本研究根据我国制度背景下的城市空间与农村流动人口特点，借鉴欧美学术界提出的移民"空间区隔融合"理论与"健康的邻里效应"的理论与方法；研究我国农村流动人口亚群体在城市的空间分布状况及其与流动人口健康相关问题的关系。项目将通过应答推动抽样在成都市获取农村流动人口，记录每一名被调查者的个体坐标数据以建立地理信息数据库，调查其社会人口学状况、流动特征、自我报告的健康状况与城市卫生服务利用等信息，同时收集血糖与血压的客观生物学指标以建立属性数据库。综合空间数据与属性数据对资料进行分析，采用空间统计学最新发展出来的分析点状数据的方法，通过主题图，空间扫描，空间聚集分析等方法研究我国城市中不同亚群体流动人口的城市空间分布特征，健康状况与卫生服务状况及其联系。在相关研究的基础探讨将GIS应用于流动人口卫生管理与卫生政策方面的可行途径。

In the past 15 years, there has been a considerable development in the study on the effects of urban spatial context on health in Western industrialized countries. Studies have found that the features of neighborhoods are linked to health. The spatial characteristics of migration and their well-being (including health) have also been recognized in the Western literature. The migrants in China have increased dramatically to 260 million in past 30 years. Some spatial characteristics of migrants in China had been noticed since late 1990's, but until now data regarding migrants' spatial patterns in china are very limited, so is the relation to migrants' health. Based on migration-related 'segmented assimilation theory' and theory of 'neighborhoods effects on health', we assume that there are different social economic migrants groups in urban China and different groups have different spatial distributions which are linked with their health. This project will choose four symmetrical sampling sites in north, south, east and west part of Chengdu city, and use respondent driven sampling (RDS) to recruit rural to urban migrants. In addition to the social economic and health information, the coordinates of the respondents will be recorded. The spatial and attribute databases will be set up and integrated to analyze the relationship of migrants' spatial patterns, social economic status and health. The study will use thematic maps to describe the geographic distribution of the attribute data, and apply spatial overlay analysis to visualize the spatial association and differentiation. The Tango's Index for Spatial Clustering will be employed to test the spatial randomness, with the Spatial Scan Statistics identifying different cluster of subgroups. Eventually, the project expects to study the spatial relationship between migrants' urban contexts and health status, and provide suggestions for migration-related health policy making.