Estimation of Socioeconomic Inequalities in Mortality in Japan Using National Census-linked Longitudinal Mortality Data.

BACKGROUND: We aimed to develop census-linked longitudinal mortality data for Japan and assess their validity as a new resource for estimating socioeconomic inequalities in health. METHODS: Using deterministic linkage, we identified, from national censuses for 2000 and 2010 and national death records, persons and deceased persons who had unique personal identifiers (generated using sex, birth year/month, address, and marital status). For the period 2010-2015, 1,537,337 Japanese men and women aged 30-79 years (1.9% in national census) were extracted to represent the sample population. This population was weighted to adjust for confounding factors. We estimated age-standardized mortality rates (ASMRs) by education level and occupational class. The slope index of inequality (SII) and relative index inequality (RII) by educational level were calculated as inequality measures. RESULTS: The reweighted sample population's mortality rates were somewhat higher than those of the complete registry, especially in younger age-groups and for external causes. All-cause ASMRs (per 100,000 person-years) for individuals aged 40-79 years with high, middle, and low education levels were 1,078 (95% confidence interval [CI], 1,051-1,105), 1,299 (95% CI, 1,279-1,320), and 1,670 (95% CI, 1,634-1,707) for men, and 561 (95% CI, 536-587), 601 (95% CI, 589-613), and 777 (95% CI, 745-808) for women, respectively, during 2010-2015. SII and RII by educational level increased among both sexes between 2000-2005 and 2010-2015, which indicates that mortality inequalities increased. CONCLUSION: The developed census-linked longitudinal mortality data provide new estimates of socioeconomic inequalities in Japan that can be triangulated with estimates obtained with other methods.

Socioeconomic inequalities in self-rated health in Japan, 32 European countries and the United States: an international comparative study.

AIMS: Japan is known as a country with low self-rated health despite high life expectancy. We compared socioeconomic inequalities in self-rated health in Japan with those in 32 European countries and the US using nationally representative samples. METHODS: We analysed individual data from the Comprehensive Survey of Living Conditions (Japan), the European Union Statistics on Income and Living Conditions, and the Behavioral Risk Factor Surveillance System (US) in 2016. We used ordered logistic regression models with four ordinal categories of self-rated health as an outcome, and educational level or occupational class as independent variables, controlling for age. RESULTS: In Japan, about half the population perceived their health as 'fair', which was much higher than in Europe (≈20-40%). The odds ratios of lower self-rated health among less educated men compared with more educated were 1.72 (95% confidence interval (CI) 1.61-1.85) in Japan, and ranged from 1.67 to 4.74 in Europe (pooled; 2.10 (95% CI 2.01-2.20)), and 6.65 (95% CI 6.22-7.12) in the US. The odds ratios of lower self-rated health among less educated women were 1.79 (95% CI 1.65-1.95) in Japan, and ranged from 1.89 to 5.30 in Europe (pooled; 2.43 (95% CI 2.33-2.54)), and 8.82 (95% CI 8.29-9.38) in the US. Socioeconomic inequalities were large when self-rated health was low for European countries, but Japan and the US did not follow the pattern. CONCLUSIONS: Japan has similar socioeconomic gradient patterns to European countries for self-rated health, and our findings revealed smaller socioeconomic inequalities in self-rated health in Japan compared with those in western countries.

Projecting years in good health between age 50-69 by education in the Netherlands until 2030 using several health indicators - an application in the context of a changing pension age.

OBJECTIVE: We investigate whether there are changes over time in years in good health people can expect to live above (surplus) or below (deficit) the pension age, by level of attained education, for the past (2006), present (2018) and future (2030) in the Netherlands. METHODS: We used regression analysis to estimate linear trends in prevalence of four health indicators: self-assessed health (SAH), the Organization for Economic Co-operation and Development (OECD) functional limitation indicator, the OECD indicator without hearing and seeing, and the activities-of-daily-living (ADL) disability indicator, for individuals between 50 and 69 years of age, by age category, gender and education using the Dutch National Health Survey (1989-2018). We combined these prevalence estimates with past and projected mortality data to obtain estimates of years lived in good health. We calculated how many years individuals are expected to live in good health above (surplus) or below (deficit) the pension age for the three points in time. The pension ages used were 65 years for 2006, 66 years for 2018 and 67.25 years for 2030. RESULTS: Both for low educated men and women, our analyses show an increasing deficit of years in good health relative to the pension age for most outcomes, particularly for the SAH and OECD indicator. For high educated we find a decreasing surplus of years lived in good health for all indicators with the exception of SAH. For women, absolute inequalities in the deficit or surplus of years in good health between low and high educated appear to be increasing over time. CONCLUSIONS: Socio-economic inequalities in trends of mortality and the prevalence of ill-health, combined with increasing statutory pension age, impact the low educated more adversely than the high educated. Policies are needed to mitigate the increasing deficit of years in good health relative to the pension age, particularly among the low educated.

The rise and fall of diseases: reflections on the history of population health in Europe since ca. 1700.

This essay explores the amazing phenomenon that in Europe since ca. 1700 most diseases have shown a pattern of 'rise-and-fall'. It argues that the rise of so many diseases indicates that their ultimate cause is not to be sought within the body, but in the interaction between humans and their environment. In their tireless pursuit of a better life, Europeans have constantly engaged in new activities which exposed them to new health risks, at a pace that evolution could not keep up with. Fortunately, most diseases have also declined again, mainly as a result of human interventions, in the form of public health interventions or improvements in medical care. The virtually continuous succession of diseases starting to fall in the 18th, 19th and 20th centuries suggests that the concept of an "epidemiological transition" has limited usefulness.

Widening Socioeconomic Inequalities in Smoking in Japan, 2001-2016.

BACKGROUND: Japan is one of the world's largest tobacco epidemic countries but few studies have focused on socioeconomic inequalities. We aimed to examine whether socioeconomic inequalities in smoking have reduced in Japan in recent times. METHODS: We analyzed data from the Comprehensive Survey of Living Conditions, a large nationally representative survey conducted every 3 years (n ≈ 700,000 per year) in Japan, during 2001-2016. Age-standardized smoking prevalence was computed based on occupational class and educational level. We calculated smoking prevalence difference (PD) and ratio (PR) of (a) manual workers versus upper non-manual workers and (b) low versus high educational level. The slope index of inequality (SII) and relative index inequality (RII) by educational level were used as inequality measures. RESULTS: Overall smoking prevalence (25-64 years) decreased from 56.0% to 38.4% among men and from 17.0% to 13.0% among women during 2001-2016. The PD between manual and upper non-manual workers (25-64 years) increased from 11.9% (95% confidence interval [CI], 11.0-12.9%) to 14.6% (95% CI, 13.5-15.6%) during 2001-2016. In 2016, smoking prevalence (25-64 years) for low, middle, and highly educated individuals were 57.8%, 43.9%, and 27.8% for men, and 34.7%, 15.9%, and 5.6% for women, respectively. SII and RII by educational level increased among both sexes. Larger socioeconomic differences in smoking prevalence were observed in younger generations, which suggests that socioeconomic inequalities in smoking evolve in a cohort pattern. CONCLUSIONS: Socioeconomic inequalities in smoking widened between 2001 and 2016 in Japan, which indicates that health inequalities will continue to exist in near future.

Trends and socioeconomic inequalities in self-rated health in Japan, 1986-2016.

INTRODUCTION: Despite having very high life expectancy, Japan has relatively poor self-rated health, compared to other high-income countries. We studied trends and socioeconomic inequalities in self-rated health in Japan using nationally representative data. METHODS: The Comprehensive Survey of Living Conditions was analyzed, every 3 years (n ≈ 0.6-0.8 million/year) from 1986 to 2016. Whereas previous studies dichotomized self-rated health as an outcome, we used four categories: very good, good, fair, and bad/very bad. Proportional odds ordinal logistic regression models are used, with ordinal scale self-rated health as an outcome, and age category, survey year and occupational class or educational level as independent variables. RESULTS: In 2016, the age-adjusted percentages for self-rated health categorized as very good, good, fair, and bad/very bad, were 24.0, 17.1, 48.7, and 10.2% among working-age men, and 21.6, 17.5, 49.4, and 11.5% among working-age women, respectively. With 1986 as the reference year, the odds ratios (ORs) of less good self-rated health were lowest in 1995 (0.69; 95% Confidence Interval [95% CI]: 0.66-0.71 of working-age men), and highest in 2010 (1.23 [95% CI: 1.19-1.27]). The ORs of male, lower non-manual workers (compared to upper non-manual) increased from 1.12 (95% CI: 1.07-1.17) in 2010 to 1.20 (95% CI: 1.15-1.26) in 2016. Between 2010 and 2016, the ORs of working-age men with middle and low levels of education (compared to a high level of education) increased from 1.22 (95% CI: 1.18-1.27) to 1.34 (95% CI: 1.29-1.38), and from 1.47 (95% CI: 1.39-1.56) to 1.75 (95% CI: 1.63-1.88), respectively. The ORs of working-age women with middle and low levels of education also increased from 1.22 (95% CI: 1.17-1.28) to 1.32 (95% CI: 1.26-1.37), and from 1.74 (95% CI: 1.61-1.88) to 2.03 (95% CI: 1.87-2.21) during the same period. CONCLUSION: Japan has the unique feature that approximately 50% of the survey respondents rated their self-rated health as fair, but with important variations over time and between socioeconomic groups. In-depth studies of the role of socioeconomic conditions may shed light on the reasons for the high prevalence of poor self-rated health in Japan.

Mixed evidence for the compression of morbidity hypothesis for smoking elimination-a systematic literature review.

BACKGROUND: There is debate around the composition of life years gained from smoking elimination. The aim of this study was to conduct a systematic review of the literature to synthesize existing evidence on the effect of smoking status on health expectancy and to examine whether smoking elimination leads to compression of morbidity. METHODS: Five databases were systematically searched for peer-reviewed articles. Studies that presented quantitative estimates of health expectancy for smokers and non-/never-smokers were eligible for inclusion. Studies were searched, selected and reviewed by two reviewers who extracted the relevant data and assessed the risk of bias of the included articles independently. RESULTS: The search identified 2491 unique records, whereof 20 articles were eligible for inclusion (including 26 cohorts). The indicators used to measure health included disability/activity limitations (n=9), health-related quality of life (EQ-5D) (n=2), weighted disabilities (n=1), self-rated health (n=9), chronic diseases (n=6), cardiovascular diseases (n=4) and cognitive impairment (n=1). Available evidence showed consistently that non-/never-smokers experience more healthy life years throughout their lives than smokers. Findings were inconsistent on the effect of smoking on the absolute number of unhealthy life years. Findings concerning the time proportionally spent unhealthy were less heterogeneous: nearly all included articles reported that non-/never-smokers experience relatively less unhealthy life years (e.g. relative compression of morbidity). CONCLUSIONS: Support for the relative compression of morbidity due to smoking elimination was evident. Further research is needed into the absolute compression of morbidity hypothesis since current evidence is mixed, and methodology of studies needs to be harmonized.

Determinants of inequalities in years with disability: an international-comparative study.

BACKGROUND: Persons with a lower socioeconomic position spend more years with disability, despite their shorter life expectancy, but it is unknown what the important determinants are. This study aimed to quantify the contribution to educational inequalities in years with disability of eight risk factors: father's manual occupation, low income, few social contacts, smoking, high alcohol consumption, high body-weight, low physical exercise and low fruit and vegetable consumption. METHODS: We collected register-based mortality and survey-based disability and risk factor data from 15 European countries covering the period 2010-14 for most countries. We calculated years with disability between the ages of 35 and 80 by education and gender using the Sullivan method, and determined the hypothetical effect of changing the prevalence of each risk factor to the prevalence observed among high educated ('upward levelling scenario'), using Population Attributable Fractions. RESULTS: Years with disability among low educated were higher than among high educated, with a difference of 4.9 years among men and 5.5 years among women for all countries combined. Most risk factors were more prevalent among low educated. We found the largest contributions to inequalities in years with disability for low income (men: 1.0 year; women: 1.4 year), high body-weight (men: 0.6 year; women: 1.2 year) and father's manual occupation (men: 0.7 year; women: 0.9 year), but contributions differed by country. The contribution of smoking was relatively small. CONCLUSIONS: Disadvantages in material circumstances (low income), circumstances during childhood (father's manual occupation) and high body-weight contribute to inequalities in years with disability.

Trends in health inequalities in 27 European countries.

Unfavorable health trends among the lowly educated have recently been reported from the United States. We analyzed health trends by education in European countries, paying particular attention to the possibility of recent trend interruptions, including interruptions related to the impact of the 2008 financial crisis. We collected and harmonized data on mortality from ca 1980 to ca 2014 for 17 countries covering 9.8 million deaths and data on self-reported morbidity from ca 2002 to ca 2014 for 27 countries covering 350,000 survey respondents. We used interrupted time-series analyses to study changes over time and country-fixed effects analyses to study the impact of crisis-related economic conditions on health outcomes. Recent trends were more favorable than in previous decades, particularly in Eastern Europe, where mortality started to decline among lowly educated men and where the decline in less-than-good self-assessed health accelerated, resulting in some narrowing of health inequalities. In Western Europe, mortality has continued to decline among the lowly and highly educated, and although the decline of less-than-good self-assessed health slowed in countries severely hit by the financial crisis, this affected lowly and highly educated equally. Crisis-related economic conditions were not associated with widening health inequalities. Our results show that the unfavorable trends observed in the United States are not found in Europe. There has also been no discernible short-term impact of the crisis on health inequalities at the population level. Both findings suggest that European countries have been successful in avoiding an aggravation of health inequalities.

Differences in life expectancy between four Western countries and their Caribbean dependencies, 1980-2014.

BACKGROUND: In the Caribbean, life expectancy in politically independent territories has increasingly diverged from that of territories that remained affiliated to their former colonizers. Because these affiliated territories differ in degree of political independence, they are not all governed in the same way. We assessed whether differences in life expectancy trends between Caribbean dependencies and their Western administrators were related to their degree of political independence, and which causes of death contributed to divergence or convergence in life expectancy. METHODS: Analysis of age-standardized death rates and decomposition of life expectancy differences between France, the Netherlands, UK, USA and their Caribbean dependencies by age and cause-of-death during the period 1980-2014. RESULTS: Life expectancy differences between Western countries and their dependencies have generally increased for men and narrowed for women, but trends have been much more favorable in the French- than in the Dutch-administered territories. The strongest contributions to widening gaps in life expectancy between Western countries and their dependencies were from mortality from cardiovascular diseases (ischemic heart disease) and external causes (homicide and traffic accidents). CONCLUSION: Dependencies with a stronger political affiliation to a Western country experienced more favorable life expectancy developments than dependencies that had more autonomy during the 1980-2014 period. The underlying mortality differences with Western countries are largely comparable among Caribbean territories but differ in magnitude, most notably for cardiovascular disease and external causes. This suggests that increases in a territory's political autonomy impairs the diffusion of new knowledge and techniques, and/or reduces government's effectiveness in implementing policies.

How does cultural capital keep you thin? Exploring unique aspects of cultural class that link social advantage to lower body mass index.

A widely used indicator for cultural class is strongly related to a lower body mass index (BMI): cultural capital measured as 'highbrow' taste. This study's objective was to theorise and measure aspects of cultural class that are more plausibly linked to low BMI, and subsequently explore their relevance. Building on Bourdieusian theory we derive four of those aspects: 'refinement' (valuing form and appearance over function and substance), 'asceticism' (self-imposed constraints), 'diversity' (appreciation of variety in and of itself) and 'reflexivity' (reflexive deliberation and internal dialogue). Using standardised interviews with 597 participants in the Dutch GLOBE study in 2016, we subsequently demonstrate: (i) newly developed survey items can reliably measure four aspects of cultural class: 'asceticism', 'general refinement', 'food refinement' and 'reflexivity' (Cronbach's alphas between 0.67-0.77); (ii) embodied/objectified cultural capital (i.e. 'highbrow' taste) was positively associated with general refinement, food refinement and reflexivity, whereas institutionalised cultural capital (i.e. education) was positively associated with asceticism and reflexivity; (iii) asceticism, general refinement, reflexivity, but not food refinement, were associated with a lower BMI; (iv) asceticism, general refinement and reflexivity together accounted for 52% of the association between embodied/objectified cultural capital and BMI, and 38% of the association between institutionalised cultural capital and BMI.

Contribution of amenable mortality to life expectancy differences between the Dutch Caribbean islands of Aruba and Curaçao and the Netherlands.

OBJECTIVE: To identify specific health care areas whose optimization could improve population health in the Dutch Caribbean islands of Aruba and Curaçao. METHODS: Comparative observational study using mortality and population data of the Dutch Caribbean islands and the Netherlands. Mortality trends were calculated, then analyzed with Joinpoint software, for the period 1988-2014. Life expectancies were computed using abridged life tables for the most recent available data of all territories (2005-2007). Life expectancy differences between the Dutch Caribbean and the Netherlands were decomposed into cause-specific contributions using Arriaga's method. RESULTS: During the period 1988-2014, levels of amenable mortality have been consistently higher in Aruba and Curaçao than in the Netherlands. For Aruba, the gap in amenable mortality with the Netherlands did not significantly change during the study period, while it widened for Curaçao. If mortality from amenable causes were reduced to similar levels as in the Netherlands, men and women in Aruba would have added, respectively, 1.19 years and 0.72 years to their life expectancies during the period 2005-2007. In Curaçao, this would be 2.06 years and 2.33 years. The largest cause-specific contributions were found for circulatory diseases, breast cancer, perinatal causes, and nephritis/nephrosis (these last two causes solely in Curaçao). CONCLUSIONS: Improvements in health care services related to circulatory diseases, breast cancer, perinatal deaths, and nephritis/nephrosis in the Dutch Caribbean could substantially contribute to reducing the gap in life expectancy with the Netherlands. Based on our study, we recommend more in-depth studies to identify the specific interventions and resources needed to optimize the underlying health care areas.

Health Policy Performance in 16 Caribbean States, 2010-2015.

OBJECTIVES: To determine whether Caribbean states vary in health policy performance in 11 different areas; to explore the association with sociodemographic, economical, and governance determinants; and to estimate the potential health gains of "best-practice" health policies. METHODS: We selected 50 indicators that included data on mortality (latest available, 2010-2015), intermediate outcomes, and policy implementation to calculate a state's health policy performance score. We related this score to country characteristics and calculated the potential number of avoidable deaths if the age-specific mortality rates of best-performer Martinique applied in all states. RESULTS: We found large differences in health policy performance among Caribbean states. Martinique, Cuba, and Guadeloupe had the highest performance scores, and Guyana, Belize, and Suriname the lowest. Political affiliation, religious fractionalization, corruption, national income, and population density were associated with health policy performance. If the mortality rates of Martinique applied to all Caribbean states, an overall mortality reduction of 12% would be achieved. CONCLUSIONS: Differences in health outcomes between Caribbean states are partly attributable to variations in health policy implementation. Our results suggest that many deaths can be prevented if Caribbean governments adopt best-practice policies.

Progress against inequalities in mortality: register-based study of 15 European countries between 1990 and 2015.

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.

Socioeconomic inequalities in disability in Europe: contribution of behavioral, work-related and living conditions.

BACKGROUND: Previous studies have shown the existence of social inequalities in disability in many European countries. However, it is not clear what factors are associated with these inequalities. The aim of this study was to assess the contribution of behavioral factors, work-related factors and living conditions to educational inequalities in disability. METHODS: We pooled data from the seventh wave of the European Social Survey (2014) which included self-reported disability measured with the Global Activity Limitations Indicator for 19 European countries. We used multivariate logistic regression to determine the contributions of behavioral factors, work-related and living conditions to educational inequalities in disability among respondents aged 30-79. RESULTS: We found that adjusting simultaneously for three groups of determinants (behavioral, work-related and living conditions) reduces the greatest proportion of inequalities in disability in both men and women, in a range >70%. Each group of determinants contributes substantially to explain inequalities in disability. CONCLUSIONS: Inequalities in disability are a major challenge for public health in most European countries. Our findings suggest that these inequalities can be reduced by diminishing inequalities in exposure to well-known health determinants.

[Death is a respecter of persons : 30 years of research comparing European countries regarding social inequality in mortality]. / Vor dem Tod sind alle ungleich : 30 Jahre Forschung zu Mortalitätsunterschieden nach Sozialstatus im europäischen Ländervergleich.

BACKGROUND: In 1989 the first international comparisons of mortality differences according to educational level and occupational status were published. A few years later systematic comparisons between European countries were initiated at the Erasmus University in Rotterdam. This became a trigger for several European Union (EU)-funded collaboration programs scrutinizing social inequalities in health. The collaboration revealed substantial differences in mortality within and between European populations. OBJECTIVE: This article provides a synthesis of the most important research results over the past 30 years and also identifies existing research gaps and potentials. MATERIAL AND METHODS: Descriptive summary of research results comparing European countries regarding male and female all-cause and cause-specific mortality according to educational level and occupational status. RESULTS: In all European populations analyzed there was a consistent gradient with substantial and in part increasing advantages for higher socioeconomic status groups. There is, however, substantial variation between individual countries. This also applies to trends and cause of death-specific analyses. While relative differences have increased in virtually all populations, absolute differences have often decreased in many populations. Among women and in higher ages the relative differences were smaller. Within Europe, the southern countries had the smallest and the eastern countries the largest gradients. Tobacco and alcohol-related diseases had an especially noteworthy impact on trends and gradients. CONCLUSION: The evidence for social health inequalities and their determinants has substantially improved during the past 30 years; however, there remains substantial potential for future research questions, for example concerning the contribution of the different phases of life to healthy aging.

Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1·7 million men and women.

BACKGROUND: In 2011, WHO member states signed up to the 25 × 25 initiative, a plan to cut mortality due to non-communicable diseases by 25% by 2025. However, socioeconomic factors influencing non-communicable diseases have not been included in the plan. In this study, we aimed to compare the contribution of socioeconomic status to mortality and years-of-life-lost with that of the 25 × 25 conventional risk factors. METHODS: We did a multicohort study and meta-analysis with individual-level data from 48 independent prospective cohort studies with information about socioeconomic status, indexed by occupational position, 25 × 25 risk factors (high alcohol intake, physical inactivity, current smoking, hypertension, diabetes, and obesity), and mortality, for a total population of 1 751 479 (54% women) from seven high-income WHO member countries. We estimated the association of socioeconomic status and the 25 × 25 risk factors with all-cause mortality and cause-specific mortality by calculating minimally adjusted and mutually adjusted hazard ratios [HR] and 95% CIs. We also estimated the population attributable fraction and the years of life lost due to suboptimal risk factors. FINDINGS: During 26·6 million person-years at risk (mean follow-up 13·3 years [SD 6·4 years]), 310 277 participants died. HR for the 25 × 25 risk factors and mortality varied between 1·04 (95% CI 0·98-1·11) for obesity in men and 2 ·17 (2·06-2·29) for current smoking in men. Participants with low socioeconomic status had greater mortality compared with those with high socioeconomic status (HR 1·42, 95% CI 1·38-1·45 for men; 1·34, 1·28-1·39 for women); this association remained significant in mutually adjusted models that included the 25 × 25 factors (HR 1·26, 1·21-1·32, men and women combined). The population attributable fraction was highest for smoking, followed by physical inactivity then socioeconomic status. Low socioeconomic status was associated with a 2·1-year reduction in life expectancy between ages 40 and 85 years, the corresponding years-of-life-lost were 0·5 years for high alcohol intake, 0·7 years for obesity, 3·9 years for diabetes, 1·6 years for hypertension, 2·4 years for physical inactivity, and 4·8 years for current smoking. INTERPRETATION: Socioeconomic circumstances, in addition to the 25 × 25 factors, should be targeted by local and global health strategies and health risk surveillance to reduce mortality. FUNDING: European Commission, Swiss State Secretariat for Education, Swiss National Science Foundation, the Medical Research Council, NordForsk, Portuguese Foundation for Science and Technology.

Socioeconomic inequalities in suicide in Europe: the widening gap.

BACKGROUND: Suicide has been decreasing over the past decade. However, we do not know whether socioeconomic inequality in suicide has been decreasing as well.AimsWe assessed recent trends in socioeconomic inequalities in suicide in 15 European populations. METHOD: The DEMETRIQ study collected and harmonised register-based data on suicide mortality follow-up of population censuses, from 1991 and 2001, in European populations aged 35-79. Absolute and relative inequalities of suicide according to education were computed on more than 300 million person-years. RESULTS: In the 1990s, people in the lowest educational group had 1.82 times more suicides than those in the highest group. In the 2000s, this ratio increased to 2.12. Among men, absolute and relative inequalities were substantial in both periods and generally did not decrease over time, whereas among women inequalities were absent in the first period and emerged in the second. CONCLUSIONS: The World Health Organization (WHO) plan for 'Fair opportunity of mental wellbeing' is not likely to be met.Declaration of interestNone.

What's the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality.

BACKGROUND: Material and behavioural factors play an important role in explaining educational inequalities in mortality, but gender differences in these contributions have received little attention thus far. We examined the contribution of a range of possible mediators to relative educational inequalities in mortality for men and women separately. METHODS: Baseline data (1991) of men and women aged 25 to 74 years participating in the prospective Dutch GLOBE study were linked to almost 23 years of mortality follow-up from Dutch registry data (6099 men and 6935 women). Cox proportional hazard models were used to calculate hazard ratios with 95% confidence intervals, and to investigate the contribution of material (financial difficulties, housing tenure, health insurance), employment-related (type of employment, occupational class of the breadwinner), behavioural (alcohol consumption, smoking, leisure and sports physical activity, body mass index) and family-related factors (marital status, living arrangement, number of children) to educational inequalities in all-cause and cause-specific mortality, i.e. mortality from cancer, cardiovascular disease, other diseases and external causes. RESULTS: Educational gradients in mortality were found for both men and women. All factors together explained 62% of educational inequalities in mortality for lowest educated men, and 71% for lowest educated women. Yet, type of employment contributed substantially more to the explanation of educational inequalities in all-cause mortality for men (29%) than for women (- 7%), whereas the breadwinner's occupational class contributed more for women (41%) than for men (7%). Material factors and employment-related factors contributed more to inequalities in mortality from cardiovascular disease for men than for women, but they explained more of the inequalities in cancer mortality for women than for men. CONCLUSIONS: Gender differences in the contribution of employment-related factors to the explanation of educational inequalities in all-cause mortality were found, but not of material, behavioural or family-related factors. A full understanding of educational inequalities in mortality benefits from a gender perspective, particularly when considering employment-related factors.