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dc.contributor.authorZhou, S-Men
dc.contributor.authorLyons, RAen
dc.contributor.authorBodger, OGen
dc.contributor.authorJohn, Aen
dc.contributor.authorBrunt, Hen
dc.contributor.authorJones, Ken
dc.contributor.authorGravenor, MBen
dc.contributor.authorBrophy, Sen
dc.date.accessioned2021-02-04T22:21:48Z
dc.date.available2021-02-04T22:21:48Z
dc.date.issued2014en
dc.identifier.urihttp://hdl.handle.net/10026.1/16853
dc.description.abstract

Although inequalities in health and socioeconomic status have an important influence on childhood educational performance, the interactions between these multiple factors relating to variation in educational outcomes at micro-level is unknown, and how to evaluate the many possible interactions of these factors is not well established. This paper aims to examine multi-dimensional deprivation factors and their impact on childhood educational outcomes at micro-level, focusing on geographic areas having widely different disparity patterns, in which each area is characterised by six deprivation domains (Income, Health, Geographical Access to Services, Housing, Physical Environment, and Community Safety). Traditional health statistical studies tend to use one global model to describe the whole population for macro-analysis. In this paper, we combine linked educational and deprivation data across small areas (median population of 1500), then use a local modelling technique, the Takagi-Sugeno fuzzy system, to predict area educational outcomes at ages 7 and 11. We define two new metrics, "Micro-impact of Domain" and "Contribution of Domain", to quantify the variations of local impacts of multidimensional factors on educational outcomes across small areas. The two metrics highlight differing priorities. Our study reveals complex multi-way interactions between the deprivation domains, which could not be provided by traditional health statistical methods based on single global model. We demonstrate that although Income has an expected central role, all domains contribute, and in some areas Health, Environment, Access to Services, Housing and Community Safety each could be the dominant factor. Thus the relative importance of health and socioeconomic factors varies considerably for different areas, depending on the levels of each of the other factors, and therefore each component of deprivation must be considered as part of a wider system. Childhood educational achievement could benefit from policies and intervention strategies that are tailored to the local geographic areas' profiles.

en
dc.format.extente113592 - ?en
dc.languageengen
dc.language.isoengen
dc.rightsAttribution-NonCommercial 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en
dc.subjectChilden
dc.subjectDatabases, Factualen
dc.subjectHealth Statusen
dc.subjectHousingen
dc.subjectHumansen
dc.subjectIncomeen
dc.subjectModels, Theoreticalen
dc.subjectRisk Factorsen
dc.subjectSocial Environmenten
dc.subjectSocioeconomic Factorsen
dc.titleLocal modelling techniques for assessing micro-level impacts of risk factors in complex data: understanding health and socioeconomic inequalities in childhood educational attainments.en
dc.typeJournal Article
plymouth.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/25409038en
plymouth.issue11en
plymouth.volume9en
plymouth.publication-statusPublished onlineen
plymouth.journalPLoS Oneen
dc.identifier.doi10.1371/journal.pone.0113592en
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Health
plymouth.organisational-group/Plymouth/Faculty of Health/School of Nursing and Midwifery
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dc.publisher.placeUnited Statesen
dcterms.dateAccepted2014-10-29en
dc.identifier.eissn1932-6203en
dc.rights.embargoperiodNot knownen
rioxxterms.versionofrecord10.1371/journal.pone.0113592en
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by-nc/4.0/en
rioxxterms.licenseref.startdate2014en
rioxxterms.typeJournal Article/Reviewen


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