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research-article

The provincial trend of population aging in China – based on population expansion forecast formula

Authors: Lingyun Duan, Ziyuan Liu, Wen Yu, Wei Chen, Dongyan Jin, Yao Feng, Yu Wang, Jiajia Liu, Han Zhou, Suhua Sun, Ruixi DaiAuthors Info & Claims

Journal of Computational Methods in Sciences and Engineering, Volume 22, Issue 1

Pages 349 - 359

https://doi.org/10.3233/JCM-215630

Published: 01 January 2022 Publication History

Abstract

China is one of the countries that have entered the stage of population aging. At present, the phenomenon of aging population has become a widespread concern of the whole society. Scientific and accurate prediction of aging population will help relevant departments to formulate specific countermeasures. This paper uses the Yearbook of China’s 1% population sampling survey in 2015 and the data published by the National Bureau of statistics. Based on the basic population prediction formula, the population prediction formula is established by using the index extrapolation method to predict the population aging development trend of provinces and cities in China from 2020 to 2050. The results show that: China’s aging degree will continue to increase, the size of the elderly population will continue to increase, 2020–2030 will be a period of rapid growth of the national population aging, after then the aging ratio will decline. The government should formulate security countermeasures for the elderly from various aspects as soon as possible and actively respond to aging the population.

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Cited By

Shan Li Tan DYao BWang Z(2024)Fall Monitoring System Based on Wearable Device and Improved KNNAutomatic Control and Computer Sciences10.3103/S014641162470059758:4(366-378)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.3103/S0146411624700597
Cheng JGuo XYang J(2022)Prediction and Operation Design of Elderly Care Market Based on Multiple Linear Regression and Regional ClusteringProceedings of the 5th International Conference on Information Technologies and Electrical Engineering10.1145/3582935.3582966(183-188)Online publication date: 4-Nov-2022
https://dl.acm.org/doi/10.1145/3582935.3582966

Index Terms

The provincial trend of population aging in China – based on population expansion forecast formula
1. Applied computing

Index terms have been assigned to the content through auto-classification.

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cover image Journal of Computational Methods in Sciences and Engineering

Journal of Computational Methods in Sciences and Engineering Volume 22, Issue 1

2022

342 pages

ISSN:1472-7978

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© 2022 – IOS Press. All rights reserved.

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IOS Press

Netherlands

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Published: 01 January 2022

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Cited By

Shan Li Tan DYao BWang Z(2024)Fall Monitoring System Based on Wearable Device and Improved KNNAutomatic Control and Computer Sciences10.3103/S014641162470059758:4(366-378)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.3103/S0146411624700597
Cheng JGuo XYang J(2022)Prediction and Operation Design of Elderly Care Market Based on Multiple Linear Regression and Regional ClusteringProceedings of the 5th International Conference on Information Technologies and Electrical Engineering10.1145/3582935.3582966(183-188)Online publication date: 4-Nov-2022
https://dl.acm.org/doi/10.1145/3582935.3582966

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Affiliations

Lingyun Duan

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

Graduate School of Chinese Academy of Agricultural Sciences, Beijing, China

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Ziyuan Liu

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

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Wen Yu

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

Graduate School of Chinese Academy of Agricultural Sciences, Beijing, China

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Wei Chen

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

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Dongyan Jin

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

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Yao Feng

Bartlett School of Environment, Energy and Resources, University College London, London, UK

Department of Economics and Management, Beijing University of Technology, Beijing, China

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Yu Wang

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

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Jiajia Liu

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

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Han Zhou

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

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Suhua Sun

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

Graduate School of Chinese Academy of Agricultural Sciences, Beijing, China

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Ruixi Dai

Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs, Beijing, China

Key Laboratory of Intelligent Agricultural Early Warning Technology and System, Chinese Academy of Agricultural Sciences, Beijing, China

Beijing Engineering Research Center for Agricultural Monitoring and Early Warning, Beijing, China

Graduate School of Chinese Academy of Agricultural Sciences, Beijing, China

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