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王延赏, 顾钿钿, 初海超, 杜汋. 环境状况对我国城乡居民健康水平影响[J]. 中国公共卫生, 2020, 36(9): 1264-1267. DOI: 10.11847/zgggws1121658
引用本文: 王延赏, 顾钿钿, 初海超, 杜汋. 环境状况对我国城乡居民健康水平影响[J]. 中国公共卫生, 2020, 36(9): 1264-1267. DOI: 10.11847/zgggws1121658
Yan-shang WANG, Tian-tian GU, Hai-chao CHU, . Effect of environmental condition on health of urban and rural residents in China[J]. Chinese Journal of Public Health, 2020, 36(9): 1264-1267. DOI: 10.11847/zgggws1121658
Citation: Yan-shang WANG, Tian-tian GU, Hai-chao CHU, . Effect of environmental condition on health of urban and rural residents in China[J]. Chinese Journal of Public Health, 2020, 36(9): 1264-1267. DOI: 10.11847/zgggws1121658

环境状况对我国城乡居民健康水平影响

Effect of environmental condition on health of urban and rural residents in China

  • 摘要:
      目的  探索我国居民健康水平与环境状况之间的关系,分析城乡居民所处环境状况对其健康的影响,为建设健康中国提供参考。
      方法  将中国综合社会调查(CGSS)2013年数据作为研究资料,选取部分城市和农村居民作为研究对象,按其自评健康状况划分为不健康与健康群体,将健康水平作为因变量,利用二分类logistic回归分析环境状况(空气污染、水污染、噪声污染、生活垃圾污染、工业垃圾污染和绿地空间)、体育锻炼以及其他人口学信息对城乡居民健康水平的影响,并引入体育锻炼 × 绿地空间交互项建立模型以挖掘体育锻炼在绿地空间与健康水平间的调节作用。
      结果  本研究最终纳入研究对象4 265名,其中城市居民2 609名(61.2 %),农村居民1 656名(38.8 %);单因素分析结果显示,城市居民健康水平明显高于农村居民;logistic回归结果显示,控制混杂因素后,在农村地区,水污染(OR = 1.469,95 % CI = 1.085~1.991)和工业垃圾污染(OR = 0.658,95 % CI = 0.438~0.990)显著影响居民健康水平;在城市地区,绿地空间是影响居民健康水平的重要因素(OR = 1.313,95 % CI = 1.075~1.604),体育锻炼在绿地空间与居民健康之间起着调节作用(OR = 1.607,95 % CI = 1.110~2.326)。
      结论  城市绿地不足和农村严重水污染导致居民出现诸多健康问题,且农村居民对工业垃圾认知程度不足;相关部门应因地制宜改善环境状况,提高全民健康水平。

     

    Abstract:
      Objective  To explore the relationship between the health status of residents and the environmental conditions and the impact of environmental conditions on the health of urban and rural residents for providing references to the construction of Healthy China.
      Methods  The data of the study were extracted from Chinese General Social Survey (CGSS) conducted across China in 2013. We selected a part of urban and rural residents surveyed in CGSS and assigned them into a healthy and an unhealthy group according to their self-rated health status. Taking health level as a dependent variable, we adopted binary logistic regression analysis to assess the impact of environmental conditions (air, water, noise, domestic garbage, and industrial waste pollutions and green space), physical exercise, and demographic factors on the health of the residents. An interactive item of physical exercise plus green space was introduced into a regression model in the analyses to evaluate modification effect of physical exercise on the correlation between green space and health level of the residents.
      Results  Of the 4 265 residents included in the study, 2 609 (61.2%) and 1 656 (38.8%) were from urban and rural regions. Univariate analysis showed that the health level of the urban residents was significantly higher than that of rural residents. The results of logistic regression analysis demonstrated that after adjusting for confounders, water pollution (odds ratio OR = 1.469, 95% confidence interval 95% CI: 1.085 – 1.991) and industrial waste pollution (OR = 0.658, 95% CI: 0.438 – 0.990) were significant impact factors for health of the residents in rural regions; while, green space (OR = 1.313, 95% CI: 1.075 – 1.604) was a significant impact factor for health of the residents in urban regions and physical exercise played a modification role on the correlation between green space and residents′ health (OR = 1.607, 95% CI: 1.110 – 2.326).
      Conclusion  Insufficient green space in urban regions and serious water pollution in rural regions have significant impact on residents′ health level and rural residents are lack of awareness on industrial waste. Environmental condition needs to be concerned by relevant agencies for promoting health of the residents.

     

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