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.

中文翻译：

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推进促进欧盟地区健康公平的工具：EURO-HEALTHY 项目。

背景技术人口健康测量被认为是支持公共卫生监测的适当工具。然而，仍然缺乏为政策评估和预测对健康公平的影响提供基础的工具。在地区不平等持续存在的背景下，确定哪些地区表现最好、哪些因素可能影响未来的健康结果以及哪些地区有改进的空间至关重要。方法 在欧洲健康项目下，开发了结合多标准价值模型的技术要素和参与过程的社会要素的工具，以从多个维度衡量健康并为政策提供信息。旗舰工具是人口健康指数（PHI），这是一种多维衡量标准，从健康决定因素和健康结果的公平性角度评估健康状况，并进一步分为子指数。还开发了用于政策分析的前瞻工具，即：(1) 2030 年欧洲人口健康未来模式的情景，将群体启发与极端世界方法相结合，以及 (2) 为政策评估提供信息的多标准评估框架（案例）里斯本研究）。最后，构建了 WebGIS 来绘制地图并将结果传达给更广泛的受众。结果 人口健康指数适用于所有欧盟 (EU) 地区，表明哪些地区落后以及哪些地区最需要投资来缩小健康差距。制定了 2030 年的三种情景 - (1) “失败的欧洲”情景（最坏情况/不平等加剧）、(2) “可持续繁荣”情景（最好情况/不平等减少）和 (3) “陷入困境”情景（欧盟和成员国维持现状）。最后，在里斯本进行的政策评估工作说明了哪些政策具有更大的改善健康的潜力，以及它们的可行性如何根据不同的情况而变化。结论 本文对人口健康领域做出了理论和实践贡献。从理论上讲，它通过推进能够整合健康多个方面（包括健康结果和多部门决定因素）的模型，有助于更广泛意义上的健康概念化。根据经验，该模型和工具与使用欧盟背景时可测量的内容密切相关，但提供了升级到其他环境的机会。