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.
