System-science Informed Public Health and Economic Research for Non-communicable Disease Prevention (the SIPHER Consortium)

问题有强有力的证据表明，我们成长、生活、工作和年龄所处的社会和经济条件比我们的生活方式选择在更大程度上决定了我们的健康。这些健康的社会决定因素，如收入、优质住房、教育或工作，在社会中分配不均，从而导致健康不平等。然而，我们对具体政策如何影响社会条件以预防健康不良和减少健康不平等知之甚少。此外，健康的大多数社会决定因素是除“健康”以外的政策部门的责任，这意味着决策者如果要对健康产生重大影响，就需要在其所有政策中促进健康。siphher将提供新的科学证据和方法，以支持这种从“卫生政策”向“健康公共政策”的转变。我们将与三个地方、区域和国家层面的政策伙伴合作，解决他们高于平均水平的慢性疾病负担和持续的健康不平等：谢菲尔德市议会、大曼彻斯特联合管理局和苏格兰政府。我们将把重点放在四项共同商定的促进健康的政策优先事项上：——创造更公平的经济——促进心理健康——提供负担得起的高质量住房——防止困难童年的长期影响。上述每个政策领域都是一个复杂的政治系统，具有许多相互竞争的优先事项，其中一个部门（例如住房）的政策选择可能对其他部门（例如贫困）产生巨大的意想不到的影响。通常没有“正确”的解决方案，因为不同结果之间的妥协需要价值判断。这意味着，要评估一项政策在健康方面的真正效益和成本，就需要在广泛的可能结果范围内评估政策影响及其相互依存关系。然而，没有一个政策制定者了解整个体系，未来的经济和政治发展是不确定的。持续监测政策和其他系统变化的预期和意外影响至关重要，因此可以修改或放弃失败的政策。我们建议使用复杂系统建模，这是为了理解和预测复杂系统中可能发生的事情，给出了对未来发展的不同合理假设。我们的模型将以每个政策领域的最佳可用数据和先前研究为基础。我们关于广泛结果中可能的政策影响的新证据将帮助政策伙伴根据不同结果对他们的重要性（例如改善健康或经济增长）在备选政策之间做出决定。我们将开发支持工具，使预测可视化，确定在竞争结果之间实现预期平衡的政策，并在新信息出现时更新建议。虽然这些方法对公共卫生政策来说是新的，但在工程和气候科学领域已经得到了证实。我们will1。与政策伙伴合作，了解政策体系和证据需求2。2 .汇集关于每个政策系统的现有数据和证据（例如，政策与结果之间的联系，结果之间的相互依赖关系）。在并非所有结果都能实现的情况下，探索公民对优先次序的偏好。在计算机模型中将政策及其对健康和非健康的影响联系起来，以分析长期的收益和成本5。建立一个互动工具，以帮助政策决策，为宣传行动提供信息，并支持政治辩论。我们将为政策制定者提供一种新的方法，使他们能够估计卫生部门以外实施的政策的卫生相关成本和效益。这将有助于我们的合作伙伴和其他希望评估如何利用稀缺的公共部门资源，以最大限度地从其所有活动中获得健康和福祉效益的人。

THE PROBLEMThere is strong evidence that the social and economic conditions in which we grow, live, work and age determine our health to a much larger degree than lifestyle choices. These social determinants of health, such as income, good quality homes, education or work, are not distributed equally in society, which leads to health inequalities. However, we know very little about how specific policies influence the social conditions to prevent ill health and reduce health inequalities. Also, most social determinants of health are the responsibility of policy sectors other than "health", which means policymakers need to promote health in ALL their policies if they are to have a big impact on health. SIPHER will provide new scientific evidence and methods to support such a shift from "health policy" to "healthy public policy".OUR POLICY FOCUSWe will work with three policy partners at local, regional and national level to tackle their above-average chronic disease burden and persistent health inequalities: Sheffield City Council, Greater Manchester Combined Authority and Scottish Government. We will focus on four jointly agreed policy priorities for good health:- Creating a fairer economy- Promoting mental wellbeing- Providing affordable, good quality housing- Preventing long-term effects of difficult childhoods.OUR COMPLEX SYSTEMS SCIENCE APPROACHEach of the above policy areas is a complex political system with many competing priorities, where policy choices in one sector (e.g. housing) can have large unintended effects in others (e.g. poverty). There is often no "correct" solution because compromises between different outcomes require value judgements. This means that to assess the true benefits and costs of a policy in relation to health, policy effects and their interdependencies need to be assessed across a wide range of possible outcomes. However, no policymaker has knowledge of the whole system and future economic and political developments are uncertain. Ongoing monitoring of expected and unexpected effects of policies and other system changes is crucial so failing policies can be revised or dropped.We propose to use complex systems modelling, which has been developed to understand and make projections of what might happen in complex systems given different plausible assumptions about future developments. Our models will be underpinned by the best available data and prior research in each policy area. Our new evidence about likely policy effects across a wide range of outcomes will help policy partners decide between alternative policies, depending on how important different outcomes are to them (e.g. improving health or economic growth). We will develop support tools that can visualise the forecasts, identify policies that achieve the desired balance between competing outcomes and update recommendations when new information emerges. Whilst new to public health policy, these methods are well-established in engineering and climate science.We will1. Work with policy partners to understand the policy systems and evidence needs2. Bring together existing data and evidence on each policy system (e.g. links between policies and outcomes, interdependencies between outcomes)3. Explore citizens' preferences for prioritising when not all outcomes can be achieved4. Link policies and their health and non-health effects in computer models to analyse benefits and costs over time5. Build an interactive tool to help policy decision-making, inform advocacy action and support political debate.SIPHER's MAIN OUTCOMEWe will provide policymakers with a new methodology that allows them to estimate the health-related costs and benefits of policies that are implemented outside the health sector. This will be useful to our partners, and others, who want to assess how scarce public sector resources can be spent to maximise the health and wellbeing benefits from all their activities.