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中国医疗卫生机构二手烟暴露空间分布及其影响因素分析

Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey

  • 摘要:
    目的 了解中国医疗卫生机构二手烟暴露的空间分布及其影响因素,为制定区域化的医疗卫生机构烟草使用控制策略和措施提供参考依据。
    方法 收集2022年中国成人烟草流行调查数据中31个省(自治区、直辖市)≥ 15岁非集体居住中国居民的相关数据,采用Geoda 1.22统计软件进行空间自相关分析和最小二乘法(OLS)空间回归模型分析医疗卫生机构二手烟暴露的主要影响因素及其空间异质性。
    结果 2022年中国医疗卫生机构二手烟暴露率为13.6%,暴露率最低的地区为上海市和北京市(暴露率为0~5%),最高的地区为江西省(暴露率为25%~30%);全局自相关分析结果显示,2022年中国医疗卫生机构二手烟暴露率空间分布呈正相关且存在空间聚集性(Moran’I = 0.359,Z = 3.430,P = 0.002),暴露率较高地区周围地区的暴露率也较高;局部自相关分析结果显示,青海省、四川省、重庆市、贵州省、湖南省和湖北省均处于高 – 高聚集区域,河北省处于低 – 低聚集区域,新疆维吾尔自治区、云南省和广东省均处于低 – 高聚集区域;OLS空间回归模型分析结果显示,男性占比越高(β = 23.878,t = 3.207,P = 0.003)、0~14岁占比越高(β = 0.751,t = 3.665,P < 0.001)、15~64岁占比越高(β = 0.929,t = 3.279,P = 0.003)、文盲率越高(β = 0.675,t = 2.703,P = 0.011)、烟草消费价格指数越高(β = 2.563,t = 2.384,P = 0.024)和控烟立法城市占比越低(β = 0.069,t = 2.119,P = 0.034)的地区,医疗卫生机构二手烟暴露率越高。
    结论 中国医疗卫生机构二手烟暴露主要集中在中南、西南和西北部地区,性别比、0~14和15~64岁占比、文盲率、烟草消费价格指数、控烟立法城市占比是中国医疗卫生机构二手烟暴露的主要影响因素。

     

    Abstract:
    Objective To 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.
    Methods Data 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.
    Results In 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.
    Conclusions SHS 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.

     

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