Coping with COVID: risk and resilience factors for mental health in a German representative panel study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic might affect mental health. Data from population-representative panel surveys with multiple waves including pre-COVID data investigating risk and protective factors are still rare. METHODS: In a stratified random sample of the German household population (n = 6684), we conducted survey-weighted multiple linear regressions to determine the association of various psychological risk and protective factors assessed between 2015 and 2020 with changes in psychological distress [(PD; measured via Patient Health Questionnaire for Depression and Anxiety (PHQ-4)] from pre-pandemic (average of 2016 and 2019) to peri-pandemic (both 2020 and 2021) time points. Control analyses on PD change between two pre-pandemic time points (2016 and 2019) were conducted. Regularized regressions were computed to inform on which factors were statistically most influential in the multicollinear setting. RESULTS: PHQ-4 scores in 2020 (M = 2.45) and 2021 (M = 2.21) were elevated compared to 2019 (M = 1.79). Several risk factors (catastrophizing, neuroticism, and asking for instrumental support) and protective factors (perceived stress recovery, positive reappraisal, and optimism) were identified for the peri-pandemic outcomes. Control analyses revealed that in pre-pandemic times, neuroticism and optimism were predominantly related to PD changes. Regularized regression mostly confirmed the results and highlighted perceived stress recovery as most consistent influential protective factor across peri-pandemic outcomes. CONCLUSIONS: We identified several psychological risk and protective factors related to PD outcomes during the COVID-19 pandemic. A comparison of pre-pandemic data stresses the relevance of longitudinal assessments to potentially reconcile contradictory findings. Implications and suggestions for targeted prevention and intervention programs during highly stressful times such as pandemics are discussed.

How Migration Status Shapes Susceptibility of Individuals' Loneliness to Social Isolation.

Objectives: Our research provides competing hypotheses and empirical evidence how associations between objectively social isolation and subjective loneliness differ between host populations, migrants, and refugees. Methods: The analysis uses data of 25,171 participants from a random sample of the German population (SOEP v.35). We estimate regression models for the host population, migrants, and refugees and test five hypotheses on the association between social isolation and loneliness using a Bayesian approach in a multiverse framework. Results: We find the strongest relative support for an increased need for social inclusion among refugees, indicated by a higher Bayes factor compared to the hosts and migrants. However, all theoretically developed hypotheses perform poorly in explaining the major pattern in our data: The association of social isolation and loneliness is persistently lower for migrants (0.15 SD-0.29 SD), with similar sizes of associations for refugees and the host population (0.38 SD-0.67 SD). Conclusion: The migration history must be actively considered in health service provision and support programs to better cater to the needs of the different groups.

The effect of exposure to long working hours on alcohol consumption, risky drinking and alcohol use disorder: A systematic review and meta-analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury.

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 (<15 years) and unpaid domestic workers. We considered for inclusion randomized controlled trials, cohort studies, case-control studies and other non-randomized intervention studies with an estimate of the effect of exposure to long working hours (41-48, 49-54 and ≥55 h/week), compared with exposure to standard working hours (35-40 h/week), on alcohol consumption (in g/week), risky drinking, and alcohol use disorder (prevalence, incidence or mortality). STUDY APPRAISAL AND SYNTHESIS METHODS: At least two review authors independently screened titles and abstracts against the eligibility criteria at a first stage and full texts of potentially eligible records at a second stage, followed by extraction of data from publications related to qualifying studies. Two or more review authors assessed the risk of bias, quality of evidence and strength of evidence, using Navigation Guide and GRADE tools and approaches adapted to this project. RESULTS: Fourteen cohort studies met the inclusion criteria, comprising a total of 104,599 participants (52,107 females) in six countries of three WHO regions (Americas, South-East Asia, and Europe). The exposure and outcome were assessed with self-reported measures in most studies. Across included studies, risk of bias was generally probably high, with risk judged high or probably high for detection bias and missing data for alcohol consumption and risky drinking. Compared to working 35-40 h/week, exposure to working 41-48 h/week increased alcohol consumption by 10.4 g/week (95% confidence interval (CI) 5.59-15.20; seven studies; 25,904 participants, I2 71%, low quality evidence). Exposure to working 49-54 h/week increased alcohol consumption by 17.69 g/week (95% confidence interval (CI) 9.16-26.22; seven studies, 19,158 participants, I2 82%, low quality evidence). Exposure to working ≥55 h/week increased alcohol consumption by 16.29 g/week (95% confidence interval (CI) 7.93-24.65; seven studies; 19,692 participants; I2 82%, low quality evidence). We are uncertain about the effect of exposure to working 41-48 h/week, compared with working 35-40 h/week on developing risky drinking (relative risk 1.08; 95% CI 0.86-1.36; 12 studies; I2 52%, low certainty evidence). Working 49-54 h/week did not increase the risk of developing risky drinking (relative risk 1.12; 95% CI 0.90-1.39; 12 studies; 3832 participants; I2 24%, moderate certainty evidence), nor working ≥55 h/week (relative risk 1.11; 95% CI 0.95-1.30; 12 studies; 4525 participants; I2 0%, moderate certainty evidence). Subgroup analyses indicated that age may influence the association between long working hours and both alcohol consumption and risky drinking. We did not identify studies for which we had access to results on alcohol use disorder. CONCLUSIONS: Overall, for alcohol consumption in g/week and for risky drinking, we judged this body of evidence to be of low certainty. Exposure to long working hours may have increased alcohol consumption, but we are uncertain about the effect on risky drinking. We found no eligible studies on the effect on alcohol use disorder. Producing estimates for the burden of alcohol use disorder attributable to exposure to long working hours appears to not be evidence-based at this time. PROTOCOL IDENTIFIER: https://doi.org/10.1016/j.envint.2018.07.025. PROSPERO REGISTRATION NUMBER: CRD42018084077.

Education differences in women's body weight trajectories: The role of motherhood.

Studies have found that education differences in women's body weight increase until middle adulthood. The explanatory mechanisms behind this increase are not well-understood. This study examined the role of education differences in the prevalence of motherhood as a risk factor for weight gain and in vulnerability to its effects on weight gain. We used longitudinal data from the German Socio-economic Panel Study. Our sample included 2,668 women aged between 17 and 45 and observed at least twice between 2002 and 2016 (n = 13,899 panel observations). We used OLS regression models to estimate initial education differences in body weight and fixed-effects panel regression models to estimate education differences in body-weight trajectories. Motherhood was associated with increasing body weight, and the effects of motherhood on weight gain varied by education. Motherhood partially accounted for the increase of education differences during reproductive age. Until the age of 30, differences in the prevalence of motherhood accounted for about 20% of the bodyweight gap between lower and higher educated women. From age 35 until 45, differential vulnerability to the effects of motherhood on body weight explained about 15% of the education gap in body weight.

Psychological distress among refugees in Germany: a cross-sectional analysis of individual and contextual risk factors and potential consequences for integration using a nationally representative survey.

OBJECTIVES: Responding to the mental health needs of refugees remains a pressing challenge worldwide. We estimated the prevalence of psychological distress in a large refugee population in Germany and assessed its association with host country factors amenable to policy intervention and integration indicators. DESIGN: A cross-sectional and population-based secondary analysis of the 2017 wave of the IAB-BAMF-SOEP refugee survey. SETTING: Germany. PARTICIPANTS: 2639 adult refugees who arrived in Germany between 2013 and 2016. MAIN OUTCOME MEASURES: Psychological distress involving symptoms of depression, anxiety and post-traumatic stress disorder was measured using the Refugee Health Screener-13. RESULTS: Almost half of the population surveyed (41.2% (95% CI: 37.9% to 44.6%)) was affected by mild, moderate or severe levels of psychological distress. 10.9% (8.4% to 13.5%) of the population screened positive for severe distress indicative of an urgent need for care. Prevalence of distress was particularly high for females (53.0% (47.2% to 58.8%)), older refugees (aged ≥55, 70.4% (58.5% to 82.2%)) and Afghans (61.5% (53.5% to 69.5%)). Individuals under threat of deportation were at a greater risk of distress than protection status holder (risk ratio: 1.55 (95% CI: 1.14 to 2.10)), single males at a greater risk than males with nuclear families living in Germany (1.34 (1.04 to 1.74)) and those in refugee housing facilities at a greater risk than those in private housing (1.21 (1.02 to 1.43)). Distressed males had a lower likelihood of employment (0.67 (0.52 to 0.86)) and reduced participation in integration courses (0.90 (0.81 to 0.99)). A trend of reduced participation in educational programmes was observed in affected females (0.42 (0.17 to 1.01)). CONCLUSION: The finding that a substantial minority of refugees in Germany exhibits symptoms of distress calls for an expansion of mental health services for this population. Service providers and policy-makers should consider the increased prevalence among female, older and Afghan refugees, as well as among single males, residents in housing facilities and those under threat of deportation. The associations between mental health and integration processes such as labour market, educational programme and integration course participation also warrant consideration.

A cross-cultural comparison of the ultrabrief mental health screeners PHQ-4 and SF-12 in Germany.

The testing of measurement invariance (MI) across different cultural backgrounds for short screeners of mental health has been mostly neglected. Therefore, we examined MI in the most common mental health screeners worldwide used to assess the psychological indicators of health among migrants and refugees: the Short-Form-12 Health Survey (SF-12) for health-related quality of life and the Patient Health Questionnaire-4 (PHQ-4) for mental distress. Three different types of representative samples in the German Socio-Economic Panel were analyzed: host population n = 19,685; migrants n = 4,966; and refugees n = 4,123. All samples were tested for each mental health screener in 1 model using a multigroup confirmatory factor analysis. Scalar MI was tested (a) between men and women, (b) between groups stratified by migration status, (c) between survey languages, (d) between country of origin, (e) between sex and country of origin, and finally (f) between age groups. Overall, we were able to demonstrate scalar MI for all 5 models, except for SF-12 regarding age groups. Thus, scores ascertained with the PHQ-4 and SF-12 can be compared between conventional migrants, refugees, and the host population in Germany in a statistically meaningful way. Substantively, female refugees turned out to be the most vulnerable group in terms of mental health and health-related quality of life. The current study is the first to evaluate MI of mental health screeners using a large-scale representative sample including refugees, migrants, and the host population. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Dimensions of Social Stratification and Their Relation to Mortality: A Comparison Across Gender and Life Course Periods in Finland.

Differences in mortality between groups with different socioeconomic positions (SEP) are well-established, but the relative contribution of different SEP measures is unclear. This study compares the correlation between three SEP dimensions and mortality, and investigates differences between gender and age groups (35-59 vs. 60-84). We use an 11% random sample with an 80% oversample of deaths from the Finnish population with information on education, occupational class, individual income, and mortality (n = 496,658; 274,316 deaths between 1995 and 2007). We estimate bivariate and multivariate Cox proportional hazard models and population attributable fractions. The total effects of education are substantially mediated by occupation and income, and the effects of occupation is mediated by income. All dimensions have their own net effect on mortality, but income shows the steepest mortality gradient (HR 1.78, lowest vs. highest quintile). Income is more important for men and occupational class more important among elderly women. Mortality inequalities are generally smaller in older ages, but the relative importance of income increases. In health inequality studies, the use of only one SEP indicator functions well as a broad marker of SEP. However, only analyses of multiple dimensions allow insights into social mechanisms and how they differ between population subgroups.

The reciprocal relationship between material factors and health in the life course: evidence from SHARE and ELSA.

The widely established health differences between people with greater economic resources and those with fewer resources can be attributed to both social causation (material factors affecting health) and health selection (health affecting material wealth). Each of these pathways may have different intensities at different ages, because the sensitivity of health to a lack of material wealth and the degree to which health can influence economic resources may change. We study the relative importance, in terms of explanatory power, of social causation and health selection, comparing the transitions from childhood to adulthood and from adulthood to old age. We use retrospective survey data from ten European countries from the Survey of Health, Ageing and Retirement in Europe (SHARELIFE, n = 18,734) and the English Longitudinal Study of Ageing (ELSA, n = 6117), and structural equations models in a cross-lagged panel design. Material wealth and health depend on their prior status, wealth more so than health. In the transition from childhood to adulthood, social causation and health selection are equally important: the standardized coefficients for men in SHARE are 0.07 and 0.06, respectively, i.e. one standard deviation increase in material wealth in childhood is associated with a 0.07 standard deviation increase in adult health. In the transition from adulthood to old age, social causation is more important than health selection (0.52 vs. 0.01), across gender and data sets. Both pathways contribute to the creation of health inequalities-however, their relative importance changes with age, which is important for understanding how health inequalities develop and how policies can address them.

Comparing Observed and Unobserved Components of Childhood: Evidence From Finnish Register Data on Midlife Mortality From Siblings and Their Parents.

In this study, we argue that the long arm of childhood that determines adult mortality should be thought of as comprising an observed part and its unobserved counterpart, reflecting the observed socioeconomic position of individuals and their parents and unobserved factors shared within a family. Our estimates of the observed and unobserved parts of the long arm of childhood are based on family-level variance in a survival analytic regression model, using siblings nested within families as the units of analysis. The study uses a sample of Finnish siblings born between 1936 and 1950 obtained from Finnish census data. Individuals are followed from ages 35 to 72. To explain familial influence on mortality, we use demographic background factors, the socioeconomic position of the parents, and the individuals' own socioeconomic position at age 35 as predictors of all-cause and cause-specific mortality. The observed part-demographic and socioeconomic factors, including region; number of siblings; native language; parents' education and occupation; and individuals' income, occupation, tenancy status, and education-accounts for between 10 % and 25 % of the total familial influence on mortality. The larger part of the influence of the family on mortality is not explained by observed individual and parental socioeconomic position or demographic background and thus remains an unobserved component of the arm of childhood. This component highlights the need to investigate the influence of childhood circumstances on adult mortality in a comprehensive framework, including demographic, social, behavioral, and genetic information from the family of origin.

The stratifying role of job level for sickness absence and the moderating role of gender and occupational gender composition.

The study investigates whether sickness absence is stratified by job level - understood as the authority and autonomy a worker holds - beyond the association with education, income, and occupation. A second objective is to establish the moderating role of gender and occupational gender composition on this stratification of sickness absence. Four competing hypotheses are developed that predict different patterns of moderation. Associations between job level and sickness absence are estimated for men and women in three groups of differing occupational gender composition, using data from the German Socio-Economic Panel Study (SOEP). For the purpose of moderation analysis, this study employs a new method based on Bayesian statistics, which enables the testing of complex moderation hypotheses. The data support the hypothesis that the stratification of sickness absence by job level is strongest for occupational minorities, meaning men in female-dominated and women in male-dominated occupations.

Retrospective life course data from European countries on how early life experiences determine health in old age and possible mid-life mediators.

The data presented in this article is related to the research paper entitled "The long arm of childhood circumstances on health in old age: Evidence from SHARELIFE" (E. Pakpahan, R. Hoffmann, H. Kröger, 2016) [1]. It presents the distribution of socioeconomic status (SES) and health from childhood until old age in thirteen European countries. In order to capture the characteristics of longitudinal data, which resembles life course data, we divide the data into three schematic periods: childhood (up to 15 years old), adulthood (30 to 60 years old), and old age (61 to 90 years old). This data set contains respondents' life histories, ranging from childhood conditions (such as housing and health) to detailed questions on education, adult SES (working history, income, and wealth) and old age health. The data can be used not only to understand on how early life experiences determine health in old age, but also to recognise the importance of possible mid-life mediators.

The Association of Levels of and Decline in Grip Strength in Old Age with Trajectories of Life Course Occupational Position.

BACKGROUND: The study of the influence of life course occupational position (OP) on health in old age demands analysis of time patterns in both OP and health. We study associations between life course time patterns of OP and decline in grip strength in old age. METHODS: We analyze 5 waves from the Survey of Health Ageing and Retirement in Europe (n = 5108, ages 65-90). We use a pattern-mixture latent growth model to predict the level and decline in grip strength in old age by trajectory of life course OP. We extend and generalize the structured regression approach to establish the explanatory power of different life course models for both the level and decline of grip strength. RESULTS: Grip strength declined linearly by 0.70 kg (95% CI -0.74;-0.66) for men and 0.42 kg (95% CI -0.45;-0.39) for women per year. The level of men's grip strength can best be explained by a critical period during midlife, with those exposed to low OP during this period having 1.67 kg (95% CI -2.33;-1.00) less grip strength. These differences remain constant over age. For women, no association between OP and levels of or decline in grip strength was found. CONCLUSIONS: Men's OP in midlife seems to be a critical period for the level of grip strength in old age. Inequalities remain constant over age. The integration of the structured regression approach and latent growth modelling offers new possibilities for life course epidemiology.

What causes health inequality? A systematic review on the relative importance of social causation and health selection.

BACKGROUND: The social gradient in health is one of the most reliable findings in public health research. The two competing hypotheses that try to explain this gradient are known as the social causation and the health selection hypothesis. There is currently no synthesis of the results of studies that test both hypotheses. METHODS: We provide a systematic review of the literature that has addressed both the health selection and social causation hypotheses between 1994 and 2013 using seven databases following PRISMA rules. RESULTS: The search strategy resulted in 2952 studies, of which, we included 34 in the review. The synthesis of these studies suggests that there is no general preference for either of the hypotheses (12 studies for social causation, 10 for health selection). However, both a narrative synthesis as well as meta-regression results show that studies using indicators for socio-economic status (SES) that are closely related to the labor market find equal support for health selection and social causation, whereas indicators of SES like education and income yield results that are in favor of the social causation hypothesis. High standards in statistical modeling were associated with more support for health selection. CONCLUSIONS: The review highlights the fact that the causal mechanisms behind health inequalities are dependent on whether or not the dimension being analyzed closely reflects labor market success. Additionally, further research should strive to improve the statistical modeling of causality, as this might influence the conclusions drawn regarding the relative importance of health selection and social causation.