Health inequalities among young workers: the mediating role of working conditions and company characteristics.

OBJECTIVE: Few studies have investigated health inequalities among young workers. The objectives of this study are to assess the extent of health inequalities in a sample of job starters and to explore the contribution of job demands and organisational factors. METHODS: We analyze data from the BIBB/BAuA Youth Employment Survey 2012. The cross-sectional survey includes a representative sample of 3214 German employees, apprentices, and trainees aged 15-24 years. Individuals were grouped by their years of schooling into low (< 12 years) and high levels of education (≥ 12 years). Regression analysis estimated the link between education and four health outcomes: self-rated health, number of health events, musculoskeletal symptoms, and mental health problems over the last 12 months. Counterfactual mediation analysis tested for indirect effects of education via working conditions (i.e., physical and psychosocial job demands) and company characteristics (i.e., company size, health prevention measures, financial situation, downsizing). All analyses were adjusted for age, sex, nationality, region, working hours, job tenure, employment relationship, and economic sector. RESULTS: Highly educated workers reported better self-rated health (b = 0.24, 95% CI 0.18-0.31) and lower numbers of health events (Rate Ratio (RR) = 0.74, 95% CI 0.67-0.82), musculoskeletal symptoms (RR = 0.73, 95% CI 0.66-0.80) and mental health problems (RR = 0.84, 95% CI 0.76-0.93). Total job demands explained between 21.6% and 87.2% of the educational differences (depending on health outcome). Unfavourable company characteristics were associated with worse health, but showed no or only small mediation effects. CONCLUSIONS: Health inequalities are already present at the early working career due to socio-economically stratified working hazards. To enhance prevention measures that aim at reducing inequalities in workplace health, we propose shifting attention towards earlier stages of life.

Child health and development in the course of the COVID-19 pandemic: are there social inequalities?

COVID-19 pandemic lockdowns and closures have influenced all children's health and development (HAD). We aimed to examine whether this differs by social circumstances. We hypothesised that socially disadvantaged children experienced more pronounced deterioration in their HAD compared with better-off children. In our trend study, we included five cohorts of school enrolment medical screening (school entrance 2018-2022) in the city of Dusseldorf, Germany. To compensate for selection bias due to the limited number of examinations in pandemic months, we chose the first 800 examinations of each cohort. We computed predicted prevalences of overweight, coordination and language problems as indicators of HAD. Neighbourhood deprivation, single-parent families and non-German nationality were used as indicators of social disadvantage. All groups of children experienced a deterioration in their HAD. Its magnitude is comparable between children with different social circumstances. For instance, between 2018 and 2021, prevalence of overweight increased from 19.2 to 24.2% in children from deprived neighbourhoods, and from 8.1 to 16.5% in children from well-off neighbourhoods. Prevalence of language problems (prepositions) increased from 49.9 to 72.1% among non-German children, and from 14.4 to 39.1% among German children.   Conclusion: Results only partly confirmed our hypothesis. However, since the pre-pandemic prevalences of HAD problems among disadvantaged children were already higher, further deterioration - regardless of its magnitude - has led to their particularly poor situation. For those children, overweight and language development should be priorities of prevention. Generally, important settings for child HAD such as kindergartens or leisure facilities should remain open in future pandemics. What is known: • The COVID-19 pandemic has had a negative impact on general child health and development. • Before the pandemic, social inequalities in child health and development were a common phenomenon. What is new: • Children in all social groups experienced a deterioration in their health and development over the course of the pandemic. • Over the course of the pandemic, children from deprived neighbourhoods have demonstrated a particularly high prevalence of overweight. Language problems are particularly prevalent among non-German children.

Changes in work-related stressors before and during the COVID-19 pandemic: differences by gender and parental status.

PURPOSE: The COVID-19 pandemic changed people's working conditions worldwide and research suggests increases in work stressors. However, it is not known to what extent these changes differ by gender or parental status. In the present study, we investigate trends in work stressors and whether these differ by gender and parental status. METHODS: We used cross-sectional time series data of the European Working Conditions Survey of 2015 and Living, Working and COVID-19 survey of spring 2020 to examine trends in work stressors by gender and parental status. Work stressors were working in leisure time, lack of psychological detachment and work-life conflict. We applied three-way multilevel regressions reporting prevalence ratios and reported predicted probabilities and average marginal effects to show trends and differences in changes in work stressors. RESULTS: Our multilevel regression results showed elevated prevalence ratios during the pandemic for working leisure time (PR: 1.43, 95% CI 1.34-1.53), psychological detachment (PR: 1.70, 95% CI 1.45-1.99) and work-life conflict (PR: 1.29, 95% CI 1.17-1.43) compared to before the pandemic. Except for working in leisure time, the increase was more significant among women and mothers. The proportion of work-life conflict in 2020 was 20.7% (95% CI 18.7-22.9) for men and 25.8% (95% CI 24.0-27.6) for women, equalling a difference of 5.1% (p < 0.001). CONCLUSIONS: There is evidence that work stressors increased disproportionately for women and mothers. This needs to be monitored and addressed to prevent widening gender inequalities in the quality of work.

Authors' response: Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias.

We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first pandemic wave in Germany (1). The authors address the potential for bias resulting from differential testing between occupational groups and propose an alternative analytical strategy for dealing with selective testing. In the following, we want to discuss two aspects of this issue, namely (i) the extent and reasons of differential testing in our cohort and (ii) the advantages and disadvantages of different analytical approaches to study risk factors for SARS-CoV-2 infection. Our study relied on nationwide prospective cohort data including more than 100 000 workers in order to compare the incidence of infections between different occupations and occupational status positions. We found elevated infection risks in personal services and business administration, in essential occupations (including health care) and among people in higher occupational status positions (ie, managers and highly skilled workers) during the first pandemic wave in Germany (2). Van Tongeren's et al main concern is that the correlations found could be affected by a systematic bias because people in healthcare professions get tested more often than employees in other professions. A second argument is that better-off people could be more likely to use testing as they are less affected by direct costs (prices for testing) and the economic hardship associated with a positive test result (eg, loss of earnings in the event of sick leave). We share the authors' view that differential testing must be considered when analysing and interpreting the data. Thus, in our study, we examined the proportion of tests conducted in each occupational group as part of the sensitivity analyses (see supplementary figure S1, accessible at www.sjweh.fi/article/4037). As expected, testing proportions were exceptionally high in medical occupations (due to employer requirements). However, we did not observe systematic differences among non-medical occupations or when categorising by skill-level or managerial responsibility. This might be explained by several reasons. First, SARS-CoV-2 testing was free of charge during the first pandemic wave in Germany, but reporting a risk contact or having symptoms was a necessary condition for testing ( https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed 5 September 2022). The newspaper article cited by van Tongeren et al is misleading as it refers to a calendar date after our study period. Second, different motivation for testing due to economic hardship in case of a positive test result is an unlikely explanation, because Germany has a universal healthcare system, including paid sick leave and sickness benefits for all workers (3). Self-employed people carry greater financial risks in case of sickness. We therefore included self-employment in the multivariable analyses to address this potential source of bias. While the observed inverse social gradient may be surprising, it actually matches with findings of ecological studies from Germany (4, 5), the United States (6, 7) as well as Spain, Portugal, Sweden, The Netherlands, Israel, and Hong Kong (8), all of which observed higher infection rates in wealthier neighbourhoods during the initial outbreak phase of the pandemic. One possible explanation is the higher mobility of managers and better educated workers, who are more likely to participate in meetings and engage in business travel and holiday trips like skiing. Given the increasing number of studies providing evidence for this hypothesis, we conclude that the inverse social gradient in our study likely reflects different exposure probabilities and is not a result of systematic bias. This also holds true for the elevated infection risks in essential workers, which is actually corroborated by a large body of research (9-11). Regarding differential likelihood of testing, van Tongeren et al state that "[i]t is relatively simple to address this problem by using a test-negative design" (1). As van Tongeren et al describe, this is a case-control approach only including individuals who were tested (without considering those who were not tested). However, the proposed analytical strategy can lead to another (more serious) selection bias if testing proportions and/or testing criteria differ between groups (12). This can be easily illustrated when comparing the results based on a time-incidence design with those obtained by a test-negative design as shown in table 1 (see PDF). Both approaches show similar results in terms of vertical occupational differences. Infection was more common if individuals had a high skill level or had a managerial position, but associations were stronger in the time-incidence design and did not reach statistical significance in the test-negative design (as indicated by the confidence intervals overlapping "1"). Unfortunately, the test-negative approach relies on a strongly reduced sample size and thus results in greater statistical uncertainty and loss of statistical power (13). In contrast, the test-negative design yields a different picture when estimating the association between essential occupation and infection risk: In this analysis, essential workers did not differ from non-essential workers in their chance of being infected with SARS-CoV-2 (the test-negative design even exhibits a lower chance for essential workers). This is rather counter-intuitive and is not in accordance with what we know about the occupational hazards of healthcare workers during the pandemic (14). The main problem is that proportions of positive tests are highly unreliable when testing proportions and/or testing criteria differ between groups. As essential workers were tested more often without being symptomatic (due to employer requirements), a lower proportion of positive tests in this group does not necessarily correspond to a lower risk of infection. Consequently, we are not convinced that the test-negative design should be the 'gold standard' for studying risk factors for SARS-CoV-2 infections (15). Especially problematic is the loss of statistical power (increasing the probability of a type II error) and the low validity of the test-positivity when test criteria and/or test proportions differ between groups. References 1. 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(7):586-587. https://doi.org/10.5271/sjweh.4052. 2. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health 2022;48:446-56. https://doi.org/10.5271/sjweh.4037. 3. Busse R, Blümel M, Knieps F, Bärnighausen T. Statutory health insurance in Germany: a health system shaped by 135 years of solidarity, self-governance, and competition. Lancet 2017;390:882-97. https://doi.org/10.1016/S0140-6736(17)31280-1. 4. Wachtler B, Michalski N, Nowossadeck E, Diercke M, Wahrendorf M, Santos-Hövener C, et al. Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany. J Heal Monit 2020;5:18-29. https://doi.org/10.25646/7057. 5. Plümper T, Neumayer E. The pandemic predominantly hits poor neighbourhoods? SARS-CoV-2 infections and COVID-19 fatalities in German districts. Eur J Public Health 2020;30:1176-80. https://doi.org/10.1093/eurpub/ckaa168. 6. Abedi V, Olulana O, Avula V, Chaudhary D, Khan A, Shahjouei S, et al. Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. J Racial Ethn Heal Disparities 2021;8:732-42. https://doi.org/10.1007/s40615-020-00833-4. 7. Mukherji N. The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase. Rev Reg Stud 2022;52. https://doi.org/10.52324/001c.35255. 8. Beese F, Waldhauer J, Wollgast L, Pförtner T, Wahrendorf M, Haller S, et al. Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review. Int J Public Health 2022;67:1-14. https://doi.org/10.3389/ijph.2022.1605128. 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo C-G, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Heal 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X. 10. Chou R, Dana T, Buckley DI, Selph S, Fu R, Totten AM. Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers. Ann Intern Med 2020;173:120-36. https://doi.org/10.7326/M20-1632. 11. Stringhini S, Zaballa M-E, Pullen N, de Mestral C, Perez-Saez J, Dumont R, et al. Large variation in anti-SARS-CoV-2 antibody prevalence among essential workers in Geneva, Switzerland. Nat Commun 2021;12:3455. https://doi.org/10.1038/s41467-021-23796-4. 12. Accorsi EK, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, et al. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. Eur J Epidemiol 2021;36:179-96. https://doi.org/10.1007/s10654-021-00727-7. 13. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Editio. New York: Routledge; 2013. https://doi.org/10.4324/9780203771587. 14. The Lancet. The plight of essential workers during the COVID-19 pandemic. Lancet 2020;395:1587. https://doi.org/10.1016/S0140-6736(20)31200-9. 15. 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:e7-8. https://doi.org/10.1097/EDE.0000000000001438.

Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany.

OBJECTIVE: The aim of this study was to identify the occupational risk for a SARS-CoV-2 infection in a nationwide sample of German workers during the first wave of the COVID-19 pandemic (1 February-31 August 2020). METHODS: We used the data of 108 960 workers who participated in a COVID follow-up survey of the German National Cohort (NAKO). Occupational characteristics were derived from the German Classification of Occupations 2010 (Klassifikation der Berufe 2010). PCR-confirmed SARS-CoV-2 infections were assessed from self-reports. Incidence rates (IR) and incidence rate ratios (IRR) were estimated using robust Poisson regression, adjusted for person-time at risk, age, sex, migration background, study center, working hours, and employment relationship. RESULTS: The IR was 3.7 infections per 1000 workers [95% confidence interval (CI) 3.3-4.1]. IR differed by occupational sector, with the highest rates observed in personal (IR 4.8, 95% CI 4.0-5.6) and business administration (IR 3.4, 95% CI 2.8-3.9) services and the lowest rates in occupations related to the production of goods (IR 2.0, 95% CI 1.5-2.6). Infections were more frequent among essential workers compared with workers in non-essential occupations (IRR 1.95, 95% CI 1.59-2.40) and among highly skilled compared with skilled professions (IRR 1.36, 95% CI 1.07-1.72). CONCLUSIONS: The results emphasize higher infection risks in essential occupations and personal-related services, especially in the healthcare sector. Additionally, we found evidence that infections were more common in higher occupational status positions at the beginning of the pandemic.

Long-term trends in psychosocial working conditions in Europe-the role of labor market policies.

BACKGROUND: Employees have witnessed rising trend in work stress over the last few decades. However, we know a little about country differences in those trends. Our article fills this gap in the literature by examining heterogeneities in trends in working conditions by country groups defined by their amount of investment into labor market policy (LMP) programs. Additionally, we provide findings on differences in occupational inequalities between country groups. METHODS: We use comparative longitudinal data of the European Working Conditions Surveys including cross-sectional information on employees from 15 countries surveyed in Waves 1995, 2000, 2005, 2010 and 2015. Estimation results are provided by three-way multilevel models with employees nested within country-years nested within countries. Our work stress measure is the proxy version of job strain based on the demand-control model. RESULTS: Our regression results indicate that for employees in countries with the least LMP spending job strain increased by 10% from 1995 to 2015 compared to a smaller and insignificant change in middle- and high-LMP countries. In low-LMP countries, inequalities in job strain also widened during the studied period: the gap in job strain between the highest- and lowest-skilled increased by 60% from 1995 to 2015. This contrasts a stable gap in middle- and high-LMP countries. CONCLUSIONS: Our results direct the attention to the vulnerable position of the least skilled and highlight that LMP investments may buffer some of the adverse impacts of globalization and technological changes and effectively improve the labor market situation of the least skilled.

Job satisfaction at older ages : A comparative analysis of Hungarian and German data.

BACKGROUND: As a response to population aging, reforms to increase the statutory retirement age and closing options for early retirement have been introduced in many European countries. This study analyzed the job satisfaction of employees in two countries with markedly different speeds of pension reforms. The German reform started in 1992 and abolished almost all options of early retirement. The Hungarian reforms started later and were completed only by 2011. Therefore, it is expected that older Hungarian workers were initially more satisfied with their jobs than similarly aged German workers. OBJECTIVE: The hypothesis was tested that older workers in a regulatory environment with accessible pathways to early retirement are on average relatively more satisfied with their job than older workers in a country with few and financially less advantageous options for early retirement. MATERIAL AND METHODS: This study used data from the European Working Conditions Surveys. Waves 2005 and 2010 represent years when early retirement pathways were abolished in Germany, while the Hungarian system offered a variety of pathways for early retirement. This is not the case in 2015 having tight regulations in both countries. Logit regressions were estimated using job satisfaction as an dependent variable and a variety of control variables were introduced step by step. RESULTS: The results from 2005 and 2010 indicate that older Hungarian employees are relatively more content with their job than similarly aged German workers. In 2015 this trend was reversed. CONCLUSION: It would be crucial to provide the opportunity and appropriate working conditions for older employees to work if they voluntarily opt for working longer. They seem to be an especially motivated pool of employees, and could productively contribute to decreasing the financial burdens caused by the demographic changes.