Cristina Linares
Senior scientist at the Carlos III Health Institute
Julio Díaz
Research professor and co-director of the Reference Unit on Climate Change, Health and the Urban Environment at the Carlos III Health Institute
We think it is an interesting article to have a global view of what will be the population over 65 years of age affected by certain temperatures in different emission scenarios.
The problem with these global studies is that they use exposure to standard temperatures to define heatwave days and their intensity, regardless of local characteristics, which go beyond fixed temperatures and fixed percentiles. In fact, this article states: ‘we use the annual count of hot days (#HDs: days with maximum temperature exceeding 37.5° C) and the 95th percentile of the 20 y daily maximum temperature distribution (TMAX95)’.
These definitions are not in line with those of the WHO, which establishes that in order to analyse the impact on mortality of heatwave days and the intensity of the heatwave, this cannot be done on the basis of meteorological criteria alone, but on the basis of epidemiological temperature-mortality relationships, since heat-related mortality is influenced by more factors than just meteorology, such as income level, socioeconomic, demographic, health or urban planning conditions.
For example, in Spain, according to the definition of heat wave set out in this article, there would be one person at risk when according to the Ministry of Health values this would not be the case. For example, Badajoz, Cordoba, Seville and others have a heatwave definition temperature above 37.5ºC. In other words, in these cities, for daily maximum temperatures of 37.5ºC there is no significant impact on mortality.
On the other hand, defining the intensity of the heatwave based on a fixed percentile (95 %) would not be representative for Spain where, at the isoclimatic level, in 52.5 % of the regions the heatwave definition temperatures are below the 95th percentile.
In summary, the study presented serves to analyse the percentage of the elderly population subjected to certain temperature conditions, but not to infer health impacts.