Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors
BackgroundCurrently, 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 consu...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2022.954247/full |
| _version_ | 1811238508241616896 |
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| author | Xiaodan Bai Xiyu Zhang Hongping Shi Guihong Geng Bing Wu Yongqiang Lai Wenjing Xiang Yanjie Wang Yu Cao Baoguo Shi Ye Li |
| author_facet | Xiaodan Bai Xiyu Zhang Hongping Shi Guihong Geng Bing Wu Yongqiang Lai Wenjing Xiang Yanjie Wang Yu Cao Baoguo Shi Ye Li |
| author_sort | Xiaodan Bai |
| collection | DOAJ |
| description | BackgroundCurrently, 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.MethodsA 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.ResultsThe 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.ConclusionThe 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. |
| first_indexed | 2024-04-12T12:42:56Z |
| format | Article |
| id | doaj.art-5d27cd6d39484c44a7fb4bd65c24ee67 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-04-12T12:42:56Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-5d27cd6d39484c44a7fb4bd65c24ee672022-12-22T03:32:44ZengFrontiers Media S.A.Frontiers in Public Health2296-25652022-10-011010.3389/fpubh.2022.954247954247Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factorsXiaodan Bai0Xiyu Zhang1Hongping Shi2Guihong Geng3Bing Wu4Yongqiang Lai5Wenjing Xiang6Yanjie Wang7Yu Cao8Baoguo Shi9Ye Li10Department of Economics, School of Economics, Minzu University of China, Beijing, ChinaResearch Center of Health Policy and Management, School of Health Management, Harbin Medical University, Harbin, ChinaDepartment of Oncology, Heze Municipal Hospital, Heze, ChinaDepartment of Economics, School of Economics, Minzu University of China, Beijing, ChinaResearch Center of Health Policy and Management, School of Health Management, Harbin Medical University, Harbin, ChinaResearch Center of Health Policy and Management, School of Health Management, Harbin Medical University, Harbin, ChinaDepartment of Economics, School of Economics, Minzu University of China, Beijing, ChinaDepartment of Economics, School of Economics, Minzu University of China, Beijing, ChinaDepartment of Economics, School of Economics, Minzu University of China, Beijing, ChinaDepartment of Economics, School of Economics, Minzu University of China, Beijing, ChinaResearch Center of Health Policy and Management, School of Health Management, Harbin Medical University, Harbin, ChinaBackgroundCurrently, 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.MethodsA 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.ResultsThe 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.ConclusionThe 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.https://www.frontiersin.org/articles/10.3389/fpubh.2022.954247/fullbreast cancer scalelight at nightmacro factorsgeographically and temporally weighted regression modeltemporal and spatial heterogeneity |
| spellingShingle | Xiaodan Bai Xiyu Zhang Hongping Shi Guihong Geng Bing Wu Yongqiang Lai Wenjing Xiang Yanjie Wang Yu Cao Baoguo Shi Ye Li Government drivers of breast cancer prevention: A spatiotemporal analysis based on the association between breast cancer and macro factors Frontiers in Public Health breast cancer scale light at night macro factors geographically and temporally weighted regression model temporal and spatial heterogeneity |
| 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 | breast cancer scale light at night macro factors geographically and temporally weighted regression model temporal and spatial heterogeneity |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2022.954247/full |
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