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Urban and Rural Disparities of Personal Health Behaviors and the Influencing Factors During the COVID-19 Outbreak in China: Based on an Extended IMB Model

OBJECTIVE: Health behavior was conducive to control the coronavirus disease (COVID-19) epidemic. This study aimed to determine the differences in health behaviors and related factors among rural and urban residents in China. METHODS: From February 14 to 22, 2020, during the peak of the COVID-19 epid...

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Autores principales: Luo, Yetao, Yao, Lili, Hu, Ling, Zhou, Li, Yuan, Feng, Zhong, Xiaoni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985648/
https://www.ncbi.nlm.nih.gov/pubmed/33208220
http://dx.doi.org/10.1017/dmp.2020.457
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author Luo, Yetao
Yao, Lili
Hu, Ling
Zhou, Li
Yuan, Feng
Zhong, Xiaoni
author_facet Luo, Yetao
Yao, Lili
Hu, Ling
Zhou, Li
Yuan, Feng
Zhong, Xiaoni
author_sort Luo, Yetao
collection PubMed
description OBJECTIVE: Health behavior was conducive to control the coronavirus disease (COVID-19) epidemic. This study aimed to determine the differences in health behaviors and related factors among rural and urban residents in China. METHODS: From February 14 to 22, 2020, during the peak of the COVID-19 epidemic in China, a total of 2449 participants (1783 (72.81%) urban residents and 666 (27.19%) rural residents) were recruited by snowball sampling on WeChat and QQ social platforms, both owned by Tencent. Data were collected through the Web-questionnaire guided by an information–motivation–behavioral skills model. The multiple-group structural equation model was applied to analyze the factors. RESULTS: Rural residents had lower health behavior scores than urban residents, even after adjusting demographic characteristics (33.86 vs 34.29, P = 0.042; total score was 40). Motivational, behavioral skills, and stress had direct positive and negative influences on health behaviors of urban and rural residents. Information and positive perception of interventions had direct effects on health behaviors in rural residents, but not in urban residents. All the factors were mediated by behavioral skills in rural and urban residents. CONCLUSIONS: This study suggests that the government should pay attention to substantial rural and urban disparities and implement different COVID-19 prevention and intervention policies for health behaviors targeting rural and urban residents.
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spelling pubmed-79856482021-03-25 Urban and Rural Disparities of Personal Health Behaviors and the Influencing Factors During the COVID-19 Outbreak in China: Based on an Extended IMB Model Luo, Yetao Yao, Lili Hu, Ling Zhou, Li Yuan, Feng Zhong, Xiaoni Disaster Med Public Health Prep Brief Report OBJECTIVE: Health behavior was conducive to control the coronavirus disease (COVID-19) epidemic. This study aimed to determine the differences in health behaviors and related factors among rural and urban residents in China. METHODS: From February 14 to 22, 2020, during the peak of the COVID-19 epidemic in China, a total of 2449 participants (1783 (72.81%) urban residents and 666 (27.19%) rural residents) were recruited by snowball sampling on WeChat and QQ social platforms, both owned by Tencent. Data were collected through the Web-questionnaire guided by an information–motivation–behavioral skills model. The multiple-group structural equation model was applied to analyze the factors. RESULTS: Rural residents had lower health behavior scores than urban residents, even after adjusting demographic characteristics (33.86 vs 34.29, P = 0.042; total score was 40). Motivational, behavioral skills, and stress had direct positive and negative influences on health behaviors of urban and rural residents. Information and positive perception of interventions had direct effects on health behaviors in rural residents, but not in urban residents. All the factors were mediated by behavioral skills in rural and urban residents. CONCLUSIONS: This study suggests that the government should pay attention to substantial rural and urban disparities and implement different COVID-19 prevention and intervention policies for health behaviors targeting rural and urban residents. Cambridge University Press 2020-11-19 /pmc/articles/PMC7985648/ /pubmed/33208220 http://dx.doi.org/10.1017/dmp.2020.457 Text en © Society for Disaster Medicine and Public Health, Inc. 2020 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Brief Report
Luo, Yetao
Yao, Lili
Hu, Ling
Zhou, Li
Yuan, Feng
Zhong, Xiaoni
Urban and Rural Disparities of Personal Health Behaviors and the Influencing Factors During the COVID-19 Outbreak in China: Based on an Extended IMB Model
title Urban and Rural Disparities of Personal Health Behaviors and the Influencing Factors During the COVID-19 Outbreak in China: Based on an Extended IMB Model
title_full Urban and Rural Disparities of Personal Health Behaviors and the Influencing Factors During the COVID-19 Outbreak in China: Based on an Extended IMB Model
title_fullStr Urban and Rural Disparities of Personal Health Behaviors and the Influencing Factors During the COVID-19 Outbreak in China: Based on an Extended IMB Model
title_full_unstemmed Urban and Rural Disparities of Personal Health Behaviors and the Influencing Factors During the COVID-19 Outbreak in China: Based on an Extended IMB Model
title_short Urban and Rural Disparities of Personal Health Behaviors and the Influencing Factors During the COVID-19 Outbreak in China: Based on an Extended IMB Model
title_sort urban and rural disparities of personal health behaviors and the influencing factors during the covid-19 outbreak in china: based on an extended imb model
topic Brief Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985648/
https://www.ncbi.nlm.nih.gov/pubmed/33208220
http://dx.doi.org/10.1017/dmp.2020.457
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