Charlotte Kühnelt, Anne Starker, Gianni Varnaccia, Anja Schienkiewitz
{"title":"入学考试作为儿童健康监测的小规模数据源,以肥胖为例。","authors":"Charlotte Kühnelt, Anne Starker, Gianni Varnaccia, Anja Schienkiewitz","doi":"10.25646/11435","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>In the scope of the nationwide obligatory school entrance examinations (SEE), a standardised assessment of the preparedness for school of preschool children takes place in the federal states of Germany. For this purpose, height and weight of the children are determined. These data are available in aggregated form at county level, but are not yet being regularly compiled and processed at national level for use in policy and research.</p><p><strong>Methods: </strong>In a pilot project, the indexing and merging of SEE data from 2015-2019 was tested in collaboration with six federal states. This was done using obesity prevalence at the time of the school entrance examination. In addition, prevalences were linked to small-scale indicators on settlement structure and sociodemographics from public databases, differences in obesity prevalence at county level were identified, and correlations to regional influencing factors were visualised.</p><p><strong>Results: </strong>It was feasible to merge SEE data from the federal states with little effort. The majority of the selected indicators were freely available in public databases. In an interactive, easily comprehensible and user-friendly Tableau dashboard for visualising the SEE data, it can be seen that obesity prevalences differ significantly between counties that are similar in terms of settlement structure or sociodemographics.</p><p><strong>Conclusions: </strong>Providing federal state SEE data and linking them to small-scale indicators enables region-based analyses and cross-state comparisons of similar counties and provides a data basis for continuous monitoring of the prevalence of obesity in early childhood.</p>","PeriodicalId":73767,"journal":{"name":"Journal of health monitoring","volume":"8 2","pages":"6-19"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318559/pdf/","citationCount":"0","resultStr":"{\"title\":\"School entrance examinations as a small-scale data source for health monitoring of children using obesity as an example.\",\"authors\":\"Charlotte Kühnelt, Anne Starker, Gianni Varnaccia, Anja Schienkiewitz\",\"doi\":\"10.25646/11435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>In the scope of the nationwide obligatory school entrance examinations (SEE), a standardised assessment of the preparedness for school of preschool children takes place in the federal states of Germany. For this purpose, height and weight of the children are determined. These data are available in aggregated form at county level, but are not yet being regularly compiled and processed at national level for use in policy and research.</p><p><strong>Methods: </strong>In a pilot project, the indexing and merging of SEE data from 2015-2019 was tested in collaboration with six federal states. This was done using obesity prevalence at the time of the school entrance examination. In addition, prevalences were linked to small-scale indicators on settlement structure and sociodemographics from public databases, differences in obesity prevalence at county level were identified, and correlations to regional influencing factors were visualised.</p><p><strong>Results: </strong>It was feasible to merge SEE data from the federal states with little effort. The majority of the selected indicators were freely available in public databases. In an interactive, easily comprehensible and user-friendly Tableau dashboard for visualising the SEE data, it can be seen that obesity prevalences differ significantly between counties that are similar in terms of settlement structure or sociodemographics.</p><p><strong>Conclusions: </strong>Providing federal state SEE data and linking them to small-scale indicators enables region-based analyses and cross-state comparisons of similar counties and provides a data basis for continuous monitoring of the prevalence of obesity in early childhood.</p>\",\"PeriodicalId\":73767,\"journal\":{\"name\":\"Journal of health monitoring\",\"volume\":\"8 2\",\"pages\":\"6-19\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318559/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of health monitoring\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25646/11435\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of health monitoring","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25646/11435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
School entrance examinations as a small-scale data source for health monitoring of children using obesity as an example.
Background: In the scope of the nationwide obligatory school entrance examinations (SEE), a standardised assessment of the preparedness for school of preschool children takes place in the federal states of Germany. For this purpose, height and weight of the children are determined. These data are available in aggregated form at county level, but are not yet being regularly compiled and processed at national level for use in policy and research.
Methods: In a pilot project, the indexing and merging of SEE data from 2015-2019 was tested in collaboration with six federal states. This was done using obesity prevalence at the time of the school entrance examination. In addition, prevalences were linked to small-scale indicators on settlement structure and sociodemographics from public databases, differences in obesity prevalence at county level were identified, and correlations to regional influencing factors were visualised.
Results: It was feasible to merge SEE data from the federal states with little effort. The majority of the selected indicators were freely available in public databases. In an interactive, easily comprehensible and user-friendly Tableau dashboard for visualising the SEE data, it can be seen that obesity prevalences differ significantly between counties that are similar in terms of settlement structure or sociodemographics.
Conclusions: Providing federal state SEE data and linking them to small-scale indicators enables region-based analyses and cross-state comparisons of similar counties and provides a data basis for continuous monitoring of the prevalence of obesity in early childhood.