[Consequences of the COVID-19 pandemic: Are there risk groups for reduced subjective well-being after the first lockdown?].

Background: Measures to contain COVID-19 have created burdens that have widened health inequalities. We examine the extent to which risk groups for reduced subjective well-being can be identified after the 2020 lockdown. In doing so, we also consider possible interactions of different social grouping characteristics as part of an intersectional approach.

Method: Socio-Economic Panel (SOEP) data from the years 2018-2020 were analyzed. A total of 16,000 cases with information on changes in well-being (SF-12 scores and individual indicators) were included in the analyses. We use the classification method "random forests" to identify groups with different trends in well-being. For the interpretation of the content, we also present results from a regression model with social and health aspects as predictors.

Results: Demographic and social characteristics explained only a very small part of the changes in subjective well-being (R = 0.007-0.012) and did not allow for the differentiation of homogeneous risk groups. Although some significant predictors were found in the regression models, the corresponding effects were mostly small. In addition to the initial state of well-being before the pandemic began, the presence of chronic illnesses and disabilities in particular contributed to the explanation of subjective well-being.

Discussion: The currently available data do not allow a clear identification of risk groups for losses in well-being in the first year of the COVID-19 pandemic. Health status before the onset of the pandemic appears to be more important for short-term changes in subjective well-being than socio-demographic and socio-economic categorization characteristics.