The role of sociodemographic, psychosocial, and behavioral factors in the use of preventive healthcare services in children and adolescents: results of the KiGGS Wave 2 study.

BACKGROUND: In Germany, various preventive services are offered to children and adolescents. These include regular standardized examinations (so called U/J examinations) and several vaccinations. Although strongly recommended, most of them are not mandatory. Our aim is to identify factors associated with the use of U/J examinations and vaccination against diphtheria, hepatitis B, Hib, pertussis, polio, and tetanus. While previous research has focused on sociodemographic factors, we also include socioeconomic, behavioral, and psychosocial factors. METHODS: We analyzed cross-sectional data from 15,023 participants (aged 0-17 years) of the nationwide representative KiGGS Wave 2 Survey. Participation in U/J examinations was assessed using a questionnaire, filled out by participants and/or their parents. Information on vaccination status was drawn from the participants' vaccination booklets. To identify relevant determinants for the use of preventive examinations and vaccinations, unadjusted and adjusted logistic regression models were employed with up to 16 different independent variables. RESULTS: Various independent variables showed an association with the use of preventive services. Higher socioeconomic status, absence of migration background, and lower household size were associated with significantly higher utilization of U examinations. Parents' marital status, area of residence, behavioral and psychosocial factors yielded insignificant results for most U/J examinations. Higher vaccination rates were found for children with no migration background, with residence in eastern Germany, lower household size, and with married parents. CONCLUSION: This study attempted to depict the influence of sociodemographic, psychosocial, and behavioral factors on the use of several preventive services. Our results indicate that predominantly sociodemographic variables influence the use of preventive services. Further efforts should be made to investigate the interplay of different determinants of healthcare use in children and adolescents.

A longitudinal analysis of health inequalities from adolescence to young adulthood and their underlying causes.

Research suggests that children of low-educated parents face greater health burdens during the passage from adolescence to young adulthood, as they are more likely to become low-educated themselves, establish behavioural and psychosocial disadvantages, or being exposed to unhealthy working conditions. However, studies examining the development and drivers of health inequalities during this particular life stage are limited in number and have produced varied results. This study investigates trajectories of self-rated health and overweight from 14 to 25 years of age, stratified by parental education, and explores the role of potential mediators (educational achievement, health behaviours, psychosocial factors, working conditions). We rely on prospective cohort data from the National Educational Panel Study (NEPS), a representative sample of 14,981 German ninth graders interviewed yearly from 2011 to 2021 (n = 90,096 person-years). First, we estimated random-effects growth curves for self-rated health and overweight over participants' age and calculated the average marginal effect of high versus low parental education. Second, a series of simulation-based mediation analyses were performed to test how much of health inequalities were explained by children's educational attainment (years of school education, years in university), health behaviours (smoking, alcohol, physical inactivity), psychosocial factors (number of grade repetitions, years in unemployment, chronic stress, self-esteem) and working conditions (physical and psychosocial job demands). We accounted for potential confounding by controlling for age, sex, migration background, residential area, household composition, and interview mode. Results show that higher parental education was related to higher self-rated health and lower probabilities of being overweight. Interaction between parental education and age indicated that, after some equalisation in late adolescence, health inequalities increased in young adulthood. Furthermore, educational attainment, health behaviours, psychosocial factors, and early-career working conditions played a significant role in mediating health inequalities. Of the variables examined, the level of school education and years spent in university were particular strong mediating factors. School education accounted for around one-third of the inequalities in self-rated health and one-fifth of the differences in overweight among individuals. Results support the idea that the transition to adulthood is a sensitive period in life and that early socio-economic adversity increases the likelihood to accumulate health disadvantages in multiple dimensions. In Germany, a country with comparatively low educational mobility, intergenerational continuities in class location seem to play a key role in the explanation of health inequalities in youth.

The role of mesolevel characteristics of the health care system and socioeconomic factors on health care use - results of a scoping review.

BACKGROUND: Besides macrolevel characteristics of a health care system, mesolevel access characteristics can exert influence on socioeconomic inequalities in healthcare use. These reflect access to healthcare, which is shaped on a smaller scale than the national level, by the institutions and establishments of a health system that individuals interact with on a regular basis. This scoping review maps the existing evidence about the influence of mesolevel access characteristics and socioeconomic position on healthcare use. Furthermore, it summarizes the evidence on the interaction between mesolevel access characteristics and socioeconomic inequalities in healthcare use. METHODS: We used the databases MEDLINE (PubMed), Web of Science, Scopus, and PsycINFO and followed the 'Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols extension for scoping reviews (PRISMA-ScR)' recommendations. The included quantitative studies used a measure of socioeconomic position, a mesolevel access characteristic, and a measure of individual healthcare utilisation. Studies published between 2000 and 2020 in high income countries were considered. RESULTS: Of the 9501 potentially eligible manuscripts, 158 studies were included after a two-stage screening process. The included studies contained a wide spectrum of outcomes and were thus summarised to the overarching categories: use of preventive services, use of curative services, and potentially avoidable service use. Exemplary outcomes were screening uptake, physician visits and avoidable hospitalisations. Access variables included healthcare system characteristics such as physician density or distance to physician. The effects of socioeconomic position on healthcare use as well as of mesolevel access characteristics were investigated by most studies. The results show that socioeconomic and access factors play a crucial role in healthcare use. However, the interaction between socioeconomic position and mesolevel access characteristics is addressed in only few studies. CONCLUSIONS: Socioeconomic position and mesolevel access characteristics are important when examining variation in healthcare use. Additionally, studies provide initial evidence that moderation effects exist between the two factors, although research on this topic is sparse. Further research is needed to investigate whether adapting access characteristics at the mesolevel can reduce socioeconomic inequity in health care use.

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.

Associations of Migration, Socioeconomic Position and Social Relations With Depressive Symptoms - Analyses of the German National Cohort Baseline Data.

Objectives: We analyze whether the prevalence of depressive symptoms differs among various migrant and non-migrant populations in Germany and to what extent these differences can be attributed to socioeconomic position (SEP) and social relations. Methods: The German National Cohort health study (NAKO) is a prospective multicenter cohort study (N = 204,878). Migration background (assessed based on citizenship and country of birth of both participant and parents) was used as independent variable, age, sex, Social Network Index, the availability of emotional support, SEP (relative income position and educational status) and employment status were introduced as covariates and depressive symptoms (PHQ-9) as dependent variable in logistic regression models. Results: Increased odds ratios of depressive symptoms were found in all migrant subgroups compared to non-migrants and varied regarding regions of origins. Elevated odds ratios decreased when SEP and social relations were included. Attenuations varied across migrant subgroups. Conclusion: The gap in depressive symptoms can partly be attributed to SEP and social relations, with variations between migrant subgroups. The integration paradox is likely to contribute to the explanation of the results. Future studies need to consider heterogeneity among migrant subgroups whenever possible.

[Occupational differences of COVID-19 morbidity and mortality in Germany. An analysis of health insurance data from 3.17 million insured persons]. / Berufsbedingte Unterschiede bei COVID-19-Morbidität und -Mortalität in Deutschland. Eine Analyse von Krankenkassendaten von 3,17 Mio. Versicherten.

INTRODUCTION: During the COVID-19 pandemic, occupation was assumed to play a central role in the occurrence of infection and disease. For Germany, however, there are only a few studies that analyse occupational differences in risk of COVID-19, COVID-19-associated hospitalisation, and mortality. METHODS: The study uses longitudinal health insurance data from the research database of the Institute for Applied Health Research (InGef) with information on 3.17 million insured persons aged 18-67 years (1,488,452 women; 1,684,705 men). Outcomes (morbidity, hospitalisation, and mortality) were determined on the basis of submitted COVID-19 diagnoses between 1 January 2020 and 31 December 2021. Occupations were classified according to four groupings of the official German classification of occupations. In addition to cumulative incidences, relative risks (RR) were calculated - separately for men and women. RESULTS: There is an increased risk of disease in personal service occupations, especially in health care, compared to other occupations (RR for women 1.46; for men 1.30). The same applies to social and cultural service occupations (but only for women) and for manufacturing occupations (only for men). In addition, the risks for hospitalisation and mortality are increased for cleaning occupations and transport and logistics occupations (especially for men). For all three outcomes, the risks are higher in non-managerial occupations and differ by skill level (highest for unskilled jobs and lowest for expert positions). CONCLUSION: The study provides important findings on work- and gender-related differences in COVID-19 morbidity and mortality in Germany, which indicate starting points for structural infection protection measures.

Self-rated health of university students in Germany-The importance of material, psychosocial, and behavioral factors and the parental socio-economic status.

Introduction: Health inequalities start early in life. The time of young adulthood, between late teens and early twenties, is especially interesting in this regard. This time of emerging adulthood, the transition from being a child to becoming an adult, is characterized by the detachment from parents and establishing of an own independent life. From a health inequality perspective, the question about the importance of the socio-economic background of parents is important. University students are an especially interesting group. Many students come from a privileged background and the question of health inequality among university students has not yet been properly studied. Methods: Based on the National Educational Panel Study (NEPS), we analyzed health inequalities among 9,000 students in Germany (∅ 20 years in the first year of their studies) over a period of 8 years. Results: We found that most university students (92%) in Germany reported a good and very good health. Yet, we still found substantial health inequalities. Students whose parents had a higher occupational status reported less health problems. Additionally, we observed that health inequalities had indirect impact on health via health behavior, psychosocial resources, and material conditions. Discussion: We believe our study is an important contribution to the understudied subject of students' health. We see the impact of social inequality on health among such a privileged group like university students as an important sign of the importance of health inequality.

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.

Protagonist der Sozialepidemiologie: Laudatio zu Ehren von PD Dr. PH Thomas Lampert ­ Träger der Salomon-Neumann-Medaille 2022.

The Salomon Neumann Medal of the German Society for Social Medicine and Prevention (DGSMP) honours individuals and institutions who have made special contributions to preventive and social medicine. In 2022, the medal was awarded to PD Dr. Thomas Lampert, Robert Koch Institute, who has been a strong advocate for reporting on health inequalities in Germany for many years. His extensive work provides a precise cartography of the social determinants of health in Germany after the turn of the millennium.

Regional disparities in SARS-CoV-2 infections by labour market indicators: a spatial panel analysis using nationwide German data on notified infections.

BACKGROUND: Regional labour markets and their properties are named as potential reasons for regional variations in levels of SARS-CoV-2 infections rates, but empirical evidence is missing. METHODS: Using nationwide data on notified laboratory-confirmed SARS-CoV-2 infections, we calculated weekly age-standardised incidence rates (ASIRs) for working-age populations at the regional level of Germany's 400 districts. Data covered nearly 2 years (March 2020 till December 2021), including four main waves of the pandemic. For each of the pandemic waves, we investigated regional differences in weekly ASIRs according to three regional labour market indicators: (1) employment rate, (2) employment by sector, and (3) capacity to work from home. We use spatial panel regression analysis, which incorporates geospatial information and accounts for regional clustering of infections. RESULTS: For all four pandemic waves under study, we found that regions with higher proportions of people in employment had higher ASIRs and a steeper increase of infections during the waves. Further, the composition of the workforce mattered: rates were higher in regions with larger secondary sectors or if opportunities of working from home were comparatively low. Associations remained consistent after adjusting for potential confounders, including a proxy measure of regional vaccination progress. CONCLUSIONS: If further validated by studies using individual-level data, our study calls for increased intervention efforts to improve protective measures at the workplace, particularly among workers of the secondary sector with no opportunities to work from home. It also points to the necessity of strengthening work and employment as essential components of pandemic preparedness plans.

School-to-work and school-to-university transition and health inequalities among young adults: a scoping review.

OBJECTIVES: The main objective was to systematically map evidence regarding the emergence of health inequalities in individuals aged 16-24 years during school-to-work and school-to-university transition (STWT). Second, we aimed to summarise the evidence on potential effects of contextual and compositional characteristics of specific institutional contexts entered during STWT on health and health behaviours. DESIGN: Scoping review. STUDY SELECTION: Relevant literature was systematically searched following the methodological framework proposed by Arksey and O'Malley. Ovid MEDLINE and Web of Science, and websites of the International Labour Organization and National Institute for Occupational Safety and Health were searched, using a predetermined search strategy. Articles in English or German published between 1 January 2000 and 3 February 2020 were considered. DATA EXTRACTION: To collect the main information from the selected studies, a data extraction spreadsheet was created. Data were summarised and grouped into five health outcomes and five institutional contexts (school, vocational training, university, work, unemployment). RESULTS: A total of 678 articles were screened for inclusion. To be able to draw a picture of the development of various health outcomes over time, we focused on longitudinal studies. Forty-six prospective studies mapping health-related outcomes during STWT were identified. Higher family socioeconomic position (SEP) was associated with higher levels of health behaviour and lower levels of health-damaging behaviour, but there was also some evidence pointing in the opposite direction. Disadvantaged family SEP negatively impacted on mental health and predicted an adverse weight development. There was limited evidence for the outcomes physical/somatic symptoms and self-rated health. Meso-level characteristics of the institutional contexts identified were not systematically assessed, only individual-level factors resulting from an exposure to these contexts, rendering an analysis of effects of contextual and compositional characteristics on health and health behaviours impossible. CONCLUSIONS: This scoping review demonstrated a wide range of health inequalities during STWT for various health outcomes. However, knowledge on the role of the core institutional contexts regarding the development of health inequalities is limited.

Striving for Health Equity: The Importance of Social Determinants of Health and Ethical Considerations in Pandemic Preparedness Planning.

Since the WHO's "Influenza Pandemic Preparedness Plan" in 1999, pandemic preparedness plans at the international and national level have been constantly adapted with the common goal to respond early to outbreaks, identify risks, and outline promising interventions for pandemic containment. Two years into the COVID-19 pandemic, public health experts have started to reflect on the extent to which previous preparations have been helpful as well as on the gaps in pandemic preparedness planning. In the present commentary, we advocate for the inclusion of social and ethical factors in future pandemic planning-factors that have been insufficiently considered so far, although social determinants of infection risk and infectious disease severity contribute to aggravated social inequalities in health.

Economic change and population health: lessons learnt from an umbrella review on the Great Recession.

OBJECTIVES: Worldwide, the COVID-19 pandemic triggered the sharpest economic downturn since the Great Recession. To prepare for future crises and to preserve public health, we conduct an overview of systematic reviews to examine the evidence on the effect of the Great Recession on population health. METHODS: We searched PubMed and Scopus for systematic reviews and/or meta-analyses focusing specifically on the impact of the Great Recession on population health (eg, mental health). Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines were followed throughout this review and critical appraisal of included systematic reviews was performed using Assessing the Methodological Quality of Systematic Reviews. RESULTS: Twenty-one studies were identified and consistently showed that the Great Recession was most risky to health, the more a country's economy was affected and the longer strict austerity policies were in place. Consequently, a deterioration of health was highest in countries that had implemented strict austerity measures (eg, Greece), but not in countries that rejected austerity measures (eg, Germany). Moreover, the impact of the Great Recession fell disproportionately on the most vulnerable groups such as people in unemployment, at risk of unemployment and those living in poverty. CONCLUSIONS: The experiences of the last economic crisis show that it is possible to limit the consequences for health. Prioritising mental healthcare and prevention, foregoing austerity measures in the healthcare system and protecting vulnerable groups are the most important lessons learnt. Moreover, given the further aggravating social inequalities, a health in all policies approach, based on a comprehensive Health Impact Assessment, is advised.

Increase in Mental Disorders During the COVID-19 Pandemic-The Role of Occupational and Financial Strains.

BACKGROUND: Numerous studies have reported an increase in mental disorders during the COVID-19 pandemic, but the exact reasons for this development are not well understood. In this study we investigate whether pandemic-related occupational and financial changes (e.g., reduced working hours, working from home, financial losses) were associated with increased symptoms of depression and anxiety compared with the situation before the pandemic. METHODS: We analyzed data from the German National Cohort (NAKO) Study. Between May and November 2020, 161 849 study participants answered questions on their mental state and social circumstances. Their responses were compared with data from the baseline survey before the pandemic (2014-2019). Linear fixed-effects models were used to determine whether individual changes in the severity of symptoms of depression (PHQ-9) or anxiety (GAD-7) were associated with occupational/ financial changes (controlling for various covariates). RESULTS: The prevalence of moderate or severe symptoms of depression and anxiety increased by 2.4% and 1.5%, respectively, during the COVID-19 pandemic compared with the preceding years. The mean severity of the symptoms rose slightly. A pronounced increase in symptoms was observed among those who became unemployed during the pandemic (+ 1.16 points on the depression scale, 95% confidence interval [0.91; 1.41], range 0-27). Increases were also seen for reduced working hours with no short-time allowance, increased working hours, working from home, insecurity regarding employment, and financial strain. The deterioration in mental health was largely statistically explained by the occupational and financial changes investigated in the model. CONCLUSION: Depressive symptoms and anxiety disorders increased slightly in the study population during the first year of the COVID-19 pandemic. Occupational and financial difficulties were an essential contributory factor. These strains should be taken into account both in the care of individual patients and in the planning of targeted prevention measures.

Role of contextual and compositional characteristics of schools for health inequalities in childhood and adolescence: a scoping review.

OBJECTIVES: To synthesise the evidence on the role of compositional or contextual characteristics of schools in the association between students' socioeconomic position and their health in primary and secondary education in developed economies. DESIGN: Scoping review. We included studies examining the role of at least one school or class characteristic on students' health inequalities and was published since 1 January 2000, in English or German. We searched PubMed/Medline, Web of Science and Education Resources Information Center. We provided a narrative synthesis and an overview of findings. School characteristics were grouped into five broad categories: school composition, school climate, school policies and organisation, food environment and facilities. RESULTS: Of 8520 records identified, 26 studies were included. Twelve studies found a moderating and 3 a mediating effect. The strongest evidence came from studies examining the moderating effect of school composition, that is, the negative impact of a low individual socioeconomic position on mental health and well-being was aggravated by a low average socioeconomic position of schools. Evidence concerning the role of school climate, school stratification (eg, performance base tracking) and sponsorship, food environment and sport facilities and equipment was generally weak or very weak and mostly based on singular findings. Overall, favourable meso-level characteristics mitigated the negative impact of low individual socioeconomic position on health outcomes. CONCLUSIONS: School characteristics affect health inequalities in children and adolescents to some degree, but future research is necessary to strengthen the existing evidence and address under-represented aspects in school characteristics and health outcomes.

Emerging socio-economic disparities in COVID-19-related deaths during the second pandemic wave in Germany.

Over the course of the second pandemic wave in late 2020, new infections with severe acute respiratory syndrome coronavirus-2 shifted from the most affluent to the most deprived regions of Germany. This study investigated how this trend in infections played out for deaths due to coronavirus disease 2019 (COVID-19) by examining area-level socio-economic disparities in COVID-19-related mortality during the second pandemic wave in Germany. The analysis was based on nationwide data on notified deaths, which were linked to an area-based index of socio-economic deprivation. In the autumn and winter of 2020/2021, COVID-19-related deaths increased faster among residents in Germany's more deprived districts. From late 2020 onwards, the mortality risks of men and women in the most deprived districts were 1.52 (95% confidence interval [CI] 1.27-1.82] and 1.44 (95% CI 1.19-1.73) times higher than among those in the most affluent districts, respectively, after adjustment for age, urbanization and population density. To promote health equity in the pandemic and beyond, deprived populations should receive increased attention in pandemic planning, infection control and disease prevention.

Association between socioeconomic position and cystatin C in the Heinz Nixdorf Recall Study.

Social inequalities in health and disease are well studied. Less information is available on inequalities in biomarker levels indicating subclinical stages of disease such as cystatin C, an early diagnostic marker of renal dysfunction and predictor for cardiovascular disease. We evaluated the relationship between cystatin C, socioeconomic position (SEP) and established cardiovascular risk factors in a population-based study. In 4475 men and women aged 45-75 years participating in the baseline examination of the Heinz Nixdorf Recall Study cystatin C was measured from serum samples with a nephelometric assay. SEP was assessed by education and household income. Linear regression models were used to analyse the association between SEP and cystatin C as well as the impact of cardiovascular risk factors (i.e., body mass index, blood pressure, blood glucose, diabetes mellitus, blood lipids, C-reactive protein, smoking) on this association. After adjustment for age and sex cystatin C decreased by 0.019 mg/l (95% confidence interval (CI) - 0.030 to - 0.008) per five years of education. While using a categorical education variable cystatin C presented 0.039 mg/l (95% CI 0.017-0.061) higher in men and women in the lowest educational category (≤ 10 years of education) compared to the highest category (≥ 18 years). Concerning income, cystatin C decreased by 0.014 mg/l (95% CI - 0.021 to - 0.006) per 1000 € after adjustment for age and sex. For men and women in the lowest income quartile cystatin C was 0.024 mg/l (95% CI 0.009-0.038) higher compared to the highest income quartile. After adjusting for established cardiovascular risk factors the observed associations were substantially diminished. Social inequalities seem to play a role in subclinical stages of renal dysfunction, which are also related to development of cardiovascular disease. Adjustment for traditional cardiovascular risk factors showed that these risk factors largely explain the association between SEP and cystatin C.

Health Inequalities in Children and Adolescents: A Scoping Review of the Mediating and Moderating Effects of Family Characteristics.

This scoping review systematically mapped evidence of the mediating and moderating effects of family characteristics on health inequalities in school-aged children and adolescents (6-18 years) in countries with developed economies in Europe and North America. We conducted a systematic scoping review following the PRISMA extension for Scoping Reviews recommendations. We searched the PubMed, PsycINFO and Scopus databases. Two reviewers independently screened titles, abstracts and full texts. Evidence was synthesized narratively. Of the 12,403 records initially identified, 50 articles were included in the synthesis. The included studies were conducted in the United States (n = 27), Europe (n = 18), Canada (n = 3), or in multiple countries combined (n = 2). We found that mental health was the most frequently assessed health outcome. The included studies reported that different family characteristics mediated or moderated health inequalities. Parental mental health, parenting practices, and parent-child-relationships were most frequently examined, and were found to be important mediating or moderating factors. In addition, family conflict and distress were relevant family characteristics. Future research should integrate additional health outcomes besides mental health, and attempt to integrate the complexity of families. The family characteristics identified in this review represent potential starting points for reducing health inequalities in childhood and adolescence.

A genetic sum score of effect alleles associated with serum lipid concentrations interacts with educational attainment.

High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and total cholesterol (TC) levels are influenced by both genes and the environment. The aim was to investigate whether education and income as indicators of socioeconomic position (SEP) interact with lipid-increasing genetic effect allele scores (GES) in a population-based cohort. Using baseline data of 4516 study participants, age- and sex-adjusted linear regression models were fitted to investigate associations between GES and lipids stratified by SEP as well as including GES×SEP interaction terms. In the highest education group compared to the lowest stronger effects per GES standard deviation were observed for HDL-C (2.96 mg/dl [95%-CI: 2.19, 3.83] vs. 2.45 mg/dl [95%-CI: 1.12, 3.72]), LDL-C (6.57 mg/dl [95%-CI: 4.73, 8.37] vs. 2.66 mg/dl [95%-CI: -0.50, 5.76]) and TC (8.06 mg/dl [95%-CI: 6.14, 9.98] vs. 4.37 mg/dl [95%-CI: 0.94, 7.80]). Using the highest education group as reference, interaction terms showed indication of GES by low education interaction for LDL-C (ßGES×Education: -3.87; 95%-CI: -7.47, -0.32), which was slightly attenuated after controlling for GESLDL-C×Diabetes interaction (ßGES×Education: -3.42; 95%-CI: -6.98, 0.18). The present study showed stronger genetic effects on LDL-C in higher SEP groups and gave indication for a GESLDL-C×Education interaction, demonstrating the relevance of SEP for the expression of genetic health risks.

Socioeconomic position is associated with N-terminal pro-brain natriuretic peptide (NT-proBNP)-Results of the population-based Heinz Nixdorf Recall study.

OBJECTIVES: N-Terminal pro Brain Natriuretic Peptide (NT-proBNP) is a diagnostic marker for heart failure and a prognostic factor for cardiovascular disease (CVD). The aim of this study was to examine the association of socioeconomic position (SEP) with NT-proBNP while assessing sex-differences and the impact of CVD risk factors and prevalent CVD on the association. METHODS: Baseline data of 4598 participants aged 45-75 years of the Heinz Nixdorf Recall Study were used. Income and education were used as SEP indicators. Age- and sex-adjusted linear regression models were fitted to calculate effect size estimates and 95% confidence intervals (95%-CIs) for the total effect of SEP indicators on NT-proBNP, while potential mediation was assessed by additionally accounting for traditional CVD risk factors (i.e., systolic blood pressure, HDL cholesterol, LDL cholesterol, diabetes, anti-hypertensive medication, lipid-lowering medication, BMI, current smoking). Education and income were included separately in the models. RESULTS: With an age- and sex-adjusted average change in NT-proBNP of -6.47% (95%-CI: -9.91; -2.91) per 1000€, the association between income and NT-proBNP was more pronounced compared to using education as a SEP indicator (-0.80% [95%-CI: -1.92; 0.32] per year of education). Sex-stratified results indicated stronger associations in men (-8.43% [95%-CI: -13.21; -3.38] per 1000€; -1.63% [95%-CI: -3.23; -0.001] per year of education) compared to women (-5.10% [95%-CI: -9.82; -0.01] per 1000€; -1.04% [95%-CI: -2.59; 0.50] per year of education). After adjusting for CVD risk factors some of the observed effect size estimates were attenuated, while the overall association between SEP indicators and NT-proBNP was still indicated. The exclusion of participants with prevalent coronary heart disease or stroke did not lead to a substantial change in the observed associations. CONCLUSIONS: In the present study associations of education and income with NT-proBNP were observed in a population-based study sample. Only parts of the association were explained by traditional CVD risk factors, while there were substantial sex-differences in the strength of the observed association. Overt coronary heart disease or stroke did not seem to trigger the associations.