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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。
Objective To establish a method of environmental health comprehensive data quality assessment and verification, validate this method model with environmental health data of a certain city, and explore verification methods suitable for large-scale data quality such as comprehensive monitoring of environmental health. Methods Based on the literature survey, the method of environmental health comprehensive data quality assessment was constructed. The model was applied to the environmental health comprehensive data quality assessment in a city from 2013 to 2015. The environmental data (air quality data, meteorological data) and health data Cause of death data, chronic disease surveillance data), and then calculate the comprehensive index of various data quality through the integrated index method. Results The method model can effectively evaluate the comprehensive environmental health data, identify specific problems of various data types, and achieve data quality comparison among different types and years. The results of single indicator verification showed that the highest rate of missing environmental factor data was 5.75% in 2013-2014 in a certain city, and the logic error rate of health effect data was higher than 10% in 2014-2015. The comprehensive index evaluation result showed that the quality of health effect data There are more problems with environmental factor data. Conclusion The method model established in this study is feasible and can provide an effective tool for the nationwide large-scale monitoring data quality verification such as comprehensive environmental health monitoring.