Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey
ObjectiveTo understand the spatial distribution and influencing factors of secondhand smoke (SHS) exposure in healthcare facilities in China, and to provide a reference for the development of regional tobacco control strategies and measures in these facilities. MethodsData were collected from the 20...
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Editorial Office of Chinese Journal of Public Health
2024-12-01
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| Series: | Zhongguo gonggong weisheng |
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| Online Access: | https://www.zgggws.com/article/doi/10.11847/zgggws1145225 |
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| author | Ying LIU Xinying ZENG Lin XIAO Shiwei LIU |
| author_facet | Ying LIU Xinying ZENG Lin XIAO Shiwei LIU |
| author_sort | Ying LIU |
| collection | DOAJ |
| description | ObjectiveTo understand the spatial distribution and influencing factors of secondhand smoke (SHS) exposure in healthcare facilities in China, and to provide a reference for the development of regional tobacco control strategies and measures in these facilities. MethodsData were collected from the 2022 China Adult Tobacco Survey, including relevant data from non-collectively residing Chinese residents aged ≥ 15 years old and above in 31 provinces (autonomous regions, municipalities) across the country. Geoda 1.22 statistical software was used to conduct spatial autocorrelation analysis and ordinary least squares (OLS) spatial regression model analysis to explore the main influencing factors of SHS exposure in healthcare facilities and their spatial heterogeneity. ResultsIn 2022, the SHS exposure rate in Chinese healthcare facilities was 13.6%. The regions with the lowest exposure rates were Shanghai city and Beijing city (exposure rates between 0% and 5%), and the region with the highest exposure rate was Jiangxi province (exposure rate between 25% and 30%). Global spatial autocorrelation analysis showed that the spatial distribution of SHS exposure rates in Chinese healthcare facilities in 2022 was positively correlated and spatially clustered (Moran′s I = 0.359, Z = 3.430, P = 0.002), indicating that regions with higher exposure rates were surrounded by regions with similarly high exposure rates. Local spatial autocorrelation analysis showed that Qinghai province, Sichuan province, Chongqing city, Guizhou province, Hunan province, and Hubei province were all in high-high cluster areas, Hebei province was in a low-low cluster area, and Xinjiang Uyghur Autonomous Region, Yunnan province, and Guangdong province were all in low-high cluster areas. OLS spatial regression model analysis showed that regions with a higher proportion of males (β = 23.878, t = 3.207, P = 0.003), a higher proportion of individuals aged 0 – 14 years (β = 0.751, t = 3.665, P < 0.001), a higher proportion of individuals aged 15 – 64 years (β = 0.929, t = 3.279, P = 0.003), a higher illiteracy rate (β = 0.675, t = 2.703, P = 0.011), a higher tobacco consumer price index (β = 2.563, t = 2.384, P = 0.024), and a lower proportion of cities with smoke-free legislation (β = 0.069, t = 2.119, P = 0.034) had higher SHS exposure rates in healthcare facilities.ConclusionsSHS exposure in Chinese healthcare facilities is mainly concentrated in central-south, southwest, and northwest China. Sex ratio, the proportions of individuals aged 0 – 14 years and 15 – 64 years, illiteracy rate, tobacco consumer price index, and the proportion of cities with smoke-free legislation are the main influencing factors of SHS exposure in healthcare facilities in China. |
| format | Article |
| id | doaj-art-d5c52993542e487ca0b21b3dc0029c79 |
| institution | Kabale University |
| issn | 1001-0580 |
| language | zho |
| publishDate | 2024-12-01 |
| publisher | Editorial Office of Chinese Journal of Public Health |
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| series | Zhongguo gonggong weisheng |
| spelling | doaj-art-d5c52993542e487ca0b21b3dc0029c792025-02-11T02:11:59ZzhoEditorial Office of Chinese Journal of Public HealthZhongguo gonggong weisheng1001-05802024-12-0140121477148010.11847/zgggws11452251145225Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional surveyYing LIU0Xinying ZENG1Lin XIAO2Shiwei LIU3Tobacco Control Office, Chinese Center for Disease Control and Prevention, Beijing 100050, ChinaTobacco Control Office, Chinese Center for Disease Control and Prevention, Beijing 100050, ChinaTobacco Control Office, Chinese Center for Disease Control and Prevention, Beijing 100050, ChinaTobacco Control Office, Chinese Center for Disease Control and Prevention, Beijing 100050, ChinaObjectiveTo understand the spatial distribution and influencing factors of secondhand smoke (SHS) exposure in healthcare facilities in China, and to provide a reference for the development of regional tobacco control strategies and measures in these facilities. MethodsData were collected from the 2022 China Adult Tobacco Survey, including relevant data from non-collectively residing Chinese residents aged ≥ 15 years old and above in 31 provinces (autonomous regions, municipalities) across the country. Geoda 1.22 statistical software was used to conduct spatial autocorrelation analysis and ordinary least squares (OLS) spatial regression model analysis to explore the main influencing factors of SHS exposure in healthcare facilities and their spatial heterogeneity. ResultsIn 2022, the SHS exposure rate in Chinese healthcare facilities was 13.6%. The regions with the lowest exposure rates were Shanghai city and Beijing city (exposure rates between 0% and 5%), and the region with the highest exposure rate was Jiangxi province (exposure rate between 25% and 30%). Global spatial autocorrelation analysis showed that the spatial distribution of SHS exposure rates in Chinese healthcare facilities in 2022 was positively correlated and spatially clustered (Moran′s I = 0.359, Z = 3.430, P = 0.002), indicating that regions with higher exposure rates were surrounded by regions with similarly high exposure rates. Local spatial autocorrelation analysis showed that Qinghai province, Sichuan province, Chongqing city, Guizhou province, Hunan province, and Hubei province were all in high-high cluster areas, Hebei province was in a low-low cluster area, and Xinjiang Uyghur Autonomous Region, Yunnan province, and Guangdong province were all in low-high cluster areas. OLS spatial regression model analysis showed that regions with a higher proportion of males (β = 23.878, t = 3.207, P = 0.003), a higher proportion of individuals aged 0 – 14 years (β = 0.751, t = 3.665, P < 0.001), a higher proportion of individuals aged 15 – 64 years (β = 0.929, t = 3.279, P = 0.003), a higher illiteracy rate (β = 0.675, t = 2.703, P = 0.011), a higher tobacco consumer price index (β = 2.563, t = 2.384, P = 0.024), and a lower proportion of cities with smoke-free legislation (β = 0.069, t = 2.119, P = 0.034) had higher SHS exposure rates in healthcare facilities.ConclusionsSHS exposure in Chinese healthcare facilities is mainly concentrated in central-south, southwest, and northwest China. Sex ratio, the proportions of individuals aged 0 – 14 years and 15 – 64 years, illiteracy rate, tobacco consumer price index, and the proportion of cities with smoke-free legislation are the main influencing factors of SHS exposure in healthcare facilities in China.https://www.zgggws.com/article/doi/10.11847/zgggws1145225secondhand smoke exposurespatial distributioninfluencing factorshealthcare facilitieschina |
| spellingShingle | Ying LIU Xinying ZENG Lin XIAO Shiwei LIU Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey Zhongguo gonggong weisheng secondhand smoke exposure spatial distribution influencing factors healthcare facilities china |
| title | Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey |
| title_full | Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey |
| title_fullStr | Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey |
| title_full_unstemmed | Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey |
| title_short | Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey |
| title_sort | spatial distribution and influencing factors of secondhand smoke exposure in chinese healthcare facilities a cross sectional survey |
| topic | secondhand smoke exposure spatial distribution influencing factors healthcare facilities china |
| url | https://www.zgggws.com/article/doi/10.11847/zgggws1145225 |
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