Tiantong Li, Xiao Hu, Li Li, Yuhe Liu, Menglu He, Conghui Huang, Xuefei Zhou, Jing Sun
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引用次数: 0
Abstract
Objective: To establish a set of visualization systems suitable for displaying the transition of malnutrition status in different population across time and space in China.
Methods: Based on the data characteristics of the four monitoring systems, including the China Nutrition and Health Surveillance, the China Health and Nutrition Survey, the Project of Children Nutrition Improvement in Poor Rural Regions, and the Nutrition Improvement Program for Rural Compulsory Education Students, to be merged and the requirements of this project, the client/server architecture(C/S architecture) application mode was adopted, the Visual Studio 2019 development tool set, Python 3.7-10 and C # 8.0 language programming were used for data integration, and a complete set of data preprocessing, data conversion and data integration calculation processes were established.
Results: The malnutrition visualization system provided a visualization display system for the nutritional status of different populations under the multi database fusion index system based on the integrated malnutrition database. The system was able to not only modify, delete and update data, but query, display and analyze malnutrition conditions including growth retardation, low weight, emaciation, micronutrient deficiency, overweight, and obesity.
Conclusion: Malnutrition visualization system dynamically presented the time series and spatial distribution of malnutrition among Chinese residents, and explored the regional characteristics and major challenges of nutrition problems in different periods.
目的:建立一套适合显示中国不同人群营养不良状况跨时空变迁的可视化系统。方法:根据拟合并的中国营养与健康监测、中国健康与营养调查、农村贫困地区儿童营养改善项目和农村义务教育学生营养改善项目四个监测系统的数据特点,并结合该项目的要求,采用客户端/服务器架构(C/S架构)应用模式,采用Visual Studio 2019开发工具集,数据集成采用Python 3.7-10和c# 8.0语言编程,建立了一套完整的数据预处理、数据转换和数据集成计算流程。结果:营养不良可视化系统提供了基于综合营养不良数据库的多数据库融合指标体系下不同人群营养状况的可视化显示系统。该系统不仅可以修改、删除和更新数据,还可以查询、显示和分析营养不良状况,包括生长迟缓、体重过轻、消瘦、微量营养素缺乏、超重和肥胖。结论:营养不良可视化系统动态呈现我国居民营养不良的时间序列和空间分布,探索不同时期营养问题的区域特征和主要挑战。