环境健康综合数据质量核查与评估初步研究

发布时间：2018-05-04 17:13

本文选题：环境健康 + 数据质量核查　；参考：《环境与健康杂志》2016年11期

【摘要】：目的建立环境健康综合数据质量核查评估方法模型,并以某市环境健康数据对该方法模型进行验证,探索适用于环境健康综合监测等大规模数据质量的核查方法。方法基于文献调研,构建环境健康综合数据质量核查评估方法模型;将模型应用于某市2013—2015年环境健康综合数据质量评估中,首先评价环境数据(空气质量数据、气象数据)和健康数据(死因数据、慢病监测数据)的各项核查指标,然后通过综合指数法计算各类数据质量的综合指数。结果该方法模型能够对环境健康综合数据进行有效的评估,可识别各类数据具体问题且实现不同类型、不同年份间数据质量的对比。单项指标核查结果表明某市2013—2014年环境因素数据的缺失率最高,为5.75%,2014—2015年健康效应数据的逻辑错误率高于10%;综合指数评价结果表明健康效应数据质量相比环境因素数据存在问题较多。结论本研究所建立的方法模型可操作性较强,能够为环境健康综合监测等全国大规模监测数据质量核查提供有效工具。
[Abstract]:Objective to establish an environmental health comprehensive data quality verification model and verify the model with a certain city's environmental health data, and to explore a verification method suitable for large-scale data quality monitoring such as comprehensive environmental health monitoring. Methods based on literature investigation, a model of environmental health comprehensive data quality verification and evaluation was constructed, and applied to a city's environmental health comprehensive data quality assessment from 2013 to 2015. Firstly, the environmental data (air quality data) was evaluated. Check indexes of meteorological data and health data (cause of death data, chronic disease monitoring data), and then calculate the comprehensive index of all kinds of data quality by comprehensive index method. Results the model can effectively evaluate the comprehensive data of environmental health, identify the specific problems of various kinds of data and realize the comparison of data quality between different types and different years. The results of single indicator verification show that a city has the highest rate of missing data on environmental factors in 2013-2014. The logical error rate of health effect data in 2014-2015 is higher than that of 10, and the result of comprehensive index evaluation shows that the quality of health effect data is more problematic than that of environmental factor data. Conclusion the method model established in this study is feasible and can provide an effective tool for the quality verification of large-scale monitoring data such as comprehensive monitoring of environmental health.
【作者单位】：中国疾病预防控制中心环境与健康相关产品安全所;
【基金】：国家自然科学基金(21277135,91543111) 中国疾病预防控制中心环境与健康相关产品安全所环境健康发展项目 “万人计划”青年拔尖人才项目
【分类号】：R12

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