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dc.contributor.authorCongdon, Pen_US
dc.date.accessioned2016-05-09T13:03:20Z
dc.date.available2015-12-18en_US
dc.date.issued2016en_US
dc.date.submitted2016-03-11T10:17:02.177Z
dc.identifier.issn1387-3741en_US
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/12227
dc.description.abstractAnalysis of healthy life expectancy is typically based on a binary distinction between health and ill-health. By contrast, this paper considers spatial modelling of disease free life expectancy taking account of the number of chronic conditions. Thus the analysis is based on population sub-groups with no disease, those with one disease only, and those with two or more diseases (multiple morbidity). Data on health status is accordingly modelled using a multinomial likelihood. The analysis uses data for 258 small areas in north London, and shows wide differences in the disease burden related to multiple morbidity. Strong associations between area socioeconomic deprivation and multiple morbidity are demonstrated, as well as strong spatial clustering.en_US
dc.format.extent58 - 74en_US
dc.languageengen_US
dc.language.isoenen_US
dc.relation.ispartofHealth Serv Outcomes Res Methodolen_US
dc.rightsCC-BY
dc.subjectBayesianen_US
dc.subjectDeprivationen_US
dc.subjectDisease free life expectancyen_US
dc.subjectMultinomialen_US
dc.subjectMultiple morbidityen_US
dc.subjectSpatialen_US
dc.titleArea variations in multiple morbidity using a life table methodology.en_US
dc.typeArticle
dc.rights.holder© The Author(s) 2016
dc.identifier.doi10.1007/s10742-015-0142-4en_US
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/27257403en_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
pubs.volume16en_US
dcterms.dateAccepted2015-12-18en_US


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