Background: Since the 2008 economic crisis in Spain, overall fertility has continued to decrease, while urban inequalities have increased. There is a general lack of studies of fertility patterns in small-areas of Spanish cities. We explored the effects of the economic crisis on fertility during three time periods in urban settings in Spain. Methods: We studied the distribution of fertility rates among women (15-49 years) from Spain and low-middle income countries (LIC) who were living in 13 Spanish cities. We mapped fertility and the MEDEA socioeconomic deprivation index in small-areas, and analyzed age-related trends in fertility rates. We performed an ecological regression analysis of fertility and the deprivation index in two pre-crisis periods (1999-2003 and 2004-2008) and one crisis period (2009-2013). Fertility rates were calculated and smoothed using the hierarchical Bayesian model (BYM). Results: Higher fertility was generally associated with socioeconomic deprivation, with adjustment for the mothers' age and nationality. While Spanish citizens tended to delay childbearing throughout the three study periods, fertility increased among Spanish adolescents from deprived urban areas during the economic crisis. There was a general decline in fertility among immigrants after the crisis, especially in southern cities. Overall, fertility appeared to be stable, with higher fertility in more deprived areas. Conclusion: Increased unemployment and changes to government family policies may have contributed to delayed childbearing in Spain. For immigrants, more restrictive immigration policies may have played a crucial role in decreasing fertility rates. Reforming such policies will be key for better reproductive rights and improved fertility rates across all population cohorts in Spain.
International audience ; This paper aims at assessing the effectiveness of introducing road safety onto the political agenda in the year 2004 – and the overall effect of the road safety measures implemented thereafter - on the number of road traffic injured people in Spain.
The aim of this study is to analyse the time trends in the European Union (EU) before and during the economic crisis in 1) the energy poverty (EP) prevalence; 2) the association between EP and health and 3) the impact of EP on health. We analyse trends among women and men in two EU macro regions, defined by a novel index of structural vulnerability to EP. The study shows how EP and its impact on health worsened during the economic crisis and identifies groups at higher risk such as women and people living in Mediterranean and Eastern European countries, which have been found to be countries with higher structural vulnerability to EP.
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. ; Objetivo: Analizar las desigualdades socioeconómicas en la mortalidad por todas las causas en hombres y mujeres de nueve áreas urbanas europeas durante la reciente crisis económica, y comparar los resultados con dos periodos previos a la crisis. Método: Estudio ecológico de tendencias basado en tres periodos (2000-2003, 2004-2008 y 2009-2014). Las unidades de análisis fueron las áreas pequeñas de nueve zonas urbanas europeas. Se utilizaron un índice compuesto de privación socioeconómica como indicador socioeconómico y otros indicadores simples. Como indicador de mortalidad se usó la razón de mortalidad estandarizada suavizada, calculada utilizando el modelo jerárquico bayesiano propuesto por Besag, York y Mollié. Para analizar la evolución de las desigualdades socioeconómicas se utilizó un modelo de regresión ecológico que incluía el indicador socioeconómico, el periodo y la interacción de ambos. Resultados: Se observaron desigualdades significativas en la mortalidad en los hombres para casi todos los indicadores socioeconómicos, periodos y áreas urbanas. Sin embargo, no hubo cambios significativos en las desigualdades en el periodo de crisis. Aunque las desigualdades entre las mujeres fueron menos comunes, hubo un incremento significativo en las desigualdades en mortalidad en el periodo de crisis en términos de desempleo y del índice de privación en Praga y Estocolmo, respectivamente. Conclusiones: Futuros análisis deberán tener en cuenta el tiempo transcurrido entre la crisis y su efecto en la mortalidad, así como diferentes causas de mortalidad y el efecto diferencial entre géneros. ; This study is a part of the EURO-HEALTHY project (Shaping EUROpean policies to promote HEALTH equity) and has received funding from the European Union's Horizon 2020 research and innovation programme (Grant Agreement No 643398). Dagmar Dzúrová and Michala Lustigova were also supported by Charles University (UNCE/HUM 018).
Numerous studies have demonstrated the relationship between summer temperatures and increased heat-related deaths. Epidemiological analyses of the health effects of climate exposures usually rely on observations from the nearest weather station to assess exposure-response associations for geographically diverse populations. Urban climate models provide high-resolution spatial data that may potentially improve exposure estimates, but to date, they have not been extensively applied in epidemiological research. We investigated temperature-mortality relationships in the city of Barcelona, and whether estimates vary among districts. We considered georeferenced individual (natural) mortality data during the summer months (June-September) for the period 1992-2015. We extracted daily summer mean temperatures from a 100-m resolution simulation of the urban climate model (UrbClim). Summer hot days (above percentile 70) and reference (below percentile 30) temperatures were compared by using a conditional logistic regression model in a case crossover study design applied to all districts of Barcelona. Relative Risks (RR), and 95% Confidence Intervals (CI), of all-cause (natural) mortality and summer temperature were calculated for several population subgroups (age, sex and education level by districts). Hot days were associated with an increased risk of death (RR = 1.13; 95% CI = 1.10-1.16) and were significant in all population subgroups compared to the non-hot days. The risk ratio was higher among women (RR = 1.16; 95% CI= 1.12-1.21) and the elderly (RR = 1.18; 95% CI = 1.13-1.22). Individuals with primary education had similar risk (RR = 1.13; 95% CI = 1.08-1.18) than those without education (RR = 1.10; 95% CI= 1.05-1.15). Moreover, 6 out of 10 districts showed statistically significant associations, varying the risk ratio between 1.12 (95% CI = 1.03-1.21) in Sants-Montjuïc and 1.25 (95% CI = 1.14-1.38) in Sant Andreu. Findings identified vulnerable districts and suggested new insights to public health policy makers on how to develop district-specific strategies to reduce risks. ; J.B. gratefully acknowledges funding from the European Union's Horizon 2020 research and innovation programme under grant agreements No 865564 (European Research Council Consolidator Grant EARLY-ADAPT), 727852 (project Blue-Action) and 730004 (project PUCS), and from the Ministry of Science and Innovation (MCIU) under grant agreements No RYC2018-025446-I (programme Ramón y Cajal) and EUR2019-103822 (project EURO-ADAPT). V.I. acknowledges funding from the European Union's Horizon 2020 research and innovation programme under grant agreements 730004 (project PUCS). H.A. gratefully acknowledges funding from the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia (grant numbers B00391 [FI-2018], B100180 [FI-2019] and B200139 [FI-2020]).
The datasets generated and analysed during the current study are stored in the eurohealthydata repository (https://eurohealthydata.uc.pt) and are available from the corresponding author upon reasonable request. ; International audience ; on behalf of the EURO-HEALTHY investigators Abstract Background: Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement.
The datasets generated and analysed during the current study are stored in the eurohealthydata repository (https://eurohealthydata.uc.pt) and are available from the corresponding author upon reasonable request. ; International audience ; on behalf of the EURO-HEALTHY investigators Abstract Background: Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement.
The datasets generated and analysed during the current study are stored in the eurohealthydata repository (https://eurohealthydata.uc.pt) and are available from the corresponding author upon reasonable request. ; International audience ; on behalf of the EURO-HEALTHY investigators Abstract Background: Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement.
The datasets generated and analysed during the current study are stored in the eurohealthydata repository (https://eurohealthydata.uc.pt) and are available from the corresponding author upon reasonable request. ; International audience ; on behalf of the EURO-HEALTHY investigators Abstract Background: Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement.
The datasets generated and analysed during the current study are stored in the eurohealthydata repository (https://eurohealthydata.uc.pt) and are available from the corresponding author upon reasonable request. ; International audience ; on behalf of the EURO-HEALTHY investigators Abstract Background: Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement.
The datasets generated and analysed during the current study are stored in the eurohealthydata repository (https://eurohealthydata.uc.pt) and are available from the corresponding author upon reasonable request. ; International audience ; on behalf of the EURO-HEALTHY investigators Abstract Background: Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement.
The datasets generated and analysed during the current study are stored in the eurohealthydata repository (https://eurohealthydata.uc.pt) and are available from the corresponding author upon reasonable request. ; International audience ; on behalf of the EURO-HEALTHY investigators Abstract Background: Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement.
Background Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement. Methods Under the EURO-HEALTHY project, tools combining the technical elements of multi-criteria value models and the social elements of participatory processes were developed to measure health in multiple dimensions and to inform policies. The flagship tool is the Population Health Index (PHI), a multidimensional measure that evaluates health from the lens of equity in health determinants and health outcomes, further divided into sub-indices. Foresight tools for policy analysis were also developed, namely: (1) scenarios of future patterns of population health in Europe in 2030, combining group elicitation with the Extreme-World method and (2) a multi-criteria evaluation framework informing policy appraisal (case study of Lisbon). Finally, a WebGIS was built to map and communicate the results to wider audiences. Results The Population Health Index was applied to all European Union (EU) regions, indicating which regions are lagging behind and where investments are most needed to close the health gap. Three scenarios for 2030 were produced - (1) the 'Failing Europe' scenario (worst case/increasing inequalities), (2) the 'Sustainable Prosperity' scenario (best case/decreasing inequalities) and (3) the 'Being Stuck' scenario (the EU and Member States maintain the status quo). Finally, the policy appraisal exercise conducted in Lisbon illustrates which policies have higher potential to improve health and how their feasibility can change according to different scenarios. Conclusions The article makes a theoretical and practical contribution to the field of population health. Theoretically, it contributes to the conceptualisation of health in a broader sense by advancing a model able to integrate multiple aspects of health, including health outcomes and multisectoral determinants. Empirically, the model and tools are closely tied to what is measurable when using the EU context but offering opportunities to be upscaled to other settings. ; The EURO-HEALTHY project (Shaping EUROpean policies to promote HEALTHequity) has received funding from the European Union's Horizon 2020 re-search and innovation programme under Grant Agreement No. 643398. Add-itionally, this study was supported by the Centre of Studies in Geographyand Spatial Planning (CEGOT), funded by national funds through the Founda-tion for Science and Technology (FCT) under the reference UID/GEO/04084/2019. The authors Angela Freitas and Cláudia Costa are recipients of Individ-ual Doctoral Fellowships funded by national funds through the Foundationfor Science and Technology (FCT), under the references SFRH/BD/123091/2016 and SFRH/BD/132218/2017, respectively.
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. ; This research was conducted under the EURO-HEALTHY project, which was funded by the European Union's Horizon 2020 research and innovation programme, Grant Agreement No 643398, and received support from the Centre of Studies in Geography and Spatial Planning (CEGOT), funded by national funds through the Foundation for Science and Technology (FCT) under the reference UID/GEO/04084/2013.
