Main findings
The study showed a large geographic variation in the CSD mortality and SED in the 66 sub-regions of Poland. For both men and women, the largest mortality was found in the more deprived and middle group sub-regions, and the lowest in the less deprived sub-regions. However, in the more deprived and middle group sub-regions benefited more from the decrease in CSD mortality in men and women. In women, the differences in the number of DPP between the SED groups were similar to that in men, except in the case of CD for which a nonsignificant trend was observed. The relationship between SED and CSD mortality was found to be significant in men after adjusting for mean BMI, mean smoking rate, and population density. In women, a significant relationship was observed with mean BMI, but the relationship between CSD mortality and SED was not significant after adjusting for covariates, although the β coefficients were similar to that of men.
Interpretation of results
Our study indicates that the variation of CSD mortality in the sub-regions of Poland can be explained at least partially by the differences in SED. The results comply with those of the studies in which synthetic SED indexes were used to assess the relationship between deprivation and mortality due to CSD and IHD [13–15, 19–22]. It has been suggested that deprivation significantly influences the mortality due to CSD in men compared to women [13, 46]. Gender differences in mortality can be possibly associated with profession due to elevated exposure to risk factors, particularly among male manual workers [47]. Furthermore, this study confirmed the relationship between SED and mortality from IHD and CD in women, which was also highlighted in other studies [48–50].
In our study, CSD mortality was shown to be associated with tobacco smoking only in men. This could reflect the higher smoking rates in the group of more deprived sub-regions as compared with the less deprived sub-regions. According to the MORGAM study, in Poland, smoking is less prevalent among women characterized by low and secondary education as compared with women with higher education, particularly in less urbanized areas [51]. A study indicated that in Eastern European countries, economic development and social as well as cultural processes associated with gender empowerment affect the differences in smoking between educated and uneducated women [52].
Our results showed inequalities in mortality across sub-regions ranked by deprivation. The lowest CSD mortality was observed in the less deprived sub-regions, which predominantly include large urban agglomerations and small cities. This may be associated with the fact that these sub-regions have access to different resources, including educational infrastructure, services, and job opportunities [50]. Furthermore, these sub-regions offer a more favorable environment, such as access to gyms and shops selling healthy foods, as well as health care services, which may contribute to better health outcomes in their residents [44, 53, 54]. The more deprived sub-regions are located in the eastern and northwest parts of Poland and are characterized by a low population density. These are considered less attractive to investors, which affects economic development. This confirms, among others, the fact that the areas of many sub-regions with a more deprived sub-regions overlap with those areas in which national farm holdings had been liquidated and more harmful effects of the economic transformation are experienced. These areas lack support programs targeting social groups deprived of earlier forms of employment, and hence are consequently linked with poor health outcomes [26, 27]. Furthermore, the area encompassing sub-regions with a high deprivation in the western part of the country was associated with a more explicit trend toward job migrations to work legally abroad. The migrations may exacerbate a optimal development of these areas due to outflow of human capital, and are also associated with a prevalence of social exclusion and poverty, leading altogether to health hazards [26, 55].
However, a reverse trend was observed for IHD-related mortality—the mortality was the highest in the less deprived sub-region group. In the case of CD, the highest mortality was found in middle sub-regions, which may suggest the occurrence of other specific factors that are not included in the study (e.g., differences in access to medical care on stroke units) [56]. It should also be emphasized that a rapid decrease in CSD mortality was noted in more deprived sub-regions with high SED index values. In the more deprived and middle group sub-regions, the percent of DPP was higher as compared with the less deprived sub-regions.
While the mortality due to CSD and CD was the lowest in the less deprived sub-regions, the reduction of mortality between 2010 and 2014 was smaller in these sub-regions compared to the sub-regions with the high SED index. This could be explained by the fact that in the best-developed—highly urbanized—sub-regions, mortality (due to better availability of cardiologic care services and invasive cardiology procedures) had been reduced in earlier years and the scope for improvement of cardiovascular health was narrower [57]. Simultaneously, in more deprived and middle sub-regions, modern prevention and therapeutic methods are increasingly becoming accessible. For example, life-saving invasive cardiology procedures have been available after 2000 not only in academic centers but also in district hospitals, which might have resulted in reduced mortality even in smaller centers with a higher SED index. This is also supported by the results of other analyses [57], according to which the reduction of mortality due to CSD among people with higher education was particularly pronounced between 1991–1993 and 2001–2003, whereas during the period 2001–2003 and 2010–2012, the reduction was considerably lower. Noticeably, this reduction of mortality was observed at a lower rate in people with low education in comparison to those with higher education.
The stratification using terciles allowed to identify the residence-related deprivation which may be of importance at intervention strategies and activities addressing improvement of cardiovascular health. In the policy process aimed to alleviate health inequalities, the activities should focus not only on the poverty reduction throughout income redistribution. It is also critical ensuring equality of health opportunity in the entire population, through education, employment, improve working conditions and preventive care [58]. Decreasing health inequalities ought to be a political and social priority, given they deteriorate economic productivity and the potential of sustainable and inclusive growth.
Strengths and limitations
To our knowledge, this study is the first to use the SED index to assess the relationship with mortality due to CSD at the population level in Poland. The study was performed considering the whole population of the country. In the 66 sub-regions, a large variation was found in CSD mortality and SED. Furthermore, the sub-regions represented all the characteristics that are typical for Poland. The synthetic SED index enabled an approximate estimation of the singular variables (education, structure in employment, salary, unemployment, and poverty). A database concerning sub-regions defined based on NUTS-3 classification, which is used in the European Union member states, was used for the first time in this study [32]. A unique strength of this study was the comparison of mortality due to CSD and the time-related changes using the DPP index in three different environments regarding deprivation level, thus, contrary to other studies reporting mortality trends in administrative areas of the country [57]. Our results showed a potent effect of health inequalities and may be, therefore, a contribution to limited literature field dealing with the associations between area-related deprivation and mortality from CSD in Central and Eastern European countries [21, 22]. Similar and comparable socioeconomic levels in specific countries of this region may facilitate cross-comparisons and may allow consistently conduct research across the populations.
The results of the study should be interpreted in light of certain limitations. The ecological design does not allow addressing the causality of the relationships. As sub-regions were considered as statistical units in this study, instead of individual persons, it was possible to investigate the inequalities between the sub-regions, while inequalities within them remain unexplored. Epidemiological analyses for geographical areas lead to best results when statistical units are populations of small size [59, 60]. It allows for better homogeneity and decreases the problem of averaging of different populations within single geographical area. Such averaging results in attenuation of studied effects in statistical models. In this paper population sizes in sub-regions were relatively large, so it was expectable that real effects might be significantly stronger and so their detection could be difficult, if not impossible. However, we were able to confirm statistically significant relationships of SED index with 4 out of 6 analyzed mortality indicators. In contrast to mortality and SED, information on covariates such as education, smoking, and BMI was based on one-point observation (Census 2011, Social Diagnosis Survey 2011), which was only available for the studied sub-regions and corresponded with the study period. It is unlikely that these characteristics changed much within the observation time. The relationship between SED and mortality due to CSD could be confounded by the sub-region differences in the exposure to the other uncontrolled factors; therefore, residual confounding should be taken into account. For example, we did not utilize stress as an important variable because of limited accessibility or missing data. However, stress is regarded a significant mediator linking the associations between deprivation and mortality due to cardiovascular diseases [61]. Noticeably, some components of the SED (e.g. percent of people on social support due to poverty) may have, at least partly, reflect the chronic stress [18]. Thus, the role of stress should be investigated in future research. Another limitation of the study is the quality of the data on deaths associated with the differences in the reliability of death-cause coding by physicians who filled out death certificates. Our results showed that the highest mortality due to IHD was observed in the less deprived (most urbanized) sub-regions. This may be explained partially by the discrepancies in death certification encoding which has been described earlier in Poland [62]. Such issue was even reported in countries with highly advanced health information systems [63]. However, territorial differences in death-cause coding could rather contribute to the greater impact of random variability on our results, and it is less likely that the occurrence of a systematic error would explain the observed relationships. The latter is supported by the overall accordance of relationships found for IHD, CD, and CSD.