From urban neighbourhood heterogeneities to health inequalities: social mechanisms, environmental exposures and their interaction

健康遵循社会梯度：低收入或低教育水平的人比富裕的人健康更差，死亡率更高。但健康并不只由个人层面的因素决定。在以前的工作中，我们表明，在小区域一级(例如，在城市社区)运作的因素发挥着独立的作用。虽然到目前为止，邻里异质性和健康不平等之间在小区域一级的联系是众所周知的，但作为这种联系基础的个人一级的社会机制还没有完全了解。此外，环境暴露还会影响健康，并可能与社会机制相互作用。在此，我们提出了一种跨学科的方法(流行病学-社会学)，以首先建立对该问题的联合理论理解。然后，我们将使用创新的方法(地理空间统计，它增加了分层模型中遗漏的空间维度)来定义以自我为中心的社区。这样，社区与健康有关的面积可以随所涉的社会机制和/或环境暴露而变化，而不依赖于任意的行政边界。我们将使用这种方法来分析现有的纵向数据集，以创建关于暴露和社会机制及其相互作用的新的经验证据，这些机制导致从邻里异质性到健康不平等。因此，我们进一步提供了理论基础，并提供了新的方法/工具，以(A)在可能的第二项目阶段收集新的、针对具体问题的经验数据，以及(B)开发以证据为基础的干预措施，以支持弱势地区。鉴于人们在经济上或族裔上选择进入可能对其健康有害的社区，这一问题与政治和公共卫生高度相关。

Health follows a social gradient: persons with low income or low education levels have worse health and a higher mortality than those who are better off. But health is not determined only by individual-level factors. In previous work we showed that factors operating at the small-area level (e.g. in urban neighbourhoods) play an independent role. Although the association at the small-area level between neighbourhood heterogeneities and health inequalities is by now well known, the social mechanisms at the level of the individual, which underlie this association, are not yet fully understood. Moreover, environmental exposures also affect health and may interact with the social mechanisms.Here we propose an interdisciplinary approach (epidemiology-sociology) to first establish a joint theoretical understanding of the problem. We will then employ innovative methods (geo-spatial statistics, which add the spatial dimension missed in hierarchical models) to define ego-centred neighbourhoods. In this way the health-relevant size of a neighbourhood can vary with the social mechanism and/or the environmental exposure in question and is not dependent on arbitrary administrative borders. We will use this approach to analyse existing longitudinal data sets to create new empirical evidence regarding exposures and social mechanisms and their interaction, which lead from neighbourhood heterogeneities to health inequalities. We thus further inform the theoretical foundation and offer new methods/tools for (a) collecting new, problem-specific empirical data in a possible second project phase and (b) developing evidence-based interventions to support disadvantaged areas. Given the strong economic or ethnic selection of people into neighbourhoods that may be harmful to their health, this issue is highly relevant to politics and public health.