OP19 Social Networks and Depressive Symptoms in Russia, Poland and the Czech Republic: Evidence from the Hapiee Study
Background In countries of Central and Eastern Europe, prevalence rates of depressive symptoms are as high as 20% in men and 40% in women. Inclusion in social networks has been found to be a strong predictor of depressive symptoms in other countries, but little research on this association has been carried out in Central and Eastern Europe. This study aims to examine this association in the adult urban population in Russia, Poland and the Czech Republic.
Methods Cross-sectional analysis was performed on baseline data (2002–2005) from the Health Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study, involving men and women aged 45–69 from the adult urban population of the three countries of interest (Total N=25,674). Depressive symptoms were measured by the Centre for Epidemiological Studies Depression (CESD–20) scale. Inclusion in social networks was measured in terms of trust in informal or formal networks, and frequency of contacts with friends and distant relatives.
Results In Russia and the Czech Republic, odds of depressive symptoms were higher for men (Russia, OR 3.94, 95%CI 2.37–6.54; Czech Republic OR 2.04, 95%CI 1.18–3.52) and women (Russia, OR 2.19, 95%CI 1.47–2.99; Czech Republic OR 1.87, 95%CI 1.10–3.16) who had nobody to rely upon, compared with those who relied on friends or family. The pattern of association between frequency of contact with distant relatives or friends and depressive symptoms varied according to gender and country of origin of participants. Not having relatives outside the household was predictive of depressive symptoms among Polish men (OR 1.54, 95% C.I. 1.10–2.15) and women (OR 2.01, 95% C.I. 1.36–2.97); and not having any friends was associated with higher odds of depressives symptoms among Russian women (OR 1.54, 95% C.I. 1.09–2.19), and Polish men (OR 1.60, 95% C.I. 1.15–2.22).
Conclusion The results presented here suggest that exclusion from social networks is a strong predictor of depressive symptoms and that there is a country specific pattern of variation in how frequency of contact with social networks affects the risk of depressive symptoms. We argue that this variation could be due to differences in economic development and social capital of Russia, Poland and the Czech Republic.