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北京市海淀区2013-2017年餐饮业餐饮具卫生状况监测与分析 被引量:2

Monitoring and analysis of sanitary status of catering equipment in Haidian District of Beijing from 2013 to 2017
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摘要 目的了解北京市海淀区餐饮业餐饮具的卫生状况,为卫生监管提供科学依据。方法 2013-2017年在全区范围内每年随机抽取A、B和C级餐饮单位,用大肠菌群快速纸片检测法随机采样和检测,并对检测结果进行χ2检验。结果 2013-2017年共抽取餐饮单位670户,采集餐饮具样品3 885件,其中2 664件合格,总体合格率68. 6%,呈逐年上升趋势(χ2=281. 16,P <0. 01)。A、B、C级餐饮单位餐饮具合格率差异有统计学意义,分别为90. 6%、73. 9%、54. 9%(χ2=302. 68,P <0. 01)。三级餐饮单位餐饮具合格率均呈逐年上升趋势(A级:χ2=31. 89,P <0. 01;B级:χ2=91. 95,P <0. 01; C级:χ2=175. 34,P <0. 01)。结论北京市海淀区餐饮业餐饮具的卫生状况逐年改善,应重点加强B、C级餐饮单位的监督管理。 Objective To understand the sanitary condition of tablewares in Haidian District of Beijing and provide scientific basis for health supervision.Methods A,B and C-class catering units were randomly selected in Haidian District during 2013 and 2017.The coliform group was randomly sampled and detected by rapid paper detection for coliform.The chi square test was used to test the results.Results During 2013 and 2017,a total of 670 catering units were selected and 3 885 samples were collected,of which 2 664 were qualified.The overall qualification rate was 68.6%,showing an upward trend year by year(χ2=281.16,P<0.01).There was a statistically significant difference in the qualification rate of tablewares in A,B and C-class catering units,which were 90.6%,73.9%and 54.9%respectively(χ2=302.68,P<0.01).The qualification rate of tablewares in all those 3 classes of catering units showed an upward trend year by year(A-class:χ2=31.89,P<0.01;B-class:χ2=91.95,P<0.01;C-class:χ2=175.34,P<0.01).Conclusion The sanitary condition of tablewares in Haidian District of Beijing has improved year by year.It is necessary to strengthen the supervision and management of B and C-class catering units.
作者 周萌 丁越江 赵振 ZHOU Meng;DING Yuejiang;ZHAO Zhen(Beijing Haidian Center for Disease Control and Prevention,Beijing100094,China)
出处 《医学动物防制》 2019年第6期598-600,共3页 Journal of Medical Pest Control
基金 北京市卫生和计划生育委员会<2017年北京市食品污染及食品中有害因素监测方案>(京卫食品[2017]5号)
关键词 餐饮业 餐饮具 卫生状况 监测 Catering industry Tableware Sanitary condition Monitoring
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