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黄河流域人口预期寿命的时空演化及影响因素分析
引用本文:张永凯,杨春月,张晚军,毕潇梅. 黄河流域人口预期寿命的时空演化及影响因素分析[J]. 地球信息科学学报, 2022, 24(5): 902-913. DOI: 10.12082/dqxxkx.2022.210692
作者姓名:张永凯  杨春月  张晚军  毕潇梅
作者单位:1.兰州财经大学农林经济管理学院,兰州 7300202.兰州财经大学经济学院,兰州 7300203.青海师范大学地理科学学院, 西宁 810008
基金项目:甘肃省“双一流”重点科研项目(GSSYLXM-06);兰州财经大学生态经济与区域发展科研创新团队支持计划(Lzufe-SRT202004);兰州财经大学丝绸经济研究院2021年度重点科研项目(JYYZ202101);兰州财经大学2019年度校级科研重点委托项目(Lzufe2019W-001)
摘    要:
健康人力资本对社会经济发展有重要的促进作用。以黄河流域71个地级行政单元为研究对象,利用变异系数、泰尔指数、空间自相关模型等方法,研究该流域人口预期寿命的时空演化特征,并根据地理探测器分析其影响因素。结果表明:(1) 2000—2019年,黄河流域人口预期寿命均值由69.99岁提升至76.96岁,整体呈上升趋势,但长期低于我国人口预期寿命均值;(2)人口预期寿命区域差异整体呈先增后降趋势,且地带间差异不断收敛,地带内差异与流域总体变化基本一致;(3)人口预期寿命存在明显空间集聚,但其空间自相关性不断减弱,且空间变化较大。具体而言,黄南藏族自治州、海南藏族自治州、甘南藏族自治州等藏区形成稳定性冷点区,山东省形成规模的稳定性热点区;(4)医疗卫生资源和自然条件对上游地区人口预期寿命影响最为显著;经济发展水平和环境污染对下游地区人口预期寿命解释力最强;教育水平是影响黄河流域各个地区人口预期寿命的重要因子。不同因子交互作用的解释力均高于单因子解释力,黄河流域人口预期寿命的空间差异是多因子共同作用的结果。

关 键 词:黄河流域  预期寿命  健康水平  时空演化  影响因素  泰尔指数  空间自相关  地理探测器
收稿时间:2021-10-31

Analysis on the Temporal and Spatial Evolution of Population Life Expectancy and Influencing Factors in the Yellow River Basin
ZHANG Yongkai,YANG Chunyue,ZHANG Wanjun,BI Xiaomei. Analysis on the Temporal and Spatial Evolution of Population Life Expectancy and Influencing Factors in the Yellow River Basin[J]. Geo-information Science, 2022, 24(5): 902-913. DOI: 10.12082/dqxxkx.2022.210692
Authors:ZHANG Yongkai  YANG Chunyue  ZHANG Wanjun  BI Xiaomei
Affiliation:1. School of Agriculture and Forestry Economics and Management, Lanzhou University of Finance and Economics, Lanzhou 730020, China2. School of Economics, Lanzhou University of Finance and Economics, Lanzhou 730020, China3. School of Geography Science, Qinghai Normal University, Xi'ning 810008, China
Abstract:
Healthy human capital plays an important role in promoting social and economic development. Taking 71 prefecture-level administrative units in the Yellow River Basin as the research area, using methods such as coefficient of variation, Theil index, and spatial autocorrelation model, the temporal and spatial evolution characteristics of population life expectancy in the basin are studied, and the influencing factors are analyzed based on geographic detectors. The results show as followed: (1) From 2000 to 2019, the average life expectancy of the population increased from 69.99 years to 76.96 years, showing an overall upward trend, but it has long been lower than the average life expectancy of our country's population; (2) The overall regional differences in life expectancy of the population in the Yellow River Basin shows a trend of increasing first and then decreasing, and the differences between the zones continue to converge. The differences within the zones are basically consistent with the overall changes in the basin; (3) There is obvious spatial agglomeration in the life expectancy of the population, but the spatial autocorrelation decreases and has large spatial variation. Specifically, the Huangnan Tibetan Autonomous Prefecture, Hainan Tibetan Autonomous Prefecture, Gannan Tibetan Autonomous Prefecture, and other Tibetan areas have formed stable cold spots, and the scale of Shandong Province forms a stability hot spot; (4) Medical and health resources and natural conditions have the most significant impact on the life expectancy of the population in the upper reaches; the level of economic development and environmental pollution have the strongest explanatory power for the life expectancy of the population in the lower reaches; the level of education is an important factor affecting the life expectancy of the population in all regions of the Yellow River Basin. The explanatory power of the interaction of different factors is higher than the explanatory power of a single factor. The spatial difference in the life expectancy of the population in the Yellow River Basin is the result of multiple factors.
Keywords:The Yellow River Basin  life expectancy  health level  temporal and spatial evolution  influencing factors  Theil index  spatial autocorrelation  Geodetector  
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