Mortality by cause of death in Colombia: a local analysis using spatial econometrics

Colombia is undergoing major changes in mortality patterns. National- and depart-ment-level cause-specific analyses have previously been carried out, but very little is known about municipal-level trends, despite their epidemiological interest. We first analyze standardized mortality rates for seven...

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Autores:
Spijker, Jeroen
Recaño, Joaquín
Martínez, Sandra
Carioli, Alessandra
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Universidad El Bosque
Repositorio:
Repositorio U. El Bosque
Idioma:
eng
OAI Identifier:
oai:repositorio.unbosque.edu.co:20.500.12495/4066
Acceso en línea:
http://hdl.handle.net/20.500.12495/4066
https://doi.org/10.1007/s10109-020-00335-1
https://repositorio.unbosque.edu.co
Palabra clave:
Spatial cluster analysis
Spatial Durbin model
Mortality
Causes of death
Epidemiology
Colombia
Rights
openAccess
License
Acceso abierto
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dc.title.spa.fl_str_mv Mortality by cause of death in Colombia: a local analysis using spatial econometrics
dc.title.translated.spa.fl_str_mv Mortality by cause of death in Colombia: a local analysis using spatial econometrics
title Mortality by cause of death in Colombia: a local analysis using spatial econometrics
spellingShingle Mortality by cause of death in Colombia: a local analysis using spatial econometrics
Spatial cluster analysis
Spatial Durbin model
Mortality
Causes of death
Epidemiology
Colombia
title_short Mortality by cause of death in Colombia: a local analysis using spatial econometrics
title_full Mortality by cause of death in Colombia: a local analysis using spatial econometrics
title_fullStr Mortality by cause of death in Colombia: a local analysis using spatial econometrics
title_full_unstemmed Mortality by cause of death in Colombia: a local analysis using spatial econometrics
title_sort Mortality by cause of death in Colombia: a local analysis using spatial econometrics
dc.creator.fl_str_mv Spijker, Jeroen
Recaño, Joaquín
Martínez, Sandra
Carioli, Alessandra
dc.contributor.author.none.fl_str_mv Spijker, Jeroen
Recaño, Joaquín
Martínez, Sandra
Carioli, Alessandra
dc.subject.keywords.spa.fl_str_mv Spatial cluster analysis
Spatial Durbin model
Mortality
Causes of death
Epidemiology
Colombia
topic Spatial cluster analysis
Spatial Durbin model
Mortality
Causes of death
Epidemiology
Colombia
description Colombia is undergoing major changes in mortality patterns. National- and depart-ment-level cause-specific analyses have previously been carried out, but very little is known about municipal-level trends, despite their epidemiological interest. We first analyze standardized mortality rates for seven cause-of-death groups to obtain high and low mortality clusters based on the spatial autocorrelation indicators Global Moran’s I and Local Moran’s I. The Mann–Whitney nonparametric test is then used to ascertain statistical associations between the high and low mortality clus-ters and known health determinants. We subsequently apply spatial lag and Durbin (when spatial autocorrelation was present) and OLS models (when not) to explain overall spatial patterns in cause-specific mortality. Age- and sex-specific cause-of-death mortality and population data were obtained from the National Administrative Department of Statistics (DANE). Deaths were corrected for each municipality due to under-registration. Results show that spatial autocorrelation declined over time for all cause-of-death categories, except male circulatory system diseases and peri-natal mortality. It is highest in external causes, especially among men, with mortal-ity hotspots moving from the central Andean area to Orinoquia and the Amazon rainforest. Male mortality is also more spatially clustered than female mortality and especially neoplasms, and external-cause mortality is also indirectly affected by the conditions of neighboring municipalities. Municipal surface area, ethnicity and pub-lic expenditure on health and education are the most frequent contextual variables explaining territorial differences in mortality. The identification of geographical mortality clusters in Colombia will allow decision makers to prioritize those regions with higher mortality.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-09-11T20:54:14Z
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dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/s10109-020-00335-1
dc.identifier.instname.spa.fl_str_mv instname:Universidad El Bosque
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https://doi.org/10.1007/s10109-020-00335-1
https://repositorio.unbosque.edu.co
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartofseries.spa.fl_str_mv Journal of geographical systems, 1435-5949, 2020
dc.relation.uri.none.fl_str_mv https://link.springer.com/article/10.1007%2Fs10109-020-00335-1
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2020-08-13
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dc.publisher.journal.spa.fl_str_mv Journal of geographical systems
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spelling Spijker, JeroenRecaño, JoaquínMartínez, SandraCarioli, Alessandra2020-09-11T20:54:14Z2020-09-11T20:54:14Z1435-5949http://hdl.handle.net/20.500.12495/4066https://doi.org/10.1007/s10109-020-00335-1instname:Universidad El Bosquereponame:Repositorio Institucional Universidad El Bosquehttps://repositorio.unbosque.edu.coapplication/pdfengSpringer NatureJournal of geographical systemsJournal of geographical systems, 1435-5949, 2020https://link.springer.com/article/10.1007%2Fs10109-020-00335-1Mortality by cause of death in Colombia: a local analysis using spatial econometricsMortality by cause of death in Colombia: a local analysis using spatial econometricsArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85Spatial cluster analysisSpatial Durbin modelMortalityCauses of deathEpidemiologyColombiaColombia is undergoing major changes in mortality patterns. National- and depart-ment-level cause-specific analyses have previously been carried out, but very little is known about municipal-level trends, despite their epidemiological interest. We first analyze standardized mortality rates for seven cause-of-death groups to obtain high and low mortality clusters based on the spatial autocorrelation indicators Global Moran’s I and Local Moran’s I. The Mann–Whitney nonparametric test is then used to ascertain statistical associations between the high and low mortality clus-ters and known health determinants. We subsequently apply spatial lag and Durbin (when spatial autocorrelation was present) and OLS models (when not) to explain overall spatial patterns in cause-specific mortality. Age- and sex-specific cause-of-death mortality and population data were obtained from the National Administrative Department of Statistics (DANE). Deaths were corrected for each municipality due to under-registration. Results show that spatial autocorrelation declined over time for all cause-of-death categories, except male circulatory system diseases and peri-natal mortality. It is highest in external causes, especially among men, with mortal-ity hotspots moving from the central Andean area to Orinoquia and the Amazon rainforest. Male mortality is also more spatially clustered than female mortality and especially neoplasms, and external-cause mortality is also indirectly affected by the conditions of neighboring municipalities. Municipal surface area, ethnicity and pub-lic expenditure on health and education are the most frequent contextual variables explaining territorial differences in mortality. The identification of geographical mortality clusters in Colombia will allow decision makers to prioritize those regions with higher mortality.Acceso abiertohttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessAcceso abierto2020-08-13ORIGINALJeroen Spijker, Joaquín Recaño_2020.pdfJeroen Spijker, Joaquín Recaño_2020.pdfapplication/pdf1917200https://repositorio.unbosque.edu.co/bitstreams/8bfb4f55-998a-4a21-874a-6bfc218c7856/downloadbb399b55018ca8495644390dd84e3238MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.unbosque.edu.co/bitstreams/2db61d13-6e1d-4e87-8de8-8919d51fd8c3/download8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILJeroen Spijker, Joaquín Recaño_2020.pdf.jpgJeroen Spijker, Joaquín Recaño_2020.pdf.jpgIM Thumbnailimage/jpeg8892https://repositorio.unbosque.edu.co/bitstreams/8a0c8316-4a20-484d-a25d-8c2f3de28a2b/downloadddf751a3b05356a8793adc0cac9e6425MD53TEXTJeroen Spijker, Joaquín Recaño_2020.pdf.txtJeroen Spijker, Joaquín Recaño_2020.pdf.txtExtracted texttext/plain101116https://repositorio.unbosque.edu.co/bitstreams/c7c04816-f0cc-42be-b9b9-c2fc5d638257/download0f73276cba0f5902bf94f9cf207c729bMD5420.500.12495/4066oai:repositorio.unbosque.edu.co:20.500.12495/40662024-02-07 10:23:22.664restrictedhttps://repositorio.unbosque.edu.coRepositorio Institucional Universidad El Bosquebibliotecas@biteca.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