Yingjun Nie, Yuanyan Ma, Xiaodong Li, Yankong Wu, Weixin Liu, Zhenke Tan, Jiahui Li, Ce Zhang, Chennan Lv, Ting Liu
{"title":"新冠肺炎在中国爆发期间的PA:一项横断面研究。","authors":"Yingjun Nie, Yuanyan Ma, Xiaodong Li, Yankong Wu, Weixin Liu, Zhenke Tan, Jiahui Li, Ce Zhang, Chennan Lv, Ting Liu","doi":"10.1007/s00521-021-06538-x","DOIUrl":null,"url":null,"abstract":"<p><p>COVID-19 has undergone several mutations and is still spreading in most countries now. PA has positive benefits in the prevention of COVID-19 infection and counteracting the negative physical and mental effects caused by COVID-19. However, relevant evidence has indicated a high prevalence of physical inactivity among the general population, which has worsened due to the outbreak of the pandemic, and there is a severe lack of exercise guidance and mitigation strategies to advance the knowledge and role of PA to improve physical and mental health in most countries during the epidemic. This study surveyed the effects of COVID-19 on PA in Chinese residents during the pandemic and provided important reference and evidence to inform policymakers and formulate policies and planning for health promotion and strengthening residents' PA during periods of public health emergencies. ANOVA, Kolmogorov-Smirnov, the chi-square test and Spearman correlation analysis were used for statistical analysis. A total of 14,715 participants were included. The results show that nearly 70% of Chinese residents had inadequate PA (95%CI 58.0%-82.19%) during the COVID-19 outbreak, which was more than double the global level (27.5%, 95%CI 25.0%-32.2%). The content, intensity, duration, and frequency of PA were all affected during the period of home isolation, and the types of PA may vary among different ages. The lack of physical facilities and cultural environment is the main factor affecting PA. However, there was no significant correlation between insufficient PA and the infection rate. During the period of home isolation and social distance of epidemic prevention, it is necessary to strengthen the scientific remote network monitoring and guidance for the process of PA in China.</p>","PeriodicalId":49766,"journal":{"name":"Neural Computing & Applications","volume":"35 19","pages":"13739-13754"},"PeriodicalIF":4.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485310/pdf/","citationCount":"2","resultStr":"{\"title\":\"PA during the COVID-19 outbreak in China: a cross-sectional study.\",\"authors\":\"Yingjun Nie, Yuanyan Ma, Xiaodong Li, Yankong Wu, Weixin Liu, Zhenke Tan, Jiahui Li, Ce Zhang, Chennan Lv, Ting Liu\",\"doi\":\"10.1007/s00521-021-06538-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>COVID-19 has undergone several mutations and is still spreading in most countries now. PA has positive benefits in the prevention of COVID-19 infection and counteracting the negative physical and mental effects caused by COVID-19. However, relevant evidence has indicated a high prevalence of physical inactivity among the general population, which has worsened due to the outbreak of the pandemic, and there is a severe lack of exercise guidance and mitigation strategies to advance the knowledge and role of PA to improve physical and mental health in most countries during the epidemic. This study surveyed the effects of COVID-19 on PA in Chinese residents during the pandemic and provided important reference and evidence to inform policymakers and formulate policies and planning for health promotion and strengthening residents' PA during periods of public health emergencies. ANOVA, Kolmogorov-Smirnov, the chi-square test and Spearman correlation analysis were used for statistical analysis. A total of 14,715 participants were included. The results show that nearly 70% of Chinese residents had inadequate PA (95%CI 58.0%-82.19%) during the COVID-19 outbreak, which was more than double the global level (27.5%, 95%CI 25.0%-32.2%). The content, intensity, duration, and frequency of PA were all affected during the period of home isolation, and the types of PA may vary among different ages. The lack of physical facilities and cultural environment is the main factor affecting PA. However, there was no significant correlation between insufficient PA and the infection rate. During the period of home isolation and social distance of epidemic prevention, it is necessary to strengthen the scientific remote network monitoring and guidance for the process of PA in China.</p>\",\"PeriodicalId\":49766,\"journal\":{\"name\":\"Neural Computing & Applications\",\"volume\":\"35 19\",\"pages\":\"13739-13754\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485310/pdf/\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neural Computing & Applications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s00521-021-06538-x\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/10/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Computing & Applications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s00521-021-06538-x","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/10/1 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
PA during the COVID-19 outbreak in China: a cross-sectional study.
COVID-19 has undergone several mutations and is still spreading in most countries now. PA has positive benefits in the prevention of COVID-19 infection and counteracting the negative physical and mental effects caused by COVID-19. However, relevant evidence has indicated a high prevalence of physical inactivity among the general population, which has worsened due to the outbreak of the pandemic, and there is a severe lack of exercise guidance and mitigation strategies to advance the knowledge and role of PA to improve physical and mental health in most countries during the epidemic. This study surveyed the effects of COVID-19 on PA in Chinese residents during the pandemic and provided important reference and evidence to inform policymakers and formulate policies and planning for health promotion and strengthening residents' PA during periods of public health emergencies. ANOVA, Kolmogorov-Smirnov, the chi-square test and Spearman correlation analysis were used for statistical analysis. A total of 14,715 participants were included. The results show that nearly 70% of Chinese residents had inadequate PA (95%CI 58.0%-82.19%) during the COVID-19 outbreak, which was more than double the global level (27.5%, 95%CI 25.0%-32.2%). The content, intensity, duration, and frequency of PA were all affected during the period of home isolation, and the types of PA may vary among different ages. The lack of physical facilities and cultural environment is the main factor affecting PA. However, there was no significant correlation between insufficient PA and the infection rate. During the period of home isolation and social distance of epidemic prevention, it is necessary to strengthen the scientific remote network monitoring and guidance for the process of PA in China.
期刊介绍:
Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems.
All items relevant to building practical systems are within its scope, including but not limited to:
-adaptive computing-
algorithms-
applicable neural networks theory-
applied statistics-
architectures-
artificial intelligence-
benchmarks-
case histories of innovative applications-
fuzzy logic-
genetic algorithms-
hardware implementations-
hybrid intelligent systems-
intelligent agents-
intelligent control systems-
intelligent diagnostics-
intelligent forecasting-
machine learning-
neural networks-
neuro-fuzzy systems-
pattern recognition-
performance measures-
self-learning systems-
software simulations-
supervised and unsupervised learning methods-
system engineering and integration.
Featured contributions fall into several categories: Original Articles, Review Articles, Book Reviews and Announcements.