European Journal of Ageing
https://d0i.0rg/l 0.1007/sl 0433-021 -00649-z
ORIGINAL INVESTIGATION
Lonely societies: low trust societies? Further explanations for national
variations in loneliness among older Europeans
Grazina Rapoliene1
• Marja Aartsen2
®
Accepted: 5 July 2021
©The Author(s) 2021
Abstract
Cross-national studies in Europe reveal sharp regional differences in the prevalence of loneliness among older adults, with
the highest prevalence of loneliness in Eastern European countries. In this study, we investigate an alternative explanation
for differences in loneliness prevalence based on differences in trust. Many of the Eastern European countries were ruled by
totalitarian regimes that undermined people's trust in other people and in the system, potentially leading to higher loneliness
prevalence. Data are derived from the sixth round of the European Social Survey conducted in 2012, based on 12,042
respondents, of which 4827 live in post-totalitarian countries and 7215 in other European countries and Israel. We estimate a
path model with trust in people, trust in the system, and social engagement included as latent variables and one dichotomous
outcome (lonely or not). We control for age, gender, health limitations, marital status, income adequacy, and education.
The results reveal that loneliness is partly constructed by the social-cultural and historical-political characteristics of the
countries in which people live. The higher prevalence of loneliness in the Eastern-European post-totalitarian countries can
be linked to a low level of trust in other people through social disengagement. Considering the role of trust in the creation
of individuals feelings of loneliness contributes to the understanding of country variations in loneliness and opens a new
perspective in loneliness research and the development of policies aimed at reducing loneliness.
Keywords Loneliness • Trust • Old age • Social engagement • Post-totalitarianism • Eastern and Central Europe
Introduction
Loneliness is a negative experience that occurs when there is
a discrepancy between desired and achieved levels of social
contact (Perlman and Peplau 1982). Research has shown the
significance of loneliness for health because of the harmful
impact on mental and physical health (Cornwell and Waite
2009), weakening of cognitive functions and the increased
risk of dementia in older age (Shankar et al. 2013), attempts
at suicide (Waern et al. 2003), and increased mortality (HoltLunstad
et al. 2015). However, the risk of being lonely is
unequally distributed across countries, with the smallest
Responsible Editor: Matthias Kliegel
S3 Marja Aartsen
Grazina Rapoliene
g.rapoliene@gmail.com
1
Lithuanian Centre for Social Sciences, Vilnius, Lithuania
2
Norwegian Social Research, Oslo Metropolitan University,
Oslo, Norway
Published online: 16 September 2021
share of lonely older people in Northern Europe (up to 6%)
and the largest shares in Russia and Eastern Europe (10-34%
in different age groups) (Yang and Victor 2011; Hansen and
Slagsvold 2015). While loneliness is most prevalent among
the oldest old, the rates of lonely young people in Eastern
European countries are higher than the rates of lonely old
people in Western European countries (Yang and Victor
2011). The increasing number and share of older people
in contemporary societies and the unequal distribution of
loneliness across countries make loneliness research among
older adults a relevant scientific and public health topic. This
study aims to shed more light on differences in loneliness
prevalence between European countries.
Previous studies have pointed towards possible mechanisms
behind cross-national differences in loneliness prevalence
among older adults. Fokkema et al. (2012) suggest
that the geographical divide in loneliness prevalence might
be largely attributable to the demographic composition of
countries—e.g. gender differences in life expectancy and
variations in the share of widows. Others argue that loneliness
is more common among the disadvantaged—i.e.
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European Journal of Ageing
those with lower socio-economic status, poorer health, and
without partner (Hansen and Slagsvold 2015)—which may
explain why Western European countries have lower loneliness
prevalence than Eastern and Central European countries.
Yet others suggest that country differences in loneliness
prevalence could be attributed to cultural differences in
relationship expectations in individualistic countries (often
Northern European) versus collectivistic countries (often
Southern European) (Jylha and Jokela 1990; Dykstra 2009).
Studies estimating the strength of the associations in multivariable
models indicate that cultural differences in relationship
expectations are associated with loneliness, but only
partially (Lykes and Kemmelmeier 2014; Swader 2018).
The question this study seeks to answer is whether the
higher prevalence of later life loneliness in Eastern and
Central European countries can be (partly) attributed to the
lower levels of trust in these countries. As part of the Eastern
Bloc, Eastern and Central European countries were under
the influence of the Soviet regime until 1991, when the
Soviet Union collapsed and communist parties lost authority
in Eastern and Central Europe. The Soviet regime can
be dated back to the revolution of 1917, or even to 1914 and
World War I, when it became possible to implement a Marxist
programme for the reorganization of society (Hobsbawm
2000). To be more precise, due to terror and repressions
of Stalin, the social reality in the Soviet Union was purely
authoritarian from 1929 to 1953, and in Central Europe from
1948 to 1953. This totalitarian regime was maintained under
Khrushchev (1954-1964) and Brezhnev (1964-1982), but
without the terror that characterized Stalin's regime (Norkus
2008). Despite decades having passed since the collapse of
the Soviet Union, contemporary psychologists studying
trauma conclude that the experience of living under a totalitarian
regime is still insufficiently discussed in the public
realm (Gailiene 2008). This lack of public discussion and
the nature of the trauma may explain why even twenty years
after the fall of the Soviet Union, in 2011, trust was not yet
restored (Sapsford et al. 2015). Older people are the most
impacted by the Soviet regime, as they spent most of their
lives under these circumstances.
Fundamental shattering of (basic) trust—in oneself,
in others, and in the world—can be caused by violence
(Endress and Pabst 2013). Violence here is understood in a
broad sense as negation of sociality (including forced labour,
military drills, suppression of free expression, structures of
political and juridical discrimination, ethnical or cultural
stigmatization) and traumatic experiences. The totalitarian
Soviet regime was built on violence and fear and characterized
by deportations, political persecutions, and the
total surveillance of private lives (Anusauskas et al. 2005;
Courtois et al. 2000), which drove out not only trust in the
state, but also trust in other people. No sphere of social life
was free from state control as the distinction between the
public and the private sphere lost its meaning in Marxist
societies (Norkus 2008). Even some thirty years later, posttotalitarian
states are still characterized by low levels of trust
in the public realm alongside higher levels of trust in the
private networks (Sapsford et al. 2015; Schrader 2004).
Not many studies among older adults have explicitly
investigated the association between trust and loneliness,
but there are reasons to expect such a relation. Psychodynamic
theories about loneliness (Fromm Reichmann 1959;
Hojat 1987) point at the relevance of childhood experiences
in the genesis of loneliness. People are born with a need for
contact and tenderness, but if this longing for intimacy is not
satisfied because of a lack of love, loneliness arises. Similarly,
the interactionist perspective on loneliness entails that
if an attachment figure is absent, loneliness arises (Weiss
1973). Based on a review of theories on loneliness, Ernst
and Cacioppo further suggest that insecure attachment that
started in childhood accumulates over the years as those
infants fail to develop age-appropriate social skills that hinders
attachment to other people (Ernst and Cacioppo 1999).
The current generation older people in former totalitarian
states were disproportionately exposed to violence in their
childhood, which coincided with the peak of the violent
totalitarian regimes, which disrupted emotional bonds.
Therefore, higher loneliness prevalence may be expected in
(former) totalitarian states.
We are aware of a few experimental studies on the relationship
between trust and loneliness with college students
(Rotenberg 1994) and younger people aged 5-21 years
(Rotenberg et al. 2010). These psychosocial studies indicated
that loneliness is inversely related to different types of
trust (Rotenberg 1994). This association is mediated, in part,
by social disengagement, i.e. a lack of integration in social
networks and relationships (Rotenberg et al. 2010). Nyquist
and others evaluated associations between trust and loneliness
in older people from a sociological perspective. Based
on Putnam's definition of social capital, they identify trust as
one of the indicators of social capital and conclude that low
social capital, especially in terms of low trust, is a risk factor
for loneliness (Nyquist et al. 2016). We therefore expect
trust to be a key explanatory factor for the higher prevalence
of loneliness in many of the Eastern European countries.
The theoretical model of our study (Fig. 1) is based on a
series of assumptions derived from relevant theories. First,
we argue that state violence, typical for totalitarian regimes,
has shattered trust (Endress and Pabst 2013). Following Luhmann
(1968), we distinguish between two interrelated types
of trust: personal or generalized trust and systemic trust, or
trust in institutions. Based on the social-ecological model
discussed in work by Holt-Lunstad (2018), we further expect
a direct effect of the type of state on loneliness. Second,
trust is considered a key concept in theories about social
engagement, either as a proxy of social capital (Coleman
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European Journal of Ageing
Generalized trust
Fig. 1 Theoretical model depicting the assumed associations between trust, social engagement, and loneliness
1988; Putnam 2000; Endress 2012, 2014; Carpiano 2006)
or as a factor contributing to social engagement (Lin 1999).
Trust is crucial for social engagement (Rotenberg et al.
2010; Cottrell et al. 2007; Ernst and Cacioppo 1999), and
when social engagement is deficient, loneliness occurs. In
sum, our hypothesis is that violence diminishes trust, which
increases the likelihood of loneliness directly and through
diminished social engagement. Post-totalitarian states are
characterized by low trust, and therefore, the prevalence of
loneliness is higher in post-totalitarian states compared to
non-post-totalitarian states.
Empirical evidence for the different parts of the model
comes from various studies. Fenger (2007) observed a strong
connection between welfare regime and levels of trust, with
the lowest levels of trust in post-communistic states, and
the highest levels of trust in social democratic states (i.e.
Scandinavian countries). Recent studies observed an inverse
relation between levels of trust and feelings of loneliness
in older Dutch people (Van Tilburg et al. 2020) and older
Finnish people (Nyqvist et al. 2016). There is substantial
evidence for an inverse relation between social engagement
and loneliness among older Germans (Luhman and Hawkley
2016), older English people (McHugh Power et al. 2019),
and older Swedish men (Dahlberg et al. 2015). Empirical
evidence for a causal effect of social engagement on trust
comes from a study by Jennings and Stoker (2004), who
observed based on long-term panel data on three generations
of Americans that trust is a cause rather than a consequence
of social engagement.
Data and method
Data are derived from the European Social Survey (ESS).
The ESS is a biennial cross-national survey that has been
conducted across Europe since 2001 (https://www.europ
eansocialsurvey.org/about/). One of the aims of the study
is to chart stability and change in social structure, conditions,
and attitudes in Europe and to interpret how Europe's
social, political, and moral fabric is changing. The study
includes questions on attitudes, beliefs, trust, and behaviour
in many European countries and Israel. For our study, we
selected the most recent round with the highest number of
post-totalitarian countries, and information about loneliness,
which was round six (2012). Round six had 29 participating
countries, of which 12 were post-totalitarian, whereas round
seven (2014) had only 21 countries, six of which were posttotalitarian.
The total, unweighted sample of people aged
65 or older in round six comprised 12,042 respondents, of
which 4827 live in post-totalitarian countries. For descriptive
purposes, we used both the unweighted and weighted
sample (Table 1). The analytical model (Fig. 2) was evaluated
with the weighted dataset only. In line with the recommendations
of the European Social Survey (ESS 2014),
we used the post-stratification weight in combination with
the population size weights. Respondents with incomplete
information on the endogenous variables in the path model
are included in the analyses as estimates are based on the
robust maximum likelihood (MLR) estimator that is part of
Mplus, which allows missingness without leading to biased
estimations of the parameters (Muthen and Asparouhov
2002). Respondents with missing information on exogenous
variables in the path analyses are excluded by default. This
applies to 1.2% (N= 188) of the study sample. All variables
included in the analytical model are depicted in Fig. 2.
Dependent variable
Loneliness is measured with a single question: Please tell me
how much of the time during the past week... youfelt lonely?
Answering categories are none or almost none of the time
(1), some of the time (2), most of the time (3), all or almost
all of the time (4). As we are interested in the prevalence of
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European Journal of Ageing
Table 1 Loneliness prevalence in 2012 by European countries plus
Israel, and post-totalitarianism
Unweighted sample Weighted sample*
Countries N Prevalence (%) N Prevalence (%)
Post-totalitarian European countries
Albania 192 28.12 31 19.45
Bulgaria 711 26.02 144 19.47
Czechia 389 23.65 156 21.96
Estonia 602 16.28 24 15.25
Hungary 390 24.1 165 23.93
Lithuania 511 18.98 51 16.56
Poland 342 18.13 571 18.26
Russian Federa- 432 31.71 1810 28.55
tion
Slovenia 263 14.45 34 14.37
Slovakia 373 16.62 68 14.43
Ukraine 471 36.09 579 29.24
Kosovo 151 18.54 10 11.59
Subtotal 4827 23.14 3641 25.43
Other European countriesand Israel
Belgium 385 13.77 206 14.39
Switzerland 306 4.25 133 4.58
Cyprus 237 18.14 11 15.03
Germany 665 5.11 1604 6.15
Denmark 388 4.12 101 5.01
Spain 371 12.13 738 11.5
Finland 540 7.59 103 7.71
France 534 18.54 1166 14.63
United Kingdom 664 8.73 1067 6.04
Ireland 529 5.29 49 4.14
Israel 450 12.89 82 13.85
Iceland 120 2.5 4 2.63
Italy 187 14.97 1202 16.39
Netherlands 479 7.52 255 5.8
Norway 277 2.17 67 1.87
Portugal 646 18.11 202 13.27
Sweden 437 6.41 176 6.24
Subtotal 7215 9.79 7168 10.23
Total 12,042 15.14 10,809 15.35
*In line with recommendations of the European Social Survey (ESS
2014), we used the post-stratification weight in combination with the
population size weights (pspwght*pweight). Source: European Social
Survey, Round 6 (2012)
loneliness, we recoded the answering categories 1 and 2 into
0 (not lonely) and categories 3 and 4 into 1 (lonely).
Independent, intermediate variables and controls
The participating countries were coded 1 (post-totalitarian
countries) or 0 (other countries). The post-totalitarian
countries were Albania, Bulgaria, Czech Republic,
Estonia, Hungary, Lithuania, Poland, Russian Federation,
Slovenia, Slovakia, Ukraine, and Kosovo. The other
countries were Belgium, Switzerland, Cyprus, Germany,
Denmark, Spain, Finland, France, UK, Ireland, Israel, Iceland,
Italy, Netherlands, Norway, Portugal, and Sweden.
Generalized trust in people is operationalized as a latent
variable based on the following three questions: Generally
speaking, would you say that most people can be trusted,
or that you can't be too careful in dealing with people?
Do you think that most people would try to take advantage
of you if they got the chance, or would they try to
be fair? And Would you say that most of the time people
try to be helpful or that they are mostly looking out for
themselves? Answering categories range from 1 (indicative
of no or low trust) to 10 (indicative of high trust). The
latent variable trust in the system is based on answers on
the following three questions: Please tell me on a score of
0-10 how much you personally trust each of the following
institutions: (1) [country]'s parliament, (2) the police,
and (3) politicians. Answering categories range from 0
(no trust at all) to 10 (complete trust). Social engagement
is also operationalized as a latent variable and reflects
engagement with other people and wider society. Social
engagement has three indicators: (1) meeting socially with
friends, relatives, or work colleagues, (2) involvement in
voluntary work or work for charitable organizations in the
past 12 months, and (3) providing help and support to people
they feel close to when they need it. Meeting socially is
an ordinal variable with seven categories, ranging from 1
(never) to 7 (everyday). Involvement in voluntary work is
an ordinal variable with six categories, which we recoded
into 1 (never), 2 (once per year), 3 (two times per year),
4 (every three months), 5 (once a month), and 6 (once
a week or more often). Support provision was measured
with a seven-point Likert scale ranging from 0 (not at all)
to 6 (completely).
Control variables were gender, age, health limitations,
widowhood, divorced, living alone, income adequacy, and
education. Gender is a dichotomous variable with male (1)
and female (2). Age is the number of years alive. Health
limitations are assessed with a question asking whether
people find themselves hampered in daily activities by illness,
disability, infirmity, or mental problems, with answering
categories "Yes, a lot" (1), "Yes, to some extent" (2), and
"No" (3). The legal marital status was used to construct three
dummy variables widowhood, divorced, and never married.
Code 1 was used if the condition applied, the 0 otherwise. To
improve the comparison between countries, we use income
adequacy rather than absolute income. Income adequacy
expresses how well people think their income is adequate
for their present life, with categories "Living comfortably on
present income" (1), "Coping on present income" (2), "Difficult
on present income" (3), and "Very difficult on present
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European Journal of Ageing
ß=-0.25
Post-
totalitarian
state (y/n)
1.00* 1.05 1.04
ß=0.39
~t
r= 0.49
Trust in
•
Take
^ *
People are
people advantage helpful
ß=-0.26
= 0.12 H
Gender (ns), age (ns), health
limitations(OR=0.57), widowed
(OR=5.16), divorced (OR=4.47),
never married (ns), income
adequacy(OR=1.31), education
ns)
1.00 1.27 0.82
Trust in
parliament
Trust in
police
Trust in
politicians
Social
meetings
Voluntary Provided
work support
Fig. 2 Analytical model and estimated statistics for the associations between the key concepts in our model. A dashed line represents a nonsignificant
association. Note: * Fixed to 1.00, OR = odds ratio, ns = not significant
income" (4). All other answers (refusal, no answer, don't
know) were coded as missing. For education, we used the
International Standard Classification of Education (ISCED)
with seven levels, ranging from "less than lower secondary"
(1) to "higher tertiary education" (7). All other values (other,
refusal, don't know, no answer) were coded as missing.
Statistical approach
We first describe loneliness prevalence among 65+ people in
the participating countries for the weighted and unweighted
sample. Next, we estimate the analytical model (Fig. 2) to
test the hypothesized associations between the key concepts
in our theoretical model. The model includes a dichotomous
outcome variable loneliness and a dichotomous variable
post-totalitarian country. It further includes continuous
latent mediators (generalized trust, trust in the system, and
social engagement). The control variables gender, age, marital
status, health limitations, income adequacy, and education
are manifest variables and included in the last step of
the estimation of the path model.
A path model with latent variables consists of a measurement
part (the estimation of the latent variables) and
a structural part (series of linear and logistic regressions
to describe the associations between the variables and the
total direct and indirect effects). The latent variables are
continuous variables that are inferred from the observed
variables, similar to factor analysis. In our model, we
have three indicators for each latent variable. If the fit of
the measurement part was satisfactory according to criteria
defined by Hu and Bentler (1999) (i.e. CFI>0.95;
RMSEA<0.06; SRMR < 0.08), the whole model including
the measurement model and the structural model was
estimated in the next step. Since we are interested in the
loneliness prevalence, we dichotomized the dependent variable
loneliness, which implies that the estimated weights
for the associations between the variables in the model
and loneliness are odds ratios (ORs). For all structural
associations, the standardized and unstandardized association
was estimated, as well as the 99% confidence interval
(CI). A regression weight is significant, if the 99% CI
does not include 1 (for ORs) or 0 (for Bs and Betas). The
model is estimated with the maximum likelihood estimator
with robust standard errors (MLR) using the Monte
Carlo integration algorithm with 500 integration points.
M L R parameter estimates are robust to non-normality and
non-independence of observations (Muthen and Muthen
1998-2015).
The estimation of our model was done with Mplus 8.4 in
three subsequent steps. In the first step (Model 1), we estimated
the basic model with type of state as sole independent
variable and loneliness as dependent variable, to provide an
estimation of the overall effect of type of state on the chance
to be lonely. In the second step, we added the latent mediators
trust in people, trust in the system, and social engagement
to evaluate the hypothesized pathways (Model 2). In
the final model, we added a number of control variables
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European Journal of Ageing
to check whether the direct and indirect effects of state on
loneliness were maintained if we additionally controlled for
factors known to be associated with loneliness (Model 3).
Results
The prevalence of loneliness among the older population
is the highest in post-totalitarian European countries
(Table 1). The average percentage of lonely people is 23 in
post-totalitarian countries, and 10 in other European countries
(unweighted data). The percentage of lonely people
in post-totalitarian countries is the lowest in Slovenia (14),
Estonia (16), and Slovakia (17), and the highest in Ukraine
(36) and Russia (32). For the non-post-totalitarian states,
we find the lowest percentages of lonely older people in
Norway (2) and Iceland (2), and the highest percentages
in France (19), Cyprus (18), and Portugal (18).
The fit indices of the measurement model including the
three latent variables were all far below the cut-off indicating
that the measurement model fitted the data very
well (CFI = 0.98; R M S E A = 0.04; SRMR = 0.03). Next,
we added the structural paths (in Fig. 2 shown as oneheaded
arrows) between the variables. We also included
a residual correlation (in Fig. 2 shown as curved two-way
arrows) between the two latent variables trust in the system
and trust in people, to take into account the potential
interrelatedness, and to control for the effect of unknown
confounding variables (MacCallum et al. 1993).
Table 2 shows the estimates of the three structural models:
only country effects (Model 1), full model without
control variables (Model 2), and full model with control
variables (Model 3). Model 1 indicates that the odds that
a person in a post-totalitarian European country is lonely
is 2.99 times higher compared to people living in other EU
countries (OR = 2.99, p< 0.01). Type of state (post-totalitarian
versus other types of country in Europe) explains
8% of the variation in loneliness. Model 2 shows that part
of the state effect on loneliness is explained by the level of
social engagement as the OR becomes smaller (OR = 1.89,
/?<0.01). There is a direct negative effect of the type of
state on trust in the system and trust in other people. People
in post-totalitarian countries have lower levels of trust
in other people (B = — 0.80, p < 0.01) and lower levels
of trust in the system (B = - 1.08, p < 0.01) than people
from non-post-totalitarian countries. Social engagement is
inversely associated with loneliness (OR = 0.15,/?<0.01),
indicating that the more socially integrated people are,
the less likely they feel lonely. In turn, social engagement
is partly explained by trust in people and trust in the system,
with trust in people having a larger effect (fl = 0.37,
/?<0.01) than trust in the system (/? = 0.18, /?<0.01).
There is no direct effect of trust in people or trust in the
system on loneliness, but there is an inverse indirect effect
of trust in people and trust in the system on loneliness
through social engagement, indicating that higher levels
of trust are associated with higher levels of social engagement
and, consequently, with lower levels of loneliness
(unstandardized total indirect effect B of general trust on
loneliness is - 0.47, p<0.01 and B=-0.23, p<0.01 for
trust in the system). Type of country, trust in people, and
trust in the system additionally explain 28% of the variation
in loneliness. Adding to Model 2, the control variables
gender, age, health limitations and partner status, income
adequacy, and education (Model 3) resulted in a loss of
significance for the direct effect of state on loneliness and
the indirect effect of trust in the system on loneliness. In
other words, the effect of type of state and trust in the system
on loneliness can be attributed to variations in health
limitations, partner status, income adequacy, and education
between the two types of countries. All other associations
remained significant.
Discussion
The research question of our study was whether the higher
prevalence of loneliness in older age in post-totalitarian
Eastern and Central European countries could be (partly)
attributed to the lower levels of trust in other people and in
the system. We hypothesized that the levels of trust in people
and in the system are inversely associated with loneliness,
both directly and through altered levels of social engagement.
Our results are mainly in line with our expectations.
The loneliness prevalence in post-totalitarian countries is
with 23% substantially higher than in other European countries,
where the average loneliness prevalence is 10%. We
observed that generalized trust and trust in the system are
significantly lower in the post-totalitarian countries than in
other countries. Trust in other people and trust in the system
are inversely associated with loneliness through lower
levels of social engagement, but only the indirect effect of
trust in people remains significant after controlling for age,
gender, health limitations, partner status, income adequacy,
and education.
We further observed that differences in loneliness prevalence
can be attributed to the higher number of widowers in
Eastern European countries, which is in line with findings
by Fokkema and colleagues (Fokkema et al. 2012), and to
socio-economic factors such as income adequacy, education,
and health limitations, which is in line with the study
by Hansen and Slagsvold (2015). Contrary to the findings
of Rotenberg (1994), we found that trust was not directly
associated with loneliness. While this may indicate potential
differences between younger and older people, it may also
be caused by a different operationalization and measurement
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Table 2 Path analyses of loneliness (yes/no) regressed on EU-region, social engagement, trust in the system and trust in people controlling for gender, age, income, education, health limitations,
widowhood, divorce, and never married (N= 11,854)
Model 1 Model 2 Model 3
OR 99% CI p B Beta OR 99% CI P B Beta OR 99% CI P
Post-totalitarian state-> Loneliness (1 =yes, 0 = no)* 2.99 2.41 3.71 0.00 1.89 132 2.69 0.00 1.21 0.79 1.86 0.31
Direct effects
State-> Generalized trust -0.80 -0.23 -1.04 0.56 0.00 -0.82 0.25 -1.04 -0.61 0.00
State-> Trust in the system -1.80 -0.28 -1.31 0.85 0.00 -1.04 0.26 -1.27 -0.80 0.00
Social Engagement (SE)-> Loneliness 0.08 0.02 0.25 0.00 0.32 0.14 0.75 0.00
Generalized Trust (GT)-> Loneliness 1.00 0.82 1.23 0.98 0.94 0.79 1.13 0.40
Trust in the system (TS)-> Loneliness 1.08 0.93 1.26 0.21 1.03 0.90 1.17 0.64
Generalized trust (GT)—> Social engagement -0.12 -0.37 0.08 0.16 0.00 0.15 0.39 0.09 0.20 0.00
Trust in the system-> Social engagement -0.05 -0.18 0.02 0.08 0.00 0.04 0.12 0.00 0.08 0.01
Indirect effects
GT-> SE-> Loneliness -031 -0.22 -0.47 0.14 0.00 -0.17 0.12 -0.29 -0.04 0.00
TS-> SE-> Loneliness -0.13 -0.10 -0.23 0.02 0.00 -0.17 0.04 -0.10 0.01 0.05
Residual correlation
Generalized trust with trust in the system (correlation) 0.47 0.42 0.53 0.00 0.49 0.43 0.54 0.00
Control variables
Educations Loneliness 0.93 0.85 1.03 0.02
Income adequacy-> Loneliness 1.31 1.05 1.63 0.01
Gender-> Loneliness 1.10 0.76 1.60 0.51
Age-> Loneliness 1.00 0.98 1.03 0.99
Health limitations-> Loneliness 0.57 0.46 0.70 0.00
Widowhood-> Loneliness 5.16 3.40 7.84 0.00
Never married-> Loneliness 1.60 0.79 3.09 0.18
Divorced-> Loneliness 4.47 2.50 8.01 0.00
Explained variance loneliness (R2) 0.08 0.36 0.34
Significant coefficients at p < .01 are printed in bold
European Journal of Ageing
of trust and loneliness, capturing different aspects. While
we used measures of trust in the system and general trust in
people, Rotenberg applied interpersonal trust scales for peer
relations. Furthermore, Rotenberg used the revised 20-item
U C L A loneliness scale (Russell et al. 1980), whereas we
used a single question to assess loneliness.
The strength of our study lies in the inclusion of former
totalitarian states, which revealed the importance of trust
for loneliness research and loneliness interventions. Based
on theories about trust and social cohesion or social engagement
and insights derived from previous research among
children and youth, we innovatively connect loneliness with
generalized trust in people and trust in the system. The study
contributes to current understanding of the construction of
loneliness by showing an association between trust and loneliness
in different social-cultural environments. Hence, in
addition to well-known individual-level risk factors, loneliness
can be considered as being constructed by macro-social
factors—such as an environment that is favourable for social
engagement—that depends on the historical-political context
and lies outside the scope of individual control. Trust in
loneliness research introduces a new perspective, different
from the cultural individualism versus collectivism perspective
as studied by Swader (2018) or Lykes and Kemmelmeier
(2014). Trust is associated with politics and history, and
hence, the seemingly individual and subjective aspects of
loneliness are deeply rooted in a much broader social fabric.
Trust also connects loneliness research and political studies,
as generalized social trust is associated not only with loneliness,
but with confidence in political institutions and satisfaction
with democracy (Zmerli and Newton 2008; Uslaner
2002), as well as with economic inequality and corruption
(Rothstein and Uslaner 2005; Freitag and Biihlmann 2009).
Limitations
The quantitative approach and questions about feeling lonely
and trust used in the ESS do not give specific information
about the conceptions of people and what they actually mean
while answering the questions about loneliness (social, emotional,
existential) or trust (trust as taking risks, habitual,
or other). Questions such as which mode of trust is most
important for social engagement, which type of loneliness
is reduced by what mechanism, or whether level of trust
influences cultural expectations (standards) with respect to
loneliness remain unanswered. Moreover, the assessment
of loneliness is based on the single question, "Do you feel
lonely?", which may generate socially desirable answers
as people do not like to admit that they feel lonely (Victor
et al. 2005). However, empirical data show that classifying
respondents as lonely when they are often or always
lonely as we do in our study is remarkable similar for single
questions and aggregated scales (Victor et al. 2005), which
limits the potential underestimation of loneliness.
Another limitation is that the ESS is a repeated crosssectional
study. While our reasoning is that the difference
in loneliness prevalence is caused by low social engagement
and diminished trust typical of post-totalitarian
countries, reversed causality between trust, social engagement,
and loneliness cannot be ruled out. For example,
lonely people may actively distance themselves from
social engagement, leading to even stronger distrust of
other people (Newall et al. 2009). Moreover, our focus was
on differences between countries, which left possible variations
within countries undetected. There are most likely
also regional or ethnic variations within countries, and
levels of trust may be patterned according to region or ethnicity
(Abascal and Baldasarri 2015). Cross-national longitudinal
studies that take into account potential regional
and/or ethnical variations are required to investigate the
causal order of the key concepts trust, social engagement
and loneliness, and within-country variations in these
relations.
Finally, we cannot fully rule out alternative explanations
for the associations between post-totalitarian regime and
loneliness prevalence. While we control for a number of
alternative explanations (e.g. differences in demographics,
health, economy, and education), there may still be factors
other than trust mediating the relationship between living in
a post-totalitarian regime and the risk of loneliness.
Conclusions
Lack of trust in other people and in the system (parliament,
police, and politicians) is an essential precondition for loneliness.
While trust cannot be directly linked to loneliness, it
is linked through the reduction in social engagement, which
is in turn associated with higher risk of loneliness. Since
levels of trust vary greatly across European countries, social
policies to reduce loneliness should be sensitive to the specifics
of particular countries and taken seriously the level of
trust people have in the system and in other people. In order
to improve the effect of loneliness interventions, a long-term
approach is advised, with generalized trust and trust in the
system stimulated or developed before loneliness interventions
are introduced.
Acknowledgements The authors gratefully acknowledge the financial
support provided by COST Action CA15122 ROSEnet funded by the
EU Framework Programme for Research and Innovation Horizon 2020,
which enabled this study to be drafted during Grazina Rapoliene's
Short Term Scientific Mission at NOVA. Marja Aartsen was supported
by a grant from the Research Council of Norway (Grant no. 299859),
based on the GENDER-NET Plus Joint Call on Gender and UN Sustainable
Development Goals (Project number GNP-187-FULL).
Springer
European Journal of Ageing
Authors'contributions Both authors contributed equally to the article.
We also thank anonymous reviewers for their helpful comments to
improve the quality of the text.
Funding Open access funding provided by OsloMet - Oslo Metropolitan
University. This work was supported by COST Action CA15122
ROSEnet, funded by the EU Framework Programme for Research and
Innovation Horizon 2020, which enabled this study to be drafted during
Grazina Rapoliene's Short Term Scientific Mission at NOVA. Marja
Aartsen was supported by a grant from the Research Council of Norway
(Grant no. 299859), based on the GENDER-NET Plus Joint Call
on Gender and UN Sustainable Development Goals (Project number
GNP-187-FULL).
Availability of data and material ESS data are open access.
Declaration
Conflict of interest The authors declare that there are no conflicts of
interest.
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,
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copy of this licence, visit http://creativecommons.Org/licenses/by/4.0/.
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