Abstract
BackgroundEvidence that elevated temperatures can lead to increased mortality is well documented, with population vulnerability being location specific. However, very few studies have been conducted that assess the effects of temperature on daily mortality in urban areas in Portugal.MethodsIn this paper time-series analysis was used to model the relationship between mean apparent temperature and daily mortality during the warm season (April to September) in the two largest urban areas in Portugal: Lisbon and Oporto. We used generalized additive Poisson regression models, adjusted for day of week and season.ResultsOur results show that in Lisbon, a 1°C increase in mean apparent temperature is associated with a 2.1% (95%CI: 1.6, 2.5), 2.4% (95%CI: 1.7, 3.1) and 1.7% (95%CI: 0.1, 3.4) increase in all-causes, cardiovascular, and respiratory mortality, respectively. In Oporto the increase was 1.5% (95%CI: 1.0, 1.9), 2.1% (95%CI: 1.3, 2.9) and 2.7% (95%CI: 1.2, 4.3) respectively. In both cities, this increase was greater for the group >65 years.ConclusionEven without extremes in apparent temperature, we observed an association between temperature and daily mortality in Portugal. Additional research is needed to allow for better assessment of vulnerability within populations in Portugal in order to develop more effective heat-related morbidity and mortality public health programs.
Highlights
Evidence that elevated temperatures can lead to increased mortality is well documented, with population vulnerability being location specific
Some groups adopted for a time series approach, while others focus on extreme events such as heat waves and cold spells using episode analysis
Statistical Methods Similar to Basu et al [17] we investigated the association between mean apparent temperature and daily mortality using generalized additive models (GAM), with a quasiPoisson link function, in the warm period (April to September)
Summary
Evidence that elevated temperatures can lead to increased mortality is well documented, with population vulnerability being location specific. Recent extreme weather events, such the European heatwave in 2003, have attracted renewed interest on weather-related health effects [2,3]. Since climate change will likely increase the mean temperature, as well as the frequency of heat events [4] there is an urgent need to evaluate the links between climate and human health, to better identify vulnerable populations and take preventive measures. Previous studies have reported that days of usually low and high ambient temperatures are associated with increases in mortality and morbidity [5,6,7,8,9]. In Europe, populations living in urban environments as well as the elderly have a high risk of mortality from ambient heat exposure [10].
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