中国大陆地区老年人健康状况空间分布及社会经济影响因素

Spatial clustering and socio-economic influence factors of health status of elderly populations in China's Mainland

目的了解中国大陆31个省、自治区、直辖市老年人健康状况空间分布及社会经济影响因素,为制定相关政策提供参考依据。方法收集2010年第六次全国人口普查中老年人自评健康数据,分析老年人健康状况空间分布情况,并应用地理加权回归模型(GWR)分析其相关社会经济影响因素。结果中国大陆31个省、自治区、直辖市老年人健康状况分布存在一定的空间聚集性,以省际为单位计算全局空间自相关Moran's I指数为0.132(P<0.05),局部空间自相关分析结果显示,省份自身及周边省份老年人健康平均分均高(高-高型)的热点区域为江苏、浙江和福建,自身及周边地区老年人健康平均分均低(低-低型)的冷点区域为新疆和西藏;地理加权回归分析结果显示,国内生产总值和医疗机构数是影响老年人健康状况的主要社会经济因素,调整R^2值为0.885,其中东部、中部、东北部和西部地区调整R^2值范围分别为0.822~0.878、0.828~0.866、0.890~0.907和0.852~0.941,东部和中部部分地区的调整R^2值低于西部和东北部;各区域国内生产总值和医疗机构数2个因素的β值范围分别为34.5~80.4和23.3~46.4。结论中国大陆31个省、自治区、直辖市老年人健康状况分布存在省际间的空间聚集,在不同区域内国内生产总值和医疗机构数对老年人健康状况的影响不同,可据此制定具有针对性的老年人健康促进策略。

Objective To examine spatial clustering and socio-economic influence factors of health status of elderly populations in China's Mainland, and to provide references for the formulation of relevant policies. Methods Data on health status of elderly populations （aged 60 years and older） were extracted from the dataset of China＇s 6th National Population Census in 2010. The spatial clustering of health status of the older people was analyzed and geographically weighted regression （GWR） was applied to explore socio-economic influence factors of health status. Results The results showed that spatial aggregation existed in the distribution of health status of elderly population at province or mu- nicipality level ,with the Moran＇s I index of 0. 132. Jiangsu, Zhejiang, and Fujian province were the regions with high- high clustering and Xinjiang, Tibet were the regions with low-low clustering. GWR results showed that gross domestic production （GDP） and the number of medical institutions were the main social and economic factors influencing the health of the elderly, with the adjusted R2 of 0. 885. The adjusted R2 were 0. 822 - 0. 878 for the eastern,0. 828 - 0. 866 for the central, 0. 890 -0. 907 for the northeastern, and 0. 852 -0. 941 for the western region, respectively, with higher values for eastern and central regions and lower values in western and northeastern regions. The values of parameter β for GDP and the number of medical institutions ranged between 34. 5 - 80.4 for the eastern and central regions and 23.3 - 46.4 for the western and northeastern regions. Conclusion Spatial clustering of health status of older populations exits in China's Mainland. The role of c factors and health resources in different regions are different for the health of the elderly in various regions. The government should develop targeted health promotion strategies for the elderly