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Spatiotemporal matching between medical resources and population ageing in China from 2008 to 2017

机译:2008年至2017年中国医疗资源与人口老龄化之间的时空匹配

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Globally, the increasingly severe population ageing issue has been creating challenges in terms of medical resource allocation and public health policies. The aim of this study is to address the space-time trends of the population-ageing rate (PAR), the number of medical resources per thousand residents (NMRTR) in mainland China in the past 10?years, and to investigate the spatial and temporal matching between the PAR and NMRTR in mainland China. The Bayesian space-time hierarchy model was employed to investigate the spatiotemporal variation of PAR and NMRTR in mainland China over the past 10?years. Subsequently, a Bayesian Geo-Detector model was developed to evaluate the spatial and temporal matching levels between PAR and NMRTR at national level. The matching odds ratio (OR) index proposed in this paper was applied to measure the matching levels between the two terms in each provincial area. The Chinese spatial and temporal matching q-statistic values between the PAR and three vital types of NMRTR were all less than 0.45. Only the spatial matching Bayesian q-statistic values between the PAR and the number of beds in hospital reached 0.42 (95% credible interval: 0.37, 0.48) nationwide. Chongqing and Guizhou located in southwest China had the highest spatial and temporal matching ORs, respectively, between the PAR and the three types of NMRTR. The spatial pattern of the spatial and temporal matching ORs between the PAR and NMRTR in mainland China exhibited distinct geographical features, but the geographical structure of the spatial matching differed from that of the temporal matching between the PAR and NMRTR. The spatial and temporal matching degrees between the PAR and NMRTR in mainland China were generally very low. The provincial regions with high PAR largely experienced relatively low spatial matching levels between the PAR and NMRTR, and vice versa. The geographical pattern of the temporal matching between the PAR and NMRTR exhibited the feature of north-south differentiation.
机译:在全球范围内,人口越来越严重的老龄化问题在医疗资源配置和公共卫生政策方面都在创造挑战。本研究的目的是解决人口衰老率(PAR)的时空趋势(PAR),过去10年内中国大陆居民(NMRTR)的医疗资源数量(NMRTR),并调查空间和中国大陆的PAR和NMRTR之间的时间匹配。贝叶斯时空层次结构模型被用来调查中国大陆在中国大陆的Spatibalerate术变异在过去的10年里。随后,开发了贝叶斯地质探测器模型,以评估国家一级的PAR和NMRTR之间的空间和时间匹配水平。本文提出的匹配赔率比(或)指数被应用于测量每个省级区域的两种术语之间的匹配水平。 PAR和三种重要类型NMRTR之间的中文空间和时间匹配Q统计值均小于0.45。只有平板匹配的贝叶斯Q统计值,医院的床位数达到0.42(可靠的间隔95%:0.37,0.48)。重庆和贵州位于中国西南部的空间和时间匹配或分别在帕特和三种类型的NMRTR之间。中国大陆的PAR和NMRTR之间的空间和时间匹配的空间模式表现出不同的地理特征,但空间匹配的地理结构与PAR和NMRTR之间的时间匹配不同。中国大陆的PAR和NMRTR之间的空间和时间匹配程度通常非常低。 Par和NMRTR之间具有高比例的省级地区在很大程度上经历了相对较低的空间匹配水平,反之亦然。 PAR和NMRTR之间的时间匹配的地理模式表现出南北区别的特征。

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