Health in Europe and Russia

Abstract

The article is devoted to differences in people's health in European countries and the social inequalities associated with this subject. An analysis of 2008 European Social Survey data (a representative sample of twenty-eight countries), World Bank statistics, and World Health Organization statistics is conducted using two-level logistic modeling techniques. The analysis shows that as a rule public health in postcommunist countries is significantly worse than in other parts of the continent. The cause of this discrepancy is the relatively low level of development of the economy, welfare, and public administration of many of these countries, as well as a weakening of social integration. It is also shown that European health is structured according to demographic and social characteristics, which are dependent on the macro context of a country's level of social development. As social development improves, social inequalities in health become more uniform.

Notes

1. Tackling Inequalities in Health—twelve European countries, national census, 1998–2004.

2. Thirteen countries of Central and Eastern Europe, 2004.

3. Among the countries covered in this round of interviews are: Belgium, Bulgaria, Great Britain, Hungary, Germany, Greece, Denmark, Israel, Spain, Cyprus, Latvia, Netherlands, Norway, Poland, Portugal, Romania, Russia, Slovakia, Slovenia, Turkey, Ukraine, Finland, France, Croatia, Czech Republic, Switzerland, Sweden, and Estonia. (Data were analyzed, weighted by a variable weight. See Weighting ESS Data (http://ess.nsd.uib.no/ess/round4/). The surveys were conducted on representative national groups (with respondents ages fifteen and older). The total number of respondents was over 50,000 people. The minimum sample size was in Cyprus with 1,215 respondents, and the largest was in Germany with 2,751 respondents. The average number of respondents was approximately 2,000.

4. Stephen Raudenbush, Anthony Bryk, and Richard Congdon, Hierarchical Linear and Nonlinear Modeling; available at www.ssicentral.com/hlm.

5. In describing our results, we use the notation adopted in the above book.

6. None of the interactions of gender, age, and education with indicators of social disorganization and alcohol consumption were not statistically significant.

7. Note that when using a less conservative parameter estimation method than the one used in our models—restricted maximum likelihood instead of Laplace—the importance of this fact is not in doubt, p <  0.001.

8. Women are more sensitive to health issues, since health falls under their role as family caretaker, while men tend not to attach importance to health issues, considering them inexcusable weakness.