Inequalities In All-cause Mortality Research Articles

Education and mortality in three Eastern European populations: findings from the PrivMort retrospective cohort study.

The aim of the study is 2-fold. Firstly, it attempts to investigate the potential impact of major political and economic changes on inequalities in all-cause mortality among men and women with different levels of education in three Eastern European countries. Secondly, to identify changes in contribution of smoking and drinking to educational differences in all-cause mortality. Study covers the period from 1982 to 2013. Data were collected in 2013-14 as a part of the PrivMort retrospective cohort study. Participants in Russia, Belarus and Hungary provided information on their educational attainment, health-related behaviors and vital statistics of their close relatives (N = 179 691). Odds ratios for mortality and relative indices of inequality (RII) were estimated for individuals aged 20-65 years, stratifying by three levels of educational attainment: higher, secondary and less than secondary education. Those in lower educational groups were significantly more likely to die, through most time periods and sub-groups. The RII increased over time in all countries and both genders, except for Hungarian men. Alcohol consumption and smoking have increasingly contributed to educational inequalities in mortality during this period. Educational inequalities in mortality in these Eastern European countries have increased during recent decades. Smoking and alcohol consumption, two major health-related behaviors, made a significant contribution to these increases in inequality.

What\u2019s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality

BackgroundMaterial 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.MethodsBaseline 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.ResultsEducational 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.ConclusionsGender 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.

Repeatedly measured material and behavioral factors changed the explanation of socioeconomic inequalities in all-cause mortality

ObjectivesWe examined whether using repeatedly measured material and behavioral factors contributed differently to socioeconomic inequalities in all-cause mortality compared to one baseline measurement. Study Design and SettingData from the Dutch prospective GLOBE cohort were linked to mortality register data (1991–2013; N = 4,851). Socioeconomic position was measured at baseline by educational level and occupation. Material factors (financial difficulties, housing tenure, health insurance) and behavioral factors (smoking, leisure time physical activity, sports participation, and body mass index) were self-reported in 1991, 1997, and 2004. Cox proportional hazards regression and bootstrap methods were used to examine the contribution of baseline-only and time-varying risk factors to socioeconomic inequalities in mortality. ResultsMen and women in the lowest educational and occupational groups were at an increased risk of dying compared to the highest groups. The contribution of material factors to socioeconomic inequalities in mortality was smaller when multiple instead of baseline-only measurements were used (25%–65% vs. 49%–93%). The contribution of behavioral factors was larger when multiple measurements were used (39%–51% vs. 19%–40%). ConclusionInclusion of time-dependent risk factors contributes to understanding socioeconomic inequalities in mortality, but careful examination of the underlying mechanisms and suitability of the model is required.

Changing socioeconomic inequalities in cancer incidence and mortality: Cohort study with 54 million person-years follow-up 1981-2011.

Cancer is increasingly responsible for the mortality gap between high and low socioeconomic position groups in high-income countries. This study investigates which cancers are contributing more to socioeconomic gaps in mortality and how this changes over time.New Zealand census data from 1981, 1986, 1991, 1996, 2001 and 2006, were linked to three to five years of subsequent mortality and cancer registrations, resulting in 54 and 42 million years of follow-up cancer incidence and mortality, respectively. Age- and ethnicity-standardised cancer mortality rates and the slope index of inequality (SII) by income were calculated.The contribution of cancer to absolute inequalities (SII) in mortality increased from 16 to 27% for men and from 12 to 31% for women from 1981-84 to 2006-11, peaking in 1991-94 for men and in 1996-99 for women and then levelling off, parallel to peaks in lung cancer inequalities. Lung cancer was the largest driver of cancer inequality trends (49% of the cancer mortality gap in 1981-84 to 33% in 2006-11 for men and 32 to 33% for women) followed by colorectal cancer in men (2 to 11%) and breast cancer in women (declining from 44 to 13%). Women in the lowest income quintile experienced no decline in cancer mortality.The contribution of cancer to income inequalities in all-cause mortality has expanded in this high-income country. Action to address socioeconomic inequalities should prioritise equitable tobacco control, obesity control and improved access to cancer screening, early diagnosis and high quality treatment for those with the lowest incomes.

Long-term trends of inequalities in mortality in 6 European countries

ObjectivesWe aimed to assess whether trends in inequalities in mortality during the period 1970–2010 differed between Finland, Norway, England and Wales, France, Italy (Turin) and Hungary.MethodsTotal and cause-specific mortality data by educational level and, if available, occupational class were collected and harmonized. Both relative and absolute measures of inequality in mortality were calculated.ResultsIn all countries except Hungary, all-cause mortality declined strongly over time in all socioeconomic groups. Relative inequalities in all-cause mortality generally increased, but more so in Hungary and Norway than elsewhere. Absolute inequalities often narrowed, but went up in Hungary and Norway. As a result of these trends, Hungary (where inequalities in mortality where almost absent in the 1970s) and Norway (where inequalities in the 1970s were among the smallest of the six countries in this study) now have larger inequalities in mortality than the other four countries.ConclusionsWhile some countries have experienced dramatic setbacks, others have made substantial progress in reducing inequalities in mortality.

Trends in socioeconomic inequalities in mortality in small areas of 33 Spanish cities.

BackgroundIn Spain, several ecological studies have analyzed trends in socioeconomic inequalities in mortality from all causes in urban areas over time. However, the results of these studies are quite heterogeneous finding, in general, that inequalities decreased, or remained stable. Therefore, the objectives of this study are: (1) to identify trends in geographical inequalities in all-cause mortality in the census tracts of 33 Spanish cities between the two periods 1996–1998 and 2005–2007; (2) to analyse trends in the relationship between these geographical inequalities and socioeconomic deprivation; and (3) to obtain an overall measure which summarises the relationship found in each one of the cities and to analyse its variation over time.MethodsEcological study of trends with 2 cross-sectional cuts, corresponding to two periods of analysis: 1996–1998 and 2005–2007. Units of analysis were census tracts of the 33 Spanish cities. A deprivation index calculated for each census tracts in all cities was included as a covariate. A Bayesian hierarchical model was used to estimate smoothed Standardized Mortality Ratios (sSMR) by each census tract and period. The geographical distribution of these sSMR was represented using maps of septiles. In addition, two different Bayesian hierarchical models were used to measure the association between all-cause mortality and the deprivation index in each city and period, and by sex: (1) including the association as a fixed effect for each city; (2) including the association as random effects. In both models the data spatial structure can be controlled within each city. The association in each city was measured using relative risks (RR) and their 95 % credible intervals (95 % CI).ResultsFor most cities and in both sexes, mortality rates decline over time. For women, the mortality and deprivation patterns are similar in the first period, while in the second they are different for most cities. For men, RRs remain stable over time in 29 cities, in 3 diminish and in 1 increase. For women, in 30 cities, a non-significant change over time in RR is observed. However, in 4 cities RR diminishes. In overall terms, inequalities decrease (with a probability of 0.9) in both men (RR = 1.13, 95 % CI = 1.12–1.15 in the 1st period; RR = 1.11, 95 % CI = 1.09–1.13 in the 2nd period) and women (RR = 1.07, 95 % CI = 1.05–1.08 in the 1st period; RR = 1.04, 95 % CI = 1.02–1.06 in the 2nd period).ConclusionsIn the future, it is important to conduct further trend studies, allowing to monitoring trends in socioeconomic inequalities in mortality and to identify (among other things) temporal factors that may influence these inequalities.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-3190-y) contains supplementary material, which is available to authorized users.

The impact of increasing income inequalities on educational inequalities in mortality - An analysis of six European countries.

BackgroundOver 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.MethodsWe 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.ResultsThe 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.ConclusionsWe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12939-016-0390-0) contains supplementary material, which is available to authorized users.

Trends in socioeconomic inequalities in self-assessed health in 17 European countries between 1990 and 2010

BackgroundBetween the 1990s and 2000s, relative inequalities in all-cause mortality increased, whereas absolute inequalities decreased in many European countries. Whether similar trends can be observed for inequalities in other health...

Decreasing educational differences in mortality over 40 years: evidence from the Turin Longitudinal Study (Italy)

BackgroundRecent studies suggest that inequalities in premature mortality have continued to rise over the last decade in most European countries, but not in southern European countries.MethodsIn this study, we assess...

Obesity and the potential reduction of social inequalities in mortality: evidence from 21 European populations.

Obesity contributes considerably to the problem of health inequalities in many countries, but quantitative estimates of this contribution and to what extent it is modifiable are scarce. We identify the potential for reducing educational inequalities in all-cause and obesity-related mortality in 21 European populations, by modifying educational differences in obesity and overweight. Prevalence data and mortality data come from 21 European populations. Mortality rate ratios come from literature reviews. We use the population attributable fraction (PAF) to estimate the impact of scenario-based changes in the social distribution of obesity on educational inequalities in mortality. An elimination of differences in obesity between educational groups would decrease relative inequality in all-cause mortality between those with high and low education by up to 12% for men and 42% for women. About half of the relative inequality in mortality could be reduced for some causes of death in several countries, often in southern Europe. Absolute inequalities in all-cause mortality would be reduced by up to 69 (men) and 67 (women) deaths per 100,000 person-years. The potential reduction of health inequality by an elimination of social inequalities in obesity might be substantial. The reductions differ by country, cause of death and gender, suggesting that the priority given to obesity as an entry-point for tackling health inequalities should differ between countries and gender.

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 2000's, 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.

Is socioeconomic status a predictor of mortality in nonagenarians? The vitality 90+ study

socioeconomic inequalities in mortality are well-known in middle-aged and younger old adults, but the situation of the oldest old is less clear. The aim of this study was to investigate socioeconomic inequalities for all-cause, cardiovascular and dementia mortality among the people aged 90 or older. the data source was a mailed survey in the Vitality 90+ study (n = 1,276) in 2010. The whole cohort of people 90 years or over irrespective of health status or dwelling place in a geographical area was invited to participate. The participation rate was 79%. Socioeconomic status was measured by occupation and education, and health status by functioning and comorbidity. All-cause and cause-specific mortality was followed for 3 years. The Cox regression, with hazard ratios (HR) and 95% confidence intervals (CI), was applied. the all-cause and dementia mortality differed by occupational class. Upper non-manuals had lower all-cause mortality than lower non-manuals (HR: 1.61; 95% CI: 1.11-2.32), skilled manual workers (HR: 1.56 95% CI: 1.09-2.25), unskilled manual workers (HR: 1.88; 95% CI: 1.20-2.94), housewives (HR: 1.77 95% CI: 1.15-2.71) and those with unknown occupation (HR: 2.33; 95% CI: 1.41-3.85). Inequalities in all-cause mortality were largely explained by the differences in functioning. The situation was similar according to education, but inequalities were not statistically significant. Socioeconomic differences in cardiovascular mortality were not significant. socioeconomic inequalities persist in mortality for 90+-year-olds, but their magnitude varies depending on the cause of death and the indicator of socioeconomic status. Mainly, mortality differences are explained by differences in functional status.

A comparison of the Scottish Index of Multiple Deprivation (SIMD) 2004 with the 2009 + 1 SIMD: does choice of measure affect the interpretation of inequality in mortality?

BackgroundThere is a growing international literature assessing inequalities in health and mortality by area based measures. However, there are few works comparing measures available to inform research design. The analysis here seeks to begin to address this issue by assessing whether there are important differences in the relationship between deprivation and inequalities in mortality when measures that have been constructed at different time points are compared.MethodsWe contrast whether the interpretation of inequalities in all-cause mortality between the years 2008-10 changes in Scotland if we apply the earliest (2004) and the 2009 + 1 releases of the Scottish Index of Multiple Deprivation (SIMD) to make this comparison. The 2004 release is based on data from 2001/2 and the 2009 + 1 release is based on data from 2008/9. The slope index of inequality (SII) and 1:10 ratio are used to summarise inequalities standardised by age/sex using population and mortality records.ResultsThe 1:10 ratio suggests some differences in the magnitude of inequalities measured using SIMD at different time points. However, the SII shows much closer correspondence.ConclusionsOverall the findings show that substantive conclusions in relation to inequalities in all-cause mortality are little changed by the updated measure. This information is beneficial to researchers as the most recent measures are not always available. This adds to the body of literature showing stability in inequalities in health and mortality by geographical deprivation over time.

Psychosocial Functioning and Intelligence Both Partly Explain Socioeconomic Inequalities in Premature Death. A Population-Based Male Cohort Study

ObjectiveThe possible contributions of psychosocial functioning and intelligence differences to socioeconomic status (SES)-related inequalities in premature death were investigated. None of the previous studies focusing on inequalities in mortality has included measures of both psychosocial functioning and intelligence.MethodsThe study was based on a cohort of 49 321 men born 1949–1951 from the general community in Sweden. Data on psychosocial functioning and intelligence from military conscription at ∼18 years of age were linked with register data on education, occupational class, and income at 35–39 years of age. Psychosocial functioning was rated by psychologists as a summary measure of differences in level of activity, power of initiative, independence, and emotional stability. Intelligence was measured through a multidimensional test. Causes of death between 40 and 57 years of age were followed in registers.ResultsThe estimated inequalities in all-cause mortality by education and occupational class were attenuated with 32% (95% confidence interval: 20–45%) and 41% (29–52%) after adjustments for individual psychological differences; both psychosocial functioning and intelligence contributed to account for the inequalities. The inequalities in cardiovascular and injury mortality were attenuated by as much as 51% (24–76%) and 52% (35–68%) after the same adjustments, and the inequalities in alcohol-related mortality were attenuated by up to 33% (8–59%). Less of the inequalities were accounted for when those were measured by level of income, with which intelligence had a weaker correlation. The small SES-related inequalities in cancer mortality were not attenuated by adjustment for intelligence.ConclusionsDifferences in psychosocial functioning and intelligence might both contribute to the explanation of observed SES-related inequalities in premature death, but the magnitude of their contributions likely varies with measure of socioeconomic status and cause of death. Both psychosocial functioning and intelligence should be considered in future studies.

Association of socioeconomic position with smoking and mortality: the contribution of early life circumstances in the 1946 birth cohort

BackgroundA large part of the socioeconomic mortality gradient can be statistically accounted for by social patterning of adult health behaviours. However, this statistical explanation does not consider the early life...

Smoking and the potential for reduction of inequalities in mortality in Europe

Socioeconomic inequalities in health and mortality remain a widely recognized problem. Countries with smaller inequalities in smoking have smaller inequalities in mortality, and smoking plays an important part in the explanation of inequalities in some countries. We identify the potential for reducing inequalities in all-cause and smoking-related mortality in 19 European populations, by applying different scenarios of smoking exposure. Smoking prevalence information and mortality data come from 19 European populations. Prevalence rates are mostly taken from National Health Surveys conducted around the year 2000. Mortality rates are based on country-specific longitudinal or cross-sectional datasets. Relative risks come from the Cancer Prevention Study II. Besides all-cause mortality we analyze several smoking-related cancers and chronic obstructive pulmonary disease/asthma. We use a newly-developed tool to quantify the changes in population health potentially resulting from modifying the population distribution of exposure to smoking. This tool is based on the epidemiological measure of the population attributable fraction, and estimates the impact of scenario-based distributions of smoking on educational inequalities in mortality. The potential reduction of relative inequality in all-cause mortality between those with high and low education amounts up to 26 % for men and 32 % for women. More than half of the relative inequality may be reduced for some causes of death, often in countries of Northern Europe and in Britain. Patterns of potential reduction in inequality differ by country or region and sex, suggesting that the priority given to smoking as an entry-point for tackling health inequalities should differ between countries.

Socioeconomic inequalities in all-cause mortality in the Czech Republic, Russia, Poland and Lithuania in the 2000s: findings from the HAPIEE Study

BackgroundRelatively large socioeconomic inequalities in health and mortality have been observed in Central and Eastern Europe (CEE) and the former Soviet Union (FSU). Yet comparative data are sparse and virtually...

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

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. 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. 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. Our results underline the continuing need for tobacco control policies, which take into account socioeconomic position.

Socioeconomic inequalities in all-cause mortality in the Czech Republic, Russia, Poland and Lithuania in the 2000s

In all three countries, non-employed people with LLSI had considerably higher poverty risk than employed people, with or without LLSI, in both time periods. Rates of poverty risk in UK for non-employed people with LLSI were much higher than in Sweden and Denmark in both years, but showed no significant change between 2005 and 2010 (38.6% CI = 35.641.2 in 2005; 35.1% CI = 31.6-38.7 in 2010). In contrast, the previously low rates of poverty risks in corresponding groups in Sweden in 2005 (13.8% CI = 9.7-17.8) had nearly doubled by 2010 (26.5% CI = 19.9-33.1). There was a non-significant increase in the previously low rates of poverty risks in Denmark (11.0% CI = 6.3-15.7) to 16.4% CI = 11.1-21.8). The increase of poverty risk in Sweden was more pronounced among men than women. Conclusions The increasing poverty risks among the non-employed people with LLSI in Sweden over time are of concern from a health equity perspective. The role of recent Swedish social policy changes should be further investigated. Key messages Poverty risks among non-employed people with LLSI in Sweden show a disturbing rising trend, not seen in Denmark or United Kingdom. Further investigation is warranted of the impact of recent Swedish policy changes among vulnerable groups.

Socio-economic inequalities in all-cause mortality in Europe: an exploration of the role of heightened social mobility

The larger than expected socio-economic inequalities in health in more egalitarian countries might be explained by a heightened social mobility in these countries. Therefore, the aim of this explorative study was to examine the associations between country-level social mobility, income inequality and socio-economic differences in all-cause mortality, using country-level secondary data from 12 European countries. Both income equality and social mobility were found to be associated with larger socio-economic differences in mortality, particularly in women. These findings suggest that social mobility and income equality, beside their shiny side of improving population health, might have a shady side of increasing socio-economic health inequalities.