[Socioeconomic inequalities in mortality in Europe]. / Les inégalités sociales de mortalité en Europe.

In all European countries, the rates of death were higher in groups of lower socioeconomic status, but the magnitude of the inequalities between groups of higher and lower socioeconomic status was much larger in some countries than in others. Inequalities in mortality were small in some Southern European countries and very large in most countries in the eastern and Baltic regions. These variations among countries appeared to be attributable in part to causes of death related to smoking or alcohol use or amenable to medical intervention. These results imply that there is opportunity to reduce inequalities in mortality. Developing policies and interventions that effectively target the structural and immediate determinants of inequalities in health is an urgent priority for public health research.

Female ever-smoking, education, emancipation and economic development in 19 European countries.

Large differences in ever-smoking rates among women are found between countries and socio-economic groups. This study examined the socio-economic inequalities in female ever-smoking rates in 19 European countries, and explored the association between cross-national differences in these inequalities and economic development and women's emancipation. Data on smoking were derived from national health interview surveys from 19 European countries. For each country, age group (25-39, 40-59 and 60+ years), educational level (4 standard levels), and cumulative ever-smoking rates were calculated as the proportion of current and former smokers of the total survey population. A Relative Index of Inequality was estimated for women in the three age groups to measure the magnitude of educational differences. In regression analyses the association of ever-smoking rates of women age 25-39 years with the gross domestic product (GDP) and the Gender Empowerment Measure (GEM) was explored. Less educated women aged 25-39 years were more likely to have ever smoked than more educated women in all countries, except Portugal. In the age groups 40-59 years the educational pattern differed between countries. Women aged 60+ years who were less educated were less likely to have ever smoked in all countries, except Norway and England. The size of inequalities varied considerably between countries and reversed within three age groups. For women 25-39 years, the association of ever-smoking rates with GDP was positive, especially for more educated women. The association of ever-smoking rates with GEM was positive for less educated women, but negative for more educated women. The results are consistent with the idea that economic development and social-cultural processes related to gender empowerment have affected the diffusion of smoking in different ways for more and less educated women.

Socioeconomic inequalities in health in 22 European countries.

BACKGROUND: Comparisons among countries can help to identify opportunities for the reduction of inequalities in health. We compared the magnitude of inequalities in mortality and self-assessed health among 22 countries in all parts of Europe. METHODS: We obtained data on mortality according to education level and occupational class from census-based mortality studies. Deaths were classified according to cause, including common causes, such as cardiovascular disease and cancer; causes related to smoking; causes related to alcohol use; and causes amenable to medical intervention, such as tuberculosis and hypertension. Data on self-assessed health, smoking, and obesity according to education and income were obtained from health or multipurpose surveys. For each country, the association between socioeconomic status and health outcomes was measured with the use of regression-based inequality indexes. RESULTS: In almost all countries, the rates of death and poorer self-assessments of health were substantially higher in groups of lower socioeconomic status, but the magnitude of the inequalities between groups of higher and lower socioeconomic status was much larger in some countries than in others. Inequalities in mortality were small in some southern European countries and very large in most countries in the eastern and Baltic regions. These variations among countries appeared to be attributable in part to causes of death related to smoking or alcohol use or amenable to medical intervention. The magnitude of inequalities in self-assessed health also varied substantially among countries, but in a different pattern. CONCLUSIONS: We observed variation across Europe in the magnitude of inequalities in health associated with socioeconomic status. These inequalities might be reduced by improving educational opportunities, income distribution, health-related behavior, or access to health care.

Identification of socioeconomic groups at increased risk for smoking in European countries: looking beyond educational level.

Educational level is most often used to identify social groups with increased prevalence of smoking. Other indicators of socioeconomic position (SEP) might, however, be equally or even more discriminatory. This study examined the extent to which smoking behavior is related to other socioeconomic indicators in addition to educational level. Data were derived from the European Household Panel. We selected data for 45,765 respondents aged 25-60 years from nine European countries. The association between six different SEP indicators and smoking prevalence was examined using prevalence rate ratios (RRs) estimated through log linear regression analyses. In univariate analyses, most selected SEP indicators were associated with smoking. In multivariate analyses, educational level, occupational class, accumulated wealth (measured by household assets), and housing tenure retained independent effects on smoking (RRs about 1.20). The effects observed for activity status and household income were small and insignificant in nearly all populations. In northern Europe, educational level had the greatest predictive value in the younger age groups; occupational class and housing tenure predicted most of smoking prevalence in the older age groups. The results showed a less pronounced and more varied pattern in southern Europe. Our results indicate that smoking prevalence is related not only to educational level but also to occupational class and measures of accumulated wealth (other than income). These measures should be used in addition to educational level to identify groups at increased risk for smoking.