Socioeconomic factors, material inequalities, and perceivedcontrol in self-rated health: cross-sectional data from seven

post-communist countries

Martin Bobaka,*, Hynek Pikharta, Richard Roseb, Clyde Hertzmanc,Michael Marmota

aInternational Centre for Health and Society, Department of Epidemiology and Public Health, University College London, London

WC1E 6BT, UKbCentre for the Study of Public Policy, University of Strathclyde, Glasgow, Scotland, UK

cDepartment of Health Care and Epidemiology, University of British Columbia, Vancouver, Canada

Abstract

This study examined the association between perceived control and several socioeconomic variables and self-ratedhealth in seven post-communist countries (Russia, Estonia, Lithuania, Latvia, Hungary, Poland, Czech Republic).

Questionnaire interviews were used to collect data on self-rated health in the last 12 months, education, maritalstatus, perceived control based on nine questions, and material deprivation based on availability of food, clothingand heating. For each population, two ecological measures of material inequalities were available: an inequality

score estimated from the survey data as the distance between the 90th and 10th percentiles of material deprivation,and Gini coecient from published sources. Data on 5330 men and women aged 2060 were analysed. Prevalenceof poor health (worse than average) varied between 8% in Czechs and 19% in Hungarians. The agesex-adjustedodds ratio for university vs primary education was 0.36 (0.260.49); odds ratios per 1 standard deviation increase in

perceived control and in material deprivation were 0.58 (95% CI 0.480.69) and 1.51 (1.401.63), respectively. Theodds ratio for an increase in inequality equivalent to the dierence between the most and the least unequalpopulations was 1.49 (0.882.52) using the material inequality score and 1.41 (0.912.20) using the Gini coecient.

No indication of an eect of either inequality measure was seen after adjustment for individuals deprivation orperceived control. The results suggest that, as in western populations, education and material deprivation arestrongly related to self-rated health. Perceived control appeared statistically to mediate some of the eects of

material deprivation. The non-significant eects of both ecological measures of inequality were eliminated bycontrolling for individuals characteristics. 7 2000 Elsevier Science Ltd. All rights reserved.

Keywords: Eastern Europe; Self-rated health; Socioeconomic factors; Psychosocial factors; Perceived control; Inequality

Introduction

This paper examines the relative contributions of in-

dividual deprivation, educational attainment, perceived

Social Science & Medicine 51 (2000) 13431350

0277-9536/00/$ - see front matter 7 2000 Elsevier Science Ltd. All rights reserved.PII: S0277-9536(00 )00096-4

www.elsevier.com/locate/socscimed

* Corresponding author. Tel.: +44-171-391-1684; fax: +44-

171-813-0242.

E-mail address: martinb@public-health.ucl.ac.uk (M.

Bobak).

control and national economic inequality with respect

to self-rated health in seven countries of Central andEastern Europe (CCEE) in the mid 1990s. During thesudden political changes in the region between 1989

and 1991, there was evidence of sharp economicdecline and social disruption in each country (UnitedNations Childrens Fund, 1997). In some countries,

economic inequality rose sharply whereas in others therelatively egalitarian distribution of income, found

throughout the region during the Soviet era, was lar-gely sustained (United Nations Childrens Fund, 1997).Mortality increased, but only marginally and transi-

ently in some countries (e.g. the Czech Republic)whereas the mortality increase was substantial andprolonged in others (e.g. Russia). The pattern of

increased mortality by cause and age suggested thatthe principal determinants were to be found in the

socioeconomic and psychosocial environments (Cornia,1997; Bobak & Marmot, 1996).Due to diculties with collecting data in CCEE,

research on health during the transition has been lim-ited. In order to understand the contributions to health

status, we overcame this problem by taking advantageof a pre-existing series of surveys and adding a smallnumber of key questions about the psychosocial en-

vironment and self-rated health. Self-rated health waschosen because it is easy to measure, has been exten-sively studied in western populations, and has been

shown to predict mortality in prospective studies (Idler& Benyamini, 1997). In addition, Carlson (1998) found

that an eastwest divide exist in self-rated health simi-lar to that in mortality.There is a rich literature on the influence of socioe-

conomic status, psychosocial factors and incomeinequalities on health in western countries. The associ-ation between socioeconomic status and health in the

former communist countries has been studied lessintensively but published reports suggest relatively

large educational gradients in mortality and prevalenceof risk factors (Kunst, 1997; Shkolnikov, Leon, Ada-mets, Andreev & Deev, 1998; Bobak, Hertzman, Sko-

dova & Marmot, 1999). Socioeconomic dierences inself-rated health in these countries have not beenreported. In addition to social status of individuals,

recent research suggest certain characteristics of popu-lations, such as income inequality, are important

aspects of the national social environment. Income dis-tribution was found to be associated with health out-comes, including self-rated health, in western countries

(Wilkinson, 1992; Kawachi, Kennedy, Lochner & Pro-throw-Stith, 1997; Kennedy, Kawachi, Glass & Pro-throw-Stith, 1998).

Psychosocial factors have been suggested as a poss-ible explanation for the social gradients in health in

western countries (Marmot, Bosma, Hemingway,Brunner & Stansfeld, 1997; Lachman & Weaver, 1998).

They may play a similar role in central and easternEurope. Control at work was found to be strongly re-

lated to myocardial infarction in the Czech Republic,and explained about half of the educational gradient inthe risk of infarction (Bobak, Hertzman, Skodova &

Marmot, 1998a). Given the large psychological litera-ture on perceived control over life more generally (forreview, see Skinner, 1996) and its association with

well-being and health (Skinner, 1996; Rodin, 1986;Lachman & Weaver, 1998), the extension of the con-cept of control beyond the working environment is

reasonable. For example, Syme (1989) has suggestedthat the concept of control could integrate manyaspects of psychosocial and social environment. Recentresearch provides some support for this speculation.

Carlson, using data from the 1992 World Value Sur-vey, detected an eastwest gap in self-rated health ana-logous to that in mortality, and found that perceived

control was related to self-rated health within andbetween 23 national samples of men and women (Carl-son, 1998). Consistent with his results, we have found

that perceived control was strongly related to perceivedhealth and physical functioning in Russia (Bobak,Pikhart, Hertzman, Rose & Marmot, 1998b).

The present analyses extend our work to seven cen-tral and eastern European countries: three CentralEuropean countries now negotiating membership inthe European Union; three Baltic states with a Central

European orientation albeit forcibly integrated into theSoviet Union as a consequence of the Second WorldWar; and Russia.

Methods

Populations and subjects

The study was carried out adding questions on self-rated health, perceived control and socioeconomic fac-tors to planned cross-sectional surveys in seven

countries between 1996 and 1998. These surveys, partof the New Democracies Barometer (NDB), New Bal-tic Barometer (NBB), and New Russia Barometer

(NRB) were created to find out what people in Centraland Eastern Europe were thinking during the period oftransition to democracy (Rose, 1996, 1997). They arerandom sample surveys which began in 1991, and

involve face-to-face interviews of adults about econ-omic, political and social attitudes and behaviour. By1997, 14 countries in the region had been sampled.

The national samples from Russia, Estonia, Lithua-nia, Latvia, Czech Republic, Hungary and Polandincluded in the present analyses were selected ran-

domly by multi-stage sampling of households and thenof adults (over 18 years) from the households. Thisreport is based on 5330 subjects (2431 men and 2899

M. Bobak et al. / Social Science & Medicine 51 (2000) 134313501344

women) in the age group 2060 years. Response ratesvaried between 51% in Latvia and 66% in Russia

(Table 1); refusal rates were between 16% and 25%,the remaining non-responders were those wherenobody was at home after three visits. All samples

were representative for the national populations interms of age, sex and education. Sampling and inter-views were conducted by local agencies.

Measurements

Data were collected by structured questionnairescompleted during interviews to subjects homes. In allcentres, the questionnaires contained identical ques-

tions on the variables of interest, and correct wordingwas checked by translating questions back into Eng-lish. Self-rated health was assessed by a standard ques-

tion How do you rate your health over the last 12months?, with answers Very good, Good, Average,Poor and Very poor. For the analyses, the outcome

was defined as reporting poor or very poor health(poor health).A score of perceived control was based on agree-

ment or disagreement with the following nine state-

ments: (1) At home, I feel I have control over whathappens in most situations; (2) I feel that what hap-pens in my life is often determined by factors beyond

my control; (3) Over the next 510 years I expect tohave many more positive than negative experiences; (4)I often have the feeling that I am being treated

unfairly; (5) In the past 10 years my life has been fullof changes without my knowing what will happennext; (6) I gave up trying to make big improvements

or changes in my life a long time ago; (7) Keepinghealthy depends on things that I can do; (8) There arecertain things I can do for myself to reduce the risk ofa heart attack; (9) There are certain things I can do for

myself to reduce the risk of getting cancer. These ques-tions were adapted from the Whitehall II Study (Mar-mot et al., 1991) and the MacArthur Foundation

programme on Midlife Development (Lachman &Boone James, 1997), are similar to questions on per-ceived constraints used by Lachman and Weaver in the

US (Lachman & Weaver, 1998). The subjects wereasked to what extent they agree/disagree with the state-ments; the answers were recorded at a six-point scale;Cronbachs alpha was 0.65.

Education was classified into four categories: pri-mary, vocational, completed secondary and completeduniversity. Marital status was categorised into married

and unmarried. Material deprivation was calculated asthe sum of responses to three questions, covering thefrequency of not having all the food, clothing and elec-

tricity/heating needed. As the responses were on four-point scale, their sum is between 0 and 9. For eachpopulation, an ecological index of material inequalityT

able1

Descriptionofpopulationsincluded

intheanalyses(onlysubjectsaged

3565are

included)

Age

(%)

Country

No.ofsubjects

(%men)

Response

rate

(%)

2030

3040

4050

5060

Prevalence

ofpoorhealth

(%)

%in

seriousdeprivationa

Inequality

index

bGinicoe

cient

Czech

R.

647(45)

61

28

24

21

28

83

426.0

Poland

753(43)

59

26

25

31

18

10

45

28.1

Hungary

654(42)

58

25

23

27

24

19

45

33.7

Estonia

740(47)

59

29

26

25

20

12

96

39.5

Latvia

665(53)

57

23

28

25

24

16

10

732.5

Lithuania

696(41)

51

25

30

24

20

13

86

34.9

Russia

1175(48)

66

24

24

29

24

15

25

844.6

aSeriousdeprivation:deprivationscore

r7(respondershousehold

inthelast12monthshadoften

todowithouteither

food,heating/electricity

orclothes).

bInequality

index:dierence

between90th

and10th

percentileofmaterialdeprivationscore

ineach

population.

M. Bobak et al. / Social Science & Medicine 51 (2000) 13431350 1345

was calculated as the dierence between the 10th and90th percentile of deprivation score. In addition, Gini

coecients for each country in 1996/97 were takenfrom UNICEF (United Nations Childrens Fund,1998).

Statistical analysis

Agesex-adjusted prevalence rates of poor health

were standardised by the direct method with thepooled data as the standard. The associations betweenpoor health and socioeconomic factors were estimatedby logistic regression. To account for clustering of in-

dividuals within states, robust standard errors basedon Huber formula were calculated using the clustersub-command in STATA (StataCorp., 1995). This pro-

cedure accounts for the violation of independenceamong individuals within the same country, and canbe also used for multi-level models. Perceived control,

material deprivation and both inequality indices weremeasured and analysed as continuous variables. Toexpress their eects in meaningful units, odds ratioswere calculated for one standard deviation (in pooled

dataset) increase in perceived control and materialdeprivation, and for an increase in inequality indicesequivalent to the dierence between the most and the

least unequal country.

Results

Table 1 describes the study samples. There werelarge dierences in the prevalence of poor health, withthe lowest prevalence in the Czech Republic (8%) and

the highest in Hungary (19%). The correlation coe-

cient between the agesex standardised prevalence of

self-rated health in the study samples and nationalmortality rates was 0.94 (n = 7). Overall, the preva-lence of poor health was higher than in western

countries, where typically less than 10% report healthworse than average. The proportion of responders

reporting material deprivation increased from 3%among Czechs to 25% in Russia. Both materialinequality index and the Gini coecient were lowest in

the Czech Republic and highest in Russia, and the cor-relation coecient between these two measures was

0.82 (n = 7). Perceived control was strongly inverselyrelated to material deprivation (r=0.42, n = 5294),and mean perceived control was considerably and sig-nificantly lower in countries with high inequality ( p