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Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors

BACKGROUND: Currently, breast cancer (BC) is ranked among the top malignant tumors in the world, and has attracted widespread attention. Compared with the traditional analysis on biological determinants of BC, this study focused on macro factors, including light at night (LAN), PM2.5, per capita con...

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Autores principales: Bai, Xiaodan, Zhang, Xiyu, Shi, Hongping, Geng, Guihong, Wu, Bing, Lai, Yongqiang, Xiang, Wenjing, Wang, Yanjie, Cao, Yu, Shi, Baoguo, Li, Ye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578696/
https://www.ncbi.nlm.nih.gov/pubmed/36268002
http://dx.doi.org/10.3389/fpubh.2022.954247
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author Bai, Xiaodan
Zhang, Xiyu
Shi, Hongping
Geng, Guihong
Wu, Bing
Lai, Yongqiang
Xiang, Wenjing
Wang, Yanjie
Cao, Yu
Shi, Baoguo
Li, Ye
author_facet Bai, Xiaodan
Zhang, Xiyu
Shi, Hongping
Geng, Guihong
Wu, Bing
Lai, Yongqiang
Xiang, Wenjing
Wang, Yanjie
Cao, Yu
Shi, Baoguo
Li, Ye
author_sort Bai, Xiaodan
collection PubMed
description BACKGROUND: Currently, breast cancer (BC) is ranked among the top malignant tumors in the world, and has attracted widespread attention. Compared with the traditional analysis on biological determinants of BC, this study focused on macro factors, including light at night (LAN), PM2.5, per capita consumption expenditure, economic density, population density, and number of medical beds, to provide targets for the government to implement BC interventions. METHODS: A total of 182 prefecture-level cities in China from 2013 to 2016 were selected as the sample of the study. The geographically and temporally weighted regression (GTWR) model was adopted to describe the spatiotemporal correlation between the scale of BC and macro factors. RESULTS: The results showed that the GTWR model can better reveal the spatiotemporal variation. In the temporal dimension, the fluctuations of the regression coefficients of each variable were significant. In the spatial dimension, the positive impacts of LAN, per capita consumption expenditure, population density and number of medical beds gradually increased from west to east, and the positive coefficient of PM2.5 gradually increased from north to south. The negative impact of economic density gradually increased from west to east. CONCLUSION: The fact that the degree of effect of each variable fluctuates over time reminds the government to pay continuous attention to BC prevention. The spatial heterogeneity features also urge the government to focus on different macro indicators in eastern and western China or southern and northern China. In other words, our research helps drive the government to center on key regions and take targeted measures to curb the rapid growth of BC.
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spelling pubmed-95786962022-10-19 Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors Bai, Xiaodan Zhang, Xiyu Shi, Hongping Geng, Guihong Wu, Bing Lai, Yongqiang Xiang, Wenjing Wang, Yanjie Cao, Yu Shi, Baoguo Li, Ye Front Public Health Public Health BACKGROUND: Currently, breast cancer (BC) is ranked among the top malignant tumors in the world, and has attracted widespread attention. Compared with the traditional analysis on biological determinants of BC, this study focused on macro factors, including light at night (LAN), PM2.5, per capita consumption expenditure, economic density, population density, and number of medical beds, to provide targets for the government to implement BC interventions. METHODS: A total of 182 prefecture-level cities in China from 2013 to 2016 were selected as the sample of the study. The geographically and temporally weighted regression (GTWR) model was adopted to describe the spatiotemporal correlation between the scale of BC and macro factors. RESULTS: The results showed that the GTWR model can better reveal the spatiotemporal variation. In the temporal dimension, the fluctuations of the regression coefficients of each variable were significant. In the spatial dimension, the positive impacts of LAN, per capita consumption expenditure, population density and number of medical beds gradually increased from west to east, and the positive coefficient of PM2.5 gradually increased from north to south. The negative impact of economic density gradually increased from west to east. CONCLUSION: The fact that the degree of effect of each variable fluctuates over time reminds the government to pay continuous attention to BC prevention. The spatial heterogeneity features also urge the government to focus on different macro indicators in eastern and western China or southern and northern China. In other words, our research helps drive the government to center on key regions and take targeted measures to curb the rapid growth of BC. Frontiers Media S.A. 2022-10-04 /pmc/articles/PMC9578696/ /pubmed/36268002 http://dx.doi.org/10.3389/fpubh.2022.954247 Text en Copyright © 2022 Bai, Zhang, Shi, Geng, Wu, Lai, Xiang, Wang, Cao, Shi and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Bai, Xiaodan
Zhang, Xiyu
Shi, Hongping
Geng, Guihong
Wu, Bing
Lai, Yongqiang
Xiang, Wenjing
Wang, Yanjie
Cao, Yu
Shi, Baoguo
Li, Ye
Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors
title Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors
title_full Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors
title_fullStr Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors
title_full_unstemmed Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors
title_short Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors
title_sort government drivers of breast cancer prevention: a spatiotemporal analysis based on the association between breast cancer and macro factors
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578696/
https://www.ncbi.nlm.nih.gov/pubmed/36268002
http://dx.doi.org/10.3389/fpubh.2022.954247
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