Bernard Baffour, Sumonkanti Das, Mu Li, Alice Richardson
{"title":"社会经济指标和偏远地区指标在理解澳大利亚幼儿脆弱性地区流行率的地域差异方面的实用性","authors":"Bernard Baffour, Sumonkanti Das, Mu Li, Alice Richardson","doi":"10.1007/s12187-024-10143-4","DOIUrl":null,"url":null,"abstract":"<p>The family lives of children and their early childhood development outcomes are attributable to the level of socio-economic disadvantage and relative isolation. This study aims to investigate how the disadvantage of the local area (i.e., socio-economic indexes for areas (SEIFA)) and the remoteness (i.e., accessibility/remoteness index of Australia (ARIA)) contribute to improved prevalence estimates of child development vulnerability in statistical areas level 3 (SA3) and 4 (SA4) across Australia. Data from the 2018 Australian Early Development Census (AEDC) has been used. The study included 308,953 children involved in the AEDC 2018 where one-in-ten of them were considered to be developmentally vulnerable, nationally. We developed models in a hierarchical Bayesian framework at the SA3 level using SEIFA and ARIA indices as covariates to account for spatial and unobserved heterogeneity. The performances of developed models are examined based on the consistency at SA3, SA4, and state level. The results reveal that SEIFA makes a significant contribution to explaining the spatial variation in childhood development vulnerability across small domains in Australia. Further, the inclusion of the ARIA score improves the model performance and provides better accuracy, particularly in remote and very remote regions. In these regions, the spatial model fails to distinguish the remoteness characteristics. The chosen non-spatial model accounting for heterogeneity at higher hierarchies performs best. The utilization of socio-economic disadvantage and geographic remoteness of the finer level domains helps to explain the geographic variation in child development vulnerability, particularly in sparsely populated remote regions in Australia.</p>","PeriodicalId":47682,"journal":{"name":"Child Indicators Research","volume":"3 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Utility of Socioeconomic and Remoteness Indicators in Understanding the Geographical Variation in the Regional Prevalence of Early Childhood Vulnerability in Australia\",\"authors\":\"Bernard Baffour, Sumonkanti Das, Mu Li, Alice Richardson\",\"doi\":\"10.1007/s12187-024-10143-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The family lives of children and their early childhood development outcomes are attributable to the level of socio-economic disadvantage and relative isolation. This study aims to investigate how the disadvantage of the local area (i.e., socio-economic indexes for areas (SEIFA)) and the remoteness (i.e., accessibility/remoteness index of Australia (ARIA)) contribute to improved prevalence estimates of child development vulnerability in statistical areas level 3 (SA3) and 4 (SA4) across Australia. Data from the 2018 Australian Early Development Census (AEDC) has been used. The study included 308,953 children involved in the AEDC 2018 where one-in-ten of them were considered to be developmentally vulnerable, nationally. We developed models in a hierarchical Bayesian framework at the SA3 level using SEIFA and ARIA indices as covariates to account for spatial and unobserved heterogeneity. The performances of developed models are examined based on the consistency at SA3, SA4, and state level. The results reveal that SEIFA makes a significant contribution to explaining the spatial variation in childhood development vulnerability across small domains in Australia. Further, the inclusion of the ARIA score improves the model performance and provides better accuracy, particularly in remote and very remote regions. In these regions, the spatial model fails to distinguish the remoteness characteristics. The chosen non-spatial model accounting for heterogeneity at higher hierarchies performs best. The utilization of socio-economic disadvantage and geographic remoteness of the finer level domains helps to explain the geographic variation in child development vulnerability, particularly in sparsely populated remote regions in Australia.</p>\",\"PeriodicalId\":47682,\"journal\":{\"name\":\"Child Indicators Research\",\"volume\":\"3 1\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Child Indicators Research\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1007/s12187-024-10143-4\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Child Indicators Research","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1007/s12187-024-10143-4","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
The Utility of Socioeconomic and Remoteness Indicators in Understanding the Geographical Variation in the Regional Prevalence of Early Childhood Vulnerability in Australia
The family lives of children and their early childhood development outcomes are attributable to the level of socio-economic disadvantage and relative isolation. This study aims to investigate how the disadvantage of the local area (i.e., socio-economic indexes for areas (SEIFA)) and the remoteness (i.e., accessibility/remoteness index of Australia (ARIA)) contribute to improved prevalence estimates of child development vulnerability in statistical areas level 3 (SA3) and 4 (SA4) across Australia. Data from the 2018 Australian Early Development Census (AEDC) has been used. The study included 308,953 children involved in the AEDC 2018 where one-in-ten of them were considered to be developmentally vulnerable, nationally. We developed models in a hierarchical Bayesian framework at the SA3 level using SEIFA and ARIA indices as covariates to account for spatial and unobserved heterogeneity. The performances of developed models are examined based on the consistency at SA3, SA4, and state level. The results reveal that SEIFA makes a significant contribution to explaining the spatial variation in childhood development vulnerability across small domains in Australia. Further, the inclusion of the ARIA score improves the model performance and provides better accuracy, particularly in remote and very remote regions. In these regions, the spatial model fails to distinguish the remoteness characteristics. The chosen non-spatial model accounting for heterogeneity at higher hierarchies performs best. The utilization of socio-economic disadvantage and geographic remoteness of the finer level domains helps to explain the geographic variation in child development vulnerability, particularly in sparsely populated remote regions in Australia.
期刊介绍:
Child Indicators Research is an international, peer-reviewed quarterly that focuses on measurements and indicators of children''s well-being, and their usage within multiple domains and in diverse cultures. The Journal will present measures and data resources, analysis of the data, exploration of theoretical issues, and information about the status of children, as well as the implementation of this information in policy and practice. It explores how child indicators can be used to improve the development and well-being of children. Child Indicators Research will provide a unique, applied perspective, by presenting a variety of analytical models, different perspectives, and a range of social policy regimes. The Journal will break through the current ‘isolation’ of academicians, researchers and practitioners and serve as a ‘natural habitat’ for anyone interested in child indicators. Unique and exclusive, the Journal will be a source of high quality, policy impact and rigorous scientific papers. Readership: academicians, researchers, government officials, data collectors, providers of funding, practitioners, and journalists who have an interest in children’s well-being issues.