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International Centre for Health and Society, University College London, UK
Jagiellonian University, Krakow, Poland
National Institute of Public Health, Prague, Czech Republic
Institute of Internal Medicine, Novosibirsk, Russia
Regional Public Health Authority, Ostrava, Czech Republic
Jagiellonian University Krakow, Poland
Institute of Internal Medicine, Novosibirsk, Russia
International Centre for Health and Society, University College London, UK
Correspondence: Dr Martin Bobak, International Centre for Health and Society, Department of Epidemiology and Public Health, University College London, 119 Torrington Place, London WC1E 6BT, UK. Tel: +44 (0)20 7679 5613; fax: +44 (0)20 7813 0242; e-mail: m.bobak{at}ucl.ac.uk
Declaration of interest None. Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To investigate the rates and distribution of depressive symptoms in urban population samples in Russia, Poland and the Czech Republic.
Method A cross-sectional study was conducted in randomly selected men and women aged 4564 years (n=2151 in total, response rate 69%) in Novosibirsk (Russia), Krakow (Poland) and Karvina (Czech Republic). The point prevalence of depressive symptoms in the past week was defined as a score of at least 16 on the Center for Epidemiological Studies Depression scale.
Results In men the prevalence of depressive symptoms was 23% in Russia, 21% in Poland and 19% in the Czech Republic; in women the rates were 44%, 40% and 34% respectively. Depressive symptoms were positively associated with material deprivation, being unmarried and binge drinking. The association between education and depression was inverse in Poland and the Czech Republic but positive in Russia.
Conclusions The prevalence of depressive symptoms in these eastern European urban populations was relatively high; as in other countries, it was associated with alcohol and several sociodemographic factors.
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INTRODUCTION |
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METHOD |
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Measurements
Depressive symptoms were measured using the Center for Epidemiologic
Studies Depression scale (CESD;
Radloff, 1977). This scale
consists of 20 self-reported items (presence of symptoms in the past week) and
scores range between 0 and 60. The full scale was used in the analysis. The
depression score was calculated if at least 16 out of 20 questions were
answered; if fewer than 20 questions were answered, the score was recalculated
to have values between 0 and 60. Cronbachs
coefficients of
internal consistency were 0.86 in Poland, 0.81 in Russia and 0.86 in the Czech
Republic.
Several social characteristics were used as covariates. Participants were grouped into four categories of attained education: primary or less, vocational (apprenticeship), secondary (A-level equivalent) and university degree. An indicator of material deprivation was assessed by questions about how often the persons household had difficulties in buying enough food or clothes and in paying bills for housing, heating and electricity; a deprivation score was calculated based on these questions. Experience of unemployment in the past 12 months was recorded for all respondents. Individuals were categorised by marital status as married/cohabiting, single, divorced or widowed. We also assessed crowding (more than one person per room), ownership of selected household items, self-perceived changes in participants income and material conditions since 1989, drinking alcohol at least once a week, mean dose of alcohol consumed per drinking session, and smoking (at least one cigarette a day).
Statistical analysis
Depressive symptoms were analysed initially as both continuous (the
CESD score) and dichotomous variables; in the latter, participants with
CESD scores of 16 and above were considered as having depressive
symptoms (Beekman et al,
1995; Ferketich et
al, 2000). Because both analyses produced essentially
identical results, findings on the dichotomised outcomes are reported
here.
The analytical strategy was as follows. First, all relevant variables were cross-tabulated by country and gender, and descriptive measures were calculated. Second, we used logistic regression to estimate age-adjusted odds ratios of depressive symptoms by socio-economic and demographic variables, for men and women separately. Where continuous scales were used for explanatory variables, the results are reported for an increase by one standard deviation. Finally, the odds ratios of depressive symptoms by socio-demographic variables were adjusted for other social covariates, in order to take into account potential confounding. These final multivariate analyses were initially also conducted separately for each country, but there was no statistically significant interaction between country and the covariates, except that the relation between education and depressive symptoms in Russia was different from that of the other two countries (a model with interaction between education and country explained the data statistically significantly better than a model without such interaction). We therefore pooled the data from all three countries and included an interaction term between country and education. The multivariate results are thus based on data from all three countries. All analyses were performed using STATA version 8 for Windows.
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RESULTS |
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After controlling for age, the presence of depressive symptoms was significantly associated with self-assessed material deprivation in all centres in both genders (Table 2). The association with education differed by country: there was an inverse relationship in Polish and Czech samples (although it did not reach statistical significance in men), but there was no clear association in Russian men and the association in Russian women was positive. Unmarried men, but not women, tended to have higher rates of depressive symptoms, but the pattern and significance differed between countries. There was no clear relationship between depressive symptoms and history of unemployment. People who drank large amounts of alcohol per drinking occasion had higher rates of depressive symptoms, although the country-specific estimates were not statistically significant. Among other variables, not reported in the table, negative rating of the changes after 1989 tended to be related to higher prevalence of depressive symptoms, but the relationship was not statistically significant in Russia or in Czech women. Depressive symptoms were not related to crowding, smoking, or drinking more often than once a week.
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Since socio-demographic characteristics are mutually correlated, we estimated their independent association with depressive symptoms in the pooled data (Table 3). After controlling for covariates, higher rates of depressive symptoms were found in women, people with higher levels of material deprivation, those divorced or widowed, and in people who consumed high doses of alcohol per drinking session. There was an interaction between education and country: higher education was associated with lower rates of depressive symptoms in the Czech Republic and Poland but with higher rates in Russia (P=0.003 for interaction). Unemployment, crowding and perception of changes in income since 1989 were not associated with depressive symptoms in the pooled data.
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DISCUSSION |
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Limitations of the study
Several limitations of the study need to be considered. First, the
CESD scale, like other screening instruments, is not perfect in
measuring clinical depression; it has relatively low specificity
(Mulrow et al, 1995),
and our definition of depressive symptoms therefore includes mainly minor
depression and psychological distress, rather than major or severe depression
(Beekman et al, 1995).
Although the CESD is probably the most widely used and extensively
validated instrument for the assessment of depressive symptoms in many
countries (Beekman et al,
1995; Mulrow et al,
1995), including Poland (Dojka
et al, 2003) and the Czech Republic
(Osecka, 1999), it has not, to
our knowledge, been used or formally validated in Russia. In theory, Russians
might report depressive symptoms differently from other nationalities, but
given the good internal consistency of the CESD scale and the
similarity of the distribution of depressive symptoms in the three
populations, such a bias is unlikely.
Second, both depressive symptoms and the covariates were self-reported. Some of the covariates are subjective, such as the rating of the changes after 1989 and, to a lesser extent, deprivation. It is therefore possible that some cross-contamination between reporting of depressive symptoms and covariates occurred, which might have led to overestimation of the strength of the relationships. For example, depressed people might view the changes over the past 10 years more negatively than those without symptoms of depression. Although the weak association between depression and unemployment argues against a major presence of this bias, the cross-sectional design is certainly vulnerable to it.
Third, it is impossible to ascertain temporality in cross-sectional studies. For example, being divorced can lead to depression, but depression can also lead to marital problems and result in divorce. In our study, this situation could have influenced the relationship between depressive symptoms and marital status and, in theory, with deprivation. However, given that deprivation relates to the whole household, a direct effect of depression on material deprivation is probably limited.
Fourth, non-response bias should also be considered. In general, people who participate in health surveys are healthier than those who do not. Thus, the levels of depressive symptoms in our study are probably underestimated. However, assuming that the differences between respondents and non-respondents were similar in all countries, the comparisons between the populations are valid, even if the absolute prevalence rates were underestimated. The non-response bias should not affect the association between depressive symptoms and socio-demographic factors within the study sample.
Fifth, the sample size was relatively small, particularly for analyses conducted separately by gender and country. Given the numerous comparisons, some of the weaker associations within centres need to be interpreted cautiously. Results of the analyses of the pooled data, however, were based on sufficient numbers of participants, and should be statistically reliable.
Finally, it is possible that the selected urban centres were not entirely representative of the whole countries. Available data suggest that Novosibirsk is fairly typical of Russia in terms of social conditions, health and alcohol intake (Nikitin & Gerasimenko, 1995; Nemtsov, 2000; Tchernina, 2000). Compared with the national average, rates of ill health and deprivation in Krakow may be somewhat underestimated and in Karvina somewhat overestimated, but overall the health patterns in Novosibirsk, Krakow and Karvina-Havirov probably approximate well those for Russia, Poland and the Czech Republic respectively. It is therefore likely that the differences between the three populations reflect differences between countries.
Differences in depressive symptoms between the three populations
In both genders, the prevalence and mean score of depressive symptoms were
somewhat higher in Russia than in the Czech Republic and Poland. The general
turmoil associated with the social and economic transition affected Russia
considerably more than Poland and the Czech Republic
(Klein & Pomer, 2001;
UNICEF, 2003), and such social
upheaval can plausibly lead to psychological distress. In the light of the
reported high and increasing levels of alcohol problems,
suicide and poor general health status (Bobak et al,
2000,
2004;
Makinen, 2000;
Shkolnikov & Cornia, 2000;
Shkolnikov et al,
2001; World Health
Organization, 2002) and the low use of antidepressant treatment in
Russia (Simon et al,
2004), we expected to find substantially higher levels of
depressive symptoms in Russia than in the other two countries. However, in our
data depressive symptoms in Russia were not dramatically more common than in
Poland. The CESD score of 16 or above does not translate into clinical
diagnostic criteria and it probably reflects largely psychological distress
(Beekman et al, 1995),
whereas it is major depression that has an impact on indices such as suicide
rate. We therefore urge caution when extrapolating from minor depressive
symptoms to all depressive disorders, including major depression.
Comparison of eastern Europe with other populations
Although there have been earlier studies of depression in central and
eastern Europe, this report is, to our knowledge, the first that has
investigated the prevalence of depressive symptoms in a general population
sample in Russia and provided a direct comparison with other parts of the
world. Community-based studies in western Europe show a wide range of
prevalence rates of depressive symptoms, defined as 16 points or above on the
CESD scale: 39% and 12% in elderly Spanish women and men respectively
(Zunzunegui et al,
2001); 13% and 9% in older French men and women respectively
(Paterniti et al,
2000); and 39% in a British study
(Weich et al, 2002).
Prevalence in elderly Europeans is usually between 10% and 15% (reviewed by
Beekman et al, 1995).
In the USA, studies using the CESD instrument reported prevalence of
depressive symptoms of 18% and 10% in women and men respectively
(Ferketich et al,
2000), but there are pronounced ethnic differences; in females,
for example, the prevalence rates range from 14% in Chinese and Japanese
Americans to 43% in Hispanic women
(Bromberger et al,
2004). A recent study in Korea found a prevalence of depressive
symptoms of 42% in women and 35% in men
(Kim et al, 2005).
Several studies of depressive symptoms, not using the CESD, in
adolescents or in women around the time of childbirth reported higher levels
of depressive symptoms in Russia than in Britain or the USA
(Charman & Pervova, 1996;
Dragonas et al, 1996;
Jose et al, 1998).
The differences between men and women were similar to results in other
European and North American populations.
In this context, the rates found in Russia, Poland and the Czech Republic are relatively high but within the range reported internationally. As mentioned above, our measurement of outcome also includes a certain amount of general distress, and the relatively high rates of depressive symptoms may partly be due to the widespread dissatisfaction related to the social upheaval during the economic transformation period. A similar explanation has been proposed for the high rates of depressive symptoms in Korea found after the 1997 financial crisis (Kim et al, 2005). The role of psychological distress, rather than major depression, in the high rates of depressive symptoms in this study is supported by an international study which found that prevalence of mood disorders (including major clinical depression) in Ukraine, a country affected by the transition even more than Russia, was similar to that in other European and North American countries (WHO World Mental Health Survey Consortium, 2005).
Socio-economic differentials within populations
In European and North American societies, depression is typically more
common in lower socio-economic groups
(Lorant et al, 2003).
In the eastern European populations surveyed in the present study, material
deprivation was the most consistent predictor of depressive symptoms; the
effects were present in all countries in both genders. The higher rates of
depressive symptoms in unmarried than married people, particularly in women,
are also consistent with studies in other populations
(van Grootheest et al,
1999). Interestingly, the influence of education, which was
previously found to predict well other outcomes in central and eastern Europe
(Bobak et al, 2000;
Plavinski et al,
2003), differed between countries. In the Czech Republic and
Poland, the levels of depressive symptoms tended to decline with increasing
education, consistent with a previous study in the Czech Republic
(Dzurova et al,
2000). In Russia, however, the association was positive, mainly
due to results in women. It is not clear what could explain such a positive
association. It could be speculated that women with higher education,
especially those who have to look after a family, might have suffered a
relatively steeper decline in perceived social status during the societal
transformation than men or women with low education. Unfortunately, our sample
was too small to conduct more detailed or subgroup analyses within the Russian
sample.
Alcohol has long been associated with depression (Edwards et al, 1997; Caan, 2002; Jenkins, 2004). In our study drinking once a week or more often was not related to depressive symptoms, but the consumption of large amounts of alcohol per drinking session showed a strong association with depression. This is consistent with a report from the Udmurtia region of Russia of a strong link between depression and alcohol dependency (Pakriev et al, 1998b). It was suggested that the binge-drinking pattern is a particularly important determinant of health in eastern European populations (Britton & McKee, 2000; Bobak et al, 2004), and our results are consistent with this proposition.
In conclusion, our study does not suggest large differences in the rates of depressive symptoms between these eastern European urban populations. Although depression scores were marginally higher in Russia than in the other two countries, depressive symptoms do not seem to explain the high and increasing rates of ill health, mortality and suicide in Russia. Depressive symptoms were associated with binge drinking and a number of socio-demographic characteristics, but the direction of the educational gradient differed between countries. Larger studies would be needed to clarify this paradoxical finding and to provide more reliable estimates of the effects of social and behavioural factors on depression in these countries.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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REFERENCES |
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Bobak, M., Pikhart, H., Rose, R., et al (2000) Socioeconomic factors, material inequalities, and perceived control in self-rated health: cross-sectional data from seven post-communist countries. Social Science and Medicine, 51, 1343 1350.[CrossRef]
Bobak, M., Room, R., Kubinova, R., et al
(2004) Contribution of alcohol consumption and drinking
patterns to rates of alcohol-related problems in urban populations in Russia,
Poland and the Czech Republic. A cross-sectional study. Journal of
Epidemiology and Community Health,
58, 238
242.
Britton, A. & McKee, M. (2000) The relation
between alcohol and cardiovascular disease in Eastern Europe: explaining the
paradox. Journal of Epidemiology and Community Health,
54, 328
332.
Bromberger, J. T., Harlow, S., Avis, N., et al
(2004) Racial/ethnic differences in the prevalence of
depressive symptoms among middle-aged women: the Study of Womens Health
Across the Nation (SWAN). American Journal of Public
Health, 94, 1378
1385.
Caan, W. (2002) Alcohol and the mind. In Drink, Drugs and Dependence. From Science to Clinical Practice (eds W. Caan & J. De Belleroche), pp. 51 68. London: Routledge.
Charman, T. & Pervova, I. (1996) Self-reported depressed mood in Russian and UK schoolchildren. A research note. Journal of Child Psychology and Psychiatry, 37, 879 883.
Dojka, E., Gorkiewicz, M. & Pajak, A. (2003) Psychometric value of CESD scale for the assessment of depression in Polish population. Psychiatria Polska, 37, 281 292.[Medline]
Dragonas, T., Golding, J., Greenwood, R., et al (1996) Stresses and strains, anxiety and depression during the first half of pregnancy. In Pregnancy in the 90s: The European Longitudinal Study of Pregnancy and Childhood (eds T. Dragonas, J. Golding, R. Ignatyeva, et al), pp. 38 44. Bristol: Sansom.
Dzurova, D., Smolova, E. & Dragomirecka, E. (2000) Mental Health in the Sociodemographic Context. Results of a Sample Survey in the Czech Republic. Prague: Charles University.
Edwards, G., Marshall, E. J. & Cook, C. H. C. (1997) The Treatment of Drinking Problems. A Guide for the Helping Professions. Cambridge: Cambridge University Press.
Ferketich, A. K., Schwartzbaum, J. A., Frid, D. J., et
al (2000) Depression as an antecedent to heart disease
among women and men in the NHANES I study. National Health and Nutrition
Examination Survey. Archives of Internal Medicine,
160, 1261
1268.
Jenkins, R. (2004) WHO Guide to Mental and Neurological Health in Primary Care. London: Royal Society of Medicine Press.
Jose, P. E., DAnna, C. A., Cafasso, L. L., et al (1998) Stress and coping among Russian and American early adolescents. Developmental Psychology, 34, 757 769.[CrossRef][Medline]
Kim, E., Jo, S. A., Hwang, J. Y., et al (2005) A survey of depressive symptoms among South Korean adults after the Korean financial crisis of late 1997: prevalence and correlates. Annals of Epidemiology, 15, 145 152.[CrossRef][Medline]
Klein, L. R. & Pomer, M. (eds) (2001) The New Russia. Transition Gone Awry. Stanford, CA: Stanford University Press.
Lorant, V., Deliege, D., Eaton, W., et al
(2003) Socioeconomic inequalities in depression: a
meta-analysis. American Journal of Epidemiology,
157, 98
112.
Makinen, L. H. (2000) Eastern European transition and suicide mortality. Social Science and Medicine, 51, 1405 1420.
Men, T., Brennan, P., Boffetta, P., et al
(2003) Russian mortality trends for 19912001: analysis
by cause and region. BMJ,
327, 964
969.
Mulrow, C. D., Williams, J. W., Gerety, M. B., et al
(1995) Case-finding instruments for depression in primary
care settings. Annals of Internal Medicine,
122, 913
921.
Murray, C. J. L. & Lopez, A.D. (1996) The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability from Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020. Cambridge, MA: Harvard University Press.
Nemtsov, A. (2000) Estimates of total alcohol consumption in Russia, 19801994. Drugs and Alcohol Dependence, 58, 133 143.
Nikitin, Y. P. & Gerasimenko, N. F. (1995) Health of Siberian Population [in Russian]. Novosibirsk: Siberian Branch of the Russian Academy of Medical Sciences.
Osecka, L. (1999) Skala Deprese CESDPsychometricka Analyza [Depression Scale CESD: Psychometric Analysis; in Czech]. Brno: Czech Academy of Sciences.
Pakriev, S., Vasar, V., Aluoja, A., et al (1998a) Prevalence of mood disorders in the rural population of Udmurtia. Acta Psychiatrica Scandinavica, 97, 169 174.[Medline]
Pakriev, S., Vasar, V., Aluoja, A., et al
(1998b) Prevalence of ICD10 harmful use of
alcohol and alcohol dependence among the rural population in Udmurtia.
Alcohol and Alcoholism,
33, 255
264.
Paterniti, S., Verdier-Taillefer, M.-H., Geneste, C., et
al (2000) Low blood pressure and risk of depression in
the elderly: a prospective community-based study. British Journal
of Psychiatry, 176, 464
467.
Plavinski, S. L., Plavinskaya, S. I. & Klimov, A. N.
(2003) Social factors and increase in mortality in Russia in
the 1990s: prospective cohort study. BMJ,
326, 1240
1242.
Radloff, L. S. (1977) The CESD scale: a self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385 401.[Abstract]
Shkolnikov, V. M. & Cornia, G. A. (2000) The population crisis and rising mortality in transitional Russia. In The Mortality Crisis in Transitional Economies (eds G. A. Cornia & R. Paniccia), pp. 253279. New York: Oxford University Press.
Shkolnikov, V., McKee, M. & Leon, D. A. (2001) Changes in life expectancy in Russia in the mid-1990s. Lancet, 357, 917 921.[CrossRef][Medline]
Simon, G. E., Fleck, M., Lucas, R., et al
(2004) Prevalence and predictors of depression treatment in
an international primary care study. American Journal of
Psychiatry, 161, 1626
1634.
Tchernina, N. (2000) Rising unemployment and coping strategies: the case of the Novosibirsk oblast in Russia. In The Mortality Crisis in Transitional Economies (eds G. A. Cornia & R. Paniccia), pp. 151173. New York: Oxford University Press.
UNICEF (2003) Social Monitor 2003. Social Trends in Transition. Florence: UNICEF Innocenti Research Centre.
van Grootheest, D. S., Beekman, A. T., Broese van Groenou, M. I., et al (1999) Sex differences in depression after widowhood. Do men suffer more? Social Psychiatry and Psychiatric Epidemiology, 34, 391 398.[CrossRef][Medline]
Weich, S., Blanchard, M., Prince, M., et al
(2002) Mental health and the built environment:
cross-sectional survey of individual and contextual risk factors for
depression. British Journal of Psychiatry,
180, 428
433.
World Health Organization (2002) Suicide Prevention in Europe: The WHO European Monitoring Survey on National Suicide Prevention Programmes and Strategies. Geneva: WHO.
World Health Organization World Mental Health Survey Consortium (2005) Prevalence, severity and unmet needs for treatment of mental disorders in the World Health Organization World Mental Health Survey. JAMA, 291, 2581 2590.
Zunzunegui, M. V., Beland, F. & Otero, A.
(2001) Support from children, living arrangements, self-rated
health and depressive symptoms of older people in Spain.
International Journal of Epidemiology,
30, 1090
1099.
Received for publication November 23, 2004. Revision received June 8, 2005. Accepted for publication June 20, 2005.
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