Projection of mortality attributed to heat and cold; the impact of climate change in a dry region of Iran, Kerman

Abstract

BackgroundEstimating the effects of climate change on human health can help health policy makers plan for the future. In Iran, there are few studies, about investigating the effects of climate change on mortality. This study aimed to project the effect of low (cold) and high (heat) temperature on mortality in a dry region of Iran, Kerman. MethodsMortality attributed to temperature was projected by estimating the temperature-mortality relation for the observed data, projection of future temperatures by the statistical downscaling model (SDSM), and quantifying the attributable fraction by applying the observed temperature-mortality relation on the projected temperature. Climate change projection was done by three climate scenarios base on Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). Adaptation was considered by using different minimum mortality temperatures (MMT) and risk reduction approaches. The current decade (2010–19) was considered as the reference period. ResultsAll three climate change scenarios, showed that the mean of temperature will rise about 1 °C, by 2050 in Kerman. The number of deaths attributed to heat were obviously higher than cold in all periods. Assuming no adaptation, over 3700 deaths attributed to temperature will happen in each decade (2020s, 2030s and 2040s) in the future, in which over 3000 deaths will be due to heat and over 450 due to cold. In the predictions, as Minimum Mortality Temperature (MMT) went up, the contribution of heat to mortality slightly decreased, and cold temperature played a more important role. By considering the risk reduction due to adaptation, the contribution of heat in mortality slightly and insignificantly decreased. ConclusionThe results showed that although low temperatures will contribute to temperature-related mortality in the future, but heat will be a stronger risk factor for mortality, especially if adaptation is low.