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High levels of cynical distrust partly predict premature mortality in middle-aged to ageing men

Authors:
  • University of Helsinki, Finland; Rehabilitation Foundation, Helsinki, Finland

Abstract

The aim of this study was to evaluate the effect of cynical distrust on mortality in middle-aged and aging men. The analysis is based on Kuopio Ischemic Heart Disease study, follow-up from 1984 to 2011. Sample consisted of 2682 men, aged 42-61 years at baseline. Data on mortality was provided by the National Death Registry, causes of death were classified by the National Center of Statistics of Finland. Cynical distrust was measured at baseline using Cynical Distrust Scale. Survival analyses were conducted using Cox regression models. In crude estimates after 28 years of follow-up, high cynical distrust was associated with 1.5-1.7 higher hazards for earlier death compared to low cynical distrust. Adjusted for conventional risk factors, high cynical distrust was significantly associated regarding CVD-free men and CVD mortality, while non-CVD mortality in study sample was consistently but not significantly associated. The risk effects were more expressed after 12-20 years rather than in earlier or later follow-up. To conclude, high cynical distrust associates with increased risk of CVD mortality in CVD-free men. The associations with non-CVD mortality are weaker and not reach statistical significance.
High levels of cynical distrust partly predict premature mortality
in middle-aged to ageing men
Kastytis S
ˇmigelskas
1
Roza Joff_
e
1
Jolita Jonynien_
e
1
Juhani Julkunen
2
Jussi Kauhanen
3
Received: March 5, 2016 / Accepted: January 30, 2017
ÓSpringer Science+Business Media New York 2017
Abstract The aim of this study was to evaluate the effect
of cynical distrust on mortality in middle-aged and aging
men. The analysis is based on Kuopio Ischemic Heart
Disease study, follow-up from 1984 to 2011. Sample
consisted of 2682 men, aged 42–61 years at baseline.
Data on mortality was provided by the National Death
Registry, causes of death were classified by the National
Center of Statistics of Finland. Cynical distrust was
measured at baseline using Cynical Distrust Scale. Sur-
vival analyses were conducted using Cox regression
models. In crude estimates after 28 years of follow-up,
high cynical distrust was associated with 1.5–1.7 higher
hazards for earlier death compared to low cynical distrust.
Adjusted for conventional risk factors, high cynical dis-
trust was significantly associated regarding CVD-free men
and CVD mortality, while non-CVD mortality in study
sample was consistently but not significantly associated.
The risk effects were more expressed after 12–20 years
rather than in earlier or later follow-up. To conclude, high
cynical distrust associates with increased risk of CVD
mortality in CVD-free men. The associations with non-
CVD mortality are weaker and not reach statistical sig-
nificance.
Keywords Cynical distrust Personality Cardiovascular
mortality Longitudinal study Epidemiology
Background
Personality is associated with health outcomes including
death, though not always consistently (Jokela et al., 2013).
For years, Type A behavior pattern was supposed to have
significant effects on health. However, research has shown
that specific traits of the Type A are more ‘toxic’ than the
whole construct. With such personality traits as impatience,
competitive drive, ambitiousness or holding anger-in
explored, hostility was found to be one of the key con-
structs associated with an increased risk of cardiovascular
events (both first and recurrent) and subsequent mortality
(Barefoot et al., 1983; Shekelle et al., 1983; Haukkala
et al., 2001; Chaput et al., 2002; Matthews et al., 2004;
Tindle et al., 2009).
Hostility may be defined as ‘‘a personality trait charac-
terizing how trustworthy individuals perceive other people
and how they handle these feelings toward others’’ (Mer-
jonen et al., 2011). In psychological terms, hostility is
specified by three components—cognitive, affective, and
behavioral. Besides cardiovascular risk, studies suggest
that hostile persons are more prone to adverse health
behaviors and outcomes, such as weight gain (Haukkala &
Uutela, 2000), high interpersonal conflict or low social
support (Everson et al., 1997). Nevertheless, meta-analyses
on the issue suggest rather small effects (Myrtek, 2001;
Chida & Steptoe, 2009). Moreover, Chida and Steptoe
(2009) found significant indications for publication bias.
In the meantime of discussing about ‘toxicity’ of hos-
tility some researchers (Smith & Frohm, 1985) suggested
the necessity to refine the hostility construct for predictive
&Kastytis S
ˇmigelskas
kastsmig@gmail.com
1
Department of Health Psychology, Lithuanian University of
Health Sciences, Kaunas, Lithuania
2
Institute of Behavioral Sciences, University of Helsinki,
Helsinki, Finland
3
Institute of Public Health and Clinical Nutrition, University
of Eastern Finland, Kuopio, Finland
123
J Behav Med
DOI 10.1007/s10865-017-9834-2
purposes of health outcomes. Greenglass and Julkunen
(1989) suggested such feature naming it cynical distrust
that reflects the cognitive component of hostility (Merjonen
et al., 2011). It is also referred to as cynical hostility or
simply cynicism. Previously the issue of cynicism and
health outcomes was analyzed in Finnish KIHD dataset
(Everson et al., 1997). However, this was conducted with
only 9 years follow-up, limited power of the study and
without the evidence about consistency of associations
across the time. Of note, current effort is not designed to
recollect previous analysis; instead, it is addressing the
issue in a different analytical pattern including consider-
ably longer follow-up.
Since the research on negative effects of cynical distrust
on health outcomes is partly ambiguous and majority of
previous research on cynicism/hostility was mainly
addressed using non-representative or small samples, we
aimed to analyze how cynical distrust associates with
mortality in a large representative sample of middle-aged
to aging men. Specifically, the stability of the risk effect
was addressed through follow-up time. Our analyses
included long follow-up (more than 25 years) with esti-
mates of follow-up on exposure–outcome associations,
which has not been addressed previously. In addition, our
study enabled us to control for possible influences of bio-
logical, psychosocial, and behavioral risk factors.
Methods
The analysis on cynical distrust and mortality was based on
the data from Kuopio Ischemic Heart Disease Risk Factor
Study (KIHD) from 1984 to 2011. It is an ongoing popu-
lation-based study addressing the issues of risk factors for
chronic diseases. Due to complete follow-up system of the
Finnish population through national health registries, there
are virtually no losses to follow-up.
Subjects
The primary sample comprised a random sample of 3433
non-institutionalized men aged 42–43, 48–49, 54–55, or
60–61 years at baseline, who resided in town of Kuopio or
surrounding rural communities in Finland. Of them, 2682
agreed to participate (response rate 82.9% of primary
sample). There were no considerable sociodemographic
differences between participants and non-participants
(Lakka & Salonen 1992). The baseline examinations were
conducted in 1984–1989, and until 2011 some men have
been followed up for about 20 years, while others up to
28 years.
Cynical distrust
For evaluation of cynicism, the Cynical Distrust Scale
(CDS) was used as a self-report questionnaire at baseline. It
is an 8-item scale, factor-derived from Cook-Medley
Hostility Inventory (Cook & Medley, 1954) and found as a
reliable and valid measure of cynicism (Greenglass &
Julkunen, 1989). Examples of items include ‘It is safer to
trust nobody’ or ‘Most people make friends because friends
are likely to be useful to them’. Low score on the scale
suggests that the respondent believes that people are dis-
honest and only care about themselves (Miller et al., 1995).
Response options were altered from the original true–false
format to a 4-point Likert scale. Items were scored reverse
and summed to obtain a CDS score ranging from 0 to 24
with higher scores indicating more expressed cynical dis-
trust.
Mortality
The outcome of interest under study was mortality—car-
diovascular (CVD; depending on baseline CVD status) and
non-cardiovascular (non-CVD). Calculations were con-
ducted separately as four scenarios: (1) CVD mortality in
all study subjects; (2) CVD mortality in subjects without
CVD history at baseline; (3) CVD mortality in subjects
with CVD history at baseline; and (4) non-CVD mortality
in all study subjects. Mortality was ascertained by linkage
to the National Death Registry with countrywide coverage
of 100%. Classification of deaths was based on the
underlying cause, reviewed at the National Center of
Statistics of Finland. The causes of death were classified
according to the International Classification of Diseases
(ICD-9), with CVD codes 390–459.
Covariates
The estimates between the exposure and outcome were
based on survival models adjusted for covariates. As
covariates, the biological, behavioral, and socioeconomic
variables were used, majority of which were considered as
conventional risk factors for many chronic diseases and
therefore having a potential effect on exposure–outcome
associations under study. The set of covariates was built
based on the previous research which demonstrated that
behavioral, biological, and socioeconomic factors con-
tribute to the models (Everson et al., 1997, Wong et al.,
2013). The full set of covariates consisted of 10 behavioral,
biological, and socioeconomic indicators (Table 1). For
CVD mortality in the total sample, the prior history of
CVD was additionally accounted for as a covariate.
J Behav Med
123
Statistical analysis
Data analysis was performed using ‘‘IBM SPSS Statistics,
version 20.0’’ software. Descriptive statistics were pre-
sented by arithmetic mean ±standard deviation (SD) and
by proportions (%). For pairwise comparisons, mean scores
of CDS scale between age groups were compared using
ttest for independent samples considering the Levene’s test
for equality of variances.
For comparison of mortality, the CDS scores were cat-
egorized to quartiles. The survival analyses were conducted
using Cox proportional hazards model with estimates of
association in hazard rate ratios (HRR). First, the bivariate
associations (crude estimates) between cynicism and mor-
tality were calculated. Then the adjustment for the set of
covariates was conducted. In order to estimate the effect of
follow-up time on the exposure–outcome associations, the
survival analyses were run separately for duration of fol-
low-up in a yearly manner as if every subject was followed
up for a given number of years from the baseline. Due to
large number of results, only 4, 8, 12, 16, 20, 24, and
28 years findings are presented.
Results
During the observation from 1984 to 2011, the average fol-
low-up time of subjects was 7532 ±2514 days (20.6 ±
6.88 years). The cumulative mortality was increasing steadily
through time, being about 40 cases per year on average. The
crude death rate during the whole period was 42.0%, with
almost half of all deaths (19.7% of total sample) being
attributed to cardiovascular diseases. The mean CDS score in
the whole sample was 12.7 ±4.20 pts (scale range from 0 to
24), with mean scores being slightly higher in older subsam-
ples, ranging from 12.2 ±4.21 pts in the youngest group to
13.3 ±4.18 pts in the oldest (p\0.001).
For comparison of cynicism and mortality, first the
unadjusted bivariate estimates were calculated for a total
follow-up of 28 years (Table 2). It was found, that 4th
quartile had consistently higher hazards (HRR between
1.46 and 1.73) for mortality compared to the lowest levels
of cynical distrust in all outcome groups (p\0.05). Fur-
ther analyses were conducted with adjustment for the set of
covariates and then findings were not that consistent.
The cynical distrust showed certain significant associa-
tions with mortality (Table 3). The analyses of CVD
mortality depending on men’s history of cardiovascular
disorders revealed that men who entered the study already
having a history of certain cardiovascular disorder had a
risk of cardiovascular death virtually independent from
cynical distrust level. In contrast, men who had no CVD
history at baseline faced more than double hazards of
Table 1 Study sample characteristics at baseline
Variable % or average ±SD
Age group (years)
42–43 12.5%
48–49 13.3%
54–55 59.4%
60–61 14.8%
Occupation
Farmers 16.2%
Blue-collar workers 44.3%
White-collar workers 39.6%
Education
Less than elementary 10.0%
Elementary 48.1%
Secondary 35.1%
Higher 6.8%
Income
Quintiles 19.7–20.3%
CVD history at baseline
Yes 37.9%
No 62.1%
HDL/LDL ratio 0.34 ±0.143
Systolic blood pressure (mmHg) 134.3 ±17.08
Body mass index (kg/m
2
) 26.9 ±3.60
Physical activity (kcal/day) 140.4 ±175.67
Smoking, cigarettes 9years 168.5 ±335.26
Alcohol consumption (g/week) 76.2 ±138.49
Table 2 Levels of cynical distrust and the risk of death through the
whole 28-years follow-up: unadjusted estimates
Mortality Quartile HRR 95% CI P
CVD 1st 1.000 –
2nd 0.956 0.728–1.256 0.746
3rd 1.337 1.009–1.771 0.043
4th 1.720 1.341–2.207 \0.001
CVD in subjects with CVD
history at baseline
1st 1.000 –
2nd 0.997 0.684–1.455 0.989
3rd 1.484 1.011–2.178 0.044
4th 1.464 1.037–2.066 0.030
CVD in subjects without
CVD history at baseline
1st 1.000 –
2nd 0.867 0.583–1.287 0.478
3rd 1.121 0.738–1.703 0.592
4th 1.731 1.203–2.492 0.003
Non-CVD 1st 1.000 –
2nd 1.025 0.806–1.303 0.841
3rd 0.948 0.716–1.255 0.708
4th 1.556 1.238–1.957 \0.001
CVD cardiovascular
J Behav Med
123
premature cardiovascular death if they were high on Cyn-
ical Distrust Scale: in CVD-naı
¨ve sample the risk of mor-
tality was peaking at 12 years (HRR =3.34) and then
decreased, especially after 20 years of follow-up.
More detailed analyses revealed (results are not pre-
sented) that the highest levels of cynicism (4th quartile) in
majority of cases had the highest hazard estimates within
analyzed period of follow-up, while the risks of the 2nd and
3rd quartiles were mainly similar to the 1st quartile.
Regarding the associations dependence on follow-up
time, in general it can be noted that the strongest point
estimates for different follow-ups were observed in period
of 12–20 years, with the exception of subjects with CVD
history at baseline. Before that period, the hazards of death
had increasing trend, while later—declining. In addition,
28 years follow-up analysis revealed that the adjusted
hazards are consistently closer to no-difference compared
to the crude estimates.
Discussion
Main problem and key findings
Cynicism is the main cognitive component of hostility and
is regarded as the primary reference of hostility term
(Greenglass & Julkunen, 1989). In previous research,
hostility has received more attention than cynicism, which
was addressed in the KIHD sample previously with average
follow-up of 9 years (Everson et al., 1997). In contrast to
the latter, our analysis tried to shed light into the rela-
tionship between cynicism and mortality with longer fol-
low-up (and thus, higher power of the study) and with
estimates of follow-up time on associations.
Findings of our study revealed that cynical distrust may
be regarded as a risk factor for premature cardiovascular
death, but only in CVD-free men. In contrast, cynical men
who had a CVD history at the onset of the study had almost
no extra risk of premature death. This difference empha-
sizes the relevance of considering the CVD status in hos-
tility research. Non-cardiovascular mortality was not
demonstrated to associate with cynical distrust, possibly
due to insufficient power of the study. So, what could be
the explanations if the associations we found are not spu-
rious?
Biological mechanisms
One of possible mechanisms how cynicism leads to pre-
mature mortality (especially cardiovascular) may be the
response to stress. In addition to the external sources of
stress, the hostile people during interactive process seem
likely to create interpersonal stresses themselves (Smith &
Frohm, 1985). Hostile individuals are seen as responding to
potential stressors with stronger effects observed in heart
rate, blood pressure, and neuroendocrine changes, espe-
cially during social and anger-provoking stressors (Neu-
mann et al., 2011; Smith & Gallo, 1999). This can be
explained by a specific reaction to stress that leads addi-
tional adreno-pituitary axis reactivity related with cardio-
vascular stress response. Further, hostility is associated
with higher probability of rapid progression of
atherosclerosis, ischemia, and myocardial infarction
(Pickering et al., 2003), and has also been positively
associated with inflammatory markers. In addition, genetic
factors should not be excluded from possible causal
mechanisms, since the genes that associate with hostility
are also playing role in regulating the platelet aggregation
Table 3 High levels of cynical distrust and the risk of death depending on follow-up time
Duration of follow-
up (years)
CVD mortality, total sample
(n =2682)
CVD mortality, subjects
without CVD history at
baseline (n =1666)
CVD mortality, subjects with
CVD history at baseline
(n =1016)
Non-CVD mortality, total
sample (n =2682)
#of
deaths
HRR
a
95% CI # of
deaths
HRR
a
95% CI # of
deaths
HRR
a
95% CI # of
deaths
HRR
a
95% CI
4 59 0.811 0.260–2.526 12
bb
47 0.468 0.137–1.597 53 1.339 0.495–3.620
8 115 1.124 0.541–2.336 33 1.557 0.408–5.941 82 0.890 0.371–2.137 120 1.186 0.650–2.167
12 213 1.637 0.992–2.700 75 3.343 1.382–8.085 138 1.019 0.548–1.895 204 1.454 0.930–2.273
16 284 1.704 1.117–2.598 101 3.236 1.577–6.644 183 1.127 0.667–1.905 294 1.426 0.990–2.054
20 365 1.585 1.118–2.248 139 2.214 1.288–3.805 226 1.280 0.811–2.018 409 1.234 0.912–1.670
24 475 1.325 0.990–1.774 193 1.774 1.153–2.730 282 1.094 0.738–1.621 538 1.195 0.920–1.552
28 529 1.205 0.919–1.580 221 1.427 0.959–2.123 308 1.108 0.765–1.606 597 1.207 0.942–1.547
a
4th quartile versus 1st quartile of cynical distrust
b
Insufficient number of deaths
J Behav Med
123
(Schultess et al., 2005). The fact that CVD mortality in our
study was associated with cynical distrust more than non-
CVD mortality suggests that possibly the negative effect of
cynical distrust affects the cardiovascular system more than
other body systems.
Behavioral and psychosocial mechanisms
The relevance of behavioral factors was supported by
Wong et al. (2013) who found that biological factors
accounted for much less of association than health behav-
iors. For example, hostility may promote poor health
behaviors such as smoking, physical inactivity, and poor
treatment adherence which all increase the risk of cardio-
vascular events (Siegler et al., 1992).
Although there are many possible biological explana-
tions of how cynicism or hostility leads to worse health,
negative psychosocial characteristics can be strong
accompanying factors. For example, hostile individuals
experience lower social support (Smith & Frohm, 1985),
subjective well-being (Wiest et al., 2011), more depression
(Haukkala & Uutela, 2000), loneliness (Newall et al.,
2013), absence of positive affect (Martı
´n-Marı
´a et al.,
2016) or purpose in life (Hill & Turiano, 2014). Thus, the
association between cynicism and mortality can have
another explanation—through negative affect as a general
phenomenon, as this can also be in the causal chain
between cynicism and premature mortality. Of note, how-
ever, recent research demonstrated that hostility can be
regarded as a stronger risk factor for cardiac outcomes
compared to other psychological indicators such as
depression, anxiety, somatization, or well-being (Rafanelli
et al., 2016).
Relevance of follow-up and cardiovascular history
Our study revealed that the time plays a significant role
when establishing the associations between cynical distrust
and mortality. In our study, it took a relatively long period
of time (up to 12 years of follow-up) to see the CVD-free
men scoring high on Cynical Distrust Scale to develop
statistically significantly higher risk of premature CVD
death. Duration of follow-up is an important factor when it
comes to analyzing psychophysiological mechanisms,
mainly because such mechanisms involve many sequential
and parallel physiological processes within a body that
trigger long-lasting changes and usually have no instant
effects. Our findings support the idea that there exists a
certain window of time (follow-up) which provides the
strongest associations between the exposure and the out-
come. In part, similar phenomenon has recently been
observed with Type A and mortality (S
ˇmigelskas et al.,
2015). However, it is not clear how specific the time
window we found is compared to other exposure–outcome
associations in general. Here the strongest survivor effect
(or survivorship bias) seems plausible, which may also help
explain the declining hazards in the last decade of follow-
up regardless of the outcome group.
The issue of strongest survivor effect can be assumed
due to our finding that the risk of CVD death was strongly
dependent on men’s previous history of cardiovascular
disorders. The hypothesis can be that the cynical men with
usual risk factor profile may have cardiovascular diagnosis
or even death before the onset of the study (at younger ages
like 40 and 50 s), while the ones who entered the study at
middle age, were CVD-free and were also high on cynical
distrust, presumably had some additional protective fac-
tors. By methodological definition, in a possible explana-
tory mechanism of presumed protective factors we should
exclude variables that were used for adjustment in our
survival analyses, such as body mass index, blood pressure
or smoking. Nevertheless, among protective factors that
were not controlled for in our case may have been other
psychosocial measures, such as high social support or
absence of negative affect.
Strengths and limitations of the study
One of the strengths of our study is a representative sample
of the middle-aged male population with a very high
response rate, virtually 100% coverage to the National
Death Registry, and multivariate adjustment for main
confounders, that included biological, behavioral and
socioeconomic factors. However, our analyses missed
other psychological features in possible causal chain
between cynical distrust and premature mortality, espe-
cially those related with negative affect. Also, some other
social or biological covariates with potential confounding
effects may have gone undetected in our analyses.
For measurement of cynicism, our study used Cynical
Distrust Scale, which is considered a more valid measure of
cynical beliefs and distrust than a general Cook-Medley
Hostility Inventory (Haukkala et al., 2001), commonly
used in hostility research. However, a potential limitation
of our study is that the cynical distrust was assessed only at
baseline, though cynical distrust may be changing over
time. For example, Merjonen et al. (2011) found that
younger people report higher cynical distrust than elder
ones in their 40 s, while in our study the trend seemed to be
increasing cynicism with age. From this perspective it can
be suggested that the decrease of cynical distrust from teen
years through 40 s takes place as an adaptation to cultural
norms and expectations within a society, while the slight
increase later from 40 to 60 s may be an outcome or
response to disillusionment of positive attitudes towards
particular people or society in general. Additionally, bio-
J Behav Med
123
logical indicators may also play a role as acting factors for
increasing cynicism through later years: neurodegenerative
changes and disorders that emerge later in life are mani-
fested in part through higher levels of aggression and
hostility. Even though the cynical distrust was demon-
strated as a stable concept, with a high test–retest corre-
lation over 12 months (Julkunen et al., 1994), cross-
sectional studies suggest higher levels of hostility in older
adults (Barefoot et al., 1993) which keeps the issue of
concept stability open.
Our study used a self-report assessment of cynicism,
which requires self-awareness and can be susceptible to
bias. Newman et al. (2011) concluded that observed hos-
tility is a superior predictor of cardiovascular events
compared to self-report measures. Most likely, such aspect
in our study would rather underestimate the effect of
cynicism due to psychologically ‘‘defensive’’ nature of
cynicism and due to social desirability bias.
Regarding measurement issue we also should note that
our study was limited in that it used categorization (quar-
tiles), since there are no cut-offs for Cynical Distrust Scale.
We did not approach the cynical distrust as a linear mea-
sure in analyses, because previous research demonstrated
that hostility scores are related to mortality in a non-linear
manner (Shekelle et al., 1983; Barefoot et al., 1983),
though linear approaches are not exceptional. In our study,
we rather see that the distrust seems to have a certain
threshold for its negative effects, if any.
Regarding the causes of death, when dividing the pri-
mary causes of death to CVD and non-CVD, there may
have been the classification bias. This could have happened
in a way, that men having non-cardiovascular disorder as
their primary chronic condition (e.g. diabetes) may have
died from CVD-related cause. We suggest that this bias
may have led to underestimate of the risk effect of non-
CVD mortality.
Even though our study was large scale, however, it still
may be underpowered, since the consistent associations
with non-CVD mortality at risk levels of 1.2–1.4 were
statistically non-significant, though the accumulating
number of deaths increased the power of the study. In
addition, our analytical approach did not present us with
estimate of how many deaths are due to specific factor of
cynical distrust; however, in the light of simultaneous
competition of negative factors (both biological and psy-
chosocial) it is virtually impossible to define the number of
lethal events due to cynical distrust, unlike in case of
infectious diseases.
Future prospects
Previous research has shown that cynicism is higher in men
than in women (Merjonen et al., 2011). Our study analyzed
only male sample, therefore future studies could address
the issue in female samples as well, because gender dif-
ferences in health-related behaviors may differently influ-
ence the associations. Also, due to possible strongest
survivor effect, studies with younger samples could add to
a more comprehensive understanding of the issue, espe-
cially studies with a longitudinal design and repeated
measures of cynicism.
For the future research, it is relevant to measure other
negative affect-related indicators in order to specify their
role in the context of cynicism. Previous studies show that
there may be many candidate variables and their multi-
collinearity may be an important issue to solve method-
ologically.
Also, we propose that in studies on hostility effects on
cardiovascular outcomes it is essential to approach the
CVD status in multivariate analysis as an effect modifier
rather than a covariate, because otherwise the effect of
CVD history on subsequent mortality may go undetected.
Similarly, careful approach is needed for decisions to
merge or not the overall mortality, as is performed in some
other studies on the issue (Wong et al., 2013). We
demonstrated, that in case of cynical distrust the negative
effect of this psychological construct manifests mostly in
CVD-free men and more on CVD mortality.
Also, the public health implications in this case may be
reasonable to some extent—it can be suggested that there is
some potential for public health interventions, addressing
personal presumptions and deep-rooted habits that need a
longer period of time to be changed or amended. For
instance, by applying behavior-oriented interventions, it
could be reasonable to make changes in personal behaviors
or perceptions which in total can be related with cynical
stance, simultaneously decreasing other negative affect
traits. Also, it can be possible to improve the skills related
with social support and interpersonal conflict. In general,
the changes of personal features through interventions are
not well established, though the potential for improvement
exists, as was demonstrated with Type A (Friedman et al.,
1986). However, the target group definition is relevant
here.
However, the extrapolation of negative effect of cynical
distrust on mortality and health in general should be
careful, at least with respect to type of outcome and CVD
status of the subjects.
Conclusions
High levels of cynical distrust seem to be associated with
an increased risk of cardiovascular death in middle-aged
and aging men that have no CVD history at baseline.
However, the risk effect is mainly expressed after
12–20 years of follow-up rather than earlier, while later the
J Behav Med
123
risk effect is declining. Medium levels of cynical distrust in
general show weak associations with mortality. The neg-
ative effect of cynical distrust on non-cardiovascular
mortality is not clear.
Compliance with ethical standards
Conflict of interest Kastytis S
ˇmigelskas, Roza Joff_
e, Jolita
Jonynien_
e, Juhani Julkunen and Jussi Kauhanen declares that they
have no conflicts of interest.
Human and animal rights and informed consent All procedures
performed in study involving human participants were in accordance
with the ethical standards of the institutional research committee and
with the 1964 Helsinki declaration and its later amendments.
Informed consent was obtained from all individual participants
included in the study.
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... Tai atskleidžia, kad CDS skalės balus analizėje galima naudoti kaip tolydų kintamąjį, ir jeigu nėra apribojimų iš kitų kintamųjų -taikyti parametrinius metodus tiek dvimatėje, tiek regresinėje analizėje. Tačiau galima pastebėti, kad nepaisant to, kai kuriuose užsienio tyrimuose CDS skalės suminiai balai yra pergrupuojami į dvi grupes (pagal medianą; [7]), taip pat tris [12] ar keturias [14] rangines kategorijas. Toks pergrupavimas sudaro papildomas analizės galimybes tais atvejais, jei kai kurie tyrimo kintamieji neatitinka parametrinių prielaidų, tačiau tai apriboja rezultatų palyginimą skirtinguose tyrimuose. ...
... Nors mūsų tyrimo imtis buvo kardiologiniai pacientai, tačiau galima manyti, kad ciniško nepasitikėjimo požiūriu tai atspindi ir bendrąją populiaciją. Tokia prielaida galima dėl to, kad mūsų tyrime vidutinė ciniško nepasitikėjimo raiška (12,6 balo) buvo labai artima teoriniam skalės vidurkiui; labai panašus ciniško nepasitikėjimo vidurkis (12,7 balo) buvo nustatytas ir reprezentatyvioje vidutinio amžiaus vyrų imtyje Suomijoje [14]. Apibendrinant galima teigti, kad aprašytoji ciniško nepasitikėjimo skalė yra validi naudoti ir Lietuvos imtyse. ...
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... Numerous studies provided evidence for a detrimental effect of cynicism on health outcomes. Cynicism has been associated with an elevated level of inflammatory biomarkers (Boyle, Jackson, & Suarez, 2007), metabolic syndrome (D'Antono, Moskowitz, & Nigam, 2013;Gremigni, 2006;Nelson, Palmer, & Pedersen, 2004), incidence of a large number of diseases, including cardiovascular and coronary heart disease (Chida & Steptoe, 2009), atherosclerosis (Pollitt et al., 2005), ulcer (Lemogne et al., 2015), diabetes (Wylie-Rosett et al., 2010) and dementia (Neuvonen et al., 2014) and consequently even increased mortality risks (Everson et al., 1997;Klabbers, Bosma, van den Akker, Kempen, & van Eijk, 2013;Smigelskas, Joffe, Jonyniene, Julkunen, & Kauhanen, 2017;Wong, Sin, & Whooley, 2014). Importantly, longitudinal studies have shown cynicism to predict health deterioration and disease onset years later, supporting the frequently held assumption of a causal effect of cynicism on poor health (Adams, Cartwright, Ostrove, Stewart, & Wink, 1998;Boyle et al., 2007;Keith et al., 2017;Lemogne et al., 2015;Vahtera, Kivimäki, Koskenvuo, & Pentti, 1997). ...
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... The higher score indicates a stronger expression of cynicism. Based on previous longitudinal research (Šmigelskas, Joffė, Jonynienė, Julkunen, & Kauhanen, 2017) the increased risk group was defined as the upper quartile. ...
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... This further allows for virtuous and vicious cycles in which the perception of social support leads others to provide more social support, whereas the perception of social rejection leads others to act in a more rejecting manner in the future. One important example of such phenomena is the considerable body of work showing that higher hostility/cynicism (i.e., not liking others and believing that others are selfish and only interested in themselves) is associated with poor cardiac outcomes (e.g., (116)(117)(118)). For example, this could be explained (at least in part) by the fact that, all else being equal, the prior expectations associated with hostility/cynicism would promote (a) perceptions of selfishness in others, (b) interactions that would promote more hostile responses from others (and subsequently greater social isolation), and (c) chronically higher autonomic arousal within such social interactions (reduced vagal tone, increased inflammation). ...
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... Whereas the high percentage of females is representative of UK psychology students (Universities and Colleges Admissions Service, 2016), future studies may want to include students from subjects with a greater percentage of males to obtain more gender-balanced samples. Second, the measure of distrust used in the present study had relatively low reliability, and future studies should consider alternative measures of dispositional distrust (e.g., cynical distrust; Šmigelskas, Joffė, Jonynienė, Julkunen, & Kauhanen, 2017). Third, the present findings are restricted to multidimensional perfectionism as conceptualized by Hewitt and Flett (1991). ...
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The perfectionism social disconnection model (PSDM; Hewitt, Flett, Sherry, & Caelian, 2006) makes an important contribution to perfectionism research explaining why perfectionism is associated with social disconnection and interpersonal hostility. Moreover, recent expansions of the PSDM suggest that the model applies to all forms of perfectionism. The present research challenges this suggestion. Three university student samples (Ns = 318, 417, and 398) completed measures of self-oriented, other-oriented, and socially prescribed perfectionism together with measures of trust, empathy, and hostility including aggression, anger, and spitefulness. In line with previous studies examining unique relationships of the three forms of perfectionism, only other-oriented and socially prescribed perfectionism showed a consistent pattern of unique relationships indicative of social disconnection and hostility. In contrast, self-oriented perfectionism showed unique relationships indicative of social connection (and low hostility regarding physical aggression and spitefulness). The present findings indicate that the PSDM may not apply to all forms of perfectionism. Not all perfectionists feel socially disconnected and hostile towards others. Self-oriented perfectionists may feel socially connected and show no higher hostility than non-perfectionists, particularly when they are low in other-oriented and socially prescribed perfectionism.
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Hostility is a multidimensional personality trait with changing expression over the life course. We performed a genome-wide association study (GWAS) of the components of hostility in a population-based sample of Finnish men and women for whom a total of 2.5 million single-nucleotide polymorphisms (SNPs) were available through direct or in silico genotyping. Hostility dimensions (anger, cynicism and paranoia) were assessed at four time points over a 15-year interval (age range 15–30 years at phase 1 and 30–45 years at phase 4) in 982–1780 participants depending on the hostility measure. Few promising areas from chromosome 14 at 99 cM (top SNPs rs3783337, rs7158754, rs3783332, rs2181102, rs7159195, rs11160570, rs941898, P values <3.9 × 10−8 with nearest gene Enah/Vasp-like (EVL)) were found suggestively to be related to paranoia and from chromosome 7 at 86 cM (top SNPs rs802047, rs802028, rs802030, rs802026, rs802036, rs802025, rs802024, rs802032, rs802049, rs802051, P values <6.9 × 10−7 with nearest gene CROT (carnitine O-octanoyltransferase)) to cynicism, respectively. Some shared suggestive genetic influence for both paranoia and cynicism was also found from chromosome 17 at 2.8 cM (SNPs rs12936442, rs894664, rs6502671, rs7216028) and chromosome 22 at 43 cM (SNPs rs7510759, rs7510924, rs7290560), with nearest genes RAP1 GTPase activating protein 2 (RAP1GAP2) and KIAA1644, respectively. These suggestive associations did not replicate across all measurement times, which warrants further study on these SNPs in other populations.Keywords: hostility; GWAS; personality; gene; development
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Hostility, as measured by the Cook-Medley Hostility Scale of the Minnesota Multiphasic Personality inventory, has been found to predict higher rates of both coronary heart disease and all-cause mortality. To evaluate one mechanism whereby hostility might contribute to health problems, the authors used regression models to determine whether hostility measured in college (1964–1966) predicted coronary risk factors assessed 21–23 years later (1987–1990) in 4,710 men and women. Of this group, 828 had lipids measured (1988–1991). Persons with higher hostility scores in college were significantly more likely at follow-up to consume more caffeine (r = 0.043), to have a larger body mass index (r = 0.055), to have higher lipid ratios (r = 0.092), and to be current smokers (r = 0.069) than those with tower hostility scores during college. Cross-sectional analyses found significant associations of contemporaneous hostility scores with the same four risk factors, as well as with alcohol consumption and hypertension (rs ranging from 0.043 to 0.117). These associations are large enough to have possible public health significance. We conclude that hostility may contribute to health problems through its influences on several coronary risk factors across the adult life span. Am J Epidemiol 1992;136:146–54.
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Objective: The role of depression and quality of life on clinical outcomes of congestive heart failure (CHF) is well-recognized. However, there are fewer studies investigating the prognostic role of subclinical psychological distress and well-being impairments. The aims of this study were to evaluate clinical/subclinical psychological distress and well-being in CHF outpatients, and the influence of these psychological factors on adverse cardiac events (re-hospitalization, cardiac death), at 4-year follow-up. Design: 68 CHF outpatients underwent psychological assessment at baseline and, after 4 years, information about cardiac events was collected in 60 patients by means of clinical records. Main outcome measures: Psychological assessment included Structured Clinical Interview for DSM (major/minor depression), Interview for Diagnostic Criteria for Psychosomatic Research (demoralization), Symptom Questionnaire, Psychological Well-Being scales. Results: At follow-up, 39.7% of the baseline sample reported cardiovascular events (14 CHF-related re-hospitalizations and 13 cardiac deaths) and 5.9% other-causes death. Among the variables examined as potential risk factors for adverse cardiovascular outcomes, only hostility was significant, even after controlling for disease severity (hazard ratio=2.38, 95%confidence interval: 1.04-5.45, p=0.040). Conclusion: In outpatients with CHF, psychological assessment should include both clinical and subclinical distress such as hostility, in order to better address psychological risk factors for cardiac outcomes.
Article
Psychosocial characteristics may be associated with an increased risk of coronary heart disease (CHD). Whether hostility predicts recurrent coronary events is unknown. A total of 792 women in the Heart and Estrogen/ progestin Replacement Study (HERS) were evaluated prospectively to determine the role of hostility as a risk factor for secondary CHD events (nonfatal myocardial infarction and CHD death). The mean age of study participants was 67 years, and the average length of follow-up was 4.1 years. The study was conducted between 1993 and 1998, and all study sites were in the United States. High Cook-Medley hostility scores were associated with greater body mass index (p = 0.01) and higher levels of serum triglycerides (p = 0.05), and they were inversely associated with high density lipoprotein cholesterol (p = 0.04), self-rated general health (p < 0.001), age (p = 0.05), and education (p = 0.001). Compared with women in the lowest hostility score quartile, women in the highest quartile were twice as likely to have had a myocardial infarction (relative hazard = 2.03, 95% confidence interval: 1.02, 4.01). The relation between hostility and CHD events was not mediated or confounded by the biologic, behavioral, and social risk factors studied. In this study, hostility was found to be an independent risk factor for recurrent CHD events in postmenopausal women. coronary disease; hostility; postmenopause; risk factors; women Abbreviations: CHD, coronary heart disease; CI, confidence interval; HERS, Heart and Estrogen/progestin Replacement Study; HMG-CoA, 3-hydroxy-3-methylglutaryl coenzyme A; RH, relative hazard. Epidemiologic evidence suggests that psychological behaviors may be associated with coronary heart disease (CHD) risk. Hostility, a construct that includes cynicism, anger, mistrust, and aggression (1), has been correlated with carotid atherosclerosis (2, 3), angiographic coronary artery disease (4, 5), exercise-induced ischemia (6), and restenosis after mechanical revascularization in women (7). High hostility scores have also been associated with an increased risk of nonfatal myocardial infarction among older women (8, 9) but not with fatal events in patients with documented
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Personality may influence the risk of death, but the evidence remains inconsistent. We examined associations between personality traits of the five-factor model (extraversion, neuroticism, agreeableness, conscientiousness, and openness to experience) and the risk of death from all causes through individual-participant meta-analysis of 76,150 participants from 7 cohorts (the British Household Panel Survey, 2006-2009; the German Socio-Economic Panel Study, 2005-2010; the Household, Income and Labour Dynamics in Australia Survey, 2006-2010; the US Health and Retirement Study, 2006-2010; the Midlife in the United States Study, 1995-2004; and the Wisconsin Longitudinal Study's graduate and sibling samples, 1993-2009). During 444,770 person-years at risk, 3,947 participants (54.4% women) died (mean age at baseline = 50.9 years; mean follow-up = 5.9 years). Only low conscientiousness-reflecting low persistence, poor self-control, and lack of long-term planning-was associated with elevated mortality risk when taking into account age, sex, ethnicity/nationality, and all 5 personality traits. Individuals in the lowest tertile of conscientiousness had a 1.4 times higher risk of death (hazard ratio = 1.37, 95% confidence interval: 1.18, 1.58) compared with individuals in the top 2 tertiles. This association remained after further adjustment for health behaviors, marital status, and education. In conclusion, of the higher-order personality traits measured by the five-factor model, only conscientiousness appears to be related to mortality risk across populations.
Article
BACKGROUND: Trait optimism (positive future expectations) and cynical, hostile attitudes toward others have not been studied together in relation to incident coronary heart disease (CHD) and mortality in postmenopausal women. METHODS AND RESULTS: Participants were 97 253 women (89 259 white, 7994 black) from the Women's Health Initiative who were free of cancer and cardiovascular disease at study entry. Optimism was assessed by the Life Orientation Test-Revised and cynical hostility by the cynicism subscale of the Cook Medley Questionnaire. Cox proportional hazard models produced adjusted hazard ratios (AHRs) for incident CHD (myocardial infarction, angina, percutaneous coronary angioplasty, or coronary artery bypass surgery) and total mortality (CHD, cardiovascular disease, or cancer related) over approximately 8 years. Optimists (top versus bottom quartile ["pessimists"]) had lower age-adjusted rates (per 10 000) of CHD (43 versus 60) and total mortality (46 versus 63). The most cynical, hostile women (top versus bottom quartile) had higher rates of CHD (56 versus 44) and total mortality (63 versus 46). Optimists (versus pessimists) had a lower hazard of CHD (AHR 0.91, 95% CI 0.83 to 0.99), CHD-related mortality (AHR 0.70, 95% CI 0.55 to 0.90), cancer-related mortality (blacks only; AHR 0.56, 95% CI 0.35 to 0.88), and total mortality (AHR 0.86, 95% CI 0.79 to 0.93). Most (versus least) cynical, hostile women had a higher hazard of cancer-related mortality (AHR 1.23, 95% CI 1.09 to 1.40) and total mortality (AHR 1.16, 95% CI 1.07 to 1.27; this effect was pronounced in blacks). Effects of optimism and cynical hostility were independent. CONCLUSIONS: Optimism and cynical hostility are independently associated with important health outcomes in black and white women. Future research should examine whether interventions designed to change attitudes would lead to altered risk.