GCRF: Dynamics of Health & Environmental Inequalities in Hebei Province, China

GCRF：健康动态

基本信息

批准号：
ES/P003567/1
负责人：
Gwilym Pryce
金额：
$ 20.54万
依托单位：
University of Sheffield
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FP003567%2F1
关键词：
GCRF Dynamics Health Environmental Inequalities

项目摘要

Hebei province has some of the most polluted cities in the world. A key priority for the 74 million people who live there is to find ways of reducing air pollution and to address the associated social and health inequalities. It is crucial that the true cost of pollution is included in economic planning. The first step is to develop the necessary data infrastructure needed to provide the government a clear picture of how pollution, health and social deprivation are related and how they have changed over time. Our proposal offers an outstanding opportunity to make a step change in the quality and richness of evidence available to decision makers in Hebei Province. The potential for impact is exceptional due to: (a) the scale and importance of the problem we are seeking to address, and (b) access to senior policy makers made possible through collaboration with the Hebei Institute of Statistical Sciences (HISS). HISS plays a vital role in generating data and developing decision support tools for the Hebei government. Over the past year we have been forging a collaboration agreement with HISS. This is fortuitous in that it sets out a long-term vision for data access and research that will inform industrial restructuring and social policy in Hebei Province during a crucial phase in its development. The imperative for change has become all the more pressing since 2014 when the Premier of China declared "war" on air pollution. Because of Hebei's proximity to Beijing (Hebei essentially surrounds the capital), it has become a target for drastic measures to reduce air pollution. There is an urgent imperative, therefore, to provide an evidence base that will inform these decisions to make them as efficient and socially just as possible, maximising the benefits for the socially vulnerable. So, our proposed project is both timely, and highly relevant to the development challenges facing Hebei. The proposed programme of research will provide the Hebei government with robust estimates of the spatial dynamics of poverty, pollution and health. Ours will be the first attempt to construct deprivation indices for Hebei province and the first estimates anywhere in China of how the geography of deprivation has changed between the 2000 and 2010 Censuses. We will also provide a range of nuanced measures that capture how the spatial structure of poverty and segregation has evolved over time, revealing, for example, whether poverty has become less centralised in Hebei's key cities (an important trend in many Western conurbations but, as yet, an unexplored issue in China). We also want to help the Hebei government understand how pollution, health and deprivation are related by developing robust statistical models. This is vital if the true costs of pollution are to be included in economic and social policy decisions in a rational and systematic way. These research plans are made possible by the unprecedented opportunities for data access afforded through the collaboration between SMI and HISS. Together with the pressing policy issues noted above the newly available data also opens up an opportunity for world-leading methodological innovation. Our research team has pioneered statistical techniques for incorporating the effects of both spatial proximity and hierarchical structuring (e.g. individuals nested within neighbourhoods) in geographical data. The health variable we plan to model has particular features (bounded between 0 and 100). This motivates a novel extension of our methodology that will yield more reliable models of the relationship between health and pollution exposure. Our project will also establish a platform for exciting ambitious research opportunities in future, paving the way for further data linkage and potentially leading to a world-class longitudinal dataset that links individuals from multiple Censuses over time.

河北省拥有世界上一些污染最严重的城市。居住在那里的7400万人的关键优先事项是找到减少空气污染并解决相关社会和健康不平等现象的方法。至关重要的是，污染的真正成本包括在经济计划中。第一步是开发所需的必要数据基础设施，以清楚地向政府提供污染，健康和社会剥夺如何相关以及它们随着时间的变化的情况。我们的建议提供了一个出色的机会，可以改变赫比省决策者可用的质量和丰富性证据。由于：（a）我们寻求解决问题的规模和重要性，以及（b）通过与Hebei Hebei统计科学学院（HISS）合作，与高级政策制定者（HISS）合作，可能会产生影响。 HISS在生成数据和为Hebei政府开发决策支持工具方面起着至关重要的作用。在过去的一年中，我们一直与Hiss达成合作协议。这是偶然的，因为它为数据访问和研究提供了长期愿景，该愿景将在其发展的关键阶段为河北省的工业重组和社会政策提供信息。自2014年中国总理宣布空气污染“战争”以来，变革的必要性变得更加紧迫。由于赫比（Hebei）靠近北京（基本上围绕着资本），它已成为减少空气污染的巨大措施的目标。因此，迫切需要提供证据基础，以使这些决定使其尽可能高效和社会上的效率，从而最大程度地提高社会脆弱的好处。因此，我们提议的项目既及时，又与Hebei面临的发展挑战高度相关。拟议的研究计划将为Hebei政府提供对贫困，污染和健康空间动态的强有力估计。我们的人将是为赫比省建造剥夺指数的首次尝试，也是中国在2000年至2010年人口普查之间如何改变剥夺的任何地方的第一个估计。我们还将提供一系列细微的措施，以捕捉贫困和种族隔离的空间结构如何随着时间的流逝而发展，例如，揭示了贫困是否已经降低了赫比的主要城市（许多西方局面的重要趋势，但在中国尚未确定的问题上，贫困的一个重要趋势）。我们还希望帮助Hebei政府通过开发强大的统计模型来了解污染，健康和剥夺如何相关。如果要以理性和系统的方式将污染的真实成本包括在经济和社会政策决策中，这将是至关重要的。通过SMI和HIS之间的合作提供了空前的数据访问机会，使这些研究计划成为可能。与上面提到的紧迫政策问题一起，新可用的数据也为世界领先的方法论创新提供了机会。我们的研究团队开创了统计技术，以纳入空间近端和分层结构（例如，嵌套在社区内的个体）中的影响。我们计划建模的健康变量具有特定的特征（在0到100之间）。这激发了我们方法论的新型扩展，该扩展将产生健康与污染暴露之间关系的更可靠的模型。我们的项目还将建立一个平台，以激发未来的雄心勃勃的研究机会，为进一步的数据链接铺平了道路，并有可能导致世界一流的纵向数据集，该数据集将随着时间的推移链接到多个人口普查的个人。