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Title: 1. dia


1
HEP
Public Health Burden of Work Stress in a
Transforming Society
March 8, 2007 Maria S. Kopp, Eva Susanszky,
Andras Szekely, Arpad Skrabski
www.behsci.sote.hu Conference of the American
Psychosomatic Society, Budapest
Hungarostudy Epidemiological Panel
2
Hungarian Legacy of Psychosomatic Medicine
HEP
  • In the twentieth century, Hungarian born
    scientists, such as
  • Sándor Ferenczi- first chair in Psychoanalysis in
    Budapest, 1919,
  • Franz Alexander,
  • Michael Bálint,
  • Hans Selye,
  • significantly contributed to laying the
    foundations of psychosomatic attitude in medicine
  • During the communist period psychology was
    regarded ideologically incorrect, and in the
    early 1950-ies there was no psychology education
    at the Hungarian universities.

Hungarostudy Epidemiological Panel
3
HEP
General adaptation Theory of János Selye
  • János Selye was born in 1907 this year is the
    anniversary of his birth
  • The three phases of stress
  • alarm reaction,
  • resistance phase,
  • and the third, physiologically most harmful
    phase, exhaustion, chronic stress!
  • During the socio-economic transition the most
    important public health burden is connected to
    chronic stress in Hungary.

Hungarostudy Epidemiological Panel
4
HEP
Chronic stress in Selyes laboratory
  • In the chronically stressed animals fatal
    consequences occurred
  • immunological,
  • cardiovascular,
  • gastroenterological collapse, and death
  • The difference between animal and human stress
    process
  • the central importance of subjective evaluation

Hungarostudy Epidemiological Panel
5
HEP
Chronic stress as a public health risk on
population level
  • In the last decades in the transforming societies
    of Central and Eastern Europe (CEE), premature
    mortality increased dramatically, first of all
    among middle aged men.
  • In Hungary the mortality rate for 40-69 years old
    men was 12.2 0/00 in 1960 and 16.2 0/00 in 2005
    it increased by 33 0/0,
  • while among 40-69 years old women it decreased
    from 9.6 0/00 to 7.8 0/00 (Demographic Yearbook,
    2005).
  • This means that in 2005, 11.395 more men deceased
    from this age group in Hungary, than in 1960
    (20.736 men in 1960, 32.131 men in 2005).
    (Source Demographic Yearbook, 2005)

Hungarostudy Epidemiological Panel
6
HEP
11.395 more men died from the 40-69 age group in
2005 in Hungary than in 1960!
Hungarostudy Epidemiological Panel
7
HEP
Natural experimental model
  • The morbidity and mortality crisis of the
    transforming Central and Eastern European
    countries is an extraordinary natural experiment
    to better understand the importance of
    psychosocial factors in health,
  • because the existing explanatory models are not
    able to explain these rapid changes in the health
    status of our population.

Hungarostudy Epidemiological Panel
8
HEP
What can explain the opposite changes in
East-West life expectancy?
  • In the 1960s, no differences in Austrian and
    Hungarian life expectancy
  • Life expectancy in Hungary in 2005
  • Male 68.6, female 76.9 years
  • Life expectancy in neighboring Austria in 2005
  • Male 76.4 - they live 7.8 years longer,
  • Female 82.1 - they live 5.2 years longer
  • improvements in the first year of life and above
    70 years of age

Hungarostudy Epidemiological Panel
9
HEP
Characteristics of health crisis in Hungary
  • Since the late 1980s, the mortality rates among
    40-69 year old men in Hungary have risen to
    higher levels than they were in the 1930s
  • Large gender difference in mortality rates.
  • Large regional differences in the 20 Hungarian
    counties and in the 150 sub-regions

Hungarostudy Epidemiological Panel
10
HEP
Mortality rate in 1000 men in corresponding age
groups in the Hungarian population (Demographic
Yearbook, 2005)
Hungarostudy Epidemiological Panel
11
HEP
Gender differences
  • What is the explanation for the increased
    vulnerability of middle aged men during this
    period of rapid economic change?
  • Although men and women share the same
    socio-economic circumstances, there are
    significant gender differences in worsening
    mortality rates.

Hungarostudy Epidemiological Panel
12
HEP
Trends in other CEE countries and in other
suddenly transforming societies
  • Similar trends in Poland and in Czech Republic,
    but improvement had started much earlier and it
    is more considerable
  • Dramatic health crisis in Russia, Ukraine and in
    the Baltic countries
  • Opposite changes in Far-Eastern suddenly changing
    societies, improved life expectancy in Japan and
    Singapore
  • What can explain these differences?

Hungarostudy Epidemiological Panel
13
HEP
Possible explanations?
  • This deterioration cannot be ascribed to
    deficiencies in health care, because
  • During these years there was a significant
    decrease in infant and old age mortality
  • Between 1960 and 1989 there was a constant
    increase in the gross domestic product in
    Hungary. Worsening material situation cannot be
    the explanation
  • Genetic factors cannot explain such a rapid
    change in middle aged mortality
  • Which factors might explain these public health
    crisis?

Hungarostudy Epidemiological Panel
14
HEP
National representative surveys in the Hungarian
population
  • The samples represent the Hungarian population
    above age 18 according to gender, age, county and
    sub-regions
  • Hungarostudy 1983 more than 6000 persons
  • Hungarostudy 1988 20.902 persons
  • Hungarostudy 1995 12.463 persons
  • Hungarostudy 2002 12.640 persons
  • the refusal rate was 17.7
  • Skrabski Á, Kopp MS, Rózsa S, Réthelyi J, Rahe RH
    (2005) Life meaning an important correlate of
    health in the Hungarian population. International
    Journal of Behavioral Medicine, 12,2, 78-85.

Hungarostudy Epidemiological Panel
15
HEP
Hungarostudy Epidemiological Panel (HEP)
follow-up study
  • Among the 12.640 persons in Hungarostudy 2002,
    from those who agreed to participate in the
    follow up study
  • 4.689 persons were interviewed again in 2005, 322
    persons deceased
  • Among these 5011 persons those people were
    included into the present analysis
  • who in 2002 were between the age of
  • 40-69

Hungarostudy Epidemiological Panel
16
HEP
Socio-economic and demographic measures
  • Education,
  • Income, family income
  • Subjective socioeconomic status
  • Subjective poverty
  • Access to car
  • Access to personal computer
  • Marital status
  • Chicago collective efficacy score
  • Family environment
  • Housing environment
  • Childhood experiences
  • Self-rated socioeconomic changes

Hungarostudy Epidemiological Panel
17
HEP
Self-rated health
  • Self-rated disability
  • Self-rated health
  • Self-reported treatment because of 25 types of
    disorders
  • Illness intrusiveness
  • Self-rated pain
  • Sleep complaints
  • Health care related needs

Hungarostudy Epidemiological Panel
18
HEP
Mental health indicators
  • Shortened Beck Depression Score
  • WHO Wellbeing (Bech,1996)
  • within WHO cheerfulness
  • Shortened Hopelessness Score
  • (Beck, 2000)
  • Hospital Anxiety Score (HAS)
  • Vital exhaustion (Appels, 1988)
  • Type D Personality (Dennolet, 2000)
  • that is Negative affect (NA)
  • and Behavioral inhibition (BI)

Hungarostudy Epidemiological Panel
19
HEP
Work stress measures
  • Job security (Rahe, Tolles, 2002)
  • Control at work (Kopp et al, 2000)
  • Dissatisfaction with work and with boss (Rahe,
    Tolles,2002)
  • Occupational troubles in the last 5 years (Rahe,
    Tolles, 2002)
  • Social support at work (Kopp et al, 2000)
  • The number of working hours per week days and on
    weekend days
  • Personal and family income
  • Employment status

Kopp, M., Skrabski, Á., Szántó, Zs., Siegrist,
J. (2006) Psychosocial determinants of premature
cardiovascular mortality differences within
Hungary Journal of Epidemiology Community
Health 60, 782-788
Hungarostudy Epidemiological Panel
20
HEP
Further psychosocial indicators
  • Shortened ways of coping (Folkman, Lazarus, 1980)
  • Stress and coping (Rahe, 2002)
  • Dysfunctional attitude score (Weissman,1979)
  • Life events (Rahe, 2002)
  • Marital stress score
  • Social capital measures
  • TCI shortened cooperativeness and sensation
    seeking
  • Womens health
  • Ethnic identity
  • Religious involvement
  • Perceived social support (Caldwell, 1987)
  • Anomie-inability for
  • long-term planning (Eurobarometer study)
  • Self-efficacy score (Schwarzer, 1992)
  • Meaning in life (R. Rahe, 2002)
  • Shortened hostility score (Cook-Medley, 1954)
  • within rivalry
  • Purposes in Life (Crumbaugh, Maholick,1964)

Hungarostudy Epidemiological Panel
21
HEP
Health behavior and lifestyle factors
  • Alcohol abuse (AUDIT)
  • Morning alcohol consumption
  • Non-stop alcohol consumption once they start
    drinking
  • Self-blame because of alcohol
  • Drug consumption
  • Smoking history
  • Suicidal behavior
  • Sport- regular physical activity
  • Body weight and height - BMI

Hungarostudy Epidemiological Panel
22
HEP
Middle aged sample predictors of premature death
  • From the latest Hungarostudy Epidemiological
    Panel 2005 follow-up study
  • 1130 men and
  • 1529 women were included into the present study,
  • who in 2002 were between the age of 40-69.
  • 99 men (8.8) and 53 women (3.6)
  • died in the 40-69 years old age groups by 2005

Premature Death measures the loss of years of
productive life due to death before age 69.
Hungarostudy Epidemiological Panel
23
HEP
Causes of mortality among the deceased in the
sample
  • In both genders cancers were the most prevalent
    causes of death
  • 36.5 among men and
  • 41.5 among women.
  • The rate of cardiovascular and
  • cerebro-vascular death was
  • 35.1 among men and
  • 29.3 among women.
  • 12.1 of men and 19.5 of women died because of
    external causes,
  • and 4.1 of men because of hepatic cirrhosis.

Hungarostudy Epidemiological Panel
24
HEP
Self-reported health and the risk (OR) of
premature mortality (40-69 years of age in 2002)
according to the Hungarostudy Epidemiological
Panel (HEP) 2005 follow up study
Hungarostudy Epidemiological Panel
25
HEP
Self-reported health and the risk (OR) of
premature mortality (40-69 years of age in 2002)
controlled for age, education, smoking, alcohol
abuse and BMI
Hungarostudy Epidemiological Panel
26
HEP
Self-reported health as predictor of premature
death
  • Subjective health status was an important
    predictor of premature death in both gender
  • OR for self-rated disability
  • 5.84 (CI 3.15-10.81), p .000 for men
  • 2.02 (CI 1.09-3.75) p .02 for women.
  • OR for self-rated health
  • 2.98 (CI 1.94-4.56) p .000 for men
  • 1.98 (CI 1.11-3.52) p .02 for women
  • In agreement with other studies, in this 41-69
    aged population male self-rated health,
    especially self-rated disability, predicted the
    male all cause mortality better than the female
    mortality.
  • The question arises, which factors might explain
    this early health deterioration.
  • Kopp MS, Skrabski Á, Réthelyi J, Kawachi I, Adler
    N (2004) Self rated health, subjective social
    status and middle-aged mortality in a changing
    society. Behavioral Medicine, 30, 65-70.

Hungarostudy Epidemiological Panel
27
HEP
Which disorders predicted premature death?
  • Among women, treatment because of cancer in 2002
    OR3.19 (1.71-5.94) .000
  • 29 of deceased women were treated in 2002,
    while 11 among survivors
  • Neither treatment because of hypertension, nor
    cardiovascular, cerebro-vascular disorders or
    other disorders in 2002 predicted premature
    death, neither among men nor among women
  • Among men, only other cardiovascular disorders
    predicted premature death OR 1.94 (1.14 -3.30)
    .01
  • the low rate of treated disorders among men who
    died within three years might mean that in
    Hungary, men do not seek medical help in the
    early phase of chronic disorders

Hungarostudy Epidemiological Panel
28
HEP
Striking gender differences in predictors of
premature mortality, increased vulnerability of
men in most respects
Hungarostudy Epidemiological Panel
29
HEP
Socioeconomic factors and the risk (OR) of
premature mortality (40-69 years of age in 2002)
according to the Hungarostudy Epidemiological
Panel (HEP) 2005 follow up study
Hungarostudy Epidemiological Panel
30
HEP
Socioeconomic factors and the risk(OR) of
premature mortality (40-69 years of age in 2002)
controlled for age, education, smoking, alcohol
abuse and BMI
Hungarostudy Epidemiological Panel
31
HEP
Socioeconomic factors as predictors of early death
  • Education (lower or higher than secondary
    studies) predicted only male premature
    mortality the odds ratio was 1.84 for men.
  • Among men, subjective poverty and subjective
    social status were also significant predictors of
    mortality.
  • Among women only the family related socioeconomic
    measures were significant predictors of
    mortality, namely no car and no personal
    computer in the family
  • ontological insecurity measures (M. Marmot, 2004)

Hungarostudy Epidemiological Panel
32
HEP
What might be the toxic components of lower
socioeconomic situation?
Hungarostudy Epidemiological Panel
33
HEP
Work-related factors and the risk (OR)
of premature mortality (40-69 years of age in
2002) according to the Hungarostudy
Epidemiological Panel (HEP) 2005 follow up study
Hungarostudy Epidemiological Panel
34
HEP
Work related predictors of premature death
  • Work related factors, first of all job
    insecurity, low control in work, low personal and
    family income and low employment grade were
    significant predictors of premature death only
    among men
  • Among women only low social support at work was
    significant predictor of premature death

Hungarostudy Epidemiological Panel
35
HEP
Unpredictability, anomie, demoralization and the
risk (OR) of premature mortality (40-69 years of
age in 2002) according to the Hungarostudy
Epidemiological Panel (HEP) 2005 follow up study
Hungarostudy Epidemiological Panel
36
HEP
Mental health and the risk (OR) of premature
mortality (40-69 years of age in 2002) according
to the Hungarostudy Epidemiological Panel
(HEP) 2005 follow up study
Hungarostudy Epidemiological Panel
37
HEP
Social support and the risk (OR) of premature
mortality (40-69 years of age in 2002) according
to the Hungarostudy Epidemiological Panel
(HEP) 2005 follow up study
Hungarostudy Epidemiological Panel
38
HEP
Health behavior and the risk (OR) of premature
mortality (40-69 years of age in 2002) according
to the Hungarostudy Epidemiological Panel (HEP)
2005 follow up study
Hungarostudy Epidemiological Panel
39
HEP
Mental health and the risk (OR) of premature
mortality (40-69 years of age in 2002) controlled
for age, education, smoking, alcohol abuse and BMI
Hungarostudy Epidemiological Panel
40
HEP
Work related and other psychosocial factors and
the risk (OR) of premature mortality (40-69 years
of age in 2002) controlled for age, education,
smoking, alcohol abuse and BMI
Hungarostudy Epidemiological Panel
41
HEP
Significant psychosocial predictors of premature
death among men
  • Work related factors, especially
  • job insecurity,
  • low control in work,
  • low personal and family income, and
  • low employment grade
  • were significant predictors of early death only
    among men.
  • Anomie, that is unpredictability there is no
    point in making plans for the future, no meaning
    in life and rivalry significantly predicted
    premature male mortality

Hungarostudy Epidemiological Panel
42
HEP
Significant mental health predictors of premature
death
  • Only among men depression, especially severe
    depression increased the risk of premature death
    5 x times, and anxiety 3 x times.
  • In 2002, the prevalence of severe depression was
    24 among the deceased men in the sample, 5.8
    among surviving men.
  • WHO wellbeing was a significant protective factor
    only among men.
  • Self-efficacy and cheerfulness were significant
    protective factors among men.

Hungarostudy Epidemiological Panel
43
HEP
Psychosocial predictors of premature death among
women
  • Dissatisfaction with personal relations
  • Family problems
  • Dissatisfaction with social support at work
  • In the case of women, the broader personal and
    family relations are the most important
    health-related factors.
  • Unhappiness and negative affect were significant
    predictors of premature mortality only among
    women.
  • Lifetime prevalence of suicide attempts was also
    an independent predictor of early mortality, but
    only among women.
  • In these respects there were no fundamental
    changes during the last decades.

Hungarostudy Epidemiological Panel
44
HEP
Chronic stress-depressive symptomatology
  • Based on the data of our national representative
    surveys, we found that the worse socioeconomic
    situation is linked to higher mortality rates
    among Hungarian men as well,
  • however, higher mortality rates are connected to
    relatively poor socioeconomic situations mainly
    through the mediation of depressive symptoms,
  • in a broader sense through chronic stress
  • Kopp MS, Réthelyi J (2004) Where psychology
    meets physiology chronic stress and premature
    mortality - the Central-Eastern-European health
    paradox. Brain Research Bulletin, 62, 351-367.
  • Kopp MS (interview) (2000) Stress The invisible
    hand in Eastern Europes death rates. Science,
    288, 1732-1733.

Hungarostudy Epidemiological Panel
45
HEP
Depressive symptomatology (BDI) severity
categories in the Hungarian population
Hungarostudy Epidemiological Panel
46
HEP
Depressive symptomatology (BDI) severity
categories according to HEP 2005 follow-up study
between 2002 and 2005 among men
Hungarostudy Epidemiological Panel
47
HEP
Depressive symptomatology (BDI) severity
categories according to HEP 2005 follow-up study
between 2002 and 2005 among women
Hungarostudy Epidemiological Panel
48
HEP
Changes in severity of depressive categories
(BDI)in Hungary between 1988 and 2005
  • Severe depression increased between 1988 and 1995
    from 2.7 to 7 in the total population
  • Between 2002 and 2005, severe depression
    increased from 4.3 to 9.2 among men the
    increase was higher among men than among women

Hungarostudy Epidemiological Panel
49
HEP
Which factors changed in Hungary during the last
decades?
1. Increased socio-economic differences within
society, increased socio-economic deprivation,
increased competition without counterbalancing
social capital 2. Increased demoralization,
unpredictability, i.e. increased anomie,
decreased social capital 3.Work related changes
increased insecurity, decreased perceived control
in work, overwork, income inequalities 4.
Increased instability of the family
Hungarostudy Epidemiological Panel
50
HEP
1. Growing polarization of the socio-economic
situation between 1960 and 2002
  • Until 1960, practically no income inequality, and
    there were no mortality differences between
    socio-economic strata.
  • Since that time increasing disparities in
    socio-economic conditions have been accompanied
    by a widening socio-economic gradient in
    mortality, especially among men.

Hungarostudy Epidemiological Panel
51
HEP
Aggregate mortality according to low vs. high
education (Mackenbach et al, 1999)
Hungarostudy Epidemiological Panel
52
HEP
2. Demoralization, unpredictability anomie,
decrease of social capital
  • Anomie (unpredictability, hopelessness, lack of
    self-confidence) increased considerably between
    since 1978 (Eurobarometer studies 1978, 1994,
    2006)
  • Social distrust increased, social capital
    decreased
  • Skrabski ,Á, Kopp MS, Kawachi i (2003) Social
    capital in a changing society cross sectional
    associations with middle aged female and male
    mortality rates, J Epidemiology and Community
    Health,57,2,114-119
  • Skrabski Á, Kopp MS, Kawachi I (2004) Social
    capital and collective efficacy in Hungary Cross
    sectional associations with middle aged female
    and male mortality rates, J Epidemiology and
    Community Health,58,340-345.

Hungarostudy Epidemiological Panel
53
HEP
3. Central role of work stress
  • Earlier employment was regarded as granted,
  • no competition, no rivalry, no motivation for
    achievement
  • since the 1970s the major changes in the labor
    market went parallel with the
  • unclear rules of the game those near to the
    Communist Party were in better position
  • increased disparities of incomes
  • consumer value system at work, income and
    subjective social status might measure
    self-respect among men

Hungarostudy Epidemiological Panel
54
HEP
Work-related stress models
  • Demand-control-social support (Karasek,
    Theorell,1990)
  • Increased demands increased competition, rivalry
  • Significant decrease in job contol
  • Transient changes in social support at work
  • Kopp MS, Skrabski Á, Szedmák S (2000)
    Psychosocial risk factors, inequality and
    self-rated morbidity in a changing society.
    Social Science and Medicine 51, 1350-1361.

Hungarostudy Epidemiological Panel
55
HEP
The model of effort-reward imbalance according to
Johannes Siegrist (1996)
  • labor income
  • career mobility/job security
  • esteem, respect

Extrinsic components
demands/obligations
reward
effort
motivation (overcommitment)
motivation (overcommitment)
Intrinsic component
Hungarostudy Epidemiological Panel
56
HEP
Effort-revard imbalance in Hungary
  • Increased efforts because of the consumer
    society increased competition, rivalry
  • Overwork second or even third jobs weekend work
  • decreased rewards
  • high degree of job instability
  • decrease in job control
  • income disparities

Hungarostudy Epidemiological Panel
57
HEP
Effort-reward imbalance and job control
incident psychiatric disorder (GHQ) Whitehall
II-Study (odds ratios Nmax4680 men,
follow-up 5.3 years)




adj. for age, employment grade, baseline GHQ
score, excluding baseline GHQ cases p lt .05
p lt .01
Source S.A. Stansfeld et al. (1999), OEM, 56
302-7.
58
HEP
Effort-reward imbalance and depressive symptoms
(CES-D) HAPIEE Study (urban population of 3
Eastern European countries N1168 men and women,
45-64 yrs.)

Range CES-D 0-60 mean CES-D 12.07 adj. for
age, sex, area p lt .05

2
3
4
Quartiles of effort-reward ratio (4 high work
stress)
Source H. Pikhart et al. (2004), Soc Sci Med,
58 1475-1482.
59
HEP
Inflammatory response (C-reactive protein CRP)
during experimentally induced mental stress among
subjects with different levels of effort-reward
imbalance (N92)
CRP change (µg/ml) as function of effort-reward
imbalance
adjusted for age, BMI, baseline levels

Source M. Hamer et al. (2006), Psychosom Med,
68 408-413.
60
Significant work related predictors of severe
depression in 2005 among Hungarian men
HEP
  • Low job control OR3.30 (1.82-5.98)
  • Increased efforts, demands
  • rivalry OR2.34 (1.28-4.26) .005
  • Decreased rewards
  • low income OR2.65 (1.69 - 4.17) .000
  • low subjective social status OR1.72 (1.11-2.65)
    .02
  • - job insecurity OR3.26 (1.94-5.47).000
  • - dissatisfaction with job OR1.75 (1.09-2.79)

Hungarostudy Epidemiological Panel
61
HEP
Conclusions
  • Men seem to be more vulnerable to the
    unpredictability, demoralization of society,
  • work-related effort-reward and demand-control
    imbalance,
  • material deprivation - low education and other
    socio-economic measures,
  • uncertainty of close family relations.
  • men regard themselves responsible for the better
    socioeconomic situation of the family

Hungarostudy Epidemiological Panel
62
HEP
Conclusions
  • Self-efficacy, secure job and strong social
    support from spouse explained the protective
    effect of high education as regards premature
    mortality among men
  • Among men the most important predictors of
    premature death were high depression and low
    self-rated health
  • Depression, low wellbeing and related
    self-destructive behavior are the results of
    chronic stressors of societal changes

Hungarostudy Epidemiological Panel
63
HEP
Why is the crisis deeper in Hungary than in
Poland and in the Czech Republic?
  • The 1956 revolution was a unique experience of
    national identity, cohesion
  • Repression of national identity was much stronger
    than in the neighboring countries increased
    anomie, demoralization
  • higher inequities within society,
  • Forced consumer value system most cheerful
    barrack- deeper decrease of social capital in
    Hungary

Hungarostudy Epidemiological Panel
64
HEP
Why isnt this public health disaster
acknowledged?
  • Given the magnitude of the problem, it is
    surprising that this deterioration in the health
    of the Hungarian population has not received more
    attention,
  • If the 33 increase in annual premature
    mortality of Hungarian men before 69 years of age
    were the result of some viral agent, there would
    be a world wide mobilization
  • That would be recognized as a public health
    disaster a massive response on a public health
    problem of this magnitude would call forth, first
    of all for health politicians.
  • Why is it not acknowledged?

Hungarostudy Epidemiological Panel
65
HEP
References
  • Kopp MS, Réthelyi J (2004) Where psychology
    meets physiology chronic stress and premature
    mortality - the Central-Eastern-European health
    paradox. Brain Research Bulletin, 62, 351-367.
  • Kopp MS, Skrabski Á, Réthelyi J, Kawachi I, Adler
    N (2004) Self rated health, subjective social
    status and middle-aged mortality in a changing
    society. Behavioral Medicine, 30, 65-70.
  • Kopp MS (interview) (2000) Stress The invisible
    hand in Eastern Europes death rates. Science,
    288, 1732-1733.
  • Kopp MS, Skrabski Á, Szedmák S (2000)
    Psychosocial risk factors, inequality and
    self-rated morbidity in a changing society.
    Social Science and Medicine 51, 1350-1361.
  • Skrabski ,Á, Kopp MS, Kawachi i (2003) Social
    capital in a changing societycross sectional
    associations with middle aged female and male
    mortality rates, J Epidemiology and Community
    Health,57,2,114-119
  • Skrabski Á, Kopp MS, Kawachi I (2004) Social
    capital and collective efficacy in Hungary Cross
    sectional associations with middle aged female
    and male mortality rates, J Epidemiology and
    Community Health,58,340-345.
  • Skrabski Á. Kopp MS, Rózsa S, Réthelyi J, Rahe RH
    (2005) Life meaning an important correlate of
    health in the Hungarian population. International
    Journal of Behavioral Medicine, 12, 2, 78-85.
  • Kopp MS, Skrabski Á, Kawachi I, Adler NE (2005)
    Low socioeconomic staus of the opposite gender is
    a risk factor for middle aged mortality. Journal
    of Epidemiology Community Health, 59, 675-678.
  • Kopp M, Skrabski Á, Szántó Zs, Siegrist, J
    (2006) Psychosocial determinants of premature
    cardiovascular mortality differences within
    Hungary. Journal of Epidemiology Community
    Health, 60, 782-788.

Hungarostudy Epidemiological Panel
66
HEP
Work stress measures
  • Control at work was assessed by Likert scaled
    answers (0 to 3) to the item How much can you
    influence what happens in your working group?
    (Kopp et al, 2000)
  • Job security was assessed by Likert scaled
    answers (0 to 2) to the item I am happy with my
    level of job security. (Rahe, Tolles, 2002)
  • Dissatisfaction with work and with boss were was
    assessed by Likert scaled answers (0 to 2) to the
    item I am unhappy with my work situation and I
    am dissatisfied with my boss (es) (Rahe,
    Tolles,2002)
  • Occupational troubles in the last 5 years were
    recorded within the Life events questionnaire.
    (Rahe, Tolles, 2002)
  • Social support at work was measured by answers
    (0-3) to the item How much help do you receive
    from co-workers?. (Kopp et al, 2000)
  • The number of working hours per week days and on
    weekend days were recorded.
  • Personal income was assessed with the help of a
    separate card showing eight categories (from 50
    thousand HUFs or less to 500 thousand HUF or more
    per month)

Hungarostudy Epidemiological Panel
67
HEP
Gender paradox of subjective social status
  • According to ecological analysis of 150
    sub-regions in Hungarostudy 2002
  • negative evaluation of subjective social status
    by women increased significantly the male
    mid-aged mortality
  • r for female SSS and male mid-aged mortality
    was .597 p .000
  • That is, the subjective evaluation of the
    relative social deprivation by women might be a
    further risk factor for male health
  • But higher education of women was protective for
    male mid-aged mortality
  • Kopp MS, Skrabski Á, Kawachi I, Adler NE (2005)
    Low socioeconomic status of the opposite gender
    is a risk factor for middle aged mortality.
  • J. Epidemiology and Community Health, 59,
    675-678.

Hungarostudy Epidemiological Panel
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