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Evaluation and analysis of the projected population of China
The population has a significant influence on economic growth, energy consumption, and climate change. Many scholars and organizations have published projections for China's future population due to its substantial population amounts. However, these projections have not been evaluated or analyz...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8901741/ https://www.ncbi.nlm.nih.gov/pubmed/35256676 http://dx.doi.org/10.1038/s41598-022-07646-x |
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author | Dai, Kaixuan Shen, Shi Cheng, Changxiu |
author_facet | Dai, Kaixuan Shen, Shi Cheng, Changxiu |
author_sort | Dai, Kaixuan |
collection | PubMed |
description | The population has a significant influence on economic growth, energy consumption, and climate change. Many scholars and organizations have published projections for China's future population due to its substantial population amounts. However, these projections have not been evaluated or analyzed, which may lead confusion to extensional studies based on these datasets. This manuscript compares several China's projection datasets at multiscale and analyzes the impacting factors affecting projection accuracy. The results indicate that the slow of actual population growth rates from 2017 is earlier than most datasets projected. Therefore, the turning point of population decline probably comes rapidly before these datasets expected during 2024 and 2034. Furthermore, the projections do not reveal the population decline from 2010 in the Northeast provinces such as Jilin and Heilongjiang, and underrate the population increase in the southern provinces such as Guangdong and Chongqing. According to the results of regression models, the rate of population changes and the number of migrations people play a significant role in projection accuracy. These findings provide meaningful guidance for scholars to understand the uncertainty of those projection datasets. Moreover, for researchers performing population projections, our discoveries provide insights to increase the projection accuracy. |
format | Online Article Text |
id | pubmed-8901741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89017412022-03-08 Evaluation and analysis of the projected population of China Dai, Kaixuan Shen, Shi Cheng, Changxiu Sci Rep Article The population has a significant influence on economic growth, energy consumption, and climate change. Many scholars and organizations have published projections for China's future population due to its substantial population amounts. However, these projections have not been evaluated or analyzed, which may lead confusion to extensional studies based on these datasets. This manuscript compares several China's projection datasets at multiscale and analyzes the impacting factors affecting projection accuracy. The results indicate that the slow of actual population growth rates from 2017 is earlier than most datasets projected. Therefore, the turning point of population decline probably comes rapidly before these datasets expected during 2024 and 2034. Furthermore, the projections do not reveal the population decline from 2010 in the Northeast provinces such as Jilin and Heilongjiang, and underrate the population increase in the southern provinces such as Guangdong and Chongqing. According to the results of regression models, the rate of population changes and the number of migrations people play a significant role in projection accuracy. These findings provide meaningful guidance for scholars to understand the uncertainty of those projection datasets. Moreover, for researchers performing population projections, our discoveries provide insights to increase the projection accuracy. Nature Publishing Group UK 2022-03-07 /pmc/articles/PMC8901741/ /pubmed/35256676 http://dx.doi.org/10.1038/s41598-022-07646-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Dai, Kaixuan Shen, Shi Cheng, Changxiu Evaluation and analysis of the projected population of China |
title | Evaluation and analysis of the projected population of China |
title_full | Evaluation and analysis of the projected population of China |
title_fullStr | Evaluation and analysis of the projected population of China |
title_full_unstemmed | Evaluation and analysis of the projected population of China |
title_short | Evaluation and analysis of the projected population of China |
title_sort | evaluation and analysis of the projected population of china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8901741/ https://www.ncbi.nlm.nih.gov/pubmed/35256676 http://dx.doi.org/10.1038/s41598-022-07646-x |
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