[1]肖 嵩 莫春宝 何开连 罗婷玉 勾若宇 曹 亮 李 友.广西某少数民族自治县人口老龄化水平分析及预测[J].大众科技,2022,24(10):172-176.
 Analysis and Forecast of Population Aging Level in a Minority Autonomous County in Guangxi[J].Popular Science & Technology,2022,24(10):172-176.
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广西某少数民族自治县人口老龄化水平 分析及预测()
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《大众科技》[ISSN:1008-1151/CN:45-1235/N]

卷:
24
期数:
2022年10
页码:
172-176
栏目:
社会科学研究
出版日期:
2022-10-20

文章信息/Info

Title:
Analysis and Forecast of Population Aging Level in a Minority Autonomous County in Guangxi
作者:
肖 嵩 莫春宝 何开连 罗婷玉 勾若宇 曹 亮 李 友 
(桂林医学院公共卫生学院,广西 桂林 541199)
关键词:
老化灰色预测模型GM(11)预测
Keywords:
ageing grey prediction model GM(11) forecast
文献标志码:
A
摘要:
目的:分析广西某人口的老龄化特征和趋势,为制定和调整人口政策提供依据。方法:搜集和整理1990年-2010年该县三次人口普查数据,对人口老龄化系数>60(%)、儿童系数(%)、中位数年龄(年)等老龄化相关指标进行计算和描述性分析,再利用灰色预测模型GM(1,1)对2020年各指标的值进行预测。结果:1990年-2010年,该县人口结构已由扩张型逐渐转变为收缩型,儿童少年数量明显降低,老年人口数量进一步增加,中青年人口成为主要部分;除了少年儿童系数、抚养比以及少儿抚养比逐年下降以外,其他指标均逐渐上升。模型精度检验表明,GM(1,1)预测模型达到了精度一级,具有良好的预测性能;截止到2020年该县各老龄化指标将进一步变化,变化较大的指标分别为UOI(2.97%)、老少比(103.54%)以及CH(7.626/10万)。结论:该县己经进入人口老龄化社会,人口老龄化的程度也在逐步加深。截止到2020年,全县已达到长寿区标准,老龄化形势严峻,因此当地政府应当更加重视老龄化问题,健全养老体系,发展老龄产业,以满足老龄化需求。
Abstract:
Objective: To analyze the the aging characteristics and trends of a certain population in Guangxi, and provide basis for the formulating and adjusting population policies. Methods: The data of the three census of the county from 1990 to 2010 were collected, and the aging population coefficient >60(%), juvenile coefficient (%), median age (years) and other aging related indexes were calculated and descriptive analysis was made. The grey prediction model GM(1,1) was used to predict the values of each index in 2020. Results: From 1990 to 2010, the population structure of the county changed from expansion type to contraction type gradually, the significantly decreasing number of children and teenager, the futher increasing number of elderly population, and middle-aged and young who become a main part of the population. In addition to the juvenile child coefficient, dependency ratio and child dependency ratio decreased year by year, the other indexes increased gradually. The accuracy test of modle showed that the GM(1,1) prediction model reached the first level of accuracy, and the prediction performance was good. By 2020, the aging indexes in this county would further change, with UOI (2.97%), the ratio of old to young (103.54%) and CH (7.626/100,000). Conclusion: The county has gotten into the aging society and the aging degree is deepening. By 2020, the whole county has reached the standard of longevity area, and the aging situation is severe. Therefore, the local government should pay more attention to the aging problem, improve the pension system, and develop the aging industry to meet the aging demand.

参考文献/References:

[1] 郝晓宁,胡鞍钢. 中国人口老龄化: 健康不安全及应对政策[J]. 中国人口·资源与环境,2010,20(3): 73-78. [2] 刘尚希,赵福昌,侯海波. 中国人口老龄化、经济增长与社会化改革[J]. 发展研究,2020(10): 4-9. [3] 黄翌. 长寿地区判别方法综合评价与适用性[J]. 中国老年学杂志,2019,39(15): 3840-3846. [4] 王丙刚,曲波,郭海强,等. 传染病预测的数学模型研究[J]. 中国卫生统计,2007(5): 536-540. [5] 祝丽玲,孟繁君,杨迪. 基于GM(1,1)模型对我国妇幼保健指标的预测[J]. 中华疾病控制杂志,2019,23(8): 977-980. [6] 刘思峰,曾波,刘解放,等. GM(1, 1)模型的几种基本形式及其适用范围研究[J]. 系统工程与电子技术,2014,36(3): 501-508. [7] 孙娜,许小珊,冯佳宁,等. ARIMA与GM(1,1)模型对我国肺结核年发病人数预测情况的比较[J]. 中国卫生统计,2019,36(1): 71-74. [8] 刘雁灵,曹文君,李菲. 新陈代谢GM(1,1)幂模型在病毒性肝炎发病率预测中的应用[J]. 中国卫生统计,2019,36(6): 854-856. [9] 宋强玲,零东智,莫云仙,等. 广西人口老龄化对卫生服务需求及利用的影响[J]. 中国老年学杂志,2016,36(24): 6273-6274. [10] 李静,吴美玲. 中国城乡人口老龄化发展质量: 差异和预测[J]. 宏观质量研究,2020,8(5): 1-13. [11] Yang J. An analysis of the longevous population in Bama[J]. Chinese Journal of Polymer Science, 1992, 4(4): 351-356. [12] 陈习琼. 基于六次人口普查数据的云南省人口老龄化分析[J]. 中国老年学杂志,2018,38(12): 3054-3057. [13] 李明. 基于GM(1,1)模型的我国人口老龄化预测[J]. 温州职业技术学院学报,2018,18(3): 42-45. [14] Wang S, Luo K, Liu Y, et al. Economic level and human longevity: Spatial and temporal variations and correlation analysis of per capita GDP and longevity indicators in China[J]. Archives of Gerontology and Geriatrics, 2015, 61(1): 93-102. [15] Wang L, Li Y, Li H, et al. Regional aging and longevity characteristics in China[J]. Archives of Gerontology and Geriatrics, 2016, 67: 153-159. [16] 王宁,张爽,曾庆均. 基于新陈代谢GM(1,1)模型的重庆市人口老龄化预测研究[J]. 西北人口,2017,38(1): 66-70. [17] 纪广月,梁劲. 广东省人口老龄化现状、特征及发展趋势预测研究[J]. 成都师范学院学报,2020,36(5): 100-104.

备注/Memo

备注/Memo:
【收稿日期】2022-06-14 【基金项目】桂林医学院博士启动基金(20501020021)。 【作者简介】肖嵩(1997-),女,桂林医学院公共卫生学院在读硕士研究生,研究方向为环境流行病学。 【通信作者】李友(1977-),女,桂林医学院公共卫生学院副教授,研究方向为环境流行病学。
更新日期/Last Update: 2023-01-04