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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
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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.

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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.

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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

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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)

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HEP
11.395 more men died from the 40-69 age group in
2005 in Hungary than in 1960!
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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.

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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

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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

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HEP
Mortality rate in 1000 men in corresponding age
groups in the Hungarian population (Demographic
Yearbook, 2005)
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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.

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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?

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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?

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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.

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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

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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

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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

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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)

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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
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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)

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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

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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.
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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.

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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
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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
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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.

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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

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HEP
Striking gender differences in predictors of
premature mortality, increased vulnerability of
men in most respects
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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
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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
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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)

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HEP
What might be the toxic components of lower
socioeconomic situation?
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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
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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

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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
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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
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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
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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
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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
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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
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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

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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.

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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.

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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.

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Depressive symptomatology (BDI) severity
categories in the Hungarian population
Hungarostudy Epidemiological Panel
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HEP
Depressive symptomatology (BDI) severity
categories according to HEP 2005 follow-up study
between 2002 and 2005 among men
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HEP
Depressive symptomatology (BDI) severity
categories according to HEP 2005 follow-up study
between 2002 and 2005 among women
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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

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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
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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.

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Aggregate mortality according to low vs. high
education (Mackenbach et al, 1999)
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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.

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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

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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.

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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
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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

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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.
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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)

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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

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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

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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

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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?

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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.

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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)

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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