- -

Detecting spatio-temporal mortality clusters of European countries by sex and ag

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Detecting spatio-temporal mortality clusters of European countries by sex and ag

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Carracedo-Garnateo, Patricia es_ES
dc.contributor.author Debón Aucejo, Ana María es_ES
dc.contributor.author Iftimi, Adina es_ES
dc.contributor.author Montes-Suay, Francisco es_ES
dc.date.accessioned 2020-05-21T03:01:53Z
dc.date.available 2020-05-21T03:01:53Z
dc.date.issued 2018-03-27 es_ES
dc.identifier.uri http://hdl.handle.net/10251/143877
dc.description.abstract [EN] Background: Mortality decreased in European Union (EU) countries during the last century. Despite these similar trends, there are still considerable differences in the levels of mortality between Eastern and Western European countries. Sub-group analysis of mortality in Europe for different age and sex groups is common, however to our knowledge a spatio-temporal methodology as in this study has not been applied to detect significant spatial dependence and interaction with time. Thus, the objective of this paper is to quantify the dynamics of mortality in Europe and detect significant clusters of mortality between European countries, applying spatio-temporal methodology. In addition, the joint evolution between the mortality of European countries and their neighbours over time was studied. Methods: The spatio-temporal methodology used in this study takes into account two factors: time and the geographical location of countries and, consequently, the neighbourhood relationships between them. This methodology was applied to 26 European countries for the period 1990-2012. Results: Principally, for people older than 64 years two significant clusters were obtained: one of high mortality formed by Eastern European countries and the other of low mortality composed of Western countries. In contrast, for ages below or equal to 64 years only the significant cluster of high mortality formed by Eastern European countries was observed. In addition, the joint evolution between the 26 European countries and their neighbours during the period 1990-2012 was confirmed. For this reason, it can be said that mortality in EU not only depends on differences in the health systems, which are a subject to national discretion, but also on supra-national developments. Conclusions: This paper proposes statistical tools which provide a clear framework for the successful implementation of development public policies to help the UE meet the challenge of rethinking its social model (Social Security and health care) and make it sustainable in the medium term. es_ES
dc.description.sponsorship The authors are grateful for the financial support provided by the Ministry of Economy and Competitiveness, project MTM2013-45381-P. Adina Iftimi gratefully acknowledges financial support from the MECyD (Ministerio de Educacion, Cultura y Deporte, Spain) Grant FPU12/04531. Francisco Montes is grateful for the financial support provided by the Spanish Ministry of Economy and Competitiveness, project MTM2016-78917-R. The research by Patricia Carracedo and Ana Debon has been supported by a grant from the Mapfre Foundation. es_ES
dc.language Inglés es_ES
dc.publisher BioMed Central Ltd. es_ES
dc.relation.ispartof International Journal for Equity in Health es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Comparative Mortality Figure es_ES
dc.subject Spatial cluster es_ES
dc.subject Local Moran s Index es_ES
dc.subject Spatial Markov es_ES
dc.subject Euro es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Detecting spatio-temporal mortality clusters of European countries by sex and ag es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1186/s12939-018-0750-z es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//MTM2016-78917-R/ES/NUEVAS FAMILIAS DE PROCESOS ESTOCASTICOS ESPACIO-TEMPORALES QUE UNIFICAN GEOESTADISTICA Y PATRONES PUNTUALES. MODELIZACION, ESTIMACION, PREDICCION SOBRE NETWORKS Y TRAYECTORIA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU12%2F04531/ES/FPU12%2F04531/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//MTM2013-45381-P/ES/DIFERENCIAS DE LONGEVIDAD EN LA UNION EUROPEA: APLICACION DE NUEVOS METODOS PARA SU EVALUACION Y ANALISIS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Carracedo-Garnateo, P.; Debón Aucejo, AM.; Iftimi, A.; Montes-Suay, F. (2018). Detecting spatio-temporal mortality clusters of European countries by sex and ag. International Journal for Equity in Health. 17:1-19. https://doi.org/10.1186/s12939-018-0750-z es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1186/s12939-018-0750-z es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 19 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 17 es_ES
dc.identifier.eissn 1475-9276 es_ES
dc.identifier.pmid 29587774 es_ES
dc.identifier.pmcid PMC5870117 es_ES
dc.relation.pasarela S\356046 es_ES
dc.contributor.funder Fundación Mapfre es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.description.references Anderson TW, Goodman LA. Statistical Inference about Markov Chains. Ann Math Stat. 1957; 28(1):89–110. es_ES
dc.description.references Anselin L. Local Indicators of Spatial Association–LISA. Geographical Anal. 1995; 27(2):93–115. es_ES
dc.description.references Bilbao-Ubillos J. Is there still such a thing as the ‘European social model’?. Int J Soc Welf. 2016; 25:110–25. es_ES
dc.description.references Bivand R. spdep: Spatial Dependence:Weighting Schemes, Statistics and Models. 2012. R package version 0.5-53. http://CRAN.R-project.org/package=spdep . es_ES
dc.description.references Bivand R, Hauke J, Kossowski T. Computing the Jacobian in Gaussian Spatial Autoregressive Models: An Illustrated Comparison of Available Methods. Geographical Anal. 2013; 45(2):150–79. es_ES
dc.description.references Bivand R, Keitt T, Rowlingson B. rgdal: Bindings for the Geospatial Data Abstraction Library. 2016. R package version 1.1-10. https://CRAN.R-project.org/package=rgdal . es_ES
dc.description.references Bivand R, Lewin-Koh N. maptools: Tools for Reading and Handling Spatial Objects. 2016. R package version 0.8-39 https://CRAN.R-project.org/package=maptools . es_ES
dc.description.references Bonneux L, Huisman C. de Beer J. Mortality in 272 European regions, 2002-2004: an update. Eur J Epidemiol. 2010; 25(1):77–85. Reporting year: 2010. es_ES
dc.description.references Charpentier A. Computational Actuarial Science with R. Chapman y Hall/CRC. 2014. es_ES
dc.description.references Cliff AD, Ord JK. Spatial autocorrelation. London: Pion; 1973. es_ES
dc.description.references Cutler D, Deaton A, Lleras-Muney A. The Determinants of Mortality. J Econ Perspect. 2006; 20(3):97–120. es_ES
dc.description.references Debón A, Chaves L, Haberman S, Villa F. Characterization of between-group inequality of longevity in European Union countries. Insur Math Econ. 2017; 75:151–65. es_ES
dc.description.references Fleiss J, Levin B, Paik M. Statistical Methods for Rates and Proportions: Wiley; 2013. es_ES
dc.description.references Gordon M. Gmisc: Descriptive Statistics, Transition Plots, and More. 2016. R package version 1.3.1. https://CRAN.R-project.org/package=Gmisc . es_ES
dc.description.references Hinde A. Demographic methods. Routledge: Routledge; 1998. es_ES
dc.description.references Hyndman RJ, Booth H, Tickle L, Maindonald J. demography: Forecasting mortality, fertility, migration and population data. 2014. package version 1.18. https://CRAN.R-project.org/package=demography . es_ES
dc.description.references Human Mortality Database. University of California, Berkeley (USA), and Max Planck Institute for Demographic Research (Germany). 2016. Available at www.mortality.org or www.humanmortality.de (data downloaded on 12th July 2016). es_ES
dc.description.references Hatzopoulos P, Haberman S. Common mortality modeling and coherent forecasts. An empirical analysis of worldwide mortality data. Insurance Math Econ. 2013; 52(2):320–37. es_ES
dc.description.references Iftimi A, Montes F, Santiyán AM, Martínez-Ruiz F. Space–time airborne disease mapping applied to detect specific behaviour of varicella in Valencia, Spain Spatial Spatio-Temporal Epidemiol. 2015; 14:33–44. es_ES
dc.description.references Julious S, Nicholl J, George S. Why do we continue to use standardized mortality ratios for small area comparisons?. J Public Health. 2001; 23(1):40–6. es_ES
dc.description.references Laurent T, Ruiz-Gazen A, Thomas-Agnan C. GeoXp: An R package for exploratory spatial data analysis. J Stat Softw. 2012; 47(2):1–23. es_ES
dc.description.references Leon DA. Trends in European life expectancy: a salutary view. Int J Epidemiol. 2011; 40:271–7. es_ES
dc.description.references Li H, Li L, Wu B, Xiong Y. The End of Cheap Chinese Labor. J Econ Perspect. 2013; 26(4):57–74. es_ES
dc.description.references Mackenbach JP, Karanikolos M, McKee M. The unequal health of Europeans: successes and failures of policies. The Lancet. 2013; 381(9872):1125–34. es_ES
dc.description.references Meslé F. Mortality in Central and Eastern Europe: Long-term trends and recent upturns. Demographic Res. 2004; 2:45–70. es_ES
dc.description.references Meslé F, Vallin J. Mortality in Europe: The divergence between East and West. Population (English Edition). 2002; 57(1):157–97. es_ES
dc.description.references Moran PAP. Notes on continuous stochastic phenomena. Biometrika. 1950; 37(1-2):17–23. es_ES
dc.description.references Moran PAP. A Test for the Serial Independence of Residuals. Biometrika. 1950; 37(1/2):178–81. es_ES
dc.description.references Neuwirth E. RColorBrewer: ColorBrewer Palettes. R package version. 2014; 1:1–2. https://CRAN.R-project.org/package=RColorBrewer . es_ES
dc.description.references Oleckno WA. Epidemiology: concepts and methods: Waveland Press, Inc.; 2008. es_ES
dc.description.references Quah D. Galton’s Fallacy and Tests of the Convergence Hypothesis. Scand J Econ. 1993; 95(4):427–43. es_ES
dc.description.references R Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. 2015. https://www.R-project.org/ . es_ES
dc.description.references Rey S. In: Fischer MM, Nijkamp P, (eds).Spatial Dynamics and Space-Time Data Analysis. Berlin, Heidelberg: Springer: Handbook of Regional Science; 2014, pp. 1365–83. es_ES
dc.description.references Rey SJ. Spatial Empirics for Economic Growth and Convergence. Geogr Anal. 2001; 33(3):195–214. es_ES
dc.description.references Riffe T. Reading Human Fertility Database and Human Mortality Database data into R. Technical Report TR-2015-004, MPIDR. 2015. es_ES
dc.description.references Schofield R, Reher D, Bideau A. The Decline of Mortality in Europe. International studies in demography. Oxford: Clarendon Press; 1991. es_ES
dc.description.references Shaw M, Orford S, Brimblecombe N, Dorling D. Widening inequality in mortality between 160 regions of 15 European countries in the early 1990s. Soc Sci Med. 2000; 50(7-8):1047–58. es_ES
dc.description.references Spinakis A, Anastasiou G, Panousis V, Spiliopoulos K, Palaiologou S, Yfantopoulos J. Expert Review and Proposals for Measurement of Health Inequalities in the European Union. European Commission. Technical report,Luxembourg: European Commission Directorate General for Health and Consumers; 2011. http://ec.europa.eu/health/social_determinants/docs/full_quantos_en.pdf . es_ES
dc.description.references Staehr K. Economic transition in Estonia. Background, reforms and results In: Rindzeviciute E, editor. Contemporary Change in Estonia. Baltic and East European Studies. Sodertorns hogskola: Baltic and East European Studies: 2004. p. 437–67. es_ES
dc.description.references Trnka L, Dankova D, Zitova J, Cimprichova L, Migliori GB, Clancy L, Zellweger J. Survey of BCG vaccination policy in Europe: 1994-96. Bull World Health Organ. 1998; 76(1):85–91. es_ES
dc.description.references United Nations Inter–agency Group for Child Mortality Estimation. Levels & Trends in Child Mortality: Report 2013. New York: Technical report, United Nations Children’s Fund; 2013. Avaliable at www.who.int/maternal_child_adolescent/documents/levels_trends_child_mortality_2013.pdf Accessed 27 Oct 2016. es_ES
dc.description.references Vågerö D. The east–west health divide in Europe: Growing and shifting eastwards. Eur Rev. 2010; 18(01):23–34. es_ES
dc.description.references Vaupel JW, Zhang Z, van Raalte AA, Vaupel JW, Zhang Z, van Raalte AA. Life expectancy and disparity: an international comparison of life table data. BMJ Open. 2011; 1:e000128. es_ES
dc.description.references Wickham H, Chang W. devtools: Tools to Make Developing R Packages Easier. R package version 1.11.1. 2016. https://CRAN.R-project.org/package=devtools . es_ES
dc.description.references Wilcox R. Introduction to robust estimation and hypothesis testing, 3rd Edition.San Diego: Academic Press; 2012. es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem