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dc.contributor.authorDi Lego, Vanessade
dc.contributor.authorSauerberg, Markusde
dc.date.accessioned2023-09-05T07:40:55Z
dc.date.available2023-09-05T07:40:55Z
dc.date.issued2023de
dc.identifier.issn1869-8999de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/88957
dc.description.abstractThe Healthy Life Years (HLY) indicator is the official European Union indicator and a cornerstone of many health policies used in over 15 countries in the EU region to set national health plans and monitor targets. It is also used to investigate trends over time in the proportion of total life years spent in good or poor health, socioeconomic inequalities in health and mortality and the male-female health survival paradox. Based on the Global Activity Limitation Indicator (GALI) included in the European Union Statistics on Income and Living Conditions (EU-SILC), a great amount of effort has been directed at harmonising and making HLY comparable across countries. Nonetheless, the characteristics of the age-specific prevalence distribution are still rarely accounted for, regardless of the fact that patterns of prevalence often fluctuate considerably by age. In addition, the impact of assumptions used at very young ages on HLY estimates are seldom discussed, despite the fact that the majority of policies and initiatives at the EU level use HLY at birth, while data on health is only available after age 16. In this paper, we assess whether smoothing the age-specific prevalence distributions by different methods, extrapolating to older ages and changing assumptions at younger ages affect HLY estimates. Overall, assumptions made before age 15 are the most important and affect women and men differently, thus affecting HLY at birth for some countries. Estimates at age 65 are very slightly impacted. Generalised linear models (GAMs) seem promising for harmonising and extrapolating to older ages, while using polynomials or aggregating into 5-year age groups seem best for younger ages. As most EU policies use HLY at birth and by sex for developing and monitoring health policies, caution is needed when estimating HLY at birth.de
dc.languageende
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/725187de
dc.rightsinfo:eu-repo/semantics/openAccessde
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otherAge-Specific Prevalence; GALI; Gender differences; Healthy Life Years; Life Table; Sensitivity; Smoothing; Sullivan Method; European Union Statistics on Income and Living Conditions European Health Interview Survey (EU-SILC), cross-sectional 2017, version release 2 in 2020de
dc.titleThe Sensitivity of the Healthy Life Years Indicator: Approaches for Dealing with Age-Specific Prevalence Datade
dc.typeinfo:eu-repo/semantics/articlede
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.identifier.urlhttp://www.comparativepopulationstudies.de/index.php/CPoS/article/view/476/373de
dc.identifier.urlhttp://www.comparativepopulationstudies.de/index.php/CPoS/article/view/476/374de
dc.source.journalComparative Population Studies - Zeitschrift für Bevölkerungswissenschaft
dc.source.volume48de
dc.publisher.countryDEUde
dc.subject.classozBevölkerungde
dc.subject.classozPopulation Studies, Sociology of Populationen
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozGesundheitde
dc.subject.thesozhealthen
dc.subject.thesozMonitoringde
dc.subject.thesozmonitoringen
dc.subject.thesozIndikatorde
dc.subject.thesozindicatoren
dc.subject.thesozGesundheitszustandde
dc.subject.thesozhealth statusen
dc.subject.thesozLebensalterde
dc.subject.thesozageen
dc.subject.thesozLebenserwartungde
dc.subject.thesozlife expectancyen
dc.subject.thesozSterblichkeitde
dc.subject.thesozmortalityen
dc.subject.thesozgeschlechtsspezifische Faktorende
dc.subject.thesozgender-specific factorsen
dc.subject.thesozinternationaler Vergleichde
dc.subject.thesozinternational comparisonen
dc.subject.thesozSchätzungde
dc.subject.thesozestimationen
dc.subject.thesozDatengewinnungde
dc.subject.thesozdata captureen
dc.identifier.urnurn:nbn:de:bib-cpos-2023-06en7de
dc.rights.licenceCreative Commons - Namensnennung, Weitergabe unter gleichen Bedingungen 4.0de
dc.rights.licenceCreative Commons - Attribution-ShareAlike 4.0en
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10045492
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internal.identifier.thesoz10047129
internal.identifier.thesoz10045579
internal.identifier.thesoz10034576
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dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo117-150de
internal.identifier.classoz10303
internal.identifier.classoz10105
internal.identifier.journal60
internal.identifier.document32
internal.identifier.ddc300
dc.source.issuetopicLevels and Trends of Health Expectancy: Understanding its Measurement and Estimation Sensitivityde
dc.identifier.doihttps://doi.org/10.12765/CPoS-2023-06de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence24
internal.identifier.pubstatus1
internal.identifier.review1
internal.check.openairetruede
internal.dda.referencehttp://www.comparativepopulationstudies.de/index.php/CPoS/oai@@oai:ojs.comparativepopulationstudies.de:article/476


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