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Nabi H, Kivimaki M, De Vogli R, Marmot MG, Singh-Manoux A. Positive and negative affect and risk of coronary heart disease: Whitehall II prospective cohort study. BMJ337:a118


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To examine the associations between positive and negative affect and subsequent coronary heart disease events independently of established risk factors. Prospective cohort study with follow-up over 12 years. 20 civil service departments originally located in London. 10,308 civil servants aged 35-55 years at entry into Whitehall II study in 1985. Fatal coronary heart disease, clinically verified incident non-fatal myocardial infarction, and definite angina (n=619, mean follow-up 12.5 years). In Cox regression analysis adjusted for age, sex, ethnicity, and socioeconomic position, positive affect (hazard ratio=1.01, 95% confidence interval 0.82 to 1.24) and the balance between positive and negative affect, referred to as the affect balance score (hazard ratio=0.89, 0.73 to 1.09), were not associated with coronary heart disease. Further adjustment for behaviour related risk factors (smoking, alcohol consumption, daily fruit and vegetable intake, exercise, body mass index), biological risk factors (hypertension, blood cholesterol, diabetes), and psychological stress at work did not change these results. However, participants in the highest third of negative affect had an increased incidence of coronary events (hazard ratio=1.32, 1.09 to 1.60), and this association remained unchanged after adjustment for multiple confounders. Positive affect and affect balance did not seem to be predictive of future coronary heart disease in men and women who were free of diagnosed coronary heart disease at recruitment to the study. A weak positive association between negative affect and coronary heart disease was found and needs to be confirmed in further studies.
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2008;337;118- BMJ
Archana Singh-Manoux
Hermann Nabi, Mika Kivimaki, Roberto De Vogli, Michael G Marmot and
cohort study
prospectivecoronary heart disease: Whitehall II
Positive and negative affect and risk of
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Positive and negative affect and risk of coronary heart
disease: Whitehall II pros pective cohort study
Hermann Nabi, research fellow,
Mika Kivimaki, professor o f social epi demiology,
Roberto De V ogli,
Michael G Marmot, head of department and director,
Archana Singh-Manoux, senior research
Objective To examine the associations between positive
and negative affect and subsequent coronary heart
disease events independently of established risk factors.
Design Prospective cohort study with follow-up over
12 years.
Setting 20 civil service departments originally located in
Participants 10 308 civil servants aged 35-55 years at
entry into Whitehall II study in 1985.
Main outcome measures Fatal coronary heart disease,
clinically verified incident non-fatal myocardial infarction,
and definite angina (n
619, mean follow-up 12.5 years).
Results In Cox regression analysis adjusted for age, sex,
ethnicity, and socioeconomic position, positive affect
(hazard ratio
1.01, 95% confidence interval 0.82 to 1.24)
and the balance between positive and negative affect,
referred to as the affect balance score (hazard ratio
0.73 to 1.09), were not associated with coronary heart
disease. Further adjustment for behaviour related risk
factors (smoking, alcohol consumption, daily fruit and
vegetable intake, exercise, body mass index), biological
risk factors (hypertension, blood cholesterol, diabetes),
and psychological stress at work did not change these
results. However, participants in the highest third of
negative affect had an increased incidence of coronary
events (hazard ratio
1.32, 1.09 to 1.60), and this
association remained unchanged after adjustment for
multiple confounders.
Conclusions Positive affect and affect balance did not
seem to be predictive of future coronary heart disease in
men and women who were free of diagnosed coronary
heart disease at recruitment to the study. A weak positive
association between negative affect and coronary heart
disease was found and needs to be confirmed in further
Smoking, hypertension, hypercholesterolaemia, and
diabetes are established risk factors for coronary heart
disease, a leading cause of morbidity and mortality in
Western industrialised countries.
However, psycho-
logical factors,suchasemotions, may also have a role in
the development of coronary heart disease.
prosp ective stud ies have found anxiety, hostility/
anger, and depression to be associated with an
increased risk of coronary heart disease in healthy
As the relative importance of these three
negative emotions on risk of coronary heart disease
remains largely undefined,
they have been hypothe-
sised to be the components of a single underlying
factor, labelled negative affect. Negative affect refers to
stable and pervasive individual differences in mood
and self-concept characterised by a general disposition
to experience a variety of aversive emotional states.
High negative affect has been described as a general
tendency to report distress, discomfort, dissatisfac-
tion, an d feelings of hopelessness over time and
regardless of the situation, and low negative affect is
characterised by calmness and serenity.
ing this conceptualisation, a considerable neurobiolo-
gical and psychological overlap betwe en anxiety,
hostility/anger, and depression has previously been
10 11
As attempts to link psychological factors to heart
disease have focused on negative emotions, mostly
whether positive emotions might also
have a role in the development of coronary heart
disease remains unclear. Research suggests that
positive affect and negative affect are two independent
systems and that positive affect is not simply the
opposite of negative affect or an absence of negative
High positive affect refers to a general
tendency to experience a state of high energy, full
concentration, and pleasurable engagement, whereas
low positive affect is characterised by sadness and
Distinct neural networks may exist to
regulate positive and negative emotions; dopamine
metabolism may be associated with positive affect and
serotonin with negative affect,
13 14
supporting the
assertion of the independence of the two types of affect.
We are aware of no previous large scale prospective
studies on the independent effects of negative and
positive affect on coronary heart disease. A six year
follow-up of 2478 older participants in North Carolina
found that positive affect was associated with decreased
risk of stroke, but it did not examine coronary heart
disease as an outcome, and the assessment of negative
Department of Epidemiology and
Public Health, University College
London, London WC1E 6BT
INSERM U687-IFR69, Villejuif,
F-94807, France
pital Sainte P
rine, Centre de
rontologie, Paris, F-75781,
Correspondence to: H Nabi
Cite this as:
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affect was limited to depressive symptoms.
In this
report from the Whitehall II study, we examine the
independent associations of both negative affect and
positive affect with subsequent coronary heart disease
after taking account of established risk factors among
participants followed up over 12 years. In addition, we
examine whether the balance between positive and
negative affect is associated with subsequent coronary
heart disease.
The Whitehall II study, established in 1985, is a
longitudinal study to examine the socioeconomic
gradient in health and disease among 10 308 civil
servants (6895 men and 3413 women).
All civil
servants aged 35-55 years in 20 London based
departments were invited to participate by letter, and
73% agreed. Each participant gave written informed
consent. Baseline examination (phase 1) took place
during 1985-8 and involved a clinical examination and
a self administered questionnaire.
We assessed positive affect and negative affectat phases
1 (1985-8) and 2 (1989-90) by using the Bradburn affect
balance scale,
a widely used measure of psychological
wellbeing. The affect balance scale consists of 10 items,
five of which are used to asse ss positive affect
(Cronbachs α=0.80) and the other five to assess
negative affect (Cronbachs α=0.67). All items are
formulated in general terms, as questions about the
participants feelings during the previous few weeks.
The items ar e phrased to elicit responses of t he
pleasurable or unpleasurable character of an experi-
ence instead of the context of the experience.
Responses in this study are on a four point Likert-
type scale from 0 (not at all) to 3 (a great deal). Scores for
each subscale range from 0 to 15; higher scores indicate
higher positive affect or higher negative affect. The
affect balance score is calculated by subtracting the
negative affect score from the positive affect score and
adding a constant of 15 to avoid negative values. The
affect balance score ranges fro m 0 (lowest affect
balance) to 30 (highest affect balance). Neither natural
thresholds nor clinically based thresholds are defined,
so we divided each scale into low, middle, and high
exposure on the basis of the distribution in the total
study population
positive affect score thirds: lowest
(0-4), middle (5-7), highest (8-15); negative affect score
thirds: lowest (0-1), middle (2-3), highest (4-15); affect
balance score thirds: lowest (0-16), middle (17-20),
highest (21-30). Only 75% of participants were asked to
complete the affect balance scale at phase 1, as this
measure was introduced after the start of the baseline
survey. Where phase 1 data were missing, we used
positive and negative affect scores at phase 2. The
percentages of replacement were 15.0% for positive
affect and 14.3% for negative affect. Correlation
coefficients of scores at phase 1 (1985-8) and phase 2
(1989-90) suggest a moderate degree of consistency of
positive affect (r= 0.52, P<0.001), negative affect
(r=0.55 P<0.001) and affect balance (r=0.54, P<0.001)
across time.
We assessed the incidence of coronary heart disease
from phase 2 (1989-90) to phase 7 (2003-4), a mean
follow-up of 12.5 (SD 3.8) years. Coronary heart
disease included fatal coronary heart disease (defined
by the international classification of diseases, 9th
revision (ICD-9) codes 410-414 or ICD-10 codes I20-
25), first non-fatal myocardial infarction, or first
definite angina. We assessed fatal coronary heart
disease by flagging participants at the NHS central
registry, which provided information on the date and
cause of death. We ascertained potential non-fatal
myocardial infarction through questionnaire items on
chest pain (the World Health Organizations Rose
) and the physicians diagnosis of heart
attack. We based confirmation of myocardial infarc-
tion according to MONICA (multinational monitoring
of trends and determinants in cardiovascular disease
criteria on electrocardiograms, markers of myocardial
necrosis, and history of chest pain from the medical
records. We assessed angina on the basis of partici-
pants reports of symptoms with corroboration in
medical records or abnormalities on a resting electro-
cardiogram, an exercise electrocardiogram, or a
coronary angiogram.
Sociodemographic measures included age, sex, and
socioeconomicposition assessed by British civil service
grade of employment t aken from the phase 1
questionnaire. Conventional risk factors assessed at
phase 1 included smoking status (never, ex-smoker,
and current), hypertension (systolic and diastolic blood
pressure >140/90 mm Hg or treatment for hyperten-
sion), blood cholesterol (<6.2 or 6.2 mmol/l), exercise
(1.5 or <1.5 hours of moderate or vigorous exercise/
week), daily fruit and vegetable intake (yes/no), alcohol
consumption in units of alcohol consumed a week (low:
<22 for men and <15 for women; moderate: 22-51 for
men and 15-35 for women; or high: >51 for men and
>35 for women), body mass index (<20, 20-24.9, 25-
29.9, or 30 kg/m
Psychosocial stress at work (job strain) was measured
at phase 1 with the self administrated job strain model
including scales of psychological job
demands, decision latitude, and social support at
20 21
We replaced missing values at phase 1 with
information at phase 2.
Statistical analyses
We assessed differences in positive affect, negative
affect, and affect balance scores as a function of
sociodemographic characteristics and traditional cor-
onary heart disease risk factors by using one way
analysis of variance, with a linear trend fitted across the
hierarchical variables. We used Cox regression to
assess the age and sex adjusted association between
various covariates and coronary heart disease.
We used six serially adjusted Cox regression models
to model the associations of positive affect, negative
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affect, and affect balance scores with incident coronary
heart disease. We adjusted model 1 for the association
between positive affect and incident coronary heart
disease for sex, age, ethnicity, and employment grade
(that is, potential confounding factors), and the
subsequent models included potential mediators for
the association. Thus, in addition to potential con-
founders, we adjusted model 2 for behaviour related
risk factors, model 3 for biological risk factors, and
model 4 for psychosocial stress at work. We adjusted
model 5 for all of the covariates outlined above and
model 6 for negative affect. We repeated this whole
exercise starting out with negative affect (using positive
affect in model 6) and the affect balance score. We also
checked for interactions between affect measures and
sex in relation to coronary heart disease on a
Table 1
Sample characteristics as a function of positive and negative affect subscales and affect balance scale scores (n
Variables No
Positive affect Negative affect Affect balance
Mean (SD) P value or for trend Mean (SD) P value or for trend Mean (SD) P value or for trend
Sex: <0.001 <0.001 <0.001
Male 6093 6.20 (2.91) 2.72 (2.27) 18.48 (4.01)
Female 2825 5.81 (3.19) 2.94 (2.60) 17.87 (4.59)
Age (years): 0.002 <0.001 <0.001
39-45 2469 6.15 (2.96) 3.15 (2.42) 18.06 (4.23)
45-50 2340 6.19 (2.98) 2.92 (2.41) 18.26 (4.24)
50-55 1827 6.03 (3.07) 2.63 (2.32) 18.40 (4.19)
55-64 2282 5.91 (3.02) 2.40 (2.29) 18.51 (4.16)
Employment grade: <0.001 0.005 <0.001
High 2704 6.55 (2.80) 2.67 (2.19) 18.88 (3.87)
Middle 4370 6.06 (2.99) 2.84 (2.36) 18.21 (4.18)
Low 1844 5.44 (3.20) 2.85 (2.69) 17.58 (4.61)
Ethnicity: <0.001 0.553 <0.001
White 8134 6.17 (2.95) 2.79 (2.36) 18.39 (4.16)
Other 784 5.01 (3.39) 2.84 (2.64) 17.17 (4.58)
Hypertension: 0.147 <0.001 0.113
No 7273 6.10 (3.00) 2.85 (2.39) 18.25 (4.22)
Yes 1645 5.98 (3.04) 2.55 (2.34) 18.44 (4.15)
Smoking status: 0.992 <0.001 0.018
Never smoker 4461 6.02 (2.99) 2.71 (2.31) 18.31 (4.12)
Ex-smoker 2893 6.25 (3.02) 2.80 (2.33) 18.45 (4.20)
Current smoker 1564 5.92 (3.01) 3.01 (2.67) 17.90 (4.43)
Alcohol consumption: 0.028 <0.001 0.527
Low 7515 6.04 (3.00) 2.76 (2.37) 18.29 (4.20)
Moderate 1198 6.30 (3.00) 2.92 (2.38) 18.38 (4.21)
High 205 6.10 (3.09) 3.36 (2.64) 17.75 (4.51)
Exercise (hours/week): <0.001 <0.001 <0.001
1.5 1659 6.83 (2.98) 2.59 (2.20) 19.24 (4.00)
<1.5 7259 5.90 (2.98) 2.84 (2.42) 18.07 (4.22)
Daily fruit and vegetables: <0.001 <0.001 <0.001
Yes 5260 6.26 (3.03) 2.72 (2.36) 18.54 (4.22)
No 3658 5.82 (2.95) 2.90 (2.41) 17.92 (4.16)
Body mass index: 0.234 0.001 0.005
<20 539 5.63 (3.06) 3.19 (2.49) 17.43 (4.42)
20-24.9 4960 6.11 (2.96) 2.81 (2.37) 18.30 (4.13)
25-29.9 2850 6.14 (3.02) 2.68 (2.34) 18.45 (4.23)
30 569 5.92 (3.23) 2.78 (2.54) 18.14 (4.56)
Diabetes: 0.048 0.055 0.13
No 8837 6.08 (3.00) 2.79 (2.39) 18.30 (4.20)
Yes 81 5.42 (3.26) 3.30 (2.33) 17.12 (4.59)
Job strain: <0.001 <0.001 <0.001
No 7859 6.22 (2.99) 2.67 (2.31) 18.55 (4.12)
Yes 1059 5.03 (2.87) 3.66 (2.68) 16.37 (4.33)
Blood cholesterol (mmol/l): 0.179 <0.001 0.107
<6.2 5424 6.11 (3.01) 2.88 (2.41) 18.23 (4.26)
6.2 3494 6.02 (2.99) 2.65 (2.33) 18.38 (4.13)
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multiplicative scale. The assumption of proportional
hazards assessed by examining the time dependent
interaction term between each predictor and logarithm
of the follow-up period (time variable) held (all
Of the 9745 participants with no history of clinically
validated coronary heart disease at phase 2, 9568
(98.1%) completed the positive affect subscales and
9605 (98.6%) completed the negative affect subscales,
either at phase 1 or phase 2. Among the 8918
participants with complete data on positive and
negative affect and all covariates, 619 coronary events
were documented between phases 2 and 7. The 827
participants who were not included in the analyses
owing to missing data on affect scales (n=614) or on
covariates (n=213) were more likely than the included
participants to be women (11.5% v 7.0%), non-white
(15.7% v 7.0%), and from the lowest employment grade
(13.1% v 7.2%). No difference in age was seen.
Table 1 shows the difference in mean positive affect,
negative affect, and affect balance scores as a function
of the characteristics of the sample. Table 2 shows the
age and sex adjusted associations between all of the
covariates and coronary heart disease events. Exam-
ination of the interactions between sex and the affect
variables in relation to coronary heart disease showed
no evidence of sex differences. Therefore, we com-
bined men and women in the subsequent multivariate
Associations of positive affect, negative affect, and affect
balance score with c oronary heart dis ease
Table 3 shows the six serially adjusted Cox regression
models designed to estimate the associations of affect
measures with coronary heart disease. We found no
association between higher positive affect scores and
the incidence of coronary heart disease (hazard ratio
1.01, 95% confidence interval 0.82 to 1.24) in the
analysis adjusted for age, sex, socioeconomic position,
and ethnicity (model 1) or after further adjustment for
behaviour related risk factors (model 2), biological risk
factors (model 3), psychological stress at work (model
4), all covariates (model 5), and negative affect (model
6). However, participants with negative affect scores in
the highest third had a slightly higher risk (hazard ratio
1.32, 1.09 to 1.60) of coronary heart disease (model 1).
Further serial adjustment (models 2 to 6) showed no
substantial change in this association. Finally, partici-
pants with affect balance scores in the highest third had
a lower, but statistically non-significant, risk (hazard
ratio 0.89, 0.73 to 1.09) of coronary heart disease,
which was little affected by adjustments (models 2 to 6).
Sensitivity analysis
To explore the effect of unmeasured comorbidity at
baseline, we examined the association between nega-
tive affect and incidence of coronary heart disease
events after removing from the analysis any events that
occurred within the first five years of the follow-up. The
number of events was reduced by 31.5% (n=424) in this
analysis, but we found no change in the magnitude of
the association between higher negative affect and
coronary heart disease (hazard ratio adjusted for age,
sex, ethnicity, and socioeconomic position 1.32, 1.05 to
1.67; P=0.016), sugge sting that this association is
unlikely to be attributable to unmeasured comorbidity
at baseline. In the main analysis reported in this paper,
we have replaced missing negative affect scores at
phase 1 with scores at phase 2 if available. We did
sensitivity analysis using negative affect scores at each
phase to test their association with coronary heart
disease incidence without any replacement. In both
Table 2
Age and sex adjusted associations between
covariates and coronary heart disease among 8918
participants (619 events)
Risk of coronary heart disease
No events/No participants
Hazard ratio
(95% CI)
Employment grade:
High 208/2704 1
Middle 283/4370 1.05 (0.88 to 1.26)
Low 128/1844 1.29 (1.00 to 1.66)
White 531/8134 1
Other 88/784 1.88 (1.50 to 2.36)
No 425/7273 1
Yes 194/1645 1.85 (1.55 to 2.19)
Smoking status:
Never smoker 286/4461 1
Ex-smoker 206/2893 1.02 (0.85 to 1.22)
Current smoker 127/1564 1.42 (1.15 to 1.75)
Alcohol consumption:
Low 519/7515 1
Moderate 87/1198 1.09 (0.87 to 1.37)
High 13/205 1.07 (0.62 to 1.86)
1.5 h/week 105/1659 1
<1.5 h/week 514/7259 1.14 (0.92 to 1.41)
Daily fruits and vegetables:
Yes 354/5260 1
No 265/3658 1.13 (0.96 to 1.32)
Body mass index:
<20 14/539 1
20-24.9 291/4960 1.87 (1.09 to 3.20)
25-29.9 250/2850 2.60 (1.51 to 4.45)
30 64/569 3.81 (2.13 to 6.80)
No 610/8837 1
Yes 9/81 1.54 (0.79 to 2.98)
Job strain:
No 537/7859 1
Yes 82/1059 1.23 (0.98 to 1.56)
Blood cholesterol (mmol/l):
<6.2 288/5424 1
6.2 331/3494 1.55 (1.32 to 1.82)
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cases, the pattern of associations was similar to that
obtained for measures with replaced missing values.
We examined the associations of positive and negative
affect with incident coronary heart disease,followed up
over a 12 year period, in the Whitehall II cohort. We
found no real association between positive affect or
affect balance and incidence of coronary heart disease.
Participants in the highest third of negative affect had a
slightly increased risk of incident coronary heart
disease, and this association remained unchanged
after taking into account the eff ects of age, sex,
employment grade, ethnicity, health related beha-
viours, biological markers, job strain, and positive
Findings in context of the literature and possible
To our knowledge, this is the first prospective cohort
study to examine the effects of both negative and
positive affect on incident coronary heart disease,
independently of known risk factors and of each other.
The findings are based on a large well characterised
cohort with coronary heart disease ascertained by
medical records and biological risk factors assessed by
clinical examination.
The finding showing negative affect as an indepen-
dent predictor of coronary heart disease incidence is
consistent with some epidemiological investigations on
negative emotions and coronary heart disease. A recent
review of negative emotions, measured as anxiety,
hostility/anger, and depression, supports their status as
risk factors for coronary heart disease.
Anger in men
has been found to be associated with a greater risk of
coronary events and coronary mortality.
22 23
men from the Northwick Park study and women from
the Framingham heart study, greater anxiety predicted
fatal coronary heart disease.
24 25
According to a recent
meta-analysis of 21 aetiological studies and 34 prog-
nostic studies, depressive symptoms are associated
with an 80% excess risk of developing coronary heart
disease or dying from coronary heart disease.
The magnitude of the association between negative
affect and coronary heart disease in our study is small
and needs to be replicated in studies using measures of
both positive and negative affect. To test the robustness
of our findings, we repeated the analysis using
continuous affect scores with assessments of the
increase in risk of coronary events across the extremes
of the distribution of the affect score. These results also
supported the status of negative affect as a risk factor
Further research is needed to examine the precise
mechanisms through which negative affect might
increase the risk of coronary heart disease. As negative
affect is thought to subsume high negative emotions
such as anxiety and depression,
it may be linked to
coronary heart disease through physiological (cardio-
vascular and neuroendocrine) responses related to
these emotions. Depression has been found to be
associated with pathophysiological changes that may
increase the risk of cardiac morbidity and mortality,
including autonomic nervous system dysfunction
(such as elevated heart rate, low heart rate variability,
and exaggerated heart rate responses to physic al
hypothalamic-pituitary-adrenal axis dys-
regulation (increased cortisol secretion),
inflammatory processes (higher concentrations of
interleukin 6, C reactive protein, and fibrinogen),
and accelerated progression of atherosclerosis as
indicated by change in carotid intima-media
Negative affect could also be linked to
coronary heart disease through health related
In our study, negative affect was not
associated with hypertension, higher body mass index,
or self reported diabetes and was inversely associated
with blood cholesterol concentration, suggesting that
thesefactors are notmajor mediators for the association
seen. The association between negative affect and
coronary heart disease was not attenuated after
adjustment for behavioural factors; thus stable
Table 3
Associations between positive affect, negative affect, and affect balance scores in
thirds and coronary heart disease (number of events/number of participants
Scores in thirds
Hazard ratio (95% CI)
Positive affect Negative affect Affect balance
Model 1
Lowest 1 1 1
Middle 1.19 (0.98 to 1.44) 1.12 (0.92 to 1.36) 0.97 (0.80 to 1.17)
Highest 1.01 (0.82 to 1.24) 1.32 (1.09 to 1.60) 0.89 (0.73 to 1.09)
Model 2
Lowest 1 1 1
Middle 1.18 (0.97 to 1.43) 1.13 (0.93 to 1.37) 0.97 (0.80 to 1.18)
Highest 1.01 (0.82 to 1.25) 1.33 (1.10 to 1.61) 0.89 (0.72 to 1.09)
Model 3
Lowest 1 1 1
Middle 1.22 (1.01 to 1.48) 1.15 (0.94 to 1.39) 0.98 (0.81 to 1.19)
Highest 1.02 (0.83 to 1.26) 1.37 (1.13 to 1.66) 0.89 (0.73 to 1.09)
Model 4
Lowest 1 1 1
Middle 1.20 (0.99 to 1.46) 1.11 (0.92 to 1.35) 0.98 (0.81 to 1.19)
Highest 1.03 (0.83 to 1.27) 1.30 (1.07 to 1.50) 0.91 (0.74 to 1.11)
Model 5**
Lowest 1 1 1
Middle 1.22 (1.01 to 1.48) 1.15 (0.94 to 1.40) 1.00 (0.82 to 1.21)
Highest 1.04 (0.85 to 1.29) 1.36 (1.12 to 1.65) 0.91 (0.74 to 1.12)
Model 6
Lowest 1 1
Middle 1.26 (1.04 to 1.53) 1.16 (0.95 to 1.41)
Highest 1.10 (0.89 to 1.36) 1.39 (1.14 to 1.69)
* No of events/No (percentage) participants for lowest, middle, and highest scores thirds were 183/2746 (30.8),
257/3403 (38.2), and 179/2769 (31) for po sitive affect; 208/3135 ( 35.2), 197/2856 (32), and 214/2927
(32.8) for negative affect; and 200/2817 (31.6), 236/3357 (37.6), and 183/2744 (30.8) for a ffect balance.
Hazard ratio adjusted for age, sex, socioeconomic position, and ethnicity.
Model 1 additionally adjusted for health related behaviours (body mass index, smoking status, exercise, da ily
fruit and vegetable intake, alcohol consumption).
Model 1 additionally adjusted for biological risk factors (b lood cholesterol, diabetes, hypertension).
Model 1 additionally a djusted for psychosocial stress at wor k.
**Model 1 + model 2 + model 3 + model 4.
Model 5 additionally adjusted for positive or negative affect.
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differences in these factors do not seem to be likely
mediators. Further research should examine whether
negative affect is related to risk factor trajectories over
time or whether it increases episodic elevations in risk
factors, such as blood pressure, that could act as a
trigger for coronary events among employees with
subclinical coronary heart disease.
Lack of a robust association between positive affect
and reduced risk of coronary heart disease in our study
is in contrast to some previous reports. An upsurge in
interest in positive affect or happiness and its associa-
tion with health has occurred recently.
32 33
In one study,
low level of positive affect was associated with
increased 10 year total mortality in older adults.
major limitation of that study was the assessment of
positive affect, done using the Center for Epidemiolo-
gic Studies of Depression scale. This scale, a measure of
depression, may not reliably distinguish between low
positive affect and high negative affect. Another study,
also in older adults, found that positive affect had a
protective association with stroke.
In that study, the
analysis was controlled for depressive symptoms but
not for the other components of negative affect, and
thus whether the observed association was indepen-
dent of the effect of negative affect remains unclear.
Moreover, the measure of stroke was self reported,
without corroboration from medical reports. As
positive and negative affect may be related to response
styles, a subjective component in the outcome measure
may introduce subjectivity bias that could artificially
inflate associations.
Interpretation of our findings should be considered
within the context of the study limitations. Firstly, as
coronary heart disease develops during a long time
span, higher levels of negative affect in the long term
rather than the short term are assumed to influence the
incidence of coronary heart disease. However, the
relative temporal stability of negative affect scores
between the two phases was only moderate in this study
(test-retest reliability over three years=0.5). This
suggests the presence of a certain amount of variability
in negative affect levels over time and implies that we
might have underestimated the cumulative impact of
high negative affect on incidence of coronary heart
disease. On the other hand, the lack of stability and the
relatively low internal consistency coefficient, which
was slightly below the conventional threshold of 0.7 for
the negative affect scale, call into question what
precisely the scale measures. These factors are likely
to have influenced our results, and we cannot eliminate
the possibility that negative affect might in part
represent a marker of changing risk exposures rather
than being solely a stable disposition to experience
aversive emotional states. However, the proportional
hazards assumption held in the Cox regression,
suggesting relatively stable effects of negative affect
over the follow-up period.
A second limitation involves modelling potential
biological and behavioural confounders as time
independent covariates. Thus, we did not assess the
possible impact of changes in these factors on the riskof
coronary heart disease events. Thirdly, our cohort of
civil servants did not include blue collar workers and
unemployed people and is thus not representative of
the general population, which may limit the generali-
sability of our findings.
Data from a large occupational cohort provide no
evidence for associations between positive affect or
affect balance and coronary heart disease in men and
women who were free of diagnosed coronary heart
disease at recruitment to the study. However, we found
negative affect to be weakly predictive of incident
coronary heart disease events, independently of socio-
demographic characteristics, conventional risk factors,
and job strain. Further research is needed to examine
whether our findings are generalisable to other
populations as well as to disentangle the potential
pathways that may link negative affect to coronary
heart disease.
Contributors: HN analysed and interpreted the data and wrote the first
draft of the manuscript. MK and A S-M contributed to the analysis and
interpretation of data. MK, RDV, MGM, and AS-M made significant
contributions to all subsequent revisions . HN is the gua rantor.
Funding: HN and MK are suppor ted by the Academy of Finl and (gra nt
117604). AS-M is supported by a
award from t he Euro pean
Science Foundati on and a
Chaire d
award from the French
Ministry of Research. MGM is supported by an MRC research
professorship. The Whitehall II stu dy is supported by grants from the
Medical Research Coun cil; British Heart Foundation ; Health and Safety
Executive; Department of Health; National Heart Lung and Blood Institute
Health Care Policy Research (HS06516); and the John D and Catherine T
MacArthur Foundation Research Networks on Successful Midlife
Development and Socio- economic Status a nd Health. Th e funding so urces
had no role in study d esign, data co llection, data analysis, data
interpretation, or writing of the report.
Competi ng interes ts: None declared.
Ethical approval: University College London Medical School committ ee on
the ethics of human research gave ethical approval for the Whitehall II
Provenance and peer review: Not commissioned; externally peer
Psychological factors are seen as important predictors of coronary heart disease; negative
affectivity may underlie these associations
No largescale studyhasexaminedthe association between negative affectand coronaryheart
Whether positive emotions might have a protective role in the development of coronary heart
disease remains unclear
Negativeaffectwasaweakpredictorofincidentcoronaryheartdiseasein menand womenwho
were free of diagnosed coronary heart disease at recruitment to the study
This association was not accounted for by established coronary risk factors
No support was found for associations of positive affect and affectbalance with coronaryheart
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Accepted: 24 April 2008
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... First, lack of health insurance decreases access to mental health care, leading individuals with limited access to health insurance to worse mental health outcomes [24,25]. Next, current research has established a link between physical and mental health, showing that improvements in physical health and physical activity lead to improvements in mental health [26][27][28][29]. ...
... Although there is no single cause for mental health distress, the explanatory variables included in this paper attempt to measure the most common associated predic -tors [24][25][26][27][28][29][32][33][34][35][36][37][38][39][40]42,43]. Since our level of analysis is at the ZCTA level, we solely focused our study on the spatial distribution and impact of such variables on mental health's geographic patterns and made no inferences at the individual level to avoid ecological fallacy issues. ...
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Residential location has been shown to significantly impact mental health, with individuals in rural communities experiencing poorer mental health compared to those in urban areas. However, the influence of an individual’s social group on the relationship between residential location and mental health outcomes remains unclear. This study disaggregates the rural-urban binary and investigates how geography and social groupings interact to shape mental health outcomes. Merging data from PLACES and Claritas PRIZM, we conducted a hotspot analysis, generated bivariate choropleth maps, and applied multiscale geographically weighted regressions to examine the spatial distribution of mental health and social groupings. Our findings reveal that mental health is influenced by complex interactions, with social groups playing a critical role. Our study highlights that not all rural and urban areas are alike, and the extent to which social groups influence mental health outcomes varies within and across these areas. These results underscore the need for policies that are tailored to meet the unique mental health needs of individuals from different social groups in specific geographic locations to inform policy interventions that more effectively address mental health disparities across diverse communities.
... Emotions, understood as psychological factors, may play a role in the onset of heart disease (Nabi et al., 2008). One area of empirical work has been to assess the association between negative emotions and the subsequent development of heart diseases such as coronary heart disease and hypertension. ...
... Individual health-relevant psychosocial factors may influence to what extent disadvantaged neighborhood environments impact on HF risk. Specifically, evidence has consistently revealed an association of dispositional optimism, a resilience factor, and negative affect, a risk factor, with cardiovascular (CV) disease (Nabi et al., 2008;Rozanski et al., 2019;Sims et al., 2019). While a clear consensus does not exist, several prominent frameworks (e.g. ...
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Objective To assess whether psychosocial factors moderate the associations between neighborhood disadvantage and incident heart failure (HF). Methods Among 1448 Non-Hispanic (NH) Black persons dually enrolled in two community-based cohorts in Jackson, Mississippi who were free of HF as of January 1, 2000, 336 HF events classified by reviewer panel accrued through December 31, 2017. Multilevel, multivariable Cox regression models were used to examine whether optimism and negative affect moderated the associations of two measures of neighborhood characteristics (the national Area Deprivation Index (ADI) and perceived neighborhood problems) on incident hospitalized HF. Results Optimism moderated the association of the ADI with incident HF. Compared to participants reporting the lowest tertile of optimism, those in the highest tertile of optimism had a 29% lower rate of HF associated with increasing ADI in fully adjusted models. We found no evidence for a moderating effect of negative affect. Conclusions This study supports optimism as a source of resilience to the detrimental effects of neighborhood disadvantage on HF risk. Population-level strategies to promote sociocultural antecedents to optimism may serve as a viable method of reducing the disproportionate burden of HF among NH Black persons.
... Keyes (2005) hovorí, že mentálne zdravie je definované ako prítomnosť emocionálnej pohody v kombinácii s vysokou úrovňou psychických, logických a sociálnych funkcií. Mentálne zdravie je subjektívny a komplexný termín zasahujúci emocionálnu, psychickú aj sociálnu rovinu a spolu s fyzickým zdravím, s ktorým sa ovplyvňujú a existuje medzi nimi silná recipročná väzba, opisovaná aj autormi Nabi et al., (2008) sú neoddeliteľnými súčasťami, ktoré spoločne tvoria koncept celkového zdravia. ...
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Opatrenia, ktorými spoločnosť reagovala na pandémiu spôsobenú koronavírusom SARS-CoV-2, sa v jej rôznych štádiách uvoľňovali a zas sprísňovali. Karanténa spôsobená opatreniami mala častokrát za následok zhoršené psychické zdravie ľudí. Vo výskume sme sa zamerali na súbor ľudí, ktorí mali pravdepodobne najprísnejšie opatrenia spomedzi všetkých spoločenských a vekových skupín N (159). Cieľom bolo zistiť úrovne depresivity, osamelosti a celkového všeobecného zdravia klientov žijúcich v zariadeniach sociálnych služieb a zároveň zistiť, či sa úrovne menia v závislosti od veku a častosti kontaktu s rodinou. Úrovne vybraných psychologických premenných boli merané pomocou dotazníkov GHQ-12 (Goldberg, 1972) , BDI-6 (Blom et al., 2012) a ULS-8 (Hays, DiMatteo, 1987). Na dosiahnutie cieľov sme použili korelácie, ktoré ukázali, že s vekom sa úrovne premenných zvyšujú a teda zhoršujú. Z hľadiska kontaktu s rodinou možno povedať, že ľudia, ktorí zažili častejší kontakt vykazovali priaznivejšie úrovne nami vybraných psychologických parametrov.
... Yet, subclinical affective disturbances such as the tendency to experience negative emotions (e.g. sadness, fearfulness) are more common than psychiatric conditions, and are associated with worse physical health outcomes similar to full-blown psychiatric disorders (Cohen & Rodriguez, 1995;Muscatello et al., 2014;Nabi et al., 2008). Further, scholars have posited that both subclinical and clinical affective disturbances influence physical health through common biological pathways (Cohen & Rodriguez, 1995). ...
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Background: Accumulating evidence suggests that positive and negative emotions, as well as emotion regulation, play key roles in human health and disease. Recent work has shown the gut microbiome is important in modulating mental and physical health through the gut-brain axis. Yet, its association with emotions and emotion regulation are understudied. Here we examined whether positive and negative emotions, as well as two emotion regulation strategies (i.e. cognitive reappraisal and suppression), were associated with the gut microbiome composition and functional pathways in healthy women. Methods: Participants were from the Mind-Body Study (N = 206, mean age = 61), a sub-study of the Nurses' Health Study II cohort. In 2013, participants completed measures of emotion-related factors. Two pairs of stool samples were collected, 6 months apart, 3 months after emotion-related factors measures were completed. Analyses examined associations of emotion-related factors with gut microbial diversity, overall microbiome structure, and specific species/pathways and adjusted for relevant covariates. Results: Alpha diversity was negatively associated with suppression. In multivariate analysis, positive emotions were inversely associated with the relative abundance of Firmicutes bacterium CAG 94 and Ruminococcaceae bacterium D16, while negative emotions were directly correlated with the relative abundance of these same species. At the metabolic pathway level, negative emotions were inversely related to the biosynthesis of pantothenate, coenzyme A, and adenosine. Conclusions: These findings offer human evidence supporting linkages of emotions and related regulatory processes with the gut microbiome and highlight the importance of incorporating the gut microbiome in our understanding of emotion-related factors and their associations with physical health.
... We focused on non-clinical adult samples (including student samples and young adults over 18) as there are marked differences between clinical and non-clinical samples in self-compassion-related constructs, such as self-criticism and fears of compassion, particularly in their association with mental health outcomes such as depression . Given the strong links between mental and physical health (Nabi et al., 2008;Surtees et al., 2008), other confounding factors may exist in clinical populations. Disentangling the mediators of self-compassion that are specific to the nonclinical population, in the absence of other co-morbid and confounding variables that are common in clinical populations, could help elucidate the actual associations between self-compassion and physical health. ...
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Objectives Growing research indicates that self-compassion is associated with key physical health outcomes in non-clinical adult populations. This systematic review was designed to characterize the mediators linking self-compassion to physical health outcomes, evaluate study quality and theoretical evidence, compare findings to the mental health literature, and provide directions for future research. Methods We searched Embase , Medline , APA PsycInfo , Scopus , AMED , and Web of Science for relevant articles (including the inclusion of formal statistical mediation tests) from 2003 to February 2022. Study quality was assessed with Downs and Black Checklist for Measuring Quality and Mediation Quality Checklist tools. Results We screened 6439 articles for title and abstracts, assessed 101 full texts for eligibility, and included 20 relevant articles. A range of mediators were categorized as testing psychological or behavioral factors. Perceived stress ( n = 5), emotion regulation ( n = 5), negative affect ( n = 3), and coping strategies ( n = 3) were the most frequently assessed mediators. In general, self-compassion had a significant indirect effect on physical health via negative affect and perceived stress (in the absence of overlapping affective mediators). Findings for emotion regulation and coping strategies were mixed. Conclusions The mediational evidence linking self-compassion to physical health via psychological and behavioral factors remains underdeveloped and focused on the measures of affect and emotion regulation. Future studies need to broaden the scope of mediators to include other self-regulatory factors indicated by theory (e.g., motivational and physiological indices) and implement designs other than cross-sectional/correlational. Protocol Registration PROSPERO CRD42021241915.
... Moreover, co-existing frailty and depressive symptoms have been reported to be associated with impaired cognitive functioning and disability based on a cross-sectional study from the Neurocognitive Outcomes of Depression in the Elderly study (Potter et al., 2016). To date, previous studies have demonstrated a strong link between frailty and depressive symptoms (Nabi et al., 2008;Surtees et al., 2008). As summarized by a metaanalysis based on 16 cross-sectional and 23 cohort studies in 2012, a positive association between depression and frailty was observed in cross-sectional studies, whereas findings from cohort studies were inconsistent (Mezuk et al., 2012). ...
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Objective Frailty and depression, as two common conditions among older adults in China, have been shown to be closely related to each other. The aim of this study was to investigate the bidirectional effects between frailty and depressive symptoms in Chinese population. Methods The bidirectional effect of frailty with depressive symptoms was analyzed among 5,303 adults ≥ 60 years of age from the China Health and Retirement Longitudinal Study (CHARLS). Phenotype and a frailty index were used to measure frailty. Depressive symptoms were evaluated using the Epidemiological Studies Depression Scale (CES-D). Logistic regression and Cox proportional hazard regression models were used to determine the bidirectional effects of frailty and depressive symptoms in cross-sectional and cohort studies, respectively. Subgroup and sensitivity analyses were further used to further verify the associations. Results In the cross-sectional study, the multivariate-adjusted ORs (95% CIs) for depressive symptoms among pre-frail and frail adults, as defined by the frailty index and phenotype, were 3.05 (2.68–3.49), and 9.78 (8.02–12.03), respectively. Depressed participants showed higher risks of pre-frailty and frailty [frailty index, 3.07 (2.69–3.50); and phenotypic frailty, 9.95 (8.15–12.24)]. During follow-up, the multivariate-adjusted HRs (95% CIs) for depressive symptoms among pre-frail and frail participants, as defined by the frailty index and phenotype, were 1.38 (1.22–1.57), and 1.30 (1.14–1.48), respectively. No significant relationship existed between baseline depressive symptoms and the incidence of frailty. Moreover, the results from subgroup and sensitivity analyses were consistent with the main results. Conclusion Although a cross-sectional bidirectional association between depressive symptom and frailty has been observed in older (≥60 years old) Chinese adults, frailty may be an independent predictor for subsequent depression. Moreover, no effect of depressive symptoms on subsequent frailty was detected. Additional bidirectional studies are warranted in China.
At a population level, aging stems from developments that have extended longevity and well-being through economic opportunity, increased sanitation, nutrition, and access to care, coupled with changes in birth trends. How persons grow older and the implications of those changes are particularly important and complex issues for rural communities and the agricultural workforce. Although much of the agricultural production in the United States occurs in rural contexts, agriculture and rurality are not synonymous between population aging and not all rural residents are engaged in agricultural production. Still, for those familiar with rural communities, the intersection between population aging and agricultural producers appears every morning at the local coffee shop or cafe. General Challenges and Benefits of Aging in Rural Contexts Independent of agricultural jobs, rural living can negatively affect one’s health and lifespan. This was illustrated by Cosby and colleagues (2019), who showed that rural-urban mortality disparities increased from the mid-1980s through 2016 and that mortality was predicted by rurality independent of education, income, and race.
Full-text available
Objectives Higher levels of happiness are associated with longer life expectancy. Our study assessed the extent to which various factors explain the protective effect of happiness on all-cause mortality risk, and whether the association differs between older men and women. Methods Using data from the Singapore Longitudinal Aging Studies (N = 6073) of community-dwelling older adults aged ≥ 55 years, we analyzed the association of baseline Likert score of happiness (1 = very sad to 5 = very happy) and mortality from mean 11.7 years of follow up. Cox regression models were used to assess the extent to which confounding risk factors attenuated the hazard ratio of association in the whole sample and sex-stratified analyses. Results Happiness was significantly associated with lower mortality (p < .001) adjusted for age, sex and ethnicity: HR = 0.85 per integer score and HR = 0.57 for fairly-or-very happy versus fairly-or-very sad. The HR estimate (0.90 per integer score) was modestly attenuated (33.3%) in models that included socio-demographic and support, lifestyle or physical health and functioning factor, but remained statistically significant. The HR estimate (0.94 per integer score) was substantially attenuated (60%) and was insignificant in the model that included psychological health and functioning. Including all co-varying factors in the model resulted in statistically insignificant HR estimate (1.04 per integer score). Similar results were obtained for HR estimates for fairly-to-very happy versus fairly-to- very sad). Discussion Much of the association between happiness and increased life expectancy could be explained by socio-demographic, lifestyle, health and functioning factors, and especially psychological health and functioning factors.
Full-text available
Unlabelled: This study sought to provide prevalence data for mental health (MH) diagnoses and psychotropic medication prescriptions among individuals in foster care and to examine their relationships with physical health status, maltreatment type, placement type, and demographic variables. Data were retrieved from electronic health records for 3,067 patients seen at integrated pediatric primary care clinics serving individuals in care. Descriptive and bivariate statistics for presence of MH diagnoses and psychotropic medication prescription were calculated. Multivariable zero-inflated negative binomial regressions were used to assess relationships. Half (50.0%) of patients had at least one MH diagnosis; trauma and stressor-related (31.5%) and attention deficit hyperactivity (22.6%) disorders were most common. 27.8% of patients were prescribed at least 1 psychotropic medication. Complex chronic physical health, having 1 and 2 or more maltreatment exposures, and being 6-11 and 12-20 years of age had significantly higher rates of having a MH diagnosis while being female, Black, Hispanic, and other race were significantly associated with lower rates. Patients with at least 1 MH diagnosis that had complex chronic physical health status, experienced sexual abuse, and were 6-11 and 12-20 years of age had significantly higher rates of psychotropic medication prescription while shelter and kinship placement and female gender were significantly associated with lower rates. Findings suggest that initial and ongoing MH screening is vital for individuals in care so that appropriate interventions can be offered. Results support implementing strategies designed to increase access to MH services for this population, such as integrated care and child psychiatry consult programs. Supplementary information: The online version contains supplementary material available at 10.1007/s40653-023-00547-9.
Full-text available
In recent studies of the structure of affect, positive and negative affect have consistently emerged as two dominant and relatively independent dimensions. A number of mood scales have been created to measure these factors; however, many existing measures are inadequate, showing low reliability or poor convergent or discriminant validity. To fill the need for reliable and valid Positive Affect and Negative Affect scales that are also brief and easy to administer, we developed two 10-item mood scales that comprise the Positive and Negative Affect Schedule (PANAS). The scales are shown to be highly internally consistent, largely uncorrelated, and stable at appropriate levels over a 2-month time period. Normative data and factorial and external evidence of convergent and discriminant validity for the scales are also presented. (PsycINFO Database Record (c) 2010 APA, all rights reserved)
CONTEXT: Although psychosocial factors are correlated, previous studies on risk factors for hypertension have typically examined psychosocial factors individually and have yielded inconsistent findings. OBJECTIVE: To examine the role of psychosocial factors of time urgency/impatience (TUI), achievement striving/competitiveness (ASC), hostility, depression, and anxiety on long-term risk of hypertension. DESIGN, SETTING, AND STUDY POPULATION: A population-based, prospective, observational study using participant data from the Coronary Artery Risk Development in Young Adults (CARDIA) study. A total of 3308 black and white adults aged 18 to 30 years (when recruited in 1985 and 1986) from 4 US metropolitan areas and followed up through 2000 to 2001. MAIN OUTCOME MEASURES: Fifteen-year cumulative incidence of hypertension (systolic blood pressure of 140 mm Hg or higher, diastolic blood pressure of 90 mm Hg or higher, or taking antihypertensive medication). RESULTS: The incidence of hypertension at year 15 was 15% from baseline and 13.6% from year 5. After adjusting for the same set of hypertension risk factors and each of the psychosocial factors of TUI, ASC, hostility, depression, and anxiety in 5 separate logistic regression models, higher TUI and hostility were significantly associated with risk of developing hypertension at 15-year follow-up for the total sample. Compared with the lowest score group, the adjusted odds ratio (OR) for TUI was 1.51 (95% confidence interval [CI], 1.12-2.03) for a score of 1; 1.47 (95% CI, 1.08-2.02) for a score of 2; and 1.84 (95% CI, 1.29-2.62) for a score of 3 to 4 (P for trend =.001). Compared with the lowest quartile group, the adjusted OR for hostility was 1.06 (95% CI, 0.76-1.47) for quartile 2; 1.38 (95% CI, 1.00-1.91) for quartile 3; and 1.84 (95% CI, 1.33-2.54) for quartile 4 (P for trend
We measured affect in 334 healthy adults on each of 7 days over a 3-week period. On the last day, salivary cortisol was assessed 14 times yielding scores for total concentration, morning rise amplitude, and slope of the time function. Trait negative affect (NA) was associated with higher total cortisol concentrations and greater morning rise in men. Cortisol levels for men low in trait positive affect (PA) did not decrease in the afternoon, resulting in a relatively high, flat rhythm. In contrast, women high in trait PA had low morning cortisol resulting in a low flat rhythm. State (person-centered) NA was not associated with same-day cortisol measures. State PA was associated with decreased total cortisol concentration in women. These are the first results showing associations between cortisol and trait PA. Differences in rhythmicity found here are noteworthy given the possible role of cortisol dysregulation in disease incidence, morbidity, mortality, and severity.
This study investigates the relation of psychosocial variables to the 20-year incidence of myocardial infarction or coronary death among women in the Framingham Study. In 1965-1967, a psychosocial interview was given along with the collection of other coronary risk factor data. This study includes 749 women aged 45-64 years who were free of coronary disease at this baseline examination. Demographic variables, psychosocial scales (such as tension and reactions of anger), and individual interview items (such as attitudes toward children, money, and religion) were measured. When age, systolic blood pressure, the ratio of serum total cholesterol to high-density lipoprotein cholesterol, diabetes, cigarette smoking, and body mass index were controlled for in multivariate proportional hazards models, the predictors of the 20-year incidence of myocardial infarction or coronary death were as follows: among employed women, perceived financial status only; among homemakers, symptoms of tension and anxiety, being lonely during the day, difficulty falling asleep, infrequent vacations, housework affecting health, and believing one is prone to heart disease (p less than 0.05 for all variables); and among both groups of women combined, low educational level, tension, and lack of vacations. These results are discussed in relation to previous findings from the Framingham Study.