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Background: Hypertension is a leading cause of cardiovascular disease. This review examines the literature on hypertension control in the Czech Republic from 1972 to 2022 addressing limited data on its effectiveness., Methods: A literature review was conducted covering the period from 1972 to 2022, utilizing MEDLINE (PubMed), Web of Science, and Scopus databases. Articles were selected based on title and abstract evaluations, with full-text reviews performed as needed. Thirteen studies involving 44,990 participants were included in this review., Results: Control rates increased from 2.8% (men) and 5.2% (women) in 1985 to 32.3% (men) and 37.4% (women) from 2015 to 2018. Women showed better blood pressure control. Specialised centres achieved higher success (48%) than general practitioners (18.4%). Diabetic patients had a lower percentage (29.1%) of patients meeting their target values (<130/80 mmHg) compared to non-diabetic patients, who had a higher percentage (60.6%) meeting their target values (<140/90 mmHg)., Conclusion: Hypertension treatment success rate in the Czech Republic improved significantly over the last 50 years and is currently comparable to that of other European countries with similar healthcare resources. However, it still remains suboptimal and lags behind the countries with the most successful treatment outcomes (Tab. 3, Fig. 1, Ref. 37). Text in PDF www.elis.sk Keywords: hypertension, treatment, effectiveness, Czech Republic, blood pressure.

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.)

Urban areas in Europe are facing a range of environmental public health challenges, such as air pollution, traffic noise and road injuries. The identification and quantification of the public health risks associated with exposure to environmental conditions is important for prioritising policies and interventions that aim to diminish the risks and improve the health of the population. With this purpose in mind, the EURO-HEALTHY project used a consistent approach to assess the impact of key environmental risk factors and urban environmental determinants on public health in European metropolitan areas. A number of environmental public health indicators, which are closely tied to the physical and built environment, were identified through stakeholder consultation; data were collected from six European metropolitan areas (Athens, Barcelona, Lisbon, London, Stockholm and Turin) covering the period 2000-2014, and a health impact assessment framework enabled the quantification of health effects (attributable deaths) associated with these indicators. The key environmental public health indicators were related to air pollution and certain urban environmental conditions (urban green spaces, road safety). The air pollution was generally the highest environmental public health risk; the associated number of deaths in Athens, Barcelona and London ranged between 800 and 2300 attributable deaths per year. The number of victims of road traffic accidents and the associated deaths were lowest in the most recent year compared with previous years. We also examined the positive impacts on health associated with urban green spaces by calculating reduced mortality impacts for populations residing in areas with greater green space coverage; results in Athens showed reductions of all-cause mortality of 26 per 100,000 inhabitants for populations with benefits of local greenspace. Based on our analysis, we discuss recommendations of potential interventions that could be implemented to reduce the environmental public health risks in the European metropolitan areas covered by this study., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The different geographical contexts seen in European metropolitan areas are reflected in the uneven distribution of health risk factors for the population. Accumulating evidence on multiple health determinants point to the importance of individual, social, economic, physical and built environment features, which can be shaped by the local authorities. The complexity of measuring health, which at the same time underscores the level of intra-urban inequalities, calls for integrated and multidimensional approaches. The aim of this study is to analyse inequalities in health determinants and health outcomes across and within nine metropolitan areas: Athens, Barcelona, Berlin-Brandenburg, Brussels, Lisbon, London, Prague, Stockholm and Turin. We use the EURO-HEALTHY Population Health Index (PHI), a tool that measures health in two components: Health Determinants and Health Outcomes. The application of this tool revealed important inequalities between metropolitan areas: Better scores were found in Northern cities when compared with their Southern and Eastern counterparts in both components. The analysis of geographical patterns within metropolitan areas showed that there are intra-urban inequalities, and, in most cities, they appear to form spatial clusters. Identifying which urban areas are measurably worse off, in either Health Determinants or Health Outcomes, or both, provides a basis for redirecting local action and for ongoing comparisons with other metropolitan areas.