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Socioeconomic status (SES) and health during childhood have been consistently observed to be associated with health in old age in many studies. However, the exact mechanisms behind these two associations have not yet been fully understood. The key challenge is to understand how childhood SES and health are associated. Furthermore, data on childhood factors and life course mediators are sometimes unavailable, limiting potential analyses. Using SHARELIFE data (N = 17230) we measure childhood SES and health circumstances, and examine their associations with old age health and their possible pathways via education, adult SES, behavioural risks, and labour market deprivation. We employ structural equation modelling to examine the mechanism of the long lasting impact of childhood SES and health on later life health, and how mediators partly contribute to these associations. The results show that childhood SES is substantially associated with old age health, albeit almost fully mediated by education and adult SES. Childhood health and behavioural risks have a strong effect on old age health, but they do not mediate the association between childhood SES and old age health. Childhood health in contrast retains a strong association with old age health after taking adulthood characteristics into account. This paper discusses the notion of the ‘long arm of childhood’, and concludes that it is a lengthy, mediated, incremental progression rather than a direct effect. Policies should certainly focus on childhood, especially when it comes to addressing childhood health conditions, but our results suggest other important entry points for improving old age health when it comes to socioeconomic determinants. [ABSTRACT FROM AUTHOR]

Background: Over the past decades, both health inequalities and income inequalities have been increasing in many European countries, but it is unknown whether and how these trends are related. We test the hypothesis that trends in health inequalities and trends in income inequalities are related, i.e. that countries with a stronger increase in income inequalities have also experienced a stronger increase in health inequalities. Methods: We collected trend data on all-cause and cause-specific mortality, as well as on the household income of people aged 35-79, for Belgium, Denmark, England & Wales, France, Slovenia, and Switzerland. We calculated absolute and relative differences in mortality and income between low- and high-educated people for several time points in the 1990s and 2000s. We used fixed-effects panel regression models to see if changes in income inequality predicted changes in mortality inequality. Results: The general trend in income inequality between high- and low-educated people in the six countries is increasing, while the mortality differences between educational groups show diverse trends, with absolute differences mostly decreasing and relative differences increasing in some countries but not in others. We found no association between trends in income inequalities and trends in inequalities in all-cause mortality, and trends in mortality inequalities did not improve when adjusted for rising income inequalities. This result held for absolute as well as for relative inequalities. A cause-specific analysis revealed some association between income inequality and mortality inequality for deaths from external causes, and to some extent also from cardiovascular diseases, but without statistical significance. Conclusions: We find no support for the hypothesis that increasing income inequality explains increasing health inequalities. Possible explanations are that other factors are more important mediators of the effect of education on health, or more simply that income is not an important determinant of mortality in this European context of high-income countries. This study contributes to the discussion on income inequality as entry point to tackle health inequalities. More research is needed to test the common and plausible assumption that increasing income inequality leads to more health inequality, and that one needs to act against the former to avoid the latter. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

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 in European populations. We used mortality and population data according to educational level from 21 European populations and developed counterfactual scenarios. The first scenario represented the improvement in the future distribution of educational attainment as expected on the basis of an assumption of cohort replacement. We estimated the effect of this counterfactual scenario on mortality with a 10-15-year time horizon among men and women aged 30-79 years using a specially developed tool based on population attributable fractions (PAF). We compared this with a second, upward levelling scenario in which everyone has obtained tertiary education. The reduction of mortality in the cohort replacement scenario ranged from 1.9 to 10.1% for men and from 1.7 to 9.0% for women. The reduction of mortality in the upward levelling scenario ranged from 22.0 to 57.0% for men and from 9.6 to 50.0% for women. The cohort replacement scenario was estimated to achieve only part (4-25% (men) and 10-31% (women)) of the potential mortality decrease seen in the upward levelling scenario. We concluded that the effect of on-going improvements in educational attainment on average mortality in the population differs across Europe, and can be substantial. Further investments in education may have important positive side-effects on population health. [ABSTRACT FROM AUTHOR]

Aims: To explore inequalities in total mortality between small areas of 16 European cities for men and women, as well as to analyse the relationship between these geographical inequalities and their socioeconomic indicators. Methods: A cross-sectional ecological design was used to analyse small areas in 16 European cities (26,229,104 inhabitants). Most cities had mortality data for a period between 2000 and 2008 and population size data for the same period. Socioeconomic indicators included an index of socioeconomic deprivation, unemployment, and educational level. We estimated standardised mortality ratios and controlled for their variability using Bayesian models. We estimated relative risk of mortality and excess number of deaths according to socioeconomic indicators. Results: We observed a consistent pattern of inequality in mortality in almost all cities, with mortality increasing in parallel with socioeconomic deprivation. Socioeconomic inequalities in mortality were more pronounced for men than women, and relative inequalities were greater in Eastern and Northern European cities, and lower in some Western (men) and Southern (women) European cities. The pattern of excess number of deaths was slightly different, with greater inequality in some Western and Northern European cities and also in Budapest, and lower among women in Madrid and Barcelona. Conclusions: In this study, we report a consistent pattern of socioeconomic inequalities in mortality in 16 European cities. Future studies should further explore specific causes of death, in order to determine whether the general pattern observed is consistent for each cause of death. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

Link and Phelan have proposed to explain the persistence of health inequalities from the fact that socioeconomic status is a “fundamental cause” which embodies an array of resources that can be used to avoid disease risks no matter what mechanisms are relevant at any given time. To test this theory we compared the magnitude of inequalities in mortality between more and less preventable causes of death in 19 European populations, and assessed whether inequalities in mortality from preventable causes are larger in countries with larger resource inequalities. We collected and harmonized mortality data by educational level on 19 national and regional populations from 16 European countries in the first decade of the 21st century. We calculated age-adjusted Relative Risks of mortality among men and women aged 30–79 for 24 causes of death, which were classified into four groups: amenable to behavior change, amenable to medical intervention, amenable to injury prevention, and non-preventable. Although an overwhelming majority of Relative Risks indicate higher mortality risks among the lower educated, the strength of the education–mortality relation is highly variable between causes of death and populations. Inequalities in mortality are generally larger for causes amenable to behavior change, medical intervention and injury prevention than for non-preventable causes. The contrast between preventable and non-preventable causes is large for causes amenable to behavior change, but absent for causes amenable to injury prevention among women. The contrast between preventable and non-preventable causes is larger in Central & Eastern Europe, where resource inequalities are substantial, than in the Nordic countries and continental Europe, where resource inequalities are relatively small, but they are absent or small in Southern Europe, where resource inequalities are also large. In conclusion, our results provide some further support for the theory of “fundamental causes”. However, the absence of larger inequalities for preventable causes in Southern Europe and for injury mortality among women indicate that further empirical and theoretical analysis is necessary to understand when and why the additional resources that a higher socioeconomic status provides, do and do not protect against prevailing health risks. [ABSTRACT FROM AUTHOR]