Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model

Bibliographic Details
Main Author: Rodrigues, Mónica Alexandra dos Santos Rodrigues
Publication Date: 2019
Other Authors: Rodrigues, Ana Paula Santana, Rocha, Alfredo
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/10316/89035
https://doi.org/10.1007/s00484-019-01685-2
Summary: Cerebrovascular diseases are the leading cause of mortality in Portugal, especially when related with extreme temperatures. This study highlights the impacts of the exposure-response relationship or lagged effect of low and high temperatures on cerebrovascular mortality, which can be important to reduce the health burden from cerebrovascular diseases. The purpose of this study was to assess the effects of weather on cerebrovascular mortality, measured by ambient temperature in the District of Lisbon, Portugal. A quasi-Poisson generalized additive model combined with a distributed lag non-linear model was applied to estimate the delayed effects of temperature on cerebrovascular mortality up to 30 days. With reference to minimum mortality temperature threshold of 22 °C, there was a severe risk (RR = 2.09, 95% CI 1.74, 2.51) of mortality for a 30-day-cumulative exposure to extreme cold temperatures of 7.3 °C (1st percentile). Similarly, the cumulative effect of a 30-day exposure to an extreme hot temperature of 30 °C (99th percentile) was 52% (RR = 1.65, 95% CI 1.37, 1.98) higher than same-day exposure. Over the 13 years of study, non-linear effects of temperature on mortality were identified, and the probability of dying from cerebrovascular disease in Lisbon was 7% higher in the winter than in the summer. The findings of this study provide a baseline for future public health prevention programs on weather-related mortality.
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spelling Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear modelCerebrovascular diseasesDistributed lag non-linear model (DLNM)Extreme temperaturesLag effectsPortugalCerebrovascular diseases are the leading cause of mortality in Portugal, especially when related with extreme temperatures. This study highlights the impacts of the exposure-response relationship or lagged effect of low and high temperatures on cerebrovascular mortality, which can be important to reduce the health burden from cerebrovascular diseases. The purpose of this study was to assess the effects of weather on cerebrovascular mortality, measured by ambient temperature in the District of Lisbon, Portugal. A quasi-Poisson generalized additive model combined with a distributed lag non-linear model was applied to estimate the delayed effects of temperature on cerebrovascular mortality up to 30 days. With reference to minimum mortality temperature threshold of 22 °C, there was a severe risk (RR = 2.09, 95% CI 1.74, 2.51) of mortality for a 30-day-cumulative exposure to extreme cold temperatures of 7.3 °C (1st percentile). Similarly, the cumulative effect of a 30-day exposure to an extreme hot temperature of 30 °C (99th percentile) was 52% (RR = 1.65, 95% CI 1.37, 1.98) higher than same-day exposure. Over the 13 years of study, non-linear effects of temperature on mortality were identified, and the probability of dying from cerebrovascular disease in Lisbon was 7% higher in the winter than in the summer. The findings of this study provide a baseline for future public health prevention programs on weather-related mortality.Springer2019-02-23info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://hdl.handle.net/10316/89035https://hdl.handle.net/10316/89035https://doi.org/10.1007/s00484-019-01685-2eng0020-71281432-1254https://link.springer.com/article/10.1007%2Fs00484-019-01685-2Rodrigues, Mónica Alexandra dos Santos RodriguesRodrigues, Ana Paula SantanaRocha, Alfredoinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2020-05-25T05:32:58Zoai:estudogeral.uc.pt:10316/89035Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T05:36:53.924708Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model
title Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model
spellingShingle Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model
Rodrigues, Mónica Alexandra dos Santos Rodrigues
Cerebrovascular diseases
Distributed lag non-linear model (DLNM)
Extreme temperatures
Lag effects
Portugal
title_short Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model
title_full Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model
title_fullStr Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model
title_full_unstemmed Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model
title_sort Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model
author Rodrigues, Mónica Alexandra dos Santos Rodrigues
author_facet Rodrigues, Mónica Alexandra dos Santos Rodrigues
Rodrigues, Ana Paula Santana
Rocha, Alfredo
author_role author
author2 Rodrigues, Ana Paula Santana
Rocha, Alfredo
author2_role author
author
dc.contributor.author.fl_str_mv Rodrigues, Mónica Alexandra dos Santos Rodrigues
Rodrigues, Ana Paula Santana
Rocha, Alfredo
dc.subject.por.fl_str_mv Cerebrovascular diseases
Distributed lag non-linear model (DLNM)
Extreme temperatures
Lag effects
Portugal
topic Cerebrovascular diseases
Distributed lag non-linear model (DLNM)
Extreme temperatures
Lag effects
Portugal
description Cerebrovascular diseases are the leading cause of mortality in Portugal, especially when related with extreme temperatures. This study highlights the impacts of the exposure-response relationship or lagged effect of low and high temperatures on cerebrovascular mortality, which can be important to reduce the health burden from cerebrovascular diseases. The purpose of this study was to assess the effects of weather on cerebrovascular mortality, measured by ambient temperature in the District of Lisbon, Portugal. A quasi-Poisson generalized additive model combined with a distributed lag non-linear model was applied to estimate the delayed effects of temperature on cerebrovascular mortality up to 30 days. With reference to minimum mortality temperature threshold of 22 °C, there was a severe risk (RR = 2.09, 95% CI 1.74, 2.51) of mortality for a 30-day-cumulative exposure to extreme cold temperatures of 7.3 °C (1st percentile). Similarly, the cumulative effect of a 30-day exposure to an extreme hot temperature of 30 °C (99th percentile) was 52% (RR = 1.65, 95% CI 1.37, 1.98) higher than same-day exposure. Over the 13 years of study, non-linear effects of temperature on mortality were identified, and the probability of dying from cerebrovascular disease in Lisbon was 7% higher in the winter than in the summer. The findings of this study provide a baseline for future public health prevention programs on weather-related mortality.
publishDate 2019
dc.date.none.fl_str_mv 2019-02-23
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
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dc.identifier.uri.fl_str_mv https://hdl.handle.net/10316/89035
https://hdl.handle.net/10316/89035
https://doi.org/10.1007/s00484-019-01685-2
url https://hdl.handle.net/10316/89035
https://doi.org/10.1007/s00484-019-01685-2
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https://link.springer.com/article/10.1007%2Fs00484-019-01685-2
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dc.publisher.none.fl_str_mv Springer
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