Literature DB >> 35701779

Mental health of Covid-19 risk groups during the first Covid-19 lockdown in Germany: a cross-sectional study.

Niels Graf1, Christine Firk2, Daniel Deimel3,4,5, Thorsten Köhler6, Janina Dyba6.   

Abstract

BACKGROUND: The ongoing Covid-19 pandemic not only threatens physical health, but also affects the mental health of people. Yet, health consequences of the pandemic do not affect all members of society equally. We therefore assessed the mental health burden of individuals who are at increased risk of severe illness from Covid-19 compared to individuals who are at low risk of severe illness during the first lockdown (March, 2020) in Germany. Furthermore, we investigated variables mediating the effect of being an individual at increased risk of serve illness on depression.
METHODS: Adult German residents (n = 2.369) provided responses to a cross-sectional online survey about risk factors for of severe illness from Covid-19 and various aspects of mental health during the first lockdown in Germany. For data collection, standardized and validated self-report measures were used and for data analysis Mann-Whitney U-tests as well as regression and mediation analyses were performed.
RESULTS: The results clearly show that the mental health burden is higher among individuals at increased risk of severe illness from Covid-19 compared to individuals at low risk of severe illness from Covid-19. Moreover, our findings indicate that the association between Covid-19 risk status and depressive symptoms is mediated by concerns about mental health, anxiety and loneliness in a causal effect chain.
CONCLUSIONS: Individuals at increased risk of severe illness from Covid-19 have an increased need for psychosocial support during times of lockdown. Future public health policies should pay special attention to these individuals and support them by targeted offers. More research, however, is needed on possible long-term consequences of social distancing on mental health.
© 2022. The Author(s).

Entities:  

Keywords:  Covid-19; Covid-19 risk group; Germany; Mental health; Pandemic

Mesh:

Year:  2022        PMID: 35701779      PMCID: PMC9196153          DOI: 10.1186/s12889-022-13593-z

Source DB:  PubMed          Journal:  BMC Public Health        ISSN: 1471-2458            Impact factor:   4.135


Introduction

The most recently discovered coronavirus, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread globally within a few months after its first identification in December 2019 [1]. The World Health Organization (WHO) declared the Covid-19 disease caused by the virus as a pandemic on March 11th 2020. In Germany, the first case of Covid-19 was confirmed on January 27th 2020 [2]. First infection clusters emerged in the federal states North Rhine-Westphalia and Bavaria throughout February 2020 [3]. Subsequently, Covid-19 cases increased rapidly, culminating in about 6016 new cases on March 16th 2020 [4]. As of June 2020, by the end of the so-called “first wave”, 183,594 persons had been diagnosed with a SARS-CoV-2 infection in Germany and the number of deaths registered in this group amounted to 8555 [5]. The cumulative rate of officially recognized Covid-19-associated hospitalizations in Germany is 10% [6]. Older people above the age of 50-60 and people with underlying medical conditions, such as heart conditions, chronic obstructive pulmonary disease (COPD), or obesity are at increased risk of severe illness from Covid-19 [7, 8]. On March 22nd 2020, the German government imposed a first lockdown to reduce infection rates and thus protect these vulnerable groups and maintain the proper functioning of the health care system. This lockdown included the closing of schools, stores, restaurants, bars, clubs, social venues and prohibited any form of mass gatherings. In addition, citizens were urged to minimized personal social contact and keep a minimum distance of 1.5 m from one another [9]. It lasted until May 4th 2020 and associated regulations were gradually eased by June 15th 2020 (see Fig. 1).
Fig. 1

First Covid-19 lockdown in Germany. Sources: Own elaboration based on data from RKI [4]

First Covid-19 lockdown in Germany. Sources: Own elaboration based on data from RKI [4] These governmental actions aim at a reduction of social contacts. Social distancing however may be associated with a substantial mental health burden and there is evidence for an association between social isolation and (mental) health problems [10, 11]. This is also supported by recent studies showing that the Covid-19 pandemic and related regulations are associated with increases in anxiety, depression and psychological distress [12-14]. The increase in mental health problems may in turn also favor dysfunctional coping and emotion regulation strategies such as substance use [15]. Even though these mental health impacts of the Covid-19 pandemic may be more significant for those who are prone to psychological problems [16], previous studies have not taken into account the mental health of individuals at increased risk of severe illness from Covid-19 due to their age or underlying medical conditions [7, 8]. Individuals at risk of severe illness from Covid-19 may be more worried about their own health and therefore avoid social contacts to reduce the risk of a Covid-19 infection. Previous studies demonstrated a relationship between concern of COVID pandemic and feelings of loneliness [17, 18]. This may increase feelings of loneliness, which in turn may result in mental health problems such as depression [19]. Hence, the primary aim of the present study is the investigation of the mental health burden of individuals who are at increased risk of severe illness from Covid-19 (high risk group for Covid-19, HRGC) compared to individuals who are at low risk of severe illness (low risk group for Covid-19, LRGC). The central hypothesis is that individuals of the HRGC are more anxious and experience more depressive symptoms due to the pandemic than individuals of the LRGC. Based on associations between anxiety, depression, and substance use, we moreover expect that HRCG individuals report enhanced substance use. Furthermore, the second aim of the current study is to investigate whether the hypothesized increase in depressive symptoms in the HRGC group is mediated by concerns about own mental health, anxiety, stress and loneliness.

Methods

Study design and data collection

Cross-sectional data were collected via an online survey from June 1st 2020 until July 17th 2020. The survey was developed in LimeSurvey (LimeSurvey GmbH, Hamburg). The weblink of the survey was included in an advert that was promoted on the websites and social media platforms of several German social service organisations and associations (German AIDS Service Organisations, German Society for Social Psychiatry, German Federation of Telephone Emergency Services, German Federation for Social Work in the Healthcare System, German Society for Social Work in Addiction Aid). To be able to participate in the study, participants had to be at least 18 years and have sufficient knowledge of the German language. Participants did not get any compensation for participating in the survey. In total, 3154 people were reached through the online survey. For this study, a subset of participants (n = 2.369) has been analysed for the comparison of the mental health burden of HRGC and LRGC participants.

Measures

The survey started with comprehensive participant information and consent forms. This introductory part was followed by 132 items on sociodemographic variables, participants’ mental health status, their perceptions of the Covid-19 pandemic and the governmental actions designed to encounter the pandemic.

Mental health

All items on mental health were part of standardized and validated self-report measures. Subscales of the German version of the Patient Health Questionnaire (PHQ-D) [20] were used to assess levels of depression (PHQ-9) (Kromke et al. 2006), anxiety (General Anxiety Disorder-7, GAD-7) [21] and somatisation (Patient Health Questionnaire-15, PHQ-15) [22]. The PHQ-9 scale assesses severity of depressive symptoms with a maximum score of 27. GAD-7 measures symptoms of anxiety with a maximum of 21. A score of 10 or above on each of the two scales points to an at least moderate major depressive episode and moderate levels of clinical anxiety [21, 23]. The items of the PHQ-15 scale include the most prevalent DSM-IV somatization disorder somatic symptoms. The total PHQ-15 scale has a maximum score of 30 and a score of 10 and above represent a moderate level of somatization [22]. The internal reliability of the PHQ-9 was with a Cronbach’s α of 0.90 similar to other studies (0.86-0.89) [23]. The internal consistency of the GAD-7 was with a Cronbach’s α = 0.91 similar to another study (0.89) [21] and of PHQ-15 with a Cronbach’s α = 0.81 equal to another study (0.82) [22].

Suicidality

Suicidality was assessed by the first item of the German version of the Suicide Behaviours Questionnaire – Revised (SBQ-R) which is acknowledged as a reliable instrument to measure suicidal risk (“Have you ever thought about or tried to take your own life?” = never (1); I had only a fleeting thought about it (2); I had at least 1 intention to kill myself, but I did not try (3); I had at least 1 intention to kill myself and I really wanted to die (3); I tried to kill myself, but I did not want to die (4); I tried to kill myself, and I really wanted to die (5)). A score of 3 and higher represents an increased risk of suicide [24, 25]. This item was complemented by a question on suicidal ideation during the first lockdown in Germany (“How often have you thought about killing yourself during the lockdown?”).

Loneliness

Emotional and social loneliness were surveyed by the 11-item De Jong Gierveld Loneliness Scale with a maximum score ranges from 0 to 22 [26]. The internal consistency of the Loneliness-Scale was with a Cronbach’s α = 0.77.

Social support

The level of social support was assessed with the help of the Oslo 3 Social Support Scale (OSSS-3). The score ranges from 3 to 14. A score of 12 and above represent a strong social support. The internal consistency of the OSSS-3 was with a Cronbach’s α = 0.66 simliar to another study (0.64) [27, 28].

Drug use

Moreover, the use of alcohol, nicotine and a range of illegal substances during the last 12 months as well as changes in substance use during the lockdown were assessed by asking the participants which substances they used in the last 12 months, respectively during the first lockdown. To differentiate between HRGC and LRGC participants, risk factors for an increased risk of severe illness from Covid-19 were assessed by the criteria of the Robert Koch Institute [29] which include smoking, obesity, cardiovascular diseases, chronic lung diseases, diabetes mellitus, cancer, and a compromised immune system. If at least one of these criteria was met, participants were included in the HRGC group.

Statistical analysis

We used a subset of the dataset and included all participants who gave information about their Covid-19 risk profile (n = 2.369). The analyses presented here compare two groups: (i) individuals at increased risk of severe illness from Covid-19 (n = 1.136; HRGC group) and (ii) Individuals at low risk of severe illness from Covid-19 (n = 1.233; LRGC group). Data analysis was conducted using IBM SPSS Statistics 25.0 (IBM corp., Armonk, USA). Significance level of p < 0.05 was considered in all analyses. For group comparisons Mann-Whitney U-tests were performed for ordinal and non-normally distributed data. Cohen’s d is reported as the estimated effect size for statistically significant results. The distribution of categorical variables was assessed by Chi-square tests. Spearman’s correlation coefficients were used to determine correlations between ordinal variables and non-normally distributed continuous variables. Pearson’s correlation was used for normally distributed continuous variables. Linear regression analysis was used to explore predictors for depressive symptoms. Additionally, mediation analysis using PROCESS macro [30] for SPSS 25 (IBM corp., Armonk, USA) was run to explore whether concerns about one’s own health, anxiety and feelings of loneliness mediated depressive symptoms. Multiple mediator models were performed to estimate indirect effects [31]. All analyses were based on 5000 bootstrapped samples. An indirect effect was considered significant when the 95% bias-corrected confidence interval did not include zero [30].

Results

Sample characteristics

Of the 3154 persons who commenced the survey, 2.369 participants completed questions on Covid-19 risk factors (75.11%). 47% (n = 1291) of those participants were classified into the HRGC. Data of non-completers were included on a pairwise basis, resulting in a different number of responses per analysis (for details on the sociodemographic characteristics of the HRGC and the LRGC, see Table 1).
Table 1

Sociodemographic characteristics

VariableCOVID-19 risk groupNon-COVID-19 risk groupp-value
NM (SD)NM (SD)t-test
Age113646.1 (14.8)123339.4 (14.6).460
N%N%X2
Gender11371236< .001
 Female70662.189672.5
 Male41236.232326.1
 Diverse191.7171.4
Employment status12911.406< .001
 Full-time employed48337.450135.6
 Part-time employed29823.138627.5
 Retired19615.2775.5
 Student15411.932523.1
 Unemployed735.7282.0
 Other876.7896.3
Monthly net income11011188< .001
  < 1.000 Euros24822.535730.1
 1.000-2.000 Euros38234.736230.5
 2.000-3.000 Euros28926.231126.2
 More than 3.000 Euros18216.515813.3
Education11331237.037
 University or university of applied sciences diploma55749.267754.7
 Completed vocational education15213.413310.8
 Completion of secondary school41736.842136.8
 Other/none70.660.5
Sociodemographic characteristics

Mental health measures

In total, 30.9% of the participants of both groups reported symptoms of a moderate depression on the PHQ-9 scale (score of 10 or higher). The median PHQ-9 score was significantly higher in the HRGC than in the LRGC group. 35.6% of the HRGC participants and 26.6% of the LRGC participants had a PHQ-9 score of 10 or higher and, therefore, exhibited moderate depressive symptoms. Compared to the LRGC, the median GAD-7 score of the HRGC was also significantly higher. Here, 29.6% of the HRGC participants and 21.4% of the LRGC participants showed at least moderate levels of generalized anxiety disorders (GAD-7 score ≥ 10). A similar pattern applies to somatic symptoms. The median PHQ-15 score was again significantly higher in the HRGC than in the LRGC group. 15,6% of the HRGC participants and 7.6% of the LRGC participants exhibited at least moderate somatic symptoms (PHQ-15 score ≥ 10). In total, 14.4% of the participants showed an elevated risk for suicide (SBQ-R Item 1 ≥ 3). Again, an elevated risk for suicide was significantly higher in the HRGC than in the LRGC (19.5% vs. 9.7%) group. The same results can be found for the median suicidal ideation during the lockdown (see Table 2).
Table 2

Mental health

VariableHRGCLRGCTest statisticSignificanceEffect size
NMdn (IQR)MNMdn (IQR)MMann-Whitney Up-valuer
Depression (PHQ-9 score)10836.00 (9.00)7.911825.00 (7.00)6.39552,002,5< .0010.12
Anxiety (GAD-7 score)10786.00 (8.00)7.1811895.00 (7.00)6.04565,787,0< .0010.10
Somatization (PHQ-15 score)8464.00 (6.00)5.1110173.00 (4.00)3.73349,393,5< .0010.16
N%N%X2p-valuePhi
Depression (PHQ-9 score ≥ 10)35135.628226.619,203< .0010.097
Anxiety (GAD-7 score ≥ 10)31929.625521.419,838< .0010.094
Somatization (PHQ-15 score ≥ 10)13215.6777.629,910< .0010.127
Suicidality lifetime SBQ-R Item 1 ≥ 322719.51249.747,544< .0010.435
NMdn (IQR)MNMdn (IQR)MMann-Whitney Up-valuer
Suicidal thoughts during lockdown5351.0 (1.00)1,764321.0 (1.00)1,59107,184,5.026*0.125
Mental health

Substance use during lockdown

There were no significant differences between the HRGC and the LRGC group for alcohol use during the lockdown. In contrast, the use of nicotine and THC during the lockdown differed significantly between the two groups. 20.1% of the HRGC reported an increased use of nicotine during the lockdown compared to 6.1% of the LRGC participants. An increased use of THC during the lockdown was reported by 6.7% of the HRGC individuals compared to 2.1% of the LRGC participants (see Table 3).
Table 3

Descriptive statistics and X2 results for substance use in the HRGC and LRGC

VariableHRGCLRGCp-valueEffect size
N%N%X2Phi
Substance use in the last 12 months
 Alcohol105697.4115193.4.190
 Nicotine61862.530229.3< .0010.333
 THC29230.518617.3< .0010.155
 Cocaine565.3231.9< .0010.093
 Amphetamines696.5292.4< .0010.101
 Methamphetamines232.180.7.0020.064
 Ecstasy656.2332.7< .0010.084
Alcohol use during lockdown11371259.0460.064
 No use23120.322618.0
 Less than before18716.421016.7
 No change41636.650039.7
 Slightly more than before22820.126921.4
 Significantly more than before756.6544.3
Nicotine use during lockdown11061177< .0010.391
 No use52947.898883.9
 Less than before696.2443.7
 No change28625.91008.5
 Slightly more than before16014.5322.7
 Significantly more than before625.6131.1
THC use during lockdown10691185< .0010.148
 No use85980.4106489.8
 Less than before393.6282.4
 No change1009.4685.7
 Slightly more than before504.7231.9
 Significantly more than before212.020.2
Descriptive statistics and X2 results for substance use in the HRGC and LRGC

Loneliness, social support and professional assistance

Loneliness was significantly higher in the HRGC group compared to the LRGC (7.3% vs. 3.8%). The level of perceived social support did not differ significantly between both groups (see Table 4).
Table 4

Dealing with the pandemic

VariableHRGCLRGCTest statisticSignificanceEffect size
N%N%X2p-valuePhi
Loneliness (11-item De Jong Gierveld Loneliness Scale) score ≥ 16777.3453.813,005< .0010.076
Social support (OSSS-3) score ≥ 1225022.430025.02260.133
NMdn (IQR)MNMdn (IQR)MMann-Whitney-Up-valuer
Burdens of social distancing12894.00 (3.00)3.5114083.00 (2.00)3.44881,196,0.185
Meaningfulness of social distancing12845.00 (2.00)4.8814025.00 (2.00)4.77840,222,0.0020.060
Concerns about the pandemic...
 Concerns about own health12823.00 (2.00)2.9413982.00 (2.00)2.3685,748,5< .0010.208
 Concerns about the health of friends12714.00 (2.00)4.0814024.00 (2.00)3.96844,683,0.0180.045
 Concerns about own financial situation12712.00 (2.00)2.3914062.00 (2.00)2.14827,655,5< .0010.067
 Concerns about the German healthcare system12793.00 (2.00)2.8413962.00 (3.00)2.63822,044,0< .0010.070
 Concerns about the German economy12774.00 (2.00)3.9913964.00 (2.00)3.8818,631,5< .0010.072
 Concerns about the German political system12744.00 (2.00)3.9613834.00 (2.00)3.79820,626,5< .0010.060

*p < .05

**p < .01

***p < .001

Dealing with the pandemic *p < .05 **p < .01 ***p < .001 Feelings of stress associated with social distancing did not differ significantly between both groups. HRGC individuals, however, were significantly more likely to perceive government actions to encounter Covid-19 as legitimate and meaningful than LRGC participants. Generally, HRGC individuals were significantly more concerned about the pandemic than LRGC participants. Here, HRGC individuals were significantly more worried about their own health, the health of their friends, the health system in Germany, their financial situation as well as the German economic and political system than LRGC participants (see Table 4).

Factors contributing to depressive symptoms during the lockdown

Bivariate correlations showed a significant positive association between depression, anxiety, loneliness and the perceived stress level due to social distancing (see Table 5).
Table 5

Bivariate correlations of loneliness, depression and stress due to social distancing

1234
1Depression1
2Anxiety.824**1
3Loneliness.591**.477**1
4Stress due to social distancing during lockdown.406**.400**.428**1

** p < 0.01

Bivariate correlations of loneliness, depression and stress due to social distancing ** p < 0.01 Linear regression was used to identify predictors of depressive symptoms during the lockdown. Being male (β = −.025, p = .044), younger age (β = −.041, p = .001), being a HRGC individual (β = .052, p < .001), loneliness (β = .238, p < .001), lower worries about the own health (β = −.030, p = .020) as well as anxiety (β = .681, p < .001) were significantly associated with depressive symptoms during the lockdown. Perceived stress due to social distancing did not significantly predict depression (β = .014, p = 314). The overall regression was statistically significant (R2 = .732, F(7-1867) = 730,778, p < .001) (see Table 6).
Table 6

Serial logistic regression model for variables associated with depression (n = 1875)

VariableDepression (PHQ-9 Score)
βStandard errorT ValueSignificance
Gender, Male−.025.156−2.011.044
Age−.041.005−3.233.001
HRGC individual.052.1504.103<.001
Loneliness.238.02115.735<.001
Concerns about own health−.030.053−2.335.020
Anxiety (GAD-7 Score).681.01843.429<.001
Stress due to social distancing during lockdown.014.0571.007.314
Serial logistic regression model for variables associated with depression (n = 1875) Mediation analysis using PROCESS macro for SPSS 25 (IBM corp., Armonk, USA) was run to explore variables mediating the effect of being a HRGC individual on depression. All mediation analyses were controlled for age and gender as covariates. First, a parallel mediation model was run to test whether the effect of being a HRGC individual (X) on depression (Y) was mediated by concerns about own health (M1), by feelings of loneliness (M2), by stress due to social distancing (M3) or by anxiety (M4). The results of the mediation analysis (total effect: 2.02, 95% CI: 1.48-2.56; direct effect: .573, 95% CI: .278-.868) demonstrated that the indirect effects were only significant for concerns about own health (M1: CI:-.142--.009;) feelings of loneliness (M2: 95% CI:.195-.475;) and anxiety (M4: 95% CI: .815 -1.55), but not for stress due to social distancing (M3: 95% CI: −.012-.031). Based on this mediation model, a serial multiple mediation model was run. Here, mediators are linked together in a causal effect chain, with mediators allowing to influence each other (M1 (concerns about own health) → M2 (anxiety) → M3 (loneliness)). The mediation model showed that the association between Covid-19 risk group and depression was mediated by this serial mediation chain (total effect: 2.04, 95% CI: 1.49-2.57; direct effect: 95% CI: .289-.879; indirect effect: 95% CI: .055-.113) with concerns about own health being linked to anxiety and this in turn being associated with feelings of loneliness (see Fig. 2).
Fig. 2

Serial multiple mediator model. Notes: Significant indirect effect of X on Y through M1, M2 and M3 in serial (total effect: 2.04, 95% CI: 1.49-2.57; direct effect: 95% CI: .289-.879; indirect effect: 95% CI: .055-.113). Unstandardized beta coefficients are presented. For the direct effect unstandardized coefficients (before and after the mediators (in parentheses) were added to the model) are presented. Mediation analyses was controlled for gender and age. *p < .05** p < .01, *** p < .001

Serial multiple mediator model. Notes: Significant indirect effect of X on Y through M1, M2 and M3 in serial (total effect: 2.04, 95% CI: 1.49-2.57; direct effect: 95% CI: .289-.879; indirect effect: 95% CI: .055-.113). Unstandardized beta coefficients are presented. For the direct effect unstandardized coefficients (before and after the mediators (in parentheses) were added to the model) are presented. Mediation analyses was controlled for gender and age. *p < .05** p < .01, *** p < .001

Discussion

According to estimations of the RKI, 52% of all persons living in Germany aged 15 or older belong to a group at risk for severe illness from Covid-19 [32]. The proportion of individuals at increased risk for severe illness from Covid-19 (HRGC) in this study was 47% and thus remarkably higher. The primary aim of this study was to investigate differences in mental health problems (such as depression, anxiety, psychosomatic symptoms and substance use) during the Covid-19 pandemic in HRGC individuals compared to LRCG individuals. In addition, we discuss the relation of these findings in regard to the general German population. We found that 35.9% of the HRGC individuals reported moderate depressive symptoms compared to 26.6% of the LRGC individuals. The proportion of persons with at least moderate depressive symptoms in the HRGC group is remarkably higher than in the LRGC group and four times as high as in the German general population [33]. Regarding the overall rate of depression during the time of the first lockdown in Germany, rates were estimated to have increased to 14.3% (PHQ-2 score ≥ 3) in the general population [12]. Yet, more than twice as many individuals in the HRCG group reported depressive symptoms. Moreover, 29.6% of the HRGC individuals exhibited clinically relevant symptoms of a generalized anxiety disorder in the presented study, while this applies to only 21.4% of the LRGC group. Again, this rate is considerably higher than in the general German population, where the prevalence is estimated at 5,9% [34]. Several studies confirm an increase of generalized anxiety disorders during the first period of the pandemic. A German study [12] reported at least moderate symptoms of generalized anxiety disorders (GAD-7 score ≥ 10) in 16.8% of the participants, which is still a substantially lower rate than in our HRGC group. In terms of somatic symptoms 15.6% of the HRGC individuals and 7.6% of the LRGC individuals showed clinically relevant somatic symptoms in this study, compared to only 9.3% in the German general population [22]. In addition, 19.5% of the HRGC individuals and 9.7% of the LRGC individuals reported an elevated risk for suicide. Hence, the proportion of individuals with and increased risk for suicide is three times higher in the HRGC group than in the German general population [24]. Based on previous studies [19, 35] pointing to the importance of feelings of loneliness for depression, the second aim of the current study was to investigate the association of concerns about own health, anxiety, perceived loneliness, and stress due to lockdown measures with depressive symptoms. Using mediator models, we demonstrated that the direct effect of being an HRGC individual on depression was mediated by concerns about own health, anxiety and feelings of loneliness. In a serial mediation model, an indirect causal effect chain was observed showing that being an HRCG individual was related to concerns about own health, which was associated with increased feelings of anxiety and loneliness and loneliness in turn was related to higher rates of depression. These findings show that HRGC individuals appear to be more worried about their own health during the pandemic than LRGC individuals. We assume that HRGC individuals have avoided social contacts to protect themselves from Covid-19 infections. This increase in social isolation may have resulted in the observed higher rates of loneliness in HRCG individuals, which were associated with depressive symptoms. This is in line with a study by Mayerl et al. [36] showing that COVID-19-related social restrictions were associated with feelings of loneliness and predicted depressive symptoms 10 months later. Quadt et al. [37], proposed a model that perceived loneliness may initiate a cascade of complex body-brain interactions responsible for severe mental and physical health problems. The results clearly show that the mental health burden is higher among persons at increased risk of severe illness from Covid-19 compared to persons at low risk of severe illness from Covid-19. HRGC individuals are more worried about their own health and report more loneliness, anxiety and depressive symptoms. One factor that may counteract feelings of loneliness and low social connectedness is social support. Therefore, social support during lockdown periods is of utmost importance for individuals prone to mental health problems. Consequently, people at increased risk of severe illness from Covid-19 should not only be protected from a Covid infection but should also receive psychosocial support to decrease feelings of loneliness and increase feelings of social connectedness (e.g. chat-based hotlines, online communication platforms) in order to minimize negative consequences for their mental health during periods of lockdown. This is also in line with a recent study showing that greater social connectedness is associated with reduced stress and fatigue during Covid-19 related lockdown [38]. These findings underline the importance of maintaining social connections also during Covid-19 restrictions to reduce depressive symptoms in pandemic situations. This study has several limitations. Firstly, it needs to be pointed out that cross-sectional data were collected via an online survey tool, which was mainly promoted by German social service organisations. This recruitment process is likely to have caused a selection bias within the sample by primarily reaching individuals in need for advice from those organisations. Hence, the data collected is not representative of the German general population. Accordingly, representative cross-sectional samples and longitudinal data are desirable in future research. Secondly, the outcome instruments used in the survey were not entirely adapted to the time period of interest, i. e. the first lockdown in Germany. Therefore, it remains unclear whether the mental health burdens reported here changed due to the lockdown. Third, we have not measured social withdrawal directly, but only assume that concerns about own health resulted in reduced social contacts, which may explain the association with perceived loneliness.

Conclusions

This study demonstrates that the mental health burden of the Covid-19 pandemic is high. This is especially true for individuals who are at increased risk of severe illness from Covid-19. These individuals have a particular need for psychosocial support during times of lockdown. Therefore, they should be specifically supported by corresponding offers (e.g. by phone, in chats or online). Moreover, government officials should take into account the mental health consequences of measures aiming at social distancing. More research, however, is needed on possible long-term consequences of social distancing on mental health.
  27 in total

1.  Psychometric evaluation of the Generalized Anxiety Disorder Screener GAD-7, based on a large German general population sample.

Authors:  Andreas Hinz; Annette M Klein; Elmar Brähler; Heide Glaesmer; Tobias Luck; Steffi G Riedel-Heller; Kerstin Wirkner; Anja Hilbert
Journal:  J Affect Disord       Date:  2016-12-18       Impact factor: 4.839

Review 2.  The effect of loneliness on depression: A meta-analysis.

Authors:  Evren Erzen; Özkan Çikrikci
Journal:  Int J Soc Psychiatry       Date:  2018-05-23

Review 3.  Brain-body interactions underlying the association of loneliness with mental and physical health.

Authors:  Lisa Quadt; Giulia Esposito; Hugo D Critchley; Sarah N Garfinkel
Journal:  Neurosci Biobehav Rev       Date:  2020-06-28       Impact factor: 8.989

4.  [Psychometric Properties of the German Version of the Suicide Behaviors Questionnaire Revised (SBQ-R)].

Authors:  Heide Glaesmer; Nestor D Kapusta; Tobias Teismann; Birgit Wagner; Nina Hallensleben; Lena Spangenberg; Thomas Forkmann
Journal:  Psychother Psychosom Med Psychol       Date:  2017-09-28

5.  Loneliness, Mental Health, and Substance Use among US Young Adults during COVID-19.

Authors:  Viviana E Horigian; Renae D Schmidt; Daniel J Feaster
Journal:  J Psychoactive Drugs       Date:  2020-10-28

6.  Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis.

Authors:  Nader Salari; Amin Hosseinian-Far; Rostam Jalali; Aliakbar Vaisi-Raygani; Shna Rasoulpoor; Masoud Mohammadi; Shabnam Rasoulpoor; Behnam Khaledi-Paveh
Journal:  Global Health       Date:  2020-07-06       Impact factor: 4.185

7.  Population with an increased risk of severe COVID-19 in Germany. Analyses from GEDA 2019/2020-EHIS.

Authors:  Alexander Rommel; Elena von der Lippe; Marina Treskova-Schwarzbach; Stefan Scholz
Journal:  J Health Monit       Date:  2021-04-21

8.  Covid-19: risk factors for severe disease and death.

Authors:  Rachel E Jordan; Peymane Adab; K K Cheng
Journal:  BMJ       Date:  2020-03-26

9.  Social support in the general population: standardization of the Oslo social support scale (OSSS-3).

Authors:  Rüya-Daniela Kocalevent; Lorenz Berg; Manfred E Beutel; Andreas Hinz; Markus Zenger; Martin Härter; Urs Nater; Elmar Brähler
Journal:  BMC Psychol       Date:  2018-07-17

10.  Loneliness in the UK during the COVID-19 pandemic: Cross-sectional results from the COVID-19 Psychological Wellbeing Study.

Authors:  Jenny M Groarke; Emma Berry; Lisa Graham-Wisener; Phoebe E McKenna-Plumley; Emily McGlinchey; Cherie Armour
Journal:  PLoS One       Date:  2020-09-24       Impact factor: 3.240

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