Heat Effects on Mortality in 15 European Cities

Baccini, Michela; Biggeri, Annibale; Accetta, Gabriele; Kosatsky, Tom; Katsouyanni, Klea; Analitis, Antonis; Anderson, Hugh; Bisanti, Luigi; D’Ippoliti, Daniela; Dáňová, Jana; Forsberg, Bertil; Médina, Sylvia; Páldy, Anna; Rabczenko, Daniel; Schindler, Christian; Michelozzi, Paola

doi:10.1097/ede.0b013e318176bfcd

Cited by 749 publications

(675 citation statements)

References 30 publications

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“…Previous studies reported that temperature-related mortalities are more pronounced in the elderly (Revich and Shaposhnikov 2008;Anderson and Bell 2009). However, the heterogeneity among different age groups is worth further examination (Hajat et al 2007;Baccini et al 2008;Ishigami et al 2008). In this study, we investigated both effects of heat and cold temperatures on different types of mortality (including non-accidental, cardiopulmonary, cardiovascular, and respiratory) and age-specific non-accidental mortality.…”

Section: Introductionmentioning

confidence: 99%

Effects of temperature on mortality in Hong Kong: a time series analysis

Chan

2014

Int J Biometeorol

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Although interest in assessing the impacts of hot temperature and mortality in Hong Kong has increased, less evidence on the effect of cold temperature on mortality is available. We examined both the effects of heat and cold temperatures on daily mortality in Hong Kong for the last decade (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011). A quasi-Poisson model combined with a distributed lag non-linear model was used to assess the non-linear and delayed effects of temperatures on cause-specific and age-specific mortality.Non-linear effects of temperature on mortality were identified. The relative risk of non-accidental mortality associated with cold temperature (11.1°C, 1 st percentile of temperature) relative to 19.4°C(25 th percentile of temperature) was 1.17 (95% confidence interval (CI): 1.04, 1.29) for lags 0-13. The relative risk of non-accidental mortality associated with high temperature (31.5°C, 99 th percentile of temperature) relative to 27.8°C (75 th percentile of temperature) was 1.09 (95% CI: 1.03, 1.17) for lags 0-3. In Hong Kong, extreme cold and hot temperatures increased the risk of mortality. The effect of cold lasted longer and greater than that of heat. People older than 75 years were the most vulnerable group to cold temperature, while people aged 65-74 were the most vulnerable group to hot temperature.Our findings may have implications for developing intervention strategies for extreme cold and hot temperatures.

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Section: Introductionmentioning

confidence: 99%

Effects of temperature on mortality in Hong Kong: a time series analysis

Chan

2014

Int J Biometeorol

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“…Amaury de Souza (1) Flavio Aristone (1) Luciane Fernandes (1) Li Bai (2) Weiwei Yu (3) Débora Aparecida da Silva Santos (1) Ismail Sabba (4) ingresos por enfermedades respiratorias y franja de edad. Las mayores medias de ingreso se dieron en la franja de …”

Section: Artigo Originalunclassified

Hospitalizações por infecção respiratória associada a fatores ambientais

Souza¹,

Aristone²,

Fernandes³

et al. 2014

RBPS

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RESUMOObjetivo: Avaliar a relação entre variáveis meteorológicas e doenças respiratórias por faixa etária. Métodos: Trata-se de um estudo ecológico de séries temporais para o período compreendido entre 2008 e 2011. Primeiramente, as internações foram analisadas por grupo de faixa etária e, em seguida, relacionadas com informações climáticas, temperatura, precipitação, umidade relativa do ar e velocidade dos ventos, através da climatologia dinâmica e de parâmetros estatísticos, utilizando análise de regressão múltipla, teste qui-quadrado e distribuição normal. Resultados: Os resultados mostraram 12.067 registros de internações por doenças respiratórias e por faixa etária. As maiores médias de internação ocorreram na faixa etária de 1 a 4 anos, com média de 42,09%, (5.079) e acima de 60 anos, com média de 27,14% (3.274) para o período de estudo, sendo as pneumonias predominantes, com 81,0% (9.774) das internações. Verificou-se menor número de internações em janeiro e maior, em junho e julho. Conclusão: Com base nas investigações realizadas, observou-se correlação significativa entre os parâmetros climáticos e as internações por doenças respiratórias. Descritores

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“…This lag is consistent with the lag modeling done using the DLNM testing of the mortality data (not shown). Minimum temperatures represent a measure that has been highlighted in earlier research (BACCINI et al 2011;BACCINI et al 2008). The theoretical explanation for the impact of high minimum temperatures on health is that this temperature represents the level of physiological respite from heat that an organism gets at night.…”

Section: The Formula For Calculating the Relaic For Model I Is: Exp((mentioning

confidence: 99%

“…The analytical method chosen was a good fit for the project, as it was well adapted to the data available (only cases, limited cofactors) and an estimate of the exposure effect in Barcelona is not needed, as this work has already been done (MATTHIES & MENNE 2009;BACCINI et al 2011;BACCINI et al 2008;SAÉZ et al 2000). Because the available, spatially located mortality data had only two cofactors (age and sex), modeling interactions would have been limited, even using a more complex analytical methodology.…”

Section: Appropriateness Of a Case-only Design For This Studymentioning

confidence: 99%

Excess Heat-Related Mortality in Micro-Urban Heat Islands: A Case-only Study in Barcelona

Glutting¹

2013

GI_Forum 2013 – Creating the GISociety

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Background: Extreme heat events (EHE) are of increasing public health concern. In urban areas, micro-urban heat islands (MUHI) raise the possibility of increased mortality risk. This study identified MUHI in the city of Barcelona, Spain, using Landsat 7 thermal infrared imagery and overlaid them onto at-home deaths between 2000-2003, identified from a mortality registry and geocoded using the Google API. Hot days were defined as days with mean minimum temperatures above the 90 th percentile of historic temperatures. Data were analyzed using a case-only design, with a logistic regression model adjusted for spatial autocorrelation. Results: In the period 2000-2003, at-home deaths in MUHI were associated with 15% greater odds of dying on hot days than at-home deaths outside of MUHI. Conclusions: MUHI were a risk factor for at-home deaths during EHE in the study period (2000)(2001)(2002)(2003) in the city of Barcelona. In urban areas facing similar conditions (limited use of air-conditioning, among others), residents of MUHI may be at increased mortality risk during extreme heat events.

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Heat Effects on Mortality in 15 European Cities

Cited by 749 publications

References 30 publications

Effects of temperature on mortality in Hong Kong: a time series analysis

Effects of temperature on mortality in Hong Kong: a time series analysis

Hospitalizações por infecção respiratória associada a fatores ambientais

Excess Heat-Related Mortality in Micro-Urban Heat Islands: A Case-only Study in Barcelona

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