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The aims of the study were to (1) analyze the association between negative aspects of close relationships and increased risk for coronary heart disease and (2) examine whether the association is stronger among women and people of lower social position. Prospective cohort study of 9011 British civil servants (6114 men and 2897 women). Negative aspects of close relationships and other social support measures (confiding/emotional and practical) were assessed with the Close Persons Questionnaire during phase 2 (1989-1990) or phase 1 (1985-1988). Associations between negative aspects of close relationships and incident coronary events were determined during an average follow-up period of 12.2 years. Covariates included sociodemographic characteristics (age, sex, marital status, and employment grade), biological factors (obesity, hypertension, diabetes mellitus, and cholesterol level), psychosocial factors (negative affectivity, depression, and work stress), and health behaviors (smoking, alcohol intake, exercise, and fruit and vegetable consumption). After adjustment for sociodemographic characteristics, biological factors, and other dimensions of social support, individuals who experienced negative aspects of close relationships had a higher risk of incident coronary events (hazard ratio, 1.34; 95% confidence interval, 1.10-1.63). The association was attenuated but remained statistically significant after additional adjustment for negative affectivity and depression (hazard ratio, 1.25; 95% confidence interval, 1.02-1.55). Although women and men in a lower employment grade were more likely to be exposed to negative aspects of close relationships, sex and social position had no statistically significant interaction effects. Confiding/emotional and practical support were not associated with incident coronary events. Adverse close relationships may increase the risk of heart disease.
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ORIGINAL INVESTIGATION
Negative Aspects of Close Relationships
and Heart Disease
Roberto De Vogli, PhD, MPH; Tarani Chandola, DPhil; Michael Gideon Marmot, PhD, FRCP
Background: The aims of the study were to (1) ana-
lyze the association between negative aspects of close re-
lationships and increased risk for coronary heart dis-
ease and (2) examine whether the association is stronger
among women and people of lower social position.
Methods: Prospective cohort study of 9011 British civil
servants (6114 men and 2897 women). Negative as-
pects of close relationships and other social support mea-
sures (confiding/emotional and practical) were assessed
with the Close Persons Questionnaire during phase 2
(1989-1990) or phase 1 (1985-1988). Associations be-
tween negative aspects of close relationships and inci-
dent coronary events were determined during an aver-
age follow-up period of 12.2 years. Covariates included
sociodemographic characteristics (age, sex, marital sta-
tus, and employment grade), biological factors (obesity,
hypertension, diabetes mellitus, and cholesterol level),
psychosocial factors (negative affectivity, depression, and
work stress), and health behaviors (smoking, alcohol in-
take, exercise, and fruit and vegetable consumption).
Results: After adjustment for sociodemographic char-
acteristics, biological factors, and other dimensions of so-
cial support, individuals who experienced negative as-
pects of close relationships had a higher risk of incident
coronary events (hazard ratio, 1.34; 95% confidence in-
terval, 1.10-1.63). The association was attenuated but re-
mained statistically significant after additional adjust-
ment for negative affectivity and depression (hazard ratio,
1.25; 95% confidence interval, 1.02-1.55). Although
women and men in a lower employment grade were more
likely to be exposed to negative aspects of close relation-
ships, sex and social position had no statistically signifi-
cant interaction effects. Confiding/emotional and prac-
tical support were not associated with incident coronary
events.
Conclusion: Adverse close relationships may increase
the risk of heart disease.
Arch Intern Med. 2007;167(18):1951-1957
A
N EXTENSIVE BODY OF RE-
search shows that social re-
lations are associated with
better health
1,2
and re-
duced risks of cardiovas-
cular disease.
3-6
However, contradictory
findings on the health benefits of struc-
tural support
6
and the limited protective
effect of marital status against cardiovas-
cular disease among women
7,8
have stimu-
lated further scientific inquiry into the
quality of social relationships.
Emerging theoretical concepts and em-
pirical evidence indicate that negative as-
pects of close relationships, although oc-
curring less often than positive exchanges,
have more potent effects in determining
daily mood and well-being.
9-12
A longitu-
dinal study of older adults, which evalu-
ated comparable measures of positive and
negative social exchanges, showed that
negative exchanges were associated with
negative affect both cross-sectionally and
during a period of 3 months. Positive ex-
changes, however, exhibited only a cross-
sectional association with positive affect
but no association with negative affect
cross-sectionally or longitudinally.
13
Other
studies showed that negative interper-
sonal interactions are associated with
poorer mental health, physical function-
ing,
14
and sickness absence.
15
So far, little research has examined the
association between negative aspects of
close relationships and coronary heart dis-
ease (CHD). Poor marital quality was an
important prognostic factor for myocar-
dial infarction (MI)
16
and congestive heart
failure.
17
A recent cohort study analyzing
marital quality and the occurrence of the
metabolic syndrome
18
(a cluster of risk fac-
tors for cardiovascular disease
19
and dia-
betes mellitus
20
) found that maritally dis-
satisfied women were 3 times more likely
to have the metabolic syndrome than were
maritally satisfied women.
21
Evidence suggests that negative as-
pects of close relationships are more likely
to be seen in women and people in lower
social positions. Women are more likely
Author Affiliations:
International Institute for
Society and Health, Department
of Epidemiology and Public
Health, University College
London, London, England.
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to be sensitive and invest more time and energy in so-
cial relationships than are men.
22
Women report higher
psychological distress and negative social interactions,
despite having more close relationships and giving and
receiving more support than men.
23,24
People of lower social position are generally more likely
to be exposed to stressful socioeconomic circumstances
25
that can negatively influence interpersonal relationships.
A recent study showed that financial strain was associ-
ated with negative interactions with relatives and depres-
sive symptoms.
26
Another investigation showed that older
adults living in deteriorated neighborhoods were more
likely to encounter negative exchanges with family mem-
bers and friends.
27
A prospective investigation among the
elderly persons showed that cumulative exposure to nega-
tive interactions was associated with self-reported heart
disease over a 6-year period, but only among the partici-
pants who had less than a high school education.
28
The aims of the present study were to (1) analyze the
association between negative aspects of close relation-
ships and increased risk for CHD and (2) examine whether
the association is stronger among women and people of
lower social position.
METHODS
STUDY POPULATION
The target population of the Whitehall II study, a prospective
cohort study, is all nonindustrial civil servants aged 35 to 55
years who worked in the London offices of 20 civil service de-
partments at baseline (1985-1988). Full details of the meth-
ods of the final cohort, which consisted of 10 308 subjects (3414
women), are reported elsewhere.
29
The present study in-
cluded 9011 respondents (6114 men and 2897 women) with
available information on negative aspects of close relation-
ships in phase 2 (1989-1990) or phase 1 (1985-1988) and no
history of CHD events in phase 2. The association between nega-
tive aspects of close relationships and incident CHD events was
determined over an average follow-up period of 12.2 years.
NEGATIVE ASPECTS OF CLOSE RELATIONSHIPS
AND SOCIAL SUPPORT
In phase 2, 7907 participants completed the Close Persons Ques-
tionnaire (available from the authors on request), which in-
cludes 15 items about negative aspects of close relationships, con-
fiding/emotional support, and practical support received in the
past 12 months. In phase 1, 7669 participants completed the ques-
tionnaire (only 74.39% of respondents were asked to complete
it). The 3 subscales were derived from the items using factor analy-
sis.
30
Although the questionnaire assesses social relationships rela-
tive to a maximum of 4 close relationships, our analyses fo-
cused on the first close relationship only, for which the reliability
was the highest.
30
Negative aspects of close relationships, a 4-item
scale, refer to adverse exchanges and conflict within a relation-
ship nominated by the respondents as their closest one. Sources
of negative aspects of close relationships were divided into 2 cat-
egories: partner or not partner. Confiding/emotional support is
a 7-item scale measuring wanting to confide, confiding, sharing
interests, boosting self-esteem, and reciprocity relative to the first
close relationship. Practical support, also referred to as instru-
mental support, is a 3-item scale that measures major and mi-
nor practical help or support received from the closest person.
30
Each item of the 3 social support measures has been evaluated
on a Likert scale from 1 to 4, with higher scores indicating more
negative aspects for the negative aspect items or more positive
support for scales of confiding/emotional and practical support.
The Likert-scaled responses for the items of each social support
scale were summed. For those with missing scores at phase 2,
we used information from phase 1 when available. The final scores
were grouped into tertiles representing different levels of expo-
sure to negative aspects of close relationships, confiding/
emotional, and practical support.
The Close Persons Questionnaire has been validated in terms
of reliability and validity. Cronbach was 0.63 for negative as-
pects of close relationships, 0.85 for confiding/emotional sup-
port, and 0.82 for practical support. A retest reliability study
of 4-week intervals showed moderately high agreement for nega-
tive close relationships (r=0.72) and practical support (r=0.71),
and high agreement for confiding/emotional support (r=0.88).
To evaluate validity, the questionnaire was sent to the person
closest to each of the last 60 interviewees who nominated a close
relationship. Negative aspects of close relationships showed the
best agreement between the report of respondent and the first
close relationship (r= 0.65 for female spouse and r=0.40 for male
spouse).
30
INCIDENT CORONARY EVENTS
The main outcome variable was a measure of incident coro-
nary events between phase 2 (1989-1990) and the end of phase
7 (2003-2004), including fatal MI, nonfatal MI, or angina from
clinical records (electrocardiograms [ECGs] and hospital or gen-
eral practitioner records) and excluding those events that were
self-reported. To assess fatal MI, participants’ records were
flagged for mortality at the National Health Service Central Reg-
istry (mortality data were corroborated by other sources in-
cluding the death certificate). Deaths resulting from MI were
given codes 410-414 from the International Classification of Dis-
eases, 9th Revision.
15
Potential new cases of nonfatal MI were
ascertained with questionnaire items on chest pain
16
and phy-
sician’s diagnosis of heart attack. Details of physician diag-
noses and investigation results were sought from medical rec-
ords for all potential cases of MI. Resting ECGs were performed
(Siemens Mingorec, Siemens Medical Solutions, Erlangen, Ger-
many) and assigned Minnesota codes.
17
Based on all available
data (from questionnaire, study ECGs, hospital acute ECGs,
and cardiac enzymes), nonfatal MI was defined using MONICA
(Multinational Monitoring of Trends and Determinants in Car-
diovascular Disease) criteria.
18
Classification of MI was car-
ried out blind to other study data independently by 2 trained
coders, with adjudication by a third in the (rare) event of dis-
agreement. Angina was initially assessed through participants’
reports of symptoms
19
and then corroborated by medical rec-
ords or abnormalities on a resting ECG, exercise ECG, or coro-
nary angiogram. The outcome was composed of clinically veri-
fied incident coronary events only.
31
Actual dates of events were
used from National Health Service records.
COVARIATES
Covariates at baseline included sociodemographic character-
istics such as age, sex, marital status (married or cohabiting;
never married; and separated, widowed, or divorced), and em-
ployment grade (administrative, executive, and clerical), as well
as biological, psychosocial, and behavioral factors. Biological
factors were measured in phase 1 and included hypertension
(use of antihypertensive medication or systolic/diastolic blood
pressure 140/90 mm Hg vs others), serum total cholesterol
concentration (measured in millimoles per liter), obesity (body
mass index [calculated as weight in kilograms divided by height
in meters squared] 30), and self-reported diabetes mellitus.
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Psychosocial factors included depression, negative affectiv-
ity, and work stress, and were measured in phase 2 or phase 1.
Negative affectivity was measured by the negative affect sub-
scale of the Affect Balance Scale.
32
Participants were divided into
3 tertiles of negative affectivity (lowest, middle, and highest).
Depression was assessed by the depression subscale of the Gen-
eral Health Questionnaire.
33
The scores on the General Health
Questionnaire depression subscale ranged from 0 to 12, with
those scoring 4 or higher being classified as “depressed.” Mea-
sures of work stress (high demands and low job control) were
assessed by an adapted version of the job content instru-
ment.
34
For each participant, we calculated the means of job
demands and job control scores and assigned them in the low-
est, middle, or highest tertile. For those participants with miss-
ing items in phase 2 in any of the psychosocial factors, we used
information from phase 1.
Health behaviors were measured in phase 2 and included
smoking (smoker or nonsmoker), alcohol intake (none, mod-
erate [1-21 units/wk for men and 1-14 units/wk for women],
and heavy drinking [21 units/wk for men and 14 for wom-
en]), exercise (vigorous or 1.5 h/wk of vigorous activity, mod-
erate or 1.5 h/wk of moderate activity, and none/mild or 1.5
h/wk of moderate or vigorous activity), and fruit and veg-
etable consumption (daily vs not daily). Missing data in phase
2 were replaced by equivalent behavioral data from phase 1.
STATISTICAL ANALYSIS
The
2
test for trend, the test for heterogeneity, and the analy-
sis of variance were used to assess the linearity or differences
across categories of negative aspects of close relationships by
sex. Survival analyses using Cox proportional hazards models
were used to analyze the association between negative close re-
lationships and incident coronary events during follow-up af-
ter adjustment for other covariates. The proportional hazards
assumption was checked by examining the interaction term be-
tween each of the covariates and time. None of these interac-
tion term regression coefficients were significantly different from
zero. In addition, multicollinearity assumptions were exam-
ined through a correlation matrix of regression coefficients. In
model 1, the association between adverse close relationships
and heart disease was adjusted for sociodemographic charac-
teristics, biological factors, and source of support. Additional
adjustments for negative affectivity and depression were made
in model 2. In model 3, measures of work stress (job demands
and job control) were added to the model. Model 4 addition-
ally adjusted for health behaviors (smoking, exercise, alcohol
intake, and fruit and vegetable consumption).
The role of sex, social position, and other potential effect modi-
fiers (source of support, marital status, confiding/emotional sup-
port, and practical support) were tested by analyzing the statis-
tical significance of age-adjusted interaction terms. All P values
(2-tailed) below .05 were considered to be statistically signifi-
cant. The relation between negative close relationships and coro-
nary events was analyzed using samples less than the total sample
size because fully adjusted models included only participants with
no missing data on all covariates. Participants with a history of
coronary events in phase 2 were excluded from the analyses. All
analyses were performed using the software package SPSS, ver-
sion 11.0 (SPSS Inc, Chicago, Illinois).
RESULTS
Table 1 shows characteristics of the participants by dif-
ferent levels of exposure to negative close relationships and
by sex. Negative close relationships were more likely to
be experienced by younger individuals, women (data not
shown), and men in the lower employment grade, and were
less likely to be reported by people who were never mar-
ried. Exposure to negative close exchanges was also asso-
ciated with negative affectivity, depression, work stress,
low confiding/emotional support, and partner as a source
of support. Men experiencing adverse close relationships
were less likely to consume fruit and vegetables daily. There
were no statistically significant differences in terms of prac-
tical support, smoking, exercise, and alcohol intake.
Of 8499 participants free of CHD at baseline and with
no missing values on all covariates, 589 reported a coro-
nary event.
Table 2 displays the hazard ratios of inci-
dent CHD by reports of negative aspects of close rela-
tionships and other measures of social support (confiding/
emotional and practical). After adjustment for age, sex,
marital status, employment grade, obesity, hyperten-
sion, diabetes mellitus, cholesterol level, social support
dimension, and source of support (model 1), a dose-
response association was seen between greater reports
of stressful close relationships and incident CHD. Indi-
viduals who experienced a high level of negative aspects
of close relationships were 1.34 times (95% confidence
interval, 1.10-1.63) more likely to experience an inci-
dent CHD event compared with those with a low level
of negative close relationships. When additionally ad-
justing for negative affectivity and depression (model 2),
the relationship was attenuated (HR, 1.25; 95% confi-
dence interval, 1.02-1.55) but remained statistically sig-
nificant. The effect size of the relationship remained un-
changed when measures of work stress such as job
demands and job control (model 3) were included. Ad-
ditional adjustment for health-related behaviors (exer-
cise, smoking, alcohol intake, and fruit and vegetable con-
sumption) (model 4) had little effect on the relationship.
Confiding/emotional and practical support were not as-
sociated with incident coronary events.
Table 3 examines the association between negative
aspects of close relationships and incident coronary events
by sex and employment grade. No statistically signifi-
cant interaction effects were found for either. We also
analyzed additional interaction terms (marital status,
source of support, confiding/emotional support, practi-
cal support, negative affectivity, depression, and work
stress). Interaction effects were observed in some cases:
the association between negative close relationships and
incident coronary events was higher among individuals
reporting their partner as a first close relationship, those
with higher confidential/emotional and practical sup-
port, and those who were widowed, divorced, or sepa-
rated. However, none of the interaction terms reached
statistical significance (P.10 for all).
COMMENT
Results of this study indicate that negative interactions
in close relationships increase the risk of incident CHD.
The effect is independent of sociodemographic charac-
teristics (age, sex, marital status, and employment grade),
biological factors (obesity, hypertension, diabetes melli-
tus, and cholesterol level), psychosocial factors (nega-
tive affectivity, depression, and work stress), and health-
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related behaviors (smoking, alcohol intake, exercise, and
fruit and vegetable consumption). In contrast to our origi-
nal hypotheses, interaction effects by sex and social po-
sition were not statistically significant. Although our find-
ings show that negative interactions in close relationships
are more likely to occur to women and participants in
lower employment grade, they produce similar effects on
heart disease regardless of sex and social position. When
we considered other potential effect modifiers, interac-
tion effects were observed for marital status, source of
support, and confiding/emotional and practical sup-
port, but they failed to reach statistical significance.
Table 1. Characteristics of Participants by Levels of Negative Aspects of Close Relationships by Sex
Characteristic
Negative Aspects of Close Relationships
Men, % Women, %
No.
Tertile
P for
Trend No.
Tertile
P for
Trend
Lowest
(n = 2096)
Middle
(n = 2031)
Highest
(n = 1987)
Lowest
(n = 1036)
Middle
(n = 909)
Highest
(n = 952)
Mean age, y 6114 44.4 43.6 43.7 .001
a
2897 45.9 44.6 44.7 .001
a
Employment grade .001 .45
Administrative 2398 36.1 34.2 29.7 341 30.5 37.0 32.6
Professional 3227 33.5 33.3 33.2 1175 35.2 33.4 31.4
Clerical 489 30.9 27.8 41.3 1381 37.5 28.3 34.2
Marital status .001
b
.18
b
Married/cohabiting 4987 33.7 33.1 33.2 1771 34.8 30.7 34.5
Never married 798 40.4 33.5 26.2 626 38.8 33.7 27.5
Divorced/widowed/separated 315 28.9 34.6 36.5 485 34.8 30.5 34.6
Confiding/emotional support .001 .001
Lowest tertile 2306 30.2 31.7 38.0 938 29.9 32.1 38.1
Middle tertile 1935 29.4 36.0 34.6 1006 33.5 32.2 34.3
Highest tertile 2306 44.4 32.2 23.4 946 44.2 29.8 26.0
Practical support .99 .97
Lowest tertile 2083 35.6 33.4 31.0 1276 36.0 32.4 31.7
Middle tertile 1605 31.3 32.3 36.4 743 32.7 32.6 34.7
Highest tertile 2414 35.3 33.7 31.0 862 38.3 28.5 33.2
Source of support .001 .01
Not partner 4800 36.7 35.3 28.0 1332 36.9 33.3 29.8
Partner 1307 33.6 32.6 33.7 1562 34.7 29.8 35.5
Negative affectivity .001 .001
Lowest tertile 2124 49.5 33.2 17.2 1000 50.0 31.9 18.1
Middle tertile 2040 32.5 35.8 31.7 836 38.9 32.4 28.7
Highest tertile 1929 19.6 30.5 49.9 1029 19.7 30.4 49.9
Depression .001 .001
Not depressed 4646 37.4 33.6 29.0 2044 39.7 31.7 28.6
Depressed 1462 24.4 31.9 43.6 850 26.4 30.5 43.2
Job demands .001 .001
Lowest tertile 1203 36.6 32.7 30.8 877 39.2 30.8 30.0
Middle tertile 2708 35.8 33.4 30.8 1218 36.2 31.6 32.2
Highest tertile 2201 31.2 33.3 35.5 796 31.2 31.8 37.1
Job control .001 .03
Lowest tertile 1277 31.3 30.2 38.4 1377 34.4 29.9 35.7
Middle tertile 2096 32.9 34.1 33.1 865 37.3 32.8 29.8
Highest tertile 2731 36.7 34.0 29.3 641 36.3 33.1 30.6
Smoking .08 .29
No 5245 34.5 33.8 31.6 2290 36.2 31.4 32.4
Yes 780 32.3 30.3 37.7 590 34.1 31.5 34.4
Exercise .98 .39
Mild 1994 34.6 31.6 33.8 1349 33.1 33.7 33.2
Moderate 2625 34.5 34.5 31.0 1198 38.6 29.3 32.1
Vigorous 1399 33.7 33.0 33.4 261 33.7 30.7 35.6
Alcohol consumption .26
b
.52
b
Moderate 4165 34.9 33.3 31.8 1775 36.5 31.3 32.1
Abstinent 834 32.6 30.8 36.6 889 35.3 29.9 34.8
Heavy 1111 33.1 34.8 32.0 250 32.0 37.2 30.8
Fruit and vegetables .001 .21
Daily 3433 36.0 35.0 29.0 1826 36.2 31.9 31.9
Not daily 2668 32.1 31.0 36.9 1069 35.0 30.4 34.6
a
Calculated using F test for linearity.
b
Calculated using the test for heterogeneity.
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Our findings expand and corroborate previous re-
search on the effect of negative aspects of marital quality
in influencing health
35
by showing that negative interac-
tions in close relationships are determinants of coronary
events. This was not the case for confiding/emotional sup-
port and practical support. The possibility that negative close
relationships are more powerful predictors of health than
other aspects of social support is consistent with previous
research findings indicating that individuals tend to men-
tally replay negative encounters more than they replay posi-
tive ones.
36
It is possible that negative aspects of close re-
lationships are more important for the health of individuals
because of the power of negative close relationships to ac-
tivate stronger emotions (worrying and anxiety) and the
consequent physiological effects. In contrast, other more
positive forms of support may not affect the physiology of
individuals in a measurable or clinically relevant way.
37
Pathways linking negative close interactions and heart
disease may include behaviors, emotions, and biologi-
cal reactions. Marital distress has been found to be as-
sociated with poor diet, lack of exercise,
8
substance abuse
such as problem drinking in men,
38
and nonadherence
to medical regimens.
8
However, our results showed that
the association between negative close relationships and
heart disease remained virtually unchanged after con-
trolling for health behaviors. When one considers emo-
tional factors and their biological translation into the body,
research shows that negative marital interactions are as-
sociated with depression, often in combination with re-
duced self-esteem
39
and/or higher levels of anger.
40
These
emotional reactions have been found to influence CHD
41
through the cumulative “wear and tear” on organs and
tissues caused by alterations of autonomic functions, neu-
roendocrine changes, disturbances in coagulation, and
inflammatory and immune responses.
42
Our findings par-
tially support the hypothesis that negative emotions may
mediate the relationship between adverse negative rela-
tionships and heart disease. When we adjusted for emo-
tional factors such as negative affectivity and depres-
sion, the relationship was attenuated.
This study has a number of shortcomings. Our mea-
sure of self-reported negative interactions in close rela-
tionships may not reflect an objective evaluation of this
factor or may be influenced by personality traits or spe-
Table 2. Hazard Ratios (and 95% Confidence Intervals) of Incident Coronary Events
Model 1
a
Model 2
b
Model 3
c
Model 4
d
Cases/No.
Negative aspects of close relationships
Lowest tertile 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 186/2957
Middle tertile 1.19 (0.97-1.46) 1.16 (0.94-1.42) 1.16 (0.94-1.42) 1.15 (0.94-1.42) 189/2785
Highest tertile 1.34 (1.10-1.63) 1.25 (1.02-1.55) 1.25 (1.01-1.54) 1.23 (1.00-1.52) 214/2757
Negative affectivity
Lowest tertile 1 [Reference] 1 [Reference] 1 [Reference] 206/3044
Middle tertile 1.03 (0.84-1.26) 1.01 (0.82-1.24) 1.02 (0.83-1.25) 188/2774
Highest tertile 1.15 (0.93-1.42) 1.10 (0.88-1.37) 1.09 (0.88-1.36) 207/2864
Depression
Not depressed 1 [Reference] 1 [Reference] 1 [Reference] 436/6462
Depressed 1.16 (0.95-1.40) 1.15 (0.95-1.40) 1.14 (0.94-1.39) 165/2220
Confiding/emotional support
Lowest tertile 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 201/2968
Middle tertile 1.05 (0.86-1.28) 1.07 (0.88-1.31) 1.06 (0.87-1.29) 1.06 (0.87-1.30) 186/2723
Highest tertile 1.05 (0.86-1.28) 1.09 (0.89-1.33) 1.08 (0.89-1.33) 1.09 (0.89-1.33) 202/2808
Negative affectivity
Lowest tertile 1 [Reference] 1 [Reference] 1 [Reference] 200/2970
Middle tertile 1.08 (0.88-1.32) 1.05 (0.86-1.29) 1.06 (0.87-1.30) 186/2721
Highest tertile 1.24 (1.01-1.53) 1.19 (0.96-1.46) 1.17 (0.95-1.45) 202/2810
Depression
Not depressed 1 [Reference] 1 [Reference] 1 [Reference] 431/6338
Depressed 1.18 (0.97-1.43) 1.17 (0.97-1.42) 1.16 (0.96-1.41) 158/2161
Practical support
Lowest tertile 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 209/3210
Middle tertile 1.17 (0.95-1.44) 1.17 (0.95-1.44) 1.17 (0.95-1.44) 1.18 (0.96-1.46) 172/2201
Highest tertile 1.01 (0.83-1.24) 1.02 (0.84-1.25) 1.01 (0.83-1.24) 1.03 (0.84-1.26) 210/3100
Negative affectivity
Lowest tertile 1 [Reference] 1 [Reference] 1 [Reference] 202/2957
Middle tertile 1.05 (0.86-1.29) 1.04 (0.85-1.27) 1.04 (0.85-1.28) 185/2719
Highest tertile 1.22 (1.00-1.50) 1.17 (0.95-1.45) 1.16 (0.94-1.44) 204/2817
Depression
Not depressed 1 [Reference] 1 [Reference] 1 [Reference] 430/6350
Depressed 1.20 (0.99-1.46) 1.20 (0.99-1.45) 1.19 (0.98-1.44) 161/2161
a
Model 1 adjusts for age, sex, employment grade, marital status, obesity, hypertension, diabetes mellitus, cholesterol level, social support dimension, and
source of support.
b
Model 2 adjusts for model 1, negative affectivity, and depression.
c
Model 3 adjusts for model 2, job demands, and job control.
d
Model 4 adjusts for model 3, smoking, exercise, alcohol intake, and fruit and vegetable consumption.
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cific characteristics of respondents.
30
Another limita-
tion of our exposure measure is that it is based on the
characteristics of the first close relationship only, of which
64.2% were spouses. This prevented us from investigat-
ing the health effects of negative social interactions in a
more extended network. For the main predictor we used
phase 1 information in cases in which phase 2 informa-
tion was not available. This is a potential limitation be-
cause data may not be missing at random. Compared with
participants with available information on adverse close
relationships in both phases, those with missing infor-
mation in phase 1 but available measures in phase 2 were
slightly younger (44.1 years vs 45.0), more likely to be
in a higher employment grade (P .001), but similar in
terms of sex, biological factors, and incident coronary
events. This suggests that the missing respondents for the
phase 1 measure of negative aspects of close relation-
ships were largely similar to the analytical sample with
the exception of fewer respondents in the high employ-
ment grade. The different periods in which covariates
were measured could be sources of bias because mea-
sures in phase 1 could conceivably have changed by
phase 2. Time variability, together with the use of crude
dichotomous and 3-category measures, may be respon-
sible for the failure of some interaction terms to reach
statistical significance because the strength of all asso-
ciations could have been reduced. However, dichoto-
mous and 3-category measures may be quite stable over
time; when repeating the analysis with phase 2 or phase
1 data only, adjusted for biological factors in phase 1
and demographic, behavioral, and psychosocial factors
in the respective phases, the associations of negative as-
pects of close relationships with incident coronary
events were very similar. Finally, the generalization of
results may also be questioned because British civil ser-
vants may not adequately represent the general popula-
tion (industrial workers were not included). However,
most of the working population is now employed in of-
fice jobs, and the exclusion of the upper and lower ends
of the social hierarchy is likely to have produced an
underestimation of the health effects of negative close
relationships.
In conclusion, a person’s heart condition seems to be
influenced by negative intimate relationships. In this pro-
spective cohort study, we showed that negative aspects
of close relationships, not confiding/emotional support
and practical support, are associated with CHD.
Accepted for Publication: April 29, 2007.
Correspondence: Roberto De Vogli, PhD, MPH, Depart-
ment of Epidemiology and Public Health, University Col-
lege London, 1-19 Torrington Pl, London WC1E 6BT,
England (r.devogli@ucl.ac.uk).
Author Contributions: Study concept and design: De Vogli,
Chandola, and Marmot. Acquisition of data: De Vogli,
Chandola, and Marmot. Analysis and interpretation of data:
De Vogli, Chandola, and Marmot. Drafting of the manu-
script: De Vogli and Chandola. Critical revision of the
manuscript for important intellectual content: Chandola and
Marmot. Statistical analysis: De Vogli and Chandola.
Obtained funding: Chandola. Study supervision: Marmot.
Financial Disclosure: None reported.
Funding/Support: The Whitehall II Study was sup-
ported by grants from the Medical Research Council, Brit-
ish Heart Foundation, Health and Safety Executive, and
Department of Health; grant HL36310 from the Na-
tional Heart, Lung, and Blood Institute, grant AG13196
from the National Institute on Aging, and grant HS06516
from the Agency for Health Care Policy Research, all part
of the National Institutes of Health; and a grant from the
John D. and Catherine T. MacArthur Foundation Re-
search Networks on Successful Midlife Development and
Socioeconomic Status and Health.
Additional Contributions: We are grateful for the con-
tributions of all members of the Whitehall II Study team
and extend our gratitude to all participating civil servants
in the Whitehall II Study; the participating civil service de-
partments, their welfare, personnel, and establishment offi-
cers; the Occupational Health and Safety Agency, Lon-
don; and the Council of Civil Service Unions, London.
Table 3. Interaction Effects Among Negative Aspects
of Close Relationships, Sex, and Social Position
and Additional Interaction Terms
Characteristic
Negative Aspects of Close Relationships
by Tertile, Age-Adjusted HR (95% CI)
Lowest Middle Highest
Sex
Men 1 [Reference] 1.28 (1.02-1.61) 1.30 (1.04-1.63)
Women 1 [Reference] 0.99 (0.66-1.48) 1.31 (0.91-1.89)
P for interaction
.39
a
Employment grade
High 1 [Reference] 1.39 (1.00-1.91) 1.09 (0.77-1.55)
Middle 1 [Reference] 1.13 (0.83-1.52) 1.48 (1.12-1.96)
Low 1 [Reference] 1.08 (0.69-1.69) 1.25 (0.83-1.88)
P for interaction
.96
b
Close relationship
Close relationship
or partner
1 [Reference] 1.26 (0.89-1.80) 1.04 (0.71-1.53)
Close relationship
is partner
1 [Reference] 1.17 (0.93-1.49) 1.39 (1.11-1.74)
P for interaction
.23
a
Practical support
Low 1 [Reference] 1.31 (0.95-1.80) 1.19 (0.86-1.66)
Medium 1 [Reference] 1.36 (0.94-1.96) 1.15 (0.79-1.67)
High 1 [Reference] 1.00 (0.71-1.41) 1.53 (1.12-2.09)
P for interaction
.11
b
Confiding/emotional
support
Low 1 [Reference] 1.06 (0.75-1.50) 1.18 (0.85-1.63)
Medium 1 [Reference] 1.27 (0.89-1.81) 1.34 (0.95-1.90)
High 1 [Reference] 1.32 (0.95-1.83) 1.44 (1.03-2.02)
P for interaction
.89
b
Marital status
Married/cohabiting 1 [Reference] 1.20 (0.96-1.50) 1.32 (1.06-1.64)
Never married 1 [Reference] 1.20 (0.72-2.01) 1.09 (0.62-1.91)
Widowed/divorced/
separated
1 [Reference] 1.36 (0.68-2.74) 1.43 (0.73-2.79)
P for interaction
.68
b
Abbreviations: CI, confidence interval; HR, hazard ratio.
a
Interaction test between negative social support and covariate on 2 df.
b
Interaction test between negative social support and covariate on 4 df.
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... With a closer look, the overall assessment as a "negative relationship" is problematic. Negative aspects are usually associated with ambivalence or with a simultaneity of positive and negative aspects of the relationship, since a purely negative relationship, according to Klein Ikkink and van Tilburg (1999), is usually dissolved due to a lack of benefit (on ambivalence, see also Ajzen, 2001;Coser, 1956;Lüscher, 2011;Ross et al., 2019;Simmel, 1950Simmel, [1908). In accordance with the equal importance of both aspects of the relationship, individuals will find it difficult to give a positive or negative overall assessment. ...
... The stress-induced development of disease (allostasis) has already been widely researched (e.g., Rensing, 2013). The association between social stress and cardiovascular diseases is well known, for example, in the case of high blood pressure (Sneed & Cohen, 2014), coronary heart disease (Orth-Gomér, 2007de Vogli et al., 2007), or strokes (Tanne et al., 2004). The endocrine system (hormone balance) is also altered by negative interactions. ...
... For example, special negative ties could be a sign of exclusion (e.g., having a bully). They can also be a sign for integration, because they seem to occur mostly in close relationships (Coser, 1956). Just how and under which conditions negative ties contribute to social strain has yet to be revealed. ...
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Thanks to improvements in living standards and health behavior as well as medical progress since the second half of the twentieth century, old age has become a life phase in its own right. This phase usually begins by the transition from working life to retirement (Kohli, 2000). Both the chance of reaching retirement and the life expectancy after retirement have increased significantly (Eisenmenger & Emmerling, 2011). The post-work phase spans several decades for many people now. In addition, people who retire are considerably healthier and more independent than their peers of earlier birth cohorts (Crimmins, 2004). The expansion of this phase of life has been accompanied by a differentiation of older people in terms of health and independence: healthy and active people experience this phase, as do people in need of help and care. This fact is considered by distinguishing between old and very old people (Baltes, 2007). Characteristics of old age are absence of non-compensable health restrictions, self-determination of various activities (e.g., traveling, hobbies, voluntary work), and strong social integration. Overall, the demands of old age can be coped well in this phase. Very old age is characterized by an increase in physical and cognitive losses and diseases, and a decrease in the abilities and possibilities of compensating for deficits (Baltes, 1997; Baltes & Smith, 2003).
... With a closer look, the overall assessment as a "negative relationship" is problematic. Negative aspects are usually associated with ambivalence or with a simultaneity of positive and negative aspects of the relationship, since a purely negative relationship, according to Klein Ikkink and van Tilburg (1999), is usually dissolved due to a lack of benefit (on ambivalence, see also Ajzen, 2001;Coser, 1956;Lüscher, 2011;Ross et al., 2019;Simmel, 1950Simmel, [1908). In accordance with the equal importance of both aspects of the relationship, individuals will find it difficult to give a positive or negative overall assessment. ...
... The stress-induced development of disease (allostasis) has already been widely researched (e.g., Rensing, 2013). The association between social stress and cardiovascular diseases is well known, for example, in the case of high blood pressure (Sneed & Cohen, 2014), coronary heart disease (Orth-Gomér, 2007de Vogli et al., 2007), or strokes (Tanne et al., 2004). The endocrine system (hormone balance) is also altered by negative interactions. ...
... For example, special negative ties could be a sign of exclusion (e.g., having a bully). They can also be a sign for integration, because they seem to occur mostly in close relationships (Coser, 1956). Just how and under which conditions negative ties contribute to social strain has yet to be revealed. ...
... With a closer look, the overall assessment as a "negative relationship" is problematic. Negative aspects are usually associated with ambivalence or with a simultaneity of positive and negative aspects of the relationship, since a purely negative relationship, according to Klein Ikkink and van Tilburg (1999), is usually dissolved due to a lack of benefit (on ambivalence, see also Ajzen, 2001;Coser, 1956;Lüscher, 2011;Ross et al., 2019;Simmel, 1950Simmel, [1908). In accordance with the equal importance of both aspects of the relationship, individuals will find it difficult to give a positive or negative overall assessment. ...
... The stress-induced development of disease (allostasis) has already been widely researched (e.g., Rensing, 2013). The association between social stress and cardiovascular diseases is well known, for example, in the case of high blood pressure (Sneed & Cohen, 2014), coronary heart disease (Orth-Gomér, 2007de Vogli et al., 2007), or strokes (Tanne et al., 2004). The endocrine system (hormone balance) is also altered by negative interactions. ...
... For example, special negative ties could be a sign of exclusion (e.g., having a bully). They can also be a sign for integration, because they seem to occur mostly in close relationships (Coser, 1956). Just how and under which conditions negative ties contribute to social strain has yet to be revealed. ...
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“Tell me how much your friends earn and I’ll tell you whether you smoke, what diseases you have and how old you’re going to become!” Part of this statement should be familiar to those who are interested in the connection between social inequality and health. People of comparatively lower socioeconomic status are at higher risk of health problems and are more likely to fall ill and die earlier than those who have a higher income etc. However, the sentence does not ask about your own income, but about the income of your friends. Is this information really meaningful? Does it really make a difference to your own health which friends you have, who you surround yourself with in your everyday life and what social position these people have?
... With a closer look, the overall assessment as a "negative relationship" is problematic. Negative aspects are usually associated with ambivalence or with a simultaneity of positive and negative aspects of the relationship, since a purely negative relationship, according to Klein Ikkink and van Tilburg (1999), is usually dissolved due to a lack of benefit (on ambivalence, see also Ajzen, 2001;Coser, 1956;Lüscher, 2011;Ross et al., 2019;Simmel, 1950Simmel, [1908). In accordance with the equal importance of both aspects of the relationship, individuals will find it difficult to give a positive or negative overall assessment. ...
... The stress-induced development of disease (allostasis) has already been widely researched (e.g., Rensing, 2013). The association between social stress and cardiovascular diseases is well known, for example, in the case of high blood pressure (Sneed & Cohen, 2014), coronary heart disease (Orth-Gomér, 2007de Vogli et al., 2007), or strokes (Tanne et al., 2004). The endocrine system (hormone balance) is also altered by negative interactions. ...
... For example, special negative ties could be a sign of exclusion (e.g., having a bully). They can also be a sign for integration, because they seem to occur mostly in close relationships (Coser, 1956). Just how and under which conditions negative ties contribute to social strain has yet to be revealed. ...
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The loss of employment is an event that interferes with the lives of everyone affected, causes stress, and can have a negative impact on their health. Meta-analyses show that unemployed people have a worse state of health and a mortality risk that is at least 1.6 times higher than those who are employed. Unemployment is associated with a lower mental and physical health status and, in some cases, with riskier health behavior (particularly tobacco consumption). There are two important theses on the role of social networks in this context: (1) Unemployment changes social networks so that they no longer fulfill their positive function for health (mediator thesis); (2) Unemployment leaves social networks unchanged and persons with resource-rich networks suffer less from health losses due to unemployment (moderator thesis). This article provides an overview of empirical analyses on the topic of networks and unemployment.
... With a closer look, the overall assessment as a "negative relationship" is problematic. Negative aspects are usually associated with ambivalence or with a simultaneity of positive and negative aspects of the relationship, since a purely negative relationship, according to Klein Ikkink and van Tilburg (1999), is usually dissolved due to a lack of benefit (on ambivalence, see also Ajzen, 2001;Coser, 1956;Lüscher, 2011;Ross et al., 2019;Simmel, 1950Simmel, [1908). In accordance with the equal importance of both aspects of the relationship, individuals will find it difficult to give a positive or negative overall assessment. ...
... The stress-induced development of disease (allostasis) has already been widely researched (e.g., Rensing, 2013). The association between social stress and cardiovascular diseases is well known, for example, in the case of high blood pressure (Sneed & Cohen, 2014), coronary heart disease (Orth-Gomér, 2007de Vogli et al., 2007), or strokes (Tanne et al., 2004). The endocrine system (hormone balance) is also altered by negative interactions. ...
... For example, special negative ties could be a sign of exclusion (e.g., having a bully). They can also be a sign for integration, because they seem to occur mostly in close relationships (Coser, 1956). Just how and under which conditions negative ties contribute to social strain has yet to be revealed. ...
Chapter
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The influence and significance of social networks in health research are becoming widely discussed. Sociological network research meets the demand for a stronger consideration of “contexts” or the “environment” that influences health and care. Social networks are conceived as a mediating meso-level, which mediates between social macro-structures (e.g., healthcare systems, institutions, and organizations) and individual (not always) rationally acting actors. This perspective offers the possibility to analyze a variety of psychosocial mechanisms. These mechanisms can influence individual health in different ways, including (health) behavior, psyche, or physiology. In this chapter we present some central theoretical concepts, as well as empirical results, on network effects under the headings of “social support,” “social integration,” “social influence,” and “social contagion.”
... With a closer look, the overall assessment as a "negative relationship" is problematic. Negative aspects are usually associated with ambivalence or with a simultaneity of positive and negative aspects of the relationship, since a purely negative relationship, according to Klein Ikkink and van Tilburg (1999), is usually dissolved due to a lack of benefit (on ambivalence, see also Ajzen, 2001;Coser, 1956;Lüscher, 2011;Ross et al., 2019;Simmel, 1950Simmel, [1908). In accordance with the equal importance of both aspects of the relationship, individuals will find it difficult to give a positive or negative overall assessment. ...
... The stress-induced development of disease (allostasis) has already been widely researched (e.g., Rensing, 2013). The association between social stress and cardiovascular diseases is well known, for example, in the case of high blood pressure (Sneed & Cohen, 2014), coronary heart disease (Orth-Gomér, 2007de Vogli et al., 2007), or strokes (Tanne et al., 2004). The endocrine system (hormone balance) is also altered by negative interactions. ...
... For example, special negative ties could be a sign of exclusion (e.g., having a bully). They can also be a sign for integration, because they seem to occur mostly in close relationships (Coser, 1956). Just how and under which conditions negative ties contribute to social strain has yet to be revealed. ...
Chapter
Full-text available
“Tell me how much your friends earn, and I’ll tell you if you smoke, what diseases you have and how long your life will be!” With this somewhat pointed statement, we wanted to shed light on the empirically well-confirmed connection between social and health inequalities from the perspective of network research at the beginning of this book (see chapter “Social networks and health inequalities: a new perspective for research”). Social networks are understood here as mediating entities at an intermediate or meso-level, whose structure and function mediate between vertical (income, education, occupational status, etc.) as well as horizontal (e.g., age, gender, ethnic origin) inequalities and health inequalities (e.g., life expectancy, morbidity rates). Besides this mediating influence a moderating relationship wherein social networks amplify or diminish vertical and horizontal inequalities seems to be reasonable.
... With a closer look, the overall assessment as a "negative relationship" is problematic. Negative aspects are usually associated with ambivalence or with a simultaneity of positive and negative aspects of the relationship, since a purely negative relationship, according to Klein Ikkink and van Tilburg (1999), is usually dissolved due to a lack of benefit (on ambivalence, see also Ajzen, 2001;Coser, 1956;Lüscher, 2011;Ross et al., 2019;Simmel, 1950Simmel, [1908). In accordance with the equal importance of both aspects of the relationship, individuals will find it difficult to give a positive or negative overall assessment. ...
... The stress-induced development of disease (allostasis) has already been widely researched (e.g., Rensing, 2013). The association between social stress and cardiovascular diseases is well known, for example, in the case of high blood pressure (Sneed & Cohen, 2014), coronary heart disease (Orth-Gomér, 2007de Vogli et al., 2007), or strokes (Tanne et al., 2004). The endocrine system (hormone balance) is also altered by negative interactions. ...
... For example, special negative ties could be a sign of exclusion (e.g., having a bully). They can also be a sign for integration, because they seem to occur mostly in close relationships (Coser, 1956). Just how and under which conditions negative ties contribute to social strain has yet to be revealed. ...
Chapter
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There are significant differences in morbidity (incidence of disease) and mortality (death rate) between men and women. By puberty, male adolescents are more likely to have health problems. During puberty, girls suffer from chronic and mental illnesses and male adolescents are more likely to suffer from acute and life-threatening diseases. Boys and men have riskier health behavior. The field of research mainly relates to the binarity of the sexes—men and women. Studies on trans and queer persons are rare in this field. Networks have a gender-specific effect on risk behavior. Women provide more and more time-consuming social support, even in case of illness. After widowhood, networks have both negative and positive effects, which are gender-specific.
... Whitney [50] reported that women wanted others to understand and to share information about the symptoms of endometriosis. The quality of one's social relationships is reliably related to positive and negative physical health outcomes [51,52]. Therefore, a social surrounding that is less understanding can have adverse effects on health-on an individual and reciprocal level in endometriosis patients and their partners. ...
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Background Endometriosis is often associated with severe dysmenorrhea, pelvic pain and dyspareunia and has a high impact on daily life as well as sexuality. Quality of partnership positively influences the course of various diseases and ability to cope with emotional and physical distress. However, studies focusing on the male partners of endometriosis patients are rare, and even less is known about the reciprocal relationship in these couples. Therefore, this study aims to explore the interrelations in couples with endometriosis in matters of psychological distress, sexual and partnership satisfaction and social support. Methods The cross-sectional study was conducted in two university-affiliated fertility centres in Germany and Austria with n = 104 female/male couples affected by endometriosis. Participants completed a questionnaire regarding endometriosis, partnership, sexuality, stress, anxiety, depression and social support. Both women and men were asked about the impact of women’s endometriosis-related pain (IEP) on their everyday life (e.g. leisure time). Data were analysed using the Actor-Partner-Interdependence Model. Results Significant partner effects were evident: High depression, anxiety and stress scores in women were associated with a higher IEP in men (all p ≤ 0.01), reciprocally high stress and depression scores in men were correlated with a higher IEP in women (all p ≤ 0.05). Less sexual satisfaction in women was associated with a higher IEP in men ( p = 0.040). There was a significant reciprocal association between the perceived lack of understanding from the social environment and a higher IEP, for both women ( p = 0.022) and men ( p = 0.027). Conclusions The male partner should be taken into account when counselling or treating women with endometriosis. Our study shows a high interdependence and reciprocal influence from both partners—positively and negatively—concerning psychological distress and sexual satisfaction. Furthermore, there ought to be more awareness for the psychosocial impact of endometriosis, especially in regard to social support and understanding. Talking about and improving sexual satisfaction as well as enhancing stress reducing techniques may hold great benefits for dealing with endometriosis. Registration number The study is registered with the German Clinical Trials Register (DRKS), number DRKS00014362.
Chapter
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