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Stress and Gender Gender related differences in a changing society. Maria S Kopp MD, PhD , Árpád Skrabski, PhD, Csilla Csoboth, MD, PhD. Gender Medicine Working Group, Institute of Behavioural sciences, Budapest, Hungary www.behsci.sote.hu Gender-Specific Medicine Conference

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Stress and gender gender related differences in a changing society l.jpg

Stress and GenderGender related differences in a changing society

Maria S Kopp MD, PhD, Árpád Skrabski, PhD, Csilla Csoboth, MD, PhD.

Gender Medicine Working Group,

Institute of Behavioural sciences, Budapest, Hungary

www.behsci.sote.hu

Gender-Specific Medicine Conference

February 23-26,2006, Berlin


Gender differences l.jpg
Gender differences:

  • Although men and women share the same socio-economic circumstances, there are significant gender differences in worsening mortality rates in Hungary

  • Socioeconomic differences are more closely connected with male premature mortality rates

  • What is the explanation for the increased vulnerability of middle aged men during this period of rapid economic change?


Aggregate mortality according to low versus high education mackenbach et al 1999 l.jpg
Aggregate mortality according to low versus high education(Mackenbach et al, 1999)



Special experimental model l.jpg
Special experimental model Hungary (2001)

  • The paradoxical features of gender related premature mortality and morbidity rates in Central-Eastern-European countries might be regarded as

  • a special experimental model to understand better the human consequences of chronic stress and

  • gender differences in this respect


What can explain the opposite changes in gender differences in life expectancy l.jpg
What can explain the opposite changes in Hungary (2001)gender differences in life expectancy?

  • In the 1970s no differences in Austrian and Hungarian life expectancy

  • Life expectancy in Hungary today:

  • Male 68.2, female 76.5 years-8.3 years differences in Hungary, 2.3 years lost

  • In neighbouring Austria:

  • Male 75.9- they live 7.7 years longer,

  • Female 81.7- they live 5.2 years longer

    5.8 years differences in Austria


Growing polarization of the socio economic situation between 1960 and 2002 l.jpg
Growing polarization of the socio-economic situation between 1960 and 2002

  • Until 1960, practically no income inequality, there were no mortality differences between socio-economic strata and there were smaller gender differences

  • Since that time increasing disparities in socio-economic conditions have been accompanied by a widening socio-economic gradient in mortality, but much more among men.


Slide8 l.jpg
Mortality rate in 1000 men in corresponding age groups in the Hungarian population(Demographic Yearbook, 2004)


Possible explanations l.jpg
Possible explanations: the Hungarian population

  • This deterioration cannot be ascribed to defficiencies in health care,because

  • during these years there was a significant decrease in infant and old age mortality and improvements in other dimensions of health care.

  • Between 1960 and 1989 there was a constant increase in the gross domestic product in Hungary. Worsening material situation cannot be the explanation

  • Genetic causes- sudden changes, not probable, possible changes in genetic expression


General adaptation theory of j nos selye l.jpg
General adaptation Theory of János Selye: the Hungarian population

  • The three phases of stress:

  • alarm reaction,

  • resistance phase and,

  • the third, physiologically most harmful phase, exhaustion, chronic stress

  • What type of chronic stress level is higher among men than among women in Hungary?


Gender differences11 l.jpg
Gender differences the Hungarian population

  • There are no fundamental gender differences in physiological adaptation processes

  • Although male and female hormones influence it in both respect

  • Estrogenes decrease the stress reactivity

  • According to animal studies, males appear to be more vulnerable to long-lasting stress-induced hippocampal damage than females (Uno et al, J. Neurosci,9,1705-1711,1989), the decline of circulating testosterone levels resulting from uncontrollable stress seems to play an additional role.

  • Perinatal processes might result in dysregulation- post-natal depression


Early life chronic stress l.jpg
Early life chronic stress: the Hungarian population

  • Phases of disruption of mother-infant or peer bonding:

  • 1. "protest" behaviour (acute and resistance phases of stress).

  • 2.“despair”: locomotor inactivity and a disinterst in motivationally salient external stimuli.

  • 3."detachment""hardwired" in the brain of many social mammals and results in high stress vulnerability


Attachment theory bowlby imre hermann l.jpg
Attachment theory (Bowlby, Imre Hermann) the Hungarian population

  • Physiological, psychological and developmental importance of the early childhood affective mother-child bond and the negative consequences of the disruption of this relationship.

  • According to follow up studies, insecure attachment predicts later emotional instability and health deterioration. Maltreatment at an early age can have enduring negative effects on a child’s brain development and function, and on his or her vulnerability to stress.


Special gender roles crucial effect of maternal care l.jpg
Special gender roles, crucial effect of maternal care the Hungarian population

  • Maternal neglect behaviour results in attachment disturbances

  • Animal experiments: influence of „caring” and „non-caring” mothers on development of offsprings

  • Naturally occuring variations in maternal care alter the expression of genes that regulate behavioral and endocrine responses to stress, as well as hippocampal synaptic development – related to oxytocin receptor gene expression (M.J.Meaney: Ann Rev Neurosci2001, 24,1161-1192)

  • Intergenerational transmission- importance of maternal care- in low socioeconomic groups more maternal neglect


Learned helplessness as result of chronic stress l.jpg
Learned helplessness the Hungarian populationas result of chronic stress

  • A condition of loss of control created by subjecting animals or humans to an unavoidable, emotionally negative life situation (such as unavoidable shocks, relative deprivation, role conflict, etc). Being unable to avoid or escape (flight or fight) an aversive situation for a long period of time produces a feeling of helplessness that generalises to subsequent situations.


Brain consequences of learned helplessness l.jpg
Brain consequences of learned helplessness: the Hungarian population

  • The hippocampus is primarily affected by the long-lasting elevations of circulating corticosteroids resulting from uncontrollable stress. Severe stress for a prolonged period causes damage in hippocampal pyramidal neurons, especially in the CA 3 and CA4 region and reductions in the length and arborization of their dendrites.


Main biological pathways of chronic stress l.jpg
Main biological pathways the Hungarian population of chronic stress:

  • - Dysregulation of the hypothalamus-hypophysis-adrenocortical (HPA) axis and the sympathetic-adrenal-medullary system (SAM) resulting in elevations in serum catecholamin and cortisol levels.

  • Sympathoadrenal hyperactivity contributes to the development of CVD through effects of catecholamines upon the heart, blood vessels and platelets.

  • Sympathoadrenal activation modifies the function of circulating platelets


Human learned helplessness l.jpg
Human learned helplessness: the Hungarian population

  • expectancy that responses and outcomes are uncontrollable and might result in only emotionally negative consequences.

  • refers to the motivational, cognitive and emotional components of the interpretation of the environmental stimuli

  • Central importance: values, self-ideal, expectations, attitudes

  • Gender differences in this respect.


Gender differences19 l.jpg
Gender differences? the Hungarian population

  • Differences in environmental, cultural and gender role requirements

  • Masculine versus feminine societies ( Geert Hofstede, 2001:Cultures consequences ) Hungary is extremely masculine society- different gender roles

  • Socioeconomic status seems to be more important for men,

  • Family affairs for women

  • Differences according to education level


Effect of sex nonconformity l.jpg
Effect of sex „nonconformity” the Hungarian population

  • Girls who are more „masculine” according to attitude scores

  • and boys who are more „feminine” tend to do better in intellectual giftednes measured by National Merit test score

  • This nonconforming seems to be more important among girls

  • Bem Sex-Role Inventory (BSRI) – masculine, feminine adjective checklists (Lippa,R, 1998, in Males, Females and Behavior, eds:Ellis L, Ebertz, L,Praeger, pp.177-194.)


Gender differences21 l.jpg
Gender differences: the Hungarian population

  • Anxiety and depression is significantly higher among women according to most of the studies

  • In Hungary male depression rate is relatively higher, similar to female depression rates

  • Anxiety rates are twofold of male anxiety rates

  • Alcohol and drog abuse, smoking is much more prevalent among men

  • Depression seems to influence cardiovascular risk more among men than among women according to follow up studies. (Pennix et al, 2001, Arch.Gen.Psych,58,221-227)

  • Despite similar free cortisol responses of men and women (studied in the luteal phase) to psychosocial stress, gender may exert differential effects on the immune system by modulating glucocorticoid sensitivity of proinflammatory cytokine production.(Rohleider et al,2001,Psychosom Med 63,966-972)


Objectives of our behavioral medicine studies in hungary l.jpg
Objectives of our behavioral medicine studies in Hungary: the Hungarian population

  • To reveal those social, mental and behavioural factors in their inter-relatedness with biological processes that lead to health deterioration in the Hungarian middle-aged population,

  • Analyse gender related differences in this respect,

  • introduce effective preventive strategies that are based on research findings


National representative surveys in the hungarian population l.jpg
National representative surveys in the Hungarian population the Hungarian population

  • The samples represent the Hungarian population above age 16 according to gender, age and county

  • Hungarostudy 1983 more than 6000 persons

  • Hungarostudy 1988 20.902 persons

  • Hungarostudy 1995 12.463 persons


Latest surveys hungarostudy 2002 and follow up in progress l.jpg
Latest surveys: Hungarostudy 2002 and follow up in progress the Hungarian population

  • 12,643 persons were interviewed in their homes, they represented the population above age 18 according to age and sex and counties

  • The refusal rate was 17,7% for the full sample, although there were significant differences, depending on settlements

  • About 6.500 persons agreed to participate in a follow up study- now in progress


Socio economic factors l.jpg

Education, the Hungarian population

Income,

Subjective socioeconomic status (Nancy Adler)

Acces to car

Employment

Marital status

Housing environment

Family environment

Childhood experiences

Self-rated socioeconomic changes

Socio-economic factors:


Hungarostudy indicators mental health l.jpg

Shortened Beck Depression Score the Hungarian population

Hospital Anxiety Score

WHO Wellbeing Questionnaire

Self-efficacy score

Vital exhaustion score

Hostility Score

Type D Personality Questionnaire

Hopelessness Score

Hungarostudy indicators, mental health:


Further mental health indicators l.jpg

Social support questionnaire the Hungarian population

(Caldwell)

Marital stress questionnaire

Social capital measures: trust, civic associations

Chicago collective efficacy

Stress and coping

Ways of coping questionnaire

Purposes in Life

Meaning (R.Rahe)

Anomie score

TCI shortened cooperativeness and sensation seeking

Dysfunctional attitude score

Life events

Further mental health indicators:


Work stress variables l.jpg
Work stress variables: the Hungarian population

  • Control at work

  • Social support at work

  • Working hours per week days

  • and weekend days

  • Income as job related reward

  • Job security

  • Unemployment


Health behaviour lifestyle and other confounding factors l.jpg

Smoking the Hungarian population

Alcohol (AUDIT)

Drug consumption

Physical activity

Body weight and height- BMI

Sleep complaints

Religious involvement

Suicidal behaviour

Womens health- factors related to pregnancy and birth

ethnical factors

Health behaviour, lifestyle and other confounding factors:



Slide31 l.jpg

Clinical depression (BDI: 18-), men Hungarian adult population (above 18)

Hungarostudy 2002


Slide32 l.jpg

Clinical depression (BDI: 18-), female Hungarian adult population (above 18)

Hungarostudy 2002



Significance of chronic stress depressive symptomatology l.jpg
Significance of chronic stress-depressive symptomatology men and women (Hungarostudy 2002)

  • Based on the data of our national representative surveys, we found that the worse socioeconomic situation is linked to higher morbidity and mortality rates in Hungary as well,

  • however, higher morbidity rates are connected to relatively poor socioeconomic situations mainly through the mediation of depressive symptoms,

  • in broader sense through chronic stress


Low income depression and morbidity l.jpg
Low income, depression and morbidity men and women (Hungarostudy 2002)

  • In 1988 depression mediated between low income and self-rated morbidity among men,

  • while among women low income was not significantly connected neither to depression, nor with self reported morbidity.

  • In 1995 low income became directly connected to morbidity both in men and women,

  • but the mediating effect of depression between low income and morbidity remained more important among men than among women.


Why are men more susceptible to relative income inequality l.jpg
Why are men more susceptible to relative income inequality? men and women (Hungarostudy 2002)

  • 1.Income inequality is much higher among men.

  • 2. Men are more susceptible to loss of status than women. Animal experiments have shown males to be more sensitive than females to loss of dominance position, that is loss of position in hierarchy. In animal studies social rank is the best predictor of quality of life and health among males.


Depression and chronic stress l.jpg
Depression and chronic stress: men and women (Hungarostudy 2002)

  • A self-destructive circle develops from the enduring relatively disadvantageous socioeconomic situation and depressive symptoms,

  • This circle resulting in chronic stress, might play a significant role in the increase of morbidity and mortality rates in the lower socioeconomic groups of the population.

  • 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.


For 150 hungarian subregions l.jpg

Ecological level analyses: men and women (Hungarostudy 2002)determinants of mid-aged mortality differences based onnational representative survey data and national statistical mortality data

for 150 Hungarian subregions



Ecological studies on determinants of chronic stress in the hungarian population l.jpg
Ecological studies on determinants of chronic stress in the Hungarian population

  • Socio-economic status (education and income), social capital and collective efficacy (neigborhood cohesion) explained a considerable part of the sub-regional variance in middle aged mortality rates,

  • Competitive attitude was a significant predictor of mortality only among men, while religious involvement was a significant protective factor only among women.

  • 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 ,30, 65-70.


  • Interaction between male and female health l.jpg
    Interaction between male and female health: Hungarian population

    • It is an interesting finding that the most important social capital variables of the opposite sex seem to influence the mortality for the other sex:

    • Civic support perceived by men is a protective factor for women, while the amount of reciprocity perceived by women seems to be a significant predictor of male health.

    • 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.


    Which are the protective factors for women l.jpg
    Which are the protective factors for women? Hungarian population

    • Relative economic deprivation, rival attitude and social distrust are all less important risk factors for women

    • The socio-economic differences are less important regarding the middle aged female mortality differences.

    • Neighborhood cohesion, religious involvement and reciprocity were not so much influenced by sudden socio-economic changes, therefore the protective network of women remained relatively unchanged.


    Gender paradox of subjective social status l.jpg
    Gender paradox of subjective social status: Hungarian population

    • Female subjective social status influenced highly significantly the male mid-aged mortality:

    • r (female SSS and male mid-aged mortality)= -.597 p=.000

    • That is, the subjective evaluation of the relative social deprivation by women might be an important risk factor for men as well

    • Kopp MS, Skrabski Á, Kawachi I, Adler NE (2005) Low socioeconomic staus of the opposite gender is a risk factor for middle aged mortality, J. Epidemiology and Community Health59,675-678.


    Correlations of male and female social status and male mid aged mortality l.jpg
    Correlations of male and female social status and male mid aged mortality

    Korrelációs együtthatók, középkoró férfiak halálozása


    Significant correlations of total mid aged cv mortality rates among men n 150 l.jpg

    Education -.599 aged mortality

    Income -.512

    Unemployment .465

    Social support from friends -.372

    Subjective social status .353

    Depression .352

    Weekend work hours .344

    Anomie .340

    Non stop alcohol .288

    Morning alcohol .266

    Hostility .257

    Control at work -.255

    Self-blame because of alcohol .250

    Job security -.220

    Social support at work -.197

    Smoking (cigarettes pro day) .188

    Significant correlations of total mid-aged CV mortality rates among men (n=150):


    Significant correlations of total mid aged cv mortality rates among women l.jpg

    Education -.527 aged mortality

    Income -.402

    Unemployment .378

    Social support from friends -.345

    Depression .331

    Non stop alcohol .313

    Job security -.304

    Subjective social status .303

    Anomie .287

    Hostility .229

    Control at work -.275

    Weekend work hours .225

    Morning alcohol .224

    Social support at work -.179

    Smoking (cigarettes pro day) .151

    Significant correlations of total mid-aged CV mortality rates among women:


    Work stress variables in relation to total mid aged cv mortality rates l.jpg
    Work stress variables in relation to total mid-aged CV mortality rates:

    Total male mid-aged CV mortality:

    Explained variance

    - weekend work hours 11.2 %

    - social support at work 14.7 %

    Total female mid-aged CV mortality

    - job security 8.7 %

    - weekend work hours 10.9 %


    Work stress variables in relation to mid aged ischemic heart disease mortality rates l.jpg
    Work stress variables in relation to mid-aged ischemic heart disease mortality rates:

    Male mid-aged IHD mortality:

    Explained variance

    - social support at work 3.9 %

    - weekend work hours 7.6 %

    Female mid-aged IHD mortality

    - control at work 10.6 %


    Work stress variables in relation to mid aged cerebrovascular mortality rates l.jpg
    Work stress variables in relation to mid-aged cerebrovascular mortality rates:

    Male mid-aged cerebrovascular mortality:

    Explained variance

    - weekend work hours 11.7 %

    - control at work 14.4 %

    Female mid-aged cerebrovascular mortality

    - job security 4.8 %

    - week day work hours 7.2 %


    Gender differences51 l.jpg
    Gender differences: cerebrovascular mortality rates:

    • Low control at work and low social support at work were strongly associated with premature cardiovascular mortality rates in both sexes

    • although considerable gender differences

    • Weekend workload was most closely connected with male

    • Job insecurity with female CV mortality


    Other psychosocial risk factors l.jpg
    Other psychosocial risk factors: cerebrovascular mortality rates:

    • Low social support from friends

    • Depression

    • Anomie

    • Hostility were significantly connected with premature CV mortality differences,

    • These factors explained 18.4 % of male a

    • And 15.1 % of female total CV mortality differences

    • Significantly connected with work stress variables


    Socio economic and behavioural factors l.jpg
    Socio-economic and behavioural factors cerebrovascular mortality rates:

    • Low personal income, low education and non-stop drinking explained 31.6 % of male premature CV mortality differences,

    • Low education and non stop drinking explained 25.3 % of female CV mortality differences,

    • Low education and income were strongly associated with work stress, i.e. low control at work, weekend workload, low job security, low social support at work and depression


    Conclusion mediating role of work stress and psycosocial factors l.jpg
    Conclusion: mediating role of work stress and psycosocial factors

    • The worse socioeconomic situation is linked to higher CV mortality rates in Hungary as well,

    • however, higher CV mortality rates are connected to relatively poor socioeconomic situations mainly through the mediation of work related and psychosocial risk factors,

    • These factors create chronic stress situations, which can be measured by depressive symptomatology, especially in the low socio-economic strata and in the deprived regions.

    • Kopp MS, Skrabski Á, Szántó Zs, Siegrist J (accepted for publication) Psychosocial determinants of premature cardiovascular mortality differences within Hungary, J. Epid. Community Health


    Marital stress and cardiovascular vulnerability l.jpg

    Marital stress and cardiovascular vulnerability factors

    Piroska Balog, Maria S Kopp

    Institute of Behavioral Sciences

    Semmelweis University


    Methods i l.jpg
    Methods factorsI.:

    Hungarostudy 2002

    • 12680 persons – national representative study

    • middle aged (<65 years), actively working, married or cohabiting men (2206) and women (1820)

    • 343 men and 300 women treated with hypertension

    • 49 men and 106 women treated with depression

    • Control: healthy men (731) and women (434)

    • 242 men and 280 women with high marital stress


    Slide57 l.jpg

    Methods factorsII.:

    • Marital stress: Shortened Marital Stress Scale (5 questions related to the quality of marital relationship).

    • Depression: Shortened Beck Depression Inventory(9 questions)

    • Has been treated with hypertension?

    • Has been treated with depression?

    • Age, socio-economic status

    • Body Mass Index

    • Smoking

    • Alcohol

    • Lack of physical activity


    Results marital stress and depressive symptoms bdi l.jpg
    Results: factorsMarital stress and depressive symptoms (BDI).

    Healthy men and women

    Men and women treated with hypertension

    Men and women treated with depression


    Slide59 l.jpg

    men

    Age

    OR=1.08

    (95% CI: 1.06-1.10)

    Hypertension

    OR=1.74

    (95% CI: 1,09-2,79)

    Marital stress

    OR=1.16 (95% CI: 1.12-1.21)

    OR=1.01

    (95% CI: 1.00-1.02)

    Body Mass Index

    NS

    Socio-economic status, alcohol, sedentary lifestyle

    Smoking


    Slide60 l.jpg

    Women

    Age

    OR=1.02

    (95% CI: 1.00-1.05)

    OR=2,78

    (95% CI: 1,58-4,88)

    Treatment for depression

    Marital stress

    OR=1.14 (95% CI: 1.07-1.20)

    NS

    Body Mass Index

    Socio-economic status, alcohol, smoking, sedentary lifestyle


    Slide61 l.jpg

    men

    Age

    OR=1.08

    (95% CI: 1.06-1.10)

    Hypertension

    OR=1.17 (95% CI: 1.12-1.22)

    Body Mass Index

    OR=1.01

    (95% CI: 1.00-1.02)

    Smoking

    OR=1.07 (95% CI: 1.05-1.10)

    NS

    NS

    Depression (BDI)

    Socio-economic status, alcohol, sedentary lifestyle,

    Marital stress


    Summary l.jpg
    Summary (treatment for depression)

    • High marital stress

      • Is related to increase of depressive symptoms both in men and women

      • In men it is a risk factor for hypertension, independently from traditional risk factors – through depressive symptoms

      • In women it is an independent risk factor for treatment for depression

      • In men with hypertension depression remained unrecognized (and untreated!)


    Mental health promotion consequences l.jpg
    Mental health promotion consequences: (treatment for depression)

    • Cognitive behavioural methods of early correction of vulnerability in high risk groups are in the focus of our preventive programmes

    • School and working place related „lifeskills” programmes seems to strenghten the coping abilities of high risk groups

    • There is a need for differentiated preventive and health promotion programmes for male and female subgroups of the population


    References l.jpg
    References: (treatment for depression)

    • 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 Europe s Death Rates, Science, 288, 9.June 2000, 1732-1733.

    • Kopp MS, Skrabski Á, Szedmák S (2000) Psychosocial risk factors, inequality and self-rated morbidity in a changing society, Social Sciences and Medicine 51, 1350-1361.

    • Kopp MS, Skrabski Á, Kawachi I, Adler NE (2005) Low socioeconomic staus of the opposite gender is a risk factor for middle aged mortality, J. Epidemiology and Community Health, 59,675-678.

    • Kopp MS, Skrabski Á, Szántó Zs, Siegrist J (accepted for publication) Psychosocial determinants of premature cardiovascular mortality differences within Hungary, J. Epid. Community Health

    • Kopp M, Kovács M (2006) The Quality of Life of the Hungarian population (in Hungarian) Semmelweis Publ., Budapest

    • Balog P, Janszky I, Leineweber C, Blom M, Wamala SP, Orth-Gomer K (2003): Depressive symptoms in relation to marital and work stress in women with and without coronary heart disease. The Stockholm Female Conary Risk Study. Journal of Psychosomatic Research,  54, 113-119.

    • Blom M, Janszky I, Balog P, Orth-Gomer K, Wamala SP (2003): Social Rlations in women with coronary heart disease. The effects of work and Marital stress. Journal of Cardiovascular Risk; 10 (3):201-206.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, 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, Rózsa S, Réthelyi J, Rahe RH (2005)Life meaning: an important correlate of health int he Hungarian population, International Journal of Behavioral Medicine, 12,2, 78-85.


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