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Purpose: To study the trends of smoking-attributable mortality among the low and high educated in consecutive birth cohorts in 11 European countries. Methods: Register-based mortality data were collected among adults aged 30 to 79 years in 11 European countries between 1971 and 2012. Smoking-attributable deaths were estimated indirectly from lung cancer mortality rates using the Preston-Glei-Wilmoth method. Rate ratios and rate differences among the low and high-educated were estimated and used to estimate the contribution of inequality in smoking-attributable mortality to inequality in total mortality. Results: In most countries, smoking-attributable mortality decreased in consecutive birth cohorts born between 1906 and 1961 among low- and high-educated men and high-educated women, but not among low-educated women among whom it increased. Relative educational inequalities in smoking-attributable mortality increased among both men and women with no signs of turning points. Absolute inequalities were stable among men but slightly increased among women. The contribution of inequality in smoking-attributable mortality to inequality in total mortality decreased in consecutive generations among men but increased among women. Conclusions: Smoking might become less important as a driver of inequalities in total mortality among men in the future. However, among women, smoking threatens to further widen inequalities in total mortality.

Socioeconomic inequalities in disability-free life expectancy (DFLE) exist across all European countries, yet the driving determinants of these differences are not completely known. We calculated the impact on educational inequalities in DFLE of equalizing the distribution of eight risk factors for mortality and disability using register-based mortality data and survey data from 15 European countries for individuals between 35 and 80 years old. From the selected risk factors, the ones that contribute the most to the educational inequalities in DFLE are low income, high body-weight, smoking (for men), and manual occupation of the father. Potentially large reductions in inequalities can be achieved in Eastern European countries, where educational inequalities in DFLE are also the largest.

Purpose: To study the trends of smoking-attributable mortality among the low and high educated in consecutive birth cohorts in 11 European countries. Methods: Register-based mortality data were collected among adults aged 30 to 79 years in 11 European countries between 1971 and 2012. Smoking-attributable deaths were estimated indirectly from lung cancer mortality rates using the Preston-Glei-Wilmoth method. Rate ratios and rate differences among the low and high-educated were estimated and used to estimate the contribution of inequality in smoking-attributable mortality to inequality in total mortality. Results: In most countries, smoking-attributable mortality decreased in consecutive birth cohorts born between 1906 and 1961 among low- and high-educated men and high-educated women, but not among low-educated women among whom it increased. Relative educational inequalities in smoking-attributable mortality increased among both men and women with no signs of turning points. Absolute inequalities were stable among men but slightly increased among women. The contribution of inequality in smoking-attributable mortality to inequality in total mortality decreased in consecutive generations among men but increased among women. Conclusions: Smoking might become less important as a driver of inequalities in total mortality among men in the future. However, among women, smoking threatens to further widen inequalities in total mortality.

Background Educational inequalities in health and mortality in European countries have often been studied in the context of welfare regimes or political systems. We argue that the healthcare system is the national level feature most directly linkable to mortality amenable to healthcare. In this article, we ask to what extent the strength of educational differences in mortality amenable to healthcare vary among European countries and between European healthcare system types. Methods This study uses data on mortality amenable to healthcare for 21 European populations, covering ages 35–79 and spanning from 1998 to 2006. ISCED education categories are used to calculate relative (RII) and absolute inequalities (SII) between the highest and lowest educated. The healthcare system typology is based on the latest available classification. Metaanalysis and ANOVA tests are used to see if and how they can explain between-country differences in inequalities and whether any healthcare system types have higher inequalities. Results All countries and healthcare system types exhibited relative and absolute educational inequalities in mortality amenable to healthcare. The low-supply and low performance mixed healthcare system type had the highest inequality point estimate for the male (RII = 3.57; SII = 414) and female (RII = 3.18; SII = 209) population, while the regulation-oriented public healthcare systems had the overall lowest (male RII = 1.78; male SII = 123; female RII = 1.86; female SII = 78.5). Due to data limitations, results were not robust enough to make substantial claims about typology differences. Conclusions This article aims at discussing possible mechanisms connecting healthcare systems, social position, and health. Results

BACKGROUND: Educational inequalities in health and mortality in European countries have often been studied in the context of welfare regimes or political systems. We argue that the healthcare system is the national level feature most directly linkable to mortality amenable to healthcare. In this article, we ask to what extent the strength of educational differences in mortality amenable to healthcare vary among European countries and between European healthcare system types. METHODS: This study uses data on mortality amenable to healthcare for 21 European populations, covering ages 35-79 and spanning from 1998 to 2006. ISCED education categories are used to calculate relative (RII

BACKGROUND: In many countries smoking rates have declined and obesity rates have increased, and social inequalities in each have varied over time. At the same time, mortality has declined in most high-income countries, but gaps by educational qualification persist-at least partially due to differential smoking and obesity distributions. This study uses a compass typology to simultaneously examine the magnitude and trends in educational inequalities across multiple countries in: a) smoking and obesity; b) smoking-related mortality and c) cause-specific mortality. METHODS: Smoking prevalence, obesity prevalence and cause-specific mortality rates (35-79 year olds by sex) in nine European countries and New Zealand were sourced from between 1980 and 2010. We calculated relative and absolute inequalities in prevalence and mortality (relative and slope indices of inequality, respectively RII, SII) by highest educational qualification. Countries were then plotted on a compass typology which simultaneously examines trends in the population average rates or odds on the x-axis, RII on the Y-axis, and contour lines depicting SII. FINDINGS: Smoking and obesity. Smoking prevalence in men decreased over time but relative inequalities increased. For women there were fewer declines in smoking prevalence and relative inequalities tended to increase. Obesity prevalence in men and women increased over time with a mixed picture of increasing absolute and sometimes relative inequalities. Absolute inequalities in obesity increased for men and women in Czech Republic, France, New Zealand, Norway, for women in Austria and Lithuania, and for men in Finland. Cause-specific mortality. Average rates of smoking-related mortality were generally stable or increasing for women, accompanied by increasing relative inequalities. For men, average rates were stable or decreasing, but relative inequalities increased over time. Cardiovascular disease, cancer, and external injury rates generally decreased

Socioeconomic inequalities in mortality are a challenge for public health around the world, but appear to be resistant to policy-making. We aimed to identify European countries which have been more successful than others in narrowing inequalities in mortality, and the factors associated with narrowing inequalities. We collected and harmonised mortality data by educational level in 15 European countries over the last 25 years, and quantified changes in inequalities in mortality using a range of measures capturing different perspectives on inequality (e.g., ‘relative’ and ‘absolute’ inequalities, inequalities in ‘attainment’ and ‘shortfall’). We determined which causes of death contributed to narrowing of inequalities, and conducted country- and period-fixed effects analyses to assess which country-level factors were associated with narrowing of inequalities in mortality. Mortality among the low educated has declined rapidly in all European countries, and a narrowing of absolute, but not relative inequalities was seen in many countries. Best performers were Austria, Italy (Turin) and Switzerland among men, and Spain (Barcelona), England and Wales, and Austria among women. Ischemic heart disease, smoking-related causes (men) and amenable causes often contributed to narrowing inequalities. Trends in income inequality, level of democracy and smoking were associated with widening inequalities, but rising health care expenditure was associated with narrowing inequalities. Trends in inequalities in mortality have not been as unfavourable as often claimed. Our results suggest that health care expansion has counteracted the inequalities widening effect of other influences.

Background Socioeconomic inequalities in longevity have been found in all European countries. We aimed to assess which determinants make the largest contribution to these inequalities. Methods We did an international comparative study of inequalities in risk factors for shorter life expectancy in Europe. We collected register-based mortality data and survey-based risk factor data from 15 European countries. We calculated partial life expectancies between the ages of 35 years and 80 years by education and gender and determined the effect on mortality of changing the prevalence of eight risk factors—father with a manual occupation, low income, few social contacts, smoking, high alcohol consumption, high bodyweight, low physical exercise, and low fruit and vegetable consumption—among people with a low level of education to that among people with a high level of education (upward levelling scenario), using population attributable fractions. Findings In all countries, a substantial gap existed in partial life expectancy between people with low and high levels of education, of 2·3–8·2 years among men and 0·6–4·5 years among women. The risk factors contributing most to the gap in life expectancy were smoking (19·8% among men and 18·9% among women), low income (9·7% and 13·4%), and high bodyweight (7·7% and 11·7%), but

Background We compared mortality inequalities by occupational class in Japan and South Korea with those in European countries, in order to determine whether patterns are similar. Methods National register-based data from Japan, South Korea and eight European countries (Finland, Denmark, England/Wales, France, Switzerland, Italy (Turin), Estonia, Lithuania) covering the period between 1990 and 2015 were collected and harmonised. We calculated age-standardised all-cause and cause-specific mortality among men aged 35–64 by occupational class and measured the magnitude of inequality with rate differences, rate ratios and the average inter-group difference. Results Clear gradients in mortality were found in all European countries throughout the study period: manual workers had 1.6–2.5 times higher mortality than upper non-manual workers. However, in the most recent time-period, upper non-manual workers had higher mortality than manual workers in Japan and South Korea. This pattern emerged as a result of a rise in mortality among the upper non-manual group in Japan during the late 1990s, and in South Korea during the late 2000s, due to rising mortality from cancer and external causes (including suicide), in addition to strong mortality declines among lower non-manual and manual workers. Conclusion Patterns of mortality by occupational class are remarkably different between European countries and Japan and South Korea. The recently observed patterns in the latter two countries may be related to a larger impact on the higher occupational classes of the economic crisis of the late 1990s and the late 2000s, respectively

Objectives: To assess to what extent educational differences in total life expectancy (TLE) and disability-free life expectancy (DFLE) could be reduced by improving fruit and vegetable consumption in ten Euro

The magnitude of socioeconomic inequalities in mortality differs importantly between countries, but these variations have not been satisfactorily explained. We explored the role of behavioral and structural determinants of these variations, by using a dataset covering 17 European countries in the period 1970–2010, and by conducting multilevel multivariate regression analyses. Our results suggest that between-country variations in inequalities in current mortality can partly be understood from variations in inequalities in smoking, excessive alcohol consumption, and poverty. Also, countries with higher national income, higher quality of government, higher social transfers, higher health care expenditure and more self-expression values have smaller inequalities in mortality. Finally, trends in behavioral risk factors, particularly smoking and excessive alcohol consumption, appear to partly explain variations in inequalities in mortality trends. This study shows that analyses of variations in health inequa

Objective: The aim of this paper is to empirically evaluate whether widening educational inequalities in mortality are related to the substantive shifts that have occurred in the educational distribution. Materials and methods: Data on education and mortality from 18 European populations across several decades were collected and harmonized as part of the Demetriq project. Using a fixed-effects approach to account for time trends and national variation in mortality, we formally test whether the magnitude of relative inequalities in mortality by education is associated with the gender and age-group specific proportion of high and low educated respectively. Results: The results suggest that in populations with larger proportions of high educated and smaller proportions of low educated, the excess mortality among intermediate and low educated is larger, all other things being equal. Conclusion: We conclude that the widening educational inequalities in mortality being observed in recent decades may in part be attributed to educational expansion.

Background: Socioeconomic inequalities in alcohol-related mortality have been documented in several European countries, but it is unknown whether the magnitude of these inequalities differs between countries and whether these inequalities increase or decrease over time. Methods and Findings: We collected and harmonized data on mortality from four alcohol-related causes (alcoholic psychosis, dependence, and abuse; alcoholic cardiomyopathy; alcoholic liver cirrhosis; and accidental poisoning by alcohol) by age, sex, education level, and occupational class in 20 European populations from 17 different countries, both for a recent period and for previous points in time, using data from mortality registers. Mortality was age-standardized using the European Standard Population, and measures for both relative and absolute inequality between low and high socioeconomic groups (as measured by educational level and occupational class) were calculated. Rates of alcohol-related mortality are higher in lower educational and occupational groups in all countries. Both relative and absolute inequalities are largest in Eastern Europe, and Finland and Denmark also have very large absolute inequalities in alcohol-related mortality. For example, for educational inequality among Finnish men, the relative index of inequality is 3.6 (95% CI 3.3–4.0) and the slope index of inequality is 112.5 (95% CI 106.2–118.8) deaths per 100,000 person-years. Over time, the relative inequality in alcohol-related mortality has increased in many countries, but the main change is a strong rise of absolute inequality in several countries in Eastern Europe (Hungary, Lithuania, Estonia) and Northern Europe (Finland, Denmark) because of a rapid rise in alcohol-related mortality in lower socioeconomic groups. In some of these countries, alcohol-related causes now account for 10% or more of the socioeconomic inequality in total mortality. Because our study relies on routinely collected underlying causes of death

Objectives: To evaluate educational inequalities in diabetes mortality in Europe in the 2000s, and to assess whether these inequalities differ between genders.Methods: Data were obtained from mortality registries covering 14 European countries. To determin

Background: Cause-of-death data linked to information on socioeconomic position form one of the most important sources of information about health inequalities in many countries. The proportion of deaths from ill-defined conditions is one of the indicators of the quality of cause-of-death data. We investigated educational differences in the use of ill-defined causes of death in official mortality statistics. Methods: Using age-standardized mortality rates from 16 European countries, we calculated the proportion of all deaths in each educational group that were classified as due to "Symptoms, signs and ill-defined conditions". We tested if this proportion differed across educational groups using Chi-square tests. Results: The proportion of ill-defined causes of death was lower than 6.5% among men and 4.5% among women in all European countries, without any clear geographical pattern. This proportion statistically significantly differed by educational groups in several countries with in most cases a higher proportion among less than secondary educated people compared with tertiary educated people. Conclusions: We found evidence for educational differences in the distribution of ill-defined causes of death. However, the differences between educational groups were small suggesting that socioeconomic inequalities in cause-specific mortality in Europe are not likely to be biased.

__Abstract__ Background: The Millennium Declaration in 2000 brought special global attention to HIV, tuberculosis, and malaria through the formulation of Millennium Development Goal (MDG) 6. The Global Burden of Disease 2013 study provides a consistent and comprehensive approach to disease estimation for between 1990 and 2013, and an opportunity to assess whether accelerated progress has occured since the Millennium Declaration. Methods: To estimate incidence and mortality for HIV, we used the UNAIDS Spectrum model appropriately modified based on a systematic review of available studies of mortality with and without antiretroviral therapy (ART). For concentrated epidemics, we calibrated Spectrum models to fit vital registration data corrected for misclassification of HIV deaths. In generalised epidemics, we minimised a loss function to select epidemic curves most consistent with prevalence data and demographic data for all-cause mortality. We analysed counterfactual scenarios for HIV to assess years of life saved through prevention of mother-to-child transmission (PMTCT) and ART. For tuberculosis, we analysed vital registration and verbal autopsy data to estimate mortality using cause of death ensemble modelling. We analysed data for corrected case-notifications, expert opinions on the case-detection rate, prevalence surveys, and estimated cause-specific mortality using Bayesian meta-regression to generate consistent trends in all parameters. We analysed malaria mortality and incidence using an updated cause of death database, a systematic analysis of verbal autopsy validation studies for malaria, and recent studies (2010-13) of incidence, drug resistance, and coverage of insecticide-treated bednets. Findings: Globally in 2013, there were 1·8 million new HIV infections (95% uncertainty interval 1·7 million to 2·1 million), 29·2 million prevalent HIV cases (28·1 to 31·7), and 1·3 million HIV deaths (1·3 to 1·5). At the peak of the epidemic in 2005, HIV caused 1·7 mil

Although higher education has been associated with lower mortality rates in many studies, the effect of potential improvements in educational distribution on future mortality levels is unknown. We therefore estimated the impact of projected increases in higher education on mortality

Background: Previous studies have reported large socioeconomic inequalities in mortality from conditions amenable to medical intervention, but it is unclear whether these can be attributed to inequalities in access or quality of health care, or to confounding influences such as inequalities in background risk of diseases. We therefore studied whether inequalities in mortality from conditions amenable to medical intervention vary between countries in patterns which differ from those observed for other (non-amenable) causes of death. More specifically, we hypothesized that, as compared to non-amenable causes, inequalities in mortality from amenable causes are more strongly associated with inequalities in health care use and less strongly with inequalities in common risk factors for disease such as smoking. Methods: Cause-specific mortality data for people aged 3074 years were obtained for 14 countries, and were analysed by calculating age-standardized mortality rates and relative risks comparing a lower with a higher educational group. Survey data on health care use and behavioural risk factors for people aged 3074 years were obtained for 12 countries, and were analysed by calculating age-and sex-adjusted odds ratios comparing a low with a higher educational group. Patterns of association were explored by calculating correlation coefficients. Results: In most countries and for most amenable causes of death substantial inequalities in mortality were observed, but inequalities in mortality from amenable causes did not vary between countries in patterns that are different from those seen for inequalities in non-amenable mortality. As compared to non-amenable causes, inequalities in mortality from amenable causes are not more strongly associated with inequalities in health care use. Inequalities in mortality from amenable causes are also not less strongly associated with common risk factors such as smoking. Conclusions: We did not find evidence that inequalities in mortal

Background: Studies of socioeconomic inequalities in mortality consistently point to higher death rates in lower socioeconomic groups. Yet how these between-group differences relate to the total variation in mortality risk between individuals is unknown.Methods: We used data assembled and harmonized as part of the Eurothine project, which includes census-based mortality data from 11 European countries. We matched this to national data from the Human Mortality Database and constructed life tables by gender and educational level. We measured variation in age at death using Theil's entropy index, and decomposed this measure into its between- and within-group components.Results: The least-educated groups lived between three and 15 years fewer than the highest-educated groups, the latter having a more similar age at death in all countries. Differences between educational groups contributed between 0.6% and 2.7% to total variation in age at death between individuals in Western European countries and between 1.2% and 10.9% in Central and Eastern European countries. Variation in age at death is larger and differs more between countries among the least-educated groups.Conclusions: At the individual level, many known and unknown factors are causing enormous variation in age at death, socioeconomic position being only one of them. Reducing variations in age at death among less-educated people by providing protection to the vulnerable may help to reduce inequalities in mortality between socioeconomic groups.

OBJECTIVE: To describe the magnitude of socioe conomic inequalities in tuberculosis (TB) mortality by level of education in male, female, urban and rural populations in several European countries. DESIGN: Data were obtained from the Eurothine Project, covering 16 populations between 1990 and 2003. Age- and sex-standardised mortality rates, the relative index of inequality and the slope index of inequality were used to assess educational inequalities. RESULTS: The number of TB deaths reported was 8530, with a death rate of 3 per 100 000 per year, of which 73% were males. Educational inequalities in TB mortality were present in all European populations. Inequalities in TB mortality were greater than in total mortality. Relative and absolute inequalities were large in Eastern European and Baltic countries but relatively small in Southern European countries and in Norway, Finland and Sweden. Inequalities in mortality were observed among both men and women, and in both rural and urban populations. CONCLUSIONS: Socio-economic inequalities in TB mortality exist in all European countries. Firm political commitment is required to reduce inequalities in the social determinants of TB incidence. Targeted public health measures are called for to improve access to treatment of vulnerable groups and thereby reduce TB mortality.

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. Copyright

Background: To study the association of socioeconomic and demographic indicators with ever initiating regular smoking and quitting smoking among ever regular smokers in Estonia in order to identify target groups for equity-oriented tobacco control policies. Methods: Data for 4277 individuals in the 25-64 age group come from three cross-sectional studies conducted in 2000, 2002 and 2004. Age-standardized prevalence rates and odds ratios with 95% confidence intervals were calculated. Results: High rates of ever initiation were observed for lower educated men and women after controlling for other socioeconomic indicators. This association was not observed for women above age 50. Independent, although weaker associations were found among men who were unemployed or with a low occupational status. Low cessation rates were observed among men who were unemployed, who had a lower occupational position or who had a low income. These associations remained after controlling for other socioeconomic variables. The effect of income became stronger in the older age groups among men. Rates of ever initiation and cessation also varied strongly in relationship to some demographic variables. The highest initiation rates were found among divorced women and among women living in the capital city. The lowest cessation rates were found among divorced women, and among Russian men. Conclusions: While educational level was the strongest predictor of ever initiating regular smoking, smoking cessation was related more directly to aspects of social disadvantage originating in adult life. To be effective, tobacco control interventions should not only target lower educated, but also those in material disadvantage.

OBJECTIVES: This study compared differences in total and cause-specific mortality by educational level among women with those among men in 7 countries: the United States, Finland, Norway, Italy, the Czech Republic, Hungary, and Estonia. METHODS: National data were obtained for the period ca. 1980 to ca. 1990. Age-adjusted rate ratios comparing a broad lower-educational group with a broad upper-educational group were calculated with Poisson regression analysis. RESULTS: Total mortality rate ratios among women ranged from 1.09 in the Czech Republic to 1.31 in the United States and Estonia. Higher mortality rates among lower-educated women were found for most causes of death, but not for neoplasms. Relative inequalities in total mortality tended to be smaller among women than among men. In the United States and Western Europe, but not in Central and Eastern Europe, this sex difference was largely due to differences between women and men in cause-of-death pattern. For specific causes of death, inequalities are usually larger among men. CONCLUSIONS: Further study of the interaction between socioeconomic factors, sex, and mortality may provide important clues to the explanation of inequalities in health.