Using a Complex Systems Approach to Understanding Population Mental Health.

使用复杂的系统方法来了解人群心理健康。

• 批准号: MR/N014588/1
• 负责人: Daniel Lewis
• 金额: $ 35.05万
• 依托单位: London School of Hygiene & Tropical Medicine
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FN014588%2F1
• 关键词: Using; Complex; Systems; Approach; Understanding

There is a growing consensus that it is not just individual characteristics and behaviours that influence health and wellbeing, but the types of neighbourhoods we live in, and the opportunities they afford us. This consensus is reflected by published evidence of inequalities in people's life chances between different places, the Marmot review "Fair Society Healthy Lives" demonstrates by association that neighbourhoods that are more deprived also tend to have populations with lower life expectancies.The overall evidence for neighbourhood effects is somewhat limited, only recently has research begun to demonstrate an unambiguous association between neighbourhood and health. Health outcomes and behaviours studied have particularly focused on diet and physical activity, which have been linked to a range of neighbourhood contextual factors including access to green space, places to buy fresh fruit and vegetables (or conversely fast-food), and the 'walkability' of the built environment. Mental health and wellbeing has received markedly less focus, although some high quality studies have looked at the relationship between neighbourhood green space and wellbeing. Emerging epidemiological evidence has benefitted from researchers working across disciplines, particularly with geographers, in order to produce robust study designs. Nonetheless, evidence of a causal link between our changing neighbourhoods, and our changing health is rather less forthcoming, owing to the complexity of the social-ecological processes hypothesised to be taking place.This research project aims to make a significant contribution to empirical evidence for neighbourhood effects by applying 'systems thinking.' This means treating neighbourhoods as complex, dynamic multi-factorial processes, where existing research treats them as simple, stationary snapshots with limited depth. Specific training in 'Urban Informatics' will greatly augment my existing expertise in Geographic Information Science and Social Epidemiology, and give me the tools required to operationalise dynamic, rather than static, representations of neighbourhoods. Capturing how neighbourhoods change over time alongside how individuals change over time is fundamental to unpicking causality.In particular, the research will focus on the effects on mental health and wellbeing of people moving, expecting to move, or preferring to move, at both the neighbourhood scale, and the individual scale. We know that neighbourhoods are not equal, and yet in terms of population movement - people moving into or out of a neighbourhood - we tend to treat them equally. Studies have suggested that failing to account for this dynamic neighbourhood process - the residential movement of people - can have implications on our expectations for people's health through what are termed 'selection effects'. These neighbourhood compositional factors will be studied alongside contextual aspects of neighbourhoods, notably neighbourhood crime and disorder and neighbourhood economic insecurity, in order to explain how mental health and wellbeing is affected by neighbourhood social and environmental changes.This type of research is only just becoming possible, due to a range of complementary factors. Firstly, world-class training at New York University's Centre for Urban Science and Progress (NYU CUSP). Secondly, the availability of the UK's rich longitudinal "Understanding Society" survey data. Thirdly, the proliferation of open, and free government administrative data, and finally, the growing support from research councils in promoting 'Big Data' and informatics approaches. This fellowship takes advantage of all of these factors, with the hope of producing world-leading research on neighbourhoods and health.

越来越多的人认为，影响健康和福祉的不仅仅是个人特征和行为，还有我们居住的社区类型以及它们为我们提供的机会。这一共识反映在不同地方之间人们生活机会不平等的公开证据中，Marmot评论“公平社会健康生活”通过关联表明，更贫困的社区也往往有预期寿命较低的人口。研究的健康结果和行为特别关注饮食和身体活动，这与一系列邻里环境因素有关，包括获得绿色空间，购买新鲜水果和蔬菜的地方（或相反的快餐），以及建筑环境的“可步行性”。心理健康和幸福感受到的关注明显较少，尽管一些高质量的研究关注了邻里绿色空间和幸福感之间的关系。新兴的流行病学证据受益于跨学科的研究人员，特别是地理学家，以产生强大的研究设计。尽管如此，由于假设发生的社会生态过程的复杂性，我们不断变化的邻里之间的因果关系的证据，我们不断变化的健康是相当不容易的。本研究项目旨在通过应用“系统思维”的邻里效应的经验证据作出重大贡献。“这意味着将社区视为复杂，动态的多因素过程，现有的研究将其视为简单，深度有限的静态快照。在“城市信息学”的具体培训将大大增强我在地理信息科学和社会流行病学现有的专业知识，并给我所需的工具来操作动态，而不是静态，邻里的代表。了解社区如何随着时间的推移而变化，以及个人如何随着时间的推移而变化，是解开因果关系的基础。特别是，该研究将重点关注在社区规模和个人规模上移动，期望移动或更喜欢移动的人对心理健康和福祉的影响。我们知道，邻里之间并不平等，但在人口流动方面-人们迁入或迁出一个邻里-我们倾向于平等对待他们。研究表明，如果不考虑这种动态的邻里关系过程-人们的居住流动-可能会通过所谓的“选择效应”对我们对人们健康的期望产生影响。这些邻里构成因素将与邻里的背景方面一起研究，特别是邻里犯罪和混乱以及邻里经济不安全，以解释邻里社会和环境变化如何影响心理健康和福祉。由于一系列补充因素，这种类型的研究才刚刚成为可能。首先，在纽约大学城市科学与进步中心（NYU CUSP）接受世界一流的培训。其次，英国丰富的纵向“理解社会”调查数据。第三，开放和免费的政府行政数据的扩散，最后，研究委员会在促进“大数据”和信息学方法方面的支持越来越多。该奖学金利用所有这些因素，希望产生世界领先的邻里和健康研究。

项目成果

Health Geographies: A Critical Introduction

健康地理学：重要介绍

• 发表时间: 2017
• 作者: Brown