{"title":"VigiNUTRI Brasil:食品和营养监测系统(Sisvan Web)监测的青少年个人数据的申请、数据提取、处理和一致性分析方法。","authors":"Rafaella Lemos Alves, Natacha Toral, Thiago Luiz Nogueira da Silva, Vivian Siqueira Santos Gonçalves","doi":"10.1590/S2237-96222024v33e20231479.en","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To describe the methods for requesting, extracting data, processing and analyzing the consistency of anthropometric and food consumption data of adolescents monitored by Sisvan Web.</p><p><strong>Methods: </strong>Methodological study with individualized data from Sisvan web between 2008 and 2018. The modules of anthropometry and consumption, made available by the Ministry of Health, had a unique identifier for linkages. Implausible values and individuals outside the age range were excluded. Consistency analyses, with corrections for imputations and descriptive statistics, were performed using Stata 16.0 software.</p><p><strong>Results: </strong>A database was obtained with 18,812,232 observations of anthropometric data between 2008 and 2018 and 440,534 records of food consumption between 2015 and 2018; after merging the banks, 64,976 observations were obtained.</p><p><strong>Conclusion: </strong>The combination of anthropometry and food consumption databases made it possible to link individual adolescent data and build a database with information for future analyzes relating to the dietary and nutritional profile of the same individual.</p><p><strong>Main results: </strong>The proposal for processing individual data from the Food and Nutrition Surveillance System (Sisvan Web) generated 18 million observations for anthropometric data and 65,000 observations after merging the anthropometry and food consumption databases.</p><p><strong>Implications for services: </strong>This work will enable replication of the methodology for processing data available in Sisvan Web, allowing for enhanced analyzes by healthcare teams and researchers in the field of public health.</p><p><strong>Perspectives: </strong>It is expected that these procedures will assist researchers, managers and healthcare professionals in handling and analyzing the information generated by Sisvan Web.</p>","PeriodicalId":51473,"journal":{"name":"Epidemiologia e Servicos de Saude","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11473065/pdf/","citationCount":"0","resultStr":"{\"title\":\"VigiNUTRI Brasil: methods of request, data extraction, treatment and consistency analysis of individual data from adolescents monitored by the Food and Nutrition Surveillance System (Sisvan Web).\",\"authors\":\"Rafaella Lemos Alves, Natacha Toral, Thiago Luiz Nogueira da Silva, Vivian Siqueira Santos Gonçalves\",\"doi\":\"10.1590/S2237-96222024v33e20231479.en\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To describe the methods for requesting, extracting data, processing and analyzing the consistency of anthropometric and food consumption data of adolescents monitored by Sisvan Web.</p><p><strong>Methods: </strong>Methodological study with individualized data from Sisvan web between 2008 and 2018. The modules of anthropometry and consumption, made available by the Ministry of Health, had a unique identifier for linkages. Implausible values and individuals outside the age range were excluded. Consistency analyses, with corrections for imputations and descriptive statistics, were performed using Stata 16.0 software.</p><p><strong>Results: </strong>A database was obtained with 18,812,232 observations of anthropometric data between 2008 and 2018 and 440,534 records of food consumption between 2015 and 2018; after merging the banks, 64,976 observations were obtained.</p><p><strong>Conclusion: </strong>The combination of anthropometry and food consumption databases made it possible to link individual adolescent data and build a database with information for future analyzes relating to the dietary and nutritional profile of the same individual.</p><p><strong>Main results: </strong>The proposal for processing individual data from the Food and Nutrition Surveillance System (Sisvan Web) generated 18 million observations for anthropometric data and 65,000 observations after merging the anthropometry and food consumption databases.</p><p><strong>Implications for services: </strong>This work will enable replication of the methodology for processing data available in Sisvan Web, allowing for enhanced analyzes by healthcare teams and researchers in the field of public health.</p><p><strong>Perspectives: </strong>It is expected that these procedures will assist researchers, managers and healthcare professionals in handling and analyzing the information generated by Sisvan Web.</p>\",\"PeriodicalId\":51473,\"journal\":{\"name\":\"Epidemiologia e Servicos de Saude\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11473065/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Epidemiologia e Servicos de Saude\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1590/S2237-96222024v33e20231479.en\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"Multidisciplinary\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemiologia e Servicos de Saude","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1590/S2237-96222024v33e20231479.en","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Multidisciplinary","Score":null,"Total":0}
引用次数: 0
摘要
目的:描述通过 Sisvan Web 监测的青少年人体测量和食物消耗数据的请求、提取、处理和分析方法:描述申请、提取数据、处理和分析 Sisvan Web 监测的青少年人体测量和食物消费数据一致性的方法:对 2008 年至 2018 年期间 Sisvan Web 的个性化数据进行方法研究。由卫生部提供的人体测量和消费模块具有唯一标识符,可用于链接。排除了不合理的数值和超出年龄范围的个体。使用 Stata 16.0 软件进行了一致性分析,并对替换和描述性统计进行了校正:数据库中获得了 2008 年至 2018 年的 18 812 232 个人体测量数据观测值和 2015 年至 2018 年的 440 534 个食物消耗记录;合并数据库后,获得了 64 976 个观测值:将人体测量数据库和食物消费数据库结合起来,可以将青少年个人数据联系起来,并建立一个数据库,为今后分析同一个人的膳食和营养状况提供信息:主要成果:处理食品和营养监测系统(Sisvan Web)个人数据的建议产生了 1,800 万个人体测量数据观测值,在合并人体测量和食品消费数据库后产生了 65,000 个观测值:这项工作将能够复制 Sisvan Web 中的数据处理方法,使医疗团队和公共卫生领域的研究人员能够加强分析:预计这些程序将有助于研究人员、管理人员和医疗保健专业人员处理和分析由 Sisvan Web 生成的信息。
VigiNUTRI Brasil: methods of request, data extraction, treatment and consistency analysis of individual data from adolescents monitored by the Food and Nutrition Surveillance System (Sisvan Web).
Objective: To describe the methods for requesting, extracting data, processing and analyzing the consistency of anthropometric and food consumption data of adolescents monitored by Sisvan Web.
Methods: Methodological study with individualized data from Sisvan web between 2008 and 2018. The modules of anthropometry and consumption, made available by the Ministry of Health, had a unique identifier for linkages. Implausible values and individuals outside the age range were excluded. Consistency analyses, with corrections for imputations and descriptive statistics, were performed using Stata 16.0 software.
Results: A database was obtained with 18,812,232 observations of anthropometric data between 2008 and 2018 and 440,534 records of food consumption between 2015 and 2018; after merging the banks, 64,976 observations were obtained.
Conclusion: The combination of anthropometry and food consumption databases made it possible to link individual adolescent data and build a database with information for future analyzes relating to the dietary and nutritional profile of the same individual.
Main results: The proposal for processing individual data from the Food and Nutrition Surveillance System (Sisvan Web) generated 18 million observations for anthropometric data and 65,000 observations after merging the anthropometry and food consumption databases.
Implications for services: This work will enable replication of the methodology for processing data available in Sisvan Web, allowing for enhanced analyzes by healthcare teams and researchers in the field of public health.
Perspectives: It is expected that these procedures will assist researchers, managers and healthcare professionals in handling and analyzing the information generated by Sisvan Web.