县域就医可达性及其与居民健康相关性研究——以福建省永泰县为例

Accessibility to Primary Care and Its Correlation with People's Health——A Case Study of Yongtai County,Fujian Province

随着社会经济的发展,居民健康问题愈发成为政府决策部门与利益相关者关注的重要方面。为了更好的理解县域范围内居民就医可达性与健康状况的关系,本文以永泰县为例,运用E2SFCA模型,分析就医可达性的空间特征,并在此基础上,从全年龄段和分年龄段方面探讨就医空间可达性与居民健康的相关性。结果表明：（1）永泰县就可达性空间分布并不均衡,整体表现出以县城为中心的圈层结构,并具有高等级道路指向性;（2）可达性系数2.589 6以上的地区覆盖全县16.29%面积,1.409 3以下占65.29%。医疗资源匮乏,道路密度较低以及居民点分散是缺医范围较广的主要原因。（3）永泰县就医可达性变化幅度区域性差异显著,县中心周围等值线分布密集,边缘乡镇等值线分布较为稀疏,可达性衰减较慢。（4）相关性分析表明,永泰县就医可达性与居民健康存在显著负相关,但就医可达性与居民健康的相关性分年龄段差异明显,即相关性在15~65岁年龄组显著,在0~14岁和65岁以上年龄组不存在相关性。

with the development of society and economy, the governmental decision-making department and stakeholders have brought much more into focus on people＇s health. To better understand the relationship of people＇s accessibility to primary care and their health status, the thesis uses E2SFCA model and takes the Yongtai County as the case to analyze the spatial feature of the accessibility to primary care. Furthermore, the correlation of people＇s accessibility to primary care and health of all ages and different ages is explored. The result indicates that. （1）There are uneven distributions in the accessibility to primary care in the Yongtai County. The whole spatial distribution is like a con- centric circle of the core of the county town, and presents the indication of high--grade road. （2）The area where the accessibility coefficient is above 2.5896 covers 16.29% of the Yongtai County, while the area where the accessibility coefficient is above 1.4093 covers 65.29%. The deficit medical resource, the low road density and the dispersed population settlements are the major reasons of the vast area lacking the access to primary care. （3）The accessibility variance is regionally significant, and isolines in county or town are dense, while isolines in the remote townships are much sparser, so its accessibility is slower in decaying. （4）The correlation analysis indicates that. the accessibility to primary care has a significant negative correlation with people＇s health. But the correlation is different at different ages. The correlation is significant at age 15 to 65, while there are no correlation between 0 to 14 and above 65 of age.