found. CONCLUSIONS: The results indicate that onset of workplace bullying is associated with an immediate or short-term increase in anxiety symptoms. This study provides novel insights regarding temporal aspects and causal inference of the bullying-anxiety relationship useful for managing psychological hazards and preventing mental illness at work.

OBJECTIVE: In terms of prevention, it is important to determine effects on cardiovascular disease (CVD) when some workplace psychosocial resources are high while others are low. The aim of the study was to assess the prospective relationship between clustering of workplace psychosocial resources and risk of CVD among employees. METHODS: We pooled data from three cohort studies of 135 669 employees (65% women, age 18–65 years and free of CVD) from Denmark, Finland and Sweden. Baseline horizontal resources (culture of collaboration and support from colleagues) and vertical resources (leadership quality and procedural justice) were measured using standard questionnaire items. Incident CVD, including coronary heart and cerebrovascular disease, was ascertained using linked electronic health records. We used latent class analysis to assess clustering (latent classes) of workplace psychosocial resources. Cox proportional hazard models were used to examine the association between these clusters and risk of CVD, adjusting for demographic and employment-related factors and pre-existing physical and mental disorders. RESULTS: We identified five clusters of workplace psychosocial resources from low on both vertical and horizontal resources (13%) to generally high resources (28%). High horizontal resources were combined with either intermediate [hazard ratio (HR) 0.84, 95% confidence interval (CI) 0.74–0.95] or high (HR 0.88, 95% CI 0.78–1.00) vertical resources were associated with lower risks of CVD compared to those with generally low resources. The association was most prominent for cerebrovascular disease (eg, general high resources: HR 0.80, 95% CI 0.67–0.96). CONCLUSIONS: Individuals with high levels of workplace psychosocial resources across horizontal and vertical dimensions have a lower risk of CVD, particularly cerebrovascular disease.

OBJECTIVES: The aim of this study was to analyze whether individuals reporting exposure to workplace bullying had a higher risk of suicidal behavior, including both suicide attempt and death by suicide, than those not reporting such exposure. METHODS: Using a prospective cohort study design, we linked data from nine Danish questionnaire-based surveys (2004–2014) to national registers up to 31 December 2016. Exposure to workplace bullying was measured by a single item. Suicide attempts were identified in hospital registers and death by suicide in the Cause of Death Register. Among participants with no previous suicide attempts, we estimated hazard ratios (HR) and 95% confidence intervals (CI), adjusting for sex, age, marital status, socioeconomic status, and history of psychiatric morbidity. RESULTS: The sample consisted of 98 330 participants (713 798 person-years), 63.6% were women, and the mean age was 44.5 years. Of these participants, 10 259 (10.4%) reported workplace bullying. During a mean follow-up of 7.3 years, we observed 184 cases of suicidal behavior, including 145 suicide attempts, 35 deaths by suicide and 4 cases that died by suicide after surviving a suicide attempt. The fully-adjusted HR for the association between workplace bullying and suicidal behavior was 1.65 (95% CI 1.06–2.58). The HR for suicide attempts and death by suicide were 1.65 (1.09–2.50) and 2.08 (0.82–5.27), respectively. Analyses stratified by sex showed a statistically significant association between workplace bullying and suicidal behavior among men but not women. CONCLUSIONS: The results suggest that exposure to workplace bullying is associated with an elevated risk of suicidal behavior among men.

OBJECTIVE: This study aimed to investigate the importance of combined psychosocial work factors for the risk of long-term sickness absence (LTSA). METHODS: We followed 69 371 employees in the general working population (Work Environment and Health in Denmark study 2012–2018), without LTSA during the preceding year, for up to two years in the Danish Register for Evaluation of Marginalization. Using k-means cluster analyses and weighted Cox-regression controlling for age, gender, survey year, education, health-behaviors, and physical work demands, we determined the prospective association of 11 identified clusters – based on the combination of nine psychosocial work factors (recognition, quantitative demands, work pace, emotional demands, influence, justice, role clarity, role conflicts, and support from colleagues) – with the risk of LTSA. RESULTS: During 124 045 person-years of follow-up, 6197 employees developed LTSA (weighted 8.5%). Using the cluster with the most favorable psychosocial scores as reference, clusters scoring poorly on several combined psychosocial factors had increased risk of LTSA. The cluster scoring poor on all nine psychosocial factors exhibited the highest risk [hazard ratio (HR) 1.68, 95% confidence interval (CI) 1.45–1.94]. Scoring poorly on one or two psychosocial factors did not increase the risk of LTSA when combined with favorable scores on the other psychosocial factors. Interaction analyses showed that gender, but not age and education, modified the association between cluster and LTSA. CONCLUSION: Scoring poorly on several combined psychosocial work factors plays an important role in the risk of LTSA. Scoring favorably on several psychosocial factors outweighed the potentially adverse effects of scoring poorly on one or two factors.

OBJECTIVE: This study aimed to examine the association between work-unit level leadership quality and individual-level long-term sickness absence (LTSA) in the hospital sector and effect modification by chronic disorders. METHODS: This longitudinal analysis included 33 025 Danish public hospital employees who were followed-up for one year after baseline in March 2014. Leadership quality was assessed by questionnaire with mean responses aggregated by work-unit and characterized in tertiles. LTSA during follow-up was determined from employer records. Chronic disorders at baseline was assessed from the Danish hospital and prescription registers. We performed multilevel logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusting for potential confounders. We evaluated interaction between chronic illness and low leadership quality on multiplicative and additive scales. RESULTS: We identified employees as healthy (60.8%) or with somatic (31.6%), mental (3.3%), or both somatic and mental (4.3%) disorders. During follow-up, 6% of employees registered a LTSA. Medium and high leadership quality were associated with lower risk of LTSA with OR of 0.84 (95% CI 0.76–0.94) and 0.73 (95% CI 0.65–0.82) respectively, compared to low leadership quality. Associations were similar for healthy employees and employees with only somatic disorders, whereas no association was observed for employees with mental disorders (in presence or absence of somatic disorders). No statistically significant (α=0.05) interactions between leadership quality and chronic disorders on LTSA were observed. CONCLUSION: The findings suggest that the quality of leadership in work units is associated with risk of long-term sick leave in the Danish public hospital sector and that strong leadership protects employees against LTSA.

Background Mounting evidence has demonstrated a role of psychosocial stressors such as discrimination in hypertension and cardiovascular diseases. The objective of this study was to provide the first instance of research evidence examining prospective associations of workplace discrimination with onset of hypertension. Methods and Results Data were from MIDUS (Midlife in the United States), a prospective cohort study of adults in the United States. Baseline data were collected in 2004 to 2006, with an average 8‐year follow‐up period. Workers with self‐reported hypertension at baseline were excluded, yielding a sample size of 1246 participants for the main analysis. Workplace discrimination was assessed using a validated 6‐item instrument. During follow‐up with 9923.17 person‐years, 319 workers reported onset of hypertension, and incidence rates of hypertension were 25.90, 30.84, and 39.33 per 1000 person‐years among participants with low, intermediate, and high levels of workplace discrimination, respectively. Cox proportional hazards regression analyses demonstrated that workers who experienced high exposure to workplace discrimination, compared with workers with low exposure, had a higher hazard of hypertension (adjusted hazard ratio, 1.54 [95% CI, 1.11–2.13]). Sensitivity analysis excluding more baseline hypertension cases based on additional information on blood pressure plus antihypertensive medication use (N=975) showed slightly stronger associations. A trend analysis showed an exposure‐response association. Conclusions Workplace discrimination was prospectively associated with elevated risk of hypertension among US workers. The adverse impacts of discrimination on cardiovascular disease have major implications for workers' health and indicate a need for government and employer policy interventions addressing discrimination.

OBJECTIVE: Previous studies on effects of emotional demands on depression have relied on self-reported exposure data and lacked control for potential confounding by pre-employment risk factors for depression. This study used a register-based design to examine the risk of hospital-treated depressive disorder in relation to occupational levels of emotional demands at work, furthermore addressing the role of risk factors for depression before workforce entry. METHODS: We analyzed data from two Danish register-based cohorts – Job Exposure Matrix Analyses of Psychosocial Factors and Healthy Ageing in Denmark (JEMPAD, N= 1 665 798) (17) and Danish Work Life Course Cohort (DaWCo, N=939 411), which link assessments of emotional demands by job exposure matrices to records of hospital-treated depressive disorder among employees aged 15–59 years at baseline (average follow up: 9.7 years in JEMPAD, 7.3 years in DaWCo). Potential confounders comprised sociodemographics, job control, work-related violence and physical demands at work. In DaWCo, we followed individuals from their entry into the workforce, and also included data on risk factors for depression before workforce entry (eg, parental income, education, and psychiatric diagnoses). RESULTS: Employees in occupations with high emotional demands had an increased risk of hospital-treated depressive disorder with confounder-adjusted hazard ratios of 1.32 [95% confidence interval (CI) 1.24‒1.41] and 1.19 (95% CI 1.09‒1.30) in JEMPAD and DaWCO, respectively. This association remained after controlling for risk factors before workforce entry. CONCLUSIONS: This study suggests that employees in occupations with high emotional demands are at increased risk of hospital-treated depressive disorder. This increased risk was neither attributable to reporting bias nor explained by the included risk factors for depression recorded before workforce entry.

Abstract Purpose Managers’ knowledge and behaviors in addressing musculoskeletal pain and sickness absence is not well understood. We investigated the association between managers’ knowledge and behaviours in relation to employees’ pain and their future risk of musculoskeletal pain and associated sickness absence. Methods The prospective study included 535 eldercare employees, and 42 managers from 20 nursing homes. Managers’ self-reported knowledge and behaviors in relation to employees’ pain were grouped using Principal Components Analysis. Eldercare employees reported pain-related sickness absence, and number of days with musculoskeletal pain repeatedly over 1 year. We investigated associations using mixed-effects regression models. Results We identified four types of managers’ knowledge and behaviors: 1) Pain-prevention (actions for prevention of employee pain), 2) Pain-management (actions to assist employees manage pain), 3) Pain-entitlements (communicating entitlements to employees with pain), and 4) Pain-accommodations (ability to facilitate workplace accommodations for employees with pain). The employees of managers with higher scores on knowledge of pain-entitlements reported fewer days of pain-related sickness absence (β = -0.62; 95%CI [-1.14; -0.10]). The employees of managers with higher scores on pain-management were more likely to report low back pain (β = 0.57; 95%CI [0.02; 1.11]). We found several key associations between the knowledge and behaviors measures and pain-related sickness absence (interactions). Conclusion Managers’ knowledge and behaviors in relation to employees’ pain were associated with employees’ future musculoskeletal pain and sickness absence. The relationships are complex, suggesting that a multifaceted approach is needed to ensure that managers are adequately informed on how to manage and accommodate employees with musculoskeletal pain to reduce sickness absence.

OBJECTIVES: Several studies have examined the health consequences of workplace threats and violence, however, due to methodological issues the epidemiological evidence is limited. The purpose of this study was to examine the prospective association between self-labelled exposure to work-related threats and violence and the risk of depression, measured by a standardized psychiatric interview and new prescriptions of anti-depressive medication. METHODS: Employees were recruited from the Danish PRISME cohort established in 2007 where 4489 Danish public employees answered a postal questionnaire with follow-ups in 2009 and 2011. In all three waves, depression was diagnosed by clinical interviews with the Schedules for Clinical Assessment in Neuropsychiatry (SCAN). In addition, we ascertained prescription of anti-depressive medication from a national register. Using logistic regression and Cox proportional hazard models, we estimated the association between exposure to threats and violence at baseline and SCAN depression and prescription of anti-depressive medication during two years of follow-up. RESULTS: Self-labelled exposure to work-related threats and violence was associated with a risk of SCAN diagnosed depression two years later, odds ratios (OR) 2.20 [95% confidence interval (CI) 1.13–4.28] and OR 2.11 (95% CI 1.05–4.24), respectively, with indication of a dose–response. Self-labelled exposure to work-related threats and violence was associated with prescription of anti-depressive medication in a two-year period, hazard ratios (HR) 2.55 (95% CI 1.47–4.40) and HR 1.47 (95% CI 0.70–3.06), respectively. CONCLUSION: Exposure to work-related threats or violence is associated with an increased risk of depression two years later, measured with a psychiatric interview and register data on prescribed antidepressants.

OBJECTIVES: We aimed to identify eldercare wards with different types of resident handling characteristics (‘phenotypes’) and determine the prospective association between these characteristics and musculoskeletal pain and sickness absence among workers during a one-year follow-up. METHODS: Our study was based on the DOSES cohort, including 467 workers at 103 eldercare wards. At baseline, resident handlings were assessed using onsite observations. Workers’ self-reported musculoskeletal pain and sickness absence were assessed during the following year using text messages. Observations of the frequency of handlings per shift, use of assistive devices, assistance from others, and barriers (interruptions and impediments) were estimated for each worker, aggregated at ward level, and entered into a latent profile analysis, identifying ward phenotypes. We then used generalized estimating equations to determine associations between ward phenotypes, musculoskeletal pain and sickness absence. RESULTS: We identified four ward phenotypes: ‘turbulent’ (many handlings with devices and assistance, many barriers), ‘strained’ (many handlings without devices or assistance, some barriers), ‘unpressured’ (few handlings, yet without devices or assistance, few barriers) and ‘balanced’ (some handlings with devices and assistance, some barriers). Compared to workers in balanced wards, workers in turbulent wards had more days with neck-shoulder and low-back pain (LBP); and those working in strained wards had more days with LBP and higher pain intensities. CONCLUSION: We found that ward phenotypes based on resident handling characteristics were predictive of musculoskeletal pain and sickness absence over one year. This shows that organizational factors related to resident handling are important determinants of musculoskeletal health among eldercare workers.

Purpose Common mental health problems are a substantial burden in many western countries. Studies have pointed out that work related factors can both increase and decrease the risk of developing mental health problems. Influence at work is a key factor relating the psychosocial work environment to employees mental health. However, little is known regarding how contemporary employees experience and understand influence at work. The purpose of this study is to explore this in depth. Methods We conducted semi-structured interviews with 59 employees in knowledge and relational work and analysed the data using principles from Interpretative Phenomenological Analysis (IPA). Findings TWe identified three themes each consisting of two interrelated parts, where the second part describes the consequences of the identified type of influence for employees: 1) work tasks and performance, 2) relations and belonging, 3) identity and becoming. Conclusions The interviewed employees had a multifaceted understanding of influence at work and that influence at work mattered to them in different but important ways. Our hope is that managers, employees and consultants will be inspired by the three themes when designing work tasks, organizations and interventions in order to increase the level of influence and thereby help enhance the mental well-being of employees.

This issue of the journal includes a meta-review, ie, a systematic review of systematic reviews, summarizing the published evidence on the associations between exposure to adverse psychosocial working conditions and risk of developing diseases or disorders during the past 20 years (1). Although the authors allowed inclusion of reviews reporting results from cross-sectional studies, the majority of the included reviews were restricted to prospective cohort studies – the gold standard method in psychosocial occupational epidemiology. We commend the authors for their succinct summary of the current knowledge on the topic, encompassing this multitude of exposures and outcomes in one single paper. The paper finds that there is consistent evidence of associations between certain psychosocial working conditions (job strain, effort-reward imbalance, job insecurity, long working hours) and certain health conditions (cardiovascular diseases and mental disorders, in particular depression). The paper also identifies the lack of studies concerning numerous other working and health conditions, as elegantly depicted in their figure 1, showing the presence or absence of reviews concerning all combinations of the included exposures and outcomes. The early days of psychosocial occupational epidemiology Compared to other fields of occupational health, research on psychosocial working conditions and health is a relatively recent discipline (2). One of the first studies on the topic was a paper by Friedman et al, published in 1958, reporting increased cholesterol levels and reduced blood clotting time among tax accountants during a period of putative high occupational stress, the annual April 15th tax filing deadline in the United States (3). Curiously, though, this observation did not inspire research on occupational stressors but rather led to the development of the concept of “type A behavior”, a behavioral pattern characterized by feelings of time urgency, competitiveness and hostility that became the dominant psychosocial explanation for risk of coronary heart disease in the late 1970s and early 1980s (4). The concept later largely disappeared from the discussion as findings from earlier epidemiological studies could not be replicated (5). In Belgium, Kornitzer and colleagues published a paper in 1975 on the risk of coronary heart disease in employees at two banks, and discussed whether the higher occurrence in one of the banks could be related to work organization (6), a hypothesis which they later examined and corroborated (7). In the 1960s in Sweden, Gardell, Frankenhaeuser and others pioneered both theoretical concepts and empirical research on the role of work under- and overload, participation and alienation for both workplace democracy and workers’ health (8-10). This research inspired, among other things, the development of the demand‒control model (job strain model) (11) that was tested in Swedish cohorts from the early 1980s (12, 13). The demand-control model quickly became the dominant approach for understanding the contribution of psychosocial working conditions to risk of cardiovascular disease, but reviews of these studies showed inconsistent results (14, 15). A major advance was made in 2012, when the “Individual-Participant Data Meta-Analysis in Working Populations (IPD-Work) Consortium published pooled estimates from 13 European cohort studies with almost 200 000 participants, showing a prospective association between exposure to job strain and risk of coronary heart disease (16). A key novelty of the IPD approach was to apply harmonized measures of exposures and outcomes in all included cohorts. Subsequent papers from the IPD-Work consortium showed associations between job strain and stroke (17), diabetes (18) and depression (19), between long working hours and coronary heart disease and stroke (20), diabetes (21) and depression (22) and between effort–reward imbalance and coronary heart disease (23). Whereas research on psychosocial work environment and risk of cardiovascular disease has a long history, dating back to the 1980s, research on psychosocial work environment and mental disorders emerged only towards the end of the 1990s, but then rapidly accelerated. When Stansfeld & Candy published the first systematic review and meta-analysis on psychosocial working conditions and common mental disorders in this journal in 2006, they identified only 11 papers (24). In contrast, a recent review by Mikkelsen et al identified 56 papers on the association between psychosocial working conditions and risk of incident clinical depressive disorders (25). The past 20 years of research The meta-review by Niedhammer et al only included reviews with meta-analyses that were published between 2000 and 2020. Given the acceleration of research and the growing number of studies published on the topic, this is a reasonable approach to provide an overview of the current knowledge base. Despite the restriction to the last 20 years, Niedhammer et al identified no less than 72 eligible review studies, a clear indicator of the massive proliferation of studies and the maturation of the research field. Given this vast number of studies, it is timely to ponder what we have learned. For outcomes such as cardiovascular diseases and depression, the included reviews show rather consistently that employees who report certain psychosocial working conditions, in particular job strain, effort–reward imbalance, job insecurity and long working hours, are at increased risk. But how certain can we be that these associations are causal? First, caution is needed because most of the pooled estimates are modest, usually

OBJECTIVES: Poor psychosocial work environments in hospitals are associated with higher employee turnover. In this prospective cohort study, we aimed to identify and quantify which aspects of the psychosocial work environment have the greatest impact on one-year employee turnover rates within a hospital setting, both overall and within occupational groups. METHODS: The study population included 24 385 public hospital employees enrolled in the Danish Well-being in Hospital Employees cohort in 2014. We followed the participants for one year and registered if they permanently left their workplace. Using baseline sociodemographic, workplace, and psychosocial work environment characteristics, we applied the parametric g-formula to simulate hypothetical improvements in the psychosocial work environment and estimated turnover rate differences (RD) per 10 000 employees per year and 95% confidence intervals (95% CI). RESULTS: Of the 24 385 participants, 2552 (10.5%) left the workplace during the one-year follow-up. Up to 44% of this turnover was potentially preventable through hypothetical improvements in the psychosocial work environment. The specific hypothetical improvements with the largest effects were in satisfaction with work prospects (RD -522 turnovers per 10 000 person-years, 95% CI -536– -508), general job satisfaction (RD -339, 95% CI -353– -325) and bullying (RD -200, 95% CI -214– -186). The potential for preventing turnover was larger for nurses than for physicians and other healthcare employees. CONCLUSIONS: Improvements in the psychosocial work environment may have great potential for reducing turnover among hospital staff, particularly among nurses.

Summary: Background: Heavy alcohol consumption increases the risk of several chronic diseases. In this multicohort study, we estimated the number of life-years without major chronic diseases according to different characteristics of alcohol use. Methods: In primary analysis, we pooled individual-level data from up to 129,942 adults across 12 cohort studies with baseline data collection on alcohol consumption, drinking patterns, and history between 1986 and 2005 (the IPD-Work Consortium). Self-reported alcohol consumption was categorised according to UK guidelines – non-drinking (never or former drinkers); moderate consumption (1–14 units); heavy consumption (>14 units per week). We further subdivided moderate and heavy drinkers by binge drinking pattern (alcohol-induced loss of consciousness). In addition, we assessed problem drinking using linked data on hospitalisations due to alcohol abuse or poisoning. Follow-up for chronic diseases for all participants included incident type 2 diabetes, coronary heart disease, stroke, cancer, and respiratory disease (asthma and chronic obstructive pulmonary disease) as ascertained via linkage to national morbidity and mortality registries, repeated medical examinations, and/or self-report. We estimated years lived without any of these diseases between 40 and 75 years of age according to sex and characteristics of alcohol use. We repeated the main analyses using data from 427,621 participants in the UK Biobank cohort study. Findings: During 1·73 million person-years at risk, 22,676 participants in IPD-Work cohorts developed at least one chronic condition. From age 40 to 75 years, never-drinkers [men: 29·3 (95%CI 27·9–30·8) years, women 29·8 (29·2–30·4) years)] and moderate drinkers with no binge drinking habit [men 28·7 (28·4–29·0) years, women 29·6 (29·4–29·7) years] had the longest disease-free life span. A much shorter disease-free life span was apparent in participants who experienced alcohol poisoning [men 23·4 (20·9–26·0) years, women 24·0 (21·4–26·5) years] and those with self-reported heavy overall consumption and binge drinking [men: 26·0 (25·3–26·8), women 27·5 (26·4–28·5) years]. The pattern of results for alcohol poisoning and self-reported alcohol consumption was similar in UK Biobank. In IPD-Work and UK Biobank, differences in disease-free years between self-reported moderate drinkers and heavy drinkers were 1·5 years or less. Interpretation: Individuals with alcohol poisonings or heavy self-reported overall consumption combined with a binge drinking habit have a marked 3- to 6-year loss in healthy longevity. Differences in disease-free life between categories of self-reported weekly alcohol consumption were smaller. Funding: Medical Research Council, National Institute on Aging, NordForsk, Academy of Finland, Finnish Work Environment Fund.

OBJECTIVES: The demographic changes in Europe underline the need for an extension of working lives. This study investigates the importance of physical work demands and psychosocial work factors for working beyond the state pension age (65 years). METHODS: We combined data from three cohorts of the general working population in Denmark (DWECS 2005 and 2010, and DANES 2008), where actively employed workers aged 55–59 years replied to questionnaires about work environment and were followed until the age of 66 years in the Danish AMRun register of paid employment. Using logistic regression analyses, we calculated prevalence ratios (PR) and 95% confidence intervals (CI) for the association between physical and psychosocial work factors and working beyond state pension age, adjusted for age, sex, cohort, cohabiting, sector, income, vocational education, working hours, lifestyle, and previous sickness absence. RESULTS: Of the 2884 workers aged 55–59 years, 1023 (35.5%) worked beyond the state pension age. Higher physical work demands was associated with a lower likelihood (PR 0.69, 95% CI 0.58–0.82) and a good psychosocial work environment was associated with higher likelihood (average of 7 items: PR 1.81, 95% CI 1.49–2.20) of working beyond state pension age. Stratified analyses did not change the overall pattern, ie, a good overall psychosocial work environment – as well as several specific psychosocial factors – increased the likelihood of working beyond state pension age, both for those with physically active and seated work. CONCLUSION: While high physical work demands was a barrier, a good psychosocial work environment seems to facilitate working beyond state pension age, also for those with physically active work.

About one year ago, we wrote about how the COVID-19 pandemic was unfolding worldwide and started to impact our personal and professional lives (1). Little did we know that, one year later, more than 2.5 million people would have died, with the highest death tolls in Europe, North America, and Latin America (2). Whereas in many countries, life expectancy has increased steadily over the past decades with a couple of months per year, emerging evidence shows that the COVID-19 pandemic will abruptly end this trend in various countries. As one of the most affected countries, life expectancy at birth in the US was down during the first half of 2020 already 1.0 per year compared to 2019 (3). Projections indicate a potential loss in life expectancy of 1.13 years in 2020 for the total US population, resulting in the lowest life expectancy since 2003. The disproportionate burden of COVID-19 mortality is reflected in a staggering loss of 3.1 years in the Latino population and 2.1 years in the Black population (4). It can be expected that,disparities in life expectancy between social and ethnic groups have increased in many countries, demonstrating that COVID-19 has affected different groups differently. Although deaths attributed to COVID-19 mainly occur among the elderly, often with underlying health conditions, there is scattered evidence that an individual`s type of job may contribute to the risk of becoming infected and, hence, to the mortality pattern in society. One of the first reports has emerged from the UK, where death certificates hold information on occupation. COVID-19-related mortality was highest among men in the lowest skilled occupations, with security guards among the occupation with the highest death rate. Other occupations with increased risks included taxi drivers, chauffeurs, bus drivers, restaurant chefs, and sales and retail assistants. Men and women in social care, including care and home-care workers, had increased mortality, but doctors and nurses in healthcare had death rates similar to the general workforce (5). 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 socio-economic 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 (5). 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. Again, Latino and Black Californian workers were disproportionally affected (6). Hence, working and living circumstances are strongly intertwined, best illustrated by several well-documented outbreaks of COVID-19 in slaughterhouses pointing at working conditions significantly interrelated to housing and transportation arrangements, and precarious work with migrant workers doing the lowest paid jobs (7). A recent large population-based study in Sweden showed that COVID-19-related mortality was influenced by housing conditions (less m^2 per individual in household; someone of working age in the household), neighbourhood characteristics (higher population density) and educational level (lower education) (8). This raises the question how well we can distinguish the relative contribution of these risk factors to COVID-19, with the added complexity that these risk factors often occur together in vulnerable groups. There is a lively debate as to which occupations face the highest risks of contracting COVID-19, pointing primarily towards jobs in health and social care dealing with (suspected) COVID-19 patients, and jobs that involve a large number of daily contact with the public or close physical proximity to others. However, clear insight is lacking as access to testing capacity and suitable protective equipment, and organizational and environmental control measures strongly differ across occupations. A large study among more than 2 million users of a COVID-19 symptoms app in the US and the UK showed that frontline healthcare workers reported a 12-fold higher rate of positive COVID-19 tests compared to the general community. After adjustment for the likelihood of receiving a COVID-19 test, by using inverse probability weighting, the increased likelihood of receiving a positive COVID-19 test reduced to a 3.4-fold rate, demonstrating the risk of bias due to access to testing capacity (9). Many studies have been published on infection rates within specific occupational groups, but robust studies at population level across a variety of occupations are needed to investigate the incidence of infection from coronavirus across professions. An illustrative example is the study on SARS-CoV-2 antibody seroprevalence across 18 cities in Iran, which showed rates among healthcare workers comparable to that of supermarket cashiers, pharmacy employees, and hotel staff (10). These findings suggest that the risk resulting from a working environment at higher risk of infection (eg, hospitals) may be mitigated due to effective precautions, while more measures and training may be needed in those settings with a low perception of danger and less trained workers. From an occupational health perspective, we are not only facing the fatal and non-fatal consequences of COVID-19 but also the indirect effects on mental health. Many authors have reported anecdotal evidence about higher levels of symptoms of anxiety, depression, and post-traumatic disorder among healthcare professionals. These cross-sectional studies are mere indications that workers exposed to COVID-19 patients are psychologically stressed. One of the first longitudinal studies was conducted in Japan, following more than 1000 workers during the two months of the first wave. After adjusting for the covariates, psychological distress (and subscales of fatigue, anxiety, and depression) as well as fear and worry of COVID-19 increased among healthcare workers, whereas psychological stress remained remarkably constant among non-healthcare workers (11). While the pandemic may broadly affect the mental health of the general population (12), there is a concern that it will particularly adversely affect the mental health of those most vulnerable, ie, those who already had existing mental health problems before the pandemic emerged (13). Keeping and reintegrating individuals with mental health problems in the labor market was already a major public and occupational health challenge prior COVID-­19 (14), and it might become an even bigger challenge in the near future. Less is still known about the risk to the health of workers who were required to change their regular work practice. The baseline survey of an occupational cohort in the US illustrates the profound impact of the COVID-19 pandemic where 30% of all workers had to work from home, 24% had reduced working hours or income, and 19% were furloughed or placed on leave of absence (15). Working from home may increase flexibility and control, but this may be offset by a non-work-friendly environment (eg, no room to work alone, lack of high-quality internet connection, and no ergonomic working station). A panel study in Germany suggested that particularly women working from home with children were at higher risk of exhaustion, with job autonomy and partner support partly mitigating this effect (16). A small longitudinal study in England found that 72% of workers who changed to remote work experienced increased sedentary behavior, poorer quality of sleep, and more mood disturbances (17). A repeated cross-sectional study, comparing 2016 with 2020, showed more experience and diversity in internet use, but also considerably more `techno stress`, defined as individual’s attempts and struggles to deal with constantly evolving ICTs and changing cognitive and social requirements (18). The long-lasting effects on workers` health are still unknown. It is a safe bet to accept that work arrangements will not remain the same after the pandemic. We suggest three priorities for the research agenda on COVID-19 and occupational health: 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. The impact of COVID-19 on changes in how, where, and when we work, and the consequences for workers’ health, especially mental health. The pandemic has strongly accelerated trends of already existing macroeconomic changes (eg, towards online marketplaces), and there is a need for both occupational health professionals and policy makers to adapt to this acceleration. The traditional workplace may be abandoned for many workers, and new ways must be found on how work will create value for the organization as well as the worker. The impact of the pandemic on social inequalities. This is a great concern as vulnerable groups have been disproportionately affected and their working conditions cannot be isolated from poorer social, economic, and living conditions. We can only reiterate our previous words: COVID-19 will have both short-term and long-lasting impacts on societies, healthcare systems, workplaces and individuals alike. Occupational health experts are challenged to contribute to a world, especially the world of work, that is a better place after this pandemic. References 1. Burdorf A, Porru F, Rugulies R. The Covid-19 (Coronavirus) pandemic: consequences for occupational health. Scand J Work Environ Health 2020;46:229-30. https://doi.org/10.5271/sjweh.3893 2. Johns Hopkins Corona virus resource center. Available at: https://coronavirus.jhu.edu/data/mortality, accessed March 2, 2021. 3. Arias E, Tejada-Vera B, Ahmad F. Provisional Life Expectancy Estimates for January through June, 2020. US Department of Health and Human Services: National Vital Statistics System Report No. 010, Feb 2021. https://doi.org/10.15620/100392 4. Andrasfay T, Goldman N. Reductions in 2020 US life expectancy due to COVID-19 and the disproportionate impact on the Black and Latino populations. PNAS 2021;118:e2014746118. https://doi.org/10.1073/pnas.2014746118 5. United Kingdom Office for National Statistics. Statistical bulletin: Coronavirus (COVID-19) related deaths by occupation, England and Wales: deaths registered up to and including 20 April 2020. Release date: 11 May 2020. 6. Chen YH, Glymour M, Riley A, Balmes J, Duchowny K, Harrison R, et al. Excess mortality associated with the COVID-19 pandemic among Californians 18-65 years of age, by occupational sector and occupation: March through October 2020. medRxiv preprint. https://doi.org/10.1101/2021.01.21.21250266 7. Kromhout H. Learning from a global pandemic. Occup Environ Med 2020;77:587-8. https://doi.org/10.1136/oemed-2020-106801 8. Brandén M, Aradhya S, Kolk M, Härkönen J, Drefahl S, Malmberg B, et al. Residential context and COVID-19 mortality among adults aged 70 years and older in Stockholm: a population-based, observational study using individual-level data. Lancet Healthy Longev 2020;1:e80-88. https://doi.org/10.1016/S2666-7568(20)30016-7 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo CG, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Health 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X 10. Poustchi H, Darvishian M, Mohammadi Z, Shayanrad A, Delavari A, Bahadorimonfared A, et al. SARS-CoV-2 antibody seroprevalence in the general population and high-risk occupational groups across 18 cities in Iran: a population-based cross-sectional study. Lancet Infect Dis 2020, Published Online December 15, 2020. doi.org/10.1016/S1473-3099(20)30858-6 11. Sasaki N, Kuroda R, Tsuno K, Kawakami N. The deterioration of mental health among healthcare workers during the COVID-19 outbreak: A population-based cohort study of workers in Japan. Scand J Work Environ Health 2020;46:639-44. https://doi.org/10.5271/sjweh.3922 12. Galea S, Merchant RM, Lurie N. The mental health consequences of COVID-19 and physical distancing. The need for prevention and early intervention. JAMA Intern Med. 2020;180(6):817- 8. https://doi.org/10.1001/jamainternmed.2020.1562 13. Varga TV, Bu F, Dissing AS, Elsenburg LK, Herranz Bustamante JJ, Matta J et al. Loneliness, worries, anxiety, and precautionary behaviours in response to the COVID-19 pandemic: A longitudinal analysis of 200,000 Western and Northern Europeans. The Lancet Reg Health Eur. 2021;(2):100020. https://doi.org/10.1016/j.lanepe.2020.100020 14. Schuring M, Robroek SJW, Burdorf A. The benefits of paid employment among persons with common mental health problems: evidence for the selection and causation mechanism. Scand J Work Environ Health 2017;43:540-9. https://doi.org/10.5271/sjweh.3675 15. Kobayashi LC, O’Shea BQ, Kler JS, Nishimura R, Palavicino-Maggio CB, Eastman MR, et al. Cohort profile: the COVID-19 Coping Study, a longitudinal mixed-methods study of middle-aged and older adults’ mental health and well-being during the COVID-19 pandemic in the USA. BMJ Open 2021;11:e044965. https://doi.org/10.1136/bmjopen-2020-044965 16. Meyer B, Zill A, Dilba D, Gerlach R, Schumann S. Employee psychological well-being during the COVID-19 pandemic in Germany: A longitudinal study of demands, resources, and exhaustion. Int J Psychol 2021. Feb 21, online. https://doi.org/10.1002/ijop.12743 17. Barone Gibbs B, Kline CE, Huber KA, Paley JL, Perera S. COVID-19 shelter-at-home and work, life-style and well-being in desk workers. Occup Med 2021, Feb 18. https://doi.org/10.1093/occmed/kqab011 18. Nimrod G. Technostress in a hostile world: older internet users before and during the COVID-19 pandemic. Aging Mental Health 2020, online. https://doi.org/10.1080/13607863.2020.1861213

OBJECTIVES: This study aimed to examine the association between job strain and incident coronary heart disease (CHD) in Denmark, while accounting for changes of job strain. METHODS: We included all employees residing in Denmark in 2000, aged 30–59 years with no prevalent CHD (N=1 660 150). We determined exposure to job strain from 1996–2009 using a job exposure matrix (JEM) with annual updates. Follow-up for incident CHD was from 2001–2010 via linkage to health records. We used Cox regression to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the association between job strain and incident CHD. RESULTS: During 16.1 million person-years, we identified 24 159 incident CHD cases (15.0 per 10 000 person-years). After adjustment for covariates, job strain in 2000 predicted onset of CHD during a mean follow-up of 9.71 years (HR 1.10, 95% CI 1.07–1.13). When analyzing changes in job strain from one year to the next and CHD in the subsequent year, persistent job strain (HR 1.07, 95% CI 1.03–1.10), onset of job strain (HR 1.20, 95% CI 1.12–1.29) and removal of strain (HR 1.20, 95% CI 1.12–1.28) were associated with higher CHD incidence compared to persistent no job strain. Associations were similar among men and women. CONCLUSIONS: Job strain is associated with a higher risk of incident CHD in Denmark. As we used a JEM, we can rule out reporting bias. However, under- or overestimation of associations is possible due to non-differential misclassification of job strain and residual confounding by socioeconomic position.

Background: The study aimed to determine the association of individual cognitive ability in late midlife with labor market participation among older workers. Methods: This prospective cohort study estimates the risk of long-term sickness absence, disability pension, early retirement, and unemployment from scores on the Intelligenz-Struktur-Test 2000R by combining data from 5076 workers from the Copenhagen Aging and Midlife Biobank with a register on social transfer payments. Analyses were stepwise adjusted for age, gender, physical and psychosocial work environment, health behaviors, occupational social class, education, and chronic diseases. Results: In the fully adjusted model, low cognitive ability (≥1 standard deviation below the mean for each gender) and high cognitive ability (≥1 standard deviation above the mean for each gender) were not associated with risk of any of the four labor market outcomes. Conclusion: Individual cognitive ability in late midlife was not associated with risk of long-term sickness absence, disability pension, early retirement, and unemployment in the fully adjusted model. Thus, no direct effect of individual cognitive ability in late midlife was observed on the risk of permanently or temporarily leaving the labor market.

OBJECTIVE: This review aimed to examine systematically the epidemiological evidence linking work-related exposure to violence and threats thereof with risk of mental disorders and mental ill-health symptoms. METHODS: We searched PubMed, EMBASE, PsycINFO and Web of Science to identify original studies that provide quantitative risk estimates. The evidence was weighted according to completeness of reporting, potential common method bias, and bias due to differential selection and drop out, selective reporting, and misclassification of exposure and outcome. RESULTS: We identified 14 cross-sectional and 10 cohort studies with eligible risk estimates, of which 4 examined depressive disorder and reported an elevated risk among the exposed [pooled relative risk (RR) 1.42, 95% confidence interval (CI) 1.31–1.54, I^2=0%]. The occurrence of depressive and anxiety symptoms, burnout and psychological distress was examined in 17 studies (pooled RR 2.33, 95% CI 3.17, I^2=42%), and 3 studies examined risk of sleep disturbance (pooled RR 1.22, 95% CI 1.09–1.37, I2=0%). In most studies, common method bias and confounding could not be ruled out with confidence and strong heterogeneity in most outcome definitions invalidate the strict interpretation of most pooled risk estimates. CONCLUSION: The reviewed studies consistently indicate associations between workplace violence and mental health problems. However, due to methodological limitations the causal associations (if any) may be stronger or weaker than the ones reported in this study. Prospective studies with independent and validated reporting of exposure and outcome and repeated follow-up with relevant intervals are highly warranted.

OBJECTIVES: This study determined the prospective relation between physical workload and long-term sickness absence (LTSA) and examined if work-unit social capital may buffer the effect of high physical workload on LTSA. METHODS: We included 28 925 participants from the Danish Well-being in HospitAL Employees (WHALE) cohort, and followed them for two years. Physical workload and social capital were self-reported and categorized into low, medium, and high. Physical workload was analyzed on the individual level, whereas social capital was analyzed on the work-unit level. LTSA data were obtained from the employers’ payroll system. We performed two-level logistic regression analyses: joint-effect and stratified analyses adjusted for baseline covariates. RESULTS: High versus low physical workload was associated with a higher risk of LTSA [odds ratio (OR) 1.55, 95% confidence interval (CI) 1.40–1.72]. There was a multiplicative interaction (P=0.007) and a tendency of sub-additive interaction [relative excess risk due to interaction (RERI) -0.49, 95% CI -1.03–0.06] between physical workload and social capital. Doubly exposed employees had the highest risk of LTSA (OR 2.45; 95% CI 2.02–2.98), but this effect was smaller than expected from the sum of their main effects. CONCLUSIONS: We found a prospective relation between physical workload and LTSA but no evidence of high social capital buffering the effect of high physical workload. High physical workload was a risk factor for LTSA at all levels of social capital and employees exposed to both exposures had the highest risk of LTSA. Interventions should aim at both improving social capital and reducing physical workload in order to efficiently prevent LTSA.

ObjectivesThis systematic review assesses the scientific evidence regarding the effectiveness of organisational-level workplace mental health interventions on stress, burnout, non-clinical depressive and anxiety symptoms, and wellbeing in construction workers.MethodsEligibility criteria were randomized controlled trials (RCTs), cluster randomized controlled trials (cRCTs), controlled or uncontrolled before- and after studies published in peer-reviewed journals between 2010 and May 2022 in five databases (Academic Search Complete, PsycInfo, PubMed, Scopus and Web of Science). Outcomes were stress, burnout and non-clinical depression and anxiety symptoms, and wellbeing (primary) and workplace changes and sickness absenteeism (secondary). Quality appraisal was conducted using the QATQS scale, a narrative synthesis was applied. The protocol was published in PROSPERO CRD42020183640 https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020183640.Main resultsWe identified five articles (four studies) with a total sample size of 260, one cRCT, one controlled before- and after study, and two uncontrolled before- and after studies. The methodological quality of one study was rated as moderate, while for three studies it was weak. One study showed significant effects of a work redesign programme in short-term physiological stress parameters, one study showed a significant employee perceived improvement of information flow after supervisor training and one study showed a substantial non-significant decline in sick leave. There was no significant effect on general mental health (SF12) nor on emotional exhaustion. The focus of all studies was on physical health, while detailed mental health and wellbeing measures were not applied.Main conclusionsThe evidence for the effectiveness of organisational-level workplace mental health interventions in construction workers is limited with opportunities for methodological and conceptual improvement. Recommendations include the use of a wider range of mental health and wellbeing outcomes, interventions tailored to the specific workplace and culture in construction and the application of the principles of complex interventions in design and evaluation.

As working conditions are increasingly characterized by socio-emotional demands, interpersonal interactions and relationships, and mental requirements, at least in high-income, post-industrialized societies, work and mental health has evolved as a key topic of occupational health research (1, 2). In this editorial, we focus on three main themes within this topic: (i) identifying factors at work that contribute to the onset of mental health problems and clinical mental disorders; (ii) using work as a “therapeutic tool” for individuals with mental health problems; and (iii) conducting and evaluating intervention studies. Regarding the first theme, one of the earliest systematic reviews on work-related risk factors of common mental disorders was published in 2006 by Stansfeld & Candy in this journal (3), an article that today is a “citation classic” (876 citations in Web of Science as of 6 October 2019). The authors identified job strain and effort–reward imbalance as risk factors, while acknowledging that only few studies of high quality were available (3). Today, more high quality studies are available and recent meta-analyses reported that job strain (4) and effort–reward imbalance (5) predict incident depressive disorders, corroborating the conclusion of the pioneering 2006 review. Other reviews suggest that also low job control (6), workplace bullying (6), and job insecurity (7) may be involved in the etiology of depressive disorders. Long working hours are also discussed, however, a recent review reported that associations between long working hours and depressive symptoms were relatively small and differed between world regions (8). Currently, the World Health Organization (WHO) and the International Labour Organization (ILO) are working on parameters for estimating the global burden of depressive disorders attributable to long working hours (9). Despite this progress in research, important challenges remain, for example the overreliance on traditional cohort studies with one baseline and one follow-up measure only, and on self-reported measures of working conditions that may be affected by undetected prevalent mental health problems (10). Recent studies, using multiple exposure measures with fixed-effects analyses (11) or job exposure matrices (12) have started to address these challenges. Further, more research is needed on mental disorders other than depressive disorders, such as anxiety or adjustment disorders (10). Regarding the second theme – work as a therapeutic tool – a key publication was the report by Dame Carol Black for the British Government in 2008 on “Working for a healthier tomorrow” (13). The report argued that “work which is appropriate to an individual’s knowledge, skills and circumstances, and undertaken in a safe, healthy and supportive working environment, promotes good physical and mental health, helps to prevent ill-health and can play an active part in helping people recover from illness” (13, p67). Results from observational studies have confirmed the association between employment and better mental health (15), however, it remains unclear if being employed and re-employed influences mental health, or if better mental health increases chances for work retention and re-employment. A recent review on re-employment programs reported “some indications that re-employment programmes […] had a positive effect on quality of life” but found “no evidence for benefits concerning mental health and functioning”, thus questioning the results from the observational studies (16). In an attempt to disentangle selection and causation, Schuring et al (17) used a combination of fixed and random effects models to analyze observational data on re-employment of Dutch residents diagnosed with a mental disorder. The results indicated both selection and causation effects, with the reservations that only a small fraction of the study participants actually returned to work (8%) and that confounding by time-varying confounders could not be ruled out (17). Regarding the third theme – intervention studies aiming to protect and enhance workers’ mental health – little is known about the key for success. It is therefore welcomed that in this issue of the Scandinavian Journal of Work, Environment and Health, three reviews either solely or partly focus on this topic. Phillips and colleagues identified 50 randomized controlled trials using e-mental health interventions, including 34 of those in meta-analyses (18). The interventions focused on making changes in the individual, with about two-thirds based on cognitive behavioral therapy. The authors reported “moderate effects on stress, insomnia and burnout and small treatment effects on depression, anxiety, well-being, and mindfulness”. Bordado Sköld and colleagues conducted a systematic review on the effect of exercise interventions at work on either psychosocial working conditions or workers’ mental health (19). The 22 included studies showed large heterogeneity in terms of study design, populations, interventions and outcome measures. Consequently, the authors did not calculate pooled estimates but performed a qualitative synthesis. Some studies reported improvements in mental health scores in the intervention groups, other studies did not find any effects. Overall, the results did not provide support for the hypothesis that workplace exercise programs may be beneficial for workers’ mental health. There was also no convincing effect on psychosocial working conditions. Proper & van Oostrom conducted a “meta-review” (a systematic review of previously published reviews) on the effect of workplace health promotion interventions on metabolic risk factors and musculoskeletal and mental health (20). They identified 23 reviews, including 9 of high quality. There was strong evidence for an effect of workplace health promotion programs on weight-related outcomes and the prevention of musculoskeletal disorders. Regarding mental health, Proper & van Oostrom identified 6 reviews, 4 of low and 2 of high quality. The interventions included e-mental health interventions, cognitive behavior therapy, stress management, psycho-education and physical activity. The authors conclude that there was strong evidence that e-mental health and cognitive behavior techniques had a positive effect on workers’ mental health, whereas the evidence for intervention on physical activity was less clear, echoing the conclusions by Phillips et al (18) and Bordado Sköld et al (19). What do we learn from these three reviews? First, interventions based on cognitive behavior therapy, including e-mental health interventions, seem to be an effective tool for protecting and enhancing workers’ mental health (18, 20). However, as Phillips et al noted (18), more than two-thirds of the participants in e-mental health studies were highly educated (having at least some years of university education), and jobs in knowledge-intensive occupational sectors, such as information technology, were overrepresented. Considering that mental disorders are more prevalent in individuals of lower socioeconomic position (21–23), one may be concerned that e-mental health interventions do not reach those who need help most. Further, it remains unclear if e-mental health intervention are as effective for workers with low education as they seem to be for workers with high education. Second, exercise programs at work sometimes seem to have a positive effect on mental health and other times not (19, 20), thus, no clear conclusion can be drawn. The reason for these inconsistent results are unknown as exploring these reasons was beyond the scope of the reviews (19, 20). Third, the interventions did not aim to change the work environment but rather the individual worker. In the review by Bordado Sköld (19) this was a given as the review was about exercise programs. But e-mental health interventions could have been about guidance for changing working conditions and workplace health promotion does not have to be limited to health behaviors and cognitive changes but could also target the work environment, as it has been proposed in the concepts of “Comprehensive Health Promotion” (24) and “Total Worker HealthTM” (25). However, these type of interventions did not seem to have qualified for the review on e-mental health (18) or the meta-review on workplace health promotion (20). A recent meta-review on “workplace interventions for common mental disorders” (26) identified – in agreement with the meta-review by Proper & van Oostrom (20) – cognitive behavioral therapy-based stress management as the intervention with the strongest evidence for a positive effect on workers’ mental health. The only effective intervention regarding working conditions and mental health identified in this review were interventions to increase worker control (eg, self-scheduling of shifts and gradual/partial retirement) (26). However, the evidence was weaker than for cognitive behavioral therapy. Considering the above-delineated evidence for an association between adverse working conditions and the risk of developing mental disorders (3–12) and the ongoing discussion about using work matched to one’s “knowledge, skills and circumstances, and undertaken in a safe, healthy and supportive working environment” (13) as a therapeutic tool for individuals with prevalent mental health problems and disorders (13, 15-17), it is disconcerting that organizational-level, work environment interventions to protect or enhance workers’ mental health seem either not to qualify for systematic reviews (18, 20) or, if they do, show rather weak or inconsistent results (26, 27). One reason why organizational-level interventions have not shown convincing effects regarding workers’ mental health may be that these type of interventions are highly dependent on the context in which they are implemented in (28, 29). Consequently, researchers in this field have argued for no longer only asking “What works?”, but instead “What works, for whom, under what circumstances, and how?”(30, 31). It can be regarded as a sign of scientific progress that this question is now increasingly being posed, indicating the retreat of the idea that workplace organizational interventions can be evaluated in a similar way to those of clinical trials testing the efficaciousness of a new drug (32–34). However, the real progress that still needs to be made would be to find answers to the question “What works, for whom, under what circumstances, and how?”, to report these answers in research articles, and finally to summarize these results in new types of systematic reviews and meta-analyses (35). Occupational mental health research has quite some way to go until we reach this stage.

OBJECTIVE: The aim of this study was to determine the association of physical capability with health-related labor market outcomes among older workers. METHODS: The prospective risk of disability pension and long-term sickness absence (LTSA) of ≥6 weeks was estimated from physical capability on 5076 older workers (age 49–63 years) from the Copenhagen Aging and Midlife Biobank (CAMB). Physical capability was objectively measured through nine different tests (jump performance, postural balance, chair-rise, explosive muscle strength, maximal strength of the hand, back and abdominal muscles, lung capacity, and aerobic fitness) and linked to a high-quality register on social transfer payments among all Danish residents. Cox-regression analyses estimated the association of physical capability with risk of disability pension and LTSA. RESULTS: For all measures, low physical capability [≥1 standard deviation (SD) below the mean for each gender] was associated with increased risk of disability pension and/or LTSA, whereas high physical capability (≥1 SD above the mean for each gender) was not. A capability−response association was observed between the number of tests with low capability and disability pension and LTSA (P40% of premature exits from the labor market.

SUMMARY: Background: Studies on the association between long working hours and health have captured only a narrow range of outcomes (mainly cardiometabolic diseases and depression) and no outcome-wide studies on this topic are available. To achieve wider scope of potential harm, we examined long working hours as a risk factor for a wide range of disease and mortality endpoints. Methods: The data of this multicohort study were from two population cohorts from Finland (primary analysis, n=59 599) and nine cohorts (replication analysis, n=44 262) from Sweden, Denmark, and the UK, all part of the Individual-participant Meta-analysis in Working Populations (IPD-Work) consortium. Baseline-assessed long working hours (≥55 hours per week) were compared to standard working hours (35-40 h). Outcome measures with follow-up until age 65 years were 46 diseases that required hospital treatment or continuous pharmacotherapy, all-cause, and three cause-specific mortality endpoints, ascertained via linkage to national health and mortality registers. Findings: 2747 (4·6%) participants in the primary cohorts and 3027 (6·8%) in the replication cohorts worked long hours. After adjustment for age, sex, and socioeconomic status, working long hours was associated with increased risk of cardiovascular death (hazard ratio 1·68; 95% confidence interval 1·08-2·61 in primary analysis and 1·52; 0·90-2·58 in replication analysis), infections (1·37; 1·13-1·67 and 1·45; 1·13-1·87), diabetes (1·18; 1·01-1·38 and 1·41; 0·98-2·02), injuries (1·22; 1·00-1·50 and 1·18; 0·98-1·18) and musculoskeletal disorders (1·15; 1·06-1·26 and 1·13; 1·00-1·27). Working long hours was not associated with all-cause mortality. Interpretation: Follow-up of 50 health outcomes in four European countries suggests that working long hours is associated with an elevated risk of early cardiovascular death and hospital-treated infections before age 65. Associations, albeit weak, were also observed with diabetes, musculoskeletal disorders and injuries. In these data working long hours was not related to elevated overall mortality. Funding: NordForsk, the Medical Research Council, the National Institute on Aging, the Wellcome Trust, Academy of Finland, and Finnish Work Environment Fund.

Background: The World Health Organization (WHO) and the International Labour Organization (ILO) are developing the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury (WHO/ILO Joint Estimates), supported by a large number of individual experts. Evidence from previous reviews suggests that exposure to long working hours may cause depression. In this article, we present a systematic review and meta-analysis of parameters for estimating (if feasible) the number of deaths and disability-adjusted life years from depression that are attributable to exposure to long working hours, for the development of the WHO/ILO Joint Estimates. Objectives: We aimed to systematically review and meta-analyse estimates of the effect of exposure to long working hours (three categories: 41–48, 49–54 and ≥55 h/week), compared with exposure to standard working hours (35–40 h/week), on depression (three outcomes: prevalence, incidence and mortality). Data sources: We developed and published a protocol, applying the Navigation Guide as an organizing systematic review framework where feasible. We searched electronic academic databases for potentially relevant records from published and unpublished studies, including the WHO International Clinical Trial Registers Platform, Medline, PubMed, EMBASE, Web of Science, CISDOC and PsycInfo. We also searched grey literature databases, Internet search engines and organizational websites; hand-searched reference lists of previous systematic reviews; and consulted additional experts. Study eligibility and criteria: We included working-age (≥15 years) workers in the formal and informal economy in any WHO and/or ILO Member State but excluded children (aged

Summary: Background: High emotional demands at work can affect employees’ health and there is a need to understand whether such an association might be modified by other working conditions. We aimed to examine emotional demands at work as a risk factor for long-term sickness absence and analyse whether influence, possibilities for development, role conflicts, and physical demands at work might modify this risk. Methods: We did a nationwide, population-based, prospective cohort study in Denmark and included employed individuals who were residing in Denmark in 2000, aged 30–59 years, who had complete data on age, sex, and migration background, with information on emotional demands and possible effect modifiers from job exposure matrices, and covariates and outcome (sickness absence) from population registers. Individuals with long-term sickness absence (≥6 weeks of consecutive sickness absence) between Jan 1, 1998, and Dec 31, 2000, and self-employed individuals were excluded. We assessed long-term sickness absence during a 10-year period from Jan 1, 2001, to Dec 31, 2010. Using Cox regression, we estimated hazard ratios (HRs) and 95% CIs and tested interaction as departure from additivity, estimating relative excess risk due to interaction (RERI). Multivariable adjusted models included sex, age, cohabitation, migration background, and income. Findings: 1 521 352 employed individuals were included and contributed data between Jan 1, 2000, and Dec 31, 2010. During 11 919 021 person-years (mean follow-up 7·8 years), we identified 480 685 new cases of long-term sickness absence. High emotional demands were associated with increased risk of long-term sickness absence compared with low emotional demands, after adjusting for age, sex, cohabitation, migration background, income, and the four possible effect modifiers (adjusted HR 1·55 [95% CI 1·53–1·56]). The association between high emotional demands and risk of long-term sickness absence was stronger in a synergistic way when individuals were also exposed to low possibilities for development (RERI 0·35 [95% CI 0·22–0·47]; 28·9 additional cases per 1000 person-years) and high role conflicts (0·13 [0·11–0·15]; 22·0 additional cases per 1000 person-years). No synergy was observed for influence and physical demands at work. Interpretation: People in occupations with high emotional demands were at increased risk of long-term sickness absence. Our findings on synergistic interactions suggest that, in emotionally demanding occupations, increasing possibilities for development and reducing work-related role conflicts might reduce long-term sickness absence. Further interventional studies are needed to confirm or refute this hypothesis. Funding: Danish Work Environment Research Fund, NordForsk.

Background: World Health Organization (WHO) and International Labour Organization (ILO) systematic reviews reported sufficient evidence for higher risks of ischemic heart disease and stroke amongst people working long hours (≥55 hours/week), compared with people working standard hours (35–40 hours/week). This article presents WHO/ILO Joint Estimates of global, regional, and national exposure to long working hours, for 194 countries, and the attributable burdens of ischemic heart disease and stroke, for 183 countries, by sex and age, for 2000, 2010, and 2016. Methods and Findings: We calculated population-attributable fractions from estimates of the population exposed to long working hours and relative risks of exposure on the diseases from the systematic reviews. The exposed population was modelled using data from 2324 cross-sectional surveys and 1742 quarterly survey datasets. Attributable disease burdens were estimated by applying the population-attributable fractions to WHO’s Global Health Estimates of total disease burdens. Results: In 2016, 488 million people (95% uncertainty range: 472–503 million), or 8.9% (8.6–9.1) of the global population, were exposed to working long hours (≥55 hours/week). An estimated 745,194 deaths (705,786–784,601) and 23.3 million disability-adjusted life years (22.2–24.4) from ischemic heart disease and stroke combined were attributable to this exposure. The population-attributable fractions for deaths were 3.7% (3.4–4.0) for ischemic heart disease and 6.9% for stroke (6.4–7.5); for disability-adjusted life years they were 5.3% (4.9–5.6) for ischemic heart disease and 9.3% (8.7–9.9) for stroke. Conclusions: WHO and ILO estimate exposure to long working hours (≥55 hours/week) is common and causes large attributable burdens of ischemic heart disease and stroke. Protecting and promoting occupational and workers’ safety and health requires interventions to reduce hazardous long working hours.

In this issue of the Journal, a group of distinguished Nordic researchers, led by Anne Helene Garde and including four of our Associated Editors, present a discussion paper that originated from a workshop and provides detailed recommendations on night shift work (1). The recommendations are very clear: to protect workers’ health, night shift schedules should have: (i) ≤3 consecutive night shifts; (ii) shift intervals of ≥11 hours; and (iii) ≤9 hours shift duration. For pregnant women, night work should be limited to one shift per week. The authors acknowledge that under circumstances allowing better possibilities for daytime sleep, recommendations could be different. The discussion paper is remarkable in that it provides clear and strong recommendations based on what the authors themselves call a “limited literature”, thus a limited scientific evidence on the risk of shift work for cancer and other health and safety risks. In a recent editorial, British researchers concluded that, due to heterogeneity of shift working in longitudinal studies, it is too difficult to draw a firm conclusion about the risk of breast cancer, let alone about an exposure threshold for night shift work (2). Yet, both Nordic and British researchers seemed to agree that we should not postpone recommendations on best practice in shift work scheduling for reasons of lack of certainty on causal inference. For the most important health and safety conditions the Nordic authors are concerned with – cancer, cardiovascular disease, diabetes, injuries and pregnancy-related outcomes – the evidence relies on observational studies. Although longitudinal studies on shift work increasingly use register-based exposure information on working hours patterns, often based on payroll data that is linked with registers in healthcare (3, 4), these studies are still vulnerable to important biases, such as selection bias and residual confounding. There are several examples in the literature of well-conducted observational studies suggesting an effect of an exposure that subsequently was not corroborated in randomized controlled trials (RCT). One of the most famous examples is hormone replacement therapy (HRT) in post-menopausal women. Numerous observational studies suggested a protected effect of HRT with regard to risk of cardiovascular disease (5, 6), but when an RCT was finally conducted, it found the effect of HRT to be more harmful than beneficial (7). Recently, a large-scale RCT found no effect of vitamin D intake on reduced risk of depression (8), despite numerous observational studies suggesting such an effect (9). Thus, there are good reasons to treat results from observational studies with caution. On the other hand, exercising caution does not mean that one should abstain from making recommendations when evidence is based on observational studies only, in the hope that this would keep one on the safe side of scientific scrutiny. There is no safe side. In accordance with Paul Watzlawick’s famous quote that “one cannot not communicate” (10), it can be reasoned that not making recommendations is also a form of recommendation, the recommendation to continue business as usual. The recommendation to stop asbestos production, which rather came too late than too early, was not based on RCT but observational studies on the multiple health-hazardous effects of asbestos (11). Thus, when considering the evidence, researchers should not only consider the best evidence based on available data and their causal inference, but also the potential consequences of continuing current practice. Fifty-five years ago, Sir Austin Bradford Hill published his famous nine viewpoints on causal inference in health research (12). As pointed out by Bradford Hill, as well as other scholars (13), none of the nine viewpoints (today mostly known as “criteria”) ensures that an observed observation is causal, however, they still might be helpful in assessing the confidence whether or not a measure of association indicates a causal link between two variables. Today, causal inference remains an intensively discussed topic. In its December 2016 issue, the International Journal of Epidemiology published a series of articles, discussion papers and letters on causal inference in epidemiology, in particular on the merits and limitations of the counterfactual “potential outcome approach”, which relies heavily on experiments whether induced by the researcher or natural changes in particular situations that may be interpreted as happening at random (14, 15). This approach has been criticized by proponents of a more “pluralistic approach” for a variety of reasons, among others that it limits causality to particular factors that are usually not widely generalizable (16, 17). Very recently (September 2020), in an opinion paper (18), the main proponent of the potential outcome approach, Tyler VanderWeele asked: “Can sophisticated study designs with regression analyses of observational data provide causal inferences?” The answer seem to be a cautious “yes”. Regarding single observational studies, VanderWeele lists eight considerations that increase confidence in the estimate, including longitudinal design; the quality of the assessment of exposure, outcome and confounders; flexible statistical modeling examining robustness to modelling decisions; and attempts to address unmeasured confounding. Evidence then may evolve from accumulation of results from multiple high-quality studies, in particular if these have different designs that are subject to different biases (18). The struggle on causal interpretation and subsequent evidence-based recommendations is also visible in the GRADE (Grading of Recommendations, Assessments and Evaluations) system, which rates the certainty of evidence and the strengths of recommendations in systematic reviews, for example in Scandinavian Journal of Work, Environment and Health articles (19-22). As GRADE has its origins in healthcare evaluation, its evidence assessment favors the RCT, and although the GRADE working group encourages applying GRADE to observational studies (23), the quality rating of observational studies always starts with “low quality”, with possibilities for upgrading and downgrading, whereas the quality rating of RCT starts with “high quality”. The recently developed “Navigation Guide” (24) - a methodology for synthesizing evidence in systematic reviews that evolved from environmental research but is now also applied in occupational health research (25, 26) - recommends a different approach, where the quality assessment of observational studies starts with “moderate” before the process of up- or downgrading (24). Garde et al’s paper (1) is not a systematic review, it uses neither GRADE nor Navigation Guide methodology and does not grade the evidence. It is a discussion paper written by leading researchers in the field that base their conclusions and recommendations on their knowledge of the literature, including systematic reviews. Given that a substantial proportion of the workforce is exposed to some type of night shift work, this is a bold, but necessary, step. We are looking forward to further research, both original studies and reviews, corroborating or challenging the conclusions and recommendations of this discussion paper. References 1. Garde AH, Begtrup L, Bjorvatn B, Bonde JP, Hansen J, Hansen ÅM, et al. How to schedule night shift work in order to reduce health and safety risks. Scand J Work Environ Health. 2020;46(6):557-569. https://doi.org/10.5271/sjweh.3920 2. McElvenny DM, Crawford JO, Cherrie JW. What should we tell shift workers to do to reduce their cancer risk? Occup Med (Lond). 2018;68(1):5-7. https://doi.org/10.1093/occmed/kqx187 3. Nielsen HB, Larsen AD, Dyreborg J, Hansen ÅM, Pompeii LA, Conway SH, et al. Risk of injury after evening and night work - findings from the Danish Working Hour Database. Scand J Work Environ Health. 2018;44(4):385-393. https://doi.org/10.5271/sjweh.3737 4. Härmä M, Ropponen A, Hakola T, Koskinen A, Vanttola P, Puttonen S, et al. Developing register-based measures for assessment of working time patterns for epidemiologic studies. Scand J Work Environ Health. 2015;41(3):268-279. https://doi.org/10.5271/sjweh.3492 5. Grodstein F, Stampfer M. The epidemiology of coronary heart disease and estrogen replacement in postmenopausal women. Prog Cardiovasc Dis. 1995;38(3):199-210. https://doi.org/10.1016/S0033-0620(95)80012-3 6. Grodstein F, Stampfer MJ, Manson JE, Colditz GA, Willett WC, Rosner B, et al. Postmenopausal estrogen and progestin use and the risk of cardiovascular disease. N Engl J Med. 1996;335(7):453-461. https://doi.org/10.1056/NEJM199608153350701 7. Manson JE, Hsia J, Johnson KC, Rossouw JE, Assaf AR, Lasser NL, et al. Estrogen plus progestin and the risk of coronary heart disease. N Engl J Med. 2003;349(6):523-534. https://doi.org/10.1056/NEJMoa030808 8. Okereke OI, Reynolds CF, 3rd, Mischoulon D, Chang G, Vyas CM, Cook NR, et al. Effect of long-term vitamin D3 supplementation vs placebo on risk of depression or clinically relevant depressive symptoms and on change in mood scores: a randomized clinical trial. JAMA. 2020;324(5):471-480. https://doi.org/10.1001/jama.2020.10224 9. Li H, Sun D, Wang A, Pan H, Feng W, Ng CH, et al. Serum 25-hydroxyvitamin D levels and depression in older adults: a dose-response meta-analysis of prospective cohort studies. Am J Geriatr Psychiatry. 2019;27(11):1192-1202. https://doi.org/10.1016/j.jagp.2019.05.022 10. Watzlawick P, Beavin-Bavelas J, Jackson D. Pragmatics of human communication. A study of interactional patterns, pathologies and paradoxes. New York: Norten; 1967. 11. Gee D, Greenberg M. Asbestos: from ’magic’ to malevolent mineral. In: European Environment Agency, editor. Late lessons from early warnings: the precautionary principle 1896-2000. Environmental issue report No 22/2001. Luxembourg: Office for Official Publications of the European Communities; 2001. p.52-63. Available from: https://www.eea.europa.eu/publications/environmental_issue_report_2001_22. 12. Bradford Hill A. The environment and disease: association or causation? Proc R Soc Med. 1965;58:295-300. https://doi.org/10.1177/003591576505800503 13. Rothman KJ, Greenland S. Causation and causal inference in epidemiology. Am J Public Health. 2005;95 (Suppl 1):S144-150. https://doi.org/10.2105/AJPH.2004.059204 14. VanderWeele TJ. Commentary: On causes, causal inference, and potential outcomes. Int J Epidemiol. 2016;45(6):1809-1816. 15. Robins JM, Weissman MB. Commentary: Counterfactual causation and streetlamps: what is to be done? Int J Epidemiol. 2016;45(6):1830-1835. 16. Vandenbroucke JP, Broadbent A, Pearce N. Causality and causal inference in epidemiology: the need for a pluralistic approach. Int J Epidemiol. 2016;45(6):1776-1786. https://doi.org/10.1093/ije/dyv341 17. Krieger N, Davey Smith G. The tale wagged by the DAG: broadening the scope of causal inference and explanation for epidemiology. Int J Epidemiol. 2016;45(6):1787-1808. https://doi.org/10.1093/ije/dyw114 18. VanderWeele TJ. Can sophisticated study designs with regression analyses of observational data provide causal inferences? JAMA Psychiatry. Online First https://doi.org/10.1001/jamapsychiatry.2020.2588 19. Rönnblad T, Grönholm E, Jonsson J, Koranyi I, Orellana C, Kreshpaj B, et al. Precarious employment and mental health: a systematic review and meta-analysis of longitudinal studies. Scand J Work Environ Health. 2019;45(5):429-443. https://doi.org/10.5271/sjweh.3797 20. Andersen JH, Malmros P, Ebbehoej NE, Flachs EM, Bengtsen E, Bonde JP. Systematic literature review on the effects of occupational safety and health (OSH) interventions at the workplace. Scand J Work Environ Health. 2019;45(2):103-113. https://doi.org/10.5271/sjweh.3775 21. Oakman J, Neupane S, Proper KI, Kinsman N, Nygard CH. Workplace interventions to improve work ability: A systematic review and meta-analysis of their effectiveness. Scand J Work Environ Health. 2018;44(2):134-146. https://doi.org/10.5271/sjweh.3685 22. Stock SR, Nicolakakis N, Vezina N, Vezina M, Gilbert L, Turcot A, et al. Are work organization interventions effective in preventing or reducing work-related musculoskeletal disorders? A systematic review of the literature. Scand J Work Environ Health. 2018;44(2):113-133. https://doi.org/10.5271/sjweh.3696 23. Schünemann H, Hill S, Guyatt G, Akl EA, Ahmed F. The GRADE approach and Bradford Hill’s criteria for causation. J Epidemiol Community Health. 2011;65(5):392-395. https://doi.org/10.1136/jech.2010.119933 24. Woodruff TJ, Sutton P. The Navigation Guide systematic review methodology: a rigorous and transparent method for translating environmental health science into better health outcomes. Environ Health Perspect. 2014;122(10):1007-1014. https://doi.org/10.1289/ehp.1307175 25. Li J, Pega F, Ujita Y, Brisson C, Clays E, Descatha A, et al. The effect of exposure to long working hours on ischaemic heart disease: A systematic review and meta-analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury. Environ Int. 2020;142:105739. https://doi.org/10.1016/j.envint.2020.105739 26. Descatha A, Sembajwe G, Pega F, Ujita Y, Baer M, Boccuni F, et al. The effect of exposure to long working hours on stroke: A systematic review and meta-analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury. Environ Int. 2020;142:105746. https://doi.org/10.1016/j.envint.2020.105746

OBJECTIVES: The aim of this study was to describe the development and the content of the Danish Psychosocial Work Environment Questionnaire (DPQ) and to test its reliability and validity. METHODS: We describe the identification of dimensions, the development of items, and the qualitative and quantitative tests of the reliability and validity of the DPQ. Reliability and validity of a 150 item version of the DPQ was evaluated in a stratified sample of 8958 employees in 14 job groups of which 4340 responded. Reliability was investigated using internal consistency and test-retest reliability. The factorial validity was investigated using confirmatory factor analysis (CFA). For each multi-item scale, we undertook CFA within each job group and multi-group CFA to investigate factorial invariance across job groups. Finally, using multi-group multi-factor CFA, we investigated whether scales were empirically distinct. RESULTS: Internal consistency reliabilities and test-retest reliabilities were satisfactory. Factorial validity of the multi-item scales was satisfactory within each of the 14 job groups. Factorial invariance was demonstrated for 10 of the 28 multi-item scales. The hypothesis that the scales of the DPQ were empirically distinct was supported. The final DPQ version consisted of 119 items covering 38 different psychosocial work environment dimensions. CONCLUSIONS: Overall, the DPQ is a reliable and valid instrument for assessing psychosocial working conditions in a variety of job groups. The results indicate, however, that questions about psychosocial working conditions may be understood differently across job groups, which may have implications for the comparability of questionnaire-based measures of psychosocial working conditions across job groups.

Abstract Background A high level of workplace social capital (WSC) may contribute to the protection of employees’ health. We hypothesized that a participatory workplace intervention would increase the level of WSC defined as vertical WSC (i.e. WSC linking together employees and their leaders) and horizontal WSC (i.e. WSC bonding employees together). Methods We conducted a secondary data analysis of a cluster randomized controlled trial that was implemented among all employees in 78 municipal Danish pre-schools (44 intervention and 34 control group schools). The study sample consisted of 606 employees, 386 in the intervention and 220 in the control group. The intervention aimed to improve the psychosocial working environment by using a participatory approach and focusing on core job tasks. Vertical and horizontal WSC was measured by five and four items, respectively, at baseline and at 24-months follow-up. We estimated intervention effect by calculating the interaction of change over time by group assignment (intervention versus control group) and included workplace identification number in a repeated statement to take into account that employees were nested within workplaces. We conducted post-hoc analyses to examine whether intervention effect differed by implementation degree. Results WSC decreased in both groups. In the main analyses, there was no statistically significant difference between intervention and control group, neither for vertical nor horizontal WSC. However, when we excluded intervention workplaces with a low degree of implementation, we found a statistically significant difference between the intervention and the control group (estimate: 0.25, 95% CI: 0.00 to 0.50, p = 0.049), indicating that vertical WSC decreased in the control group and remained stable in the intervention group. Conclusions There was not a statistically significant difference between intervention and control group in the main analysis. Post-hoc analyses, however, suggest that the intervention may have prevented a decrease in vertical WSC among employees in workplaces with a high or a medium degree of implementation. A conference abstract with the key results of this study has been previously presented and published, European Journal of Public Health, Volume 28, Issue suppl_4, November 2018, cky260, https://academic.oup.com/eurpub/article/28/suppl_4/cky260/5187184. Trial registration ISRCTN16271504, retrospectively registered on November 15, 2016.

Background: The World Health Organization (WHO) and the International Labour Organization (ILO) are developing a joint methodology for estimating the national and global work-related burden of disease and injury (WHO/ILO joint methodology), with contributions from a large network of experts. In this paper, we present the protocol for two systematic reviews of parameters for estimating the number of deaths and disability-adjusted life years from depression attributable to exposure to long working hours, to inform the development of the WHO/ILO joint methodology. Objectives: We aim to systematically review studies on occupational exposure to long working hours (Systematic Review 1) and systematically review and meta-analyse estimates of the effect of long working hours on depression (Systematic Review 2), applying the Navigation Guide systematic review methodology as an organizing framework, conducting both systematic reviews in tandem and in a harmonized way. Data sources: Separately for Systematic Reviews 1 and 2, we will search electronic academic databases for potentially relevant records from published and unpublished studies, including Medline, EMBASE, Web of Science, CISDOC and PsycINFO. We will also search electronic grey literature databases, Internet search engines and organizational websites; hand search reference list of previous systematic reviews and included study records; and consult additional experts. Study eligibility and criteria: We will include working-age (≥15 years) participants in the formal and informal economy in any WHO and/or ILO Member State, but exclude child workers (

OBJECTIVES: This study aimed to examine the association between negative life events, job stressors (low job control or high psychosocial job demands) and offspring asthma phenotypes (early-onset transient, early-onset persistent and late-onset asthma). METHODS: In a population-based cohort study comprising 547 533 liveborn singletons, we determined negative life events and offspring asthma at age six years using data from Danish nationwide registers. We assessed job demands and job control from gender-specific job exposure matrices. Prevalence ratios (PR) of each asthma phenotype were estimated using log-binomial regression. RESULTS: Maternal exposure to negative life events prenatally was not significantly associated with offspring asthma. Among mothers with low job demands, low job control was associated with increased risk for early-onset transient asthma [PR=1.14, 95% confidence interval (CI) 1.09–1.19], early-onset persistent asthma (PR=1.17, 95% CI 1.11–1.23), and late-onset asthma (PR=1.06, 95% CI 1.00–1.14). Among mothers with high job demands, low job control was not associated with offspring asthma apart from a reduced risk of early-onset persistent asthma (PR=0.94, 95% CI 0.90–0.97). These associations were independent of child sex and parental atopic history. CONCLUSIONS: Maternal stressors in private life do not seem to influence offspring asthma significantly. Low job control is associated with offspring asthma, which is modified by maternal psychosocial job demands. Our findings warrant further exploration.

The term “psychosocial work environment” appears frequently in research articles, including those published in the Scandinavian Journal of Work, Environment and Health (1‒8). Recently, the first international handbook on the emerging field of “psychosocial epidemiology” extensively addressed the contribution of psychosocial working conditions to health and illness (9). 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 (10). Such concerns recently motivated the Swedish Work Environment Authority to remove the term psychosocial work environment when they published their new provision on the organizational and social work environment: ”A common term used for this work environment is psychosocial. This is a broad concept that basically refers to how the individual experiences and responds to his or her surroundings and thus the individual becomes the focus. Instead, we have chosen to highlight the organizational and social conditions and requirements at work because that is what the employer can control.” (11, p12). (Translated from Swedish by the author.) In the following, I provide some comments on this debate. I 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. Historical use of the term "psychosocial work environment" To my knowledge, the first English-language research article using “psychosocial work environment” in the title was published in 1982. It was on “Myocardial infarction risk and psychosocial work environment: an analysis of the male Swedish working force”, authored by the two Swedish researchers Lars Alfredsson and Töres Theorell and the US-American researcher Robert Karasek (12). Also in the following years, the term was mainly used in articles by Swedish/US author groups. In 1991, 21 researchers, again most of them from Sweden and the US, contributed to the book The Psychosocial Work Environment: Work Organization, Democratization and Health (13). The book was published in memory of Bertil Gardell, who held the first chair of work and organizational psychology at the Department of Psychology at the University of Stockholm from 1976 until his early death in 1987 (14). Since the 1960s, Gardell had published on topics such alienation, monotonous and deskilling work, influence and autonomy, and many articles in the book were dedicated to these factors (13). This line of research led, among other things, to the development of the demand‒control (job strain) model that dominated psychosocial work environment research in the 1980s and 1990s (15). In the 1990s and early 2000s, psychosocial work environment research increasingly included new concepts, such as balance between efforts and rewards (16), organizational justice (17), workplace social capital (18) and workplace bullying (19). One could say that psychosocial work environment research became more “psychological”, in the sense that research became increasingly focused on whether or not workers feel treated fairly and respected and on the emotional effects of work tasks, procedures, or behaviors by supervisors, colleagues, clients and customers. In the Encyclopaedia of Occupational Health and Safety, published in 1998 by the International Labor Office (ILO) (20), the chapter on “Psychosocial and Organizational Factors” illustrated this broadened perspective. “These conditions, which are commonly referred to as psychosocial factors, include aspects of the job and work environment such as organizational climate or culture, work roles, interpersonal relationships at work, and the design and content of tasks (eg, variety, meaning, scope, repetitiveness, etc.). The concept of psychosocial factors extends also to the extra-organizational environment (eg, domestic demands) and aspects of the individual (eg, personality and attitudes), which may influence the development of stress at work. Frequently, the expressions work organization or organizational factors are used interchangeably with psychosocial factors in reference to working conditions which may lead to stress.” (20, p34.32). This quote also shows that defining “psychosocial factors” can be challenging. On the one hand, the authors regard psychosocial factors as interchangeable with “work organization”. On the other hand, they point out that psychosocial factors also extend to “aspects of the individual” such as “personality and attitudes”. The use of the same term for very different phenomena such as work organization and personality and attitudes is problematic in the ILO definition, and it is unclear how work organization and individual aspects are thought to be related to each other. A conceptual framework for research on psychosocial work environment and health Figure 1 shows a conceptual framework for research on psychosocial work environment and health depicting the relation of the psychosocial work environment to phenomena both on the societal and individual level. I adapted and modified the framework from two previous publications: an editorial on "Psychosocial determinants of health in social epidemiology" by Martikainen et al (21) and a book chapter on "Epidemiology of health and illness: A ­socio-psycho-physiological perspective" by Rugulies et al (22). Similar frameworks have been published elsewhere (23‒25). The steps in the causal pathway are denoted with roman numerals to which I will refer frequently. The pathway starts with (i) (macro-level) economic, social and political structures, such as the modes of production, division of labor, type of social welfare regime or the legal system and (ii) (meso-level) workplace structures, such as type of employment contract or adequacy of staffing that (iii) impact the meso-level psychosocial working conditions, such as job demands, work organization, content of work or social relations at work. These psychosocial working conditions are experienced by (iv) the individual, or group of individuals, and elicit cognitive and emotional processes. Through these processes the psychosocial working conditions subsequently evoke (v) psycho-physiological changes and (vi) health-related behaviors that (vii) affect risk of somatic diseases and mental disorders. A challenge for psychosocial work environment research is the step from (iii) to (iv), where the working conditions “get under the skin” of the workers and are assumed to alter the workers’ cognitions, emotions, behavior and physiology ‒ a process that has also been termed as “embodiment” (26). This is a two-way process, in which not only the working conditions alter the mind and the body of the workers, but where the workers’ cognitions and emotions also alter the way the workers experience working conditions (27). This raises the question to what extent the working conditions in the environment (iii) differ from the experienced working conditions by the individual (iv), a question that is in particular crucial for research that aims to ascertain psychosocial working conditions as exposures in the environment but for practical reasons measures these conditions by self-report from the individual (28, 29). A related question is the extent to which experiencing working conditions requires a conscious process, or if certain working conditions could be embodied while bypassing the consciousness of the individual (30). The conceptual framework depicted in figure 1 may be useful for placing studies from different academic disciplines into a bigger picture of psychosocial work environment research, emphasizing the transdisciplinary nature of this type of research. Work environment research that is denoted as “psychosocial” is often focused on how psychosocial working conditions (iii), such as job demands, work organization, job content or social relations at work (1) are affecting psycho-physiological changes (v) (eg, stress axis activation) (31), health-related behaviors (vi) (eg, smoking or leisure time physical activity) (32, 33) or risk of diseases and disorders (vii), such as cardiovascular disease (34, 35), diabetes (36, 37), musculoskeletal disorders (38) or depression (39-41). In addition to this, the framework in figure 1 suggests that psychosocial work environment research may also include research on the historical origins of contemporary societal structures (i) (42-44) and on the impact of macro-level phenomena (i) (eg, the global financial crisis of 2007) on workers’ health (vii) (45) and how this impact may be explained by changes in workplace structures (ii), for example by staff reductions, or by deteriorating working conditions and reduced job security (iii) (46, 47). Psychosocial work environment research may further include psychobiological research that focuses on how the cognitive and emotional processing of the individual (iv) evoke psycho-physiological changes (v) (48). The framework in figure 1 shows a uni-directional process. Although reversed associations are possible, for example that health and illness (vii) may affect individuals’ health-related behaviors (vi) or cognitive and emotional processes (iv), such bi-directional associations are intentionally not depicted to emphasize the main direction in the chain of causation from the macro-level to the meso-level to the individual-level. One exception though has been made, indicated by the dashed arrows originating from “individual-level experience and cognitive and emotional processes” and pointing to “workplace structures” and “psychosocial working conditions”. These arrows are shown to acknowledge workers’ individual and collective efforts to change workplace structures and working conditions. One example is the struggle of labor unions worldwide for the eight-hour work day in the 19th and early 20th centuries (49). Another example is what has been termed as “job crafting”, that is the behaviors of workers to reduce barriers and enhance resources at work (50). To summarize, I suggest to regard the psychosocial work environment as an intermediate step in a causal pathway linking economic, social and political structures with health and illness through psychological and psycho-physiological processes. Because of the intermediary position of the psychosocial work environment, psychosocial work environment research is not limited to “how the individual experiences and responds to his or her surroundings” (11, p12), but includes also research on the macro- and meso-level structures that determine and shape the psychosocial work environment. The psychosocial work environment is therefore a key research field for understanding how the interrelation of societal structures, environmental exposures, and psychological and psycho-physiological processes affect health and illness. Acknowledgement Many thanks to my colleagues from the “Psychosocial Work Environment Research Group” at the National Research Centre for the Working Environment, Copenhagen, Denmark, for their inspiring and critical feedback on an internal discussion paper on the meaning of psychosocial work environment circulated in spring 2018. Special thanks to senior researchers Birgit Aust and Ida EH Madsen for comments to the first draft of this editorial.

Background: The World Health Organization (WHO) and the International Labour Organization (ILO) are developing Joint Estimates of the work-related burden of disease and injury (WHO/ILO Joint Estimates), with contributions from a large network of experts. Evidence from mechanistic data suggests that exposure to long working hours may increase alcohol consumption and cause alcohol use disorder. In this paper, we present a systematic review and meta-analysis of parameters for estimating the number of deaths and disability-adjusted life years from alcohol consumption and alcohol use disorder that are attributable to exposure to long working hours, for the development of the WHO/ILO Joint Estimates. Objectives: We aimed to systematically review and meta-analyse estimates of the effect of exposure to long working hours (three categories: 41–48, 49–54 and ≥55 h/week), compared with exposure to standard working hours (35–40 h/week), on alcohol consumption, risky drinking (three outcomes: prevalence, incidence and mortality) and alcohol use disorder (three outcomes: prevalence, incidence and mortality). Data sources: We developed and published a protocol, applying the Navigation Guide as an organizing systematic review framework where feasible. We searched electronic bibliographic databases for potentially relevant records from published and unpublished studies, including the WHO International Clinical Trials Register, Ovid MEDLINE, PubMed, Embase, and CISDOC on 30 June 2018. Searches on PubMed were updated on 18 April 2020. We also searched electronic grey literature databases, Internet search engines and organizational websites; hand-searched reference list of previous systematic reviews and included study records; and consulted additional experts. Study eligibility and criteria: We included working-age (≥15 years) workers in the formal and informal economy in any WHO and/or ILO Member State but excluded children (

Objective/background: Associations between exposure to effort-reward imbalance at work (eg, high time pressure/low appreciation) and risk of sleep disturbances have been reported, but the direction of the effect is unclear. The present study investigated changes in effort-reward imbalance and risk of concomitant and subsequent onset of sleep disturbances. Methods: Participants with sleep disturbances at baseline were excluded. We included participants from a population-based cohort in Denmark (n = 8,464, 53.6% women, mean age = 46.6 years), with three repeated measurements (2012 (T0); 2014 (T1); 2016 (T2)). Changes in effort-reward imbalance (T0-T1) were categorized into ‘increase’, ‘decrease’ and ‘no change’. Self-reported sleep disturbances (difficulties initiating or maintaining sleep, non-restorative sleep, daytime tiredness) were dichotomized (presence versus absence). We regressed concomitant (T1) and subsequent (T2) sleep disturbances on changes in effort-reward imbalance (T0-T1) and calculated odds ratios (OR) and 95% confidence intervals, adjusted for sex, age, education and cohabitation. Results: At follow-up, 8.4% (T1) and 12.5% (T2) reported onset of sleep disturbances. Increased effort-reward imbalance was associated with concomitant sleep disturbances (T1) (OR = 3.16, 2.56–3.81), whereas decreased effort-reward imbalance was not (OR = 1.22, 0.91–1.63). There was no association between increased effort-reward imbalance and subsequent sleep disturbances (T2) (OR = 1.00, 0.74–1.37). Results were similar for men and women. Conclusions: Increased effort-reward imbalance was associated with a three-fold higher risk of concomitant onset of sleep disturbances at two-year follow-up, but not subsequent onset of sleep disturbances at four-year follow-up, indicating that changes in effort-reward imbalance have immediate rather than delayed effects on sleep impairment. It is possible that the results from the two-year follow-up were to some extent affected by reverse causality.

Background: The World Health Organization (WHO) and the International Labour Organization (ILO) are developing Joint Estimates of the work-related burden of disease and injury (WHO/ILO Joint Estimates), with contributions from a large network of experts. Evidence from mechanistic data suggests that exposure to long working hours may cause ischaemic heart disease (IHD). In this paper, we present a systematic review and meta-analysis of parameters for estimating the number of deaths and disability-adjusted life years from IHD that are attributable to exposure to long working hours, for the development of the WHO/ILO Joint Estimates. Objectives: We aimed to systematically review and meta-analyse estimates of the effect of exposure to long working hours (three categories: 41–48, 49–54 and ≥55 h/week), compared with exposure to standard working hours (35–40 h/week), on IHD (three outcomes: prevalence, incidence and mortality). Data sources: We developed and published a protocol, applying the Navigation Guide as an organizing systematic review framework where feasible. We searched electronic databases for potentially relevant records from published and unpublished studies, including MEDLINE, Scopus, Web of Science, CISDOC, PsycINFO, and WHO ICTRP. We also searched grey literature databases, Internet search engines and organizational websites; hand-searched reference lists of previous systematic reviews; and consulted additional experts. Study eligibility and criteria: We included working-age (≥15 years) workers in the formal and informal economy in any WHO and/or ILO Member State but excluded children (aged

Background: The World Health Organization (WHO) and the International Labour Organization (ILO) are developing joint estimates of the work-related burden of disease and injury (WHO/ILO Joint Estimates), with contributions from a large network of individual experts. Evidence from mechanistic data and prior studies suggests that exposure to long working hours may cause stroke. In this paper, we present a systematic review and meta-analysis of parameters for estimating the number of deaths and disability-adjusted life years from stroke that are attributable to exposure to long working hours, for the development of the WHO/ILO Joint Estimates. Objectives: We aimed to systematically review and meta-analyse estimates of the effect of exposure to long working hours (three categories: 41–48, 49–54 and ≥55 h/week), compared with exposure to standard working hours (35–40 h/week), on stroke (three outcomes: prevalence, incidence, and mortality). Data sources: A protocol was developed and published, applying the Navigation Guide to systematic reviews as an organizing framework where feasible. We searched electronic databases for potentially relevant records from published and unpublished studies, including Ovid MEDLINE, PubMed, EMBASE, Scopus, Web of Science, CISDOC, PsycINFO, and WHO ICTRP. We also searched grey literature databases, Internet search engines, and organizational websites; hand-searched reference lists of previous systematic reviews; and consulted additional experts. Study eligibility and criteria: We included working-age (≥15 years) individuals in the formal and informal economy in any WHO and/or ILO Member State but excluded children (aged