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北京地区人口非传染性疾病脆弱性评估研究

Assessment on the population vulnerability to non-communicable diseases in Beijing
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摘要 目的应用非传染性疾病(noncommunicable diseases,NCDs)脆弱性评估指标体系和技术方法,系统评估,找出脆弱性因素,为有效预防和控制NCDs提供科学依据。方法 2017年基于经济合作与发展组织(OECD)国家、中国等NCDs相关数据资料,综合采用Data分析,对比分析等方法,确定北京地区人口NCDs各分类分级脆弱性指标水平;进一步运用分层加权评分法,确定综合脆弱性大小;再采用矩阵分析法,确定综合脆弱性等级。结果北京地区人口NCDs脆弱性综合评估分值为77.50分,属于高脆弱性。导致北京地区人口NCDs的关键脆弱性因素,依次为NCDs相关危险因素暴露超敏感性(75.15%)、高敏感性人群(73.00%)、防控能力缺失(63.75%)和健康水平不均等化(61.20%)。结论高脆弱性是导致北京地区人口NCDs的最主要因素,降低NCDs,重点是加强危险因素和人群敏感性防控。 Objective To assess the population vulnerability to non-communicable diseases(NCDs) in Beijing by applying the established vulnerability evaluation index and technical skills in the previous study, and to provide scientific evidence for NCDs prevention and control. Methods The stratified and hierarchical population vulnerability levels were determined by using NCDs data analysis and comparative analysis which were collected from China and OECD in 2017. The analytic hierarchy process(AHP) and matrix analysis were used to determine the overall score of vulnerability and overall vulnerability level. Results The overall score of population vulnerability to NCDs in Beijing was 77.50. The hierarchical vulnerability indices were further prioritized by their levels and the key vulnerability factors were found to be multiple risk factors exposure(75.15%), high vulnerable populations(73.00%), inadequate capacities for prevention and control of NCDs(63.75%) and health inequalities(61.20%). Conclusions The high population vulnerability to NCDs is a leading factor to the high incidence of NCDs in Beijing, therefore, reducing the risk factor exposure and population susceptibility is critical in the prevention and control of NCDs.
作者 董博锋 高星 DONG Bo-feng;GAO Xing(School of Public Health,Capital Medical University,Beijing 100069,China)
出处 《中国预防医学杂志》 CAS CSCD 2019年第2期113-117,共5页 Chinese Preventive Medicine
基金 北京市自然科学基金资助项目(2011-7110001)
关键词 非传染性疾病 脆弱性评估 脆弱性等级 指标体系 层次分析 矩阵指数 Non-communicable diseases Vulnerability assessment Vulnerability level Index system Analytic hierarchy process Matrix index
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