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Objectives: Although the contribution of health care to survival from cancer has been studied extensively, much less is known about its contribution to population health. We examine how medical innovations have influenced trends in cause-specific mortality at the national level., Methods: Based on literature reviews, we selected six innovations with proven effectiveness against cervical cancer, Hodgkin's disease, breast cancer, testicular cancer, and leukaemia. With data on the timing of innovations and cause-specific mortality (1970-2005) from seven European countries we identified associations between innovations and favourable changes in mortality., Results: For none of the five specific cancers, sufficient evidence for an association between introduction of innovations and a positive change in mortality could be found. The highest association was found between the introduction of Tamoxifen and breast cancer mortality., Conclusions: The lack of evidence of health care effectiveness may be due to gradual improvements in treatment, to effects limited to certain age groups or cancer subtypes, and to contemporaneous changes in cancer incidence. Research on the impact of health care innovations on population health is limited by unreliable data on their introduction.

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.

Background: Governments have identified innovation in pharmaceuticals and medical technology as a priority for health policy. Although the contribution of medical care to health has been studied extensively in clinical settings, much less is known about its contribution to population health. We examine how innovations in the management of four circulatory disorders have influenced trends in cause-specific mortality at the population level., Methods: Based on literature reviews, we selected six medical innovations with proven effectiveness against hypertension, ischaemic heart disease, heart failure and cerebrovascular disease. We combined data on the timing of these innovations and cause-specific mortality trends (1970-2005) from seven European countries. We sought to identify associations between the introduction of innovations and favourable changes in mortality, using Joinpoint-models based on linear spline regression., Results: For both ischaemic heart disease and cerebrovascular disease, the timing of medical innovations was associated with improved mortality in four out of five countries and five out of seven countries, respectively, depending on the innovation. This suggests that innovation has impacted positively on mortality at the population level. For hypertension and heart failure, such associations could not be identified., Conclusion: Although improvements in cause-specific mortality coincide with the introduction of some innovations, this is not invariably true. This is likely to reflect the incremental effects of many interventions, the time taken for them to be adopted fully and the presence of contemporaneous changes in disease incidence. Research on the impact of medical innovations on population health is limited by unreliable data on their introduction.

Objectives: There is a renewed interest in health system indicators. In 1976 a measure of quality of healthcare, amenable mortality, was introduced by Rutstein. This indicator is based on the concept that deaths from certain causes should not occur in the presence of timely and effective healthcare. In the project "Amenable mortality in the European Union: toward better indicators for the effectiveness of health systems" (AMIEHS), we introduce a new approach to the selection of indicators of amenable mortality., Methods: Based on predefined selection criteria and a broad review of the literature on the effectiveness of medical interventions, a first set of potential indicators of amenable mortality (causes of death) was selected. The timing of the introduction of medical innovations was established through reviews and questionnaires sent to national experts from seven participating European countries. The preselected indicators were then validated by a trend analysis that identified associations between the timing of innovations and cause-specific mortality trends and by a Delphi-procedure., Results: After a short review of previous lists of amenable mortality indicators and a detailed description of the innovative procedure in the AMIEHS project we present a list of 14 causes of death that passed our selection criteria. We illustrate our empirical validation of these indicators using the examples of peptic ulcer and renal failure., Conclusions: The innovation developed in the AMIEHS study is a rigorous new approach to the concept of amenable mortality that includes empirical validation. Only validated indicators can be successfully used to assess the quality of healthcare systems in international comparisons., (Copyright © 2012 SESPAS. Published by Elsevier Espana. All rights reserved.)

Background and Study Aims: There is widespread consensus on the need for better indicators of the effectiveness of healthcare. We carried out an analysis of the validity of amenable mortality as an indicator of the effectiveness of healthcare, focusing on the potential use in routine surveillance systems of between-country variations in rates of mortality. We assessed whether the introduction of specific healthcare innovations coincided with declines in mortality from potentially amenable causes in seven European countries. In this paper, we summarise the main results of this study and illustrate them for four conditions., Data and Methods: We identified 14 conditions for which considerable declines in mortality have been observed and for which there is reasonable evidence in the literature of the effectiveness of healthcare interventions to lower mortality. We determined the time at which these interventions were introduced and assessed whether the innovations coincided with favourable changes in the mortality trends from these conditions, measured using Poisson linear spline regression. All the evidence was then presented to a Delphi panel., Main Results: The timing of innovation and favourable change in mortality trends coincided for only a few conditions. Other reasons for mortality decline are likely to include diffusion and improved quality of interventions and in incidence of diseases and their risk factors, but there is insufficient evidence to differentiate these at present. For most conditions, a Delphi panel could not reach consensus on the role of current mortality levels as measures of effectiveness of healthcare., Discussion and Conclusions: Improvements in healthcare probably lowered mortality from many of the conditions that we studied but occurred in a much more diffuse way than we assumed in the study design. Quantification of the contribution of healthcare to mortality requires adequate data on timing of innovation and trends in diffusion and quality and in incidence of disease, none of which are currently available. Given these gaps in knowledge, between-country differences in levels of mortality from amenable conditions should not be used for routine surveillance of healthcare performance. The timing and pace of mortality decline from amenable conditions may provide better indicators of healthcare performance.

Background: Socioeconomic differences in health are a major challenge for public health. However, realistic estimates to what extent they are modifiable are scarce. This problem can be met through the systematic application of the population attributable fraction (PAF) to socioeconomic health inequalities., Methods: The authors used cause-specific mortality data by educational level from Belgium, Norway and Czech Republic and data on the prevalence of smoking, alcohol, lack of physical activity and high body mass index from national health surveys. Information on the impact of these risk factors on mortality comes from the epidemiological literature. The authors calculated PAFs to quantify the impact on socioeconomic health inequalities of a social redistribution of risk factors. The authors developed an Excel tool covering a wide range of possible scenarios and the authors compare the results of the PAF approach with a conventional regression., Results: In a scenario where the whole population gets the risk factor prevalence currently seen among the highly educated inequalities in mortality can be reduced substantially. According to the illustrative results, the reduction of inequality for all risk factors combined varies between 26% among Czech men and 94% among Norwegian men. Smoking has the highest impact for both genders, and physical activity has more impact among women., Conclusions: After discussing the underlying assumptions of the PAF, the authors concluded that the approach is promising for estimating the extent to which health inequalities can be potentially reduced by interventions on specific risk factors. This reduction is likely to differ substantially between countries, risk factors and genders.

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.

Previous studies have reported important variations in the magnitude of health inequalities between countries that belong to different welfare systems. This suggests that there is scope for reducing health inequalities by means of country-level interventions. The present study adds to this literature by exploring whether the magnitude of socioeconomic inequalities in mortality is associated with social inequality levels. Denmark and the USA belong to fundamentally different welfare systems (social democratic and liberal) and our study thereby contributes to the ongoing debate on whether welfare systems are linked to health inequalities. We analyze Denmark and the USA in terms of socioeconomic differences in mortality above age 58. The data sources were Danish register data from 1980 to 2002 (n = 2,029,324), and survey data from the US Health and Retirement Study (HRS) from 1992 to 2006 (n = 9374). Survival analysis was used to study the impact of socioeconomic status on mortality and the magnitude of mortality differences between the two countries was compared. The results showed surprisingly that mortality differentials were larger in Denmark than in the USA even after controlling for a number of covariates: The poorest 10 percent of the Danish elderly population have a mortality rate ratio of 3.32 (men) and 3.70 (women) compared to the richest 25 percent. In the USA the corresponding rate ratios are 1.67 and 1.56. Low income seems to be a more powerful risk factor for mortality than low education. A number of possible explanations for higher mortality differences in Denmark are discussed: unintended positive correlation between generous health services and health inequality, early life influences, mortality selection, and relative deprivation., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Death rates for working-age men in European state socialist countries deviated from general improvements in survival observed in the rest of Europe during the 20th century. The magnitude of structural labor force changes across countries correlates with lagged increases in death rates for men in the working ages. This pattern is consistent with a hypothesis that hyper-development of heavy industry and stagnation (even contraction) of the service sector created anomic conditions leading to unhealthy lifestyles and self-destructive behavior among men moving from primary-sector to secondary-sector occupations. Occupational contrasts within countries similarly show concentration of rising male death rates among blue collar workers. Collapse of state socialist systems produced rapid corrections in labor force structure after 1990, again correlated with a fading of the state socialist mortality syndrome in following decades. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11113-010-9192-z) contains supplementary material, which is available to authorized users.

Objectives: Although mortality differences between groups of different socioeconomic status (SES) are known to decrease at higher age, the reasons for this are unknown. This study reviews the existing arguments for convergence versus divergence of SES mortality differences in old age, differentiates between increasing age and worsening health, and discusses explanations for the observed convergence., Methods: Register data of all Danish men aged ≥ 59 years between 1980 and 2002 (n = 938,427), and survival analysis, are used to examine mortality differences between income groups, controlling for seven variables. Interaction models describe the change of SES mortality differences with age or health, days in hospital being a proxy for the latter., Results: Large mortality differences were found with relative risks of 0.28-0.36 for income groups above the 25th income percentile compared with those below the 10th percentile. Mortality differentials are stable across age groups but converge when health deteriorates., Discussion: The idea of "age as leveler" has to be revised because it is illness and not age that levels SES mortality differences. That the transition from poor health to death is independent from SES suggests that social mortality differences originate in early stages of the health deterioration process. Intensive treatment for very sick people will not decrease SES mortality differences.

Objectives: Although research on health limitations has investigated gender differences in health and mortality, gender differentials in individual-level trajectories have been studied less frequently. Moreover, there are no studies on the relationship between course types and subsequent mortality. We investigate course types, explore confounding by socioeconomic and demographic correlates, and pose the question of whether the gender gap in morbidity results from differences in the onset of, and/or survival with, health limitations., Methods: Using the German Socioeconomic Panel, we identify individual trajectories of health limitations and use multinomial logistic regressions to explore confounding and the relationship with mortality., Results: The frequency of stable trajectories without limitations is lower among women because they tend to experience courses that involve extended periods of limitations and deteriorating health. Women also experience more frequently improvement after deterioration. The female mortality advantage is particularly large after health deterioration., Discussion: Health limitations do not make men and women more equal in the face of death. Our results are consistent with earlier studies showing that mortality selection and differences in chronic conditions may explain the gender gap in health and mortality. We extend previous research showing that the female health disadvantage is largely the result of their mortality advantage.