Socioeconomic and sociodemographic differences in the consequences of the COVID-19 pandemic and their impact on self-rated health and mental well-being: results from a cross-sectional study in Germany

RESEARCH Open Access © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit h t t p : / / c r e a t i v e c o m m o n s . o r g / l i c e n s e s / b y / 4 . 0 /. Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 https://doi.org/10.1186/s12889-025-23698-w BMC Public Health *Correspondence: Birgit Babitsch [email protected] Full list of author information is available at the end of the article Abstract Background Although the COVID-19 pandemic has demonstrably led to an increase in health inequities, only a few studies have analyzed their underlying mechanisms by taking into account socioeconomic status and sociodemographic differences at the same time. Similarly, only few studies have explored the impact of COVID-19 containment measures on inequities in living conditions, health-related risks, and coping resources. This study aims to address these gaps by exploring the complex associations of socioeconomic and sociodemographic factors with changes in life circumstances, pandemic-related experiences, self-rated health, and well-being among adults living in Germany. Methods A total of 2,123 adults (women: 49.8%, men: 50.2%) living in Germany participated in the cross-sectional online study ExCo:Well between July and August 2022. The survey included questions on socioeconomic status, sociodemographic factors, social circumstances, resources and burdens, as well as health outcomes. The data were analyzed using bivariate and multivariable logistic regression analyses. Results Our results show significant disparities in self-rated health and mental well-being based on socioeconomic status. For sociodemographic differences, the results are mixed, with only women consistently showing worse health outcomes than men. Immigration status played a limited role. Although measures to contain the COVID-19 pandemic more commonly affected the life and work conditions of more privileged participants, socioeconomically disadvantaged participants experienced higher burdens and had fewer coping resources. Logistic regression analyses showed that health inequities decreased when resources and burdens were considered. Conclusions By covering the whole period of the COVID-19 pandemic, our data allow for an overall assessment of this critical time as well as a better understanding of mechanisms underlying health inequities. Our findings suggest that more important than the number of government-induced social changes is their quality and their potential to AQ1 AQ2 Socioeconomic and sociodemographic differences in the consequences of the COVID-19 pandemic and their impact on selfrated health and mental well-being: results from a cross-sectional study in Germany BirgitBabitsch1* and CristinaCiupitu-Plath2 Page 2 of 18Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 Introduction SARS-CoV-2 affected all societies and tested their resilience in dealing with this unknown virus that caused over 7 million deaths worldwide [1], and more than 174,000 fatalities in Germany alone [2]. In addition to large-scale vaccination programs, broader public health and social measures (PHSM) were implemented to contain the COVID-19 pandemic, including curfews, physical distancing, business closures, and mask wearing. In Germany, these strategies were deployed alongside numerous economic policy measures designed to alleviate the financial burden of the pandemic. Impact of the COVID-19 pandemic on self-rated health and well-being Apart from its high death toll, the COVID-19 pandemic also contributed to significant reductions in self-rated health [3–5] and well-being [6–13]. Although the magnitude of these associations varied across different samples [8, 10–12, 14–17], taken together they deliver a wellrounded overview of the health impacts of the pandemic, as self-rated health and well-being are two of the most commonly used health indicators [18, 19]. Despite their partial overlap and largely subjective nature, these two constructs provide distinct information about individual health. Albeit usually relying on a single-item assessment, self-rated health is a broad and largely stable construct reflecting individuals’ perception of their functioning at the intersection of physical, mental, and social health [20]. In turn, well-being refers to a state of positive mental health, in which individuals can reach their full potential and effectively contribute to their community as socially and psychologically well-adjusted and functioning members [21]. Sociodemographic differences in the impact of the COVID19 pandemic on self-rated health and well-being The effects of the COVID-19 pandemic on self-rated health and well-being have varied not only in magnitude, but also across different population groups [11, 13, 22]. Typically, women [5, 23], older age groups [5] and people with low educational attainment [4, 5], lower income or financial insecurity [4, 24, 25] were less likely to rate their health as good during the COVID-19 pandemic. Similarly, most studies found an association between poorer well-being and female gender [6, 8, 10, 13, 22, 26–28], younger age [6, 8, 11, 13, 22], lower educational attainment [8, 10, 11, 26, 27, 29], lower household incomes AQ3 [13], living in socioeconomically disadvantaged neighborhoods [6, 7] and having a chronic disease [13, 26, 27]. Explanatory factors in self-rated health and well-being in the COVID-19 pandemic Overall, both the direct threat posed by SARS-CoV-2 and PHSM consequences such as financial insecurity and reduced social contacts contributed to reductions in selfrated health [3, 17, 24] and mental well-being [7, 22, 30]. Although PHSM typically had a greater impact on socioeconomically disadvantaged populations [31, 32], some studies found that increased risks were only associated with some PHSM (e.g., job loss, worsening financial situation) [33, 34], but not others (e.g., reductions in work hours) [33]. In contrast, coping strategies such as exercising or spending time with family were positively associated with well-being [26] and individuals with a high functional coping profile also had the highest well-being scores [35]. People reporting lower well-being used significantly more distraction strategies such as home entertainment, while those with higher well-being dedicated more time to self-care, family and friends [36]. Overall, the ability to cope with restrictions in social life was lower in socioeconomically disadvantaged populations [34]. Health inequities before and during the COVID-19 pandemic Numerous studies have consistently shown that socioeconomic and sociodemographic differences play an important role in shaping individuals’ chances of living in good health [37–40]. In Germany, even prior to the pandemic, societal factors such as the increase in income inequality between 1994 and 2014 were associated with a significant decline in self-rated health [41] and life expectancy [42]. At the same time, individual characteristics like gender [43, 44] and migration [45, 46] are strong predictors of health status among people living in Germany. The conceptual framework proposed by the WHO Commission on Social Determinants of Health (CSDH) clearly distinguishes between such structural (e.g., policies, socioeconomic and sociodemographic factors) and intermediary (e.g., living conditions, psychosocial factors) determinants of health [47]. Drawing on this framework, it is important to note that the COVID19 pandemic occurred within the context of preexisting social and health inequities associated with greater vulnerability and higher risk of poorer health outcomes negatively impact material and social livelihoods in the long run. To improve health equity, tailored social security and health promotion interventions need to be systematically integrated in pandemic or crisis response plans. Keywords Socioeconomic status, Sociodemographic factors, Health inequity, COVID-19, Self-efficacy, Resources, Burden, Self-rated health, Mental well-being Page 3 of 18Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 among socioeconomically disadvantaged groups, a phenomenon described as a syndemic pandemic [48–54]. A higher risk of contracting COVID-19, a more severe course of disease, and higher mortality [2, 31, 48, 49, 55– 66] have been found in socioeconomically disadvantaged groups, a pattern also noted in Germany [67, 68]. Factors driving health inequity during COVID-19 The factors underlying observed COVID-19 disparities are clearly rooted in much of the same mechanisms that are responsible for endemic health inequities [48, 49, 54, 64, 69, 70]. As a result of the drastic social changes during the COVID-19 pandemic, structures of social disparity were likely reinforced or exacerbated [54]. Accordingly, a COVID-19-specific adaptation of the CSDH [70] included PHSM as structural determinants and the different risks of exposure to SARS-CoV-2 as intermediary determinants of health. The higher vulnerability of socioeconomically disadvantaged groups to the COVID-19 pandemic can therefore be understood as a double burden resulting from (1) a higher pandemic impact on the structural and intermediary determinants of health [47] and (2) a poorer health status prior to the pandemic [37–40]. Specifically, socioeconomically disadvantaged groups had a higher probability of experiencing a deterioration in their living conditions, more risks, and fewer resources and coping mechanisms [48, 49, 54, 70]. Against this background, the amount and quality of coping resources available are likely to play a crucial role in the emergence of health inequities [71–73]. Therefore, distinguishing between ex-ante and ex-post social and health inequities was suggested as a helpful mechanism for working out the inequitable structures and individual possibilities that affected the handling of dramatic pandemic-related changes or resulted from these changes [74]. Using these frameworks can help identify specific strategies to adequately support socioeconomically disadvantaged groups during future public health crises and avoid an increase in health inequities in the long term. Study aim, research questions, and hypotheses While a growing body of research has investigated the role of socioeconomic status and sociodemographic factors in shaping experiences during the COVID-19 pandemic, detailed analyses of the interplay between these factors, changes in living conditions, and health-related resources remain limited. Existing studies often focus on single determinants or broad indicators, leaving a gap in understanding the complex inequities that emerged during the pandemic as illustrated by the concept of syndemic pandemic [48–54]. Further research is needed to assess the role of health-related resources and their interplay with risk factors in a differentiated manner, which is crucial to elucidate health inequities associated with the COVID-19 pandemic. To address this research gap, our study provides a detailed examination of the complex associations between socioeconomic and sociodemographic factors, changes in life circumstances, pandemic-related experiences, and self-rated health and well-being among adults living in Germany. The main research question explored in this study is: How is the relationship of socioeconomic and sociodemographic factors with self-rated health or mental well-being influenced by pandemic-related burdens and resources in Germany? The following hypotheses were tested: 1) People with low socioeconomic status report poorer self-rated health and lower mental well-being compared to people with high socioeconomic status. 2) Older people, women, as well as immigrants and their (direct) descendants report poorer self-rated health and lower mental well-being compared to younger people, men, and people without an immigration history. 3) The social consequences and burdens associated with the COVID-19 pandemic are greater among people with low socioeconomic status than among those with high socioeconomic status. 4) Resources are lower among people with low socioeconomic status than among those with high socioeconomic status. 5) Resources and burdens influence the association of socioeconomic and sociodemographic factors with self-rated health and mental well-being, respectively. With its rich data on social determinants, changes in living conditions, and specific health-related resources, this paper contributes to a deeper understanding of health inequities in Germany and can help identify opportunities to support population health under challenging circumstances. Methods Study design The data originate from the cross-sectional, online study “Experiencing the COVID-19 Pandemic: Association between Resources, Social Health, and Well-Being (ExCo:Well)”. The impact of the COVID-19 pandemic extended beyond direct health threats to significantly alter daily life due to PHSM. Recognizing this profound and unequal impact ExCo:Well aimed to investigate 1. how PHSM affected individuals’ daily life experiences, 2. whether these experiences were driven by socioeconomic and sociodemographic differences, and 3. how all these factors affected self-rated health and mental well-being. Page 4 of 18Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 This study builds on and expands existing research by providing a detailed description of changes related to PHSM, COVID-19 related burdens, and COVID-19 specific and general resources (e.g., general self-efficacy). Beginning in March 2020, numerous measures to contain the COVID-19 pandemic were enacted in Germany by the government at the federal and state level, including curfews, physical distancing, the closure of businesses, and mask wearing. The measures were dynamically adapted to the SARS-CoV-2 infection rates and have been significantly scaled back since May 2022 and completely eliminated as of 8 April 2023 [75, 76]. ExCo:Well was conducted in Germany from 22 July 2022 to 22 August 2022, generating insights into participants’ views and experiences of the entire COVID-19 pandemic and the first months after pandemic restrictions were loosened. Data were collected by an external survey company (respondi, https://mingle.respondi.com) from members of an online panel that has been successfully used in other population-based studies during the COVID-pandemic [77]. The survey included 49 questions, divided into the following sections: COVID-19 pandemic experiences, COVID-19 related personal and societal changes, COVID-19 related (digital) health literacy, COVID-19 specific and general resources, self-rated health, mental well-being, personal attitudes, COVID-19 specific burdens, socioeconomic, and sociodemographic factors. Wherever possible, validated instruments were used in the development of the survey; the development of new questions specifically to assess COVID-19-related aspects followed a structured qualitative approach including cognitive interviews (see Operationalization section for details). The study is reported according to the STROBE statement [78]. Study sample All participants were members of an online panel who were informed about the study and invited to participate by an external survey company. A total of 4,753 people accepted the invitation and met the inclusion criteria, of which 3,175 completed the online questionnaire in full. Quota sampling was used to achieve representativeness in terms of age (18 to 74 years) and gender (crossed), as well as federal state based on Eurostat 2020 data. Moreover, a quota of 30% was set for people with low educational attainment to ensure sufficient data were available for stratified analyses. This corresponds to the distribution of educational attainment among people living in Germany [79]. A sample size was calculated for regression analysis, requiring a minimum of 1,169 participants (power of 0.9, effect size of 0.02, significance level of α = 0.05) [80]. However, to allow for stratified analyses (e.g., by immigration status or educational attainment), it was decided to increase the sample size. The final sample size of 2,123 was randomly selected by the external survey company, which is appropriate in terms of quotas (see above) and data quality. After completion of the data collection, an anonymized data set was provided to the research team by the external survey company. All the data protection requirements were guaranteed by the external company. The study was approved by the ethics committee of Osnabrück University (Ethik-41/2022, 28.6.2022). Operationalization Sociodemographic and socioeconomic variables In this study, socioeconomic (education, income, subjective social status) and sociodemographic factors (age, gender, immigration status) were assessed using various measures. Age was divided into four groups in line with federal health reporting procedures [81]: 18–29, 30–44, 45–64, and 65–74 years. Gender was self-reported by participants as ‘male’ or ‘female’. Immigration status was assessed according to the recommended standards in Germany [82–84]. A distinction was made between two categories: (a) immigrants and their (direct) descendants (i.e., participants not born in Germany or participants born in Germany with both parents born outside of Germany) and (b) people without an immigration history (i.e., participants and one or both parents born in Germany) [84]. Education was assessed using the CASMIN classification [85] and divided into basic, medium and higher educational attainment [86]. Subjective social status (SSS) was measured using the MacArthur Scale of Subjective Social Status [87] as a self-assessment on a 10-step ladder. Participants’ responses were then categorized as low (scale values 1–4), medium (scale values 5–6) and high SSS (scale values 7–10) [88]. Income was assessed as the monthly net household income in line with the demographic reporting standard [89]. In addition, participants were given the option to offer ‘no response’. For the analysis, income categories were combined into four monthly net household income groups (< €1.000, €1.000-2.999; €3.000-4.999; >=€5.000). An adjustment of income level by household size was not possible. Information on partnership and parental status, as well as community size was also requested. Living situation during the COVID-19 pandemic Several aspects of participants’ living situation were surveyed to assess the changes they have experienced due to the COVID-19 pandemic in Germany. Participants were asked (a) to provide an overall assessment of how easy it was for them to navigate the COVID-19 pandemic and (b) to indicate how much their life circumstances Page 5 of 18Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 changed during this time. Both aspects were assessed using 5-point Likert scales with the following answer options (a) 1= ‘very easy’, 2= ‘easy’, 3= ‘neither easy nor difficult’, 4= ‘difficult’, 5= ‘very difficult’, (b) 1= ‘not at all’, 2= ‘rather weak’, 3= ‘neither strong nor weak’, 4= ‘rather strong’, 5= ‘very strong’), which were combined into three groups for analysis (1= ‘rather difficult or rather strong’; 2= ‘neither’; 3= ‘rather easy or rather weak’). In addition, the prevalence of the most common PHSM in Germany (e.g., working from home, extra work, closure of companies or loss of employment, work hour reduction, reduction in overtime and/or holiday, delegation of other tasks, and homeschooling) [75, 76] were assessed (response categories: ‘yes’, ‘no’, ‘not applicable’). Each category was analyzed separately. A limitation of this assessment is that it does not provide information on the magnitude and duration of these changes. In order to gauge how participants experienced the entire COVID-19 pandemic, they were asked to indicate the extent to which they felt threatened, burdened, and restricted during this time. For this purpose, they were given five response options ranging from ‘very strong’ to ‘not at all’. This 5-point Likert scale was reduced to three values for analysis. Moreover, to explore how the participants’ living situation recovered after the PHSM were scaled back, they were asked to estimate how similar their current living situation was compared to their living situation before the COVID-19 pandemic. The extent to which participants’ life situation had returned to normal was assessed in two ways: first, using a 5-point Likert scale (response categories: ‘not at all’ to ‘very strong’), and second, using a slider scale that allowed respondents to select any number between 0 and 100%. Burdens during the COVID-19 pandemic The COVID-19 Pandemic-related Burden Scale (CBS) was created to assess specific burdens on social life resulting from PHSM to contain the COVID-19 pandemic in Germany. The scale items were developed in 2021 based on a comprehensive literature review, including both scientific and popular sources, and validated through cognitive interviews (N = 5). The items capture not only changes in material living conditions, but also burdens experienced in daily life. The final CBS included 12 items rated on a 5-point Likert Scale (1= ‘completely disagree’, 2= ‘mostly disagree’, 3= ‘somewhat agree’, 4= ‘mostly agree’, 5= ‘completely agree’). In addition, the response category ‘does not apply’ was offered. Because of their similar meaning, the response categories ‘does not apply’ and ‘strongly disagree’ were merged in the analysis. To estimate the overall burden, the CBS score was calculated by adding all 12 items (range 12–60). Reliability was good, with Cronbach’s alpha = 0.869. Principal component analysis (PCA) revealed two independent factors of the CBS: (1) material burden (range: 6–30, Cronbach’s alpha = 0.833) and (2) psychosocial burden (range: 6–30, Cronbach’s alpha = 0.851) (see Additional file 1, Supplementary Table 1). Resources during the COVID-19 pandemic The COVID-19 Pandemic-Related Resources and Coping Scale (CRCS) was developed in 2020 based on a comprehensive literature review of coping strategies during the pandemic, including both scientific and popular sources, and validated through cognitive interviews (N = 5). The final CRCS included 12 items rated on a 5-point Likert scale (1= ‘does not apply at all’, 2= ‘applies to a low extent’, 3= ‘applies to a moderate extent’, 4= ‘applies to a large extent’, 5= ‘applies to a very large extent’). To estimate the overall level of coping, the CRCS score was calculated by adding all 12 items (range 12–60). Reliability was good, with Cronbach’s alpha for standardized items = 0.881. For the CRCS, a PCA was performed, identifying two factors: (1) self-focused coping strategies (range: 7–35, Cronbach’s alpha = 0.856) and (2) social engagement (range: 5–25, Cronbach’s alpha = 0.756) (see Additional file 1, Supplementary Table 2). Participants’ general self-efficacy (GSE) was assessed using the 10-item scale developed by Jerusalem & Schwarzer [90]. The items measure optimistic expectations of competence, i.e., the confidence that one can master a difficult situation, whereby success is attributed to one’s own abilities. A total score was generated (range 10 to 40), with higher values indicating higher self-efficacy. A dichotomous variable (low vs. high self-efficacy) was created using the value 29 as a cut-off point [90]. Reliability was excellent (Cronbach’s alpha = 0.926). Self-rated health and mental well-being To describe the health status of the sample, participants’ self-rated health [91] and the presence of a chronic disease (‘yes’/’no’) were assessed. Using a 5-point Likert scale, the participants were asked to rate their overall health status from ‘very good’ to ‘very poor’ [91]. A dichotomous variable was created to distinguish between ‘rather good’ (response categories: ‘good’ and ‘very good’) and ‘rather poor’ (response categories: ‘satisfactory’, ‘poor’ and ‘very poor’) self-rated health. The WHO-5 questionnaire [92] was used to survey mental well-being. All five items were added to obtain a total score (range 0–25). Following Brähler et al. [93], a dichotomous variable was created with a cut-off point at 13. Reliability was excellent (Cronbach’s alpha = 0.923). Data analysis The data were analyzed using IBM SPSS Version 29.0. Univariate and bivariate analyses were carried out for the Page 6 of 18Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 descriptive analysis. The median was used when the data were not normally distributed, as determined by the Kolmogorov-Smirnov test. All analyses were stratified by socioeconomic (educational attainment (CASMIN), monthly net household income, and SSS) and sociodemographic (age, gender, and immigration status) variables. Significance was tested using the Pearson chi2-test, the Mann-Whitney-U test, and the Kruskal-Wallis test, as appropriate. Factor analyses were conducted to examine the properties of the new scales (CBS, CRCS). The reliability of all scales was tested with Cronbach’s alpha. Multivariable logistic regression models were calculated for self-rated health (1 = rather good) and for mental well-being (1 = high) as dependent variables. The independent variables were selected based on theoretical considerations and included block-wise: (1) socioeconomic and sociodemographic variables, (2) resources and burdens, and (3) presence of a chronic disease. The significance level was set at 0.05 for all analyses. Results Study sample Female and male participants were almost equally represented in the sample, reflecting the gender distribution of the population living in Germany. On average, participants were 46.3 years old; the largest age group was between 45 and 65 years old (40.0%). In total, 9.4% of the participants were immigrants or their (direct) descendants. A basic level of education was attained by 31.3%, a medium level by 47.7% and a high level by 21.0% of the participants. Two-thirds of the participants had a monthly net household income between 1,000 and 4,999 euros; 7.6% did not answer this question. SSS was classified as low by 29.8% of participants and as high by 32.5%. A total of 61.4% lived in a partnership, 55.2% had children and 42.4% lived in a place with fewer than 20,000 inhabitants. A SARS-CoV-2 infection was reported by 37.4% of the participants (see Table1). Changes in and perceptions of personal living conditions during the COVID-19 pandemic The PHSM to contain the COVID-19 pandemic have drastically changed living conditions and revealed numerous patterns of inequity. Considering the whole period of the COVID-19 pandemic, half of the participants (52.5%) reported experiencing rather significant life changes. This was significantly more common among younger participants (60.8%) and those with a low SSS (56.6%), but also among those with higher education (55.5%). Overall, 30.3% of respondents worked from home, 19.2% reported additional work, 11.3% lost their jobs, 15.1% experienced work hour reductions, 14.9% had to reduce overtime or take leave, 15.4% were given new responsibilities, and 18.8% had to take on homeschooling or childcare responsibilities. Many of these life changes were more commonly reported by participants with higher socioeconomic status. The COVID-19 pandemic was perceived as threatening by 40.3% of participants, burdening by 49.8%, and restrictive by 51.4%. These perceptions varied more across sociodemographic groups, but little across socioeconomic strata, where only significant differences with regard to the perceived burden of the COVID-19 pandemic were noted. Specifically, a higher percentage of older participants perceived the pandemic as a threat, yet significantly more participants in younger age groups felt burdened by the pandemic. Female participants fared worse than male participants on all assessed measures. Navigating the COVID-19 pandemic was retrospectively rated as being rather difficult by a third of the participants. Younger age groups, female participants, and participants with lower SSS were significantly more likely to report this. Table 1 Description of the study sample Characteristics (N = 2,123) N% Gender Female 1,058 49.8 Male 1,065 50.2 Age groups 18–29 years 406 19.1 30–44 years 567 26.7 45–64 years 849 40.0 65–74 years 301 14.2 Age (in years, median) 2,123 47.0 Age (in years, mean, (std. dev)) 2,123 46.3 (15.4) Immigrants and their (direct) descendants 199 9.4 Educational attainment (CASMIN) Basic 665 31.3 Medium 1,013 47.7 Higher 445 21.0 Monthly net household income No answer 161 7.6 Up to under 1,000 euros 243 11.4 1,000 to 2,999 euros 947 44.6 3,000 to 4,999 euros 576 27.1 5,000 euros and more 196 9.2 SSS Low 633 29.8 Medium 800 37.7 High 690 32.5 Living in partnership 1,303 61.4 Children 1,171 55.2 Community size Fewer than 20,000 inhabitants 900 42.4 Infection with SARS-CoV-2 (self-reported) 793 37.4 Page 7 of 18Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 At the time of data collection, 43.3% of the study participants reported that their current living situation had started to become more similar to their living situation before the COVID-19 pandemic. This is consistent with participants’ overall assessment that their current living situation corresponds to 79% (median) of their living situation before the COVID-19 pandemic. Recovery rates were significantly lower among participants who were younger, female, and had lower SSS. For example, 50.9% of participants with high SSS vs. 34.8% of participants with low SSS reported that they had returned to their usual, pre-pandemic living situation (see Table 2, see Additional file 2, Supplementary Table2_1 for the results stratified for immigration status, educational attainment (CASMIN) and monthly net household income). Experienced burdens during the COVID-19 pandemic The majority of participants experienced burdens related to their personal, social and material situation, as measured by the COVID-19 Pandemic-related Burden Scale (CBS). Considering the entire COVID-19 pandemic, 22.5% of the participants felt that their livelihood was threatened and 34.3% assumed that it would take a long time to return to their previous living standard. A high percentage of participants experienced challenges in their social lives and in coping with changed living conditions. Younger age groups, female participants, immigrants and their (direct) descendants, and those with low SSS perceived their life situation as more challenging, with few exceptions. The overall perceived burden was low, with a median CBS score of 24.0 (range 12–60). This was also found for both the Psychosocial burden subscale (median = 15.0, range 6–30) and the Material burden subscale (median = 8.0, range 6–30). Both types of burdens were significantly greater among younger age groups and participants with low SSS (see Table3, see Additional file 2, Supplementary Table3_1 for the results stratified for immigration status, educational attainment (CASMIN) and monthly net household income). Resources during the COVID-19 pandemic Although most participants tried to live a normal daily life, they also used different coping strategies to adapt to their new, restricted living situation, such as taking more time to relax (42.7%) or spending more time in nature (44.6%). In addition, a third of the study participants increased the time they spent with their families and made more efforts to improve their health. There were some significant social differences, showing that older participants and those with low SSS were less likely to use most of the assessed coping strategies. A mixed pattern was noted regarding gender differences in coping strategies. Almost half of the sample had high GSE, with a median of 29.0 and a mean (standard deviation) of 28.5 (5.7). However, large social differences in participants’ GSE were observed. For example, GSE scores were significantly higher among participants with higher educational attainment, higher SSS, and higher monthly net household income, as well as among male participants and older age groups (see Table4, see Additional file 2, Supplementary Table4_1 for the results stratified for immigration status, educational attainment (CASMIN) and monthly net household income). Self-rated health and mental well-being Overall, 47.3% of the sample rated their health as very good or good, and 50.4% had a chronic disease. Older participants and participants with low SSS reported poorer self-rated health and were also more likely to have a chronic disease. For example, 73.6% of participants with low SSS rated their health as rather poor as opposed to just 31.2% of participants with high SSS. Almost two-thirds of the sample reported high mental well-being levels, but there were notable differences by socioeconomic status, with significantly more participants with lower SSS reporting lower mental well-being levels. Contrary to self-rated health, younger participants (median = 14.0) rated their mental well-being lower than older participants (median = 17.0) (see Table5, see Additional file 2 Supplementary Table5_1 for the results stratified for immigration status, educational attainment (CASMIN) and monthly net household income). Effects of socioeconomic and sociodemographic factors, resources, and burdens on self-rated health and mental well-being Multivariable logistic regression analyses revealed that self-rated health was influenced by socioeconomic and sociodemographic factors as well as resources and burdens. Model 1 showed lower odds of participants assessing their self-rated health status as ‘rather good’ among older and female participants as well as among persons with lower SSS. People with high SSS were 4.4 times [3.30–5.81] more likely to have a ‘rather good’ self-rated health status than people with low SSS. When resources and burdens were considered (model 2), GSE (1.10 [1.08–1.12]) increased the odds of a ‘rather good’ self-rated health status, while COVID-19-related burdens (CBS) had a negative effect (0.97 [0.96–0.98]). In model 3, only Psychosocial Burdens (0.97 [0.95–0.98]) reduced, while Self-Focused Coping Strategies (1.03 [1.00-1.05]) slightly increased the odds of reporting a ‘rather good’ self-rated health status. In the final model 4, the presence of a chronic disease was added and emerged as strong risk factor for self-rated health (0.19, Page 8 of 18Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 Characteristics (N = 2,123) NAge Gender SSS Total 18–29 30–44 45–64 65–74 p1M F p1L M H p1 Changes in life through measures to contain the COVID-19 pandemic < 0.001 0.038 0.016 Rather stronga (%) 1,115 60.8 57.8 48.3 43.2 50.6 54.4 56.6 52.9 48.4 52.5 Working from home (%) < 0.001 < 0.001 < 0.001 Yes 644 56.7 40.4 20.7 3.0 34.8 25.8 16.6 28.2 45.4 30.3 No 606 24.1 32.5 32.0 17.3 29.1 28.0 25.9 31.9 27.1 28.5 Not applicable 873 19.2 27.2 47.2 79.7 36.1 46.2 57.5 39.9 27.5 41.1 Extra work (%) < 0.001 < 0.001 < 0.001 Yes 408 26.1 30.3 14.7 1.7 19.2 19.3 14.1 21.0 21.9 19.2 No 945 51.2 49.6 46.3 20.9 49.3 39.7 36.2 45.6 50.9 44.5 Not applicable 770 22.7 20.1 39.0 77.4 31.5 41.0 49.8 33.4 27.2 36.3 Loss of employment (%) < 0.001 < 0.001 < 0.001 Yes 240 15.0 13.9 10.4 4.0 12.5 10.1 12.3 11.4 10.3 11.3 No 1,116 58.9 64.2 52.4 22.6 57.4 47.7 39.7 54.9 61.7 52.6 Not applicable 767 26.1 21.9 37.2 73.4 30.1 42.2 48.0 33.8 28.0 36.1 Work hour reductions (%) < 0.001 < 0.001 < 0.001 Yes 321 19.2 21.2 13.7 2.3 16.9 13.3 13.3 15.0 17.0 15.1 No 1,016 53.7 57.7 47.8 21.6 52.0 43.7 37.3 49.9 55.2 47.9 Not applicable 786 27.1 21.2 38.5 76.1 31.1 43.0 49.4 35.1 27.8 37.0 Reduction overtime and/or holiday (%) < 0.001 < 0.001 < 0.001 Yes 317 19.0 22.0 13.1 1.3 16.8 13.0 11.2 13.8 19.7 14.9 No 1,023 55.2 57.3 48.3 21.3 51.2 45.2 38.5 52.3 52.3 48.2 Not applicable 783 25.9 20.6 38.6 77.4 32.0 41.8 50.2 34.0 28.0 36.9 Delegation of other tasks (%) < 0.001 < 0.001 < 0.001 Yes 328 26.8 20.8 11.4 1.3 15.9 15.0 12.0 15.3 18.8 15.4 No 1,020 48.3 57.5 50.4 23.3 52.0 44.0 38.2 50.2 54.5 48.0 Not applicable 775 24.9 21.7 38.2 75.4 32.1 40.9 49.8 34.5 26.7 36.5 Homeschooling (%) < 0.001 < 0.001 < 0.001 Yes 400 20.7 35.8 12.1 3.3 18.8 18.9 16.3 18.0 22.2 18.8 No 787 44.6 35.8 40.3 20.3 42.1 32.0 28.1 39.5 42.5 37.1 Not applicable 936 34.7 28.4 47.6 76.4 39.2 49.1 55.6 42.5 35.4 44.1 Perceived threat from the COVID-19 pandemic 0.013 0.003 0.390 Rather stronga (%) 855 40.9 39.3 38.6 45.8 36.8 43.8 42.8 38.5 40.0 40.3 Perceived burden of the COVID-19 pandemic < 0.001 < 0.001 < 0.001 Rather stronga (%) 1,057 58.6 52.7 46.9 40.5 44.1 55.5 55.9 49.8 44.2 49.8 Perceived restrictions due to the COVID-19 pandemic < 0.001 < 0.001 0.092 Rather stronga (%) 1,092 59.9 58.7 47.6 37.2 47.1 55.8 55.1 50.0 49.7 51.4 Table 2 Experiences and changes in the life situation through the COVID-19 pandemic stratified by age, gender and SSS Page 9 of 18Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 [0.15–0.24]). The impact of socioeconomic and sociodemographic factors on self-rated health decreased when additional variables were included. Model 1 significantly contributed to the prediction of self-rated health and explained 25% of its variance, which increased to 43% when additional variables were taken into account (model 4). All models had good model fit (Hosmer-Lemeshow-Test) (see Table6). Similar results were found in the analysis of mental well-being (see Table 7). Model 1 showed that the odds of having a high mental well-being level was higher for people with a higher level of education (1.45 [1.06–1.99]), medium (1.93 [1.53–2.44]) or high SSS (4.13 [3.11–5.48]), as well as for older participants (1.02 [1.01–1.02]); lower odds were observed for female participants (0.64 [0.53– 0.78]). Resources increased and burdens decreased the odds of high mental well-being (models 2 and 3), with the exception of the Material Burden Subscale of the CBS. In the final model 4, having a chronic disease was associated with 53% lower odds of high mental well-being. Immigration status did not emerge as a significant predictor of neither self-rated health nor mental well-being (see Tables6 and 7) in any of the models. The contribution of social determinants toward a high mental wellbeing level decreased from model 1 to model 4, but only medium SSS became insignificant. The logistic regression models were statistically significant and had good model fit (Hosmer-Lemeshow-Test). The explained variance increased from 16% in model 1 to 34% in model 4 (see Table7). Discussion The aim of the study was to explore the complex associations between socioeconomic and sociodemographic factors, changes in life circumstances, pandemic-related burdens and resources, and indicators of self-rated health and well-being among adults living in Germany. As such, the study contributes to a better understanding of how endemic health inequities, which have been documented in numerous studies both internationally [37, 38] and in Germany [39–42] contributed to the adverse impacts of the COVID-19 pandemic, which has been characterized as a syndemic pandemic [48–54]. The main strength of our study lies in utilizing multiple measures of socioeconomic status, sociodemographic differences, and living conditions during the COVID-19 pandemic, and leveraging them to characterize life experiences and their influence on self-rated health and mental well-being. Another strength of the study is that it was carried out at the end of the COVID-19 pandemic, providing a retrospective assessment of the whole pandemic period and all the associated changes in participants’ social circumstances and health. Characteristics (N = 2,123) NAge Gender SSS Total 18–29 30–44 45–64 65–74 p1M F p1L M H p1 Overall assessment of dealing with the COVID-19 pandemic 0.010 < 0.001 < 0.001 Rather difficultb (%) 759 42.9 37.2 33.6 29.6 31.6 39.9 43.4 34.3 30.4 35.8 Change in living situation due to the relaxation of COVID-19-related restrictions < 0.001 0.456 < 0.001 Rather stronga (%) 919 54.9 50.4 37.7 29.9 43.3 43.3 34.8 43.5 50.9 43.3 Percentage of adjustment between current living situation and everyday life before the coronavirus pandemic <.0013.0202<.0013 Median 2,123 70.0 75.0 80.0 80.0 80.0 77.0 71.0 77.5 80.0 79.0 1 Pearson Chi2-Test unless otherwise noted; 2 Mann-Whitney-U test; 3 Kruskal-Wallis test; a Includes the response categories: ‘rather strong’ and ‘very strong’; b Includes the response categories: ‘difficult’ and ‘very difficult’; Gender: M Male, F Female, SSS: L Low, M Medium, H High Table 2 (continued) Page 16 of 18Babitsch and Ciupitu-Plath BMC Public Health (2025) 25:2523 not only enhance our understanding of syndemic pandemic impacts but also provide insights for tailoring public health interventions. In addition to initiatives aimed at combating the spread and health consequences of SARSCoV-2, health promotion measures should be an integral part of crisis management. Given their prominence as risk factors in our study, policymakers and healthcare providers should systematically incorporate strategies that effectively address markers of socioeconomic disadvantage to reduce health disparities during future health crises. Abbreviations CBS COVID-19 Pandemic related Burden Scale CRCS COVID-19 Pandemic-Related Resources and Coping Scale F Female GSE General self-efficacy ID Immigrants and their (direct) descendants M Male NIH No immigration history PHSM Public health and social measures SSS Subjective social status Supplementary Information The online version contains supplementary material available at h t t p s : / / d o i . o r g / 1 0 . 1 1 8 6 / s 1 2 8 8 9 - 0 2 5 - 2 3 6 9 8 - w. Supplementary Material 1.Items on the CBS and CRCS scales.Information is provided on the items and components of the CBS and CRCS scales and subscales. Supplementary Material 2.Additional analyses are provided regarding immigration status, educational attainment (CASMIN) and monthly net household income.Findings are presented regarding immigration status, educational attainment (CASMIN) and monthly net household income. Acknowledgements The authors thank all participants for supporting this study by sharing their views. Authors' contributions Study design (BB), Data analysis (BB, CCP), Initial Draft (BB), Writing, Editing and Proofreading (BB, CCP). Funding Open Access funding enabled and organized by Projekt DEAL. Open Access funding enabled and organized by Projekt DEAL. Open Access funding enabled and organized by Projekt DEAL. This research received no external funding. The APC was partly funded by the publication fund, which is financed by the Osnabrück University and the German Research Foundation (DFG). Data availability The data that support the findings of this paper are available from the corresponding author upon reasonable request. Declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Osnabrück University (Ethik-41/2022, 28.6.2022). All participants were members of an online panel who were informed about the study and gave informed consent for participation. The study was conducted in accordance with relevant guidelines and regulations. Consent for publication Not applicable. Competing interests The authors declare no competing interests. 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