Summary of findings
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 could be distinguished from those seen for inequalities in non-amenable mortality. More specifically, our hypothesis 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, was not supported by the data. Inequalities in mortality from amenable causes are larger in countries with larger inequalities in visits to any doctor, but so are inequalities from non-amenable causes. And just like inequalities in mortality from non-amenable causes, inequalities in mortality from amenable conditions also tended to be larger in countries where inequalities in smoking, smoking-related deaths and alcohol-related deaths were larger.
This study has several limitations. As shown by the variation between studies in selection of causes of death deemed to be amenable to health care intervention  this selection is to some extent arbitrary. Our selection is somewhat wider than that used in previous studies, including the study by Stirbu  to which this is a follow-up. Because our results are rather consistent across amenable causes of death, we do not think that other selections would have led to substantially different results.
Specific attention should be paid to mortality from HIV/AIDS, which was largely missing from our data. It is only after about 1995 that HIV/AIDS was distinguished as a cause of death. Due to this exclusion, inequalities in mortality from infectious diseases may have been underestimated. This underestimation may be particularly large for southern European countries, which were severely affected by the AIDS/HIV epidemic in the 1990s. It is therefore of special interest to have the results for the Basque country, the only Southern population for which HIV/AIDS deaths were included. Compared to Barcelona, Madrid and Turin, larger relative inequalities in mortality from other infectious diseases were found in the Basque country (Additional file 1: Table S 3).
Our study had to rely on routinely collected mortality data, which are not necessarily fully comparable between countries. Differences between countries in certification and coding of causes of death are unlikely to have affected our results, because our focus is on comparing lower and higher educated groups within the same country. Our results would only be biased if there is an association between country-specific certification or coding practices and educational level, which is not likely. Most of the mortality data used in this study were census-linked, but data from some Central and Eastern European countries and the Baltic region were based on a cross-sectional unlinked design. This limitation has been discussed in the paper of Stirbu et al  and is not likely to substantially affect our results.
For most of the determinants our study had to rely on national health or multipurpose surveys, and self-reported data on health care use and behavioural risk factors may be unreliable. The different national surveys varied in phrasing of the questions, answer categories, recall periods and response rates. However, the influence of these differences on the outcome of this study can be expected to be limited. Inequalities in reporting between socioeconomic groups will only have affected our results if these inequalities also differed between countries, which is less likely. Also, a comparison between inequalities in self-reported smoking and mortality from smoking-related causes (Table 5) shows a reasonable degree of correspondence. The limited number of countries available for our correlation analysis also limits the scope of our analysis.
Unfortunately, the number of determinants of mortality that could be included in our analysis was limited. More extensive or more detailed data on inequalities in health care use might have led to different findings, because previous studies have shown that there are socioeconomic inequalities in use of specific medical procedures in many countries [16–19]. However, comparable information on inequalities in application of specific interventions is not available.
In accordance with previous studies [9, 20] we found that a lower educational level is associated with a substantially higher mortality from causes thought to be amenable to medical intervention. These inequalities are particularly large in Central and Eastern Europe and the Baltic region, and have led to speculations about the role of inequalities in access or quality of health care in explaining the large inequalities in all-cause mortality in these countries [21–23]. The current study, however, has not found clear evidence for a role of health care, and suggests that larger inequalities in amenable mortality may instead be due to the same risk factors as those involved in other causes of death.
Many authors have commented on the possibility that observed variations in amenable mortality (between countries, regions, social groups) may be due to variations in background risk, and not in access or quality of health care. It is easy to see that this might be the case, because levels of cause-specific mortality are not only influenced by survival rates but also by the incidence rates of the underlying diseases. Incidence rates of conditions amenable to medical intervention may differ between socioeconomic groups, because they differ in exposure to the determinants of incidence (e.g. material living conditions, behavioural risk factors, psychosocial conditions). Our finding that lower educational groups have a higher prevalence of negative health behaviour, such as smoking, obesity and excessive alcohol use, is in line with what others have found [24–26]. It is interesting to see that in our study the largest inequalities were found in mortality from infectious diseases, e.g. tuberculosis. Although we cannot exclude the possibility that survival from TB is lower among the lower educated, due to inequalities in access or quality of health care, it is well-known that incidence is also higher . In the Baltic countries the high inequalities in mortality from TB might also be explained by alcohol use, which has been shown in an earlier study .
We did find inequalities in the use of health care. In a series of studies, Van Doorslaer and colleagues found that inequalities in seeing a specialist are usually “pro-rich”, while seeing a general practitioner is often not related to socio-economic position (after taking health status into account) . Our results (Table 4) are in line with their findings. Previous studies have also reported on a lower use of preventive interventions in lower socioeconomic groups [18, 19], a finding that our study reproduced. A lower use of treatment and control of cardiovascular risk factors has also been found for uninsured adults, who tend to come from the lower socioeconomic groups .
Although we did find an association between inequalities in health care use (i.e., visit to any doctor) and inequalities in amenable mortality, we regard this as potentially spurious because the same association emerged for inequalities in mortality from non-amenable conditions (Table 6). Our study is one among many which has been unable to find consistent and/or exclusive associations between amenable mortality and health care use [31, 32]. Lack of clear evidence of an effect should not be misinterpreted as evidence for lack of an effect, but as the burden of proof lies with those who promote the use of amenable mortality our study urges for caution in the use of these indicators.
Although our findings do not point into the direction of health care, in-depth studies using a more powerful research design may reveal that variations in exposure to shortcomings in health care explain some of the differences in mortality between educational groups. This could be done through a retrospective audit into one specific cause of amenable mortality e.g. TB, colorectal cancer, or cerebrovascular disease. A more ambitious approach would be the performance of a prospective follow up study of one of the amenable conditions, relating socioeconomic variations in mortality outcomes to socioeconomic variations in health care utilization.