tetano
Editor, Senior Moderator
Int J Biometeorol. 2016 Jun 18. [Epub ahead of print]
[h=1]The effect of extreme cold temperatures on the risk of death in the two major Portuguese cities.[/h] Antunes L[SUP]1,[/SUP][SUP]2[/SUP], Silva SP[SUP]3[/SUP], Marques J[SUP]4[/SUP], Nunes B[SUP]3,[/SUP][SUP]5[/SUP], Antunes S[SUP]4[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] It is well known that meteorological conditions influence the comfort and human health. Southern European countries, including Portugal, show the highest mortality rates during winter, but the effects of extreme cold temperatures in Portugal have never been estimated. The objective of this study was the estimation of the effect of extreme cold temperatures on the risk of death in Lisbon and Oporto, aiming the production of scientific evidence for the development of a real-time health warning system. Poisson regression models combined with distributed lag non-linear models were applied to assess the exposure-response relation and lag patterns of the association between minimum temperature and all-causes mortality and between minimum temperature and circulatory and respiratory system diseases mortality from 1992 to 2012, stratified by age, for the period from November to March. The analysis was adjusted for over dispersion and population size, for the confounding effect of influenza epidemics and controlled for long-term trend, seasonality and day of the week. Results showed that the effect of cold temperatures in mortality was not immediate, presenting a 1-2-day delay, reaching maximum increased risk of death after 6-7 days and lasting up to 20-28 days. The overall effect was generally higher and more persistent in Lisbon than in Oporto, particularly for circulatory and respiratory mortality and for the elderly. Exposure to cold temperatures is an important public health problem for a relevant part of the Portuguese population, in particular in Lisbon.
[h=4]KEYWORDS:[/h] Cold effect; Distributed lag non-linear models; Minimum temperature; Mortality; Relative risk
PMID: 27318999 [PubMed - as supplied by publisher]
[h=1]The effect of extreme cold temperatures on the risk of death in the two major Portuguese cities.[/h] Antunes L[SUP]1,[/SUP][SUP]2[/SUP], Silva SP[SUP]3[/SUP], Marques J[SUP]4[/SUP], Nunes B[SUP]3,[/SUP][SUP]5[/SUP], Antunes S[SUP]4[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] It is well known that meteorological conditions influence the comfort and human health. Southern European countries, including Portugal, show the highest mortality rates during winter, but the effects of extreme cold temperatures in Portugal have never been estimated. The objective of this study was the estimation of the effect of extreme cold temperatures on the risk of death in Lisbon and Oporto, aiming the production of scientific evidence for the development of a real-time health warning system. Poisson regression models combined with distributed lag non-linear models were applied to assess the exposure-response relation and lag patterns of the association between minimum temperature and all-causes mortality and between minimum temperature and circulatory and respiratory system diseases mortality from 1992 to 2012, stratified by age, for the period from November to March. The analysis was adjusted for over dispersion and population size, for the confounding effect of influenza epidemics and controlled for long-term trend, seasonality and day of the week. Results showed that the effect of cold temperatures in mortality was not immediate, presenting a 1-2-day delay, reaching maximum increased risk of death after 6-7 days and lasting up to 20-28 days. The overall effect was generally higher and more persistent in Lisbon than in Oporto, particularly for circulatory and respiratory mortality and for the elderly. Exposure to cold temperatures is an important public health problem for a relevant part of the Portuguese population, in particular in Lisbon.
[h=4]KEYWORDS:[/h] Cold effect; Distributed lag non-linear models; Minimum temperature; Mortality; Relative risk
PMID: 27318999 [PubMed - as supplied by publisher]