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ORIGINAL INVESTIGATION
Onset of loneliness in older adults: results of a 28 year
prospective study
Marja Aartsen •Marja Jylha
¨
Published online: 5 February 2011
The Author(s) 2011. This article is published with open access at Springerlink.com
Abstract The goal of this research is to test whether
often observed correlates of loneliness in older age are
related to onset of loneliness longitudinally. Despite the
increasing number of longitudinal studies, the investigation
of factors that are related to onset of loneliness is still
limited. Analyses are based on data of the TamELSA
study, which is a population-based prospective study in
Tampere, Finland and started in 1979. For the present study
469 older adults aged between 60 and 86 years at baseline,
who were not lonely at baseline, were selected and fol-
lowed-up in 1989, 1999 and 2006. During the 28 years of
follow-up approximately one third (N=178) of the study
population developed feelings of loneliness. Logistic
regression analyses indicated that losing a partner, reduced
social activities, increased physical disabilities, increased
feelings of low mood, uselessness and nervousness, rather
than baseline characteristics, are related to enhanced feel-
ings of loneliness at follow-up. The higher incidence of
loneliness among women can be fully explained by the
unequal distribution of risk factors among men and women
(e.g., women more often become widowed). Our results are
in line with the cognitive approach that conceptualizes
loneliness as an unpleasant feeling due to a perceived
discrepancy between the desired and the achieved level of
social and personal resources.
Keywords Correlates of loneliness Older age
Introduction
Images of aging often include loneliness as a key charac-
teristic of older age. However, the majority of scientific
studies in this field indicate that the prevalence of severe
loneliness (i.e., those who often feel lonely) among older
people is relatively low, ranging from 3% in Nordic
countries to approximately 30% in southern European
countries (Jylha
¨and Jokela 1990). Yet, due to the adverse
health consequences such as increased depression (Caci-
oppo et al. 2006) or increased likelihood of nursing home
admissions (Russell et al. 1997), loneliness is nevertheless
a relevant public health issue. Insight into factors that are
associated with an increased risk of becoming lonely may
reveal important information to our understanding of
loneliness and to the design of interventions to prevent or
reduce loneliness.
There is a growing body of knowledge about factors that
are associated with loneliness in older age such as living
alone (Wenger et al. 1996), quality of the relationship with
children (Long and Martin 2000), socio economic status
(Pinquart and So
¨rensen 2001), quality of the marriage (De
Jong Gierveld et al. 2009), self-efficacy (Fry and Debats
2002), personality (Solano et al. 1982; Newall et al. 2009),
cognition (Martin et al. 1997), self-perceived health (Kaasa
1998), and cultural norms and values (Jylha
¨and Jokela
1990) (see for a meta analysis Pinquart and So
¨rensen
2001). Also genetic factors have been found to increase the
risk of loneliness (Boomsma et al. 2005). Results on gender
differences in loneliness are still inconclusive, but as far as
they have been detected they are generally small (De Jong
Gierveld 1998, Dykstra and De Jong Gierveld 2004; Stokes
Communicated by Hans-Werner Wahl.
M. Aartsen M. Jylha
¨
School of Public Health, University of Tampere,
Tampere, Finland
M. Aartsen (&)
VU University Amsterdam, Faculty of Social Sciences,
De Boelelaan, 1081 1081HV, Amsterdam
e-mail: m.j.aartsen@vu.nl
123
Eur J Ageing (2011) 8:31–38
DOI 10.1007/s10433-011-0175-7
and Levin 1986), and may be the consequence of the
unequal distribution of risk factors across men and women
(Pinquart and So
¨rensen 2001; Victor et al. 2005). Previous
research thus revealed a wide range of factors, also referred
to as the personal and social resources of the individual (De
Jong Gierveld 1998).
Longitudinal studies on loneliness suggest that losing
social and personal resources, for example increasing dis-
ability and decreasing social integration (Jylha
¨2004), and
the loss of a partner (Dykstra et al. 2005), lead to enhanced
levels of loneliness. The acknowledgement of the impor-
tance of losing personal and social resources for the indi-
vidual’s feelings of loneliness shows similarities with ideas
by Hobfoll (1989,2001) who argues that social resources
are important for well-being. People therefore strife to
obtain and protect personal resources. Losing resources is
disproportionately more influential on level of well-being
than gaining resources (Hobfoll 2001).
The present study seeks to investigate the impact of
baseline levels of a wide range of social and personal
resources, and losses in these resources, on the onset of
loneliness in older age. In accord with previous ideas and
findings about loneliness we expect that negative changes
(or losses) in resources increase the risk of becoming
lonely at follow-up. Next to this, we will investigate to
what extent gender differences can be explained in terms of
a differential exposure to risk factors across men and
women. The selection of resources included in this study is
based on review studies by De Jong Gierveld (1998) and
Pinquart and So
¨rensen (2001) and obviously on the avail-
ability of information in the dataset.
Methods
Data
Data were derived from the Tampere Longitudinal Study
on Aging (TamELSA), which started as part of the World
Health Organization’s (WHO) Eleven Country Study on
Health Care in 1979 (Heikkinen et al. 1983; Waters et al.
1989). The sample and procedures have been described
in more detail elsewhere (Jylha
¨et al. 1992). In short,
TamELSA is a longitudinal prospective study starting in
1979, with follow-up measures in 1989, 1999 and 2006.
Individuals, aged between 60 and 89 years at baseline,
were randomly selected from the population register of
Tampere in Finland, stratified to gender and 5 year birth
cohorts. The baseline sample consisted of 1,059 individuals
of which 49.8% was male, representing 82 percent of the
initially approached persons. In 1989, a second measure-
ment round was conducted and 435 (of which 40.2% were
men) of the baseline sample could be re-interviewed. The
third measurement was conducted in 1999, among 123
survivors (33.3% men) and the forth measurement was
conducted in 2006 among 51 survivors (27.5% men). In
addition, a new sample (N=395) of 208 men and 187
women aged between 60 and 69 years old, drawn from the
Tampere population register was added to the study in
1989. In 1999, 275 (47.3% men), and in 2006, 200 (45.0%
men) individuals could be re-interviewed.
Logistic regression with stepwise selection of predictors
revealed that 28 years survival was related to younger age,
better self rated health and female gender. Loneliness, level
of education, and marital status were not related to sur-
vival. For the 18 year survival in the new cohort the same
predictors were observed. In addition to younger age, better
self rated health and female gender, also being married at
baseline positively influenced survival. All interviews were
conducted face-to-face at the homes of the respondents,
except for the data collection in 2006, when interviews
were conducted by telephone. Questions on the study
variables were asked in the same way at all four waves.
Study sample
For the present study, a sub-sample (N=469) of partici-
pants who were not lonely at baseline, and who had at least
one follow-up measure was used. Data of both cohorts
were merged by measurement cycle, not measurement
year, and analyzed together. At first follow-up, 463
(96.5%) of the 469 participants and at the second follow-up
304 (42.5%) participants could be re-interviewed. At third
follow-up 31 participants were re-interviewed (6.5%). The
large difference in participant numbers between the third
and fourth measurement is mainly due to the later inclusion
of the new cohort, for which only three measurement
rounds were conducted.
Measurements
Loneliness
Loneliness is measured by a single question ‘do you feel
lonely’ with response categories often, sometimes, never
and don’t know. For the analyses, the variable was recoded
into three categories, i.e., never (1), sometimes (2) and
often (3). People who answered the question about feelings
of loneliness with ‘‘don’t know’’ (n=11) were removed
from the analysis since we were not sure whether this
answer indicated some loneliness, the presence of memory
problems or other reasons. Onset of loneliness was defined
to be present at the first, second or third follow-up if a 1 or
2 points increase (increase from not lonely to sometimes or
often lonely) on the loneliness index occurred. Once the
32 Eur J Ageing (2011) 8:31–38
123
onset was defined, changes in loneliness in the subsequent
follow-ups were not taken into account.
Covariates
Baseline measures and changes in partner status, having
friends, being socially active, self rated health, physical
disabilities, mood, nervousness, irritability and feelings of
uselessness were included in the analytical models as
potential risk factors for the onset of loneliness. Partner
status was recoded into three categories; living with partner
(1), never married, divorced or separated, hereafter referred
to as living alone (2) and widowed (3). Having friends is
measured with the question ‘‘Do you have any good
friends’’ with answering categories yes (1) and no (2).
Being socially active was based on the combination of five
questions about participation during the past 12 months in
the following activities; family ceremonies, going to the
theatre, library visits, attending religious services, and
traveling to a foreign country. Answering categories ranged
from 0 (never) to 9 (9 times or more). Based on what has
been done in an earlier study with this dataset (Jylha
¨2004),
a sum score of all activities was calculated with equal
weights for all activities except family ceremonies, for
which the score was halved. The respondent’s social
activity was rated as high (1) if the sum score of all
activities was higher than 3, moderate (2) if the sum score
was 2 or 3, and low (3) if the sum score was 0 or 1. Self-
perceived health was assessed with the question ‘‘How
would you evaluate your present health’’ with answering
categories fairly good to very good (1), average (2), and
fairly bad to bad (3). Physical disabilities were based on 4
questions concerning basic physical activities of daily liv-
ing (ADL) (able to using toilet, washing, dressing, and
incontinence problems) and 2 questions concerning
instrumental activities of daily living (iADL) (cooking and
light household tasks). If no disabilities were reported on
any of the activities, physical disability was evaluated as
absent (1). If disabilities with the performance of at least
one iADL, and one ADL were reported, physical disabili-
ties were rated as moderate (2). Disabilities with at least
two ADL functions were rated as severe physical disabil-
ities (3).
The 2 week prevalence of low mood, irritability, and
nervousness was assessed with the following questions; ‘‘In
the last two weeks, have you suffered from low spirits or
depression’’, ‘‘…irritability or bursts of anger’’, and
‘‘ …nerves tensions or nervousness’’, respectively. Each
question was recoded into three categories: no (1), some-
times (2), and often to nearly constantly (3). Feelings of
uselessness were assessed with the question ‘‘Do you feel
unnecessary?’’ with answering categories never (1),
sometimes (2), and often (3). Irritability, nervousness and
feelings of uselessness were only measured in 1979, 1989
and 1999 so participants of the 1979 cohort can have a
maximum of three observations and participants of the
1989 cohort a maximum of two.
Statistical analysis
The analyses were conducted in several subsequent steps.
After descriptive analyses on the characteristics of the
participants, a bivariate logistic regression was conducted
of loneliness onset (yes/no) on each baseline and change
score of the risk factors, while controlling for age. Subse-
quently, the unique contribution to the onset of loneliness
of each significant risk factor derived from the bivariate
models was estimated in a multivariate logistic regression
model. Since the time period between the measurement
waves was rather extended, the direction of causation may
still be questionable. Therefore, we finally conducted a
logistic regression analysis of onset of loneliness after 18
or 20 years, regressed on changes in risk factors during the
first 10 years.
Results
Descriptive statistics
In the first 10 years following after the first measurement
round, 135 of the 469 (28.1%) participants became lonely;
18 to 20 years after the first measurement another 37 par-
ticipants became lonely and during the last 20 to 28 years
again 6 participants became lonely, leading to a 28 years
incidence rate of loneliness of 37.1% (n=178). Recovery
from loneliness after people became lonely occurred in 28
cases (5.8% of the study sample). Since this was not the
topic of our study, we did not further analyze predictors of
recovery. The basic characteristics of the participants and
changes in risk factors are presented in Table 1. Though
the selection of a subsample of older adults who were not
lonely at baseline and who had at least one follow-up
measure inevitably led to a selection of healthier and
younger people, there was sufficient onset of loneliness and
sufficient variability in baseline and change scores to serve
our research aims.
Risk factors of loneliness
The significance of the risk factors was first analyzed in a
bivariate logistic regression model, while controlling for
the effect of age. Table 2shows that, apart from gender,
none of the baseline levels of the selected factors predicted
onset of loneliness, unless the levels of these factors
changed during follow-up. Women had a 48% higher
Eur J Ageing (2011) 8:31–38 33
123
probability to become lonely than men. Losing a partner
increased the risk of becoming lonely with a factor 2.7.
People whose social activity level reduced were 2 times
more likely to become lonely, and an increase in physical
disabilities but not decrease in self-perceived physical
health doubled the risks of becoming lonely. Increased
feelings of low mood, nervousness, and uselessness led,
respectively, to a 5.1, 3.3, and 4.5 times increased risk of
becoming lonely.
To determine the unique contribution of the predictors
found to be significant in the bivariate models, we con-
ducted a stepwise multivariate logistic regression analysis
with forward selection of the risk factors. Several signifi-
cant bivariate associations between the factors and onset of
loneliness lost their significance when other variables were
taken into account. Variables that were no longer associ-
ated with onset of loneliness were gender, loss of friends,
and loss of physical health (see Table 3). Risk factors
remaining to have a unique contribution to the onset of
loneliness are losing a partner, reduced social activities,
increased feelings of low mood, nervousness and useless-
ness. The increase in the risk of becoming lonely varied
from a factor 1.8 (reduction in social activities) to 4.0
(increased feelings of low mood). Taken together, these
factors accounted for almost 30% of the variability in
loneliness onset. Inspection of the collinearity statistics
revealed that there was no collinearity among the risk
factors (Correlations (Kendall’s Tau) ranged from 0.05 to
0.21; Tolerance 0.89–0.94, VIF 1.06–1.13).
Since low mood, increased feelings of nervousness and
increased feelings of uselessness are conceptually related
constructs (Russell et al. 1980) we further investigated the
zero-order correlates between these constructs and loneli-
ness, and calculated which part of the explained variance in
onset of loneliness could be accounted to these factors. The
zero-order correlations between mood, irritability and
uselessness reveals that correlations ranged from 0.10 for
loneliness and irritability, to 0.42 for loneliness and feel-
ings of uselessness suggesting that the overlap between the
constructs and loneliness is weak to moderate. In addition,
stepwise logistic regression with variables entered in three
blocks revealed that age (first block), and gender, loss of
the partner, loss of friends, loss of social activities, and
reduced physical abilities (second block) could explain
13.4% of the total variance in onset of loneliness. An
additional 16.6% of the total variance in loneliness was
accounted to lowered mood, increased feelings of ner-
vousness, and increased feelings of uselessness.
Since the time period between the measurement waves
is rather extended, and loneliness and risk factors may have
influenced each other mutually during the period between
the measurements, we finally checked whether onset of
loneliness between the second and third measurement
could be predicted by changes in risk factors during the
first 10 years (Table 4). As there were only 37 new lone-
liness cases between the second and third measurement, the
Table 1 Baseline characteristics and changes in characteristics of the
study sample (N=469)
M,NSD, %
Age (M, SD) 66.2 5.6
Female gender (N, %) 256 53.3
Partner status (N,%)
Living with partner 325 67.7
No partner 74 15.4
Widowed 81 16.9
Loss of partner at FU (N, %) 121 25.2
Having no friends (N, %) 39 8.2
Loss of friends at FU (N, %) 67 14.0
Social activity (N,%)
High activity 367 77.3
Moderate 42 8.8
Low 66 13.9
Reduced social activity at FU (N, %) 169 35.2
Self-perceived health (N,%)
Good 243 50.7
Average 164 34.2
Poor 72 15.0
Decline in self-perceived health at FU (N, %) 137 28.5
Physical disabilities (N,%)
Absent 401 83.7
Moderate 31 6.5
Severe 47 9.8
Increased physical disabilities at FU (N, %) 213 44.4
Feelings of low mood (N,%)
Never 402 84.5
Sometimes 55 11.6
Often 19 4.0
Increased feelings of low mood at FU (N, %) 133 27.7
Feelings of irritation (N,%)
Never 395 83.2
Sometimes 73 15.4
Often 7 1.5
Increased feelings of irritations at FU (N, %) 63 13.1
Feelings of nervousness (N,%)
Never 360 75.5
Sometimes 92 19.3
Often 25 5.2
Increased feelings of nervousness at FU (N, %) 77 16.0
Self esteem (N,%)
Good 412 88.6
Somewhat low 49 10.5
Low 4 0.9
Lowered self esteem at FU (N, %) 99 20.6
34 Eur J Ageing (2011) 8:31–38
123
Table 2 Bivariate associations between risk factors and onset of loneliness, controlling for age (reference group is not lonely)
Risk factors Lonely (n=178/469)
OR 95% C.I. pWald statistic
Age (per year increase) 0.99 0.96 1.02 0.55 0.37
Being female 1.59 1.08 2.33 0.02 5.50
Partner status
Living with partner is ref group
No partner 1.03 0.61 1.74 0.92 0.01
Widowed 1.00 0.51 1.96 1.00 0.00
Loss of partner at FU 2.97 1.94 4.55 \0.001 24.85
No friends 1.02 0.50 2.06 0.97 0.00
Loss of friends at FU 2.25 1.32 3.82 0.00 8.92
Social activity
High activity is ref group
Moderate 0.91 0.52 1.58 0.73 0.12
Low 0.97 0.42 2.22 0.95 0.01
Reduced social activity at FU 2.08 1.40 3.08 \0.001 13.03
Self-perceived health (SPH)
Good health is ref group
Average 1.15 0.66 2.00 0.63 0.24
Poor 0.94 0.53 1.68 0.84 0.04
Decline in SPH at FU 1.36 0.90 2.06 0.14 2.14
Physical health
Good physical health is ref group
Average 1.46 0.79 2.70 0.23 1.46
Poor 1.90 0.72 5.03 0.19 1.69
Reduced physical health at FU 2.19 1.49 3.21 \0.001 15.84
Feelings of low mood
Never feelings of low mood is ref group
Sometimes 1.57 0.60 4.09 0.35 0.86
Often 1.08 0.37 3.18 0.89 0.02
Increased feelings of low mood at FU 5.17 3.35 7.98 \0.001 54.90
Feelings of irritation
Never feelings of irritation is ref group
Sometimes 0.78 0.15 4.08 0.77 0.09
Often 0.47 0.09 2.61 0.39 0.74
Increased feelings of irritations at FU 1.29 0.75 2.24 0.36 0.83
Feelings of nervousness
Never feelings of nervousness is ref group
Sometimes 1.26 0.54 2.95 0.59 0.29
Often 0.65 0.26 1.64 0.36 0.84
Increased feelings of nervousness at FU 3.24 1.94 5.40 \0.001 20.26
Feelings of uselessness
Never feeling useless is ref group
Sometimes 1.92 0.27 13.81 0.52 0.42
Often 1.11 0.14 8.56 0.92 0.01
Increased feelings of uselessness at FU 4.70 2.92 7.55 \0.001 40.82
Statistically significant (p\0.05) odds ratios are displayed in bold
Eur J Ageing (2011) 8:31–38 35
123
power to detect significance dropped considerably, so we
only checked whether the directions were in accord with
our results described above. Age and changes in risk fac-
tors in the first 10 years increased the risk of becoming
lonely during the following 10 years, which reiterated our
previous findings. In addition, these results suggest that
changes in risk factors may have long lasting effects on the
onset of loneliness.
Discussion
The aim of this study was to give more insight into the
origins of loneliness in older adults by investigating whe-
ther changes in factors found to be associated with lone-
liness also leads to an enhanced likelihood of becoming
lonely at follow-up. In addition, we investigated to what
extent gender differences could be explained in terms of a
differential exposure to risk factors across men and women.
The study indicated that onset of loneliness in older age is
more likely if people become more depressed, have
increased feelings of uselessness, have increased feelings
of nervousness, lose their partner, and have reduced levels
of social activity. Baseline levels of social and psycho-
logical resources did not predict onset of loneliness. As far
as men and women differ in feelings of loneliness, this can
be explained in terms of a higher exposure to risk factors
for women, and not to individual differences in vulnera-
bility to loneliness between men and women.
Our findings are important in several ways. Firstly, this
longitudinal study gave further support to the notion that
losses in social and personal resources, rather than a small
network or ill health, enhances the likelihood of becoming
lonely. This fits to the idea that loneliness is understood as
being the result of a subjective evaluation of the discrep-
ancy between achieved, or rather the lost relationships, as
compared with desired relationships.
Secondly, the study suggests that also losses in psy-
chological resources, such as worsening of mental health,
increase the likelihood of becoming lonely. More specifi-
cally, we found that increased feelings of uselessness,
increased feelings of nervousness and increased feelings of
low mood lead to a higher likelihood to become lonely in
the future This is in line with the study of Newall et al.
(2009) who found that control beliefs are important pre-
dictors of loneliness, and consistent with the theory of
conservation of resources (Hobfoll 1988) stating that
resources helping to maintain well-being can be social
conditions (such as having a partner) but also psychologi-
cal. It is also in line with the idea that personal charac-
teristics can create difficulties for the person trying to
establish or maintain satisfactory relationships (Perlman
and Peplau 1981). In accord with the study of Fry and
Debats (2002) we found that reductions in personal
Table 3 Final model for the
multivariate associations
between risk factors and onset
of loneliness, controlling for age
(reference group is not lonely,
Method =Forward stepwise
selection of variables)
Nagelkerke R
2
=0.30
Statistically significant
(p\0.05) odds ratios are
displayed in bold
Risk factors Lonely (n=178/469)
OR 95% C.I. pWald statistic
Age (per year increase) 0.98 0.94 1.02 0.34 0.92
Loss of partner at FU 2.07 1.28 3.35 0.00 8.82
Reduced social activities at FU 1.80 1.15 2.83 0.01 6.56
Increased feelings of low mood at FU 4.04 2.53 6.44 \0.01 34.33
Increased feelings of nervousness at FU 1.96 1.09 3.50 0.02 5.08
Increased feelings of uselessness at FU 3.51 2.08 5.91 \0.01 22.30
Table 4 Multivariate
associations between changes in
risk factors (T1–T2) and
incidence of loneliness (T2–T3),
controlling for age (reference
group is no incident loneliness
between T1 and T2,
Method =Enter)
Risk factors Lonely (n=37/432)
OR 95% C.I. pWald statistic
Age (per year increase) 1.09 1.01 1.18 0.03 4.78
Gender 1.22 0.61 2.46 0.58 0.31
Loss of partner between T1 and T2 1.56 0.52 4.65 0.42 0.64
Loss of friends between T1 and T2 1.03 0.29 3.69 0.97 0.00
Loss of social activities between T1 and T2 1.14 0.46 2.83 0.78 0.08
Loss of physical health between T1 and T2 0.80 0.36 1.75 0.57 0.32
Increased feelings of low mood between T1 and T2 1.26 0.49 3.27 0.63 0.23
Increased feelings of nervousness between T1 and T2 1.70 0.24 1.47 0.25 1.30
Increased feelings of uselessness between T1 and T2 1.52 0.50 4.66 0.47 0.53
36 Eur J Ageing (2011) 8:31–38
123
resources are even stronger predictors of loneliness than
reductions in social resources.
One could argue that low mood, irritability, nervousness
or feelings of uselessness are concepts that are closely
related to loneliness, and may be considered two sides of
the same coin. However, based on the zero-order correla-
tions between mood, irritability and uselessness we may
conclude that there is indeed overlap, but correlations are
weak to moderate. In addition, the combined effect of
mood, uselessness, irritability and nervousness only
accounts for 17% of the variance in loneliness onset,
leaving a substantive amount of variance to be explained
by other factors.
Finally, it appears that a reduction in social activities
leads to enhanced feelings of loneliness. With refer to the
activity theory (Havighurst 1963) and the continuity theory
(Atchley 1989) this increased feeling of loneliness may be
the result of peoples inability to substitute activities or roles
that are lost by new ones, which results in reduced well-
being to which loneliness is closely related (e.g., Fees et al.
1999).
Our main finding that losses in social and personal
resources, rather than their baseline level lead to a higher
likelihood of becoming lonely may also indicate the exis-
tence of subgroups of people who differ in sensitivity to
risk factors leading to different trajectories of loneliness
development. In this study, we selected people who were
not lonely at baseline. Given the long lasting effect of
many of the risk factors observed in our study, it is striking
that baseline levels did not predict loneliness. Since we
started with a selection of people who were not lonely at
baseline, we may have selected not only people that were
fortunate enough to have not encountered any risk leading
to enhanced levels of loneliness, but also people who have
encountered risk events without affecting them. The
acknowledgement of different subgroups is important for
the theoretical and conceptual understanding of loneliness
as well as for the development of intervention strategies
(Victor et al. 2004). Further research on loneliness may
benefit from insights into loneliness trajectories by identi-
fying distinctive clusters of individual trajectories within
the population, and see if covariates shaping the trajecto-
ries may have differential effect across the sub groups of
people.
Several limitations of our study need to be acknowl-
edged. There is a large time period between the follow-up
measures, which may be problematic in causality research.
The right time interval for causality to show up is highly
dependent on the dynamics of the relationships between
loneliness and its correlates. For example, Guiaux and
colleagues showed that support from members in the per-
sonal network of widowed people, starts to increase already
before widowhood, continues shortly after widowhood, but
than returns to lower levels in the long run (Guiaux et al.
2007). In addition, onset of loneliness at the first follow-up
could have occurred shortly after the baseline measure and
we can not rule out the possibility that onset of loneliness
might have led to lowered levels of mood or increased
feelings of irritability. Nevertheless, our additional analy-
ses testing whether onset of loneliness between the second
and third measurement could be predicted by changes in
risk factors during the first 10 years were in line with our
results, which made us feel comfortable with our general
conclusions.
Another limitation of our long follow-up period is the
large attrition of the study sample, which has resulted in a
healthier, and younger study sample compared to the ori-
ginal population. Next, change scores are based on
observed data, which may have lead to some overestima-
tion of change due to measurement error (Bassi et al.
2000). An alternative approach in this study could have
been the use of Latent Growth Models to account for
missing values, overestimation of change, the potential
correlations between error terms, and the unreliability of
measurements. Two potentially interesting attributes of
growth trajectories are rates of change and initial status
(Duncan and Duncan 2004). In these models, the time
perspective is an important feature as changes are modeled
over time. However, in this specific instance we preferred
less emphasis on the influence of time by using clear-cut
categories of the selected variables such as onset of lone-
liness versus no onset and loss of resources versus no loss
of resources.
Finally, some of the selected study variables especially
the psychological factors mood, irritability, and nervous-
ness were assessed with a limited number of items and a
limited number of answering categories. Therefore, reli-
ability and the validity of these concepts may be lower than
in well-established measurement scales or clinical assess-
ments. It may be of interest to see if the effect of changes in
personality factors is sustained if more elaborated ques-
tionnaires or clinical criteria are used.
An advantage of the longitudinal design is clearly the
possibility to investigate the potential causal effect of
(changes) in resources on the likelihood of becoming
lonely in the future. Despite the long follow-up and the
large attrition, our study sheds new light on the relative
importance of social and psychological resources in pre-
venting older people from becoming lonely. The study
allowed us to conclude that some, but not all, correlates of
loneliness generally believed to enhance loneliness are also
related to an increased likelihood of becoming lonely. In
particular, losses of social and psychological resources
rather than baseline characteristics are related to an
increased likelihood of becoming lonely. Gender differ-
ences in loneliness seem to be the result of the unequal
Eur J Ageing (2011) 8:31–38 37
123
exposure to risk factors (e.g., women become more often
widowed).
Acknowledgment The Tampere Longitudinal Study in Ageing as
been financed by the Academy of Finland and the Ministry of Social
Affairs and health as part of the Research Programme on Ageing.
Open Access This article is distributed under the terms of the
Creative Commons Attribution Noncommercial License which per-
mits any noncommercial use, distribution, and reproduction in any
medium, provided the original author(s) and source are credited.
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