School of Statistics, Shanxi University of Finance and Economics, Wucheng Road 696, Taiyuan, 030006, China.
First Hospital of Shanxi Medical University, Jiefang South Road 85, Taiyuan, 030001, China.
BMC Public Health. 2020 Jun 3;20(1):845. doi: 10.1186/s12889-020-08976-z.
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.
全球范围内,人口老龄化问题日益严重,给医疗资源配置和公共卫生政策带来了挑战。本研究旨在探讨中国内地过去 10 年人口老龄化率(PAR)和每千人口医疗资源数(NMRTR)的时空趋势,并分析中国内地 PAR 与 NMRTR 的时空匹配关系。
采用贝叶斯时空分层模型分析中国内地过去 10 年 PAR 和 NMRTR 的时空变化,采用贝叶斯地理探测器模型评价全国范围内 PAR 与 NMRTR 的时空匹配水平。文中提出匹配优势比(OR)指数,用以衡量各省级地区 PAR 与 NMRTR 之间的匹配程度。
PAR 与三种主要类型 NMRTR 的时空匹配 q 统计值均小于 0.45。仅全国范围内 PAR 与医院床位数的时空匹配贝叶斯 q 统计值达到 0.42(95%可信区间:0.37,0.48)。中国西南部的重庆和贵州在 PAR 与三种 NMRTR 之间的时空匹配 OR 值最高。中国内地 PAR 与 NMRTR 之间时空匹配 OR 值的空间格局具有明显的地理特征,但 PAR 与 NMRTR 之间时空匹配的地理结构与时间匹配不同。
中国内地 PAR 与 NMRTR 的时空匹配程度总体较低。PAR 较高的省级地区 PAR 与 NMRTR 之间的空间匹配水平较低,反之亦然。PAR 与 NMRTR 之间的时间匹配地理格局呈现南北分化的特征。