INTERPERSONAL RELATIONS AND GROUP PROCESSES
Alone in the Crowd: The Structure and Spread of Loneliness in a
Large Social Network
John T. Cacioppo
University of Chicago
James H. Fowler
University of California, San Diego
Nicholas A. Christakis
Harvard University
The discrepancy between an individual’s loneliness and the number of connections in a social network
is well documented, yet little is known about the placement of loneliness within, or the spread of
loneliness through, social networks. The authors use network linkage data from the population-based
Framingham Heart Study to trace the topography of loneliness in people’s social networks and the path
through which loneliness spreads through these networks. Results indicated that loneliness occurs in
clusters, extends up to 3 degrees of separation, is disproportionately represented at the periphery of social
networks, and spreads through a contagious process. The spread of loneliness was found to be stronger
than the spread of perceived social connections, stronger for friends than family members, and stronger
for women than for men. The results advance understanding of the broad social forces that drive
loneliness and suggest that efforts to reduce loneliness in society may benefit by aggressively targeting
the people in the periphery to help repair their social networks and to create a protective barrier against
loneliness that can keep the whole network from unraveling.
Keywords: loneliness, social network, social isolation, contagion, longitudinal study
Human social isolation is recognized as a problem of vast importance.
(Harlow, Dodsworth, & Harlow, 1965, p. 90)
Social species do not fare well when forced to live solitary lives.
Social isolation decreases the lifespan of the fruit fly, Drosophilia
melanogaster (Ruan & Wu, 2008); promotes the development of
obesity and Type 2 diabetes in mice (Nonogaki, Nozue, & Oka,
2007); delays the positive effects of running on adult neurogenesis
in rats (Stranahan, Khalil, & Gould, 2006); increases the activation
of the sympatho-adrenomedullary response to an acute immobili-
zation or cold stressor in rats (Dronjak, Gavrilovic, Filipovic, &
Radojcic, 2004); decreases the expression of genes regulating
glucocorticoid response in the frontal cortex of piglets (Poletto,
Steibel, Siegford, & Zanella, 2006); decreases open field activity,
increases basal cortisol concentrations, and decreases lymphocyte
proliferation to mitogens in pigs (Kanitz, Tuchscherer, Puppe,
Tuchscherer, & Stabenow, 2004); increases the 24-hr urinary
catecholamines levels and evidence of oxidative stress in the aortic
arch of the Watanabe heritable hyperlipidemic rabbit (Nation et al.,
2008); increases the morning rises in cortisol in squirrel monkeys
(Lyons, Ha, & Levine, 1995); and profoundly disrupts psychosex-
ual development in rhesus monkeys (Harlow et al., 1965).
Humans, born to the longest period of abject dependency of any
species and dependent on conspecifics across the lifespan to sur-
vive and prosper, do not fare well, either, whether they are living
solitary lives or whether they simply perceive that they live in
isolation. The average person spends about 80% of waking hours
in the company of others, and the time with others is preferred to
the time spent alone (Emler, 1994; Kahneman, Krueger, Schkade,
Schwarz, & Stone, 2004). Social isolation, in contrast, is associ-
ated not only with lower subjective well-being (Berscheid, 1985;
Burt, 1986; Myers & Diener, 1995) but also with broad-based
morbidity and mortality (House, Landis, & Umberson, 1988).
Humans are an irrepressibly meaning-making species, and a
large literature has developed showing that perceived social iso-
lation (i.e., loneliness) in normal samples is a more important
predictor of a variety of adverse health outcomes than is objective
social isolation (e.g., (Cole et al., 2007; Hawkley, Masi, Berry, &
Cacioppo, 2006; Penninx et al., 1997; Seeman, 2000; Sugisawa,
Liang, & Liu, 1994). In an illustrative study, Caspi, Harrington,
Moffitt, Milne, & Poulton (2006) found that loneliness in adoles-
cence and young adulthood predicted how many cardiovascular
John T. Cacioppo, Department of Psychology, University of Chicago;
James H. Fowler, Department of Political Science, University of California,
San Diego; Nicholas A. Christakis, Department of Health Care Policy, Har-
vard Medical School and Department of Sociology, Harvard University.
The research was supported by National Institute on Aging Grants
R01AG034052-01 (to John T. Cacioppo), P01AG031093, and R01AG24448
(to Nicholas A. Christakis).
Correspondence concerning this article should be addressed to John T.
Cacioppo, Department of Psychology, University of Chicago, Chicago, IL,
60637. E-mail: Cacioppo@uchicago.edu
Journal of Personality and Social Psychology, 2009, Vol. 97, No. 6, 977–991
? 2009 American Psychological Association 0022-3514/09/$12.00 DOI: 10.1037/a0016076
977

risk factors (e.g., body mass index, waist circumference, blood
pressure, cholesterol) were elevated in young adulthood and that
the number of developmental occasions (i.e., childhood, adoles-
cence, young adulthood) at which participants were lonely pre-
dicted the number of elevated risk factors in young adulthood.
Loneliness has also been associated with the progression of
Alzheimer’s disease (Wilson et al., 2007), obesity (Lauder, Mum-
mery, Jones, & Caperchione, 2006), increased vascular resistance
(Cacioppo, Hawkley, Crawford, et al., 2002), elevated blood pres-
sure (Cacioppo, Hawkley, Crawford, et al., 2002; Hawkley et al.,
2006), increased hypothalamic pituitary adrenocortical activity
(Adam, Hawkley, Kudielka, & Cacioppo, 2006; Steptoe, Owen,
Kunz-Ebrecht, & Brydon, 2004), less salubrious sleep (Cacioppo,
Hawkley, Berntson, et al., 2002; Pressman et al., 2005), dimin-
ished immunity (Kiecolt-Glaser et al., 1984; Pressman et al.,
2005), reduction in independent living (Russell, Cutrona, de la
Mora, & Wallace, 1997; Tilvis, Pitkala, Jolkkonen, & Strandberg,
2000), alcoholism (Akerlind & Hornquist, 1992), depressive
symptomatology (Cacioppo et al., 2006; Heikkinen & Kauppinen,
2004), suicidal ideation and behavior (Rudatsikira, Muula, Siziya,
& Twa-Twa, 2007), and mortality in older adults (Penninx et al.,
1997; Seeman, 2000). Loneliness has even been associated with
gene expression: specifically, the under-expression of genes bear-
ing anti-inflammatory glucocorticoid response elements and over-
expression of genes bearing response elements for proinflamma-
tory NF-
B/Rel transcription factors (Cole et al., 2007).
Adoption and twin studies indicate that loneliness has a sizable
heritable component in children (Bartels, Cacioppo, Hudziak,
& Boomsma, 2008; McGuire & Clifford, 2000) and in adults
(Boomsma, Cacioppo, Muthen, Asparouhov, & Clark, 2007;
Boomsma, Cacioppo, Slagboom, & Posthuma, 2006; Boomsma,
Willemsen, Dolan, Hawkley, & Cacioppo, 2005). Social factors
have a substantial impact on loneliness, as well, however. For
instance, freshmen who leave family and friends behind often feel
increased social isolation when they arrive at college, even though
they are surrounded by large numbers of other young adults (e.g.,
Cutrona, 1982; Russell, Peplau, & Cutrona, 1980). Lower levels of
loneliness are associated with marriage (Hawkley, Browne, &
Cacioppo, 2005; Pinquart & Sorenson, 2003), higher education
(Savikko, Routasalo, Tilvis, Strandberg, & Pitkala, 2005), and
higher income (Andersson, 1998; Savikko et al., 2005), whereas
higher levels of loneliness are associated with living alone
(Routasalo, Savikko, Tilvis, Strandberg, & Pitkala, 2006), infre-
quent contact with friends and family (Bondevik & Skogstad,
1998; Hawkley et al., 2005; Mullins & Dugan, 1990), dissatisfac-
tion with living circumstances (Hector-Taylor & Adams, 1996),
physical health symptoms, chronic work and/or social stress
(Hawkley et al., 2008), small social network (Hawkley et al., 2005;
Mullins & Dugan, 1990), lack of a spousal confidant (Hawkley et
al., 2008), marital or family conflict (Jones, 1992; Segrin, 1999),
poor quality social relationships (Hawkley et al., 2008; Mullins &
Dugan, 1990; Routasalo et al., 2006), and divorce and widowhood
(Dugan & Kivett, 1994; Dykstra & de Jong Gierveld, 1999;
Holmen, Ericsson, Andersson, & Winblad, 1992; Samuelsson,
Andersson, & Hagberg, 1998).
The discrepancy between an individual’s subjective report of
loneliness and the reported or observed number of connections in
their social network is well documented (e.g., see Berscheid &
Reis, 1998), but few details are known about the placement of
loneliness within or the spread of loneliness through a social
network. The association between the loneliness of individuals
connected to each other, and their clustering within the network,
could be attributed to at least three social psychological processes.
First, the induction hypothesis posits that the loneliness in one
person contributes to or causes the loneliness in others. The emo-
tional, cognitive, and behavioral consequences of loneliness may
contribute to the induction of loneliness. For instance, emotional
contagion refers to the tendency for the facial expressions, vocaliza-
tions, postures, and movements of interacting individuals to lead to a
convergence of their emotions (Hatfield, Cacioppo, & Rapson, 1994).
When people feel lonely, they tend to be shyer, more anxious, more
hostile, more socially awkward, and lower in self-esteem (e.g., Ber-
scheid & Reis, 1998; Cacioppo et al., 2006). Emotional contagion
could therefore contribute to the spread of loneliness to those with
whom they interact. Cognitively, loneliness can affect and be affected
by what one perceives and desires in their social relationships (Peplau
& Perlman, 1982; Rook, 1984; Wheeler, Reis, & Nezlek, 1983). To
the extent that interactions with others in an individual’s social net-
work influence a person’s ideal or perceived interpersonal relation-
ship, that person’s loneliness should be influenced. Behaviorally,
when people feel lonely, they tend to act toward others in a less
trusting and more hostile fashion (e.g., Rotenberg, 1994; cf. Berscheid
& Reis, 1998; Cacioppo & Patrick, 2008). These behaviors, in turn,
may lower the satisfaction of others with the relationship or lead to a
weakening or loss of the relationship and a consequent induction of
loneliness in others.
Second, the homophily hypothesis posits that lonely or non-
lonely individuals choose one another as friends and become
connected (i.e., the tendency of like to attract like; McPherson,
Smith-Lovin, & Cook, 2001). Byrne’s (1971) law of attraction
specifies that there is a direct linear relationship between interper-
sonal attraction and the proportion of similar attitudes. The asso-
ciation between similarity and attraction is not limited to attitudes,
and the characteristics on which similarity operates move from
obvious characteristics (e.g., physical attractiveness) to less obvi-
ous ones (social perceptions) as relationships develop and deepen
(e.g., Neimeyer & Mitchell, 1988). Although feelings of loneliness
can be transient, stable individual differences in loneliness may
have sufficiently broad effects on social cognition, emotion, and
behavior to produce similarity-based social sorting.
Finally, the shared environment hypothesis posits that con-
nected individuals jointly experience contemporaneous exposures
that contribute to loneliness. Loneliness, for instance, tends to be
elevated in matriculating students, because for many, their arrival
at college is associated with a rupture of normal ties with their
family and friends (Cutrona, 1982). People who interact within a
social network may also be more likely to be exposed to the same
social challenges and upheavals (e.g., coresidence in a dangerous
neighborhood, job loss, retirement).
To distinguish among these hypotheses requires repeated mea-
sures of loneliness, longitudinal information about network ties,
and information about the nature or direction of the ties (e.g., who
nominated whom as a friend; Carrington, Scott, & Wasserman,
2005; Fowler & Christakis, 2008b). With the recent application of
innovative research methods to network linkage data from the
population-based Framingham Heart Study (FHS), these data are
now available and have been used to trace the distinctive paths
through which obesity (Christakis & Fowler, 2007), smoking
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CACIOPPO, FOWLER, AND CHRISTAKIS