Domantas Jasilionis

The changing relation between education and life expectancy in central and eastern Europe in the 1990s

Background: The political and social transition in central and eastern Europe has been generally associated with widening educational differences in life expectancy. However, interpretation of these findings is complicated because the size of educational categories within the population has also changed. It is therefore important to disentangle these two phenomena. Setting: The Czech Republic, Estonia, the Russian Federation and, as a western European reference, Finland, in two periods, 1988–89 and 1998–99. Methods: Life tables were calculated in three categories: university; secondary; and less than secondary education. Changes in life expectancy were decomposed into contributions of population composition and within-category mortality. Results: In Finland and the Czech Republic improvements are seen in all educational groups, with only a slight widening of the educational differences. Over 80% of the total life expectancy increase is attributable to improved mortality within educational categories. In Estonia and Russia, less favourable overall trends coincide with a dramatic widening of the educational gap. A decrease in life expectancy in those with low and middle education has been compensated for, to a small degree in Russia but a greater extent in Estonia, by improvements among those with higher education and by the improved population composition. For highly educated Estonians, the gains were seen at all ages, the greatest at age ⩾60 years. In Russia mortality increased in those <60 years although compensated for by improvements at older ages. Conclusions: Russia and Estonia exhibit much less equitable transitions compared with the Czech Republic. Analyses of trends in health inequalities should capture the changing population composition. In Russia and Estonia an improved educational structure prevented an even greater decline in life expectancy. The highly educated Estonians can potentially catalyse a wider health progress.

Increasing absolute mortality disparities by education in Finland, Norway and Sweden, 1971–2000

Background and objectives Studies on socioeconomic health disparities often suffer from a lack of uniform data and methodology. Using high quality, census-linked data and sensible inequality measures, this study documents the changes in absolute and relative mortality differences by education in Finland, Norway and Sweden over the period 1971 to 2000. Methods The age-standardised mortality rates and the population exposures for three educational categories were computed from detailed data provided by the national statistical offices. Mortality disparities by education were assessed using two range measures (rate differences and rate ratios), and two Gini-like measures (the average inter-group difference (AID) and the Gini coefficient (G)). The formulae for the decomposition of the change in the AID into (1) the contribution of change in population composition by education, and (2) the contribution of mortality change were introduced. Results Mortality decreases were often greater for high than for medium and low education. Both relative and absolute mortality disparities tend to increase over time. The magnitude and timing of the increases in absolute disparities vary by country. Both the rate differences and the AIDs have increased since the 1970s in Norway and Sweden, and since the 1980s in Finland. The contributions of the changes in population composition to the total AID increase were substantial in all countries, and for both sexes. The mortality contributions were substantial for males in Norway and Sweden. Conclusions The study reports increases in absolute mortality disparity, and its components. This trend needs to be further studied and addressed by policies.

How can inequalities in mortality be reduced? A quantitative analysis of 6 risk factors in 21 european populations

Background Socioeconomic inequalities in mortality are one of the greatest challenges for health policy in all European countries, but the potential for reducing these inequalities is unclear. We therefore quantified the impact of equalizing the distribution of six risk factors for mortality: smoking, overweight, lack of physical exercise, lack of social participation, low income, and economic inactivity. Methods We collected and harmonized data on mortality and risk factors by educational level for 21 European populations in the early 2000s. The impact of the risk factors on mortality in each educational group was determined using Population Attributable Fractions. We estimated the impact on inequalities in mortality of two scenarios: a theoretical upward levelling scenario in which inequalities in the risk factor were completely eliminated, and a more realistic best practice scenario, in which inequalities in the risk factor were reduced to those seen in the country with the smallest inequalities for that risk factor. Findings In general, upward levelling of inequalities in smoking, low income and economic inactivity hold the greatest potential for reducing inequalities in mortality. While the importance of low income is similar across Europe, smoking is more important in the North and East, and overweight in the South. On the basis of best practice scenarios the potential for reducing inequalities in mortality is often smaller, but still substantial in many countries for smoking and physical inactivity. Interpretation Theoretically, there is a great potential for reducing inequalities in mortality in most European countries, for example by equity-oriented tobacco control policies, income redistribution and employment policies. Although it is necessary to achieve substantial degrees of upward levelling to make a notable difference for inequalities in mortality, the existence of best practice countries with more favourable distributions for some of these risk factors suggests that this is feasible.

Educational differences in disability-free life expectancy: a comparative study of long-standing activity limitation in eight European countries

Healthy life expectancy is a composite measure of length and quality of life and an important indicator of health in aging populations. There are few cross-country comparisons of socioeconomic differences in healthy life expectancy. Most of the existing comparisons focus on Western Europe and the United States, often relying on older data. To address these deficiencies, we estimated educational differences in disability-free life expectancy for eight countries from all parts of Europe in the early 2000s. Long-standing severe disability was measured as a Global Activity Limitation Indicator (GALI) derived from the European Union Statistics on Income and Living Conditions (EU-SILC) survey. Census-linked mortality data were collected by a recent project comparing health inequalities between European countries (the EURO-GBD-SE project). We calculated sex-specific educational differences in disability-free life expectancy between the ages of 30 and 79 years using the Sullivan method. The lowest disability-free life expectancy was found among Lithuanian men and women (33.1 and 39.1 years, respectively) and the highest among Italian men and women (42.8 and 44.4 years, respectively). Life expectancy and disability-free life expectancy were directly related to the level of education, but the educational differences were much greater in the latter in all countries. The difference in the disability-free life expectancy between those with a primary or lower secondary education and those with a tertiary education was over 10 years for males in Lithuania and approximately 7 years for males in Austria, Finland and France, as well as for females in Lithuania. The difference was smallest in Italy (4 and 2 years among men and women, respectively). Highly educated Europeans can expect to live longer and spend more years in better health than those with lower education. The size of the educational difference in disability-free life expectancy varies significantly between countries. The smallest and largest differences appear to be in Southern Europe and in Eastern and Northern Europe, respectively.

Educational Inequalities in Three Smoking-Related Causes of Death in 18 European Populations

INTRODUCTION Smoking is an important determinant of socioeconomic inequalities in mortality in many countries. As the smoking epidemic progresses, updates on the development of mortality inequalities attributable to smoking are needed. We provide estimates of relative and absolute educational inequalities in mortality from lung cancer, aerodigestive cancers, and chronic obstructive pulmonary disease (COPD)/asthma in Europe and assess the contribution of these smoking-related diseases to inequalities in all-cause mortality. METHODS We use data from 18 European populations covering the time period 1998-2007. We present age-adjusted mortality rates, relative indices of inequality, and slope indices of inequality. We also calculate the contribution of inequalities in smoking-related mortality to inequalities in overall mortality. RESULTS Among men, relative inequalities in mortality from the 3 smoking-related causes of death combined are largest in the Czech Republic and Hungary and smallest in Spain, Sweden, and Denmark. Among women, these inequalities are largest in Scotland and Norway and smallest in Italy and Spain. They are often larger among men and tend to be larger for COPD/asthma than for lung and aerodigestive cancers. Relative inequalities in mortality from these conditions are often larger in younger age groups, particularly among women, suggesting a possible further widening of inequalities in mortality in the coming decades. The combined contribution of these diseases to inequality in all-cause mortality varies between 13% and 32% among men and between -5% and 30% among women. CONCLUSION Our results underline the continuing need for tobacco control policies, which take into account socioeconomic position.

Trends and geographic differentials in mortality under age 60 in India

The study examines overall and region-specific mortality changes and regional mortality variation in India since the 1970s, using data from the Sample Registration System (SRS). An evaluation of the quality of SRS data confirms their reliability for children and adults under age 60. The results suggest the convergence of mortality across the regions of India with important inter-state differences in the pace of health improvements over time. After spectacular progress during the 1970s and the 1980s, many Indian states have witnessed slower mortality improvements in both young and adult age groups. India faces difficulties in making further reductions in infant mortality and in the burden of chronic and man-made diseases at adult ages.

Occupational class inequalities in all-cause and cause-specific mortality among middle-aged men in 14 European populations during the early 2000s

This study analyses occupational class inequalities in all-cause mortality and four specific causes of death among men, in Europe in the early 2000s, and is the most extensive comparative analysis of occupational class inequalities in mortality in Europe so far. Longitudinal data, obtained from population censuses and mortality registries in 14 European populations, from around the period 2000–2005, were used. Analyses concerned men aged 30–59 years and included all-cause mortality and mortality from all cancers, all cardiovascular diseases (CVD), all external, and all other causes. Occupational class was analysed according to five categories: upper and lower non-manual workers, skilled and unskilled manual workers, and farmers and self-employed combined. Inequalities were quantified with mortality rate ratios, rate differences, and population attributable fractions (PAF). Relative and absolute inequalities in all-cause mortality were more pronounced in Finland, Denmark, France, and Lithuania than in other populations, and the same countries (except France) also had the highest PAF values for all-cause mortality. The main contributing causes to these larger inequalities differed strongly between countries (e.g., cancer in France, all other causes in Denmark). Relative and absolute inequalities in CVD mortality were markedly lower in Southern European populations. We conclude that relative and absolute occupational class differences in all-cause and cause specific mortality have persisted into the early 2000s, although the magnitude differs strongly between populations. Comparisons with previous studies suggest that the relative gap in mortality between occupational classes has further widened in some Northern and Western European populations.

Widening socioeconomic differences in mortality among men aged 65 years and older in Germany

Background Although socioeconomic mortality differences in Germany are well documented, trends in group-specific mortality and differences between the eastern and the western parts of the country remain unexplored. Methods Population and death counts by level of lifetime earnings (1995–1996 to 2007–2008) and broad occupational groups (1995–1996 to 2003–2004) for men aged 65 years and older were obtained from the German Federal Pension Fund. Directly standardised mortality rates and life expectancy at age 65 were used as mortality measures. Results Mortality declined in all socioeconomic groups in eastern and western Germany and these declines tended to be larger in higher status groups. Relative socioeconomic differences in age-standardised mortality rates and in life expectancy at age 65 widened over time. Absolute differences widened over the majority of time periods. The widening was more pronounced in eastern Germany. Conclusions Widening socioeconomic mortality differences in Germany, especially in eastern Germany, show that population groups did not benefit equally from the improvements in survival. The results suggest that special efforts have to be taken in order to reduce mortality among people with lower socioeconomic status, especially in eastern Germany. Health equity should be considered a priority when planning policies, practices, and changes in the healthcare system and related sectors.

Lithuania mental health country profile

As a part of international mental health policy, programmes and services project, the ‘country profile’ instrument was used for assessment of mental health policy and services in the Republic of Lithuania. Analysis of contextual factors revealed high levels of social pathology (including violence, suicide and other self-destructive behaviour) with stigmatizing approaches by the general population to mentally disturbed persons and other vulnerable groups. Analysis of existing data about resources invested in the mental health care system raises questions for policymakers about the effectiveness of this traditional way of investment. The largest proportion of physical and human capital is concentrated in psychiatric institutions, with large numbers of beds, psychiatrists and increasing funding for medications, while other components of care—such as housing, psychosocial and vocational rehabilitation, community-based child mental health services—are not being developed. Statistical accounts keep the tradition of presenting processes as outcomes, while modern assessment of outcomes of services, programmes and policies are lacking. The findings from this country profile may be very useful in the development of modern mental health policies in the countries of Eastern and Central Europe, which have been deprived for decades from the opportunity to introduce evidence-based mental health policies and services.

Suicides among cancer patients in Lithuania: A population-based census-linked study

BACKGROUND This study aims to estimate suicide risk and its socio-demographic determinants among cancer patients in the country showing the highest suicide rates among developed countries. METHODS The study is based on a unique census-linked dataset based on the linkages between the records from death and cancer registers and the 2001 population census records. Standardized mortality ratios for suicide (SMRs) were calculated for patients diagnosed with cancer in Lithuania between April 6, 2001 and December 31, 2009, relative to suicide rates in the general population. RESULTS We found that the relative suicide risk was elevated for both males and females, with SMRs of 1.43 (95% CI 1.23-1.66) and 1.32 (95% CI 0.95-1.80), respectively. This relationship for females became statistically significant and stronger after excluding skin cancers. The highest suicide risks were observed at older ages and during the period shortly after the diagnosis. The groups showing an increased suicide risk include lower educated, non-married, and rural male patients. CONCLUSION The results of our study point to inadequacies of the health care system in dealing with mental health problems of cancer patients. Interventions allowing early detection of depression or suicidal ideation may help to prevent suicide among cancer patients in Lithuania.