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Loneliness and social isolation as risk factors for CVD: Implications for evidence-based patient care and scientific inquiry

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A recent meta-analysis has shown that loneliness and social isolation are risk factors for coronary heart disease and stroke.1 These latest findings, specific to cardiovascular outcomes, are consistent with substantial research indicating broad health risks (eg, immune functioning, cardiovascular functioning, cognitive decline) associated with the quantity and quality of social relationships—including several meta-analyses documenting mortality risk.2 ,3 In the most comprehensive of these,3 the overall odds for mortality was 1.50, similar to the risk from light smoking and exceeding the risks conferred by hypertension and obesity. Thus, the epidemiological data suggest that having more and better quality social relationships is linked to decreased health risks and having fewer and poorer quality relationships increased risk.2 ,3 Research has also documented the influence of social connections (including measures specific to loneliness and isolation) on multiple pathways involved in both the development and progression of coronary heart disease and stroke. As depicted in figure 1, these include lifestyle (eg, nutrition, physical activity, sleep),4 treatment adherence and cooperation,5 and direct effects on surrogate biological markers.6 ,7 Recent longitudinal data from four nationally representative US samples revealed a dose–response effect of social integration on several surrogate biomarkers of cardiovascular disease including hypertension, body mass index, waist circumference and inflammation (hs-CRP).6 Moreover, most epidemiological studies control for lifestyle factors (eg, smoking, physical activity), documenting an independent influence of social relationships on mortality. Taken together, these latest findings specific to loneliness and isolation1 bolster the already robust evidence documenting that social connections significantly predict morbidity and mortality, supporting the case for inclusion as a risk factor for cardiovascular disease (CVD). Figure 1 Simplified model of possible direct and indirect pathways by which social connections influence disease morbidity and mortality. How should these data inform clinical practice? …
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Loneliness and social isolation as risk
factors for CVD: implications for
evidence-based patient care and
scientic inquiry
Julianne Holt-Lunstad,
1
Timothy B Smith
2
LONELINESS AND SOCIAL ISOLATION
AS RISK FACTORS FOR CVD
A recent meta-analysis has shown that
loneliness and social isolation are risk
factors for coronary heart disease and
stroke.
1
These latest ndings, specicto
cardiovascular outcomes, are consistent
with substantial research indicating broad
health risks (eg, immune functioning, car-
diovascular functioning, cognitive decline)
associated with the quantity and quality of
social relationshipsincluding several
meta-analyses documenting mortality
risk.
23
In the most comprehensive of
these,
3
the overall odds for mortality was
1.50, similar to the risk from light
smoking and exceeding the risks con-
ferred by hypertension and obesity. Thus,
the epidemiological data suggest that
having more and better quality social rela-
tionships is linked to decreased health
risks and having fewer and poorer quality
relationships increased risk.
23
Research has also documented the inu-
ence of social connections (including mea-
sures specic to loneliness and isolation)
on multiple pathways involved in both the
development and progression of coronary
heart disease and stroke. As depicted in
gure 1, these include lifestyle (eg, nutri-
tion, physical activity, sleep),
4
treatment
adherence and cooperation,
5
and direct
effects on surrogate biological markers.
67
Recent longitudinal data from four
nationally representative US samples
revealed a doseresponse effect of social
integration on several surrogate biomar-
kers of cardiovascular disease including
hypertension, body mass index, waist cir-
cumference and inammation (hs-CRP).
6
Moreover, most epidemiological studies
control for lifestyle factors (eg, smoking,
physical activity), documenting an inde-
pendent inuence of social relationships
on mortality. Taken together, these latest
ndings specic to loneliness and isola-
tion
1
bolster the already robust evidence
documenting that social connections sig-
nicantly predict morbidity and mortality,
supporting the case for inclusion as a risk
factor for cardiovascular disease (CVD).
TARGETING SOCIAL ISOLATION AND
LONELINESS IN EVIDENCE-BASED
PATIENT CARE
How should these data inform clinical
practice? To begin, the data suggest the
need for greater prioritisation and inclu-
sion of social variables (quantity and
quality) in medical education, individual
risk assessment and public health surveil-
lance, guidelines and policies applied to
populations and health service delivery.
Medical education
The cumulative evidence points to the
benet of including social factors in
medical training and continuing education
for healthcare professionals. Physicians
supervising students and residents can
assess patients social risk factors and then
discuss with patients the importance of
nurturing and maintaining positive social
connections as part of a healthy lifestyle.
Evidence-based training could include
social factors in medical case examples
and textbooks to provide realistic patient
descriptions with life circumstances rele-
vant to disease development, progression
and response to treatment. For instance, a
case description of a 55-year-old male
with hypertension and atrial brillation
who is responding poorly to treatment
could include relevant circumstances of
intense marital conict that have elevated
levels of distress and increased adiposity
due to increased consumption of low
quality foods away from home. Given the
multiple social factors associated with
health conditions and patients responses
to treatment, medical training that
requires consideration of patients social
circumstances could improve patients
outcomes.
Medical training can also make explicit
the processes for making effective
referrals to mental health and social
support services. In the hypothetical case
of the patient mentioned above, referral
for marital counselling and stress manage-
ment therapy would be indicated. Medical
training can encourage physicians to pro-
actively identify relevant social and psy-
chological conditions, rather than ignore
those conditions simply because they
would be treated by another specialist. In
the same way cardiologists refer and
follow-up with patients who have
comorbid renal disease, they should refer
and follow-up with patients experiencing
social isolation or distress. Social factors
must now be given attention in course-
work detailing the major ndings of
health psychology and neuroscience,
rather than relegating such information to
a side note (eg, a mini-lecture during stu-
dents exposure to psychiatry).
Risk assessment
Patient information should be used to
inform treatment. Hospitals and clinics
should include assessments of social inte-
gration and/or loneliness in electronic
medical records. This important step can
identify individuals at riskwhich may
also have multiple implications for health
service delivery. Further, at a broader
level, population-wide surveillance will
aid public health efforts.
Such efforts will require multifactorial
risk assessment. While short and simple
assessments are desirable, single-item
assessments would be insufcient and
problematic. According to meta-analytic
data,
3
multivariate measures of social rela-
tionships yield data much more predictive
of death (OR=1.91) than simplistic mea-
sures (OR=1.19). Further, although lone-
liness and social isolation entail equivalent
levels of risk, they are not interchange-
able. Social isolation denotes few social
connections or interactions, whereas lone-
liness involves the subjective perception of
isolationthe discrepancy between ones
desired and actual level of social connec-
tion. Although social isolation and loneli-
ness may co-occur, individuals can be
isolated without feeling lonely or feel
lonely despite having others present. Thus
assessments should include objective/
quantitative aspects of relationships (eg,
network size, marital status), as well as
more subjective/qualitative aspects (eg,
loneliness, social support, perceived rela-
tionship quality). Each signi cantly pre-
dicts risk for mortality,
3
and may
potential tap into different mechanistic
pathways; thus, multifactorial assessments
may best capture overall risk. A key chal-
lenge will be how to develop a
1
Department of Psychology and Neuroscience, Brigham
Young University, Provo, Utah, USA;
2
Department of
Counseling Psychology, Brigham Young University,
Provo, Utah, USA
Correspondence to Dr Julianne Holt-Lunstad,
Department of Psychology and Neuroscience, Brigham
Young University, Provo UT 84602, USA;
julianne_holt-lunstad@byu.edu
Holt-Lunstad J, Smith TB. Heart Month 2016 Vol 0 No 0 1
Editorial
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point-of-care assessment that is multifa-
ceted, has predictive validity, and easily
incorporated into day-to-day clinical
practice.
Population-based recommendations
and policies
The WHO now lists Social Support
Networks as a determinant of health
(http://www.who.int/hia/evidence/doh/en/).
Major health organisations specictocar-
diovascular disease (eg, American Heart
Association, British Heart Foundation)
should also include social connections in
their lists of major risk factors, similar to
comparable lifestyle factors that currently
receive sustained attention. Government
and pr ofessional health organisations will
need to establish recommendations for
social relationship quantity and quality for
the broader population and specicrisk
groups. These recommendations should be
based on empirical evidence, subject to
periodic revision and annual public health
surveillance.
Among other European nations, the UK
has already undertaken several public
health initiatives intended to reduce social
isolation and decrease risk for premature
mortality. Current efforts are focused pri-
marily on older adults or individuals
reporting high levels of loneliness;
however, recommendations and cautions
can be broadly applied. A broad approach
is supported by evidence indicating (a)
remarkable consistency of effect across
different countries and across multiple
individual characteristics (eg, gender,
health status), with data suggesting greater
relative risk prior to retirement age;
2
(b) a
gradient effect of social connection rather
than a threshold effect
36
and (c) social
relationships affect cardiovascular health
by altering biomarkers and shaping health
behaviours across the lifespanincluding
adolescence, young adulthood, middle age
and old age.
6
Thus, efforts to promote
public health via social connection need
not be limited to specic groups but can
be applied across the risk trajectory.
Health service delivery: prevention
Attention to social connection needs to be
incorporated into existing preventative
efforts. Chronic illnesses, including car-
diovascular diseases, develop slowly over
decades. Because social relations inuence
multiple mechanistic pathways in both the
development and progression of disease,
they warrant attention in primary, second-
ary and tertiary prevention efforts. Given
efforts aimed at primary prevention result
in lower economic costs to the individual,
family, employers and the broader health-
care systemwe urge healthcare and
health policy professionals to prioritise
social connections in prevention efforts.
FURTHER SCIENTIFIC INQUIRY
Despite robust literature of epidemio-
logical evidence, several important ques-
tions remain.
Causal mechanisms
Social isola tion and loneliness are clearly
risk factors for cardio vascular disease
(CVD).
8
How ev er, the term risk fact or can
imply prediction and causality, and causality
is not easily established. Similar to other risk
factors for CVD (eg, hypertension, obesity,
smoking, choles terol levels) the inuence of
social rela tionships is complex and multifac-
torial (no single putative mechanism).
8
Furthermore, we must take a multilevel
approach considering microlevel (eg, genetic
markers of susceptibility, geneenvironment
intera ctions) to macrolev el (eg, cultural
norms, neighbourhood chara cteristics) pro-
cesses to better understand additional path-
wa ys by which social r ela tionships inuence
physicalhealth,aswellasthepathwaysby
which we ma y interv ene to r educe risk and
improve health.
Interventions
Perhaps the biggest challenge and oppor-
tunity for the future is to design effective
interventions to increase social connec-
tions. Previous interventions involving
social support have had mixed results.
Additional research is needed to deter-
mine what works best for whom, in what
conditions. Notably, the major effects
established via epidemiological data are
based on existing social relationships (eg,
family, friends), yet many clinical inter-
ventions use hired personnel to deliver
support to patients. This discrepancy may
be problematic because support from the
patients family and broader social net-
works may differ from that provided by
hired personnel in several important ways
(eg, trust built over decades, regular social
contact, importance of the relationship,
degree of social control, sense of obliga-
tion in the relationship). Thus, efforts to
strengthen existing family relationships
may prove more effective than interven-
tions by hired personnel.
Figure 1 Simplied model of possible direct and indirect pathways by which social connections inuence disease morbidity and mortality.
2 Holt-Lunstad J, Smith TB. Heart Month 2016 Vol 0 No 0
Editorial
group.bmj.com on April 19, 2016 - Published by http://heart.bmj.com/Downloaded from
On a related note, policies that for essen-
tial reasons restrict access to patients
medical records and information may have
indirectly contributed to a practice climate
not conducive to family involvement, even
when the patient authorises family involve-
ment. Hospitals and clinics should make
efforts to enhance family involvement
when authorised by the patient.
Social technology
Social technology has rapidly become a
dominant form of communication and
social interaction. While existing and
developing technology has the potential
to combat loneliness and isolation (facili-
tating social connection), it may also con-
tribute to problems exacerbating risk.
With such rapid changes in the way
people are interacting socially, empirical
research is needed to address several
important questions. Does interacting
socially via technology reduce or replace
face-to-face social interaction and/or alter
social skills? Due to the rapid and instant
access afforded, does technology acceler-
ate relationship processes (both positive
and negative) leading to accentuation of
sociality or lack thereof? Do social rela-
tionships/interactions via technology have
a similar inuence health and well-being?
CONCLUSIONS
Decades of research have documented an
unequivocal inuence of social connec-
tions on longevity,
23
with a recent
meta-analysis conrming the association
between social isolation and CVD.
1
Given
projected increases in levels of social
isolation and loneliness in Europe and
North America, medical science needs to
squarely address the ramications for
physical health. Similar to how cardiolo-
gists and other healthcare professionals
have taken strong public stances regarding
other factors exacerbating CVD (eg,
smoking, diets high in saturated fats),
further attention to social connections is
needed in research and public health sur-
veillance, prevention and intervention
efforts. Those efforts will necessarily inte-
grate methods and ndings from related
disciplines and expand the complexity of
research questions and analyses.
Twitter Follow Julianne Holt-Lunstad at @jholtlunstad
Contributors JHL and TBS participated in the drafting
of this editorial and take full responsibility for its
content.
Competing interests None declared.
Provenance and peer review Commissioned;
internally peer reviewed.
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Holt-Lunstad J, Smith TB. Heart Month 2016 Vol 0 No 0 3
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inquiry
evidence-based patient care and scientific
factors for CVD: implications for
Loneliness and social isolation as risk
Julianne Holt-Lunstad and Timothy B Smith
published online April 18, 2016Heart
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The quality and quantity of individuals' social relationships has been linked not only to mental health but also to both morbidity and mortality. This meta-analytic review was conducted to determine the extent to which social relationships influence risk for mortality, which aspects of social relationships are most highly predictive, and which factors may moderate the risk. Data were extracted on several participant characteristics, including cause of mortality, initial health status, and pre-existing health conditions, as well as on study characteristics, including length of follow-up and type of assessment of social relationships. Across 148 studies (308,849 participants), the random effects weighted average effect size was OR = 1.50 (95% CI 1.42 to 1.59), indicating a 50% increased likelihood of survival for participants with stronger social relationships. This finding remained consistent across age, sex, initial health status, cause of death, and follow-up period. Significant differences were found across the type of social measurement evaluated (p<0.001); the association was strongest for complex measures of social integration (OR = 1.91; 95% CI 1.63 to 2.23) and lowest for binary indicators of residential status (living alone versus with others) (OR = 1.19; 95% CI 0.99 to 1.44). The influence of social relationships on risk for mortality is comparable with well-established risk factors for mortality. Please see later in the article for the Editors' Summary.
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Social support has been reliably related to lower rates of morbidity and mortality. An important issue concerns the physiological mechanisms by which support influences such health endpoints. In this review, I examine evidence linking social support to changes in cardiovascular, neuroendocrine, and immune function. Consistent with epidemiological evidence, social support appears to be related to more positive "biological profiles" across these disease-relevant systems. Recent research on immune-mediated inflammatory processes is also starting to provide data on more integrative physiological mechanisms potentially linking social support to health. The implications of these links, along with future research directions are discussed.
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The concept of the risk factor for chronic diseases, such as cardiovascular disorders, is derived from the application of epidemiological methods initially developed for infectious and nutritional deficiency diseases to chronic conditions to identify the factor(s) linked to the development of the chronic disease. Typically in infectious or nutritional deficiency conditions, a single causative agent or primary cause is identified. Thus, the cause of tuberculosis is the tubercle bacillus, and the cause of pellagra is niacin deficiency. However, for cardiovascular diseases, in which causes are usually complex and multifactorial, new concepts were required. For example, individuals with hypertension have a far greater risk for cardiovascular disease than those without hypertension, but many individuals with hypertension never have clinical sequelae, and many individuals with diagnosed cardiovascular diseases have no hypertension. One can also argue that many individuals who are exposed to the tubercle bacillus do not develop clinical tuberculosis, but the converse is not true; no one has tuberculosis without the tubercle bacillus. This provides a clear distinction between multifactorial diseases, such as coronary disease where the risk factor concept is paramount, and other health conditions. The initial application of the risk factor concept was well developed long before the term was coined. Early in the previous century, insurance companies noted that individuals with high blood pressure were at higher risk for premature mortality1 and therefore would be accepted for life insurance only on payment of an additional premium. Insurance companies also recognized the related risk factor of obesity, and imposed higher premiums on overweight clients. In this context, risk factors are used as predictors of disease and mortality. Surprisingly, insurance companies failed to recognize the enormous contribution of smoking to cardiovascular risk until later. Although the underlying concept had been widely discussed and applied, the term “risk factor” was …
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In a review of the literature from 1948 to 2001, 122 studies were found that correlated structural or functional social support with patient adherence to medical regimens. Meta-analyses establish significant average r-effect sizes between adherence and practical, emotional, and unidimensional social support; family cohesiveness and conflict; marital status; and living arrangement of adults. Substantive and methodological variables moderate these effects. Practical support bears the highest correlation with adherence. Adherence is 1.74 times higher in patients from cohesive families and 1.53 times lower in patients from families in conflict. Marital status and living with another person (for adults) increase adherence modestly. A research agenda is recommended to further examine mediators of the relationship between social support and health.
  • J Holt-Lunstad
  • T B Smith
Holt-Lunstad J, Smith TB. Heart Month 2016 Vol 0 No 0