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张晓, 杨绪廷, 高衍新, 杜英林, 江媛媛, 孙文, 石峰. 基于主成分 – TOPSIS的黄河流域山东段农村环境卫生综合评价[J]. 中国公共卫生, 2024, 40(1): 61-67. DOI: 10.11847/zgggws1141889
引用本文: 张晓, 杨绪廷, 高衍新, 杜英林, 江媛媛, 孙文, 石峰. 基于主成分 – TOPSIS的黄河流域山东段农村环境卫生综合评价[J]. 中国公共卫生, 2024, 40(1): 61-67. DOI: 10.11847/zgggws1141889
ZHANG Xiao, YANG Xuting, GAO Yanxin, DU Yinglin, JIANG Yuanyuan, SUN Wen, SHI Feng. Comprehensive assessment of rural environmental sanitation for 25 prefectures/counties/districts in and outside the Yellow River Basin, Shandong province – principal component and TOPSIS analysis[J]. Chinese Journal of Public Health, 2024, 40(1): 61-67. DOI: 10.11847/zgggws1141889
Citation: ZHANG Xiao, YANG Xuting, GAO Yanxin, DU Yinglin, JIANG Yuanyuan, SUN Wen, SHI Feng. Comprehensive assessment of rural environmental sanitation for 25 prefectures/counties/districts in and outside the Yellow River Basin, Shandong province – principal component and TOPSIS analysis[J]. Chinese Journal of Public Health, 2024, 40(1): 61-67. DOI: 10.11847/zgggws1141889

基于主成分 – TOPSIS的黄河流域山东段农村环境卫生综合评价

Comprehensive assessment of rural environmental sanitation for 25 prefectures/counties/districts in and outside the Yellow River Basin, Shandong province – principal component and TOPSIS analysis

  • 摘要:
      目的   基于2021年山东省农村环境卫生监测项目工作指标,对黄河流域山东段农村环境卫生进行综合评价,识别发展短板,探讨改善策略。
      方法  基于主成分 — 逼近理想解排序(TOPSIS)分析法,根据山东省2021年农村环境卫生监测工作方案,在现有的农村环境卫生监测体系中,选择13个沿黄河流域区县作为研究对象,同时以其他12个非沿黄河流域区县为对照,选择9个正向高优指标拟合评价模型,采用单个评价指标与最优理想解的标准化距离对黄河流域山东段农村环境卫生进行综合评价。
      结果   从监测指标中筛选出9个核心指标用于主成分分析,分别为全县农民人均年纯收入(万元)、年度农村人均纯收入(万元)、县级农村环境卫生投入(万元)、农村环境卫生综合整治项目创建率(%)、环境卫生管理制度建设率(%)、卫生厕所普及率(%)、集中式供水覆盖率(%)、农村生活垃圾转运率(%)、农村生活污水转运率(%);经主成分分析,农村环境卫生监测项目评价指标可以用3个主成分表示,分别为经济状况、卫生管理、基础卫生设施,其特征值 λ 分别为2.109、2.076和1.349,累计贡献率为61.486% 。利用TOPSIS欧式距离计算各区县综合评价指数,综合评价指数前5位的区县为黄河流域的桓台县和寿光市(0.705,0.665),非黄河流域的荣成市、兖州市、高密市(0.758,0.687,0.662)。变异系数最大的为黄河流域区县经济状况评价指数(0.481),最小的为黄河流域农村环境卫生管理评价指数(0.114)。
      结论  黄河流域区县的优势在于其较好的农村环境卫生管理和基础卫生设施建设,但黄河流域区县经济状况对其综合评价指数的贡献低于非黄河流域区县。

     

    Abstract:
      Objective  To comprehensively assess rural environmental sanitation of 25 prefectures/counties/districts in and outside the Yellow River Basin, Shandong province for developing strategies on improvement of rural environmental sanitation.
      Methods  We collected monitoring data of 2021 on rural environment sanitation of 25 prefectures/counties/districts of Shandong province; the 13 regions located at the Yellow River Basin were set as cases and the 12 regions outside the basin as controls. Principal component analysis and technique for order preference by similarity to an ideal solution (TOPSIS) analysis was adopted in the assessment. Nine positive high performance indicators were introduced to fit the evaluation model. Regional-specific standardized distance between the scores of each of the nine indicators and optimal ideal solution was utilized to evaluate rural environment sanitation of the 25 prefectures/counties/districts and comprehensive evaluation index was calculated for each of the 25 regions using Euclidean distance approximation method to determine ideal points through TOPSIS.
      Results  The nine core indicators included in the principal component analysis were region-specific annual net income per capita for farmers, annual net income per capital for all rural residents, county-level investment in rural environmental health, construction rate of comprehensive improvement projects for rural sanitation, construction rate of environment sanitation management system, prevalence of sanitary toilet, coverage of centralized rural water supply, transfer ratio of solid waste in rural areas, and transfer ratio of domestic sewage in rural areas. The three identified principal components for rural environment sanitation evaluation were economic condition, sanitation management, and primary health facilities, with the eigenvalues of 2.109, 2.076, and 1.349 and a cumulative contribution rate of 61.485%. Among the top five prefectures/counties/districts with higher values of comprehensive evaluation index, two were located in the Yellow River Basin (Huantai county and Shouguang prefecture, with the scores of 0.705 and 0.665) and three were outside of the basin (Rongcheng, Yanzhou and Gaomi prefectures, with the scores of 0.758, 0.687, and 0.662, respectively). Among the three identified principal components, the score for economic conditions showed the highest coefficient of variation (CV, 0.481) for the regions in the Yellow River Basin; while, the score for rural environmental sanitation management showed the lowest CV (0.114).
      Conclusion  In rural Shandong, the sanitation management and primary health facilities are better in the regions in the Yellow River Basin but the contribution of the economic situation to the comprehensive index for environment sanitation evaluation is relatively low compared to those in the regions outside of the basin.

     

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