Temporal evolution the dose-response relation of temperature-mortality in Aragón (Spain) over the period 1987 to 2006
The relationship between temperature and mortality from heat waves is influenced by socioeconomic, demographic and climate factors that make necessary to study under a local perspective. This factors change over a timescale, so it’s necessary to analyze them in a local bias for extrapolate the results over time through weather prediction models.
The aim of this study was to determine the temperature threshold that triggers an increase in heat-induced mortality in Aragón, Spain to determine their impact on mortality and costs.
METHODS:
A longitudinal ecological study was conducted according to an autoregressive integrated moving average (ARIMA) model of a time series for daily deaths. After establishing cross-correlation functions (CCFs) and a subsequent modelling of a multivariate ARIMA model with exogenous variables, the impact on the mortality was assessed as the relative risk of mortality for each degree that the temperature threshold was exceeded.
RESULTS:
Mortality showed a statistically significant increase when the daily maximum temperature exceeded the threshold of 38°C for 1987 to 2006. The threshold was equal in the three time periods (1987-1993, 1994-2000, and 2001-2006) into which this time period was divided.
A relative risk of mortality of 1,38 (IC95% 1,09-1,88) was established for each degree that exceeded 38°C for 1987-2006. This risk was also calculated for time periods: 1,36 (IC95% 1,08-1,82) from 1987-93; 1,35 (IC95% 1,10-1,73) in the period 1994-2000 and 1,22 (IC95% 1,05-1,47) across 2001- 2006. No statistically significant differences between the three research periods.
CONCLUSIONS:
Exposure to extreme high temperatures led to a significant increase in the mortality rate. Thus, the articulation of preventive measures to minimise the impact of extreme heat on human health is necessary.
The relative risk is constant over the study period indicate the need for studies on a longer time horizon that allows us to detect changes as study points.