论文部分内容阅读
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 understand the spatial distribution of health status of the elderly in 31 provinces, autonomous regions and municipalities directly under the Central Government and the socio-economic factors in China and provide references for formulating relevant policies. Methods The health data of the elderly in the sixth national census in 2010 were collected to analyze the spatial distribution of health status of the elderly. Geo-weighted regression model (GWR) was used to analyze the related socio-economic factors. Results The spatial distribution of health status of the elderly in 31 provinces, autonomous regions and municipalities directly under the Central Government in China showed some spatial clustering. The Moran’s I index of global spatial autocorrelation was 0.132 (P <0.05), and the results of local spatial autocorrelation analysis . The hot spots with high (high-high) average scores of health for the elderly in the province and surrounding provinces are the cold spots in Jiangsu, Zhejiang and Fujian provinces where the average health scores of the elderly are low (low-low type) in themselves and in the surrounding areas Xinjiang and Tibet. The results of geo-weighted regression analysis showed that the GDP and medical institutions were the major socio-economic factors affecting the health status of the elderly. The R ~ 2 value was adjusted to 0.885. The eastern, central, northeastern and western regions The adjustment range of R ~ 2 was 0.822 ~ 0.878, 0.828 ~ 0.866, 0.890 ~ 0.907 and 0.852 ~ 0.941, respectively, while the adjusted R ~ 2 values in eastern and central part of China were lower than those in the west and northeast. The regional GDP and medical The number of institutions for two factors in the range of β values were 34.5 ~ 80.4 and 23.3 ~ 46.4. Conclusion The health status of the elderly in 31 provinces, autonomous regions and municipalities directly under the Central Government in China is spatially concentrated across provinces. The impact of GDP and health institutions on the health status of the elderly in different regions is different. Therefore, Sexual health promotion strategies for the elderly.