基于地理探测器的欠发达地区健康资源时空分异及影响因素研究

doi:10.12118/j.issn.1000–6060.2021.02.30

摘要/Abstract

摘要：

医疗卫生资源是健康服务体系的基础和保障,高水平、高均衡性的医疗卫生资源是人民健康的保障。以甘肃省为例,基于卫生资源集聚度和变异系数、基尼系数、泰尔指数及分解,分析2010—2017年甘肃省14个市、州医疗卫生资源水平及均衡性的差异,运用地理探测器模型分析影响因素。结果表明：（1） 2010—2017年甘肃省医疗卫生资源水平及其均衡性整体上升。（2）医疗卫生资源水平及均衡性分布呈现东南>西北的格局,经济较好的陇中、陇东地区优于其他地区,其中兰州市资源水平及均衡性最高。（3）甘肃省人均医疗卫生资源水平及均衡性要优于地均医疗卫生资源,河西地区由于面积广阔、人口集聚度相对较小,人均均衡性明显优于地均均衡性。（4）甘肃省整体医疗卫生资源水平差异逐渐减小,医疗卫生资源均衡性得到了较好的改善,同时其区域内差异减小、区域间差异逐渐增大,且河西地区和陇中地区的内部差异是甘肃省整体差异的主要贡献者。（5）经济水平是影响医疗卫生资源水平的主导因素,人均国内生产总值和人口老龄化与其他因子的交互作用的解释力较高,同时自然因素的解释力逐年上升。

关键词: 医疗卫生资源水平, 均衡性, 区域差异, 地理探测器

Abstract:

Medical resources are the foundation of a quality health service system which in turn ensures a safe and secure community, therefore, it is important to study regional differences in medical resources and identify the factors that influence them to optimize the planning and distribution of these resources for strategic deployment of the Healthy China Action Plan. Using Gansu Province, China as an example, the coefficient of variation, the Gini coefficient, the Theil index, and the form of decomposition as well as the agglomeration degree of health resources and spatiotemporal differences in the level and equilibrium of medical resources were analyzed for Gansu from 2010 to 2017. The factors affecting the spatial distribution of medical resources were identified using GeoDetector. The results reveal five important facts: (1) From 2010 to 2017, the level and equilibrium of medical resources in Gansu Province increased by 14.96%, which laid the foundation for equal access to basic public services, thereby improving the public service system. The growth rates of medical resources in Hexi, Longzhong, Longdong, and Longnan areas were 24.60%, 11.51%, 14.91%, and 12.28%, respectively, of which the Hexi area showed the most significant growth. (2) The level and equilibrium of allocation of medical resources presented a pattern of southeast superior to northwest. The level and equilibrium of medical resources in Longdong and Longzhong, which are areas of high economic status, were higher than the levels and equilibria in other areas, among which Lanzhou, Pingliang, and Longnan had relatively high equilibrium. (3) The level and equilibrium of medical resources per capita were better than those for individual geographic locales within Gansu Province, especially in the Hexi area because of its vast area and relatively small population which creates a per capita balance that is better than the average balance for the entire province. (4) The overall difference gradually decreased in Gansu Province over time, and consequently the balance of medical resources improved. At the same time, intraregional differences decreased but the regional difference gradually increased. The regional difference is the main contributor to the overall difference in Gansu. (5) Economic factors are the main factors impacting medical resources and the factors used to explain the interaction between the real GDP per capita, population aging, and other factors. The influence of natural factors on medical resources increased each year. The level of medical resources in regions of high economic status was relatively balanced, while remote areas had low levels of medical resources due to geographical and environmental constraints.

Key words: medical resources, equilibrium, regional differences, geodetectors

赵海莉,王启雯,朱立祥,李晓芹,田浩宇. 基于地理探测器的欠发达地区健康资源时空分异及影响因素研究[J]. 干旱区地理, 2021, 44(2): 594-603.

ZHAO Haili,WANG Qiwen,ZHU Lixiang,LI Xiaoqin,TIAN Haoyu. Spatial-temporal evolution and influencing factors of health resources in underdeveloped areas based on geodetectors[J]. Arid Land Geography, 2021, 44(2): 594-603.

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泰尔指数		2010年	2011年	2012年	2013年	2014年	2015年	2016年	2017年
差异	总差异	0.179	0.164	0.176	0.175	0.177	0.161	0.163	0.166
	区域间	0.085	0.080	0.080	0.080	0.086	0.085	0.093	0.094
	区域内	0.095	0.085	0.096	0.096	0.091	0.076	0.070	0.073
	河西	0.052	0.045	0.052	0.048	0.045	0.046	0.040	0.036
	陇中	0.019	0.018	0.019	0.017	0.015	0.012	0.011	0.016
	陇东	0.010	0.008	0.013	0.018	0.016	0.011	0.011	0.012
	陇南	0.014	0.013	0.012	0.013	0.015	0.007	0.008	0.008
贡献度/%	区域间	47.310	48.520	45.560	45.410	48.520	52.630	57.000	56.280
贡献度/%	区域内	52.690	51.480	54.440	54.590	51.480	47.370	43.000	43.720

目标层	要素层	指标层	数据来源/单位
医疗卫生资源配置影响因素	社会经济发展	x₁	统计年鉴/元
		x₂	统计年鉴/% 统计年鉴/% 统计年鉴/% 统计年鉴/% 统计年鉴/%
		x₃
	人口分布	x₄
	人口分布	x₅
	地形	x₆	GIS提取/°
	地形	x₇	GIS提取/m

年份	x₁	x₂	x₃	x₄	x₅	x₆	x₇
2010	0.800*	0.790**	0.089	0.873***	0.377	0.121	0.207
2011	0.787*	0.740**	0.318	0.877***	0.320	0.139	0.218
2012	0.738	0.848***	0.236	0.832**	0.520	0.107	0.195
2013	0.737	0.806**	0.583	0.796**	0.343	0.133	0.219
2014	0.697	0.827***	0.197	0.789**	0.448	0.136	0.212
2015	0.755	0.813***	0.432	0.835**	0.132	0.195	0.263
2016	0.822**	0.906***	0.300	0.847**	0.162	0.224	0.295
2017	0.858**	0.685	0.547	0.873***	0.093	0.303	0.250

2010年		2013年		2015年		2017年
交互因子	作用值	交互因子	作用值	交互因子	作用值	交互因子	作用值
x₂ ∩ x₅	1.000	x₁ ∩ x₅	1.000	x₃ ∩ x₅	1.000	x₁ ∩ x₂	0.992
x₄ ∩ x₅	0.999	x₄ ∩ x₅	1.000	x₁ ∩ x₅	0.999	x₂ ∩ x₄	0.992
x₁ ∩ x₅	0.989	x₄ ∩ x₆	0.979	x₄ ∩ x₅	0.996	x₄ ∩ x₅	0.988
x₁ ∩ x₃	0.982	x₃ ∩ x₅	0.976	x₃ ∩ x₄	0.989	x₃ ∩ x₄	0.980
x₃ ∩ x₄	0.982	x₂ ∩ x₆	0.953	x₂ ∩ x₅	0.960	x₂ ∩ x₃	0.960
x₂ ∩ x₄	0.962	x₃ ∩ x₄	0.946	x₂ ∩ x₄	0.952	x₁ ∩ x₅	0.959
x₁ ∩ x₆	0.949	x₂ ∩ x₄	0.943	x₄ ∩ x₆	0.946	x₅ ∩ x₆	0.952
x₁ ∩ x₂	0.942	x₁ ∩ x₂	0.940	x₁ ∩ x₃	0.945	x₅ ∩ x₇	0.952
x₂ ∩ x₃	0.938	x₂ ∩ x₅	0.937	x₅ ∩ x₆	0.941	x₂ ∩ x₆	0.934
x₁ ∩ x₇	0.934	x₄ ∩ x₇	0.934	x₅ ∩ x₇	0.941	x₂ ∩ x₇	0.934