Spatial differentiation and key determinants of health-related well-being in Tameside and Glossop: geo-visualisation and multi-level spatial modelling

Tameside 和 Glossop 的空间分异和健康相关福祉的关键决定因素：地理可视化和多层次空间建模

• 批准号: 2886163
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2886163
• 关键词: Spatial; differentiation; key; determinants; health

This proposed study aims to bridge the above identified knowledge gaps by systematically examining the key determinants, and their interrelations, over differential health-related well-being in urban neighbourhoods from a human-environment perspective. The study will greatly benefit from gaining access to different geo-referenced health datasets provided by the collaborative partner and fostering inter-disciplinary research between planning academics and public health practitioners. The proposed study will address two main questions: how can we understand the spatially variated patterns of health related well-being across different neighbourhoods; and how different dimensions of determinants are interrelated and impact on health-related well-being of residents in different neighbourhoods?There are five key research objectives:(1) To develop a conceptual framework that guides our theoretical understanding and empirical modelling of key determinants (under different dimensions) and their interrelations on health-related well-being, both physical and emotional, by adopting a salutogenic approach that focuses on the human-environment perspective. (2) To operationalise multi-variate measures of key health-related well-being determinants by collating, validating and integrating relevant data sources and indicators from different geo-referenced datasets and population/patient surveys.(3) To establish the variegated geographic patterns and temporal change of different chronic diseases and health outcomes across different neighbourhoods and to understand their spatial correlations with the different health-related determinants via GIS mapping and spatial clustering analysis. (4) To apply multi-level spatial modelling framework to establish the interrelations among different dimensions of determinants over different spatial levels and to establish their relative importance in explaining differential health-related well-being of residents in different neighbourhoods.(5) To draw out the evidence-base to inform policy and practice development over the tackling of health inequalities issues and to foster joint working in local authorities and combined authorities to reduce health inequalities in and beyond the case study area.Tameside and Glossop, where our collaborative partner operates, is the case study area. While the case study area consists of neighbourhoods with varied socio-spatial contexts, residents in many neighbourhoods suffer from lower life expectancy and other chronic diseases and live in the country's 10% most deprived neighbourhoods

这项拟议的研究旨在通过系统地检查关键决定因素及其相互关系来弥合上述知识差距，从人类环境的角度来看，城市社区中与健康相关的福祉。这项研究将从合作伙伴提供的不同地理参考的健康数据集并促进计划学者与公共卫生从业人员之间的跨学科研究中获得大大受益。拟议的研究将解决两个主要问题：我们如何了解不同社区的健康相关福祉的空间变化模式；以及决定因素的不同方面是如何相互关联的，并对不同社区中居民与健康相关的福祉的影响？有五个关键的研究目标：（1）开发一个概念框架，指导我们的理论理解和主要决定因素的理论理解和经验建模（在不同的维度下）及其在与健康相关的健康方面的相互关系，无论是身体和情感的，都采用了一种敬意的方法，该方法侧重于人类环境的观点。 （2）通过整理，验证和整合来自不同地理参考的数据集以及人口/患者调查的相关数据源和指标的关键健康相关福祉决定因素的多变量量度。（3）建立变异的地理模式模式以及不同社区之间不同慢性疾病和健康结果的时间变化，并通过GIS映射和空间聚类分析来了解其与不同与健康相关的决定因素的空间相关性。 （4）应用多级空间建模框架来在不同空间层面上建立决定因素的不同维度之间的相互关系，并确定它们在解释不同社区中与差异健康相关的福利方面的相对重要性。提供证据基础，以告知政策和实践制定有关解决健康不平等问题的问题，并促进在地方当局工作的联合，并联合当局减少案例研究区域内外的健康不平等。Tamesideand Grossop，我们的协作合作伙伴在这里运作，是案例研究领域。案例研究区域由社区各种环境组成，但许多社区的居民患有寿命较低和其他慢性疾病，并生活在该国10％的最贫困的社区中