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Background: Recently, research focus has returned to amenable mortality to health care, despite the decreasing trend, as it remains a significant contributor to social and economic loss due to premature death. This article assesses the trends of amenable mortality over time and, its spatial inequalities with respect to deprivation, in Hungary., Methods: An ecological analysis of mortality amenable to health care was carried out using smoothed indirectly standardized mortality ratios, calculated by full hierarchical Bayesian methods, at municipality level. The association between the spatial distribution of amenable mortality and deprivation was also assessed using a Hungarian specific deprivation index., Results: Trends of mortality amenable to health care were characterized by a decreasing pattern across the studied period, 1996-2008. Areas of significantly high risk of amenable mortality were identified in the North-eastern, Eastern and South-western parts of Hungary. A statistically significant association was found between amenable mortality and deprivation status in both genders. After correcting for bias due to socio-economic confounders, the patterns of areas with excess risks significantly changed., Conclusion: Differences in deprivation alone cannot explain the spatial distribution of mortality amenable to health care. This study highlights the importance of exploring other factors (e.g. health-care system and individual life style) beyond socio-economic status, which affect health inequalities particularly for health policy makers, who are responsible for the mitigation of health disparities.

Heat waves are expected to increase in frequency and magnitude with climate change. The first part of a study to produce projections of the effect of future climate change on heat-related mortality is presented. Separate city-specific empirical statistical models that quantify significant relationships between summer daily maximum temperature (T (max)) and daily heat-related deaths are constructed from historical data for six cities: Boston, Budapest, Dallas, Lisbon, London, and Sydney. 'Threshold temperatures' above which heat-related deaths begin to occur are identified. The results demonstrate significantly lower thresholds in 'cooler' cities exhibiting lower mean summer temperatures than in 'warmer' cities exhibiting higher mean summer temperatures. Analysis of individual 'heat waves' illustrates that a greater proportion of mortality is due to mortality displacement in cities with less sensitive temperature-mortality relationships than in those with more sensitive relationships, and that mortality displacement is no longer a feature more than 12 days after the end of the heat wave. Validation techniques through residual and correlation analyses of modelled and observed values and comparisons with other studies indicate that the observed temperature-mortality relationships are represented well by each of the models. The models can therefore be used with confidence to examine future heat-related deaths under various climate change scenarios for the respective cities (presented in Part 2).

According to the 5th Assessment Report of IPCC, one of the greatest health impacts of climate change will be the heat-related excess mortality. In Hungary, the National Adaptation Geo-Information System (NAGiS) helps the adaptation process of climate change. Within CRIGiS project, which was initiated to extend the NAGiS, our special subtask was the assessment of heat-related excess mortality at different area levels in the present and for two predicted future periods. This assessment is described in this paper. The Hungarian Central Statistical Office provided the daily mortality data for the period of May 1 - Sep 30, 2005-2014. The observed daily mean temperature data for the same period at small area level (NUTS 4, Nomenclature of territorial units for statistics) were provided by the Hungarian Meteorological Service (HMS). The modeled daily mean temperature data at NUTS 4 level based on the ALADIN-Climate model for three periods, May 1 - Sep 30 of 1991-2020, 2021-2050, and 2071-2100, were also provided by HMS. The heatwave days were defined by the 90th percentile of the frequency distribution of daily mean temperatures at different area levels. The excess mortality was computed by extracting the mean daily mortality of cool days from the number of deaths on heatwave days. As we found a difference between the frequency distributions of observed and modeled present periods, a correction was done assuring that the yearly sums of excess mortality were the same in the observed and modeled present periods. Based on the corrected threshold values the changes in the future could be predicted. During 2005-2014, the range of daily threshold temperature was between 22.3 °C and 25.4 °C, the mean excess mortality was 15.8% on the heatwave days at NUTS 4 level. At national level, daily mortality was higher by 51 cases on heatwave days than on cool days, which corresponded to an excess of 783 death cases per year in average. According to the climate model, the number and intensity of heatwave days will increase in relation to the present situation. Assuming the same population and level of sensitivity, for 2021-2050 a 2.6-fold, for 2071-2100 a 7.4-fold increase of excess deaths is predicted causing 2030 and 5800 cases per year, respectively. The prediction of excess mortality at different area levels in the NAGiS database will help stakeholders to prepare adaptation measures to climate change. [ABSTRACT FROM AUTHOR]

Several studies have reported significant health effects of air pollution even at low levels of air pollutants, but in most of theses studies linear nonthreshold relations were assumed. We investigated the exposure–response association between ambient particles and mortality in the 22 European cities participating in the APHEA (Air Pollution and Health—A European Approach) project, which is the largest available European database. We estimated the exposure–response curves using regression spline models with two knots and then combined the individual city estimates of the spline to get an overall exposure–response relationship. To further explore the heterogeneity in the observed city-specific exposure–response associations, we investigated several city descriptive variables as potential effect modifiers that could alter the shape of the curve. We conclude that the association between ambient particles and mortality in the cities included in the present analysis, and in the range of the pollutant common in all analyzed cities, could be adequately estimated using the linear model. Our results confirm those previously reported in Europe and the United States. The heterogeneity found in the different city-specific relations reflects real effect modification, which can be explained partly by factors characterizing the air pollution mix, climate, and the health of the population.

Abstract: An association between health and socio-economic status is well known. Based on international and national studies, the aims of this study were to develop a multi-dimensional index at the municipality level, to provide information about socio-economic deprivation in Hungary and to investigate the association between socio-economic status and the spatial distribution of premature mortality due to diseases of the circulatory system. Seven municipality level socio-economic indicators were used from the National Information System of Spatial Development (income, low qualification, unemployment, one-parent families, large families, density of housing and car ownership). After normalisation and standardisation, indicator weights were evaluated using factor analysis. A risk analysis study was conducted using the Rapid Inquiry Facility software to evaluate the association between deprivation and the spatial distribution of premature mortality due to diseases of the circulatory system for the years 1998–2004. Areas of significantly high deprivation were identified in the northeastern, eastern and southwestern parts of Hungary. A statistically significant association was found between premature cardiovascular mortality and deprivation status in both genders. The Deprivation Index is the first composite index at the municipality level in Hungary and includes key factors that affect socio-economic status. The identified association highlighted the fact that inequalities in socio-economic status may reflect the spatial distribution of health status in a population. The results can be used to inform prevention strategies and help plan local health promotion programs aimed at reducing health inequalities. [Copyright &y& Elsevier]