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ORIGINAL RESEARCH
published: 14 March 2022
doi: 10.3389/fpubh.2022.844560
Frontiers in Public Health | www.frontiersin.org 1March 2022 | Volume 10 | Article 844560
Edited by:
Katherine Henrietta Leith,
University of South Carolina,
United States
Reviewed by:
Patricia M. Alt,
Towson University, United States
Thomas Edward Strayer III,
Vanderbilt University Medical Center,
United States
*Correspondence:
Daniel Lüdecke
d.luedecke@uke.de
Specialty section:
This article was submitted to
Aging and Public Health,
a section of the journal
Frontiers in Public Health
Received: 28 December 2021
Accepted: 18 February 2022
Published: 14 March 2022
Citation:
Lüdecke D and von dem
Knesebeck O (2022) Decline in Mental
Health in the Beginning of the
COVID-19 Outbreak Among European
Older Adults—Associations With
Social Factors, Infection Rates, and
Government Response.
Front. Public Health 10:844560.
doi: 10.3389/fpubh.2022.844560
Decline in Mental Health in the
Beginning of the COVID-19 Outbreak
Among European Older
Adults—Associations With Social
Factors, Infection Rates, and
Government Response
Daniel Lüdecke*and Olaf von dem Knesebeck
Institute of Medical Sociology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
Objective: Governments across the world have deployed a wide range of
non-pharmaceutical interventions (NPI) to mitigate the spread of COVID-19. Certain NPIs,
like limiting social contacts or lockdowns, had negative consequences for mental health
in the population. Especially elder people are prone to mental illnesses during the current
pandemic. This article investigates how social factors, infections rates, and stringency of
NPIs are associated with a decline in mental health in different European countries.
Methods: Data stem from the eighth wave of the SHARE survey. Additional data sources
were used to build macro indicators for infection rates and NPIs. Two subsamples
of persons with mental health problems were selected (people who reported being
depressed, n=9.240 or nervous/anxious, n=10.551). Decline in mental health was
assessed by asking whether depressive symptoms or nervousness/anxiety have become
worse since the beginning of the COVID-19 outbreak. For each outcome, logistic
regression models with survey-design were used to estimate odds ratios (OR), using
social factors (age, gender, education, living alone, and personal contacts) and macro
indicators (stringency of NPIs and infection rates) as predictors.
Results: Higher age was associated with a lower likelihood of becoming more
depressed (OR 0.87) or nervous/anxious (OR 0.88), while female gender increased the
odds of a decline in mental health (OR 1.53 for being more depressed; OR 1.57 for
being more nervous/anxious). Higher education was only associated with becoming
more nervous/anxious (OR 1.59), while living alone or rare personal contacts were not
statistically significant. People from countries with higher infection rates were more likely
to become more depressed (OR 3.31) or nervous/anxious (OR 4.12), while stringency of
NPIs showed inconsistent associations.
Conclusion: A majority of European older adults showed a decline in mental health
since the beginning of the COVID-19 outbreak. This is especially true in countries with
high prevalence rates of COVID-19. Among older European adults, age seems to be a
Lüdecke and von dem Knesebeck Decline in Mental Health
protective factor for a decline in mental health while female gender apparently is a risk
factor. Moreover, although NPIs are an essential preventative mechanism to reduce the
pandemic spread, they might influence the vulnerability for elderly people suffering from
mental health problems.
Keywords: COVID-19, mental health, social factors, elder people, NPI, depression, anxiety
INTRODUCTION
The new coronavirus infection (COVID-19), first discovered in
December 2019 in Wuhan City, China, has spread worldwide.
Accordingly, the World Health Organization (WHO) officially
declared the outbreak as international public health emergency
(1). COVID-19 is a severe respiratory infection with high
infection rate and relatively high mortality, in particular when
medication or vaccination was not available. Consequently,
governments across the world have deployed a wide range of
non-pharmaceutical interventions (NPIs) to mitigate the spread
of COVID-19. The responses to COVID-19 in different countries
varied from herd immunity strategies, which implied only few
or almost no measures, to more assertive approaches based
on the implementation of a wide range of stringent NPIs (2,
3). The prevalence of COVID-19 affected the stringency of
NPIs implemented in different countries. However, countries
undertaking more strict measures were also able to contain the
pandemic outbreak. Thus, there were both great variations in
the stringency of government responses and infection rates of
COVID-19 between countries worldwide (4,5).
One of the main goals of the various NPIs was to protect risk
groups who are particularly vulnerable to COVID-19. Especially
old age was highlighted early as a risk factor for adverse outcomes
of a COVID-19 infection and is one of the most important
determinants of mortality (6,7). Studies suggest that the odds of
in-hospital deaths increase by a factor of 1.1 per year of age (8).
The downside of certain NPIs, such as limiting social contacts,
gathering restrictions, or short- and medium-term lockdowns,
is an increased risk of negative consequences for mental health
in the population. Again, especially the older population is a
risk group that is prone to mental illnesses during the current
pandemic (9,10).
Mental health is not only affected by limited social contacts
and lockdowns. Rather, widespread occurrences of infectious
diseases in general, and of COVID-19 in particular, are closely
related to symptoms of psychological distress and affected mental
health (11). In a survey among the Chinese population, 37.1%
of the elderly had experienced depression and anxiety during
the pandemic (12,13). Studies about previous experiences
with outbreaks of infectious diseases also have found that the
proportion of people who are mentally affected by a pandemic
is higher than people who are physically infected. In this regard,
depressive feelings, anxiety and fear were common adverse effects
(14,15).
It is known that social factors such as social contacts and
relationships, serve as protective buffers that lower the risk
of morbidity and mortality (16). Furthermore, social networks
have a positive impact on mental health (17). However, the
psychological distress for the general population caused by the
COVID-19 pandemic and its government response measures is
not fully understood yet. International studies mostly focus on
the mental health impact of infected quarantined patients and
rarely on government response measures in general (18).
Against this background, this article addresses the following
research questions: (1) What is the prevalence of a decline
in mental health in different European countries during the
COVID-19 pandemic? (2) What are the associations of social
factors (gender, age, education, and social contacts) with a decline
in mental health? (3) Do the associations vary according to
infection rates and government response measures?
MATERIALS AND METHODS
Sample and Participants
Analyses were based on data from the eighth wave of SHARE,
the Survey of Health, Aging, and Retirement in Europe (19).
SHARE is a large pan-European social science panel study.
The first wave of data collection started in 2004, including 12
countries. New waves of data collection were repeated every 2–
3 years. Refresher samples were drawn to compensate for panel
attrition. In total, about 530,000 interviews with people from 28
European countries and Israel were conducted. Topics covered
in the interviews are, among others, social networks, physical
and mental health, employment, retirement, financial situation,
and social activities. The wave of 2020 was the first one that
included data on the pandemic outbreak and was carried out
in 27 countries. Based on population registers, SHARE used
probability samples within the countries and includes non-
institutionalized adults aged 50 years or older and, if available,
their partners. Exclusion criteria were: being incarcerated, moved
abroad, unable to speak the language of questionnaire, deceased,
hospitalized, moved to an unknown address or not residing
at sampled address (20,21). The outbreak of the COVID-19
pandemic hit the data collection in the middle of the 8th
wave, thus fieldwork was suspended and a specific COVID-19
questionnaire was developed to collect data with pandemic
related topics. The fieldwork for this survey started in June 2020
and ended in September 2020.
The final SHARE sample consisted of N=46.500 participants
from 27 countries. As we were interested in the decline of mental
health, we only considered those respondents who previously
reported being depressed and/or being nervous or anxious
(see measures). Thus, for the present study, two subsamples
of persons with mental health problems were selected (people
Frontiers in Public Health | www.frontiersin.org 2March 2022 | Volume 10 | Article 844560
Lüdecke and von dem Knesebeck Decline in Mental Health
who reported being depressed, n=9.240 or nervous/anxious,
n=10.551).
Additional Data Sources
Additional data sources were used to build two macro indicators.
The stringency in government response toward the COVID-19
outbreak was based on the Oxford COVID-19 Government
Response Tracker (OxCGRT), a global panel database of
pandemic policies that covered more than 180 countries (22). For
each country at each day of the pandemic, measures to reduce the
spread of the outbreak, like longer or stricter lockdown measures,
reduced social contacts, and similar, were recorded and a daily
index of government response for each country (stringency
index) was calculated. Countries with higher stringency index
have undertaken more intensive measures to reduce the spread
of COVID-19. Data was filtered to include only those countries
that were also present in this survey.
Data on numbers of confirmed cases of people infected with
COVID-19 were taken from the COVID-19 Data Repository
by the Center for Systems Science and Engineering (CSSE) at
the Johns Hopkins University (23). Data on confirmed cases
are collected from more than 190 countries. Based on these
data, the percentage of the population infected with COVID-19
was calculated. Again, only data from countries that were also
included in this survey was used.
Both data sources were continuously updated and thereby
reflected the evolution of infection rates and government
measures during the pandemic. To adequately represent the
situation in the participants’ countries at the time of the
SHARE fieldwork, only those data for government response and
confirmed cases that referred to the period from the beginning
of the COVID-19 outbreak until the time of field work in each
SHARE country was used (i.e., summer 2020).
Measures
Dependent Variables
Mental health problems were assessed by asking “In the last
month, have you been sad or depressed?.” If answered yes,
a person is considered as “depressed.” Similarly, people were
considered as being nervous or anxious if they answered “yes” to
the question “In the last month, have you felt nervous, anxious, or
on edge?.” Decline in mental health was then assessed by asking
those respondents who were depressed or nervous/anxious,
whether that has “been more so, less so, or about the same as
before the outbreak of Corona?.” The variable was dichotomized.
The option “more so” was considered as decline in mental health,
“less so” and “about the same” refers to no decline in mental
health. Both mental health indicators were recoded this way.
Independent Variables
Social factors included in the regression models are respondent’s
age, gender, education, whether they lived alone in their
household and personal contacts. Education was based on the
International Standard Classification of Education (24), which
ranges from 0 to 6 (low to higher education) and is recoded
into three levels: “low (lower/upper secondary),” “mid (post-
secondary),” and “high (tertiary).” Personal contacts describe the
intensity of contacts that respondents had with family and friends
from outside their home since the outbreak of COVID-19. The
question was “Since the outbreak of Corona, how often did you
have personal contact, that is, face to face, with the following
people from outside your home? Was it daily, several times a
week, about once a week, less often, or never?.” People were asked
to respond to this question with regard to their (a) children,
(b) parents, (c) other relatives, and (d) neighbors, friends, or
colleagues. Rare personal contacts are present if the respondents
had personal contacts less than once a week in relation to all of
the four groups.
The stringency in government response toward the
COVID-19 outbreak and the percentage of the population
infected with COVID-19 were used as macro indicators in the
regression models. For each country, the mean value for the daily
Oxford stringency index values, from the start of the pandemic
until the beginning of the fieldwork, was calculated. This variable
represents the average government response within each country
to the COVID-19 outbreak and has a possible range from 0 to
100 (22). Based on the distribution of this variable, an indicator
was built, with countries being classified into three groups: low
stringency (average Oxford stringency index <40), middle
stringency (index between 40 and 45) and high stringency
(index >45). The proportion of the population infected with
COVID-19, which was calculated based on the data from the
COVID-19 Data Repository, refers to the cumulative percentage
from the beginning of the pandemic until the start of the SHARE
data collection in each country (i.e., summer 2020).
Statistical Analysis
Descriptive statistics were used to document the sample
characteristics. For each of the two dependent variables
indicating decline in mental health, three logistic regression
models for complex samples were calculated, using quasi-
binomial links to properly account for survey-weighting,
disproportional sampling, and selective mortality. The country
variable was used to define the strata in the survey-design, hence
the regression models accounted for the fact that respondents
were clustered within different countries. Robust Horvitz-
Thompson standard errors are reported (25). The first model
only included social factors, the second model only included the
two macro indicators, and the third (full) model included both
social factors and macro indicators. Models were checked for the
presence of multicollinearity. All models had a variance inflation
factor (VIF) below 2.8, indicating no severe collinearity issues
(26). All analyses were performed using the R statistical package
(27), including the packages “survey” (28), “ggplot2” (29), and
“parameters” (30).
RESULTS
Classification of Stringency and COVID
Infection Rates
Each of the country classifications “low stringency,” “middle
stringency,” and “high stringency” included nine countries (see
Table 1). The average stringency index for low stringency
countries varied from 34 to 39. Latvia, Slovenia and Bulgaria
Frontiers in Public Health | www.frontiersin.org 3March 2022 | Volume 10 | Article 844560
Lüdecke and von dem Knesebeck Decline in Mental Health
TABLE 1 | Average stringency index (SI) and percentage of COVID infections in the population by country, based on data from the Oxford COVID-19 Government
Response Tracker and the COVID-19 Data Repository from CSSE.
Low stringency countries (SI <40) Middle stringency countries (SI 40–45) High stringency countries (SI >45)
Country Average SI COVID
infections, %
Country Average SI COVID
infections, %
Country Average SI COVID
infections, %
Bulgaria 38 0.08 Austria 41 0.22 Belgium 45 0.52
Denmark 39 0.21 Czech Republic 40 0.09 Croatia 47 0.60
Estonia 35 0.15 Germany 43 0.23 Cyprus 47 0.11
Finland 37 0.13 Greece 44 0.03 France 51 0.30
Latvia 38 0.06 Hungary 41 0.04 Israel 50 0.19
Luxembourg 38 0.66 Lithuania 43 0.06 Italy 56 0.39
Slovenia 39 0.07 Netherlands 43 0.29 Malta 47 0.12
Sweden 34 0.53 Poland 44 0.07 Romania 46 0.11
Bulgaria 38 0.36 Slovakia 42 0.03 Spain 47 0.52
had rather low COVID-19 infection rates of 0.06, 0.07, and
0.08%, respectively. Countries with a middle stringency had a
mean stringency index from 40 to 44. Overall, these countries
showed the lowest COVID-19 infection rates from all three
stringency classifications. High stringency countries had an
average stringency index ranging from 45 to 56. The proportion
of people infected with COVID-19 ranged from 0.11 to 0.60%,
and overall, these countries had the highest infection rates.
Sample Description
Characteristics of the subsample of respondents who reported to
be depressed or sad (n=9,240) is shown in Table 2. The mean
age of respondents was 72.3 years. 19.3% had high education.
70.0% were female. 36.5% of the participants mentioned that they
had rare personal contacts. A share of 32.3% were living alone.
63.0% reported that they felt more depressed since the beginning
of COVID-19.
Table 3 shows the characteristics of people who reported to be
nervous and/or anxious. Their average age was 71.3 years. 37.9%
were higher educated and 67.1% were of female gender. Rare
personal contacts were reported by 37.8% of the respondents.
26.5% were living alone. 71.6% mentioned being more nervous
and/or anxious since the pandemic outbreak.
Factors Associated With Feeling More
Depressed Since the COVID-19 Outbreak
Looking at the regression model with social factors included
as predictors (model 1, see Table 4), higher age was associated
with a lower likelihood of becoming more depressed (OR 0.87).
Female respondents were more likely to feel more depressed
since the outbreak (OR 1.50). Middle or higher educated persons,
compared to people with low educational level, were less likely to
feel more depressed (OR 0.61), although only middle education
was statistically significant. People who lived alone in their
household had a lower chance of feeling more depressed (OR
0.79). Rare personal contacts were not significantly associated
with feeling more depressed. Regarding the model with macro
indicators (model 2), in comparison to countries with low
stringency index, respondents from countries with middle
stringency index were less likely to feel more depressive after
the COVID-19 outbreak (OR 0.66). The likelihood of feeling
more depressed for people from countries with high stringency
index, however, was higher in comparison to the low stringency
countries (OR 1.37). An increased rate of people infected with
COVID-19 was also associated with a higher chance of feeling
more depressed (OR 3.24). In the full model (model 3), in
which both social factors and macro indicators were included,
most associations remained very similar compared to the first
two models. The most noticeable change was related to the
association with education, which has diminished in model 3.
Factors Associated With Feeling More
Nervous and/or Anxious Since the
COVID-19 Outbreak
In model 1 (see Table 5), feeling more nervous/anxious
was less likely when respondents were older (OR 0.87).
Female gender was associated with a higher likelihood of
feeling more nervous/anxious (OR 1.54). The probability
of feeling more nervous/anxious is higher for people with
high education as compared to people with low education
(OR 1.34). No statistically significant associations were found
for middle education (OR 1.08), living alone (OR 0.99),
and rare personal contacts (OR 1.07). While the stringency
index was not significantly associated with feeling more
nervous/anxious (model 2), the rate of people infected with
COVID-19 significantly increased the chance of feeling more
nervous/anxious (OR 3.95). In model 3, most associations
remained similar compared to the first two models, with
an exception for education. The likelihood of feeling more
nervous/anxious increased with medium and higher education.
DISCUSSION
The present study sought to describe the prevalence of decline
in mental health among elderly persons in Europe during the
COVID-19 pandemic and to analyse the associations of social
Frontiers in Public Health | www.frontiersin.org 4March 2022 | Volume 10 | Article 844560
Lüdecke and von dem Knesebeck Decline in Mental Health
TABLE 2 | Sample description of respondents reporting depressive symptoms, SHARE data (8th wave), unweighted.
Country NMean age
(SD)
High
education, %
Female
gender, %
Rare personal
contacts, %
Living
alone, %
More
depressed, %
Low stringency countries (SI <40)
Bulgaria 174 71.2 (9.1) 14.9 69.0 20.8 35.1 58.0
Denmark 203 71.7 (9.5) 42.3 70.9 33.0 37.4 62.6
Estonia 691 74.6 (9.7) 21.4 74.4 42.2 43.7 61.2
Finland 210 71.1 (9.7) 35.7 69.0 39.8 26.2 59.5
Latvia 137 71.6 (9.8) 24.8 73.0 45.9 47.4 45.3
Luxembourg 208 70.2 (8.5) 17.5 66.3 45.2 22.6 72.1
Slovenia 412 73.6 (9.3) 13.6 70.6 34.5 26.2 52.4
Sweden 221 75.8 (8.0) 38.2 65.6 25.7 41.6 69.7
Switzerland 326 73.5 (9.4) 17.8 70.9 46.6 38.3 70.6
Total 2,582 73.1 (9.4) 23.3 70.8 38.2 36.1 61.5
Middle stringency countries (SI 40–45)
Austria 316 75.3 (9.2) 26.0 73.1 33.5 42.4 52.8
Czech Republic 418 73.4 (8.0) 12.9 76.1 30.7 39.7 50.5
Germany 626 71.4 (9.5) 30.9 66.0 29.9 33.5 53.2
Greece 719 72.2 (10.1) 13.8 68.3 30.6 34.4 74.0
Hungary 167 72.2 (7.6) 17.2 70.7 26.9 39.5 41.9
Lithuania 327 71.9 (10.3) 33.6 70.6 50.8 36.4 63.0
Netherlands 108 72.4 (9.1) 36.7 74.1 37.4 49.1 71.3
Poland 613 69.4 (9.4) 11.9 67.2 34.0 21.7 42.6
Slovakia 192 66.3 (8.6) 5.2 64.1 35.1 22.9 49.5
Total 3,486 71.6 (9.5) 19.8 69.3 33.5 33.6 56.0
High stringency countries (SI >45)
Belgium 439 71.2 (9.6) 35.3 72.0 36.2 40.8 82.5
Croatia 296 71.0 (8.9) 11.1 67.2 28.6 24.3 56.4
Cyprus 92 75.0 (9.6) 7.6 79.3 56.0 37.0 69.6
France 529 73.7 (9.8) 28.2 73.9 34.9 41.2 67.5
Israel 164 74.6 (8.8) 26.4 68.9 41.5 34.8 73.2
Italy 722 72.2 (9.5) 7.2 68.1 39.6 19.3 77.0
Malta 212 70.5 (8.9) 2.8 66.5 69.8 17.9 78.8
Romania 326 69.9 (9.6) 3.4 69.3 42.9 21.5 58.6
Spain 392 75.2 (9.0) 9.9 70.4 23.7 19.6 76.0
Total 3,172 72.4 (9.5) 15.6 70.2 38.3 27.9 71.9
All countries
Total 9,240 72.3 (9.5) 19.3 70.0 36.5 32.3 63.0
factors, infection rates and government response measures with
a decline in mental health.
Summary of Main Findings
One finding was that the majority of older adults, who reported
depressive symptoms or being nervous and/or anxious, showed
a decline in mental health since the beginning of the COVID-19
pandemic. This holds true for respondents across all European
countries. Although the proportion of people with a decline
in mental health was higher in countries where the social life
was affected by strict government response measures, even in
countries with a milder response a majority of respondents
reported an increase in depressive symptoms, nervousness, and
anxiety. Regarding social factors, we found that increasing age
and female gender were associated with a lower chance of a
decline in mental health, while we found inconsistent or no
associations for education, rare personal contacts and living
alone. In terms of the macro indicators, there were positive
associations with the proportion of infections in the population,
but inconsistent results related to the stringency index.
Interpretation
Although the concrete impact of the COVID-19 pandemic
on mental health is not yet fully understood, studies from
former comparable outbreaks that required social restrictions
or lockdown measures confirmed that the challenges and stress
associated with such NPIs could trigger mental disorders,
especially anxiety and depressive symptoms (11,31). This
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Lüdecke and von dem Knesebeck Decline in Mental Health
TABLE 3 | Sample description of respondents reporting being nervous and/or anxious, SHARE data (8th wave), unweighted.
Country NMean age
(SD)
High education,
%
Female
gender, %
Rare personal
contacts, %
Living alone,
%
More
nervous/anxious, %
Low stringency countries (SI <40)
Bulgaria 241 70.5 (9.3) 14.1 63.9 20.4 29.0 53.1
Denmark 398 69.5 (8.7) 49.4 65.6 41.5 24.4 81.4
Estonia 813 72.6 (9.2) 23.6 69.6 42.2 35.2 69.6
Finland 268 69.3 (9.0) 47.4 64.6 37.1 23.9 60.4
Latvia 215 70.5 (9.5) 22.3 73.0 45.5 34.9 67.4
Luxembourg 239 68.8 (8.0) 18.3 62.8 43.5 20.1 80.3
Slovenia 529 72.4 (9.3) 17.0 69.9 38.4 23.4 66.0
Sweden 267 74.0 (8.5) 42.5 67.0 25.9 36.7 76.4
Switzerland 302 72.1 (9.0) 18.9 71.5 51.0 30.5 80.5
Total 3,272 71.4 (9.1) 27.6 68.0 39.3 29.2 70.7
Middle stringency countries (SI 40-45)
Austria 285 74.3 (9.1) 22.6 69.5 34.0 31.2 67.4
Czech Republic 432 73.2 (7.9) 14.7 75.2 29.6 34.5 66.9
Germany 531 69.9 (9.2) 32.6 65.5 31.5 26.7 71.8
Greece 992 71.6 (10.0) 17.5 64.7 37.0 28.3 83.3
Hungary 169 71.6 (7.2) 17.6 67.5 29.2 31.4 45.6
Lithuania 413 70.3 (10.3) 34.4 71.4 51.1 32.0 74.3
Netherlands 104 71.9 (8.7) 23.3 71.2 35.6 31.7 86.5
Poland 509 69.0 (9.1) 12.2 63.5 36.8 16.5 49.7
Slovakia 182 64.7 (8.2) 6.0 56.6 32.4 15.9 55.5
Total 3,617 70.9 (9.5) 20.6 67.0 36.0 27.4 69.6
High stringency countries (SI >45)
Belgium 536 70.5 (9.6) 36.1 67.9 36.6 36.0 84.1
Croatia 342 70.0 (8.5) 15.3 63.5 32.1 19.0 64.3
Cyprus 109 73.1 (9.7) 12.8 75.2 54.6 26.6 65.1
France 575 72.7 (9.6) 25.9 72.7 33.3 36.3 73.6
Israel 213 74.4 (8.6) 29.1 70.4 39.8 28.2 72.3
Italy 767 71.1 (9.5) 6.6 61.8 39.3 14.6 77.7
Malta 332 69.2 (8.7) 4.5 63.0 64.8 14.8 78.0
Romania 347 68.3 (8.9) 2.3 61.1 39.8 15.3 61.4
Spain 441 75.3 (8.9) 9.5 69.6 24.0 18.6 77.3
Total 3,662 71.5 (9.4) 15.9 66.4 38.3 23.3 74.5
All countries
Total 10,551 71.3 (9.4) 37.9 67.1 37.8 26.5 71.6
included both, an increase in the prevalence of disorders as
well as worsening mental health (18). Beyond the impact of
NPIs on mental health, the fear of serious health consequences
might exert a further negative influence on mental well-being.
The fact that especially older people were at higher risk for
adverse health outcomes due to COVID-19 might explain why—
compared to surveys that also included younger populations—
we found a higher proportion of decline in mental health,
which did not only occur in countries with strict government
response measures. This is in line with studies that showed the
negative psychological impact of the pandemic on the older
population due to increased morbidity and mortality risks (13,
32). In our study, we used infection rates of a population and
the stringency index as two indicators on a macro level that
reflect the pandemic threat and the rigidity of NPIs and found
links between those indicators and a decline in mental health.
Populations’ infection rates were strongly positively associated
with feeling more depressed and more nervous/anxious. This can
be explained with the health concerns of elderly people, who
were a particular risk group for adverse COVID-19 related health
outcomes. The perceived threat of the pandemic increased with
higher proportions of infected cases in the population. This fear
was in particular present in risk groups such as older people (33).
We found no evidence that the government response measures,
indicated by the stringency index, were associated with feeling
more nervous and/or anxious. Feeling more depressed, however,
was more likely for respondents living in countries with higher
stringency index. Studies that analyzed the impact of lockdown
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Lüdecke and von dem Knesebeck Decline in Mental Health
TABLE 4 | Feeling more depressed since pandemic outbreak, survey-weighted logistic regression models, showing odds ratios (OR), 95% confidence intervals (CI), and
significances (p).
Predictors Model 1 Model 2 Model 3
OR CI POR CI POR CI P
Age 0.87 0.78–0.97 0.011 0.87 0.78–0.97 0.012
Female gender 1.50 1.16–1.95 0.002 1.53 1.17–1.99 0.002
Education: low (ref.) 1.00 – – 1.00 – –
Education: middle 0.61 0.46–0.81 0.001 0.96 0.73–1.26 0.750
Education: high 0.73 0.52–1.01 0.058 1.01 0.72–1.41 0.973
Living alone 0.79 0.64–0.98 0.033 0.84 0.69–1.03 0.094
Rare personal contacts 1.06 0.82–1.37 0.640 0.96 0.73–1.27 0.796
SI: low (ref.) 1.00 – – 1.00 – –
SI: middlea0.66 0.53–0.82 <0.001 0.64 0.51–0.79 <0.001
SI: highb1.37 1.10–1.71 0.005 1.32 1.05–1.66 0.019
% COVID-19 cases 3.24 1.61–6.49 0.001 3.31 1.66–6.59 0.001
Observations 9,017 9,017 9,017
aMiddle stringency countries (reference: low stringency countries).
bHigh stringency countries (reference: low stringency countries).
TABLE 5 | Feeling more nervous/anxious since pandemic outbreak, survey-weighted logistic regression models, showing odds ratios (OR), 95% confidence intervals (CI),
and significances (p).
Predictors Model 1 Model 2 Model 3
OR CI POR CI POR CI P
Age 0.87 0.78–0.97 0.015 0.88 0.79–0.98 0.025
Female gender 1.54 1.20–1.99 0.001 1.57 1.21–2.02 0.001
Education: low (ref.) 1.00 – – 1.00 – –
Education: middle 1.08 0.81–1.43 0.615 1.37 1.03–1.80 0.028
Education: high 1.34 0.97–1.84 0.077 1.59 1.15–2.19 0.005
Living alone 0.99 0.79–1.23 0.926 1.01 0.81–1.26 0.929
Rare personal contacts 1.07 0.82–1.40 0.608 1.06 0.80–1.41 0.689
SI: low (ref.) 1.00 – – 1.00 – –
SI: middlea1.05 0.86–1.29 0.622 1.06 0.86–1.30 0.593
SI: highb0.96 0.78–1.19 0.730 1.10 0.87–1.38 0.434
% COVID-19 cases 3.95 2.01–7.74 <0.001 4.12 2.15–7.91 <0.001
Observations 10,306 10,306 10,306
aMiddle stringency countries (reference: low stringency countries).
bHigh stringency countries (reference: low stringency countries).
measures and comparable NPIs also reported negative mental
health consequences. A longitudinal study from South Africa
showed that the prevalence of depression and anxiety symptoms
was higher during the time of social restrictions (34). Another
study from Israel indicated that such measures were the main risk
factor for depression and anxiety (35).
According to our results, increasing age was associated with
a lower chance of a decline in mental health. This seemed to
be somewhat counter intuitive given that in particular elderly
people were one of the most vulnerable risk groups related to
COVID-19 and their emotional response toward the pandemic
outbreak was more apparent than in younger age groups (13,
36). Research on this topic revealed inconclusive results. While
a documentary analysis indicated that mental health in older
people was negatively affected by social restriction measures,
another recent study found that adherence to such measures was
not associated with a decline in mental health. One explanation
might be that a key issue that serves as protective factor could be
the social connectedness whose positive impact was rated higher
than the negative impact of COVID-19 related worries (37,38).
A clear association was found between gender and decline
in mental health, with female persons being more likely
to be affected. This is in line with previous research that
described significantly higher scores of psychological distress for
female gender during the pandemic (13). One study reported
significantly larger increase in depressive symptoms for female
Frontiers in Public Health | www.frontiersin.org 7March 2022 | Volume 10 | Article 844560
Lüdecke and von dem Knesebeck Decline in Mental Health
persons (37). A meta-analysis on the prevalence of depression
and anxiety among COVID-19 patients also showed higher
proportions of female patients being affected. However, the total
effect of gender was not statistically significant (39).
The associations of education and decline in mental health
differed between the two subgroups of respondents who were
more depressed and those who felt more nervous and/or anxious.
In the models with social factors only, higher education showed
weak evidence for a lower probability of decline in mental
health. In the full model, the association between education and
feeling more depressed diminished, while we found a significant
positive association between higher education and feeling more
nervous and/or anxious. The latter result was supported by
other research results. Recent longitudinal studies on the change
of mental health in the course of COVID-19 showed that a
higher educational level was associated with increases in mental
health problems (40). A reason might be that higher educated
persons may feel greater concerns about the consequences
of COVID-19, which was also reported in a study from
the US (41).
Regarding social relations, living alone was associated
with feeling more sad or depressed, but this association
diminished after controlling for the macro indicators. We
did not find clear associations for living alone and feeling
more nervous and/or anxious. Rare personal contacts were
not statistically significant in any model. Although studies
showed a positive impact of social contacts on mental health
(17), other findings suggested that there was no clear link
between social contacts and nervousness and anxiety for older
individuals (42). An explanation for the inconsistent associations
between social relations and decline in mental health could
be that older persons experience less life changes due to the
pandemic, making social contacts more important for younger
generations (43).
Limitations
Some methodological limitations have to be considered that
affect the interpretation of the findings. First, the SHARE data
only provides some rather crude measures of decline in mental.
An advantage of the mental health indicators we used is that
they refer to acute and very recent mental health problems.
On the other hand, it depends on a subjective perception of
feeling depressed, nervous or anxious and is not measured by
a validated assessment instrument for mental health disorders.
Furthermore, the mental health indicators we used may only
reflect a temporary condition and no longer lasting disorder.
Nevertheless, we decided to use this indicator as it allowed
us to measure a decline of mental health problems since the
COVID-19 outbreak using cross-sectional data.
Another limitation is related to the measures of social
relations, which might explain the inconsistent or unclear
associations in our results. Only frequency of personal contacts,
not telephone or digital contacts were assessed. Additionally,
as rare personal contacts and living alone only refer to the
quantitative dimension of social relations, they do not reflect
qualitative or functional aspects. Furthermore, due to the age
range in the sample, which defines older adults as persons aged
50 and older, respondents in the SHARE survey were a very
heterogeneous group.
Finally, it is also important to mention that data collection was
carried out in an early stage of the pandemic. Thus, our study
refers to a rather short-term impact of NPIs on mental health,
which might result in an underestimation of the associations
between government measures and mental health. In addition,
the impact of a pandemic outbreak on mental health is often
influenced by many different factors. For instance, we could
not include measures such as job security, loneliness, or other
psycho-social factors. Nonetheless, one of the strengths of this
study is the combination of a large dataset on an individual level
combined with very well-prepared data on a macro level from
other sources, which allowed us to gain more specific insights
into the complex associations of social factors, infection rates,
government response, and decline in mental health.
CONCLUSIONS
A majority of European older adults, who reported depressive
symptoms or being nervous and/or anxious, showed a decline
in mental health since the beginning of the COVID-19
pandemic. This holds especially true in countries with high
prevalence rates of COVID-19. Among older European adults,
age seems to be a protective factor for a decline in mental
health while female gender apparently is a risk factor.
Moreover, looking at government response measures, we
conclude that, despite those NPIs being an essential preventative
mechanism to reduce the pandemic spread, they might influence
the vulnerability for elderly people suffering from mental
health problems.
DATA AVAILABILITY STATEMENT
Publicly available datasets were analyzed in this study. This data
can be found at: The SHARE data is available for research purpose
after registering at the SHARE website (www.share-project.org).
Data from the Oxford COVID-19 Government Response Tracker
(OxCGRT) is freely available at https://github.com/OxCGRT/
covid-policy-tracker. The COVID-19 Data Repository stores
data on COVID cases and is located at https://github.com/
CSSEGISandData/COVID-19. All websites were lastly accessed
on 9 February 2022.
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by Ethics Council of the Max Planck Society. The
patients/participants provided their written informed consent to
participate in this study.
AUTHOR CONTRIBUTIONS
DL and OK developed the research questions. DL prepared,
analyzed and interpreted the data, and drafted and finalized
the manuscript. OK substantially contributed to interpreting the
Frontiers in Public Health | www.frontiersin.org 8March 2022 | Volume 10 | Article 844560
Lüdecke and von dem Knesebeck Decline in Mental Health
data, drafting the manuscript, and critically revised and approved
the final manuscript. All authors contributed to the article and
approved the submitted version.
FUNDING
The SHARE data collection was primarily funded by the
European Commission through FP5 (QLK6-CT-2001-00360),
FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-
2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7
(SHARE-PREP: N◦211909, SHARE-LEAP: N◦227822, SHARE
M4: N◦261982). Additional funding from the German Ministry
of Education and Research, the US National Institute on
Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291,
P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-
11, OGHA_04-064) and from various national funding sources
is gratefully acknowledged (see www.share-project.org, last
accessed 27 December 2021).
ACKNOWLEDGMENTS
This article uses data from SHARE Wave 8. Please see (20) for
methodological details. Source code to replicate the results is
available in R format at https://osf.io/stja8/.
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Conflict of Interest: The authors declare that the research was conducted in the
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