Socioeconomic inequalities in cancer mortality between and within countries in Europe: a population-based study.

Background: Reducing socioeconomic inequalities in cancer is a priority for the public health agenda. A systematic assessment and benchmarking of socioeconomic inequalities in cancer across many countries and over time in Europe is not yet available. Methods: Census-linked, whole-of-population cancer-specific mortality data by socioeconomic position, as measured by education level, and sex were collected, harmonized, analysed, and compared across 18 countries during 1990-2015, in adults aged 40-79. We computed absolute and relative educational inequalities; temporal trends using estimated-annual-percentage-changes; the share of cancer mortality linked to educational inequalities. Findings: Everywhere in Europe, lower-educated individuals have higher mortality rates for nearly all cancer-types relative to their more highly-educated counterparts, particularly for tobacco/infection-related cancers [relative risk of lung cancer mortality for lower- versus higher-educated = 2.4 (95% confidence intervals: 2.1-2.8) among men; = 1.8 (95% confidence intervals: 1.5-2.1) among women]. However, the magnitude of inequalities varies greatly by country and over time, predominantly due to differences in cancer mortality among lower-educated groups, as for many cancer-types higher-educated have more similar (and lower) rates, irrespective of the country. Inequalities were generally greater in Baltic/Central/East-Europe and smaller in South-Europe, although among women large and rising inequalities were found in North-Europe (relative risk of all cancer mortality for lower- versus higher-educated ≥1.4 in Denmark, Norway, Sweden, Finland and the England/Wales). Among men, rate differences (per 100,000 person-years) in total-cancer mortality for lower-vs-higher-educated groups ranged from 110 (Sweden) to 559 (Czech Republic); among women from approximately null (Slovenia, Italy, Spain) to 176 (Denmark). Lung cancer was the largest contributor to inequalities in total-cancer mortality (between-country range: men, 29-61%; women, 10-56%). 32% of cancer deaths in men and 16% in women (but up to 46% and 24%, respectively in Baltic/Central/East-Europe) were associated with educational inequalities. Interpretation: Cancer mortality in Europe is largely driven by levels and trends of cancer mortality rates in lower-education groups. Even Nordic-countries, with a long-established tradition of equitable welfare and social justice policies, witness increases in cancer inequalities among women. These results call for a systematic measurement, monitoring and action upon the remarkable socioeconomic inequalities in cancer existing in Europe. Funding: This study was done as part of the LIFEPATH project, which has received financial support from the European Commission (Horizon 2020 grant number 633666), and the DEMETRIQ project, which received support from the European Commission (grant numbers FP7-CP-FP and 278511). SV and WN were supported by the French Institut National du Cancer (INCa) (Grant number 2018-116). PM was supported by the Academy of Finland (#308247, # 345219) and the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No 101019329). The work by Mall Leinsalu was supported by the Estonian Research Council (grant PRG722).

Changes in mortality inequalities over two decades: register based study of European countries.

OBJECTIVE: To determine whether government efforts in reducing inequalities in health in European countries have actually made a difference to mortality inequalities by socioeconomic group. DESIGN: Register based study. DATA SOURCE: Mortality data by level of education and occupational class in the period 1990-2010, usually collected in a census linked longitudinal study design. We compared changes in mortality between the lowest and highest socioeconomic groups, and calculated their effect on absolute and relative inequalities in mortality (measured as rate differences and rate ratios, respectively). SETTING: All European countries for which data on socioeconomic inequalities in mortality were available for the approximate period between years 1990 and 2010. These included Finland, Norway, Sweden, Scotland, England and Wales (data applied to both together), France, Switzerland, Spain (Barcelona), Italy (Turin), Slovenia, and Lithuania. RESULTS: Substantial mortality declines occurred in lower socioeconomic groups in most European countries covered by this study. Relative inequalities in mortality widened almost universally, because percentage declines were usually smaller in lower socioeconomic groups. However, as absolute declines were often smaller in higher socioeconomic groups, absolute inequalities narrowed by up to 35%, particularly among men. Narrowing was partly driven by ischaemic heart disease, smoking related causes, and causes amenable to medical intervention. Progress in reducing absolute inequalities was greatest in Spain (Barcelona), Scotland, England and Wales, and Italy (Turin), and absent in Finland and Norway. More detailed studies preferably using individual level data are necessary to identify the causes of these variations. CONCLUSIONS: Over the past two decades, trends in inequalities in mortality have been more favourable in most European countries than is commonly assumed. Absolute inequalities have decreased in several countries, probably more as a side effect of population wide behavioural changes and improvements in prevention and treatment, than as an effect of policies explicitly aimed at reducing health inequalities.

Socioeconomic inequalities in mortality from conditions amenable to medical interventions: do they reflect inequalities in access or quality of health care?

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 30-74 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 30-74 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 mortality from amenable conditions are related to inequalities in access or quality of health care. Further research is needed to find the causes of socio-economic inequalities in mortality from amenable conditions, and caution should be exercised in interpreting these inequalities as indicating health care deficiencies.

More variation in lifespan in lower educated groups: evidence from 10 European countries.

BACKGROUND: Whereas it is well established that people with a lower socio-economic position have a shorter average lifespan, it is less clear what the variability surrounding these averages is. We set out to examine whether lower educated groups face greater variation in lifespans in addition to having a shorter life expectancy, in order to identify entry points for policies to reduce the impact of socio-economic position on mortality. METHODS: We used harmonized, census-based mortality data from 10 European countries to construct life tables by sex and educational level (low, medium, high). Variation in lifespan was measured by the standard deviation conditional upon survival to age 35 years. We also decomposed differences between educational groups in lifespan variation by age and cause of death. RESULTS: Lifespan variation was higher among the lower educated in every country, but more so among men and in Eastern Europe. Although there was an inverse relationship between average life expectancy and its standard deviation, the first did not completely predict the latter. Greater lifespan variation in lower educated groups was largely driven by conditions causing death at younger ages, such as injuries and neoplasms. CONCLUSIONS: Lower educated individuals not only have shorter life expectancies, but also face greater uncertainty about the age at which they will die. More priority should be given to efforts to reduce the risk of an early death among the lower educated, e.g. by strengthening protective policies within and outside the health-care system.

Premature mortality in Slovenia in relation to selected biological, socioeconomic, and geographical determinants.

AIM: To determine biological (sex and age), socioeconomic (marital status, education, and mother tongue) and geographical (region) factors connected with causes of death and lifespan (age at death, years-of-potential-life-lost, and mortality rate) in Slovenia in the 1990s. METHODS: In this population-based cross-sectional study, we analyzed all deaths in the 25-64 age group (N=14 816) in Slovenia in 1992, 1995, and 1998. Causes of death, classified into groups according to the 10th revision of International Classification of Diseases, were linked to the data on the deceased from the 1991 Census. Stratified contingency-table analyses were performed. Years-of-potential-life-lost (YPLL) were calculated on the basis of population life-tables stratified by region and linearly modeled by the characteristics of the deceased. Poisson regression was applied to test the differences in mortality rate. RESULTS: Across all socioeconomic strata, men died at younger age than women (index of excess mortality in men exceeded 200 for all studied years) and from different prevailing causes (injuries in men aged <45 years; neoplasms in women aged >35 years). For men, higher education was associated with fewer deaths from digestive and respiratory system diseases. The least educated women died relatively often from circulatory diseases, but rarely from neoplasms. Single people died from neoplasms less often. Marriage in comparison with divorce reduced the mortality rate by 1.9-fold in both men and women (P<0.001). Mortality rate in both men and women decreased with increasing education level (P<0.001). Mortality rate of ethnic Slovenians was half the mortality rate of ethnic minority members and immigrants (P<0.001). Analysis of YPLL revealed limited and nonlinear impact of education level on premature mortality. The share of neoplasms was the highest in the cluster of socioeconomically prosperous regions, whereas the share of circulatory diseases was increased in poorer regions. Significant differences were found between individual regions in age at death and mortality rate, and the differences decreased over the studied period. CONCLUSION: These data may aid in understanding the nature, prevalence and consequences of mortality as related to socioeconomic inequalities, and thus serve as a basis for setting health and social policy goals and planning health measures.