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Background: The effect of inequalities aggravated by economic recessions in the mortality rates of certain diseases has been previously described. In this study, we analyzed the relationship between socio-economic deprivation and cancer mortality. We focused on lung, colon, prostate, and breast cancers in nine European urban areas over three periods: two before (2000-2003 and 2004-2008) and one after (2009-2014) the onset of the 2008 financial crisis., Methods: This is an ecological study of trends. The units of analysis were small areas within nine European urban areas. We used a composite deprivation index as a socio-economic indicator. As a mortality indicator, we used the smoothed standardized mortality ratio, calculated using the hierarchical Bayesian model proposed by Besag, York and Mollié. To analyze the evolution of socio-economic inequalities, we fitted an ecological regression model that included the socio-economic indicator, the period of time, and the interaction between these terms., Results: In men, socio-economic inequalities in all-cancer and lung cancer mortality were observed in most of the cities studied, but did not increase after the onset of the economic crisis. In women, only two cities (Stockholm and London) showed socio-economic inequalities in all-cancer and lung cancer mortality; there was also no increase in inequalities., Conclusions: Our results did not validate our hypothesis that inequalities increase in times of crisis. However, they emphasize the importance of socio-economic measurements for understanding mortality inequalities, and can be used to inform prevention strategies and help plan local health programs aimed at reducing health inequalities., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objective: To analyse socioeconomic inequalities in all-cause mortality among men and women in nine European urban areas during the recent economic crisis, and to compare the results to those from two periods before the crisis., Method: This is an ecological study of trends based on three time periods (2000-2003, 2004-2008 and 2009-2014). The units of analysis were the small areas of nine European urban areas. We used a composite deprivation index as a socioeconomic indicator, along with other single indicators. As a mortality indicator, we used the smoothed standardized mortality ratio, calculated using the hierarchical Bayesian model proposed by Besag, York and Mollié. To analyse the evolution of socioeconomic inequalities, we fitted an ecological regression model that included the socioeconomic indicator, the period of time, and the interaction between these terms., Results: We observed significant inequalities in mortality among men for almost all the socioeconomic indicators, periods, and urban areas studied. However, no significant changes occurred during the period of the economic crisis. While inequalities among women were less common, there was a statistically significant increase in inequality during the crisis period in terms of unemployment and the deprivation index in Prague and Stockholm, respectively., Conclusions: Future analyses should also consider time-lag in the effect of crises on mortality and specific causes of death, and differential effects between genders., (Copyright © 2019 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.)

Objectives: Large socioeconomic inequalities in health are still present in the Central Europe. The aim was to explore socioeconomic inequalities in mortality in Visegrad countries-the Czech Republic, Hungary, Poland and Slovakia (V4), by three different socioeconomic indicators (unemployment, risk of poverty/social exclusion, education). The study was conducted within the H2020 Euro-Healthy project., Methods: The associations between selected socioeconomic indicators and the standardised mortality rates by four main causes (mortality related to cancer, circulatory, respiratory and digestive system) in the economically active population aged 20-64 years in the 35 NUTS 2 level regions of the V4 in the period 2011-2013 were explored, using linear regression models., Results: Lower education level was the most significant predictor of mortality in the V4. The lowest mortality rates by all causes of death were found in the regions of the Czech Republic, the highest in regions of Hungary., Conclusions: Despite the common origin, the pathways of the V4 countries in employment, poverty and education seem to be different, also having impact on health equity. Therefore, where you live in the V4 can significantly influence your health.