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.

HBM4EU feasibility studies: Lessons learned in combining health and human biomonitoring studies.

BACKGROUND: The European Human Biomonitoring Initiative (HBM4EU) is a joint program evaluating humans' exposure to several environmental substances and their potential health effects. One of the main objectives of HBM4EU is to make use of human biomonitoring (HBM) to assess human exposure to chemicals in Europe to better understand the associated health impacts and to improve chemical risk assessment. In parallel to HBM studies, health examination surveys (HESs), nutrition/dietary surveys, and disease specific health surveys are conducted in many European countries. In HESs, information collected by questionnaire(s) is supplemented with physical examinations and analysis of clinical and biological biomarkers in biological samples. HBM and health examination survey (HES) use similar data collection methods and infrastructures hence the feasibility of combining these two is explored in this paper. METHODS: Within HBM4EU, three feasibility studies (in Finland, Germany, and UK/England) were conducted to evaluate opportunities and obstacles of combining HBM and health studies. In this paper we report lessons learned from these feasibility studies. RESULTS: The Finnish feasibility study called KouBio-KUOPIO study was a new initiative without links to existing studies. The German feasibility study added a HBM module to the first follow-up examination of the LIFE-Adult-Study, a population-based cohort study. The UK feasibility integrates a sustainable HBM module into the Health Survey for England (HSfE), an annual health examination survey. Benefits of combining HBM and HESs include the use of shared infrastructures. Furthermore, participants can receive additional health information from HES, and participation rates tend to be higher due to the potential to obtain personal health information. Preparatory phases including obtaining ethical approval can be time-consuming and complicated. Recruitment of participants and low participation rates are common concerns in survey research and therefore designing user-friendly questionnaires with low participant burden is important. Unexpected events such as the COVID-19 pandemic can cause substantial challenges and delays for such studies. Furthermore, experiences from several countries demonstrated that long-term funding for combined studies can be difficult to obtain. CONCLUSIONS: In the future, incorporating HBM modules into existing HESs can provide a feasible and cost-effective method to conduct HBM studies and obtain a wide range of relevant data to support public health policies and research.

What Builds Resilience? Sociodemographic and Social Correlates in the Population-Based LIFE-Adult-Study.

Resilience is closely related to mental health and well-being. Identifying risk groups with lower resilience and the variables associated with resilience informs preventive approaches. Previous research on resilience patterns in the general population is heterogeneous, and comprehensive large-scale studies are needed. The aim of our study is to examine sociodemographic and social correlates of resilience in a large population-based sample. We examined 4795 participants from the LIFE-Adult-Study. Assessments included resilience (RS-11), social support (ESSI), and social network (LSNS), as well as the sociodemographic variables age, gender, marital status, education, and occupation. The association of resilience with sociodemographic and social correlates was examined using linear regression analyses. Higher resilience was associated with female gender, married marital status, high education, and full-time occupation. Social support and social network were positively associated with resilience. Our results implicate that resilience is related to various sociodemographic variables. Social variables seem to be particularly important for resilience. We identified risk groups with lower resilience, which should be given special attention by public health policies, especially in times of crisis. Reducing loneliness and promoting social connectedness may be promising ways to build resilience in the general population.