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dc.contributor.authorLopez-Bueno, Jose Antonio 
dc.contributor.authorNavas-Martín, Miguel Ángel 
dc.contributor.authorDiaz-Jimenez, Julio 
dc.contributor.authorMirón, Isidro Juan
dc.contributor.authorLuna, María Yolanda
dc.contributor.authorSánchez-Martínez, Gerardo
dc.contributor.authorCulqui, Dante R 
dc.contributor.authorLinares-Gil, Cristina 
dc.date.accessioned2022-04-28T10:51:55Z
dc.date.available2022-04-28T10:51:55Z
dc.date.issued2021-06-19
dc.identifier.citationEnviron Sci Eur. 2021; 33, 72.es_ES
dc.identifier.issn2190-4707es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12105/14215
dc.description.abstractBackground: While many studies analyze the effect of extreme thermal events on health, little has been written about the effects of extreme cold on mortality. This scarcity of papers is particularly relevant when we search studies about extreme cold on the health of rural population. Therefore, we tried to analyze the effect of cold waves on urban areas and rural areas from Madrid and to test whether differentiated effects exist between both population classes. For this purpose, we analyzed data from the municipalities with over 10,000 inhabitants for the period from January 1, 2000 through December 31, 2013. Municipalities were classified as urban or rural (Eurostat), and they were grouped into similar climatological zones: Urban Metropolitan Centre (UMC), Rural Northern Mountains (RNM), Rural Centre (RC) and Southern Rural (SR). The dependent variable was the daily mortality rate due to natural causes per million inhabitants (CIE-X: A00-R99) that occurred between the months of November and March for the period. The independent variable was minimum daily temperature (ºC) (Tmin). Social and demographic contextual variables were used, including: population > age 64 (%), deprivation index and housing indicators. The analysis was carried out in three phases: (1) determination of the threshold temperature (Tthreshold) which defines the cold waves; (2) determination of the relative risk (RR) for cold waves using Poisson linear regression (GLM); and (3) using GLM of the binomial family, Odds Ratios (OR) were calculated to analyze the relationship between the frequency of the appearance of cold waves and the socioeconomic variables. Results:The UMC zone experienced 585 extreme cold events related to attributable increases in the mortality rate. The average number of cold waves in the rural zones was 319. The primary risk factor was the percentage of population over age 64, and the primary protective factor was housing rehabilitation. As a whole, the period experienced more cold waves (1542) than heat waves (1130). Conclusion: The UMC was more vulnerable than the rural areas. Furthermore, the results support the development of prevention policies, especially considering the fact that cold wave events were more frequent than heat waves.es_ES
dc.description.sponsorshipThe authors gratefully acknowledge the grants for projects ENPY376/18; ENPY470/19 and ENPY 107/18 from the Carlos III Institute of Health.es_ES
dc.language.isoenges_ES
dc.publisherSpringer es_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectCold waveses_ES
dc.subjectMortalityes_ES
dc.subjectUrban–rurales_ES
dc.subjectDeprivationes_ES
dc.subjectBuilding qualityes_ES
dc.subjectAginges_ES
dc.titleThe effect of cold waves on mortality in urban and rural areas of Madrides_ES
dc.typeArtículoes_ES
dc.rights.licenseAtribución 4.0 Internacional*
dc.format.volume33es_ES
dc.format.number72es_ES
dc.identifier.doi10.1186/s12302-021-00512-zes_ES
dc.contributor.funderInstituto de Salud Carlos IIIes_ES
dc.description.peerreviewedes_ES
dc.identifier.e-issn2190-4715es_ES
dc.relation.publisherversionhttps://doi.org/10.1186/s12302-021-00512-zes_ES
dc.identifier.journalEnvironmental Sciences Europees_ES
dc.repisalud.centroISCIII::Escuela Nacional de Sanidades_ES
dc.repisalud.institucionISCIIIes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.relation.projectFISinfo:eu-repo/grantAgreement/ES/ENPY376/18es_ES
dc.relation.projectFISinfo:eu-repo/grantAgreement/ES/ENPY470/19es_ES
dc.relation.projectFISinfo:eu-repo/grantAgreement/ES/ENPY107/18es_ES


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