Please use this identifier to cite or link to this item:http://hdl.handle.net/20.500.12105/14216
Evolution of the threshold temperature definition of a heat wave vs. evolution of the minimum mortality temperature: a case study in Spain during the 1983–2018 period
Environ Sci Eur. 2021; 33:101.
Background: An area of current study concerns analysis of the possible adaptation of the population to heat, based on the temporal evolution of the minimum mortality temperature (MMT). It is important to know how is the evolution of the threshold temperatures (Tthreshold) due to these temperatures provide the basis for the activation of public health prevention plans against high temperatures. The objective of this study was to analyze the temporal evolution of threshold temperatures (Tthreshold) produced in diferent Spanish regions during the 1983–2018 period and to compare this evolution with the evolution of MMT. The dependent variable used was the raw rate of daily mortality due to natural causes ICD X: (A00-R99) for the considered period. The independent variable was maximum daily temperature (Tmax) during the summer months registered in the reference observatory of each region. Threshold values were determined using dispersion diagrams (annual) of the prewhitened series of mortality temperatures and Tmax. Later, linear ft models were carried out between the diferent values of Tthreshold throughout the study period, which permitted detecting the annual rate of change in Tthreshold. Results: The results obtained show that, on average, Tthreshold has increased at a rate of 0.57 ºC/decade in Spain, while Tmax temperatures in the summer have increased at a rate of 0.41 ºC/decade, suggesting adaptation to heat. This rate of evolution presents important geographic heterogeneity. Also, the rate of evolution of Tthreshold was similar to what was detected for MMT. Conclusions: The temporal evolution of the series of both temperature measures can be used as indicators of population adaptation to heat. The temporal evolution of Tthreshold has important geographic variation, probably related to sociodemographic and economic factors, that should be studied at the local level.
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